Sample records for plant process model
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Modeling of plant in vitro cultures: overview and estimation of biotechnological processes.
Maschke, Rüdiger W; Geipel, Katja; Bley, Thomas
2015-01-01
Plant cell and tissue cultivations are of growing interest for the production of structurally complex and expensive plant-derived products, especially in pharmaceutical production. Problems with up-scaling, low yields, and high-priced process conditions result in an increased demand for models to provide comprehension, simulation, and optimization of production processes. In the last 25 years, many models have evolved in plant biotechnology; the majority of them are specialized models for a few selected products or nutritional conditions. In this article we review, delineate, and discuss the concepts and characteristics of the most commonly used models. Therefore, the authors focus on models for plant suspension and submerged hairy root cultures. The article includes a short overview of modeling and mathematics and integrated parameters, as well as the application scope for each model. The review is meant to help researchers better understand and utilize the numerous models published for plant cultures, and to select the most suitable model for their purposes. © 2014 Wiley Periodicals, Inc.
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Single Plant Root System Modeling under Soil Moisture Variation
NASA Astrophysics Data System (ADS)
Yabusaki, S.; Fang, Y.; Chen, X.; Scheibe, T. D.
2016-12-01
A prognostic Virtual Plant-Atmosphere-Soil System (vPASS) model is being developed that integrates comprehensively detailed mechanistic single plant modeling with microbial, atmospheric, and soil system processes in its immediate environment. Three broad areas of process module development are targeted: Incorporating models for root growth and function, rhizosphere interactions with bacteria and other organisms, litter decomposition and soil respiration into established porous media flow and reactive transport models Incorporating root/shoot transport, growth, photosynthesis and carbon allocation process models into an integrated plant physiology model Incorporating transpiration, Volatile Organic Compounds (VOC) emission, particulate deposition and local atmospheric processes into a coupled plant/atmosphere model. The integrated plant ecosystem simulation capability is being developed as open source process modules and associated interfaces under a modeling framework. The initial focus addresses the coupling of root growth, vascular transport system, and soil under drought scenarios. Two types of root water uptake modeling approaches are tested: continuous root distribution and constitutive root system architecture. The continuous root distribution models are based on spatially averaged root development process parameters, which are relatively straightforward to accommodate in the continuum soil flow and reactive transport module. Conversely, the constitutive root system architecture models use root growth rates, root growth direction, and root branching to evolve explicit root geometries. The branching topologies require more complex data structures and additional input parameters. Preliminary results are presented for root model development and the vascular response to temporal and spatial variations in soil conditions.
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Fourcaud, Thierry; Zhang, Xiaopeng; Stokes, Alexia; Lambers, Hans; Körner, Christian
2008-05-01
Modelling plant growth allows us to test hypotheses and carry out virtual experiments concerning plant growth processes that could otherwise take years in field conditions. The visualization of growth simulations allows us to see directly and vividly the outcome of a given model and provides us with an instructive tool useful for agronomists and foresters, as well as for teaching. Functional-structural (FS) plant growth models are nowadays particularly important for integrating biological processes with environmental conditions in 3-D virtual plants, and provide the basis for more advanced research in plant sciences. In this viewpoint paper, we ask the following questions. Are we modelling the correct processes that drive plant growth, and is growth driven mostly by sink or source activity? In current models, is the importance of soil resources (nutrients, water, temperature and their interaction with meristematic activity) considered adequately? Do classic models account for architectural adjustment as well as integrating the fundamental principles of development? Whilst answering these questions with the available data in the literature, we put forward the opinion that plant architecture and sink activity must be pushed to the centre of plant growth models. In natural conditions, sinks will more often drive growth than source activity, because sink activity is often controlled by finite soil resources or developmental constraints. PMA06: This viewpoint paper also serves as an introduction to this Special Issue devoted to plant growth modelling, which includes new research covering areas stretching from cell growth to biomechanics. All papers were presented at the Second International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA06), held in Beijing, China, from 13-17 November, 2006. Although a large number of papers are devoted to FS models of agricultural and forest crop species, physiological and genetic processes have recently been included and point the way to a new direction in plant modelling research.
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NASA Astrophysics Data System (ADS)
Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.
2014-12-01
Topography plays a commanding role on the organization of ecohydrologic processes and resulting vegetation patterns. In southwestern United States, climate conditions lead to terrain aspect- and elevation-controlled ecosystems, with mesic north-facing and xeric south-facing vegetation types; and changes in biodiversity as a function of elevation from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations and ridge tops. These observed patterns have been attributed to differences in topography-mediated local soil moisture availability, micro-climatology, and life history processes of plants that control chances of plant establishment and survival. While ecohydrologic models represent local vegetation dynamics in sufficient detail up to sub-hourly time scales, plant life history and competition for space and resources has not been adequately represented in models. In this study we develop an ecohydrologic cellular automata model within the Landlab component-based modeling framework. This model couples local vegetation dynamics (biomass production, death) and plant establishment and competition processes for resources and space. This model is used to study the vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. Processes that lead to observed plant types across the landscape are examined by initializing the domain with randomly assigned plant types and systematically changing model parameters that couple plant response with soil moisture dynamics. Climate perturbation experiments are conducted to examine the plant response in space and time. Understanding the inherently transient ecohydrologic systems is critical to improve predictions of climate change impacts on ecosystems.
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Second Generation Crop Yield Models Review
NASA Technical Reports Server (NTRS)
Hodges, T. (Principal Investigator)
1982-01-01
Second generation yield models, including crop growth simulation models and plant process models, may be suitable for large area crop yield forecasting in the yield model development project. Subjective and objective criteria for model selection are defined and models which might be selected are reviewed. Models may be selected to provide submodels as input to other models; for further development and testing; or for immediate testing as forecasting tools. A plant process model may range in complexity from several dozen submodels simulating (1) energy, carbohydrates, and minerals; (2) change in biomass of various organs; and (3) initiation and development of plant organs, to a few submodels simulating key physiological processes. The most complex models cannot be used directly in large area forecasting but may provide submodels which can be simplified for inclusion into simpler plant process models. Both published and unpublished models which may be used for development or testing are reviewed. Several other models, currently under development, may become available at a later date.
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Working toward integrated models of alpine plant distribution.
Carlson, Bradley Z; Randin, Christophe F; Boulangeat, Isabelle; Lavergne, Sébastien; Thuiller, Wilfried; Choler, Philippe
2013-10-01
Species distribution models (SDMs) have been frequently employed to forecast the response of alpine plants to global changes. Efforts to model alpine plant distribution have thus far been primarily based on a correlative approach, in which ecological processes are implicitly addressed through a statistical relationship between observed species occurrences and environmental predictors. Recent evidence, however, highlights the shortcomings of correlative SDMs, especially in alpine landscapes where plant species tend to be decoupled from atmospheric conditions in micro-topographic habitats and are particularly exposed to geomorphic disturbances. While alpine plants respond to the same limiting factors as plants found at lower elevations, alpine environments impose a particular set of scale-dependent and hierarchical drivers that shape the realized niche of species and that require explicit consideration in a modelling context. Several recent studies in the European Alps have successfully integrated both correlative and process-based elements into distribution models of alpine plants, but for the time being a single integrative modelling framework that includes all key drivers remains elusive. As a first step in working toward a comprehensive integrated model applicable to alpine plant communities, we propose a conceptual framework that structures the primary mechanisms affecting alpine plant distributions. We group processes into four categories, including multi-scalar abiotic drivers, gradient dependent species interactions, dispersal and spatial-temporal plant responses to disturbance. Finally, we propose a methodological framework aimed at developing an integrated model to better predict alpine plant distribution.
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Dynamics of Postcombustion CO2 Capture Plants: Modeling, Validation, and Case Study
2017-01-01
The capture of CO2 from power plant flue gases provides an opportunity to mitigate emissions that are harmful to the global climate. While the process of CO2 capture using an aqueous amine solution is well-known from experience in other technical sectors (e.g., acid gas removal in the gas processing industry), its operation combined with a power plant still needs investigation because in this case, the interaction with power plants that are increasingly operated dynamically poses control challenges. This article presents the dynamic modeling of CO2 capture plants followed by a detailed validation using transient measurements recorded from the pilot plant operated at the Maasvlakte power station in the Netherlands. The model predictions are in good agreement with the experimental data related to the transient changes of the main process variables such as flow rate, CO2 concentrations, temperatures, and solvent loading. The validated model was used to study the effects of fast power plant transients on the capture plant operation. A relevant result of this work is that an integrated CO2 capture plant might enable more dynamic operation of retrofitted fossil fuel power plants because the large amount of steam needed by the capture process can be diverted rapidly to and from the power plant. PMID:28413256
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NASA Astrophysics Data System (ADS)
Vanderborght, J.; Javaux, M.; Couvreur, V.; Schröder, N.; Huber, K.; Abesha, B.; Schnepf, A.; Vereecken, H.
2013-12-01
Plant roots play a crucial role in several key processes in soils. Besides their impact on biogeochemical cycles and processes, they also have an important influence on physical processes such as water flow and transport of dissolved substances in soils. Interaction between plant roots and soil processes takes place at different scales and ranges from the scale of an individual root and its directly surrounding soil or rhizosphere over the scale of a root system of an individual plant in a soil profile to the scale of vegetation patterns in landscapes. Simulation models that are used to predict water flow and solute transport in soil-plant systems mainly focus on the individual plant root system scale, parameterize single-root scale phenomena, and aggregate the root system scale to the vegetation scale. In this presentation, we will focus on the transition from the single root to the root system scale. Using high resolution non-invasive imaging techniques and methods, gradients in soil properties and states around roots and their difference from the bulk soil properties could be demonstrated. Recent developments in plant sciences provide new insights in the mechanisms that control water fluxes in plants and in the adaptation of root properties or root plasticity to changing soil conditions. However, since currently used approaches to simulate root water uptake neither resolve these small scale processes nor represent processes and controls within the root system, transferring this information to the whole soil-plant system scale is a challenge. Using a simulation model that describes flow and transport processes in the soil, resolves flow and transport towards individual roots, and describes flow and transport within the root system, such a transfer could be achieved. We present a few examples that illustrate: (i) the impact of changed rhizosphere hydraulic properties, (ii) the effect of root hydraulic properties and root system architecture, (iii) the regulation of plant transpiration by root-zone produced plant hormones, and (iv) the impact of salt accumulation at the soil-root interface on root water uptake. We further propose a framework how this process knowledge could be implemented in root zone simulation models that do not resolve small scale processes.
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McCormack, M. Luke; Guo, Dali; Iversen, Colleen M.; ...
2017-03-13
Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual rootsmore » to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
McCormack, M. Luke; Guo, Dali; Iversen, Colleen M.
Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual rootsmore » to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.« less
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Cascade process modeling with mechanism-based hierarchical neural networks.
Cong, Qiumei; Yu, Wen; Chai, Tianyou
2010-02-01
Cascade process, such as wastewater treatment plant, includes many nonlinear sub-systems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. Firstly we propose a new neural model: hierarchical neural networks to identify the cascade process; then we use serial structural mechanism model based on the physical equations to connect with neural model. A stable learning algorithm and theoretical analysis are given. Finally, this method is used to model a wastewater treatment plant. Real operational data of wastewater treatment plant is applied to illustrate the modeling approach.
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Working toward integrated models of alpine plant distribution
Carlson, Bradley Z.; Randin, Christophe F.; Boulangeat, Isabelle; Lavergne, Sébastien; Thuiller, Wilfried; Choler, Philippe
2014-01-01
Species distribution models (SDMs) have been frequently employed to forecast the response of alpine plants to global changes. Efforts to model alpine plant distribution have thus far been primarily based on a correlative approach, in which ecological processes are implicitly addressed through a statistical relationship between observed species occurrences and environmental predictors. Recent evidence, however, highlights the shortcomings of correlative SDMs, especially in alpine landscapes where plant species tend to be decoupled from atmospheric conditions in micro-topographic habitats and are particularly exposed to geomorphic disturbances. While alpine plants respond to the same limiting factors as plants found at lower elevations, alpine environments impose a particular set of scale-dependent and hierarchical drivers that shape the realized niche of species and that require explicit consideration in a modelling context. Several recent studies in the European Alps have successfully integrated both correlative and process-based elements into distribution models of alpine plants, but for the time being a single integrative modelling framework that includes all key drivers remains elusive. As a first step in working toward a comprehensive integrated model applicable to alpine plant communities, we propose a conceptual framework that structures the primary mechanisms affecting alpine plant distributions. We group processes into four categories, including multi-scalar abiotic drivers, gradient dependent species interactions, dispersal and spatial–temporal plant responses to disturbance. Finally, we propose a methodological framework aimed at developing an integrated model to better predict alpine plant distribution. PMID:24790594
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Analysis of Cryogenic Cycle with Process Modeling Tool: Aspen HYSYS
NASA Astrophysics Data System (ADS)
Joshi, D. M.; Patel, H. K.
2015-10-01
Cryogenic engineering deals with the development and improvement of low temperature techniques, processes and equipment. A process simulator such as Aspen HYSYS, for the design, analysis, and optimization of process plants, has features that accommodate the special requirements and therefore can be used to simulate most cryogenic liquefaction and refrigeration processes. Liquefaction is the process of cooling or refrigerating a gas to a temperature below its critical temperature so that liquid can be formed at some suitable pressure which is below the critical pressure. Cryogenic processes require special attention in terms of the integration of various components like heat exchangers, Joule-Thompson Valve, Turbo expander and Compressor. Here, Aspen HYSYS, a process modeling tool, is used to understand the behavior of the complete plant. This paper presents the analysis of an air liquefaction plant based on the Linde cryogenic cycle, performed using the Aspen HYSYS process modeling tool. It covers the technique used to find the optimum values for getting the maximum liquefaction of the plant considering different constraints of other parameters. The analysis result so obtained gives clear idea in deciding various parameter values before implementation of the actual plant in the field. It also gives an idea about the productivity and profitability of the given configuration plant which leads to the design of an efficient productive plant.
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Simulation model for plant growth in controlled environment systems
NASA Technical Reports Server (NTRS)
Raper, C. D., Jr.; Wann, M.
1986-01-01
The role of the mathematical model is to relate the individual processes to environmental conditions and the behavior of the whole plant. Using the controlled-environment facilities of the phytotron at North Carolina State University for experimentation at the whole-plant level and methods for handling complex models, researchers developed a plant growth model to describe the relationships between hierarchial levels of the crop production system. The fundamental processes that are considered are: (1) interception of photosynthetically active radiation by leaves, (2) absorption of photosynthetically active radiation, (3) photosynthetic transformation of absorbed radiation into chemical energy of carbon bonding in solube carbohydrates in the leaves, (4) translocation between carbohydrate pools in leaves, stems, and roots, (5) flow of energy from carbohydrate pools for respiration, (6) flow from carbohydrate pools for growth, and (7) aging of tissues. These processes are described at the level of organ structure and of elementary function processes. The driving variables of incident photosynthetically active radiation and ambient temperature as inputs pertain to characterization at the whole-plant level. The output of the model is accumulated dry matter partitioned among leaves, stems, and roots; thus, the elementary processes clearly operate under the constraints of the plant structure which is itself the output of the model.
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MIMO model of an interacting series process for Robust MPC via System Identification.
Wibowo, Tri Chandra S; Saad, Nordin
2010-07-01
This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated. 2010 ISA. Published by Elsevier Ltd. All rights reserved.
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Evers, J B; Vos, J; Yin, X; Romero, P; van der Putten, P E L; Struik, P C
2010-05-01
Intimate relationships exist between form and function of plants, determining many processes governing their growth and development. However, in most crop simulation models that have been created to simulate plant growth and, for example, predict biomass production, plant structure has been neglected. In this study, a detailed simulation model of growth and development of spring wheat (Triticum aestivum) is presented, which integrates degree of tillering and canopy architecture with organ-level light interception, photosynthesis, and dry-matter partitioning. An existing spatially explicit 3D architectural model of wheat development was extended with routines for organ-level microclimate, photosynthesis, assimilate distribution within the plant structure according to organ demands, and organ growth and development. Outgrowth of tiller buds was made dependent on the ratio between assimilate supply and demand of the plants. Organ-level photosynthesis, biomass production, and bud outgrowth were simulated satisfactorily. However, to improve crop simulation results more efforts are needed mechanistically to model other major plant physiological processes such as nitrogen uptake and distribution, tiller death, and leaf senescence. Nevertheless, the work presented here is a significant step forwards towards a mechanistic functional-structural plant model, which integrates plant architecture with key plant processes.
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Integrated controls design optimization
Lou, Xinsheng; Neuschaefer, Carl H.
2015-09-01
A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.
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Jensen, M D; Ingildsen, P; Rasmussen, M R; Laursen, J
2006-01-01
Aeration tank settling is a control method allowing settling in the process tank during high hydraulic load. The control method is patented. Aeration tank settling has been applied in several waste water treatment plants using the present design of the process tanks. Some process tank designs have shown to be more effective than others. To improve the design of less effective plants, computational fluid dynamics (CFD) modelling of hydraulics and sedimentation has been applied. This paper discusses the results at one particular plant experiencing problems with partly short-circuiting of the inlet and outlet causing a disruption of the sludge blanket at the outlet and thereby reducing the retention of sludge in the process tank. The model has allowed us to establish a clear picture of the problems arising at the plant during aeration tank settling. Secondly, several process tank design changes have been suggested and tested by means of computational fluid dynamics modelling. The most promising design changes have been found and reported.
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Modeling of fugitive dust emission for construction sand and gravel processing plant.
Lee, C H; Tang, L W; Chang, C T
2001-05-15
Due to rapid economic development in Taiwan, a large quantity of construction sand and gravel is needed to support domestic civil construction projects. However, a construction sand and gravel processing plant is often a major source of air pollution, due to its associated fugitive dust emission. To predict the amount of fugitive dust emitted from this kind of processing plant, a semiempirical model was developed in this study. This model was developed on the basis of the actual dust emission data (i.e., total suspended particulate, TSP) and four on-site operating parameters (i.e., wind speed (u), soil moisture (M), soil silt content (s), and number (N) of trucks) measured at a construction sand and gravel processing plant. On the basis of the on-site measured data and an SAS nonlinear regression program, the expression of this model is E = 0.011.u2.653.M-1.875.s0.060.N0.896, where E is the amount (kg/ton) of dust emitted during the production of each ton of gravel and sand. This model can serve as a facile tool for predicting the fugitive dust emission from a construction sand and gravel processing plant.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Hagopian, C.R.; Lewis, P.J.; McDonald, J.J.
1983-02-01
Improvements and innovations in styrene production since 1966 are outlined. Rigorous process models are attributed to the changes. Such models are used to evaluate the effects of changing raw material costs, utility costs, and available catalyst choices. The process model can also evaluate the best operating configuration and catalyst choice for a plant. All specified innovations are incorporated in the Mobil/Badger ethylbenzene and the Cosden/Badger styrene processes (both of which are schematicized). Badger's training programs are reviewed. Badger's Styrenics Business Team converts information into plant design basis. A reaction model with input derived from isothermal and adiabatic pilot plant unitsmore » is at the heart of complete computer simulation of ethylbenzene and styrene processes.« less
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Barczi, Jean-François; Rey, Hervé; Caraglio, Yves; de Reffye, Philippe; Barthélémy, Daniel; Dong, Qiao Xue; Fourcaud, Thierry
2008-05-01
AmapSim is a tool that implements a structural plant growth model based on a botanical theory and simulates plant morphogenesis to produce accurate, complex and detailed plant architectures. This software is the result of more than a decade of research and development devoted to plant architecture. New advances in the software development have yielded plug-in external functions that open up the simulator to functional processes. The simulation of plant topology is based on the growth of a set of virtual buds whose activity is modelled using stochastic processes. The geometry of the resulting axes is modelled by simple descriptive functions. The potential growth of each bud is represented by means of a numerical value called physiological age, which controls the value for each parameter in the model. The set of possible values for physiological ages is called the reference axis. In order to mimic morphological and architectural metamorphosis, the value allocated for the physiological age of buds evolves along this reference axis according to an oriented finite state automaton whose occupation and transition law follows a semi-Markovian function. Simulations were performed on tomato plants to demonstrate how the AmapSim simulator can interface external modules, e.g. a GREENLAB growth model and a radiosity model. The algorithmic ability provided by AmapSim, e.g. the reference axis, enables unified control to be exercised over plant development parameter values, depending on the biological process target: how to affect the local pertinent process, i.e. the pertinent parameter(s), while keeping the rest unchanged. This opening up to external functions also offers a broadened field of applications and thus allows feedback between plant growth and the physical environment.
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Barczi, Jean-François; Rey, Hervé; Caraglio, Yves; de Reffye, Philippe; Barthélémy, Daniel; Dong, Qiao Xue; Fourcaud, Thierry
2008-01-01
Background and Aims AmapSim is a tool that implements a structural plant growth model based on a botanical theory and simulates plant morphogenesis to produce accurate, complex and detailed plant architectures. This software is the result of more than a decade of research and development devoted to plant architecture. New advances in the software development have yielded plug-in external functions that open up the simulator to functional processes. Methods The simulation of plant topology is based on the growth of a set of virtual buds whose activity is modelled using stochastic processes. The geometry of the resulting axes is modelled by simple descriptive functions. The potential growth of each bud is represented by means of a numerical value called physiological age, which controls the value for each parameter in the model. The set of possible values for physiological ages is called the reference axis. In order to mimic morphological and architectural metamorphosis, the value allocated for the physiological age of buds evolves along this reference axis according to an oriented finite state automaton whose occupation and transition law follows a semi-Markovian function. Key Results Simulations were performed on tomato plants to demostrate how the AmapSim simulator can interface external modules, e.g. a GREENLAB growth model and a radiosity model. Conclusions The algorithmic ability provided by AmapSim, e.g. the reference axis, enables unified control to be exercised over plant development parameter values, depending on the biological process target: how to affect the local pertinent process, i.e. the pertinent parameter(s), while keeping the rest unchanged. This opening up to external functions also offers a broadened field of applications and thus allows feedback between plant growth and the physical environment. PMID:17766310
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Liu, Jun-Jun; Xiang, Yu
2011-01-01
WRKY transcription factors are key regulators of numerous biological processes in plant growth and development, as well as plant responses to abiotic and biotic stresses. Research on biological functions of plant WRKY genes has focused in the past on model plant species or species with largely characterized transcriptomes. However, a variety of non-model plants, such as forest conifers, are essential as feed, biofuel, and wood or for sustainable ecosystems. Identification of WRKY genes in these non-model plants is equally important for understanding the evolutionary and function-adaptive processes of this transcription factor family. Because of limited genomic information, the rarity of regulatory gene mRNAs in transcriptomes, and the sequence divergence to model organism genes, identification of transcription factors in non-model plants using methods similar to those generally used for model plants is difficult. This chapter describes a gene family discovery strategy for identification of WRKY transcription factors in conifers by a combination of in silico-based prediction and PCR-based experimental approaches. Compared to traditional cDNA library screening or EST sequencing at transcriptome scales, this integrated gene discovery strategy provides fast, simple, reliable, and specific methods to unveil the WRKY gene family at both genome and transcriptome levels in non-model plants.
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Optimal allocation in annual plants and its implications for drought response
NASA Astrophysics Data System (ADS)
Caldararu, Silvia; Smith, Matthew; Purves, Drew
2015-04-01
The concept of plant optimality refers to the plastic behaviour of plants that results in lifetime and offspring fitness. Optimality concepts have been used in vegetation models for a variety of processes, including stomatal conductance, leaf phenology and biomass allocation. Including optimality in vegetation models has the advantages of creating process based models with a relatively low complexity in terms of parameter numbers but which are capable of reproducing complex plant behaviour. We present a general model of plant growth for annual plants based on the hypothesis that plants allocate biomass to aboveground and belowground vegetative organs in order to maintain an optimal C:N ratio. The model also represents reproductive growth through a second optimality criteria, which states that plants flower when they reach peak nitrogen uptake. We apply this model to wheat and maize crops at 15 locations corresponding to FLUXNET cropland sites. The model parameters are data constrained using a Bayesian fitting algorithm to eddy covariance data, satellite derived vegetation indices, specifically the MODIS fAPAR product and field level crop yield data. We use the model to simulate the plant drought response under the assumption of plant optimality and show that the plants maintain unstressed total biomass levels under drought for a reduction in precipitation of up to 40%. Beyond that level plant response stops being plastic and growth decreases sharply. This behaviour results simply from the optimal allocation criteria as the model includes no explicit drought sensitivity component. Models that use plant optimality concepts are a useful tool for simulation plant response to stress without the addition of artificial thresholds and parameters.
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Modeling plant growth and development.
Prusinkiewicz, Przemyslaw
2004-02-01
Computational plant models or 'virtual plants' are increasingly seen as a useful tool for comprehending complex relationships between gene function, plant physiology, plant development, and the resulting plant form. The theory of L-systems, which was introduced by Lindemayer in 1968, has led to a well-established methodology for simulating the branching architecture of plants. Many current architectural models provide insights into the mechanisms of plant development by incorporating physiological processes, such as the transport and allocation of carbon. Other models aim at elucidating the geometry of plant organs, including flower petals and apical meristems, and are beginning to address the relationship between patterns of gene expression and the resulting plant form.
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Application of Spatial Models in Making Location Decisions of Wind Power Plant in Poland
NASA Astrophysics Data System (ADS)
Płuciennik, Monika; Hełdak, Maria; Szczepański, Jakub; Patrzałek, Ciechosław
2017-10-01
In this paper,we explore the process of making decisions on the location of wind power plants in Poland in connection with a gradually increasing consumption of energy from renewable sources and the increase of impact problems of such facilities. The location of new wind power plants attracts much attention, and both positive and negative publicity. Visualisations can be of assistance when choosing the most advantageous location for a plant, as three-dimensional variants of the facility to be constructed can be prepared. This work involves terrestrial laser scanning of an existing wind power plant and 3D modelling followed by. The model could be subsequently used in visualisation of real terrain, with special purpose in local land development plan. This paper shows a spatial model of a wind power plant as a new element of a capital investment process in Poland. Next, we incorporate the model into an undeveloped site, intended for building a wind farm, subject to the requirements for location of power plants.
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Suchar, Vasile Alexandru; Robberecht, Ronald
2016-07-01
A process based model integrating the effects of UV-B radiation to molecular level processes and their consequences to whole plant growth and development was developed from key parameters in the published literature. Model simulations showed that UV-B radiation induced changes in plant metabolic and/or photosynthesis rates can result in plant growth inhibitions. The costs of effective epidermal UV-B radiation absorptive compounds did not result in any significant changes in plant growth, but any associated metabolic costs effectively reduced the potential plant biomass. The model showed significant interactions between UV-B radiation effects and temperature and any factor leading to inhibition of photosynthetic production or plant growth during the midday, but the effects were not cumulative for all factors. Vegetative growth were significantly delayed in species that do not exhibit reproductive cycles during a growing season, but vegetative growth and reproductive yield in species completing their life cycle in one growing season did not appear to be delayed more than 2-5 days, probably within the natural variability of the life cycles for many species. This is the first model to integrate the effects of increased UV-B radiation through molecular level processes and their consequences to whole plant growth and development.
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García-Diéguez, Carlos; Bernard, Olivier; Roca, Enrique
2013-03-01
The Anaerobic Digestion Model No. 1 (ADM1) is a complex model which is widely accepted as a common platform for anaerobic process modeling and simulation. However, it has a large number of parameters and states that hinder its calibration and use in control applications. A principal component analysis (PCA) technique was extended and applied to simplify the ADM1 using data of an industrial wastewater treatment plant processing winery effluent. The method shows that the main model features could be obtained with a minimum of two reactions. A reduced stoichiometric matrix was identified and the kinetic parameters were estimated on the basis of representative known biochemical kinetics (Monod and Haldane). The obtained reduced model takes into account the measured states in the anaerobic wastewater treatment (AWT) plant and reproduces the dynamics of the process fairly accurately. The reduced model can support on-line control, optimization and supervision strategies for AWT plants. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Simulation of Plant Physiological Process Using Fuzzy Variables
Daniel L. Schmoldt
1991-01-01
Qualitative modelling can help us understand and project effects of multiple stresses on trees. It is not practical to collect and correlate empirical data for all combinations of plant/environments and human/climate stresses, especially for mature trees in natural settings. Therefore, a mechanistic model was developed to describe ecophysiological processes. This model...
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NASA Astrophysics Data System (ADS)
Ding, Junyan; Johnson, Edward A.; Martin, Yvonne E.
2018-03-01
The diffusive and advective erosion-created landscapes have similar structure (hillslopes and channels) across different scales regardless of variations in drivers and controls. The relative magnitude of diffusive erosion to advective erosion (D/K ratio) in a landscape development model controls hillslope length, shape, and drainage density, which regulate soil moisture variation, one of the critical resources of plants, through the contributing area (A) and local slope (S) represented by a topographic index (TI). Here we explore the theoretical relation between geomorphic processes, TI, and the abundance and distribution of plants. We derived an analytical model that expresses the TI with D, K, and A. This gives us the relation between soil moisture variation and geomorphic processes. Plant tolerance curves are used to link plant performance to soil moisture. Using the hypothetical tolerance curves of three plants, we show that the abundance and distribution of xeric, mesic, and hydric plants on the landscape are regulated by the D/K ratio. Where diffusive erosion is the major erosion process (large D/K ratio), mesic plants have higher abundance relative to xeric and hydric plants and the landscape has longer and convex-upward hillslope and low channel density. Increasing the dominance of advective erosion increases relative abundance of xeric and hydric plants dominance, and the landscape has short and concave hillslope and high channel density.
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Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning
2018-03-05
This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.
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Simulating bimodal tall fescue growth with a degree-day-based process-oriented plant model
USDA-ARS?s Scientific Manuscript database
Plant growth simulation models have a temperature response function driving development, with a base temperature and an optimum temperature defined. Such growth simulation models often function well when plant development rate shows a continuous change throughout the growing season. This approach ...
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Meineke, Till; Manisseri, Chithra; Voigt, Christian A.
2014-01-01
The production of ethanol from pretreated plant biomass during fermentation is a strategy to mitigate climate change by substituting fossil fuels. However, biomass conversion is mainly limited by the recalcitrant nature of the plant cell wall. To overcome recalcitrance, the optimization of the plant cell wall for subsequent processing is a promising approach. Based on their phylogenetic proximity to existing and emerging energy crops, model plants have been proposed to study bioenergy-related cell wall biochemistry. One example is Brachypodium distachyon, which has been considered as a general model plant for cell wall analysis in grasses. To test whether relative phylogenetic proximity would be sufficient to qualify as a model plant not only for cell wall composition but also for the complete process leading to bioethanol production, we compared the processing of leaf and stem biomass from the C3 grasses B. distachyon and Triticum aestivum (wheat) with the C4 grasses Zea mays (maize) and Miscanthus x giganteus, a perennial energy crop. Lambda scanning with a confocal laser-scanning microscope allowed a rapid qualitative analysis of biomass saccharification. A maximum of 108–117 mg ethanol·g−1 dry biomass was yielded from thermo-chemically and enzymatically pretreated stem biomass of the tested plant species. Principal component analysis revealed that a relatively strong correlation between similarities in lignocellulosic ethanol production and phylogenetic relation was only given for stem and leaf biomass of the two tested C4 grasses. Our results suggest that suitability of B. distachyon as a model plant for biomass conversion of energy crops has to be specifically tested based on applied processing parameters and biomass tissue type. PMID:25133818
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COST ESTIMATION MODELS FOR DRINKING WATER TREATMENT UNIT PROCESSES
Cost models for unit processes typically utilized in a conventional water treatment plant and in package treatment plant technology are compiled in this paper. The cost curves are represented as a function of specified design parameters and are categorized into four major catego...
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NASA Astrophysics Data System (ADS)
Evtushenko, V. F.; Myshlyaev, L. P.; Makarov, G. V.; Ivushkin, K. A.; Burkova, E. V.
2016-10-01
The structure of multi-variant physical and mathematical models of control system is offered as well as its application for adjustment of automatic control system (ACS) of production facilities on the example of coal processing plant.
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DNA damage and repair in plants – from models to crops
Manova, Vasilissa; Gruszka, Damian
2015-01-01
The genomic integrity of every organism is constantly challenged by endogenous and exogenous DNA-damaging factors. Mutagenic agents cause reduced stability of plant genome and have a deleterious effect on development, and in the case of crop species lead to yield reduction. It is crucial for all organisms, including plants, to develop efficient mechanisms for maintenance of the genome integrity. DNA repair processes have been characterized in bacterial, fungal, and mammalian model systems. The description of these processes in plants, in contrast, was initiated relatively recently and has been focused largely on the model plant Arabidopsis thaliana. Consequently, our knowledge about DNA repair in plant genomes - particularly in the genomes of crop plants - is by far more limited. However, the relatively small size of the Arabidopsis genome, its rapid life cycle and availability of various transformation methods make this species an attractive model for the study of eukaryotic DNA repair mechanisms and mutagenesis. Moreover, abnormalities in DNA repair which proved to be lethal for animal models are tolerated in plant genomes, although sensitivity to DNA damaging agents is retained. Due to the high conservation of DNA repair processes and factors mediating them among eukaryotes, genes and proteins that have been identified in model species may serve to identify homologous sequences in other species, including crop plants, in which these mechanisms are poorly understood. Crop breeding programs have provided remarkable advances in food quality and yield over the last century. Although the human population is predicted to “peak” by 2050, further advances in yield will be required to feed this population. Breeding requires genetic diversity. The biological impact of any mutagenic agent used for the creation of genetic diversity depends on the chemical nature of the induced lesions and on the efficiency and accuracy of their repair. More recent targeted mutagenesis procedures also depend on host repair processes, with different pathways yielding different products. Enhanced understanding of DNA repair processes in plants will inform and accelerate the engineering of crop genomes via both traditional and targeted approaches. PMID:26557130
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Vreck, D; Gernaey, K V; Rosen, C; Jeppsson, U
2006-01-01
In this paper, implementation of the Benchmark Simulation Model No 2 (BSM2) within Matlab-Simulink is presented. The BSM2 is developed for plant-wide WWTP control strategy evaluation on a long-term basis. It consists of a pre-treatment process, an activated sludge process and sludge treatment processes. Extended evaluation criteria are proposed for plant-wide control strategy assessment. Default open-loop and closed-loop strategies are also proposed to be used as references with which to compare other control strategies. Simulations indicate that the BM2 is an appropriate tool for plant-wide control strategy evaluation.
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Visualized modeling platform for virtual plant growth and monitoring on the internet
NASA Astrophysics Data System (ADS)
Zhou, De-fu; Tian, Feng-qui; Ren, Ping
2009-07-01
Virtual plant growth is a key research topic in Agriculture Information Technique and Computer Graphics. It has been applied in botany, agronomy, environmental sciences, computre sciences and applied mathematics. Modeling leaf color dynamics in plant is of significant importance for realizing virtual plant growth. Using systematic analysis method and dynamic modeling technology, a SPAD-based leaf color dynamic model was developed to simulate time-course change characters of leaf SPAD on the plant. In addition, process of plant growth can be computer-stimulated using Virtual Reality Modeling Language (VRML) to establish a vivid and visible model, including shooting, rooting, blooming, as well as growth of the stems and leaves. In the resistance environment, e.g., lacking of water, air or nutrient substances, high salt or alkaline, freezing injury, high temperature, suffering from diseases and insect pests, the changes from the level of whole plant to organs, tissues and cells could be computer-stimulated. Changes from physiological and biochemistry could also be described. When a series of indexes were input by the costumers, direct view and microcosmic changes could be shown. Thus, the model has a good performance in predicting growth condition of the plant, laying a foundation for further constructing virtual plant growth system. The results revealed that realistic physiological and pathological processes of 3D virtual plants could be demonstrated by proper design and effectively realized in the internet.
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NASA Astrophysics Data System (ADS)
Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.
2014-04-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures - for example, by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow for a more detailed analysis of the dynamic behaviour of the soil-plant interface. We coupled two of such high-process-oriented independent models and calibrated both models simultaneously. The catchment modelling framework (CMF) simulated soil hydrology based on the Richards equation and the van Genuchten-Mualem model of the soil hydraulic properties. CMF was coupled with the plant growth modelling framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo-based generalized likelihood uncertainty estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from a uniform distribution. The model was applied to three sites with different management in Müncheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matter of roots, storages, stems and leaves. The shape parameter of the retention curve n was highly constrained, whereas other parameters of the retention curve showed a large equifinality. We attribute this slightly poorer model performance to missing leaf senescence, which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need for including agricultural management options in the coupled model.
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Use of Words and Visuals in Modelling Context of Annual Plant
ERIC Educational Resources Information Center
Park, Jungeun; DiNapoli, Joseph; Mixell, Robert A.; Flores, Alfinio
2017-01-01
This study looks at the various verbal and non-verbal representations used in a process of modelling the number of annual plants over time. Analysis focuses on how various representations such as words, diagrams, letters and mathematical equations evolve in the mathematization process of the modelling context. Our results show that (1) visual…
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Ludwig, T; Kern, P; Bongards, M; Wolf, C
2011-01-01
The optimization of relaxation and filtration times of submerged microfiltration flat modules in membrane bioreactors used for municipal wastewater treatment is essential for efficient plant operation. However, the optimization and control of such plants and their filtration processes is a challenging problem due to the underlying highly nonlinear and complex processes. This paper presents the use of genetic algorithms for this optimization problem in conjunction with a fully calibrated simulation model, as computational intelligence methods are perfectly suited to the nonconvex multi-objective nature of the optimization problems posed by these complex systems. The simulation model is developed and calibrated using membrane modules from the wastewater simulation software GPS-X based on the Activated Sludge Model No.1 (ASM1). Simulation results have been validated at a technical reference plant. They clearly show that filtration process costs for cleaning and energy can be reduced significantly by intelligent process optimization.
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Virtual Plant Tissue: Building Blocks for Next-Generation Plant Growth Simulation
De Vos, Dirk; Dzhurakhalov, Abdiravuf; Stijven, Sean; Klosiewicz, Przemyslaw; Beemster, Gerrit T. S.; Broeckhove, Jan
2017-01-01
Motivation: Computational modeling of plant developmental processes is becoming increasingly important. Cellular resolution plant tissue simulators have been developed, yet they are typically describing physiological processes in an isolated way, strongly delimited in space and time. Results: With plant systems biology moving toward an integrative perspective on development we have built the Virtual Plant Tissue (VPTissue) package to couple functional modules or models in the same framework and across different frameworks. Multiple levels of model integration and coordination enable combining existing and new models from different sources, with diverse options in terms of input/output. Besides the core simulator the toolset also comprises a tissue editor for manipulating tissue geometry and cell, wall, and node attributes in an interactive manner. A parameter exploration tool is available to study parameter dependence of simulation results by distributing calculations over multiple systems. Availability: Virtual Plant Tissue is available as open source (EUPL license) on Bitbucket (https://bitbucket.org/vptissue/vptissue). The project has a website https://vptissue.bitbucket.io. PMID:28523006
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Network news: prime time for systems biology of the plant circadian clock.
McClung, C Robertson; Gutiérrez, Rodrigo A
2010-12-01
Whole-transcriptome analyses have established that the plant circadian clock regulates virtually every plant biological process and most prominently hormonal and stress response pathways. Systems biology efforts have successfully modeled the plant central clock machinery and an iterative process of model refinement and experimental validation has contributed significantly to the current view of the central clock machinery. The challenge now is to connect this central clock to the output pathways for understanding how the plant circadian clock contributes to plant growth and fitness in a changing environment. Undoubtedly, systems approaches will be needed to integrate and model the vastly increased volume of experimental data in order to extract meaningful biological information. Thus, we have entered an era of systems modeling, experimental testing, and refinement. This approach, coupled with advances from the genetic and biochemical analyses of clock function, is accelerating our progress towards a comprehensive understanding of the plant circadian clock network. Copyright © 2010 Elsevier Ltd. All rights reserved.
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Isabelle, Boulangeat; Pauline, Philippe; Sylvain, Abdulhak; Roland, Douzet; Luc, Garraud; Sébastien, Lavergne; Sandra, Lavorel; Jérémie, Van Es; Pascal, Vittoz; Wilfried, Thuiller
2013-01-01
The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling. PMID:24403847
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NASA Astrophysics Data System (ADS)
Papastefanou, P.; Fleischer, K.; Hickler, T.; Grams, T.; Lapola, D.; Quesada, C. A.; Zang, C.; Rammig, A.
2017-12-01
The Amazon basin was recently hit by severe drought events that were unprecedented in their severity and spatial extent, e.g. during 2005, 2010 and 2015/2016. Significant amounts of biomass were lost, turning large parts of the rainforest from a carbon sink into a carbon source. It is assumed that drought-induced tree mortality from hydraulic failure played an important role during these events and may become more frequent in the Amazon region in the future. Many state-of-the-art dynamic vegetation models do not include plant hydraulic processes and fail to reproduce observed rainforest responses to drought events, such as e.g. increased tree mortality. We address this research gap by developing a simple plant-hydraulic module for the dynamic vegetation model LPJ-GUESS. This plant-hydraulic module uses leaf water potential and cavitation as baseline processes to simulate tree mortality under drought stress. Furthermore, we introduce different plant strategies in the model, which describe e.g. differences in the stomatal regulation under drought stress. To parameterize and evaluate our hydraulic module, we use a set of available observational data from the Amazon region. We apply our model to the Amazon Basin and highlight similarities and differences across other measured and predicted drought responses, e.g. extrapolated observations and data derived from satellite measurements. Our results highlight the importance of including plant hydraulic processes in dynamic vegetation models to correctly predict vegetation dynamics under drought stress and show major differences on the vegetation dynamics depending on the selected plant strategies. We also identify gaps in process understanding of the triggering factors, the extent and the consequences of drought responses that hampers our ability to predict potential impact of future drought events on the Amazon rainforest.
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NASA Astrophysics Data System (ADS)
Clavijo, H. W.
2016-12-01
Modeling the soil-plant-atmosphere continuum has been central part of understanding interrelationships among biogeochemical and hydrological processes. Theory behind of couplings Land Surface Models (LSM) and Dynamical Global Vegetation Models (DGVM) are based on physical and physiological processes connected by input-output interactions mainly. This modeling framework could be improved by the application of non-equilibrium thermodynamic basis that could encompass the majority of biophysical processes in a standard fashion. This study presents an alternative model for plant-water-atmosphere based on energy-mass thermodynamics. The system of dynamic equations derived is based on the total entropy, the total energy balance for the plant, the biomass dynamics at metabolic level and the water-carbon-nitrogen fluxes and balances. One advantage of this formulation is the capability to describe adaptation and evolution of dynamics of plant as a bio-system coupled to the environment. Second, it opens a window for applications on specific conditions from individual plant scale, to watershed scale, to global scale. Third, it enhances the possibility of analyzing anthropogenic impacts on the system, benefiting from the mathematical formulation and its non-linearity. This non-linear model formulation is analyzed under the concepts of qualitative system dynamics theory, for different state-space phase portraits. The attractors and sources are pointed out with its stability analysis. Possibility of bifurcations are explored and reported. Simulations for the system dynamics under different conditions are presented. These results show strong consistency and applicability that validates the use of the non-equilibrium thermodynamic theory.
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Plant Growth Models Using Artificial Neural Networks
NASA Technical Reports Server (NTRS)
Bubenheim, David
1997-01-01
In this paper, we descrive our motivation and approach to devloping models and the neural network architecture. Initial use of the artificial neural network for modeling the single plant process of transpiration is presented.
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Modelling the effect of environmental factors on resource allocation in mixed plants systems
NASA Astrophysics Data System (ADS)
Gayler, Sebastian; Priesack, Eckart
2010-05-01
In most cases, growth of plants is determined by competition against neighbours for the local resources light, water and nutrients and by defending against herbivores and pathogens. Consequently, it is important for a plant to grow fast without neglecting defence. However, plant internal substrates and energy required to support maintenance, growth and defence are limited and the total demand for these processes cannot be met in most cases. Therefore, allocation of carbohydrates to growth related primary metabolism or to defence related secondary metabolism can be seen as a trade-off between the demand of plants for being competitive against neighbours and for being more resistant against pathogens. A modelling approach is presented which can be used to simulate competition for light, water and nutrients between plant individuals in mixed canopies. The balance of resource allocation between growth processes and synthesis of secondary compounds is modelled by a concept originating from different plant defence hypothesis. The model is used to analyse the impact of environmental factors such as soil water and nitrogen availability, planting density and atmospheric concentration of CO2 on growth of plant individuals within mixed canopies and variations in concentration of carbon-based secondary metabolites in plant tissues.
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An approach to developing an integrated pyroprocessing simulator
NASA Astrophysics Data System (ADS)
Lee, Hyo Jik; Ko, Won Il; Choi, Sung Yeol; Kim, Sung Ki; Kim, In Tae; Lee, Han Soo
2014-02-01
Pyroprocessing has been studied for a decade as one of the promising fuel recycling options in Korea. We have built a pyroprocessing integrated inactive demonstration facility (PRIDE) to assess the feasibility of integrated pyroprocessing technology and scale-up issues of the processing equipment. Even though such facility cannot be replaced with a real integrated facility using spent nuclear fuel (SF), many insights can be obtained in terms of the world's largest integrated pyroprocessing operation. In order to complement or overcome such limited test-based research, a pyroprocessing Modelling and simulation study began in 2011. The Korea Atomic Energy Research Institute (KAERI) suggested a Modelling architecture for the development of a multi-purpose pyroprocessing simulator consisting of three-tiered models: unit process, operation, and plant-level-model. The unit process model can be addressed using governing equations or empirical equations as a continuous system (CS). In contrast, the operation model describes the operational behaviors as a discrete event system (DES). The plant-level model is an integrated model of the unit process and an operation model with various analysis modules. An interface with different systems, the incorporation of different codes, a process-centered database design, and a dynamic material flow are discussed as necessary components for building a framework of the plant-level model. As a sample model that contains methods decoding the above engineering issues was thoroughly reviewed, the architecture for building the plant-level-model was verified. By analyzing a process and operation-combined model, we showed that the suggested approach is effective for comprehensively understanding an integrated dynamic material flow. This paper addressed the current status of the pyroprocessing Modelling and simulation activity at KAERI, and also predicted its path forward.
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An approach to developing an integrated pyroprocessing simulator
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Hyo Jik; Ko, Won Il; Choi, Sung Yeol
Pyroprocessing has been studied for a decade as one of the promising fuel recycling options in Korea. We have built a pyroprocessing integrated inactive demonstration facility (PRIDE) to assess the feasibility of integrated pyroprocessing technology and scale-up issues of the processing equipment. Even though such facility cannot be replaced with a real integrated facility using spent nuclear fuel (SF), many insights can be obtained in terms of the world's largest integrated pyroprocessing operation. In order to complement or overcome such limited test-based research, a pyroprocessing Modelling and simulation study began in 2011. The Korea Atomic Energy Research Institute (KAERI) suggestedmore » a Modelling architecture for the development of a multi-purpose pyroprocessing simulator consisting of three-tiered models: unit process, operation, and plant-level-model. The unit process model can be addressed using governing equations or empirical equations as a continuous system (CS). In contrast, the operation model describes the operational behaviors as a discrete event system (DES). The plant-level model is an integrated model of the unit process and an operation model with various analysis modules. An interface with different systems, the incorporation of different codes, a process-centered database design, and a dynamic material flow are discussed as necessary components for building a framework of the plant-level model. As a sample model that contains methods decoding the above engineering issues was thoroughly reviewed, the architecture for building the plant-level-model was verified. By analyzing a process and operation-combined model, we showed that the suggested approach is effective for comprehensively understanding an integrated dynamic material flow. This paper addressed the current status of the pyroprocessing Modelling and simulation activity at KAERI, and also predicted its path forward.« less
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Emissions model of waste treatment operations at the Idaho Chemical Processing Plant
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schindler, R.E.
1995-03-01
An integrated model of the waste treatment systems at the Idaho Chemical Processing Plant (ICPP) was developed using a commercially-available process simulation software (ASPEN Plus) to calculate atmospheric emissions of hazardous chemicals for use in an application for an environmental permit to operate (PTO). The processes covered by the model are the Process Equipment Waste evaporator, High Level Liquid Waste evaporator, New Waste Calcining Facility and Liquid Effluent Treatment and Disposal facility. The processes are described along with the model and its assumptions. The model calculates emissions of NO{sub x}, CO, volatile acids, hazardous metals, and organic chemicals. Some calculatedmore » relative emissions are summarized and insights on building simulations are discussed.« less
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Using a 3D CAD plant model to simplify process hazard reviews
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tolpa, G.
A Hazard and Operability (HAZOP) review is a formal predictive procedure used to identify potential hazard and operability problems associated with certain processes and facilities. The HAZOP procedure takes place several times during the life cycle of the facility. Replacing plastic models, layout and detail drawings with a 3D CAD electronic model, provides access to process safety information and a detailed level of plant topology that approaches the visualization capability of the imagination. This paper describes the process that is used for adding the use of a 3D CAD model to flowsheets and proven computer programs for the conduct ofmore » hazard and operability reviews. Using flowsheets and study nodes as a road map for the review the need for layout and other detail drawings is all but eliminated. Using the 3D CAD model again for a post-P and ID HAZOP supports conformance to layout and safety requirements, provides superior visualization of the plant configuration and preserves the owners equity in the design. The response from the review teams are overwhelmingly in favor of this type of review over a review that uses only drawings. Over the long term the plant model serves more than just process hazards analysis. Ongoing use of the model can satisfy the required access to process safety information, OHSA documentation and other legal requirements. In this paper extensive instructions address the logic for the process hazards analysis and the preparation required to assist anyone who wishes to add the use of a 3D model to their review.« less
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Higher Plants in life support systems: design of a model and plant experimental compartment
NASA Astrophysics Data System (ADS)
Hezard, Pauline; Farges, Berangere; Sasidharan L, Swathy; Dussap, Claude-Gilles
The development of closed ecological life support systems (CELSS) requires full control and efficient engineering for fulfilling the common objectives of water and oxygen regeneration, CO2 elimination and food production. Most of the proposed CELSS contain higher plants, for which a growth chamber and a control system are needed. Inside the compartment the development of higher plants must be understood and modeled in order to be able to design and control the compartment as a function of operating variables. The plant behavior must be analyzed at different sub-process scales : (i) architecture and morphology describe the plant shape and lead to calculate the morphological parameters (leaf area, stem length, number of meristems. . . ) characteristic of life cycle stages; (ii) physiology and metabolism of the different organs permit to assess the plant composition depending on the plant input and output rates (oxygen, carbon dioxide, water and nutrients); (iii) finally, the physical processes are light interception, gas exchange, sap conduction and root uptake: they control the available energy from photosynthesis and the input and output rates. These three different sub-processes are modeled as a system of equations using environmental and plant parameters such as light intensity, temperature, pressure, humidity, CO2 and oxygen partial pressures, nutrient solution composition, total leaf surface and leaf area index, chlorophyll content, stomatal conductance, water potential, organ biomass distribution and composition, etc. The most challenging issue is to develop a comprehensive and operative mathematical model that assembles these different sub-processes in a unique framework. In order to assess the parameters for testing a model, a polyvalent growth chamber is necessary. It should permit a controlled environment in order to test and understand the physiological response and determine the control strategy. The final aim of this model is to have an envi-ronmental control of plant behavior: this requires an extended knowledge of plant response to environment variations. This needs a large number of experiments, which would be easier to perform in a high-throughput system.
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A neural network model to predict the wastewater inflow incorporating rainfall events.
El-Din, Ahmed Gamal; Smith, Daniel W
2002-03-01
Under steady-state conditions, a wastewater treatment plant usually has a satisfactory performance because these conditions are similar to design conditions. However, load variations constitute a large portion of the operating life of a treatment facility and most of the observed problems in complying with permit requirements occur during these load transients. During storm events upsets to the different physical and biological processes may take place in a wastewater treatment plant, and therefore, the ability to predict the hydraulic load to a treatment facility during such events is very beneficial for the optimization of the treatment process. Most of the hydrologic and hydraulic models describing sewage collection systems are deterministic. Such models require detailed knowledge of the system and usually rely on a large number of parameters, some of which are uncertain or difficult to determine. Presented in this paper, an artificial neural network (ANN) model that is used to make short-term predictions of wastewater inflow rate that enters the Gold Bar Wastewater Treatment Plant (GBWWTP), the largest plant in the Edmonton area (Alberta, Canada). The neural model uses rainfall data, observed in the collection system discharging to the plant, as inputs. The building process of the model was conducted in a systematic way that allowed the identification of a parsimonious model that is able to learn (and not memorize) from past data and generalize very well to unseen data that was used to validate the model. The neural network model gave excellent results. The potential of using the model as part of a real-time process control system is also discussed.
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NASA Astrophysics Data System (ADS)
Caldararu, S.; Kern, M.; Engel, J.; Zaehle, S.
2016-12-01
Despite recent advances in global vegetation models, we still lack the capacity to predict observed vegetation responses to experimental environmental changes such as elevated CO2, increased temperature or nutrient additions. In particular for elevated CO2 (FACE) experiments, studies have shown that this is related in part to the models' inability to represent plastic changes in nutrient use and biomass allocation. We present a newly developed vegetation model which aims to overcome these problems by including optimality processes to describe nitrogen (N) and carbon allocation within the plant. We represent nitrogen allocation to the canopy and within the canopy between photosynthetic components as an optimal processes which aims to maximize net primary production (NPP) of the plant. We also represent biomass investment into aboveground and belowground components (root nitrogen uptake , biological N fixation) as an optimal process that maximizes plant growth by considering plant carbon and nutrient demands as well as acquisition costs. The model can now represent plastic changes in canopy N content and chlorophyll and Rubisco concentrations as well as in belowground allocation both on seasonal and inter-annual time scales. Specifically, we show that under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry would predicts a quick onset of N limitation. In general, our model aims to include physiologically-based plant processes and avoid arbitrarily imposed parameters and thresholds in order to improve our predictive capability of vegetation responses under changing environmental conditions.
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Calibration and simulation of two large wastewater treatment plants operated for nutrient removal.
Ferrer, J; Morenilla, J J; Bouzas, A; García-Usach, F
2004-01-01
Control and optimisation of plant processes has become a priority for WWTP managers. The calibration and verification of a mathematical model provides an important tool for the investigation of advanced control strategies that may assist in the design or optimization of WWTPs. This paper describes the calibration of the ASM2d model for two full scale biological nitrogen and phosphorus removal plants in order to characterize the biological process and to upgrade the plants' performance. Results from simulation showed a good correspondence with experimental data demonstrating that the model and the calibrated parameters were able to predict the behaviour of both WWTPs. Once the calibration and simulation process was finished, a study for each WWTP was done with the aim of improving its performance. Modifications focused on reactor configuration and operation strategies were proposed.
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Metallurgical Plant Optimization Through the use of Flowsheet Simulation Modelling
NASA Astrophysics Data System (ADS)
Kennedy, Mark William
Modern metallurgical plants typically have complex flowsheets and operate on a continuous basis. Real time interactions within such processes can be complex and the impacts of streams such as recycles on process efficiency and stability can be highly unexpected prior to actual operation. Current desktop computing power, combined with state-of-the-art flowsheet simulation software like Metsim, allow for thorough analysis of designs to explore the interaction between operating rate, heat and mass balances and in particular the potential negative impact of recycles. Using plant information systems, it is possible to combine real plant data with simple steady state models, using dynamic data exchange links to allow for near real time de-bottlenecking of operations. Accurate analytical results can also be combined with detailed unit operations models to allow for feed-forward model-based-control. This paper will explore some examples of the application of Metsim to real world engineering and plant operational issues.
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A plant’s perspective of extremes: Terrestrial plant responses to changing climatic variability
Reyer, C.; Leuzinger, S.; Rammig, A.; Wolf, A.; Bartholomeus, R. P.; Bonfante, A.; de Lorenzi, F.; Dury, M.; Gloning, P.; Abou Jaoudé, R.; Klein, T.; Kuster, T. M.; Martins, M.; Niedrist, G.; Riccardi, M.; Wohlfahrt, G.; de Angelis, P.; de Dato, G.; François, L.; Menzel, A.; Pereira, M.
2013-01-01
We review observational, experimental and model results on how plants respond to extreme climatic conditions induced by changing climatic variability. Distinguishing between impacts of changing mean climatic conditions and changing climatic variability on terrestrial ecosystems is generally underrated in current studies. The goals of our review are thus (1) to identify plant processes that are vulnerable to changes in the variability of climatic variables rather than to changes in their mean, and (2) to depict/evaluate available study designs to quantify responses of plants to changing climatic variability. We find that phenology is largely affected by changing mean climate but also that impacts of climatic variability are much less studied but potentially damaging. We note that plant water relations seem to be very vulnerable to extremes driven by changes in temperature and precipitation and that heatwaves and flooding have stronger impacts on physiological processes than changing mean climate. Moreover, interacting phenological and physiological processes are likely to further complicate plant responses to changing climatic variability. Phenological and physiological processes and their interactions culminate in even more sophisticated responses to changing mean climate and climatic variability at the species and community level. Generally, observational studies are well suited to study plant responses to changing mean climate, but less suitable to gain a mechanistic understanding of plant responses to climatic variability. Experiments seem best suited to simulate extreme events. In models, temporal resolution and model structure are crucial to capture plant responses to changing climatic variability. We highlight that a combination of experimental, observational and /or modeling studies have the potential to overcome important caveats of the respective individual approaches. PMID:23504722
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Editorial: Plant organ abscission: from models to crops
USDA-ARS?s Scientific Manuscript database
The shedding of plant organs is a highly coordinated process essential for both vegetative and reproductive development (Addicott, 1982; Sexton and Roberts, 1982; Roberts et al., 2002; Leslie et al., 2007; Roberts and Gonzalez-Carranza, 2007; Estornell et al., 2013). Research with model plants, name...
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Seo, Eunyoung; Woo, Jongchan; Park, Eunsook; Bertolani, Steven J; Siegel, Justin B; Choi, Doil; Dinesh-Kumar, Savithramma P
2016-11-01
Autophagy is important for degradation and recycling of intracellular components. In a diversity of genera and species, orthologs and paralogs of the yeast Atg4 and Atg8 proteins are crucial in the biogenesis of double-membrane autophagosomes that carry the cellular cargoes to vacuoles and lysosomes. Although many plant genome sequences are available, the ATG4 and ATG8 sequence analysis is limited to some model plants. We identified 28 ATG4 and 116 ATG8 genes from the available 18 different plant genome sequences. Gene structures and protein domain sequences of ATG4 and ATG8 are conserved in plant lineages. Phylogenetic analyses classified ATG8s into 3 subgroups suggesting divergence from the common ancestor. The ATG8 expansion in plants might be attributed to whole genome duplication, segmental and dispersed duplication, and purifying selection. Our results revealed that the yeast Atg4 processes Arabidopsis ATG8 but not human LC3A (HsLC3A). In contrast, HsATG4B can process yeast and plant ATG8s in vitro but yeast and plant ATG4s cannot process HsLC3A. Interestingly, in Nicotiana benthamiana plants the yeast Atg8 is processed compared to HsLC3A. However, HsLC3A is processed when coexpressed with HsATG4B in plants. Molecular modeling indicates that lack of processing of HsLC3A by plant and yeast ATG4 is not due to lack of interaction with HsLC3A. Our in-depth analyses of ATG4 and ATG8 in the plant lineage combined with results of cross-kingdom ATG8 processing by ATG4 further support the evolutionarily conserved maturation of ATG8. Broad ATG8 processing by HsATG4B and lack of processing of HsLC3A by yeast and plant ATG4s suggest that the cross-kingdom ATG8 processing is determined by ATG8 sequence rather than ATG4.
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Plant growth and architectural modelling and its applications
Guo, Yan; Fourcaud, Thierry; Jaeger, Marc; Zhang, Xiaopeng; Li, Baoguo
2011-01-01
Over the last decade, a growing number of scientists around the world have invested in research on plant growth and architectural modelling and applications (often abbreviated to plant modelling and applications, PMA). By combining physical and biological processes, spatially explicit models have shown their ability to help in understanding plant–environment interactions. This Special Issue on plant growth modelling presents new information within this topic, which are summarized in this preface. Research results for a variety of plant species growing in the field, in greenhouses and in natural environments are presented. Various models and simulation platforms are developed in this field of research, opening new features to a wider community of researchers and end users. New modelling technologies relating to the structure and function of plant shoots and root systems are explored from the cellular to the whole-plant and plant-community levels. PMID:21638797
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PID feedback controller used as a tactical asset allocation technique: The G.A.M. model
NASA Astrophysics Data System (ADS)
Gandolfi, G.; Sabatini, A.; Rossolini, M.
2007-09-01
The objective of this paper is to illustrate a tactical asset allocation technique utilizing the PID controller. The proportional-integral-derivative (PID) controller is widely applied in most industrial processes; it has been successfully used for over 50 years and it is used by more than 95% of the plants processes. It is a robust and easily understood algorithm that can provide excellent control performance in spite of the diverse dynamic characteristics of the process plant. In finance, the process plant, controlled by the PID controller, can be represented by financial market assets forming a portfolio. More specifically, in the present work, the plant is represented by a risk-adjusted return variable. Money and portfolio managers’ main target is to achieve a relevant risk-adjusted return in their managing activities. In literature and in the financial industry business, numerous kinds of return/risk ratios are commonly studied and used. The aim of this work is to perform a tactical asset allocation technique consisting in the optimization of risk adjusted return by means of asset allocation methodologies based on the PID model-free feedback control modeling procedure. The process plant does not need to be mathematically modeled: the PID control action lies in altering the portfolio asset weights, according to the PID algorithm and its parameters, Ziegler-and-Nichols-tuned, in order to approach the desired portfolio risk-adjusted return efficiently.
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Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R
2017-01-01
Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.
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Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard
2011-04-01
Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype-phenotype model, we present here a three-dimensional functional-structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed.
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Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard
2011-01-01
Background and Aims Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype–phenotype model, we present here a three-dimensional functional–structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. Methods The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Key Results Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. Conclusions We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed. PMID:21247905
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Continuity-based model interfacing for plant-wide simulation: a general approach.
Volcke, Eveline I P; van Loosdrecht, Mark C M; Vanrolleghem, Peter A
2006-08-01
In plant-wide simulation studies of wastewater treatment facilities, often existing models from different origin need to be coupled. However, as these submodels are likely to contain different state variables, their coupling is not straightforward. The continuity-based interfacing method (CBIM) provides a general framework to construct model interfaces for models of wastewater systems, taking into account conservation principles. In this contribution, the CBIM approach is applied to study the effect of sludge digestion reject water treatment with a SHARON-Anammox process on a plant-wide scale. Separate models were available for the SHARON process and for the Anammox process. The Benchmark simulation model no. 2 (BSM2) is used to simulate the behaviour of the complete WWTP including sludge digestion. The CBIM approach is followed to develop three different model interfaces. At the same time, the generally applicable CBIM approach was further refined and particular issues when coupling models in which pH is considered as a state variable, are pointed out.
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Regenerative life support system research
NASA Technical Reports Server (NTRS)
1988-01-01
Sections on modeling, experimental activities during the grant period, and topics under consideration for the future are contained. The sessions contain discussions of: four concurrent modeling approaches that were being integrated near the end of the period (knowledge-based modeling support infrastructure and data base management, object-oriented steady state simulations for three concepts, steady state mass-balance engineering tradeoff studies, and object-oriented time-step, quasidynamic simulations of generic concepts); interdisciplinary research activities, beginning with a discussion of RECON lab development and use, and followed with discussions of waste processing research, algae studies and subsystem modeling, low pressure growth testing of plants, subsystem modeling of plants, control of plant growth using lighting and CO2 supply as variables, search for and development of lunar soil simulants, preliminary design parameters for a lunar base life support system, and research considerations for food processing in space; and appendix materials, including a discussion of the CELSS Conference, detailed analytical equations for mass-balance modeling, plant modeling equations, and parametric data on existing life support systems for use in modeling.
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Development of a Scale-up Tool for Pervaporation Processes
Thiess, Holger; Strube, Jochen
2018-01-01
In this study, an engineering tool for the design and optimization of pervaporation processes is developed based on physico-chemical modelling coupled with laboratory/mini-plant experiments. The model incorporates the solution-diffusion-mechanism, polarization effects (concentration and temperature), axial dispersion, pressure drop and the temperature drop in the feed channel due to vaporization of the permeating components. The permeance, being the key model parameter, was determined via dehydration experiments on a mini-plant scale for the binary mixtures ethanol/water and ethyl acetate/water. A second set of experimental data was utilized for the validation of the model for two chemical systems. The industrially relevant ternary mixture, ethanol/ethyl acetate/water, was investigated close to its azeotropic point and compared to a simulation conducted with the determined binary permeance data. Experimental and simulation data proved to agree very well for the investigated process conditions. In order to test the scalability of the developed engineering tool, large-scale data from an industrial pervaporation plant used for the dehydration of ethanol was compared to a process simulation conducted with the validated physico-chemical model. Since the membranes employed in both mini-plant and industrial scale were of the same type, the permeance data could be transferred. The comparison of the measured and simulated data proved the scalability of the derived model. PMID:29342956
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A dynamical systems model for nuclear power plant risk
NASA Astrophysics Data System (ADS)
Hess, Stephen Michael
The recent transition to an open access generation marketplace has forced nuclear plant operators to become much more cost conscious and focused on plant performance. Coincidentally, the regulatory perspective also is in a state of transition from a command and control framework to one that is risk-informed and performance-based. Due to these structural changes in the economics and regulatory system associated with commercial nuclear power plant operation, there is an increased need for plant management to explicitly manage nuclear safety risk. Application of probabilistic risk assessment techniques to model plant hardware has provided a significant contribution to understanding the potential initiating events and equipment failures that can lead to core damage accidents. Application of the lessons learned from these analyses has supported improved plant operation and safety over the previous decade. However, this analytical approach has not been nearly as successful in addressing the impact of plant processes and management effectiveness on the risks of plant operation. Thus, the research described in this dissertation presents a different approach to address this issue. Here we propose a dynamical model that describes the interaction of important plant processes among themselves and their overall impact on nuclear safety risk. We first provide a review of the techniques that are applied in a conventional probabilistic risk assessment of commercially operating nuclear power plants and summarize the typical results obtained. The limitations of the conventional approach and the status of research previously performed to address these limitations also are presented. Next, we present the case for the application of an alternative approach using dynamical systems theory. This includes a discussion of previous applications of dynamical models to study other important socio-economic issues. Next, we review the analytical techniques that are applicable to analysis of these models. Details of the development of the mathematical risk model are presented. This includes discussion of the processes included in the model and the identification of significant interprocess interactions. This is followed by analysis of the model that demonstrates that its dynamical evolution displays characteristics that have been observed at commercially operating plants. The model is analyzed using the previously described techniques from dynamical systems theory. From this analysis, several significant insights are obtained with respect to the effective control of nuclear safety risk. Finally, we present conclusions and recommendations for further research.
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Kazadi Mbamba, Christian; Flores-Alsina, Xavier; John Batstone, Damien; Tait, Stephan
2016-09-01
The focus of modelling in wastewater treatment is shifting from single unit to plant-wide scale. Plant-wide modelling approaches provide opportunities to study the dynamics and interactions of different transformations in water and sludge streams. Towards developing more general and robust simulation tools applicable to a broad range of wastewater engineering problems, this paper evaluates a plant-wide model built with sub-models from the Benchmark Simulation Model No. 2-P (BSM2-P) with an improved/expanded physico-chemical framework (PCF). The PCF includes a simple and validated equilibrium approach describing ion speciation and ion pairing with kinetic multiple minerals precipitation. Model performance is evaluated against data sets from a full-scale wastewater treatment plant, assessing capability to describe water and sludge lines across the treatment process under steady-state operation. With default rate kinetic and stoichiometric parameters, a good general agreement is observed between the full-scale datasets and the simulated results under steady-state conditions. Simulation results show differences between measured and modelled phosphorus as little as 4-15% (relative) throughout the entire plant. Dynamic influent profiles were generated using a calibrated influent generator and were used to study the effect of long-term influent dynamics on plant performance. Model-based analysis shows that minerals precipitation strongly influences composition in the anaerobic digesters, but also impacts on nutrient loading across the entire plant. A forecasted implementation of nutrient recovery by struvite crystallization (model scenario only), reduced the phosphorus content in the treatment plant influent (via centrate recycling) considerably and thus decreased phosphorus in the treated outflow by up to 43%. Overall, the evaluated plant-wide model is able to jointly describe the physico-chemical and biological processes, and is advocated for future use as a tool for design, performance evaluation and optimization of whole wastewater treatment plants. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Resilience of riverbed vegetation to uprooting by flow
NASA Astrophysics Data System (ADS)
Perona, P.; Crouzy, B.
2018-03-01
Riverine ecosystem biodiversity is largely maintained by ecogeomorphic processes including vegetation renewal via uprooting and recovery times to flow disturbances. Plant roots thus heavily contribute to engineering resilience to perturbation of such ecosystems. We show that vegetation uprooting by flow occurs as a fatigue-like mechanism, which statistically requires a given exposure time to imposed riverbed flow erosion rates before the plant collapses. We formulate a physically based stochastic model for the actual plant rooting depth and the time-to-uprooting, which allows us to define plant resilience to uprooting for generic time-dependent flow erosion dynamics. This theory shows that plant resilience to uprooting depends on the time-to-uprooting and that root mechanical anchoring acts as a process memory stored within the plant-soil system. The model is validated against measured data of time-to-uprooting of Avena sativa seedlings with various root lengths under different flow conditions. This allows for assessing the natural variance of the uprooting-by-flow process and to compute the prediction entropy, which quantifies the relative importance of the deterministic and the random components affecting the process.
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Leistra, Minze; Wolters, André; van den Berg, Frederik
2008-06-01
Volatilisation of pesticides from crop canopies can be an important emission pathway. In addition to pesticide properties, competing processes in the canopy and environmental conditions play a part. A computation model is being developed to simulate the processes, but only some of the input data can be obtained directly from the literature. Three well-defined experiments on the volatilisation of radiolabelled parathion-methyl (as example compound) from plants in a wind tunnel system were simulated with the computation model. Missing parameter values were estimated by calibration against the experimental results. The resulting thickness of the air boundary layer, rate of plant penetation and rate of phototransformation were compared with a diversity of literature data. The sequence of importance of the canopy processes was: volatilisation > plant penetration > phototransformation. Computer simulation of wind tunnel experiments, with radiolabelled pesticide sprayed on plants, yields values for the rate coefficients of processes at the plant surface. As some input data for simulations are not required in the framework of registration procedures, attempts to estimate missing parameter values on the basis of divergent experimental results have to be continued. Copyright (c) 2008 Society of Chemical Industry.
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Rodríguez, Luis F; Li, Changying; Khanna, Madhu; Spaulding, Aslihan D; Lin, Tao; Eckhoff, Steven R
2010-07-01
An engineering economic model, which is mass balanced and compositionally driven, was developed to compare the conventional corn dry-grind process and the pre-fractionation process called quick germ-quick fiber (QQ). In this model, documented in a companion article, the distillers dried grains with solubles (DDGS) price was linked with its protein and fiber content as well as with the long-term average relationship with the corn price. The detailed economic analysis showed that the QQ plant retrofitted from conventional dry-grind ethanol plant reduces the manufacturing cost of ethanol by 13.5 cent/gallon and has net present value of nearly $4 million greater than the conventional dry-grind plant at an interest rate of 4% in 15years. Ethanol and feedstock price sensitivity analysis showed that the QQ plant gains more profits when ethanol price increases than conventional dry-grind ethanol plant. An optimistic analysis of the QQ process suggests that the greater value of the modified DDGS would provide greater resistance to fluctuations in corn price for QQ facilities. This model can be used to provide decision support for ethanol producers. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
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Warren, Jeffrey M; Hanson, Paul J; Iversen, Colleen M; Kumar, Jitendra; Walker, Anthony P; Wullschleger, Stan D
2015-01-01
There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction. No claim to original US Government works. New Phytologist © 2014 New Phytologist Trust.
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Enhancing Elementary Pre-service Teachers' Plant Processes Conceptions
NASA Astrophysics Data System (ADS)
Thompson, Stephen L.; Lotter, Christine; Fann, Xumei; Taylor, Laurie
2016-06-01
Researchers examined how an inquiry-based instructional treatment emphasizing interrelated plant processes influenced 210 elementary pre-service teachers' (PTs) conceptions of three plant processes, photosynthesis, cellular respiration, and transpiration, and the interrelated nature of these processes. The instructional treatment required PTs to predict the fate of a healthy plant in a sealed terrarium (Plant-in-a-Jar), justify their predictions, observe the plant over a 5-week period, and complete guided inquiry activities centered on one of the targeted plant processes each week. Data sources included PTs' pre- and post-predictions with accompanying justifications, course artifacts such as weekly terrarium observations and science journal entries, and group models of the interrelated plant processes occurring within the sealed terraria. A subset of 33 volunteer PTs also completed interviews the week the Plant-in-a-Jar scenario was introduced and approximately 4 months after the instructional intervention ended. Pre- and post-predictions from all PTs as well as interview responses from the subgroup of PTs, were coded into categories based on key plant processes emphasized in the Next Generation Science Standards. Study findings revealed that PTs developed more accurate conceptions of plant processes and their interrelated nature as a result of the instructional intervention. Primary patterns of change in PTs' plant process conceptions included development of more accurate conceptions of how water is used by plants, more accurate conceptions of photosynthesis features, and more accurate conceptions of photosynthesis and cellular respiration as transformative processes.
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Modelling of sedimentation and remobilization in in-line storage sewers for stormwater treatment.
Frehmann, T; Flores, C; Luekewille, F; Mietzel, T; Spengler, B; Geiger, W F
2005-01-01
A special arrangement of combined sewer overflow tanks is the in-line storage sewer with downstream discharge (ISS-down). This layout has the advantage that, besides the sewer system, no other structures are required for stormwater treatment. The verification of the efficiency with respect to the processes of sedimentation and remobilization of sediment within the in-line storage sewer with downstream discharge is carried out in a combination of a field and a pilot plant study. The model study was carried out using a pilot plant model scaled 1:13. The following is intended to present some results of the pilot plant study and the mathematical empirical modelling of the sedimentation and remobilization process.
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Modeling of solar polygeneration plant
NASA Astrophysics Data System (ADS)
Leiva, Roberto; Escobar, Rodrigo; Cardemil, José
2017-06-01
In this work, a exergoeconomic analysis of the joint production of electricity, fresh water, cooling and process heat for a simulated concentrated solar power (CSP) based on parabolic trough collector (PTC) with thermal energy storage (TES) and backup energy system (BS), a multi-effect distillation (MED) module, a refrigeration absorption module, and process heat module is carried out. Polygeneration plant is simulated in northern Chile in Crucero with a yearly total DNI of 3,389 kWh/m2/year. The methodology includes designing and modeling a polygeneration plant and applying exergoeconomic evaluations and calculating levelized cost. Solar polygeneration plant is simulated hourly, in a typical meteorological year, for different solar multiple and hour of storage. This study reveals that the total exergy cost rate of products (sum of exergy cost rate of electricity, water, cooling and heat process) is an alternative method to optimize a solar polygeneration plant.
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Unraveling the Plant-Soil Interactome
NASA Astrophysics Data System (ADS)
Lipton, M. S.; Hixson, K.; Ahkami, A. H.; HaHandkumbura, P. P.; Hess, N. J.; Fang, Y.; Fortin, D.; Stanfill, B.; Yabusaki, S.; Engbrecht, K. M.; Baker, E.; Renslow, R.; Jansson, C.
2017-12-01
Plant photosynthesis is the primary conduit of carbon fixation from the atmosphere to the terrestrial ecosystem. While more is known about plant physiology and biochemistry, the interplay between genetic and environmental factors that govern partitioning of carbon to above- and below ground plant biomass, to microbes, to the soil, and respired to the atmosphere is not well understood holistically. To address this knowledge gap there is a need to define, study, comprehend, and model the plant ecosystem as an integrated system of integrated biotic and abiotic processes and feedbacks. Local rhizosphere conditions are an important control on plant performance but are in turn affected by plant uptake and rhizodeposition processes. C3 and C4 plants have different CO2 fixation strategies and likely have differential metabolic profiles resulting in different carbon sources exuding to the rhizosphere. In this presentation, we report on an integrated capability to better understand plant-soil interactions, including modeling tools that address the spatiotemporal hydrobiogeochemistry in the rhizosphere. Comparing Brachypodium distachyon, (Brachypodium) as our C3 representative and Setaria viridis (Setaria) as our C4 representative, we designed, highly controlled single-plant experimental ecosystems based these model grasses to enable quantitative prediction of ecosystem traits and responses as a function of plant genotype and environmental variables. A metabolomics survey of 30 Brachypodium genotypes grown under control and drought conditions revealed specific metabolites that correlated with biomass production and drought tolerance. A comparison of Brachypodium and Setaria grown with control and a future predicted elevated CO2 level revealed changes in biomass accumulation and metabolite profiles between the C3 and C4 species in both leaves and roots. Finally, we are building an mechanistic modeling capability that will contribute to a better basis for modeling plant water and nutrient cycling in larger scale models.
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Vincenot, Christian E; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco
2016-01-01
In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)-Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed.
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Vincenot, Christian E.; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco
2016-01-01
In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)—Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed. PMID:27252707
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Multiscale Models in the Biomechanics of Plant Growth
Fozard, John A.
2015-01-01
Plant growth occurs through the coordinated expansion of tightly adherent cells, driven by regulated softening of cell walls. It is an intrinsically multiscale process, with the integrated properties of multiple cell walls shaping the whole tissue. Multiscale models encode physical relationships to bring new understanding to plant physiology and development. PMID:25729061
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Kitchen, James L.; Allaby, Robin G.
2013-01-01
Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. PMID:27137364
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Numerical model for the uptake of groundwater contaminants by phreatophytes
Widdowson, M.A.; El-Sayed, A.; Landmeyer, J.E.
2008-01-01
Conventional solute transport models do not adequately account for the effects of phreatophytic plant systems on contaminant concentrations in shallow groundwater systems. A numerical model was developed and tested to simulate threedimensional reactive solute transport in a heterogeneous porous medium. Advective-dispersive transport is coupled to biodegradation, sorption, and plantbased attenuation processes including plant uptake and sorption by plant roots. The latter effects are a function of the physical-chemical properties of the individual solutes and plant species. Models for plant uptake were tested and evaluated using the experimental data collected at a field site comprised of hybrid poplar trees. A non-linear equilibrium isotherm model best represented site conditions.
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A Seed-Based Plant Propagation Algorithm: The Feeding Station Model
Salhi, Abdellah
2015-01-01
The seasonal production of fruit and seeds is akin to opening a feeding station, such as a restaurant. Agents coming to feed on the fruit are like customers attending the restaurant; they arrive at a certain rate and get served at a certain rate following some appropriate processes. The same applies to birds and animals visiting and feeding on ripe fruit produced by plants such as the strawberry plant. This phenomenon underpins the seed dispersion of the plants. Modelling it as a queuing process results in a seed-based search/optimisation algorithm. This variant of the Plant Propagation Algorithm is described, analysed, tested on nontrivial problems, and compared with well established algorithms. The results are included. PMID:25821858
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The Evolution of Land Plants and the Silicate Weathering Feedback
NASA Astrophysics Data System (ADS)
Ibarra, D. E.; Caves Rugenstein, J. K.; Bachan, A.; Baresch, A.; Lau, K. V.; Thomas, D.; Lee, J. E.; Boyce, C. K.; Chamberlain, C. P.
2017-12-01
It has long been recognized that the advent of vascular plants in the Paleozoic must have changed silicate weathering and fundamentally altered the long-term carbon cycle. Efforts to quantify these effects have been formulated in carbon cycle models that are, in part, calibrated by weathering studies of modern plant communities. In models of the long-term carbon cycle, plants play a key role in controlling atmospheric CO2, particularly in the late Paleozoic. We test the impact of some established and recent theories regarding plant-enhanced weathering by coupling a one-dimensional vapor transport model to a reactive transport model of silicate weathering. In this coupled model, we evaluate consequences of plant evolutionary innovation that have not been mechanistically incorporated into most existing models: 1) the role of evolutionary shifts in plant transpiration in enhancing silicate weathering by increasing downwind transport and recycling of water vapor to continental interiors; 2) the importance of deeply-rooted plants and their associated microbial communities in increasing soil CO2 and weathering zone length scales; and, 3) the cumulative effect of these processes. Our modeling approach is framed by energy/supply constraints calibrated for minimally vegetated-, vascular plant forested-, and angiosperm-worlds. We find that the emergence of widespread transpiration and associated inland vapor recycling approximately doubles weathering solute concentrations when deep-rooted vascular plants (Devonian-Carboniferous) fully replace a minimally vegetated (pre-Devonian) world. The later evolution of angiosperms (Cretaceous and Cenozoic) and subsequent increase in transpiration fluxes increase weathering solute concentrations by approximately an additional 20%. Our estimates of the changes in weatherability caused by land plant evolution are of a similar magnitude, but explained with new process-based mechanisms, than those used in existing carbon cycle models. We suggest a feedback where the increase in solute concentrations is compensated by a decrease in runoff and temperature, permitting lower steady-state atmospheric pCO2. Consequently, plants have increased the strength of the climatic feedback on silicate weathering since the late Paleozoic.
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NASA Astrophysics Data System (ADS)
Ghimire, B.; Riley, W. J.; Koven, C. D.; Randerson, J. T.; Mu, M.; Kattge, J.; Rogers, A.; Reich, P. B.
2014-12-01
In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However mechanistic representation of nitrogen uptake linked to root traits, and functional nitrogen allocation among different leaf enzymes involved in respiration and photosynthesis is currently lacking in Earth System models. The linkage between nitrogen availability and plant productivity is simplistically represented by potential photosynthesis rates, and is subsequently downregulated depending on nitrogen supply and other nitrogen consumers in the model (e.g., nitrification). This type of potential photosynthesis rate calculation is problematic for several reasons. Firstly, plants do not photosynthesize at potential rates and then downregulate. Secondly, there is considerable subjectivity on the meaning of potential photosynthesis rates. Thirdly, there exists lack of understanding on modeling these potential photosynthesis rates in a changing climate. In addition to model structural issues in representing photosynthesis rates, the role of plant roots in nutrient acquisition have been largely ignored in Earth System models. For example, in CLM4.5, nitrogen uptake is linked to leaf level processes (e.g., primarily productivity) rather than root scale process involved in nitrogen uptake. We present a new plant model for CLM with an improved mechanistic presentation of plant nitrogen uptake based on root scale Michaelis Menten kinetics, and stronger linkages between leaf nitrogen and plant productivity by inferring relationships observed in global databases of plant traits (including the TRY database and several individual studies). We also incorporate improved representation of plant nitrogen leaf allocation, especially in tropical regions where significant over-prediction of plant growth and productivity in CLM4.5 simulations exist. We evaluate our improved global model simulations using the International Land Model Benchmarking (ILAMB) framework. We conclude that mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers leads to overall improvements in CLM4.5's global carbon cycling predictions.
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Techno-economic analysis of a transient plant-based platform for monoclonal antibody production
Nandi, Somen; Kwong, Aaron T.; Holtz, Barry R.; Erwin, Robert L.; Marcel, Sylvain; McDonald, Karen A.
2016-01-01
ABSTRACT Plant-based biomanufacturing of therapeutic proteins is a relatively new platform with a small number of commercial-scale facilities, but offers advantages of linear scalability, reduced upstream complexity, reduced time to market, and potentially lower capital and operating costs. In this study we present a detailed process simulation model for a large-scale new “greenfield” biomanufacturing facility that uses transient agroinfiltration of Nicotiana benthamiana plants grown hydroponically indoors under light-emitting diode lighting for the production of a monoclonal antibody. The model was used to evaluate the total capital investment, annual operating cost, and cost of goods sold as a function of mAb expression level in the plant (g mAb/kg fresh weight of the plant) and production capacity (kg mAb/year). For the Base Case design scenario (300 kg mAb/year, 1 g mAb/kg fresh weight, and 65% recovery in downstream processing), the model predicts a total capital investment of $122 million dollars and cost of goods sold of $121/g including depreciation. Compared with traditional biomanufacturing platforms that use mammalian cells grown in bioreactors, the model predicts significant reductions in capital investment and >50% reduction in cost of goods compared with published values at similar production scales. The simulation model can be modified or adapted by others to assess the profitability of alternative designs, implement different process assumptions, and help guide process development and optimization. PMID:27559626
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Techno-economic analysis of a transient plant-based platform for monoclonal antibody production.
Nandi, Somen; Kwong, Aaron T; Holtz, Barry R; Erwin, Robert L; Marcel, Sylvain; McDonald, Karen A
Plant-based biomanufacturing of therapeutic proteins is a relatively new platform with a small number of commercial-scale facilities, but offers advantages of linear scalability, reduced upstream complexity, reduced time to market, and potentially lower capital and operating costs. In this study we present a detailed process simulation model for a large-scale new "greenfield" biomanufacturing facility that uses transient agroinfiltration of Nicotiana benthamiana plants grown hydroponically indoors under light-emitting diode lighting for the production of a monoclonal antibody. The model was used to evaluate the total capital investment, annual operating cost, and cost of goods sold as a function of mAb expression level in the plant (g mAb/kg fresh weight of the plant) and production capacity (kg mAb/year). For the Base Case design scenario (300 kg mAb/year, 1 g mAb/kg fresh weight, and 65% recovery in downstream processing), the model predicts a total capital investment of $122 million dollars and cost of goods sold of $121/g including depreciation. Compared with traditional biomanufacturing platforms that use mammalian cells grown in bioreactors, the model predicts significant reductions in capital investment and >50% reduction in cost of goods compared with published values at similar production scales. The simulation model can be modified or adapted by others to assess the profitability of alternative designs, implement different process assumptions, and help guide process development and optimization.
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Thermodynamic model effects on the design and optimization of natural gas plants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Diaz, S.; Zabaloy, M.; Brignole, E.A.
1999-07-01
The design and optimization of natural gas plants is carried out on the basis of process simulators. The physical property package is generally based on cubic equations of state. By rigorous thermodynamics phase equilibrium conditions, thermodynamic functions, equilibrium phase separations, work and heat are computed. The aim of this work is to analyze the NGL turboexpansion process and identify possible process computations that are more sensitive to model predictions accuracy. Three equations of state, PR, SRK and Peneloux modification, are used to study the effect of property predictions on process calculations and plant optimization. It is shown that turboexpander plantsmore » have moderate sensitivity with respect to phase equilibrium computations, but higher accuracy is required for the prediction of enthalpy and turboexpansion work. The effect of modeling CO{sub 2} solubility is also critical in mixtures with high CO{sub 2} content in the feed.« less
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Processing on weak electric signals by the autoregressive model
NASA Astrophysics Data System (ADS)
Ding, Jinli; Zhao, Jiayin; Wang, Lanzhou; Li, Qiao
2008-10-01
A model of the autoregressive model of weak electric signals in two plants was set up for the first time. The result of the AR model to forecast 10 values of the weak electric signals is well. It will construct a standard set of the AR model coefficient of the plant electric signal and the environmental factor, and can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on agricultural productions.
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Advancements in Risk-Informed Performance-Based Asset Management for Commercial Nuclear Power Plants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liming, James K.; Ravindra, Mayasandra K.
2006-07-01
Over the past several years, ABSG Consulting Inc. (ABS Consulting) and the South Texas Project Nuclear Operating Company (STPNOC) have developed a decision support process and associated software for risk-informed, performance-based asset management (RIPBAM) of nuclear power plant facilities. RIPBAM applies probabilistic risk assessment (PRA) tools and techniques in the realm of plant physical and financial asset management. The RIPBAM process applies a tiered set of models and supporting performance measures (or metrics) that can ultimately be applied to support decisions affecting the allocation and management of plant resources (e.g., funding, staffing, scheduling, etc.). In general, the ultimate goal ofmore » the RIPBAM process is to continually support decision-making to maximize a facility's net present value (NPV) and long-term profitability for its owners. While the initial applications of RIPBAM have been for nuclear power stations, the methodology can easily be adapted to other types of power station or complex facility decision-making support. RIPBAM can also be designed to focus on performance metrics other than NPV and profitability (e.g., mission reliability, operational availability, probability of mission success per dollar invested, etc.). Recent advancements in the RIPBAM process focus on expanding the scope of previous RIPBAM applications to include not only operations, maintenance, and safety issues, but also broader risk perception components affecting plant owner (stockholder), operator, and regulator biases. Conceptually, RIPBAM is a comprehensive risk-informed cash flow model for decision support. It originated as a tool to help manage plant refueling outage scheduling, and was later expanded to include the full spectrum of operations and maintenance decision support. However, it differs from conventional business modeling tools in that it employs a systems engineering approach with broadly based probabilistic analysis of organizational 'value streams'. The scope of value stream inclusion in the process can be established by the user, but in its broadest applications, RIPBAM can be used to address how risk perceptions of plant owners and regulators are impacted by plant performance. Plant staffs can expand and refine RIPBAM models scope via a phased program of activities over time. This paper shows how the multi-metric uncertainty analysis feature of RIPBAM can apply a wide spectrum of decision-influencing factors to support decisions designed to maximize the probability of achieving, maintaining, and improving upon plant goals and objectives. In this paper, the authors show how this approach can be extremely valuable to plant owners and operators in supporting plant value-impacting decision-making processes. (authors)« less
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Short-Term Planning of Hybrid Power System
NASA Astrophysics Data System (ADS)
Knežević, Goran; Baus, Zoran; Nikolovski, Srete
2016-07-01
In this paper short-term planning algorithm for hybrid power system consist of different types of cascade hydropower plants (run-of-the river, pumped storage, conventional), thermal power plants (coal-fired power plants, combined cycle gas-fired power plants) and wind farms is presented. The optimization process provides a joint bid of the hybrid system, and thus making the operation schedule of hydro and thermal power plants, the operation condition of pumped-storage hydropower plants with the aim of maximizing profits on day ahead market, according to expected hourly electricity prices, the expected local water inflow in certain hydropower plants, and the expected production of electrical energy from the wind farm, taking into account previously contracted bilateral agreement for electricity generation. Optimization process is formulated as hourly-discretized mixed integer linear optimization problem. Optimization model is applied on the case study in order to show general features of the developed model.
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NASA Astrophysics Data System (ADS)
Joshi, D. M.
2017-09-01
Cryogenic technology is used for liquefaction of many gases and it has several applications in food process engineering. Temperatures below 123 K are considered to be in the field of cryogenics. Extreme low temperatures are a basic need for many industrial processes and have several applications, such as superconductivity of magnets, space, medicine and gas industries. Several methods can be used to obtain the low temperatures required for liquefaction of gases. The process of cooling or refrigerating a gas to a temperature below its critical temperature so that liquid can be formed at some suitable pressure, which is below the critical pressure, is the basic liquefaction process. Different cryogenic cycle configurations are designed for getting the liquefied form of gases at different temperatures. Each of the cryogenic cycles like Linde cycle, Claude cycle, Kapitza cycle or modified Claude cycle has its own advantages and disadvantages. The placement of heat exchangers, Joule-Thompson valve and turboexpander decides the configuration of a cryogenic cycle. Each configuration has its own efficiency according to the application. Here, a nitrogen liquefaction plant is used for the analysis purpose. The process modeling tool ASPEN HYSYS can provide a software simulation approach before the actual implementation of the plant in the field. This paper presents the simulation and statistical analysis of the Claude cycle with the process modeling tool ASPEN HYSYS. It covers the technique used to optimize the liquefaction of the plant. The simulation results so obtained can be used as a reference for the design and optimization of the nitrogen liquefaction plant. Efficient liquefaction will give the best performance and productivity to the plant.
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NASA Astrophysics Data System (ADS)
Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz
2010-05-01
Today, crop models have a widespread application in natural sciences, because plant growth interacts and modifies the environment. Transport processes involve water and nutrient uptake from the saturated and unsaturated zone in the pedosphere. Turnover processes include the conversion of dead root biomass into organic matter. Transpiration and the interception of radiation influence the energy exchange between atmosphere and biosphere. But many more feedback mechanisms might be of interest, including erosion, soil compaction or trace gas exchanges. Most of the existing crop models have a closed structure and do not provide interfaces or code design elements for easy data transfer or process exchange with other models during runtime. Changes in the model structure, the inclusion of alternative process descriptions or the implementation of additional functionalities requires a lot of coding. The same is true if models are being upscaled from field to landscape or catchment scale. We therefore conclude that future integrated model developments would benefit from a model structure that has the following requirements: replaceability, expandability and independency. In addition to these requirements we also propose the interactivity of models, which means that models that are being coupled are highly interacting and depending on each other, i.e. the model should be open for influences from other independent models and react on influences directly. Hence, a model which consists of building blocks seems to be reasonable. The aim of the study is the presentation of the new crop model type, the plant growth model framework, PMF. The software concept refers to an object-oriented approach, which is developed with the Unified Modeling Language (UML). The model is implemented with Python, a high level object-oriented programming language. The integration of the models with a setup code enables the data transfer on the computer memory level and direct exchange of information about changing boundary conditions. The crop model concept refers to two main elements. A plant model, which represents an abstract network of plant organs and processes and a process library, which holds mathematical solutions for the growth processes. Growth processes were mainly taken from existing, well known crop models such as SUCROS and CERES. The crop specific properties of root architecture are described based on a maximum rooting depth and a vertical growth rate. The biomass distribution depends on an interactive allocation process due to the soil layers with a daily time step. In order to show the performance and capabilities of PMF, the model is coupled with the Catchment Modeling Framework (CMF) and the simple nitrogen mineralization model DeComp. The main feature of the integrated model set up is the interaction between root growth, water uptake and nitrogen supply of the soil. We show a virtual case study on the hillslope scale and spatially dependence of water and nitrogen stress based on topographic position and seasonal development.
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Patterson, David Albert; Strehmel, Alexander; Erzgräber, Beate; Hammel, Klaus
2017-12-01
In a recent scientific opinion of the European Food Safety Authority it is argued that the accumulation of plant protection products in sediments over long time periods may be an environmentally significant process. Therefore, the European Food Safety Authority proposed a calculation to account for plant protection product accumulation. This calculation, however, considers plant protection product degradation within sediment as the only dissipation route, and does not account for sediment dynamics or back-diffusion into the water column. The hydraulic model Hydrologic Engineering Center-River Analysis System (HEC-RAS; US Army Corps of Engineers) was parameterized to assess sediment transport and deposition dynamics within the FOrum for Co-ordination of pesticide fate models and their USe (FOCUS) scenarios in simulations spanning 20 yr. The results show that only 10 to 50% of incoming sediment would be deposited. The remaining portion of sediment particles is transported across the downstream boundary. For a generic plant protection product substance this resulted in deposition of only 20 to 50% of incoming plant protection product substance. In a separate analysis, the FOCUS TOXSWA model was utilized to examine the relative importance of degradation versus back-diffusion as loss processes from the sediment compartment for a diverse range of generic plant protection products. In simulations spanning 20 yr, it was shown that back-diffusion was generally the dominant dissipation process. The results of the present study show that sediment dynamics and back-diffusion should be considered when calculating long-term plant protection product accumulation in sediment. Neglecting these may lead to a systematic overestimation of accumulation. Environ Toxicol Chem 2017;36:3223-3231. © 2017 SETAC. © 2017 SETAC.
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Application of Advanced Process Control techniques to a pusher type reheating furnace
NASA Astrophysics Data System (ADS)
Zanoli, S. M.; Pepe, C.; Barboni, L.
2015-11-01
In this paper an Advanced Process Control system aimed at controlling and optimizing a pusher type reheating furnace located in an Italian steel plant is proposed. The designed controller replaced the previous control system, based on PID controllers manually conducted by process operators. A two-layer Model Predictive Control architecture has been adopted that, exploiting a chemical, physical and economic modelling of the process, overcomes the limitations of plant operators’ mental model and knowledge. In addition, an ad hoc decoupling strategy has been implemented, allowing the selection of the manipulated variables to be used for the control of each single process variable. Finally, in order to improve the system flexibility and resilience, the controller has been equipped with a supervision module. A profitable trade-off between conflicting specifications, e.g. safety, quality and production constraints, energy saving and pollution impact, has been guaranteed. Simulation tests and real plant results demonstrated the soundness and the reliability of the proposed system.
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Tomasula, P M; Yee, W C F; McAloon, A J; Nutter, D W; Bonnaillie, L M
2013-05-01
Energy-savings measures have been implemented in fluid milk plants to lower energy costs and the energy-related carbon dioxide (CO2) emissions. Although these measures have resulted in reductions in steam, electricity, compressed air, and refrigeration use of up to 30%, a benchmarking framework is necessary to examine the implementation of process-specific measures that would lower energy use, costs, and CO2 emissions even further. In this study, using information provided by the dairy industry and equipment vendors, a customizable model of the fluid milk process was developed for use in process design software to benchmark the electrical and fuel energy consumption and CO2 emissions of current processes. It may also be used to test the feasibility of new processing concepts to lower energy and CO2 emissions with calculation of new capital and operating costs. The accuracy of the model in predicting total energy usage of the entire fluid milk process and the pasteurization step was validated using available literature and industry energy data. Computer simulation of small (40.0 million L/yr), medium (113.6 million L/yr), and large (227.1 million L/yr) processing plants predicted the carbon footprint of milk, defined as grams of CO2 equivalents (CO2e) per kilogram of packaged milk, to within 5% of the value of 96 g of CO 2e/kg of packaged milk obtained in an industry-conducted life cycle assessment and also showed, in agreement with the same study, that plant size had no effect on the carbon footprint of milk but that larger plants were more cost effective in producing milk. Analysis of the pasteurization step showed that increasing the percentage regeneration of the pasteurizer from 90 to 96% would lower its thermal energy use by almost 60% and that implementation of partial homogenization would lower electrical energy use and CO2e emissions of homogenization by 82 and 5.4%, respectively. It was also demonstrated that implementation of steps to lower non-process-related electrical energy in the plant would be more effective in lowering energy use and CO2e emissions than fuel-related energy reductions. The model also predicts process-related water usage, but this portion of the model was not validated due to a lack of data. The simulator model can serve as a benchmarking framework for current plant operations and a tool to test cost-effective process upgrades or evaluate new technologies that improve the energy efficiency and lower the carbon footprint of milk processing plants. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Throughput Optimization of Continuous Biopharmaceutical Manufacturing Facilities.
Garcia, Fernando A; Vandiver, Michael W
2017-01-01
In order to operate profitably under different product demand scenarios, biopharmaceutical companies must design their facilities with mass output flexibility in mind. Traditional biologics manufacturing technologies pose operational challenges in this regard due to their high costs and slow equipment turnaround times, restricting the types of products and mass quantities that can be processed. Modern plant design, however, has facilitated the development of lean and efficient bioprocessing facilities through footprint reduction and adoption of disposable and continuous manufacturing technologies. These development efforts have proven to be crucial in seeking to drastically reduce the high costs typically associated with the manufacturing of recombinant proteins. In this work, mathematical modeling is used to optimize annual production schedules for a single-product commercial facility operating with a continuous upstream and discrete batch downstream platform. Utilizing cell culture duration and volumetric productivity as process variables in the model, and annual plant throughput as the optimization objective, 3-D surface plots are created to understand the effect of process and facility design on expected mass output. The model shows that once a plant has been fully debottlenecked it is capable of processing well over a metric ton of product per year. Moreover, the analysis helped to uncover a major limiting constraint on plant performance, the stability of the neutralized viral inactivated pool, which may indicate that this should be a focus of attention during future process development efforts. LAY ABSTRACT: Biopharmaceutical process modeling can be used to design and optimize manufacturing facilities and help companies achieve a predetermined set of goals. One way to perform optimization is by making the most efficient use of process equipment in order to minimize the expenditure of capital, labor and plant resources. To that end, this paper introduces a novel mathematical algorithm used to determine the most optimal equipment scheduling configuration that maximizes the mass output for a facility producing a single product. The paper also illustrates how different scheduling arrangements can have a profound impact on the availability of plant resources, and identifies limiting constraints on the plant design. In addition, simulation data is presented using visualization techniques that aid in the interpretation of the scientific concepts discussed. © PDA, Inc. 2017.
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Chen, Yi- Ping Phoebe; Hanan, Jim
2002-01-01
Models of plant architecture allow us to explore how genotype environment interactions effect the development of plant phenotypes. Such models generate masses of data organised in complex hierarchies. This paper presents a generic system for creating and automatically populating a relational database from data generated by the widely used L-system approach to modelling plant morphogenesis. Techniques from compiler technology are applied to generate attributes (new fields) in the database, to simplify query development for the recursively-structured branching relationship. Use of biological terminology in an interactive query builder contributes towards making the system biologist-friendly.
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Three-Dimensional Modeling of Weed Plants Using Low-Cost Photogrammetry
Andújar, Dionisio; Fernández-Quintanilla, César; Dorado, José
2018-01-01
Sensing advances in plant phenotyping are of vital importance in basic and applied plant research. Plant phenotyping enables the modeling of complex shapes, which is useful, for example, in decision-making for agronomic management. In this sense, 3D processing algorithms for plant modeling is expanding rapidly with the emergence of new sensors and techniques designed to morphologically characterize. However, there are still some technical aspects to be improved, such as an accurate reconstruction of end-details. This study adapted low-cost techniques, Structure from Motion (SfM) and MultiView Stereo (MVS), to create 3D models for reconstructing plants of three weed species with contrasting shape and plant structures. Plant reconstruction was developed by applying SfM algorithms to an input set of digital images acquired sequentially following a track that was concentric and equidistant with respect to the plant axis and using three different angles, from a perpendicular to top view, which guaranteed the necessary overlap between images to obtain high precision 3D models. With this information, a dense point cloud was created using MVS, from which a 3D polygon mesh representing every plants’ shape and geometry was generated. These 3D models were validated with ground truth values (e.g., plant height, leaf area (LA) and plant dry biomass) using regression methods. The results showed, in general, a good consistency in the correlation equations between the estimated values in the models and the actual values measured in the weed plants. Indeed, 3D modeling using SfM algorithms proved to be a valuable methodology for weed phenotyping, since it accurately estimated the actual values of plant height and LA. Additionally, image processing using the SfM method was relatively fast. Consequently, our results indicate the potential of this budget system for plant reconstruction at high detail, which may be usable in several scenarios, including outdoor conditions. Future research should address other issues, such as the time-cost relationship and the need for detail in the different approaches. PMID:29614039
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Conceptual hierarchical modeling to describe wetland plant community organization
Little, A.M.; Guntenspergen, G.R.; Allen, T.F.H.
2010-01-01
Using multivariate analysis, we created a hierarchical modeling process that describes how differently-scaled environmental factors interact to affect wetland-scale plant community organization in a system of small, isolated wetlands on Mount Desert Island, Maine. We followed the procedure: 1) delineate wetland groups using cluster analysis, 2) identify differently scaled environmental gradients using non-metric multidimensional scaling, 3) order gradient hierarchical levels according to spatiotem-poral scale of fluctuation, and 4) assemble hierarchical model using group relationships with ordination axes and post-hoc tests of environmental differences. Using this process, we determined 1) large wetland size and poor surface water chemistry led to the development of shrub fen wetland vegetation, 2) Sphagnum and water chemistry differences affected fen vs. marsh / sedge meadows status within small wetlands, and 3) small-scale hydrologic differences explained transitions between forested vs. non-forested and marsh vs. sedge meadow vegetation. This hierarchical modeling process can help explain how upper level contextual processes constrain biotic community response to lower-level environmental changes. It creates models with more nuanced spatiotemporal complexity than classification and regression tree procedures. Using this process, wetland scientists will be able to generate more generalizable theories of plant community organization, and useful management models. ?? Society of Wetland Scientists 2009.
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Jianbo Cui; Changsheng Li; Carl Trettin
2005-01-01
A comprehensive biogeochemical model, Wetland-DNDC, was applied to analyze the carbon and hydrologic characteristics of forested wetland ecosystem at Minnesota (MN) and Florida (FL) sites. The model simulates the flows of carbon, energy, and water in forested wetlands. Modeled carbon dynamics depends on physiological plant factors, the size of plant pools,...
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Hu, Yue; Boyer, Treavor H
2017-05-15
The application of bicarbonate-form anion exchange resin and sodium bicarbonate salt for resin regeneration was investigated in this research is to reduce chloride ion release during treatment and the disposal burden of sodium chloride regeneration solution when using traditional chloride-form ion exchange (IX). The target contaminant in this research was dissolved organic carbon (DOC). The performance evaluation was conducted in a completely mixed flow reactor (CMFR) IX configuration. A process model that integrated treatment and regeneration was investigated based on the characteristics of configuration. The kinetic and equilibrium experiments were performed to obtain required parameters for the process model. The pilot plant tests were conducted to validate the model as well as provide practical understanding on operation. The DOC concentration predicted by the process model responded to the change of salt concentration in the solution, and showed a good agreement with pilot plant data with less than 10% difference in terms of percentage removal. Both model predictions and pilot plant tests showed over 60% DOC removal by bicarbonate-form resin for treatment and sodium bicarbonate for regeneration, which was comparable to chloride-form resin for treatment and sodium chloride for regeneration. Lastly, the DOC removal was improved by using higher salt concentration for regeneration. Copyright © 2017 Elsevier Ltd. All rights reserved.
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IMPROVING TACONITE PROCESSING PLANT EFFICIENCY BY COMPUTER SIMULATION, Final Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
William M. Bond; Salih Ersayin
2007-03-30
This project involved industrial scale testing of a mineral processing simulator to improve the efficiency of a taconite processing plant, namely the Minorca mine. The Concentrator Modeling Center at the Coleraine Minerals Research Laboratory, University of Minnesota Duluth, enhanced the capabilities of available software, Usim Pac, by developing mathematical models needed for accurate simulation of taconite plants. This project provided funding for this technology to prove itself in the industrial environment. As the first step, data representing existing plant conditions were collected by sampling and sample analysis. Data were then balanced and provided a basis for assessing the efficiency ofmore » individual devices and the plant, and also for performing simulations aimed at improving plant efficiency. Performance evaluation served as a guide in developing alternative process strategies for more efficient production. A large number of computer simulations were then performed to quantify the benefits and effects of implementing these alternative schemes. Modification of makeup ball size was selected as the most feasible option for the target performance improvement. This was combined with replacement of existing hydrocyclones with more efficient ones. After plant implementation of these modifications, plant sampling surveys were carried out to validate findings of the simulation-based study. Plant data showed very good agreement with the simulated data, confirming results of simulation. After the implementation of modifications in the plant, several upstream bottlenecks became visible. Despite these bottlenecks limiting full capacity, concentrator energy improvement of 7% was obtained. Further improvements in energy efficiency are expected in the near future. The success of this project demonstrated the feasibility of a simulation-based approach. Currently, the Center provides simulation-based service to all the iron ore mining companies operating in northern Minnesota, and future proposals are pending with non-taconite mineral processing applications.« less
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An ASM/ADM model interface for dynamic plant-wide simulation.
Nopens, Ingmar; Batstone, Damien J; Copp, John B; Jeppsson, Ulf; Volcke, Eveline; Alex, Jens; Vanrolleghem, Peter A
2009-04-01
Mathematical modelling has proven to be very useful in process design, operation and optimisation. A recent trend in WWTP modelling is to include the different subunits in so-called plant-wide models rather than focusing on parts of the entire process. One example of a typical plant-wide model is the coupling of an upstream activated sludge plant (including primary settler, and secondary clarifier) to an anaerobic digester for sludge digestion. One of the key challenges when coupling these processes has been the definition of an interface between the well accepted activated sludge model (ASM1) and anaerobic digestion model (ADM1). Current characterisation and interface models have key limitations, the most critical of which is the over-use of X(c) (or lumped complex) variable as a main input to the ADM1. Over-use of X(c) does not allow for variation of degradability, carbon oxidation state or nitrogen content. In addition, achieving a target influent pH through the proper definition of the ionic system can be difficult. In this paper, we define an interface and characterisation model that maps degradable components directly to carbohydrates, proteins and lipids (and their soluble analogues), as well as organic acids, rather than using X(c). While this interface has been designed for use with the Benchmark Simulation Model No. 2 (BSM2), it is widely applicable to ADM1 input characterisation in general. We have demonstrated the model both hypothetically (BSM2), and practically on a full-scale anaerobic digester treating sewage sludge.
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An End-to-End Model of Plant Pheromone Channel for Long Range Molecular Communication.
Unluturk, Bige D; Akyildiz, Ian F
2017-01-01
A new track in molecular communication is using pheromones which can scale up the range of diffusion-based communication from μm meters to meters and enable new applications requiring long range. Pheromone communication is the emission of molecules in the air which trigger behavioral or physiological responses in receiving organisms. The objective of this paper is to introduce a new end-to-end model which incorporates pheromone behavior with communication theory for plants. The proposed model includes both the transmission and reception processes as well as the propagation channel. The transmission process is the emission of pheromones from the leaves of plants. The dispersion of pheromones by the flow of wind constitutes the propagation process. The reception process is the sensing of pheromones by the pheromone receptors of plants. The major difference of pheromone communication from other molecular communication techniques is the dispersion channel acting under the laws of turbulent diffusion. In this paper, the pheromone channel is modeled as a Gaussian puff, i.e., a cloud of pheromone released instantaneously from the source whose dispersion follows a Gaussian distribution. Numerical results on the performance of the overall end-to-end pheromone channel in terms of normalized gain and delay are provided.
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Anticipatory control: A software retrofit for current plant controllers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Parthasarathy, S.; Parlos, A.G.; Atiya, A.F.
1993-01-01
The design and simulated testing of an artificial neural network (ANN)-based self-adapting controller for complex process systems are presented in this paper. The proposed controller employs concepts based on anticipatory systems, which have been widely used in the petroleum and chemical industries, and they are slowly finding their way into the power industry. In particular, model predictive control (MPC) is used for the systematic adaptation of the controller parameters to achieve desirable plant performance over the entire operating envelope. The versatile anticipatory control algorithm developed in this study is projected to enhance plant performance and lend robustness to drifts inmore » plant parameters and to modeling uncertainties. This novel technique of integrating recurrent ANNs with a conventional controller structure appears capable of controlling complex, nonlinear, and nonminimum phase process systems. The direct, on-line adaptive control algorithm presented in this paper considers the plant response over a finite time horizon, diminishing the need for manual control or process interruption for controller gain tuning.« less
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Overman, Allen R.; Scholtz, Richard V.
2011-01-01
The expanded growth model is developed to describe accumulation of plant biomass (Mg ha−1) and mineral elements (kg ha−1) in with calendar time (wk). Accumulation of plant biomass with calendar time occurs as a result of photosynthesis for green land-based plants. A corresponding accumulation of mineral elements such as nitrogen, phosphorus, and potassium occurs from the soil through plant roots. In this analysis, the expanded growth model is tested against high quality, published data on corn (Zea mays L.) growth. Data from a field study in South Carolina was used to evaluate the application of the model, where the planting time of April 2 in the field study maximized the capture of solar energy for biomass production. The growth model predicts a simple linear relationship between biomass yield and the growth quantifier, which is confirmed with the data. The growth quantifier incorporates the unit processes of distribution of solar energy which drives biomass accumulation by photosynthesis, partitioning of biomass between light-gathering and structural components of the plants, and an aging function. A hyperbolic relationship between plant nutrient uptake and biomass yield is assumed, and is confirmed for the mineral elements nitrogen (N), phosphorus (P), and potassium (K). It is concluded that the rate limiting process in the system is biomass accumulation by photosynthesis and that nutrient accumulation occurs in virtual equilibrium with biomass accumulation. PMID:22194842
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NASA Astrophysics Data System (ADS)
Houska, Tobias; Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz
2014-05-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the Van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 x 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape parameter of the retention curve n was highly constrained whilst other parameters of the retention curve showed a large equifinality. The root and storage dry matter observations were predicted with a NSE of 0.94, a low bias of 58.2 kg ha-1 and a high R2 of 0.98. Dry matters of stem and leaves were predicted with less, but still high accuracy (NSE=0.79, bias=221.7 kg ha-1, R2=0.87). We attribute this slightly poorer model performance to missing leaf senescence which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use-efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need of including agricultural management options in the coupled model.
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NASA Astrophysics Data System (ADS)
Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.
2013-12-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape parameter of the retention curve n was highly constrained whilst other parameters of the retention curve showed a large equifinality. The root and storage dry matter observations were predicted with a NSE of 0.94, a low bias of -58.2 kg ha-1 and a high R2 of 0.98. Dry matters of stem and leaves were predicted with less, but still high accuracy (NSE = 0.79, bias = 221.7 kg ha-1, R2 = 0.87). We attribute this slightly poorer model performance to missing leaf senescence which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use-efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need of including agricultural management options in the coupled model.
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A judgment and decision-making model for plant behavior.
Karban, Richard; Orrock, John L
2018-06-12
Recently plant biologists have documented that plants, like animals, engage in many activities that can be considered as behaviors, although plant biologists currently lack a conceptual framework to understand these processes. Borrowing the well-established framework developed by psychologists, we propose that plant behaviors can be constructively modeled by identifying four distinct components: 1) a cue or stimulus that provides information, 2) a judgment whereby the plant perceives and processes this informative cue, 3) a decision whereby the plant chooses among several options based on their relative costs and benefits, and 4) action. Judgment for plants can be determined empirically by monitoring signaling associated with electrical, calcium, or hormonal fluxes. Decision-making can be evaluated empirically by monitoring gene expression or differential allocation of resources. We provide examples of the utility of this judgment and decision-making framework by considering cases in which plants either successfully or unsuccessfully induced resistance against attacking herbivores. Separating judgment from decision-making suggests new analytical paradigms (i.e., Bayesian methods for judgment and economic utility models for decision-making). Following this framework, we propose an experimental approach to plant behavior that explicitly manipulates the stimuli provided to plants, uses plants that vary in sensory abilities, and examines how environmental context affects plant responses. The concepts and approaches that follow from the judgment and decision-making framework can shape how we study and understand plant-herbivore interactions, biological invasions, plant responses to climate change, and the susceptibility of plants to evolutionary traps. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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Bioassay of Plant Growth Regulator Activity on Aquatic Plants
1990-07-01
natural plant hormonal processes. Certain substi- tuted pyrimidine and triazole compounds have been found to inhibit the syn- thesis of gibberellin in...drove down the pH to levels that were injurious to the plants. For this reason, the bicarbonate buffer was added to both stock and experimental media...digital pH meter (Orion Model 701A/Digital, Orion Research, Inc., Cambridge, MA) equipped with a dis- solved oxygen (DO) electrode (Orion Model 97-08
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NASA Astrophysics Data System (ADS)
Hidy, Dóra; Barcza, Zoltán; Marjanović, Hrvoje; Zorana Ostrogović Sever, Maša; Dobor, Laura; Gelybó, Györgyi; Fodor, Nándor; Pintér, Krisztina; Churkina, Galina; Running, Steven; Thornton, Peter; Bellocchi, Gianni; Haszpra, László; Horváth, Ferenc; Suyker, Andrew; Nagy, Zoltán
2016-12-01
The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen, and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as a base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil-moisture-related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multilayer soil module; in this paper, Biome-BGCMuSo v4.0 is documented). Case studies on a managed forest, cropland, and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance.
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Determining the potential productivity of food crops in controlled environments
NASA Technical Reports Server (NTRS)
Bugbee, Bruce
1992-01-01
The quest to determine the maximum potential productivity of food crops is greatly benefitted by crop growth models. Many models have been developed to analyze and predict crop growth in the field, but it is difficult to predict biological responses to stress conditions. Crop growth models for the optimal environments of a Controlled Environment Life Support System (CELSS) can be highly predictive. This paper discusses the application of a crop growth model to CELSS; the model is used to evaluate factors limiting growth. The model separately evaluates the following four physiological processes: absorption of PPF by photosynthetic tissue, carbon fixation (photosynthesis), carbon use (respiration), and carbon partitioning (harvest index). These constituent processes determine potentially achievable productivity. An analysis of each process suggests that low harvest index is the factor most limiting to yield. PPF absorption by plant canopies and respiration efficiency are also of major importance. Research concerning productivity in a CELSS should emphasize: (1) the development of gas exchange techniques to continuously monitor plant growth rates and (2) environmental techniques to reduce plant height in communities.
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NASA Astrophysics Data System (ADS)
Gayler, S.; Wöhling, T.; Priesack, E.; Wizemann, H.-D.; Wulfmeyer, V.; Ingwersen, J.; Streck, T.
2012-04-01
The soil moisture, the energy balance at the land surface and the state of the lower atmosphere are closely linked by complex feedback processes. The vegetation acts as the interface between soil and atmosphere and plays an important role in this coupled system. Consequently, a consistent description of the fluxes of water, energy and carbon is a prerequisite for analyzing many problems in soil-, plant- and atmospheric research. To better understand the complex interplay of the involved processes, many numerical and physics-based soil-plant-atmosphere simulation models were developed during the last decades. As these models have been developed for different purposes, the degree of complexity in describing individual feedback processes can vary considerably. In models designed to predict soil moisture, for example, plants are often sufficiently represented by a simple sink term. If these models are calibrated, sometimes only one state variable and the corresponding calibration data type is used, e.g. soil water contents or pressure heads. In this case, vegetation properties and feedbacks between soil moisture, plant growth and stomatal conductivity are neglected to a large extent. Some crop models, in turn, pay little attention to modeling soil water transport. In a coupled soil-vegetation-atmosphere model, however, the interface between soil and atmosphere has to be consistent in all directions. As different data types such as soil moisture, leaf area development and evapotranspiration may contain contrasting information about the system under consideration, the fitting of such a model to a single data type may result in a poor agreement to another data type. The trade-off between the fittings to different data types can thereby be caused by structural inadequacies in the model or by errors in input and calibration data. In our study, we compare the Community Land Model CLM (version 3.5, offline mode) with different agricultural crop models to analyze the adequacy of their structural complexity on two winter wheat research fields under different climate in South-West Germany. We investigate the ability of the models to simultaneously fit measured soil water contents, leaf area development and actual evapotranspiration rates from eddy-covariance measurements. The calibration of the models is performed in a multi-criteria context using three objective functions, which describe the discrepancy between measurements and simulations of the three data types. We use the AMALGAM evolutionary search algorithm to simultaneously estimate the most important plant and soil hydraulic parameters. The results show that the trade-off in fitting soil moisture, leaf area development and evapotranspiration can be quite large for those models that represent plant processes by simple concepts. However, these trade-offs are smaller for the more mechanistic plant growth models, so that it can be expected that these optimized mechanistic models will provide the basis for improved simulations of land-surface-atmosphere feedback processes.
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Chapter 4. New model systems for the study of developmental evolution in plants.
Kramer, Elena M
2009-01-01
The number of genetically tractable plant model systems is rapidly increasing, thanks to the decreasing cost of sequencing and the wide amenability of plants to stable transformation and other functional approaches. In this chapter, I discuss emerging model systems from throughout the land plant phylogeny and consider how their unique attributes are contributing to our understanding of development, evolution, and ecology. These new models are being developed using two distinct strategies: in some cases, they are selected because of their close relationship to the established models, while in others, they are chosen with the explicit intention of exploring distantly related plant lineages. Such complementary approaches are yielding exciting new results that shed light on both micro- and macroevolutionary processes in the context of developmental evolution.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Green, C.H.; Ready, A.B.; Rea, J.
1995-06-01
Versions of the computer program PROATES (PROcess Analysis for Thermal Energy Systems) have been used since 1979 to analyse plant performance improvement proposals relating to existing plant and also to evaluate new plant designs. Several plant modifications have been made to improve performance based on the model predictions and the predicted performance has been realised in practice. The program was born out of a need to model the overall steady state performance of complex plant to enable proposals to change plant component items or operating strategy to be evaluated. To do this with confidence it is necessary to model themore » multiple thermodynamic interactions between the plant components. The modelling system is modular in concept allowing the configuration of individual plant components to represent any particular power plant design. A library exists of physics based modules which have been extensively validated and which provide representations of a wide range of boiler, turbine and CW system components. Changes to model data and construction is achieved via a user friendly graphical model editing/analysis front-end with results being presented via the computer screen or hard copy. The paper describes briefly the modelling system but concentrates mainly on the application of the modelling system to assess design re-optimisation, firing with different fuels and the re-powering of an existing plant.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Meshkati, N.; Buller, B.J.; Azadeh, M.A.
1995-04-01
The goal of this research is threefold: (1) use of the Skill-, Rule-, and Knowledge-based levels of cognitive control -- the SRK framework -- to develop an integrated information processing conceptual framework (for integration of workstation, job, and team design); (2) to evaluate the user interface component of this framework -- the Ecological display; and (3) to analyze the effect of operators` individual information processing behavior and decision styles on handling plant disturbances plus their performance on, and preference for, Traditional and Ecological user interfaces. A series of studies were conducted. In Part I, a computer simulation model and amore » mathematical model were developed. In Part II, an experiment was designed and conducted at the EBR-II plant of the Argonne National Laboratory-West in Idaho Falls, Idaho. It is concluded that: the integrated SRK-based information processing model for control room operations is superior to the conventional rule-based model; operators` individual decision styles and the combination of their styles play a significant role in effective handling of nuclear power plant disturbances; use of the Ecological interface results in significantly more accurate event diagnosis and recall of various plant parameters, faster response to plant transients, and higher ratings of subject preference; and operators` decision styles affect on both their performance and preference for the Ecological interface.« less
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2007-09-01
simulation modeling approach to describing carbon- flow-based, ecophysiological processes and biomass dynamics of fresh- water submersed aquatic plant...the distribution and abundance of SAV. In aquatic systems a small part of the irradiance can be reflected by the water surface, and further...to the fact that water temperatures in the lake were relatively low compared to air tem- peratures because of the large inflow of groundwater (Titus
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Research on animation design of growing plant based on 3D MAX technology
NASA Astrophysics Data System (ADS)
Chen, Yineng; Fang, Kui; Bu, Weiqiong; Zhang, Xiaoling; Lei, Menglong
In view of virtual plant has practical demands on quality, image and degree of realism animation in growing process of plant, this thesis design the animation based on mechanism and regularity of plant growth, and propose the design method based on 3D MAX technology. After repeated analysis and testing, it is concluded that there are modeling, rendering, animation fabrication and other key technologies in the animation design process. Based on this, designers can subdivid the animation into seed germination animation, plant growth prophase animation, catagen animation, later animation and blossom animation. This paper compounds the animation of these five stages by VP window to realize the completed 3D animation. Experimental result shows that the animation can realized rapid, visual and realistic simulatation the plant growth process.
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How does pedogenesis drive plant diversity?
Laliberté, Etienne; Grace, James B.; Huston, Michael A.; Lambers, Hans; Teste, François P.; Turner, Benjamin L.; Wardle, David A.
2013-01-01
Some of the most species-rich plant communities occur on ancient, strongly weathered soils, whereas those on recently developed soils tend to be less diverse. Mechanisms underlying this well-known pattern, however, remain unresolved. Here, we present a conceptual model describing alternative mechanisms by which pedogenesis (the process of soil formation) might drive plant diversity. We suggest that long-term soil chronosequences offer great, yet largely untapped, potential as 'natural experiments' to determine edaphic controls over plant diversity. Finally, we discuss how our conceptual model can be evaluated quantitatively using structural equation modeling to advance multivariate theories about the determinants of local plant diversity. This should help us to understand broader-scale diversity patterns, such as the latitudinal gradient of plant diversity.
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Improved simulation of poorly drained forests using Biome-BGC.
Bond-Lamberty, Ben; Gower, Stith T; Ahl, Douglas E
2007-05-01
Forested wetlands and peatlands are important in boreal and terrestrial biogeochemical cycling, but most general-purpose forest process models are designed and parameterized for upland systems. We describe changes made to Biome-BGC, an ecophysiological process model, that improve its ability to simulate poorly drained forests. Model changes allowed for: (1) lateral water inflow from a surrounding watershed, and variable surface and subsurface drainage; (2) adverse effects of anoxic soil on decomposition and nutrient mineralization; (3) closure of leaf stomata in flooded soils; and (4) growth of nonvascular plants (i.e., bryophytes). Bryophytes were treated as ectohydric broadleaf evergreen plants with zero stomatal conductance, whose cuticular conductance to CO(2) was dependent on plant water content. Individual model changes were parameterized with published data, and ecosystem-level model performance was assessed by comparing simulated output to field data from the northern BOREAS site in Manitoba, Canada. The simulation of the poorly drained forest model exhibited reduced decomposition and vascular plant growth (-90%) compared with that of the well-drained forest model; the integrated bryophyte photosynthetic response accorded well with published data. Simulated net primary production, biomass and soil carbon accumulation broadly agreed with field measurements, although simulated net primary production was higher than observed data in well-drained stands. Simulated net primary production in the poorly drained forest was most sensitive to oxygen restriction on soil processes, and secondarily to stomatal closure in flooded conditions. The modified Biome-BGC remains unable to simulate true wetlands that are subject to prolonged flooding, because it does not track organic soil formation, water table changes, soil redox potential or anaerobic processes.
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Artificial neural network modelling of a large-scale wastewater treatment plant operation.
Güçlü, Dünyamin; Dursun, Sükrü
2010-11-01
Artificial Neural Networks (ANNs), a method of artificial intelligence method, provide effective predictive models for complex processes. Three independent ANN models trained with back-propagation algorithm were developed to predict effluent chemical oxygen demand (COD), suspended solids (SS) and aeration tank mixed liquor suspended solids (MLSS) concentrations of the Ankara central wastewater treatment plant. The appropriate architecture of ANN models was determined through several steps of training and testing of the models. ANN models yielded satisfactory predictions. Results of the root mean square error, mean absolute error and mean absolute percentage error were 3.23, 2.41 mg/L and 5.03% for COD; 1.59, 1.21 mg/L and 17.10% for SS; 52.51, 44.91 mg/L and 3.77% for MLSS, respectively, indicating that the developed model could be efficiently used. The results overall also confirm that ANN modelling approach may have a great implementation potential for simulation, precise performance prediction and process control of wastewater treatment plants.
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Enzymatic corn wet milling: engineering process and cost model
Ramírez, Edna C; Johnston, David B; McAloon, Andrew J; Singh, Vijay
2009-01-01
Background Enzymatic corn wet milling (E-milling) is a process derived from conventional wet milling for the recovery and purification of starch and co-products using proteases to eliminate the need for sulfites and decrease the steeping time. In 2006, the total starch production in USA by conventional wet milling equaled 23 billion kilograms, including modified starches and starches used for sweeteners and ethanol production [1]. Process engineering and cost models for an E-milling process have been developed for a processing plant with a capacity of 2.54 million kg of corn per day (100,000 bu/day). These models are based on the previously published models for a traditional wet milling plant with the same capacity. The E-milling process includes grain cleaning, pretreatment, enzymatic treatment, germ separation and recovery, fiber separation and recovery, gluten separation and recovery and starch separation. Information for the development of the conventional models was obtained from a variety of technical sources including commercial wet milling companies, industry experts and equipment suppliers. Additional information for the present models was obtained from our own experience with the development of the E-milling process and trials in the laboratory and at the pilot plant scale. The models were developed using process and cost simulation software (SuperPro Designer®) and include processing information such as composition and flow rates of the various process streams, descriptions of the various unit operations and detailed breakdowns of the operating and capital cost of the facility. Results Based on the information from the model, we can estimate the cost of production per kilogram of starch using the input prices for corn, enzyme and other wet milling co-products. The work presented here describes the E-milling process and compares the process, the operation and costs with the conventional process. Conclusion The E-milling process was found to be cost competitive with the conventional process during periods of high corn feedstock costs since the enzymatic process enhances the yields of the products in a corn wet milling process. This model is available upon request from the authors for educational, research and non-commercial uses. PMID:19154623
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POLUTE. Forest Air Pollutant Uptake Model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Murphy, C.E. Jr.; Sinclair, T.R.
1992-02-13
POLUTE is a computer model designed to estimate the uptake of air pollutants by forests. The model utilizes submodels to describe atmospheric diffusion immediately above and within the canopy, and into the sink areas within or on the trees. The program implementing the model is general and can be used, with only minor changes, for any gaseous pollutant. The model provides an estimate describing the response of the vegetarian-atmosphere system to the environment as related to three types of processes: atmospheric diffusion, diffusion near and inside the absorbing plant, and the physical and chemical processes at the sink on ormore » within the plant.« less
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Non-invasive monitoring and modelling of the root active zones: progresses, caveats and outlook.
NASA Astrophysics Data System (ADS)
Cassiani, G.; Putti, M.; Boaga, J.; Busato, L.; Vanella, D.; Consoli, S.
2016-12-01
Roots play a fundamental role in soil-plant-atmosphere interactions as they not only control water and nutrient exchanges necessary for plant sustenance, but also largely contribute, through the plant system, to the mass and energy exchanges between soil and atmosphere. Therefore understanding root zone processes is of major importance not only for crop management but also for wider scale catchment and global issues. Geophysical methods can greatly contribute to imaging the root zone geometry and processes, provided that high-resolution, time-lapse measurements are set up, and provided that the survey design takes into due considerations the expected processes to be imaged. In this respect, modelling and monitoring go hand in hand not only a-posteriori to try and interpret the data, but also a-priori in the attempt to optimise monitoring strategies. In this work we present a few case studies concerning root monitoring using ERT with the support of ancillary data of hydrological and physiological nature. Different degrees of integration with modelling will be presented, with the aim of showing how a full Data Assimilation scheme can be built. In addition, the results will help address fundamental questions such as: (a) is root growth controlled by optimality principles under the constraints posed by soil hydraulic and mechanical properties, by water and nutrient availability and by plant competition? (b) is the optimality above also controlling the dynamic processing of root adaptation to changing constraints? (c) to what extent can these processes of soil-plant interaction be monitored in controlled conditions as well as in true-life environments? These questions, and the availability of ever advancing modelling and monitoring capabilities, are likely to develop into a growing and exciting field of research.
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2015-12-01
FINAL REPORT Integrated spatial models of non-native plant invasion, fire risk, and wildlife habitat to support conservation of military and...as reflecting the official policy or position of the Department of Defense. Reference herein to any specific commercial product, process, or service...2. REPORT TYPE Final 3. DATES COVERED (From - To) 26/4/2010 – 25/10/2015 4. TITLE AND SUBTITLE Integrated Spatial Models of Non-Native Plant
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Christopher Litvay; Alan Rudie; Peter Hart
2003-01-01
An Excel spreadsheet developed to solve the ion-exchange equilibrium in wood pulps has been linked by dynamic data exchange to WinGEMS and used to model the non-process elements in the hardwood bleach plant of the Mead/Westvaco Evandale mill. Pulp and filtrate samples were collected from the diffusion washers and final wash press of the bleach plant. A WinGEMS model of...
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INVENTORY ANALYSIS AND COST ACCOUNTING OF FACILITY MAINTANANCE IN WASTE INCINERATION
NASA Astrophysics Data System (ADS)
Morioka, Tohru; Ozaki, Taira; Kitazume, Keiichi; Yamamoto, Tsukasa
A solid waste incineration plant consists of so many facilities and mechanical parts that it requires periodic careful maintenance of them for stable solid waste management. The current research investigates maintenance costs of the stoker type incinerator and continuous firing plants in detail and develops an accounting model for maintenance of them. This model is able to distinguish among the costs of inspection, repair and renewal by plant with seven process flaw s and three common factors. Parameters based on real data collected by questionnaire surveys give appropriate results in comparison with other plants and enable to apply the model to plants which incinerates 500 - 600 ton solid waste per day.
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Are Plant Species Able to Keep Pace with the Rapidly Changing Climate?
Cunze, Sarah; Heydel, Felix; Tackenberg, Oliver
2013-01-01
Future climate change is predicted to advance faster than the postglacial warming. Migration may therefore become a key driver for future development of biodiversity and ecosystem functioning. For 140 European plant species we computed past range shifts since the last glacial maximum and future range shifts for a variety of Intergovernmental Panel on Climate Change (IPCC) scenarios and global circulation models (GCMs). Range shift rates were estimated by means of species distribution modelling (SDM). With process-based seed dispersal models we estimated species-specific migration rates for 27 dispersal modes addressing dispersal by wind (anemochory) for different wind conditions, as well as dispersal by mammals (dispersal on animal's coat – epizoochory and dispersal by animals after feeding and digestion – endozoochory) considering different animal species. Our process-based modelled migration rates generally exceeded the postglacial range shift rates indicating that the process-based models we used are capable of predicting migration rates that are in accordance with realized past migration. For most of the considered species, the modelled migration rates were considerably lower than the expected future climate change induced range shift rates. This implies that most plant species will not entirely be able to follow future climate-change-induced range shifts due to dispersal limitation. Animals with large day- and home-ranges are highly important for achieving high migration rates for many plant species, whereas anemochory is relevant for only few species. PMID:23894290
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Li, Jian; Shi, Raoqiao; Xu, Chuanlong; Wang, Shimin
2018-05-08
The selective catalytic reduction (SCR) system, as one principal flue gas treatment method employed for the NO x emission control of the coal-fired power plant, is nonlinear and time-varying with great inertia and large time delay. It is difficult for the present SCR control system to achieve satisfactory performance with the traditional feedback and feedforward control strategies. Although some improved control strategies, such as the Smith predictor control and the model predictive control, have been proposed for this issue, a well-matched identification model is essentially required to realize a superior control of the SCR system. Industrial field experiment is an alternative way to identify the SCR system model in the coal-fired power plant. But it undesirably disturbs the operation system and is costly in time and manpower. In this paper, a process identification model of the SCR system is proposed and developed by applying the asymptotic method to the sufficiently excited data, selected from the original historical operation database of a 350 MW coal-fired power plant according to the condition number of the Fisher information matrix. Numerical simulations are carried out based on the practical historical operation data to evaluate the performance of the proposed model. Results show that the proposed model can efficiently achieve the process identification of the SCR system.
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NASA Astrophysics Data System (ADS)
Dikmen, Erkan; Ayaz, Mahir; Gül, Doğan; Şahin, Arzu Şencan
2017-07-01
The determination of drying behavior of herbal plants is a complex process. In this study, gene expression programming (GEP) model was used to determine drying behavior of herbal plants as fresh sweet basil, parsley and dill leaves. Time and drying temperatures are input parameters for the estimation of moisture ratio of herbal plants. The results of the GEP model are compared with experimental drying data. The statistical values as mean absolute percentage error, root-mean-squared error and R-square are used to calculate the difference between values predicted by the GEP model and the values actually observed from the experimental study. It was found that the results of the GEP model and experimental study are in moderately well agreement. The results have shown that the GEP model can be considered as an efficient modelling technique for the prediction of moisture ratio of herbal plants.
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Laughlin, D.C.; Abella, S.R.; Covington, W.W.; Grace, J.B.
2007-01-01
Question: How are the effects of mineral soil properties on understory plant species richness propagated through a network of processes involving the forest overstory, soil organic matter, soil nitrogen, and understory plant abundance? Location: North-central Arizona, USA. Methods: We sampled 75 0.05-ha plots across a broad soil gradient in a Pinus ponderosa (ponderosa pine) forest ecosystem. We evaluated multivariate models of plant species richness using structural equation modeling. Results: Richness was highest at intermediate levels of understory plant cover, suggesting that both colonization success and competitive exclusion can limit richness in this system. We did not detect a reciprocal positive effect of richness on plant cover. Richness was strongly related to soil nitrogen in the model, with evidence for both a direct negative effect and an indirect non-linear relationship mediated through understory plant cover. Soil organic matter appeared to have a positive influence on understory richness that was independent of soil nitrogen. Richness was lowest where the forest overstory was densest, which can be explained through indirect effects on soil organic matter, soil nitrogen and understory cover. Finally, model results suggest a variety of direct and indirect processes whereby mineral soil properties can influence richness. Conclusions: Understory plant species richness and plant cover in P. ponderosa forests appear to be significantly influenced by soil organic matter and nitrogen, which are, in turn, related to overstory density and composition and mineral soil properties. Thus, soil properties can impose direct and indirect constraints on local species diversity in ponderosa pine forests. ?? IAVS; Opulus Press.
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NASA Technical Reports Server (NTRS)
Fegley, K. A.; Hayden, J. H.; Rehmann, D. W.
1974-01-01
The feasibility of formulating a methodology for the modeling and analysis of aerospace electrical power processing systems is investigated. It is shown that a digital computer may be used in an interactive mode for the design, modeling, analysis, and comparison of power processing systems.
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High-autonomy control of space resource processing plants
NASA Technical Reports Server (NTRS)
Schooley, Larry C.; Zeigler, Bernard P.; Cellier, Francois E.; Wang, Fei-Yue
1993-01-01
A highly autonomous intelligent command/control architecture has been developed for planetary surface base industrial process plants and Space Station Freedom experimental facilities. The architecture makes use of a high-level task-oriented mode with supervisory control from one or several remote sites, and integrates advanced network communications concepts and state-of-the-art man/machine interfaces with the most advanced autonomous intelligent control. Attention is given to the full-dynamics model of a Martian oxygen-production plant, event-based/fuzzy-logic process control, and fault management practices.
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Modelling the development and arrangement of the primary vascular structure in plants.
Cartenì, Fabrizio; Giannino, Francesco; Schweingruber, Fritz Hans; Mazzoleni, Stefano
2014-09-01
The process of vascular development in plants results in the formation of a specific array of bundles that run throughout the plant in a characteristic spatial arrangement. Although much is known about the genes involved in the specification of procambium, phloem and xylem, the dynamic processes and interactions that define the development of the radial arrangement of such tissues remain elusive. This study presents a spatially explicit reaction-diffusion model defining a set of logical and functional rules to simulate the differentiation of procambium, phloem and xylem and their spatial patterns, starting from a homogeneous group of undifferentiated cells. Simulation results showed that the model is capable of reproducing most vascular patterns observed in plants, from primitive and simple structures made up of a single strand of vascular bundles (protostele), to more complex and evolved structures, with separated vascular bundles arranged in an ordered pattern within the plant section (e.g. eustele). The results presented demonstrate, as a proof of concept, that a common genetic-molecular machinery can be the basis of different spatial patterns of plant vascular development. Moreover, the model has the potential to become a useful tool to test different hypotheses of genetic and molecular interactions involved in the specification of vascular tissues.
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Barillot, Romain; Chambon, Camille; Andrieu, Bruno
2016-01-01
Background and Aims Improving crops requires better linking of traits and metabolic processes to whole plant performance. In this paper, we present CN-Wheat, a comprehensive and mechanistic model of carbon (C) and nitrogen (N) metabolism within wheat culms after anthesis. Methods The culm is described by modules that represent the roots, photosynthetic organs and grains. Each of them includes structural, storage and mobile materials. Fluxes of C and N among modules occur through a common pool and through transpiration flow. Metabolite variations are represented by differential equations that depend on the physiological processes occurring in each module. A challenging aspect of CN-Wheat lies in the regulation of these processes by metabolite concentrations and the environment perceived by organs. Key Results CN-Wheat simulates the distribution of C and N into wheat culms in relation to photosynthesis, N uptake, metabolite turnover, root exudation and tissue death. Regulation of physiological activities by local concentrations of metabolites appears to be a valuable feature for understanding how the behaviour of the whole plant can emerge from local rules. Conclusions The originality of CN-Wheat is that it proposes an integrated view of plant functioning based on a mechanistic approach. The formalization of each process can be further refined in the future as knowledge progresses. This approach is expected to strengthen our capacity to understand plant responses to their environment and investigate plant traits adapted to changes in agronomical practices or environmental conditions. A companion paper will evaluate the model. PMID:27497242
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All is not loss: plant biodiversity in the anthropocene.
Ellis, Erle C; Antill, Erica C; Kreft, Holger
2012-01-01
Anthropogenic global changes in biodiversity are generally portrayed in terms of massive native species losses or invasions caused by recent human disturbance. Yet these biodiversity changes and others caused directly by human populations and their use of land tend to co-occur as long-term biodiversity change processes in the Anthropocene. Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. The patterns thus derived confirm that while native losses are likely significant across at least half of Earth's ice-free land, model predictions indicate that plant species richness has increased overall in most regional landscapes, mostly because species invasions tend to exceed native losses. While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. Effective global stewardship of plant biodiversity in the Anthropocene will require integrated frameworks for observing, modeling and forecasting the different forms of anthropogenic biodiversity change processes at regional landscape scales, towards conserving biodiversity within the novel plant communities created and sustained by human systems.
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All Is Not Loss: Plant Biodiversity in the Anthropocene
Ellis, Erle C.; Antill, Erica C.; Kreft, Holger
2012-01-01
Anthropogenic global changes in biodiversity are generally portrayed in terms of massive native species losses or invasions caused by recent human disturbance. Yet these biodiversity changes and others caused directly by human populations and their use of land tend to co-occur as long-term biodiversity change processes in the Anthropocene. Here we explore contemporary anthropogenic global patterns in vascular plant species richness at regional landscape scales by combining spatially explicit models and estimates for native species loss together with gains in exotics caused by species invasions and the introduction of agricultural domesticates and ornamental exotic plants. The patterns thus derived confirm that while native losses are likely significant across at least half of Earth's ice-free land, model predictions indicate that plant species richness has increased overall in most regional landscapes, mostly because species invasions tend to exceed native losses. While global observing systems and models that integrate anthropogenic species loss, introduction and invasion at regional landscape scales remain at an early stage of development, integrating predictions from existing models within a single assessment confirms their vast global extent and significance while revealing novel patterns and their potential drivers. Effective global stewardship of plant biodiversity in the Anthropocene will require integrated frameworks for observing, modeling and forecasting the different forms of anthropogenic biodiversity change processes at regional landscape scales, towards conserving biodiversity within the novel plant communities created and sustained by human systems. PMID:22272360
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Lichiheb, Nebila; Personne, Erwan; Bedos, Carole; Van den Berg, Frederik; Barriuso, Enrique
2016-04-15
Volatilization from plant foliage is known to have a great contribution to pesticide emission to the atmosphere. However, its estimation is still difficult because of our poor understanding of processes occurring at the leaf surface. A compartmental approach for dissipation processes of pesticides applied on the leaf surface was developed on the base of experimental study performed under controlled conditions using laboratory volatilization chamber. This approach was combined with physicochemical properties of pesticides and was implemented in SURFATM-Pesticides model in order to predict pesticide volatilization from plants in a more mechanistic way. The new version of SURFATM-Pesticide model takes into account the effect of formulation on volatilization and leaf penetration. The model was evaluated in terms of 3 pesticides applied on plants at the field scale (chlorothalonil, fenpropidin and parathion) which display a wide range of volatilization rates. The comparison of modeled volatilization fluxes with measured ones shows an overall good agreement for the three tested compounds. Furthermore the model confirms the considerable effect of the formulation on the rate of the decline in volatilization fluxes especially for systemic products. However, due to the lack of published information on the substances in the formulations, factors accounting for the effect of formulation are described empirically. A sensitivity analysis shows that in addition to vapor pressure, the octanol-water partition coefficient represents important physicochemical properties of pesticides affecting pesticide volatilization from plants. Finally the new version of SURFATM-Pesticides is a prospecting tool for key processes involved in the description of pesticide volatilization from plants. Copyright © 2016 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Rusu-Anghel, S.
2017-01-01
Analytical modeling of the flow of manufacturing process of the cement is difficult because of their complexity and has not resulted in sufficiently precise mathematical models. In this paper, based on a statistical model of the process and using the knowledge of human experts, was designed a fuzzy system for automatic control of clinkering process.
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How does pedogenesis drive plant diversity?
Laliberté, Etienne; Grace, James B; Huston, Michael A; Lambers, Hans; Teste, François P; Turner, Benjamin L; Wardle, David A
2013-06-01
Some of the most species-rich plant communities occur on ancient, strongly weathered soils, whereas those on recently developed soils tend to be less diverse. Mechanisms underlying this well-known pattern, however, remain unresolved. Here, we present a conceptual model describing alternative mechanisms by which pedogenesis (the process of soil formation) might drive plant diversity. We suggest that long-term soil chronosequences offer great, yet largely untapped, potential as 'natural experiments' to determine edaphic controls over plant diversity. Finally, we discuss how our conceptual model can be evaluated quantitatively using structural equation modeling to advance multivariate theories about the determinants of local plant diversity. This should help us to understand broader-scale diversity patterns, such as the latitudinal gradient of plant diversity. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Pueyo, Y; Kéfi, S; Díaz-Sierra, R; Alados, C L; Rietkerk, M
2010-12-01
The dynamics of semi-arid plant communities are determined by the interplay between competition and facilitation among plants. The sign and strength of these biotic interactions depend on plant traits. However, the relationships between plant traits and biotic interactions, and the consequences for plant communities are still poorly understood. Our objective here was to investigate, with a modelling approach, the role of plant reproductive traits on biotic interactions, and the consequences for processes such as plant succession and invasion. The dynamics of two plant types were modelled with a spatially-explicit integrodifferential model: (1) a plant with seed dispersal (colonizer of bare soil) and (2) a plant with local vegetative propagation (local competitor). Both plant types were involved in facilitation due to a local positive feedback between vegetation biomass and soil water availability, which promoted establishment and growth. Plants in the system also competed for limited water. The efficiency in water acquisition (dependent on reproductive and growth plant traits) determined which plant type dominated the community at the steady state. Facilitative interactions between plant types also played an important role in the community dynamics, promoting establishment in the driest conditions and recovery from low biomass. Plants with vegetative propagation took advantage of the ability of seed dispersers to establish on bare soil from a low initial biomass. Seed dispersers were good invaders, maintained high biomass at intermediate and high rainfall and showed a high ability in taking profit from the positive feedback originated by plants with vegetative propagation under the driest conditions. However, seed dispersers lost competitiveness with an increasing investment in fecundity. All together, our results showed that reproductive plant traits can affect the balance between facilitative and competitive interactions. Understanding this effect of plant traits on biotic interactions provides insights in processes such as plant succession and shrub encroachment. Copyright © 2010 Elsevier Inc. All rights reserved.
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Simplifiying global biogeochemistry models to evaluate methane emissions
NASA Astrophysics Data System (ADS)
Gerber, S.; Alonso-Contes, C.
2017-12-01
Process-based models are important tools to quantify wetland methane emissions, particularly also under climate change scenarios, evaluating these models is often cumbersome as they are embedded in larger land-surface models where fluctuating water table and the carbon cycle (including new readily decomposable plant material) are predicted variables. Here, we build on these large scale models but instead of modeling water table and plant productivity we provide values as boundary conditions. In contrast, aerobic and anaerobic decomposition, as well as soil column transport of oxygen and methane are predicted by the model. Because of these simplifications, the model has the potential to be more readily adaptable to the analysis of field-scale data. Here we determine the sensitivity of the model to specific setups, parameter choices, and to boundary conditions in order to determine set-up needs and inform what critical auxiliary variables need to be measured in order to better predict field-scale methane emissions from wetland soils. To that end we performed a global sensitivity analysis that also considers non-linear interactions between processes. The global sensitivity analysis revealed, not surprisingly, that water table dynamics (both mean level and amplitude of fluctuations), and the rate of the carbon cycle (i.e. net primary productivity) are critical determinants of methane emissions. The depth-scale where most of the potential decomposition occurs also affects methane emissions. Different transport mechanisms are compensating each other to some degree: If plant conduits are constrained, methane emissions by diffusive flux and ebullition compensate to some degree, however annual emissions are higher when plants help to bypass methanotrophs in temporally unsaturated upper layers. Finally, while oxygen consumption by plant roots help creating anoxic conditions it has little effect on overall methane emission. Our initial sensitivity analysis helps guiding further model development and improvement. However, an important goal for our model is to use it in field settings as a tool to deconvolve the different processes that contribute to the net transfer of methane from soils to atmosphere.
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NASA Astrophysics Data System (ADS)
Luo, Keqin
1999-11-01
The electroplating industry of over 10,000 planting plants nationwide is one of the major waste generators in the industry. Large quantities of wastewater, spent solvents, spent process solutions, and sludge are the major wastes generated daily in plants, which costs the industry tremendously for waste treatment and disposal and hinders the further development of the industry. It becomes, therefore, an urgent need for the industry to identify technically most effective and economically most attractive methodologies and technologies to minimize the waste, while the production competitiveness can be still maintained. This dissertation aims at developing a novel WM methodology using artificial intelligence, fuzzy logic, and fundamental knowledge in chemical engineering, and an intelligent decision support tool. The WM methodology consists of two parts: the heuristic knowledge-based qualitative WM decision analysis and support methodology and fundamental knowledge-based quantitative process analysis methodology for waste reduction. In the former, a large number of WM strategies are represented as fuzzy rules. This becomes the main part of the knowledge base in the decision support tool, WMEP-Advisor. In the latter, various first-principles-based process dynamic models are developed. These models can characterize all three major types of operations in an electroplating plant, i.e., cleaning, rinsing, and plating. This development allows us to perform a thorough process analysis on bath efficiency, chemical consumption, wastewater generation, sludge generation, etc. Additional models are developed for quantifying drag-out and evaporation that are critical for waste reduction. The models are validated through numerous industrial experiments in a typical plating line of an industrial partner. The unique contribution of this research is that it is the first time for the electroplating industry to (i) use systematically available WM strategies, (ii) know quantitatively and accurately what is going on in each tank, and (iii) identify all WM opportunities through process improvement. This work has formed a solid foundation for the further development of powerful WM technologies for comprehensive WM in the following decade.
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Bell, Michael W; Tang, Y Sim; Dragosits, Ulrike; Flechard, Chris R; Ward, Paul; Braban, Christine F
2016-10-01
Anaerobic digestion (AD) is becoming increasingly implemented within organic waste treatment operations. The storage and processing of large volumes of organic wastes through AD has been identified as a significant source of ammonia (NH3) emissions, however the totality of ammonia emissions from an AD plant have not been previously quantified. The emissions from an AD plant processing food waste were estimated through integrating ambient NH3 concentration measurements, atmospheric dispersion modelling, and comparison with published emission factors (EFs). Two dispersion models (ADMS and a backwards Lagrangian stochastic (bLS) model) were applied to calculate emission estimates. The bLS model (WindTrax) was used to back-calculate a total (top-down) emission rate for the AD plant from a point of continuous NH3 measurement downwind from the plant. The back-calculated emission rates were then input to the ADMS forward dispersion model to make predictions of air NH3 concentrations around the site, and evaluated against weekly passive sampler NH3 measurements. As an alternative approach emission rates from individual sources within the plant were initially estimated by applying literature EFs to the available site parameters concerning the chemical composition of waste materials, room air concentrations, ventilation rates, etc. The individual emission rates were input to ADMS and later tuned by fitting the simulated ambient concentrations to the observed (passive sampler) concentration field, which gave an excellent match to measurements after an iterative process. The total emission from the AD plant thus estimated by a bottom-up approach was 16.8±1.8mgs(-1), which was significantly higher than the back-calculated top-down estimate (7.4±0.78mgs(-1)). The bottom-up approach offered a more realistic treatment of the source distribution within the plant area, while the complexity of the site was not ideally suited to the bLS method, thus the bottom-up method is believed to give a better estimate of emissions. The storage of solid digestate and the aerobic treatment of liquid effluents at the site were the greatest sources of NH3 emissions. Copyright © 2016 Elsevier Ltd. All rights reserved.
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NASA Astrophysics Data System (ADS)
Bouda, Martin; Saiers, James E.
2017-12-01
Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, descriptions of RSA have not been included because of their three-dimensional complexity, which makes them generally too computationally costly. Here we demonstrate a new, process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA under different soil moisture conditions: the RSA stencil. Using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, we show that the RSA stencil predicts plant water potentials within 2% to the outputs of a full 3D model, under the same assumptions on soil moisture heterogeneity, despite its trivial computational cost, resulting in improved predictions of water uptake and soil moisture compared to a model without RSA in a transient simulation. Our results suggest that LSM predictions of soil moisture dynamics and dependent variables can be improved by the implementation of this model, calibrated for individual PFTs using field observations.
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Dissecting a new connection between cytokinin and jasmonic acid in control of leaf growth
USDA-ARS?s Scientific Manuscript database
Plant growth is mediated by two cellular processes: division and elongation. The maize leaf is an excellent model to study plant growth since these processes are spatially separated into discreet zones - a division zone (DZ), transition zone (TZ), and elongation zone (EZ) - at the base of the leaf. ...
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Yamaura, Yuichi; Connor, Edward F; Royle, J Andrew; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio
2016-07-01
Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.
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Yamaura, Yuichi; Connor, Edward F.; Royle, Andy; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio
2016-01-01
Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.
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POLUTE; forest air pollutant uptake model. [IBM360,370; CSMP
DOE Office of Scientific and Technical Information (OSTI.GOV)
Murphy, C.E.
POLUTE is a computer model designed to estimate the uptake of air pollutants by forests. The model utilizes submodels to describe atmospheric diffusion immediately above and within the canopy, and into the sink areas within or on the trees. The program implementing the model is general and can be used, with only minor changes, for any gaseous pollutant. The model provides an estimate describing the response of the vegetarian-atmosphere system to the environment as related to three types of processes: atmospheric diffusion, diffusion near and inside the absorbing plant, and the physical and chemical processes at the sink on ormore » within the plant.IBM360,370; CSMP; OS/370.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Sandborn, R.H.
1976-01-01
M0200, a computer simulation model, was used to investigate the safeguarding of plutonium dioxide. The computer program operating the model was constructed so that replicate runs could provide data for statistical analysis of the distributions of the randomized variables. The plant model was divided into material balance areas associated with definable unit processes. Indicators of plant operations studied were modified end-of-shift material balances, end-of-blend errors formed by closing material balances between blends, and cumulative sums of the differences between actual and expected performances. (auth)
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Eco-Evo PVAs: Incorporating Eco-Evolutionary Processes into Population Viability Models
We synthesize how advances in computational methods and population genomics can be combined within an Ecological-Evolutionary (Eco-Evo) PVA model. Eco-Evo PVA models are powerful new tools for understanding the influence of evolutionary processes on plant and animal population pe...
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Soft Sensors: Chemoinformatic Model for Efficient Control and Operation in Chemical Plants.
Funatsu, Kimito
2016-12-01
Soft sensor is statistical model as an essential tool for controlling pharmaceutical, chemical and industrial plants. I introduce soft sensor, the roles, the applications, the problems and the research examples such as adaptive soft sensor, database monitoring and efficient process control. The use of soft sensor enables chemical industrial plants to be operated more effectively and stably. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Steele, Muriel M; Anctil, Annick; Ladner, David A
2014-05-01
Algaculture has the potential to be a sustainable option for nutrient removal at wastewater treatment plants. The purpose of this study was to compare the environmental impacts of three likely algaculture integration strategies to a conventional nutrient removal strategy. Process modeling was used to determine life cycle inventory data and a comparative life cycle assessment was used to determine environmental impacts. Treatment scenarios included a base case treatment plant without nutrient removal, a plant with conventional nutrient removal, and three other cases with algal unit processes placed at the head of the plant, in a side stream, and at the end of the plant, respectively. Impact categories included eutrophication, global warming, ecotoxicity, and primary energy demand. Integrating algaculture prior to activated sludge proved to be most beneficial of the scenarios considered for all impact categories; however, this scenario would also require primary sedimentation and impacts of that unit process should be considered for implementation of such a system.
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Bertheloot, Jessica; Cournède, Paul-Henry; Andrieu, Bruno
2011-10-01
Models simulating nitrogen use by plants are potentially efficient tools to optimize the use of fertilizers in agriculture. Most crop models assume that a target nitrogen concentration can be defined for plant tissues and formalize a demand for nitrogen, depending on the difference between the target and actual nitrogen concentrations. However, the teleonomic nature of the approach has been criticized. This paper proposes a mechanistic model of nitrogen economy, NEMA (Nitrogen Economy Model within plant Architecture), which links nitrogen fluxes to nitrogen concentration and physiological processes. A functional-structural approach is used: plant aerial parts are described in a botanically realistic way and physiological processes are expressed at the scale of each aerial organ or root compartment as a function of local conditions (light and resources). NEMA was developed for winter wheat (Triticum aestivum) after flowering. The model simulates the nitrogen (N) content of each photosynthetic organ as regulated by Rubisco turnover, which depends on intercepted light and a mobile N pool shared by all organs. This pool is enriched by N acquisition from the soil and N release from vegetative organs, and is depleted by grain uptake and protein synthesis in vegetative organs; NEMA accounts for the negative feedback from circulating N on N acquisition from the soil, which is supposed to follow the activities of nitrate transport systems. Organ N content and intercepted light determine dry matter production via photosynthesis, which is distributed between organs according to a demand-driven approach. NEMA integrates the main feedbacks known to regulate plant N economy. Other novel features are the simulation of N for all photosynthetic tissues and the use of an explicit description of the plant that allows how the local environment of tissues regulates their N content to be taken into account. We believe this represents an appropriate frame for modelling nitrogen in functional-structural plant models. A companion paper will present model evaluation and analysis.
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NASA Astrophysics Data System (ADS)
Renny; Supriyanto
2018-04-01
Nutrition is the chemical compounds that needed by the organism for the growth process. In plants, nutrients are organic or inorganic compounds that are absorbed from the roots of the soil. It consist of macro and micro nutrient. Macro nutrients are nutrition that needed by plants in large quantities, such as, nitrogen, calcium, pottacium, magnesium, and sulfur. The total soil nutrient is the difference between the input nutrient and the output nutrients. Input nutrients are nutrient that derived from the decomposition of organic substances. Meanwhile, the output nutrient consists of the nutrients that absorbed by plant roots (uptake), the evaporated nutrients (volatilized) and leached nutrients. The nutrient transport can be done through diffusion process. The diffusion process is essential in removing the nutrient from one place to the root surface. It will cause the rate of absorption of nutrient by the roots will be greater. Nutrient concept in paddy filed can be represented into a mathematical modelling, by making compartment models. The rate of concentration change in the compartment model forms a system of homogeneous linear differential equations. In this research, we will use Laplaces transformation to solve the compartment model and determined the dynamics of macro nutrition due to diffusion process.
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NASA Astrophysics Data System (ADS)
Saaltink, Rémon; Dekker, Stefan C.; Griffioen, Jasper; Wassen, Martin J.
2016-09-01
Interest is growing in using soft sediment as a foundation in eco-engineering projects. Wetland construction in the Dutch lake Markermeer is an example: here, dredging some of the clay-rich lake-bed sediment and using it to construct wetland will soon begin. Natural processes will be utilized during and after construction to accelerate ecosystem development. Knowing that plants can eco-engineer their environment via positive or negative biogeochemical plant-soil feedbacks, we conducted a 6-month greenhouse experiment to identify the key biogeochemical processes in the mud when Phragmites australis is used as an eco-engineering species. We applied inverse biogeochemical modeling to link observed changes in pore water composition to biogeochemical processes. Two months after transplantation we observed reduced plant growth and shriveling and yellowing of foliage. The N : P ratios of the plant tissue were low, and these were affected not by hampered uptake of N but by enhanced uptake of P. Subsequent analyses revealed high Fe concentrations in the leaves and roots. Sulfate concentrations rose drastically in our experiment due to pyrite oxidation; as reduction of sulfate will decouple Fe-P in reducing conditions, we argue that plant-induced iron toxicity hampered plant growth, forming a negative feedback loop, while simultaneously there was a positive feedback loop, as iron toxicity promotes P mobilization as a result of reduced conditions through root death, thereby stimulating plant growth and regeneration. Given these two feedback mechanisms, we propose the use of Fe-tolerant species rather than species that thrive in N-limited conditions. The results presented in this study demonstrate the importance of studying the biogeochemical properties of the situated sediment and the feedback mechanisms between plant and soil prior to finalizing the design of the eco-engineering project.
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Wang, Gang; Yuan, Jianli; Wang, Xizhi; Xiao, Sa; Huang, Wenbing
2004-11-01
Taking into account the individual growth form (allometry) in a plant population and the effects of intraspecific competition on allometry under the population self-thinning condition, and adopting Ogawa's allometric equation 1/y = 1/axb + 1/c as the expression of complex allometry, the generalized model describing the change mode of r (the self-thinning exponential in the self-thinning equation, log M = K + log N, where M is mean plant mass, K is constant, and N is population density) was constructed. Meanwhile, with reference to the changing process of population density to survival curve type B, the exponential, r, was calculated using the software MATHEMATICA 4.0. The results of the numerical simulation show that (1) the value of the self-thinning exponential, r, is mainly determined by allometric parameters; it is most sensitive to change of b of the three allometric parameters, and a and c take second place; (2) the exponential, r, changes continuously from about -3 to the asymptote -1; the slope of -3/2 is a transient value in the population self-thinning process; (3) it is not a 'law' that the slope of the self-thinning trajectory equals or approaches -3/2, and the long-running dispute in ecological research over whether or not the exponential, r, equals -3/2 is meaningless. So future studies on the plant self-thinning process should focus on investigating how plant neighbor competition affects the phenotypic plasticity of plant individuals, what the relationship between the allometry mode and the self-thinning trajectory of plant population is and, in the light of evolution, how plants have adapted to competition pressure by plastic individual growth.
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Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant
Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa
2013-09-17
System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.
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Pallas, Benoît; Clément-Vidal, Anne; Rebolledo, Maria-Camila; Soulié, Jean-Christophe; Luquet, Delphine
2013-01-01
The ability to assimilate C and allocate non-structural carbohydrates (NSCs) to the most appropriate organs is crucial to maximize plant ecological or agronomic performance. Such C source and sink activities are differentially affected by environmental constraints. Under drought, plant growth is generally more sink than source limited as organ expansion or appearance rate is earlier and stronger affected than C assimilation. This favors plant survival and recovery but not always agronomic performance as NSC are stored rather than used for growth due to a modified metabolism in source and sink leaves. Such interactions between plant C and water balance are complex and plant modeling can help analyzing their impact on plant phenotype. This paper addresses the impact of trade-offs between C sink and source activities and plant production under drought, combining experimental and modeling approaches. Two contrasted monocotyledonous species (rice, oil palm) were studied. Experimentally, the sink limitation of plant growth under moderate drought was confirmed as well as the modifications in NSC metabolism in source and sink organs. Under severe stress, when C source became limiting, plant NSC concentration decreased. Two plant models dedicated to oil palm and rice morphogenesis were used to perform a sensitivity analysis and further explore how to optimize C sink and source drought sensitivity to maximize plant growth. Modeling results highlighted that optimal drought sensitivity depends both on drought type and species and that modeling is a great opportunity to analyze such complex processes. Further modeling needs and more generally the challenge of using models to support complex trait breeding are discussed. PMID:24204372
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Rooting Theories of Plant Community Ecology in Microbial Interactions
Bever, James D.; Dickie, Ian A.; Facelli, Evelina; Facelli, Jose M.; Klironomos, John; Moora, Mari; Rillig, Matthias C.; Stock, William D.; Tibbett, Mark; Zobel, Martin
2010-01-01
Predominant frameworks for understanding plant ecology have an aboveground bias that neglects soil micro-organisms. This is inconsistent with recent work illustrating the importance of soil microbes in terrestrial ecology. Microbial effects have been incorporated into plant community dynamics using ideas of niche modification and plant-soil community feedbacks. Here, we expand and integrate qualitative conceptual models of plant niche and feedback to explore implications of microbial interactions for understanding plant community ecology. At the same time we review the empirical evidence for these processes. We also consider common mycorrhizal networks, and suggest these are best interpreted within the feedback framework. Finally, we apply our integrated model of niche and feedback to understanding plant coexistence, monodominance, and invasion ecology. PMID:20557974
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Dynamics of buckbrush populations under simulated forest restoration alternatives
David W. Huffman; Margaret M. Moore
2008-01-01
Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...
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Dynamics of buckbrush populations under simulated forest restoration alternatives (P-53)
David W. Huffman; Margaret M. Moore
2008-01-01
Plant population models are valuable tools for assessing ecological tradeoffs between forest management approaches. In addition, these models can provide insight on plant life history patterns and processes important for persistence and recovery of populations in changing environments. In this study, we evaluated a set of ecological restoration alternatives for their...
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NASA Astrophysics Data System (ADS)
Al-Talibi, A. Adhim
An estimated 4% of national energy consumption is used for drinking water and wastewater services. Despite the awareness and optimization initiatives for energy conservation, energy consumption is on the rise owing to population and urbanization expansion and to commercial and industrial business advancement. The principal concern is since energy consumption grows, the higher will be the energy production demand, leading to an increase in CO2 footprints and the contribution to global warming potential. This research is in the area of energy-water nexus, focusing on wastewater treatment plant (WWTP) energy trilogy -- the group of three related entities, which includes processes: (1) consuming energy, (2) producing energy, and (3) the resulting -- CO2 equivalents. Detailed and measurable energy information is not readily obtained for wastewater facilities, specifically during facility preliminary design phases. These limitations call for data-intensive research approach on GHG emissions quantification, plant efficiencies and source reduction techniques. To achieve these goals, this research introduced a model integrating all plant processes and their pertinent energy sources. In a comprehensive and "Energy Source-to-Effluent Discharge" pattern, this model is capable of bridging the gaps of WWTP energy, facilitating plant designers' decision-making for meeting energy assessment, sustainability and the environmental regulatory compliance. Protocols for estimating common emissions sources are available such as for fuels, whereas, site-specific emissions for other sources have to be developed and are captured in this research. The dissertation objectives were met through an extensive study of the relevant literature, models and tools, originating comprehensive lists of processes and energy sources for WWTPs, locating estimation formulas for each source, identifying site specific emissions factors, and linking the sources in a mathematical model for site specific CO2 e determination. The model was verified and showed a good agreement with billed and measured data from a base case study. In a next phase, a supplemental computational tool can be created for conducting plant energy design comparisons and plant energy and emissions parameters assessments. The main conclusions drawn from this research is that current approaches are severely limited, not covering plant's design phase and not fully considering the balance of energy consumed (EC), energy produced (EP) and the resulting CO2 e emission integration. Finally their results are not representative. This makes reported governmental and institutional national energy consumption figures incomplete and/or misleading, since they are mainly considering energy consumptions from electricity and some fuels or certain processes only. The distinction of the energy trilogy model over existing approaches is based on the following: (1) the ET energy model is unprecedented, prepared to fit WWTP energy assessment during the design and rehabilitation phases, (2) links the energy trilogy eliminating the need for using several models or tools, (3) removes the need for on-site expensive energy measurements or audits, (4) offers alternatives for energy optimization during plant's life-cycle, and (5) ensures reliable GHG emissions inventory reporting for permitting and regulatory compliance.
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NASA Astrophysics Data System (ADS)
Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons
2017-06-01
At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.
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Representing Plant Hydraulics in a Global Model: Updates to the Community Land Model
NASA Astrophysics Data System (ADS)
Kennedy, D.; Swenson, S. C.; Oleson, K. W.; Lawrence, D. M.; Fisher, R.; Gentine, P.
2017-12-01
In previous versions, the Community Land Model has used soil moisture to stand in for plant water status, with transpiration and photosynthesis driven directly by soil water potential. This eschews significant literature demonstrating the importance of plant hydraulic traits in the dynamics of water flow through the soil-plant-atmosphere continuum and in the regulation of stomatal aperture. In this study we install a simplified hydraulic framework to represent vegetation water potential and to regulate root water uptake and turbulent fluxes. Plant hydraulics allow for a more explicit representation of plant water status, which improves the physical basis for many processes represented in CLM. This includes root water uptake and the attenuation of photosynthesis and transpiration with drought. Model description is accompanied by results from a point simulation based at the Caxiuanã flux tower site in Eastern Amazonia, covering a throughfall exclusion experiment from 2001-2003. Including plant hydraulics improves the response to drought forcing compared to previous versions of CLM. Parameter sensitivity is examined at the same site and presented in the context of estimating hydraulic parameters in a global model.
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Revisiting the Holy Grail: using plant functional traits to understand ecological processes.
Funk, Jennifer L; Larson, Julie E; Ames, Gregory M; Butterfield, Bradley J; Cavender-Bares, Jeannine; Firn, Jennifer; Laughlin, Daniel C; Sutton-Grier, Ariana E; Williams, Laura; Wright, Justin
2017-05-01
One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a 'Holy Grail' in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community- and ecosystem-level processes. Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait-based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta-analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized. © 2016 Cambridge Philosophical Society.
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Modelling virus- and host-limitation in vectored plant disease epidemics.
Jeger, M J; van den Bosch, F; Madden, L V
2011-08-01
Models of plant virus epidemics have received less attention than those caused by fungal pathogens. Intuitively, the fact that virus diseases are systemic means that the individual diseased plant can be considered as the population unit which simplifies modelling. However, the fact that a vector is required in the vast majority of cases for virus transmission, means that explicit consideration must be taken of the vector, or, the involvement of the vector in the transmission process must be considered implicitly. In the latter case it is also important that within-plant processes, such as virus multiplication and systemic movement, are taken into account. In this paper we propose an approach based on the linking of transmission at the population level with virus multiplication within plants. The resulting models are parameter-sparse and hence simplistic. However, the range of model outcomes is representative of field observations relating to the apparent limitation of epidemic development in populations of healthy susceptible plants. We propose that epidemic development can be constrained by virus limitation in the early stages of an epidemic when the availability of healthy susceptible hosts is not limiting. There is an inverse relationship between levels of transmission in the population and the mean virus titre/infected plant. In the case of competition between viruses, both virus and host limitation are likely to be important in determining whether one virus can displace another or whether both viruses can co-exist in a plant population. Lotka-Volterra type equations are derived to describe density-dependent competition between two viruses multiplying within plants, embedded within a population level epidemiological model. Explicit expressions determining displacement or co-existence of the viruses are obtained. Unlike the classical Lotka-Volterra competition equations, the co-existence requirement for the competition coefficients to be both less than 1 can be relaxed. Copyright © 2011 Elsevier B.V. All rights reserved.
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The next generation of training for Arabidopsis researchers: bioinformatics and quantitative biology
USDA-ARS?s Scientific Manuscript database
It has been more than 50 years since Arabidopsis (Arabidopsis thaliana) was first introduced as a model organism to understand basic processes in plant biology. A well-organized scientific community has used this small reference plant species to make numerous fundamental plant biology discoveries (P...
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Estimating plant available water for general crop simulations in ALMANAC/APEX/EPIC/SWAT
USDA-ARS?s Scientific Manuscript database
Process-based simulation models ALMANAC/APEX/EPIC/SWAT contain generalized plant growth subroutines to predict biomass and crop yield. Environmental constraints typically restrict plant growth and yield. Water stress is often an important limiting factor; it is calculated as the sum of water use f...
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Global sensitivity analysis of DRAINMOD-FOREST, an integrated forest ecosystem model
Shiying Tian; Mohamed A. Youssef; Devendra M. Amatya; Eric D. Vance
2014-01-01
Global sensitivity analysis is a useful tool to understand process-based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD-FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The...
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Palma, José M; Ruiz, Carmelo; Corpas, Francisco J
2018-01-01
Nitric oxide (NO) is involved many physiological plant processes, including germination, growth and development of roots, flower setting and development, senescence, and fruit ripening. In the latter physiological process, NO has been reported to play an opposite role to ethylene. Thus, treatment of fruits with NO may lead to delay ripening independently of whether they are climacteric or nonclimacteric. In many cases different methods have been reported to apply NO to plant systems involving sodium nitroprusside, NONOates, DETANO, or GSNO to investigate physiological and molecular consequences. In this chapter a method to treat plant materials with NO is provided using bell pepper fruits as a model. This method is cheap, free of side effects, and easy to apply since it only requires common chemicals and tools available in any biology laboratory.
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Simulation of process identification and controller tuning for flow control system
NASA Astrophysics Data System (ADS)
Chew, I. M.; Wong, F.; Bono, A.; Wong, K. I.
2017-06-01
PID controller is undeniably the most popular method used in controlling various industrial processes. The feature to tune the three elements in PID has allowed the controller to deal with specific needs of the industrial processes. This paper discusses the three elements of control actions and improving robustness of controllers through combination of these control actions in various forms. A plant model is simulated using the Process Control Simulator in order to evaluate the controller performance. At first, the open loop response of the plant is studied by applying a step input to the plant and collecting the output data from the plant. Then, FOPDT of physical model is formed by using both Matlab-Simulink and PRC method. Then, calculation of controller’s setting is performed to find the values of Kc and τi that will give satisfactory control in closed loop system. Then, the performance analysis of closed loop system is obtained by set point tracking analysis and disturbance rejection performance. To optimize the overall physical system performance, a refined tuning of PID or detuning is further conducted to ensure a consistent resultant output of closed loop system reaction to the set point changes and disturbances to the physical model. As a result, the PB = 100 (%) and τi = 2.0 (s) is preferably chosen for setpoint tracking while PB = 100 (%) and τi = 2.5 (s) is selected for rejecting the imposed disturbance to the model. In a nutshell, selecting correlation tuning values is likewise depended on the required control’s objective for the stability performance of overall physical model.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Bidica, N.; Stefanescu, I.; Cristescu, I.
2008-07-15
In this paper we present a methodology for determination of tritium inventory in a tritium removal facility. The method proposed is based on the developing of computing models for accountancy of the mobile tritium inventory in the separation processes, of the stored tritium and of the trapped tritium inventory in the structure of the process system components. The configuration of the detritiation process is a combination of isotope catalytic exchange between water and hydrogen (LPCE) and the cryogenic distillation of hydrogen isotopes (CD). The computing model for tritium inventory in the LPCE process and the CD process will be developedmore » basing on mass transfer coefficients in catalytic isotope exchange reactions and in dual-phase system (liquid-vapour) of hydrogen isotopes distillation process. Accounting of tritium inventory stored in metallic hydride will be based on in-bed calorimetry. Estimation of the trapped tritium inventory can be made by subtraction of the mobile and stored tritium inventories from the global tritium inventory of the plant area. Determinations of the global tritium inventory of the plant area will be made on a regular basis by measuring any tritium quantity entering or leaving the plant area. This methodology is intended to be applied to the Heavy Water Detritiation Pilot Plant from ICIT Rm. Valcea (Romania) and to the Cernavoda Tritium Removal Facility (which will be built in the next 5-7 years). (authors)« less
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NASA Astrophysics Data System (ADS)
Manners, R.; Wilcox, A. C.; Merritt, D. M.
2016-12-01
The ecogeomorphic response of riparian ecosystems to a change in hydrologic properties is difficult to predict because of the interactions and feedbacks among plants, water, and sediment. Most riparian models of community dynamics assume a static channel, yet geomorphic processes strongly control the establishment and survival of riparian vegetation. Using a combination of approaches that includes empirical relationships and hydrodynamic models, we model the coupled vegetation-topographic response of three cross-sections on the Yampa and Green Rivers in Dinosaur National Monument, to a shift in the flow regime. The locations represent the variable geomorphology and vegetation composition of these canyon-bound rivers. We account for the inundation and hydraulic properties of vegetation plots surveyed over three years within International River Interface Cooperative (iRIC) Fastmech, equipped with a vegetation module that accounts for flexible stems and plant reconfiguration. The presence of functional groupings of plants, or those plants that respond similarly to environmental factors such as water availability and disturbance are determined from flow response curves developed for the Yampa River. Using field measurements of vegetation morphology, distance from the channel centerline, and dominant particle size and modeled inundation properties we develop an empirical relationship between these variables and topographic change. We evaluate vegetation and channel form changes over decadal timescales, allowing for the integration of processes over time. From our analyses, we identify thresholds in the flow regime that alter the distribution of plants and reduce geomorphic complexity, predominately through side-channel and backwater infilling. Simplification of some processes (e.g., empirically-derived sedimentation) and detailed treatment of others (e.g., plant-flow interactions) allows us to model the coupled dynamics of riparian ecosystems and evaluate the impact of small to large shifts in the flow regime. This approach will be useful to river managers and scientists, as they try to understand the potential changes to riparian ecosystems with uncertain changes to hydrologic regimes as a result of a changing climate and human demands.
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Meyer, Katja; Koester, Tino; Staiger, Dorothee
2015-01-01
Alternative pre-messenger RNA splicing in higher plants emerges as an important layer of regulation upon exposure to exogenous and endogenous cues. Accordingly, mutants defective in RNA-binding proteins predicted to function in the splicing process show severe phenotypic alterations. Among those are developmental defects, impaired responses to pathogen threat or abiotic stress factors, and misregulation of the circadian timing system. A suite of splicing factors has been identified in the model plant Arabidopsis thaliana. Here we summarize recent insights on how defects in these splicing factors impair plant performance. PMID:26213982
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Provost, G.; Stone, H.; McClintock, M.
2008-01-01
To meet the growing demand for education and experience with the analysis, operation, and control of commercial-scale Integrated Gasification Combined Cycle (IGCC) plants, the Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) is leading a collaborative R&D project with participants from government, academia, and industry. One of the goals of this project is to develop a generic, full-scope, real-time generic IGCC dynamic plant simulator for use in establishing a world-class research and training center, as well as to promote and demonstrate the technology to power industry personnel. The NETL IGCC dynamic plant simulator will combine for the first timemore » a process/gasification simulator and a power/combined-cycle simulator together in a single dynamic simulation framework for use in training applications as well as engineering studies. As envisioned, the simulator will have the following features and capabilities: A high-fidelity, real-time, dynamic model of process-side (gasification and gas cleaning with CO2 capture) and power-block-side (combined cycle) for a generic IGCC plant fueled by coal and/or petroleum coke Full-scope training simulator capabilities including startup, shutdown, load following and shedding, response to fuel and ambient condition variations, control strategy analysis (turbine vs. gasifier lead, etc.), representative malfunctions/trips, alarms, scenarios, trending, snapshots, data historian, and trainee performance monitoring The ability to enhance and modify the plant model to facilitate studies of changes in plant configuration and equipment and to support future R&D efforts To support this effort, process descriptions and control strategies were developed for key sections of the plant as part of the detailed functional specification, which will form the basis of the simulator development. These plant sections include: Slurry Preparation Air Separation Unit Gasifiers Syngas Scrubbers Shift Reactors Gas Cooling, Medium Pressure (MP) and Low Pressure (LP) Steam Generation, and Knockout Sour Water Stripper Mercury Removal Selexol™ Acid Gas Removal System CO2 Compression Syngas Reheat and Expansion Claus Plant Hydrogenation Reactor and Gas Cooler Combustion Turbine (CT)-Generator Assemblies Heat Recovery Steam Generators (HRSGs) and Steam Turbine (ST)-Generator In this paper, process descriptions, control strategies, and Process & Instrumentation Diagram (P&ID) drawings for key sections of the generic IGCC plant are presented, along with discussions of some of the operating procedures and representative faults that the simulator will cover. Some of the intended future applications for the simulator are discussed, including plant operation and control demonstrations as well as education and training services such as IGCC familiarization courses.« less
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Reduced order model based on principal component analysis for process simulation and optimization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lang, Y.; Malacina, A.; Biegler, L.
2009-01-01
It is well-known that distributed parameter computational fluid dynamics (CFD) models provide more accurate results than conventional, lumped-parameter unit operation models used in process simulation. Consequently, the use of CFD models in process/equipment co-simulation offers the potential to optimize overall plant performance with respect to complex thermal and fluid flow phenomena. Because solving CFD models is time-consuming compared to the overall process simulation, we consider the development of fast reduced order models (ROMs) based on CFD results to closely approximate the high-fidelity equipment models in the co-simulation. By considering process equipment items with complicated geometries and detailed thermodynamic property models,more » this study proposes a strategy to develop ROMs based on principal component analysis (PCA). Taking advantage of commercial process simulation and CFD software (for example, Aspen Plus and FLUENT), we are able to develop systematic CFD-based ROMs for equipment models in an efficient manner. In particular, we show that the validity of the ROM is more robust within well-sampled input domain and the CPU time is significantly reduced. Typically, it takes at most several CPU seconds to evaluate the ROM compared to several CPU hours or more to solve the CFD model. Two case studies, involving two power plant equipment examples, are described and demonstrate the benefits of using our proposed ROM methodology for process simulation and optimization.« less
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Miller, Tom E X
2007-07-01
1. It is widely accepted that density-dependent processes play an important role in most natural populations. However, persistent challenges in our understanding of density-dependent population dynamics include evaluating the shape of the relationship between density and demographic rates (linear, concave, convex), and identifying extrinsic factors that can mediate this relationship. 2. I studied the population dynamics of the cactus bug Narnia pallidicornis on host plants (Opuntia imbricata) that varied naturally in relative reproductive effort (RRE, the proportion of meristems allocated to reproduction), an important plant quality trait. I manipulated per-plant cactus bug densities, quantified subsequent dynamics, and fit stage-structured models to the experimental data to ask if and how density influences demographic parameters. 3. In the field experiment, I found that populations with variable starting densities quickly converged upon similar growth trajectories. In the model-fitting analyses, the data strongly supported a model that defined the juvenile cactus bug retention parameter (joint probability of surviving and not dispersing) as a nonlinear decreasing function of density. The estimated shape of this relationship shifted from concave to convex with increasing host-plant RRE. 4. The results demonstrate that host-plant traits are critical sources of variation in the strength and shape of density dependence in insects, and highlight the utility of integrated experimental-theoretical approaches for identifying processes underlying patterns of change in natural populations.
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Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael
2016-01-01
Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector’s life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis’ life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector–based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector. PMID:27159134
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Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael
2016-01-01
Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.
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NASA Astrophysics Data System (ADS)
Ghimire, B.; Riley, W. J.; Koven, C.
2013-12-01
Nitrogen is the most important nutrient limiting plant carbon assimilation and growth, and is required for production of photosynthetic enzymes, growth and maintenance respiration, and maintaining cell structure. The forecasted rise in plant available nitrogen through atmospheric nitrogen deposition and the release of locked soil nitrogen by permafrost thaw in high latitude ecosystems is likely to result in an increase in plant productivity. However a mechanistic representation of plant nitrogen dynamics is lacking in earth system models. Most earth system models ignore the dynamic nature of plant nutrient uptake and allocation, and further lack tight coupling of below- and above-ground processes. In these models, the increase in nitrogen uptake does not translate to a corresponding increase in photosynthesis parameters, such as maximum Rubisco capacity and electron transfer rate. We present an improved modeling framework implemented in the Community Land Model version 4.5 (CLM4.5) for dynamic plant nutrient uptake, and allocation to different plant parts, including leaf enzymes. This modeling framework relies on imposing a more realistic flexible carbon to nitrogen stoichiometric ratio for different plant parts. The model mechanistically responds to plant nitrogen uptake and leaf allocation though changes in photosynthesis parameters. We produce global simulations, and examine the impacts of the improved nitrogen cycling. The improved model is evaluated against multiple observations including TRY database of global plant traits, nitrogen fertilization observations and 15N tracer studies. Global simulations with this new version of CLM4.5 showed better agreement with the observations than the default CLM4.5-CN model, and captured the underlying mechanisms associated with plant nitrogen cycle.
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NASA Astrophysics Data System (ADS)
Natalia, Slyusar; Pisman, Tamara; Pechurkin, Nikolai S.
Among the most challenging tasks faced by contemporary ecology is modeling of biological production process in different plant communities. The difficulty of the task is determined by the complexity of the study material. Models showing the influence of climate and climate change on plant growth, which would also involve soil site parameters, could be of both practical and theoretical interest. In this work a mathematical model has been constructed to describe the growth dynamics of different plant communities of halophytic meadows as dependent upon the temperature factor and soil salinity level, which could be further used to predict yields of these plant communities. The study was performed on plants of halophytic meadows in the coastal area of Lake of the Republic of Khakasia in 2004 - 2006. Every plant community grew on the soil of a different level of salinity - the amount of the solid residue of the saline soil aqueous extract. The mathematical model was analyzed using field data of 2004 and 2006, the years of contrasting air temperatures. Results of model investigations show that there is a correlation between plant growth and the temperature of the air for plant communities growing on soils containing the lowest (0.1Thus, results of our study, in which we used a mathematical model describing the development of plant communities of halophytic meadows and field measurements, suggest that both climate conditions (temperature) and ecological factors of the plants' habitat (soil salinity level) should be taken into account when constructing models for predicting crop yields.
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Development of a material processing plant for lunar soil
NASA Technical Reports Server (NTRS)
Goettsch, Ulix; Ousterhout, Karl
1992-01-01
Currently there is considerable interest in developing in-situ materials processing plants for both the Moon and Mars. Two of the most important aspects of developing such a materials processing plant is the overall system design and the integration of the different technologies into a reliable, lightweight, and cost-effective unit. The concept of an autonomous materials processing plant that is capable of producing useful substances from lunar regolith was developed. In order for such a materials processing plant to be considered as a viable option, it must be totally self-contained, able to operate autonomously, cost effective, light weight, and fault tolerant. In order to assess the impact of different technologies on the overall systems design and integration, a one-half scale model was constructed that is capable of scooping up (or digging) lunar soil, transferring the soil to a solar furnace, heating the soil in the furnace to liberate the gasses, and transferring the spent soil to a 'tile' processing center. All aspects of the control system are handled by a 386 class PC via D/A, A/D, and DSP (Digital Signal Processor) control cards.
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Remote sensing of plant-water relations: An overview and future perspectives.
Damm, A; Paul-Limoges, E; Haghighi, E; Simmer, C; Morsdorf, F; Schneider, F D; van der Tol, C; Migliavacca, M; Rascher, U
2018-04-25
Vegetation is a highly dynamic component of the Earth surface and substantially alters the water cycle. Particularly the process of oxygenic plant photosynthesis determines vegetation connecting the water and carbon cycle and causing various interactions and feedbacks across Earth spheres. While vegetation impacts the water cycle, it reacts to changing water availability via functional, biochemical and structural responses. Unravelling the resulting complex feedbacks and interactions between the plant-water system and environmental change is essential for any modelling approaches and predictions, but still insufficiently understood due to currently missing observations. We hypothesize that an appropriate cross-scale monitoring of plant-water relations can be achieved by combined observational and modelling approaches. This paper reviews suitable remote sensing approaches to assess plant-water relations ranging from pure observational to combined observational-modelling approaches. We use a combined energy balance and radiative transfer model to assess the explanatory power of pure observational approaches focussing on plant parameters to estimate plant-water relations, followed by an outline for a more effective use of remote sensing by their integration into soil-plant-atmosphere continuum (SPAC) models. We apply a mechanistic model simulating water movement in the SPAC to reveal insight into the complexity of relations between soil, plant and atmospheric parameters, and thus plant-water relations. We conclude that future research should focus on strategies combining observations and mechanistic modelling to advance our knowledge on the interplay between the plant-water system and environmental change, e.g. through plant transpiration. Copyright © 2018 Elsevier GmbH. All rights reserved.
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Modeling, simulation, and control of an extraterrestrial oxygen production plant
NASA Technical Reports Server (NTRS)
Schooley, L.; Cellier, F.; Zeigler, B.; Doser, A.; Farrenkopf, G.
1991-01-01
The immediate objective is the development of a new methodology for simulation of process plants used to produce oxygen and/or other useful materials from local planetary resources. Computer communication, artificial intelligence, smart sensors, and distributed control algorithms are being developed and implemented so that the simulation or an actual plant can be controlled from a remote location. The ultimate result of this research will provide the capability for teleoperation of such process plants which may be located on Mars, Luna, an asteroid, or other objects in space. A very useful near-term result will be the creation of an interactive design tool, which can be used to create and optimize the process/plant design and the control strategy. This will also provide a vivid, graphic demonstration mechanism to convey the results of other researchers to the sponsor.
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Response mechanisms of conifers to air pollutants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matyssek, R.; Reich, P.; Oren, R.
1995-07-01
Conifers are known to respond to SO{sub 2}, O{sub 3}, NO{sub x} and acid deposition. Of these pollutants, O{sub 3} is likely the most widespread and phytotoxic compound, and therefore of great interest to individuals concerned with forest resources Direct biological responses have a toxicological effects on metabolism which can then scale to effects on tree growth and forest ecology, including processes of competition and succession. Air pollution can cause reductions in photosynthesis and stomatal conductance, which are the physiological parameters most rigorously studied for conifers. Some effects air pollutants can have on plants are influenced by the presence ofmore » co-occurring environmental stresses. For example, drought usually reduces vulnerability of plants to air pollution. In addition, air pollution sensitivity may differ among species and with plant/leaf age. Plants may make short-term physiological adjustments to compensate for air pollution or may evolve resistance to air pollution through the processes of selection. Models are necessary to understand how physiological processes, growth processes, and ecological processes are affected by air pollutants. The process of defining the ecological risk that air pollutants pose for coniferous forests requires approaches that exploit existing databases, environmental monitoring of air pollutants and forest resources, experiments with well-defined air pollution treatments and environmental control/monitoring, modeling, predicting air pollution-caused changes in productivity and ecological processes over time and space, and integration of social values.« less
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NASA Astrophysics Data System (ADS)
Shephard, Adam M.; Thomas, Benjamin R.; Coble, Jamie B.; Wood, Houston G.
2018-05-01
This paper presents a development related to the use of minor isotope safeguards techniques (MIST) and the MSTAR cascade model as it relates to the application of international nuclear safeguards at gas centrifuge enrichment plants (GCEPs). The product of this paper is a derivation of the universal and dimensionless MSTAR cascade model. The new model can be used to calculate the minor uranium isotope concentrations in GCEP product and tails streams or to analyze, visualize, and interpret GCEP process data as part of MIST. Applications of the new model include the detection of undeclared feed and withdrawal streams at GCEPs when used in conjunction with UF6 sampling and/or other isotopic measurement techniques.
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NASA Astrophysics Data System (ADS)
Ribes Bertomeu, Josep
Wastewater treatments require the execution of many conversion processes simultaneously and/or consecutively, making them a tricky object of study. Furthermore, complexity of treatment processes is increasing not only for the more stringent effluent standards required, but also for the new trends towards sustainable development, which in this process are mainly focused on energy saving and nutrient recovery from wastewaters in order to improve their life cycle. For this reason it becomes necessary to use simulation tools which are able to represent all these processes by means of a suitable mathematical model. They can help in determining and predicting the behaviour of the different treatment schemes. These simulators have become essential for the design, control and optimization of wastewater treatment plants (WWTP). Settling processes have a significant role in the accomplishment of effluent standards and the correct operation of the plant. However, many models that are currently employed for WWTP design and simulation do not take into account settling processes or they are handled in a very simple way, by neglecting the biochemical processes that can occur during sedimentation. People of CALAGUA research group have focussed their efforts towards a new philosophy of simulating treatment plants, which is based on the use of a unique model to represent all physical, chemical and biological processes taking place in WWTPs. In this research topic, they have worked on the development of a general quality model that considers biological conversion processes carried out by different microorganism groups, acid base chemical interactions affecting the pH value in the system, and gas-liquid transfer processes. However, a generalized use of such a quality model requires its combination with a flux model, principally for those processes where completely mixture can not be assumed, as for instance, settlers and thickeners in WWTPs. The main objective of this work has been the development and validation of a general settling model that allows simulating the main settling operations taking place in a WWTP, considering both primary and secondary settlers and thickeners. It consists in a one-dimensional model based on the flux theory of Kynch and the double-exponential settling function of Takacs that takes into account flocculation, hindered settling and compression processes. The model has been applied to simulation of settlers and thickeners by means of splitting the system into several horizontal layers, all of them considered as completely mixed reactors which are interconnected by mass flux obtained from the settling model. In order to simulate the conversion processes taking place during sedimentation, the general quality model BNRM1 has been added, and it has been proposed an iterative procedure for solving the equations for each layer in which the settler has been divided. The settling flux model validation, along with the quality model, has been carried out by applying them to a simulation of primary sludge fermentation - elutriation process. This process has been studied on a pilot plant located in the Carraixet WWTP in Alboraia (Valencia). In order to simulate the observed decrease in solids separation efficiency in the studied fermentation - elutriation process, the quality model has been modified with the addition of a new process called "disintegration of complex particulate material". This process influences the settleability of the sludge because it is considered that the disintegrated solids become non-settleable solids. This modification implies the addition of two new kinetic parameters (the specific disintegration velocity for volatile particulate material and the specific disintegration velocity for non volatile particulate material). However, the settling parameter that represents the non-settleable fraction of total suspended solids is eliminated from the model and it has been transformed into an experimental variable which is quite easy to analyze. The result of this modification is a more general model, which is applicable to fermentation - elutriation process working at any operating condition. Finally, the behaviour and capabilities of the developed model have been tested by simulating a complete WWTP on the DESASS simulation software, developed by the research group. This example includes the most important processes that can be used in a WWTP: biological nutrient removal, primary sludge fermentation and sludge digestion. The model allows considering both settling processes and biochemical processes as a whole (denitrification in secondary settlers, primary sludge fermentation and VFA elutriation, phosphorus release in thickeners because of the PAO decay, etc.). The developed model implies an important advance in study of new wastewater treatment processes because it allows dealing with global process optimization problems, by means of full plants simulation. It is very useful for studying the effects of a modification in operation conditions of one element over the operation of the rest of the elements of the WWTP. (Abstract shortened by UMI.).
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Incorporating Eco-Evolutionary Processes into Population Models:Design and Applications
Eco-evolutionary population models are powerful new tools for exploring howevolutionary processes influence plant and animal population dynamics andvice-versa. The need to manage for climate change and other dynamicdisturbance regimes is creating a demand for the incorporation of...
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Why a simulation system doesn`t match the plant
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sowell, R.
1998-03-01
Process simulations, or mathematical models, are widely used by plant engineers and planners to obtain a better understanding of a particular process. These simulations are used to answer questions such as how can feed rate be increased, how can yields be improved, how can energy consumption be decreased, or how should the available independent variables be set to maximize profit? Although current process simulations are greatly improved over those of the `70s and `80s, there are many reasons why a process simulation doesn`t match the plant. Understanding these reasons can assist in using simulations to maximum advantage. The reasons simulationsmore » do not match the plant may be placed in three main categories: simulation effects or inherent error, sampling and analysis effects of measurement error, and misapplication effects or set-up error.« less
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Noguchi, Ko; Yamori, Wataru; Hikosaka, Kouki; Terashima, Ichiro
2015-07-01
The temperature dependence of plant respiratory rate (R) changes in response to growth temperature. Here, we used a modified Arrhenius model incorporating the temperature dependence of activation energy (Eo ), and compared the temperature dependence of R between cold-sensitive and cold-tolerant species. We analyzed the temperature dependences of leaf CO2 efflux rate of plants cultivated at low (LT) or high temperature (HT). In plants grown at HT (HT plants), Eo at low measurement temperature varied among species, but Eo at growth temperature in HT plants did not vary and was comparable to that in plants grown at LT (LT plants), suggesting that the limiting process was similar at the respective growth temperatures. In LT plants, the integrated value of loge R, a measure of respiratory capacity, in cold-sensitive species was lower than that in cold-tolerant species. When plants were transferred from HT to LT, the respiratory capacity changed promptly after the transfer compared with the other parameters. These results suggest that a similar process limits R at different growth temperatures, and that the lower capacity of the respiratory system in cold-sensitive species may explain their low growth rate at LT. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.
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Zhu, Xin-Guang; Lynch, Jonathan P; LeBauer, David S; Millar, Andrew J; Stitt, Mark; Long, Stephen P
2016-05-01
A paradigm shift is needed and timely in moving plant modelling from largely isolated efforts to a connected community endeavour that can take full advantage of advances in computer science and in mechanistic understanding of plant processes. Plants in silico (Psi) envisions a digital representation of layered dynamic modules, linking from gene networks and metabolic pathways through to cellular organization, tissue, organ and whole plant development, together with resource capture and use efficiency in dynamic competitive environments, ultimately allowing a mechanistically rich simulation of the plant or of a community of plants in silico. The concept is to integrate models or modules from different layers of organization spanning from genome to phenome to ecosystem in a modular framework allowing the use of modules of varying mechanistic detail representing the same biological process. Developments in high-performance computing, functional knowledge of plants, the internet and open-source version controlled software make achieving the concept realistic. Open source will enhance collaboration and move towards testing and consensus on quantitative theoretical frameworks. Importantly, Psi provides a quantitative knowledge framework where the implications of a discovery at one level, for example, single gene function or developmental response, can be examined at the whole plant or even crop and natural ecosystem levels. © 2015 The Authors Plant, Cell & Environment Published by John Wiley & Sons Ltd.
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NASA Astrophysics Data System (ADS)
Lavrov, V. V.; Spirin, N. A.
2016-09-01
Advances in modern science and technology are inherently connected with the development, implementation, and widespread use of computer systems based on mathematical modeling. Algorithms and computer systems are gaining practical significance solving a range of process tasks in metallurgy of MES-level (Manufacturing Execution Systems - systems controlling industrial process) of modern automated information systems at the largest iron and steel enterprises in Russia. This fact determines the necessity to develop information-modeling systems based on mathematical models that will take into account the physics of the process, the basics of heat and mass exchange, the laws of energy conservation, and also the peculiarities of the impact of technological and standard characteristics of raw materials on the manufacturing process data. Special attention in this set of operations for metallurgic production is devoted to blast-furnace production, as it consumes the greatest amount of energy, up to 50% of the fuel used in ferrous metallurgy. The paper deals with the requirements, structure and architecture of BF Process Engineer's Automated Workstation (AWS), a computer decision support system of MES Level implemented in the ICS of the Blast Furnace Plant at Magnitogorsk Iron and Steel Works. It presents a brief description of main model subsystems as well as assumptions made in the process of mathematical modelling. Application of the developed system allows the engineering and process staff to analyze online production situations in the blast furnace plant, to solve a number of process tasks related to control of heat, gas dynamics and slag conditions of blast-furnace smelting as well as to calculate the optimal composition of blast-furnace slag, which eventually results in increasing technical and economic performance of blast-furnace production.
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Power Plant Model Validation Tool
DOE Office of Scientific and Technical Information (OSTI.GOV)
The PPMV is used to validate generator model using disturbance recordings. The PPMV tool contains a collection of power plant models and model validation studies, as well as disturbance recordings from a number of historic grid events. The user can import data from a new disturbance into the database, which converts PMU and SCADA data into GE PSLF format, and then run the tool to validate (or invalidate) the model for a specific power plant against its actual performance. The PNNL PPMV tool enables the automation of the process of power plant model validation using disturbance recordings. The tool usesmore » PMU and SCADA measurements as input information. The tool automatically adjusts all required EPCL scripts and interacts with GE PSLF in the batch mode. The main tool features includes: The tool interacts with GE PSLF; The tool uses GE PSLF Play-In Function for generator model validation; Database of projects (model validation studies); Database of the historic events; Database of the power plant; The tool has advanced visualization capabilities; and The tool automatically generates reports« less
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Steinmann, Zoran J N; Venkatesh, Aranya; Hauck, Mara; Schipper, Aafke M; Karuppiah, Ramkumar; Laurenzi, Ian J; Huijbregts, Mark A J
2014-05-06
One of the major challenges in life cycle assessment (LCA) is the availability and quality of data used to develop models and to make appropriate recommendations. Approximations and assumptions are often made if appropriate data are not readily available. However, these proxies may introduce uncertainty into the results. A regression model framework may be employed to assess missing data in LCAs of products and processes. In this study, we develop such a regression-based framework to estimate CO2 emission factors associated with coal power plants in the absence of reported data. Our framework hypothesizes that emissions from coal power plants can be explained by plant-specific factors (predictors) that include steam pressure, total capacity, plant age, fuel type, and gross domestic product (GDP) per capita of the resident nations of those plants. Using reported emission data for 444 plants worldwide, plant level CO2 emission factors were fitted to the selected predictors by a multiple linear regression model and a local linear regression model. The validated models were then applied to 764 coal power plants worldwide, for which no reported data were available. Cumulatively, available reported data and our predictions together account for 74% of the total world's coal-fired power generation capacity.
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Multiscale Metabolic Modeling: Dynamic Flux Balance Analysis on a Whole-Plant Scale1[W][OPEN
Grafahrend-Belau, Eva; Junker, Astrid; Eschenröder, André; Müller, Johannes; Schreiber, Falk; Junker, Björn H.
2013-01-01
Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement. PMID:23926077
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NASA Astrophysics Data System (ADS)
Darnius, O.; Sitorus, S.
2018-03-01
The objective of this study was to determine the pattern of plant calendar of three types of crops; namely, palawija, rice, andbanana, based on rainfall in Deli Serdang Regency. In the first stage, we forecasted rainfall by using time series analysis, and obtained appropriate model of ARIMA (1,0,0) (1,1,1)12. Based on the forecast result, we designed a plant calendar pattern for the three types of plant. Furthermore, the probability of success in the plant types following the plant calendar pattern was calculated by using the Markov process by discretizing the continuous rainfall data into three categories; namely, Below Normal (BN), Normal (N), and Above Normal (AN) to form the probability transition matrix. Finally, the combination of rainfall forecasting models and the Markov process were used to determine the pattern of cropping calendars and the probability of success in the three crops. This research used rainfall data of Deli Serdang Regency taken from the office of BMKG (Meteorologist Climatology and Geophysics Agency), Sampali Medan, Indonesia.
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Mechanics of plant fruit hooks
Chen, Qiang; Gorb, Stanislav N.; Gorb, Elena; Pugno, Nicola
2013-01-01
Hook-like surface structures, observed in some plant species, play an important role in the process of plant growth and seed dispersal. In this study, we developed an elastic model and further used it to investigate the mechanical behaviour of fruit hooks in four plant species, previously measured in an experimental study. Based on Euler–Bernoulli beam theory, the force–displacement relationship is derived, and its Young's modulus is obtained. The result agrees well with the experimental data. The model aids in understanding the mechanics of hooks, and could be used in the development of new bioinspired Velcro-like materials. PMID:23365190
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NASA Astrophysics Data System (ADS)
Ushakova, Sofya; Tikhomirov, Alexander A.; Velichko, Vladimir; Tikhomirova, Natalia; Trifonov, Sergey V.
2016-07-01
Mass exchange processes in the new experimental model of the biotechnical life support system (BTLSS) constructed at the Institute of Biophysics SB RAS have a higher degree of closure than in the previous BTLSS, and, thus, the technologies employed in the new system are more complex. Therefore, before closing the loops of mass exchange processes for several months, the new model of the BTLSS was run to match the technologies employed to cultivate plants and the methods used to involve inedible plant parts and human wastes into the mass exchange with the CO2 absorption rate and the amount of the resulting O2. The plant compartment included vegetables grown on the soil-like substrate (SLS) (chufa, beet, carrot, radish, and lettuce), plants hydroponically grown on expanded clay aggregate (wheat, soybean, watercress), and plants grown in aquaculture (common glasswort and watercress). Nutrient solutions for hydroponically grown plants were prepared by using products of physicochemical mineralization of human wastes. Growing the plants in aquaculture enabled maintaining NaCl concentration in the irrigation solution for hydroponically grown plants at a level safe for the plants. Inedible plant biomass was added to the SLS. Three cycles of closing the system were run, which lasted 7, 7, and 10 days. The comparison of the amount of CO2 fed into the system over 24 h (simulating human respiration) and the amount of CO2 daily exhaled by a 70-kg middle-aged human showed that between 1% and 4% of the daily emissions of CO2 were assimilated in the system, and about 3% of the average human daily O2 requirement accumulated in the system. Plant productivity was between 4 and 4.7% of the human daily vegetable requirement, or between 3 and 3.5% of the total human daily food requirement. Thus, testing of the BTLSS showed a match between the technologies employed to arrange mass exchange processes. This study was supported by the grant of the Russian Science Foundation (Project No. 14-14-00599).
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Stillwater Hybrid Geo-Solar Power Plant Optimization Analyses
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wendt, Daniel S.; Mines, Gregory L.; Turchi, Craig S.
2015-09-02
The Stillwater Power Plant is the first hybrid plant in the world able to bring together a medium-enthalpy geothermal unit with solar thermal and solar photovoltaic systems. Solar field and power plant models have been developed to predict the performance of the Stillwater geothermal / solar-thermal hybrid power plant. The models have been validated using operational data from the Stillwater plant. A preliminary effort to optimize performance of the Stillwater hybrid plant using optical characterization of the solar field has been completed. The Stillwater solar field optical characterization involved measurement of mirror reflectance, mirror slope error, and receiver position error.more » The measurements indicate that the solar field may generate 9% less energy than the design value if an appropriate tracking offset is not employed. A perfect tracking offset algorithm may be able to boost the solar field performance by about 15%. The validated Stillwater hybrid plant models were used to evaluate hybrid plant operating strategies including turbine IGV position optimization, ACC fan speed and turbine IGV position optimization, turbine inlet entropy control using optimization of multiple process variables, and mixed working fluid substitution. The hybrid plant models predict that each of these operating strategies could increase net power generation relative to the baseline Stillwater hybrid plant operations.« less
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SOYCHMBR.I - A model designed for the study of plant growth in a closed chamber
NASA Technical Reports Server (NTRS)
Reinhold, C.
1982-01-01
The analytical model SOYCHMBER.I, an update and alteration of the SOYMOD/OARDC model, for describing the total processes experienced by a plant in a controlled mass environment is outlined. The model is intended for use with growth chambers for examining plant growth in a completely controlled environment, leading toward a data base for the design of spacecraft food supply systems. SOYCHMBER.I accounts for the assimilation, respiration, and partitioning of photosynthate and nitrogen compounds among leaves, stems, roots, and potentially, flowers of the soybean plant. The derivation of the governing equations is traced, and the results of the prediction of CO2 dynamics for a seven day experiment with rice in a closed chamber are reported, together with data from three model runs for soybean. It is concluded that the model needs expansion to account for factors such as relative humidity.
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Bachis, Giulia; Maruéjouls, Thibaud; Tik, Sovanna; Amerlinck, Youri; Melcer, Henryk; Nopens, Ingmar; Lessard, Paul; Vanrolleghem, Peter A
2015-01-01
Characterization and modelling of primary settlers have been neglected pretty much to date. However, whole plant and resource recovery modelling requires primary settler model development, as current models lack detail in describing the dynamics and the diversity of the removal process for different particulate fractions. This paper focuses on the improved modelling and experimental characterization of primary settlers. First, a new modelling concept based on particle settling velocity distribution is proposed which is then applied for the development of an improved primary settler model as well as for its characterization under addition of chemicals (chemically enhanced primary treatment, CEPT). This model is compared to two existing simple primary settler models (Otterpohl and Freund; Lessard and Beck), showing to be better than the first one and statistically comparable to the second one, but with easier calibration thanks to the ease with which wastewater characteristics can be translated into model parameters. Second, the changes in the activated sludge model (ASM)-based chemical oxygen demand fractionation between inlet and outlet induced by primary settling is investigated, showing that typical wastewater fractions are modified by primary treatment. As they clearly impact the downstream processes, both model improvements demonstrate the need for more detailed primary settler models in view of whole plant modelling.
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USDA-ARS?s Scientific Manuscript database
Predictions of seedling emergence timing for spring wheat are facilitated by process-based modeling of the microsite environment in the shallow seedling recruitment zone. Hourly temperature and water profiles within the recruitment zone for 60 days after planting were simulated from the process-base...
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Jiang, Dong; Hao, Mengmeng; Wang, Qiao; Huang, Yaohuan; Fu, Xinyu
2014-01-01
The main purpose for developing biofuel is to reduce GHG (greenhouse gas) emissions, but the comprehensive environmental impact of such fuels is not clear. Life cycle analysis (LCA), as a complete comprehensive analysis method, has been widely used in bioenergy assessment studies. Great efforts have been directed toward establishing an efficient method for comprehensively estimating the greenhouse gas (GHG) emission reduction potential from the large-scale cultivation of energy plants by combining LCA with ecosystem/biogeochemical process models. LCA presents a general framework for evaluating the energy consumption and GHG emission from energy crop planting, yield acquisition, production, product use, and postprocessing. Meanwhile, ecosystem/biogeochemical process models are adopted to simulate the fluxes and storage of energy, water, carbon, and nitrogen in the soil-plant (energy crops) soil continuum. Although clear progress has been made in recent years, some problems still exist in current studies and should be addressed. This paper reviews the state-of-the-art method for estimating GHG emission reduction through developing energy crops and introduces in detail a new approach for assessing GHG emission reduction by combining LCA with biogeochemical process models. The main achievements of this study along with the problems in current studies are described and discussed. PMID:25045736
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Ma, Yuntao; Li, Baoguo; Zhan, Zhigang; Guo, Yan; Luquet, Delphine; de Reffye, Philippe; Dingkuhn, Michael
2007-01-01
Background and Aims It is increasingly accepted that crop models, if they are to simulate genotype-specific behaviour accurately, should simulate the morphogenetic process generating plant architecture. A functional–structural plant model, GREENLAB, was previously presented and validated for maize. The model is based on a recursive mathematical process, with parameters whose values cannot be measured directly and need to be optimized statistically. This study aims at evaluating the stability of GREENLAB parameters in response to three types of phenotype variability: (1) among individuals from a common population; (2) among populations subjected to different environments (seasons); and (3) among different development stages of the same plants. Methods Five field experiments were conducted in the course of 4 years on irrigated fields near Beijing, China. Detailed observations were conducted throughout the seasons on the dimensions and fresh biomass of all above-ground plant organs for each metamer. Growth stage-specific target files were assembled from the data for GREENLAB parameter optimization. Optimization was conducted for specific developmental stages or the entire growth cycle, for individual plants (replicates), and for different seasons. Parameter stability was evaluated by comparing their CV with that of phenotype observation for the different sources of variability. A reduced data set was developed for easier model parameterization using one season, and validated for the four other seasons. Key Results and Conclusions The analysis of parameter stability among plants sharing the same environment and among populations grown in different environments indicated that the model explains some of the inter-seasonal variability of phenotype (parameters varied less than the phenotype itself), but not inter-plant variability (parameter and phenotype variability were similar). Parameter variability among developmental stages was small, indicating that parameter values were largely development-stage independent. The authors suggest that the high level of parameter stability observed in GREENLAB can be used to conduct comparisons among genotypes and, ultimately, genetic analyses. PMID:17158141
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Analysis of Efficiency of the Ship Propulsion System with Thermochemical Recuperation of Waste Heat
NASA Astrophysics Data System (ADS)
Cherednichenko, Oleksandr; Serbin, Serhiy
2018-03-01
One of the basic ways to reduce polluting emissions of ship power plants is application of innovative devices for on-board energy generation by means of secondary energy resources. The combined gas turbine and diesel engine plant with thermochemical recuperation of the heat of secondary energy resources has been considered. It is suggested to conduct the study with the help of mathematical modeling methods. The model takes into account basic physical correlations, material and thermal balances, phase equilibrium, and heat and mass transfer processes. The paper provides the results of mathematical modeling of the processes in a gas turbine and diesel engine power plant with thermochemical recuperation of the gas turbine exhaust gas heat by converting a hydrocarbon fuel. In such a plant, it is possible to reduce the specific fuel consumption of the diesel engine by 20%. The waste heat potential in a gas turbine can provide efficient hydrocarbon fuel conversion at the ratio of powers of the diesel and gas turbine engines being up to 6. When the diesel engine and gas turbine operate simultaneously with the use of the LNG vapor conversion products, the efficiency coefficient of the plant increases by 4-5%.
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Simulating aerial gravitropism and posture control in plants: what has been done, what is missing
NASA Astrophysics Data System (ADS)
Coutand, Catherine; Pot, Guillaume; Bastien, R.; Badel, Eric; Moulia, Bruno
The gravitropic response requires a process of perception of the signal and a motor process to actuate the movements. Different models have been developed, some focuses on the perception process and some focuses on the motor process. The kinematics of the gravitropic response will be first detailed to set the phenomenology of gravi- and auto-tropism. A model of perception (AC model) will be first presented to demonstrate that sensing inclination is not sufficient to control the gravitropic movement, and that proprioception is also involved. Then, “motor models” will be reviewed. In herbaceous plants, differential growth is the main motor. Modelling tropic movements with simulating elongation raises some difficulties that will be explained. In woody structures the main motor process is the differentiation of reaction wood via cambial growth. We will first present the simplest biomechanical model developed to simulate gravitropism and its limits will be pointed out. Then a more sophisticated model (TWIG) will be presented with a special focus on the importance of wood viscoelasticity and the wood maturation process and its regulation by a mechanosensing process. The presentation will end by a balance sheet of what is done and what is missing for a complete modelling of gravitropism and will present first results of a running project dedicating to get the data required to include phototropism in the actual models.
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NASA Astrophysics Data System (ADS)
Saaltink, Rémon; Dekker, Stefan C.; Griffioen, Jasper; Wassen, Martin J.
2016-04-01
Interest is growing in using soft sediment as a building material in eco-engineering projects. Wetland construction in the Dutch lake Markermeer is an example: here the option of dredging some of the clay-rich lake-bed sediment and using it to construct 10.000 ha of wetland will soon go under construction. Natural processes will be utilized during and after construction to accelerate ecosystem development. Knowing that plants can eco-engineer their environment via positive or negative biogeochemical plant-soil feedbacks, we conducted a six-month greenhouse experiment to identify the key biogeochemical processes in the mud when Phragmites australis is used as an eco-engineering species. We applied inverse biogeochemical modeling to link observed changes in pore water composition to biogeochemical processes. Two months after transplantation we observed reduced plant growth and shriveling as well as yellowing of foliage. The N:P ratios of plant tissue were low and were affected not by hampered uptake of N but by enhanced uptake of P. Plant analyses revealed high Fe concentrations in the leaves and roots. Sulfate concentrations rose drastically in our experiment due to pyrite oxidation; as reduction of sulfate will decouple Fe-P in reducing conditions, we argue that plant-induced iron toxicity hampered plant growth, forming a negative feedback loop, while simultaneously there was a positive feedback loop, as iron toxicity promotes P mobilization as a result of reduced conditions through root death, thereby stimulating plant growth and regeneration. Given these two feedback mechanisms, we propose that when building wetlands from these mud deposits Fe-tolerant species are used rather than species that thrive in N-limited conditions. The results presented in this study demonstrate the importance of studying the biogeochemical properties of the building material and the feedback mechanisms between plant and soil prior to finalizing the design of the eco-engineering project.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Deng, Yueying; Kruger, Albert A.
The Hanford Tank Waste Treatment and Immobilization Plant (WTP) Statement of Work (Department of Energy Contract DE-AC27-01RV14136, Section C) requires the contractor to develop and use process models for flowsheet analyses and pre-operational planning assessments. The Dynamic (G2) Flowsheet is a discrete-time process model that enables the project to evaluate impacts to throughput from eventdriven activities such as pumping, sampling, storage, recycle, separation, and chemical reactions. The model is developed by the Process Engineering (PE) department, and is based on the Flowsheet Bases, Assumptions, and Requirements Document (24590-WTP-RPT-PT-02-005), commonly called the BARD. The terminologies of Dynamic (G2) Flowsheet and Dynamicmore » (G2) Model are interchangeable in this document. The foundation of this model is a dynamic material balance governed by prescribed initial conditions, boundary conditions, and operating logic. The dynamic material balance is achieved by tracking the storage and material flows within the plant as time increments. The initial conditions include a feed vector that represents the waste compositions and delivery sequence of the Tank Farm batches, and volumes and concentrations of solutions in process equipment before startup. The boundary conditions are the physical limits of the flowsheet design, such as piping, volumes, flowrates, operation efficiencies, and physical and chemical environments that impact separations, phase equilibriums, and reaction extents. The operating logic represents the rules and strategies of running the plant.« less
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Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.
Marshall-Colon, Amy; Long, Stephen P; Allen, Douglas K; Allen, Gabrielle; Beard, Daniel A; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A J; Cox, Donna J; Hart, John C; Hirst, Peter M; Kannan, Kavya; Katz, Daniel S; Lynch, Jonathan P; Millar, Andrew J; Panneerselvam, Balaji; Price, Nathan D; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J; Voit, Eberhard O; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang
2017-01-01
Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.
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Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform
Marshall-Colon, Amy; Long, Stephen P.; Allen, Douglas K.; Allen, Gabrielle; Beard, Daniel A.; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A. J.; Cox, Donna J.; Hart, John C.; Hirst, Peter M.; Kannan, Kavya; Katz, Daniel S.; Lynch, Jonathan P.; Millar, Andrew J.; Panneerselvam, Balaji; Price, Nathan D.; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G.; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J.; Voit, Eberhard O.; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang
2017-01-01
Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop. PMID:28555150
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Development of plant condition measurement - The Jimah Model
NASA Astrophysics Data System (ADS)
Evans, Roy F.; Syuhaimi, Mohd; Mazli, Mohammad; Kamarudin, Nurliyana; Maniza Othman, Faiz
2012-05-01
The Jimah Model is an information management model. The model has been designed to facilitate analysis of machine condition by integrating diagnostic data with quantitative and qualitative information. The model treats data as a single strand of information - metaphorically a 'genome' of data. The 'Genome' is structured to be representative of plant function and identifies the condition of selected components (or genes) in each machine. To date in industry, computer aided work processes used with traditional industrial practices, have been unable to consistently deliver a standard of information suitable for holistic evaluation of machine condition and change. Significantly the reengineered site strategies necessary for implementation of this "data genome concept" have resulted in enhanced knowledge and management of plant condition. In large plant with high initial equipment cost and subsequent high maintenance costs, accurate measurement of major component condition becomes central to whole of life management and replacement decisions. A case study following implementation of the model at a major power station site in Malaysia (Jimah) shows that modeling of plant condition and wear (in real time) can be made a practical reality.
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NASA Astrophysics Data System (ADS)
Fang, Yilin; Leung, L. Ruby; Duan, Zhuoran; Wigmosta, Mark S.; Maxwell, Reed M.; Chambers, Jeffrey Q.; Tomasella, Javier
2017-08-01
The Amazon basin has experienced periodic droughts in the past, and intense and frequent droughts are predicted in the future. Landscape heterogeneity could play an important role in how tropical forests respond to drought by influencing water available to plants. Using the one-dimensional ACME Land Model and the three-dimensional ParFlow variably saturated flow model, numerical experiments were performed for a catchment in central Amazon to elucidate processes that influence water available for plant use and provide insights for improving Earth system models. Results from ParFlow show that topography has a dominant influence on groundwater table and runoff through lateral flow. Without any representations of lateral processes, ALM simulates very different seasonal variations in groundwater table and runoff compared to ParFlow even if it is able to reproduce the long-term spatial average groundwater table of ParFlow through simple parameter calibration. In the ParFlow simulations, even in the plateau with much deeper water table depth during the dry season in the drought year of 2005, plant transpiration is not water stressed as the soil saturation is still sufficient for the stomata to be fully open based on the empirical wilting formulation in the models. This finding is insensitive to uncertainty in atmospheric forcing and soil parameters, but the empirical wilting formulation is an important factor that should be addressed using observations and modeling of coupled plant hydraulics-soil hydrology processes in future studies. The results could be applicable to other catchments in the Amazon basin with similar seasonal variability and hydrologic regimes.
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PID-controller with predictor and auto-tuning algorithm: study of efficiency for thermal plants
NASA Astrophysics Data System (ADS)
Kuzishchin, V. F.; Merzlikina, E. I.; Hoang, Van Va
2017-09-01
The problem of efficiency estimation of an automatic control system (ACS) with a Smith predictor and PID-algorithm for thermal plants is considered. In order to use the predictor, it is proposed to include an auto-tuning module (ATC) into the controller; the module calculates parameters for a second-order plant module with a time delay. The study was conducted using programmable logical controllers (PLC), one of which performed control, ATC, and predictor functions. A simulation model was used as a control plant, and there were two variants of the model: one of them was built on the basis of a separate PLC, and the other was a physical model of a thermal plant in the form of an electrical heater. Analysis of the efficiency of the ACS with the predictor was carried out for several variants of the second order plant model with time delay, and the analysis was performed on the basis of the comparison of transient processes in the system when the set point was changed and when a disturbance influenced the control plant. The recommendations are given on correction of the PID-algorithm parameters when the predictor is used by means of using the correcting coefficient k for the PID parameters. It is shown that, when the set point is changed, the use of the predictor is effective taking into account the parameters correction with k = 2. When the disturbances influence the plant, the use of the predictor is doubtful, because the transient process is too long. The reason for this is that, in the neighborhood of the zero frequency, the amplitude-frequency characteristic (AFC) of the system with the predictor has an ascent in comparison with the AFC of the system without the predictor.
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Big Data in Plant Science: Resources and Data Mining Tools for Plant Genomics and Proteomics.
Popescu, George V; Noutsos, Christos; Popescu, Sorina C
2016-01-01
In modern plant biology, progress is increasingly defined by the scientists' ability to gather and analyze data sets of high volume and complexity, otherwise known as "big data". Arguably, the largest increase in the volume of plant data sets over the last decade is a consequence of the application of the next-generation sequencing and mass-spectrometry technologies to the study of experimental model and crop plants. The increase in quantity and complexity of biological data brings challenges, mostly associated with data acquisition, processing, and sharing within the scientific community. Nonetheless, big data in plant science create unique opportunities in advancing our understanding of complex biological processes at a level of accuracy without precedence, and establish a base for the plant systems biology. In this chapter, we summarize the major drivers of big data in plant science and big data initiatives in life sciences with a focus on the scope and impact of iPlant, a representative cyberinfrastructure platform for plant science.
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NASA Astrophysics Data System (ADS)
Peng, Xinyue; Maravelias, Christos T.; Root, Thatcher W.
2017-06-01
Thermochemical energy storage (TCES), with high energy density and wide operating temperature range, presents a potential solution for CSP plant energy storage. We develop a general optimization based process model for CSP plants employing a wide range of TCES systems which allows us to assess the plant economic feasibility and energy efficiency. The proposed model is applied to a 100 MW CSP plant employing ammonia or methane TCES systems. The methane TCES system with underground gas storage appears to be the most promising option, achieving a 14% LCOE reduction over the current two-tank molten-salt CSP plants. For general TCES systems, gas storage is identified as the main cost driver, while the main energy driver is the compressor electricity consumption. The impacts of separation and different reaction parameters are also analyzed. This study demonstrates that the realization of TCES systems for CSP plants is contingent upon low storage cost and a reversible reaction with proper reaction properties.
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Plant–herbivore–decomposer stoichiometric mismatches and nutrient cycling in ecosystems
Cherif, Mehdi; Loreau, Michel
2013-01-01
Plant stoichiometry is thought to have a major influence on how herbivores affect nutrient availability in ecosystems. Most conceptual models predict that plants with high nutrient contents increase nutrient excretion by herbivores, in turn raising nutrient availability. To test this hypothesis, we built a stoichiometrically explicit model that includes a simple but thorough description of the processes of herbivory and decomposition. Our results challenge traditional views of herbivore impacts on nutrient availability in many ways. They show that the relationship between plant nutrient content and the impact of herbivores predicted by conceptual models holds only at high plant nutrient contents. At low plant nutrient contents, the impact of herbivores is mediated by the mineralization/immobilization of nutrients by decomposers and by the type of resource limiting the growth of decomposers. Both parameters are functions of the mismatch between plant and decomposer stoichiometries. Our work provides new predictions about the impacts of herbivores on ecosystem fertility that depend on critical interactions between plant, herbivore and decomposer stoichiometries in ecosystems. PMID:23303537
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NASA Astrophysics Data System (ADS)
Wilson, Eric Lee
Due to increased competition in a world economy, steel companies are currently interested in developing techniques that will allow for the improvement of the steelmaking process, either by increasing output efficiency or by improving the quality of their product, or both. Slag foaming is one practice that has been shown to contribute to both these goals. However, slag foaming is highly dynamic and difficult to model or control. This dissertation describes an effort to use artificial intelligence-based tools (genetic algorithms, fuzzy logic, and neural networks) to both model and control the slag foaming process. Specifically, a neural network is trained and tested on slag foaming data provided by a steel plant. This neural network model is then controlled by a fuzzy logic controller, which in turn is optimized by a genetic algorithm. This tuned controller is then installed at a steel plant and given control be a more efficient slag foaming controller than what was previously used by the steel plant.
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Yield model development project implementation plan
NASA Technical Reports Server (NTRS)
Ambroziak, R. A.
1982-01-01
Tasks remaining to be completed are summarized for the following major project elements: (1) evaluation of crop yield models; (2) crop yield model research and development; (3) data acquisition processing, and storage; (4) related yield research: defining spectral and/or remote sensing data requirements; developing input for driving and testing crop growth/yield models; real time testing of wheat plant process models) and (5) project management and support.
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Unsupervised domain adaptation for early detection of drought stress in hyperspectral images
NASA Astrophysics Data System (ADS)
Schmitter, P.; Steinrücken, J.; Römer, C.; Ballvora, A.; Léon, J.; Rascher, U.; Plümer, L.
2017-09-01
Hyperspectral images can be used to uncover physiological processes in plants if interpreted properly. Machine Learning methods such as Support Vector Machines (SVM) and Random Forests have been applied to estimate development of biomass and detect and predict plant diseases and drought stress. One basic requirement of machine learning implies, that training and testing is done in the same domain and the same distribution. Different genotypes, environmental conditions, illumination and sensors violate this requirement in most practical circumstances. Here, we present an approach, which enables the detection of physiological processes by transferring the prior knowledge within an existing model into a related target domain, where no label information is available. We propose a two-step transformation of the target features, which enables a direct application of an existing model. The transformation is evaluated by an objective function including additional prior knowledge about classification and physiological processes in plants. We have applied the approach to three sets of hyperspectral images, which were acquired with different plant species in different environments observed with different sensors. It is shown, that a classification model, derived on one of the sets, delivers satisfying classification results on the transformed features of the other data sets. Furthermore, in all cases early non-invasive detection of drought stress was possible.
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Rizal, Datu; Tani, Shinichi; Nishiyama, Kimitoshi; Suzuki, Kazuhiko
2006-10-11
In this paper, a novel methodology in batch plant safety and reliability analysis is proposed using a dynamic simulator. A batch process involving several safety objects (e.g. sensors, controller, valves, etc.) is activated during the operational stage. The performance of the safety objects is evaluated by the dynamic simulation and a fault propagation model is generated. By using the fault propagation model, an improved fault tree analysis (FTA) method using switching signal mode (SSM) is developed for estimating the probability of failures. The timely dependent failures can be considered as unavailability of safety objects that can cause the accidents in a plant. Finally, the rank of safety object is formulated as performance index (PI) and can be estimated using the importance measures. PI shows the prioritization of safety objects that should be investigated for safety improvement program in the plants. The output of this method can be used for optimal policy in safety object improvement and maintenance. The dynamic simulator was constructed using Visual Modeler (VM, the plant simulator, developed by Omega Simulation Corp., Japan). A case study is focused on the loss of containment (LOC) incident at polyvinyl chloride (PVC) batch process which is consumed the hazardous material, vinyl chloride monomer (VCM).
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Chapter 14: Effects of fire suppression and postfire management activities on plant invasions
Matthew L. Brooks
2008-01-01
This chapter explains how various fire suppression and postfire management activities can increase or decrease the potential for plant invasions following fire. A conceptual model is used to summarize the basic processes associated with plant invasions and show how specific fire management activities can be designed to minimize the potential for invasion. The...
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Maize root culture as a model system for studying azoxystrobin biotransformation in plants.
Gautam, Maheswor; Elhiti, Mohamed; Fomsgaard, Inge S
2018-03-01
Hairy roots induced by Agrobacterium rhizogenes are well established models to study the metabolism of xenobiotics in plants for phytoremediation purposes. However, the model requires special skills and resources for growing and is a time-consuming process. The roots induction process alters the genetic construct of a plant and is known to express genes that are normally absent from the non-transgenic plants. In this study, we propose and establish a non-transgenic maize root model to study xenobiotic metabolism in plants for phytoremediation purpose using azoxystrobin as a xenobiotic compound. Maize roots were grown aseptically in Murashige and Skoog medium for two weeks and were incubated in 100 μM azoxystrobin solution. Azoxystrobin was taken up by the roots to the highest concentration within 15 min of treatment and its phase I metabolites were also detected at the same time. Conjugated metabolites of azoxystrobin were detected and their identities were confirmed by enzymatic and mass spectrometric methods. Further, azoxystrobin metabolites identified in maize root culture were compared against azoxystrobin metabolites in azoxystrobin sprayed lettuce grown in green house. A very close similarity between metabolites identified in maize root culture and lettuce plant was obtained. The results from this study establish that non-transgenic maize roots can be used for xenobiotic metabolism studies instead of genetically transformed hairy roots due to the ease of growing and handling. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Zheng, Jinshui; Peng, Donghai; Chen, Ling; Liu, Hualin; Chen, Feng; Xu, Mengci; Ju, Shouyong; Ruan, Lifang
2016-01-01
Plant-parasitic nematodes were found in 4 of the 12 clades of phylum Nematoda. These nematodes in different clades may have originated independently from their free-living fungivorous ancestors. However, the exact evolutionary process of these parasites is unclear. Here, we sequenced the genome sequence of a migratory plant nematode, Ditylenchus destructor. We performed comparative genomics among the free-living nematode, Caenorhabditis elegans and all the plant nematodes with genome sequences available. We found that, compared with C. elegans, the core developmental control processes underwent heavy reduction, though most signal transduction pathways were conserved. We also found D. destructor contained more homologies of the key genes in the above processes than the other plant nematodes. We suggest that Ditylenchus spp. may be an intermediate evolutionary history stage from free-living nematodes that feed on fungi to obligate plant-parasitic nematodes. Based on the facts that D. destructor can feed on fungi and has a relatively short life cycle, and that it has similar features to both C. elegans and sedentary plant-parasitic nematodes from clade 12, we propose it as a new model to study the biology, biocontrol of plant nematodes and the interaction between nematodes and plants. PMID:27466450
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Jong Suk; Bragg-Sitton, Shannon M.; Boardman, Richard D.
This report has been prepared as part of an effort to design and build a modeling and simulation (M&S) framework to assess the economic viability of a nuclear-renewable hybrid energy system (N-R HES). In order to facilitate dynamic M&S of such an integrated system, research groups in multiple national laboratories have been developing various subsystems as dynamic physics-based components using the Modelica programming language. In fiscal year 2015 (FY15), Idaho National Laboratory (INL) performed a dynamic analysis of two region-specific N-R HES configurations, including the gas-to-liquid (natural gas to Fischer-Tropsch synthetic fuel) and brackish water reverse osmosis desalination plants asmore » industrial processes. In FY16, INL developed two additional subsystems in the Modelica framework: (1) a high-temperature steam electrolysis (HTSE) plant as a high priority industrial plant to be integrated with a light water reactor (LWR) within an N-R HES and (2) a gas turbine power plant as a secondary energy supply. In FY17, five new components (i.e., a feedwater pump, a multi-stage compression system, a sweep-gas turbine, flow control valves, and pressure control valves) have been incorporated into the HTSE system proposed in FY16, aiming to better realistically characterize all key components of concern. Special attention has been given to the controller settings based on process models (i.e., direct synthesis method), aiming to improve process dynamics and controllability. A dynamic performance analysis of the improved LWR/HTSE integration case was carried out to evaluate the technical feasibility (load-following capability) and safety of such a system operating under highly variable conditions requiring flexible output. The analysis (evaluated in terms of the step response) clearly shows that the FY17 model resulted in superior output responses with much smaller settling times and less oscillatory behavior in response to disturbances in the electric load than those observed with the FY16 model. Simulation results involving several case studies show that the suggested control scheme could maintain the controlled variables (including the steam utilization factor, cathode stream inlet composition, and temperatures and pressures of the process streams at various locations) within desired limits under various plant operating conditions. The results also indicate that the proposed HTSE plant could provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess plant capacity within an N-R HES.« less
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Performance analysis of Integrated Communication and Control System networks
NASA Technical Reports Server (NTRS)
Halevi, Y.; Ray, A.
1990-01-01
This paper presents statistical analysis of delays in Integrated Communication and Control System (ICCS) networks that are based on asynchronous time-division multiplexing. The models are obtained in closed form for analyzing control systems with randomly varying delays. The results of this research are applicable to ICCS design for complex dynamical processes like advanced aircraft and spacecraft, autonomous manufacturing plants, and chemical and processing plants.
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Statistical modeling of an integrated boiler for coal fired thermal power plant.
Chandrasekharan, Sreepradha; Panda, Rames Chandra; Swaminathan, Bhuvaneswari Natrajan
2017-06-01
The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R 2 analysis and ANOVA (Analysis of Variance). The dependability of the process variable (temperature) on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM) supported by DOE (design of experiments) are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant.
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Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.
Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit
2018-02-13
Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Understanding Dynamic Model Validation of a Wind Turbine Generator and a Wind Power Plant: Preprint
DOE Office of Scientific and Technical Information (OSTI.GOV)
Muljadi, Eduard; Zhang, Ying Chen; Gevorgian, Vahan
Regional reliability organizations require power plants to validate the dynamic models that represent them to ensure that power systems studies are performed to the best representation of the components installed. In the process of validating a wind power plant (WPP), one must be cognizant of the parameter settings of the wind turbine generators (WTGs) and the operational settings of the WPP. Validating the dynamic model of a WPP is required to be performed periodically. This is because the control parameters of the WTGs and the other supporting components within a WPP may be modified to comply with new grid codesmore » or upgrades to the WTG controller with new capabilities developed by the turbine manufacturers or requested by the plant owners or operators. The diversity within a WPP affects the way we represent it in a model. Diversity within a WPP may be found in the way the WTGs are controlled, the wind resource, the layout of the WPP (electrical diversity), and the type of WTGs used. Each group of WTGs constitutes a significant portion of the output power of the WPP, and their unique and salient behaviors should be represented individually. The objective of this paper is to illustrate the process of dynamic model validations of WTGs and WPPs, the available data recorded that must be screened before it is used for the dynamic validations, and the assumptions made in the dynamic models of the WTG and WPP that must be understood. Without understanding the correct process, the validations may lead to the wrong representations of the WTG and WPP modeled.« less
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Barber, Jonathan L; Thomas, Gareth O; Kerstiens, Gerhard; Jones, Kevin C
2004-01-01
Air-vegetation exchange of POPs is an important process controlling the entry of POPs into terrestrial food chains, and may also have a significant effect on the global movement of these compounds. Many factors affect the air-vegetation transfer including: the physicochemical properties of the compounds of interest; environmental factors such as temperature, wind speed, humidity and light conditions; and plant characteristics such as functional type, leaf surface area, cuticular structure, and leaf longevity. The purpose of this review is to quantify the effects these differences might have on air/plant exchange of POPs, and to point out the major gaps in the knowledge of this subject that require further research. Uptake mechanisms are complicated, with the role of each factor in controlling partitioning, fate and behaviour process still not fully understood. Consequently, current models of air-vegetation exchange do not incorporate variability in these factors, with the exception of temperature. These models instead rely on using average values for a number of environmental factors (e.g. plant lipid content, surface area), ignoring the large variations in these values. The available models suggest that boundary layer conductance is of key importance in the uptake of POPs, although large uncertainties in the cuticular pathway prevents confirmation of this with any degree of certainty, and experimental data seems to show plant-side resistance to be important. Models are usually based on the assumption that POP uptake occurs through the lipophilic cuticle which covers aerial surfaces of plants. However, some authors have recently attached greater importance to the stomatal route of entry into the leaf for gas phase compounds. There is a need for greater mechanistic understanding of air-plant exchange and the 'scaling' of factors affecting it. The review also suggests a number of key variables that researchers should measure in their experiments to allow comparisons to be made between studies in order to improve our understanding of what causes any differences in measured data between sites.
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Spiridonov, S I; Mukusheva, M K; Gontarenko, I A; Fesenko, S V; Baranov, S A
2005-01-01
A mathematical model of 137Cs behaviour in the soil-plant system is presented. The model has been parameterized for the area adjacent to the testing area Ground Zero of the Semipalatinsk Test Site. The model describes the main processes responsible for the changes in 137Cs content in the soil solution and, thereby, dynamics of the radionuclide uptake by vegetation. The results are taken from predictive and retrospective calculations that reflect the dynamics of 137Cs distribution by species in soil after nuclear explosions. The importance of factors governing 137Cs accumulation in plants within the STS area is assessed. The analysis of sensitivity of the output model variable to changes in its parameters revealed that the key soil properties significantly influence the results of prediction of 137Cs content in plants.
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Plant uprooting by flow as a fatigue mechanical process
NASA Astrophysics Data System (ADS)
Perona, Paolo; Edmaier, Katharina; Crouzy, Benoît
2015-04-01
In river corridors, plant uprooting by flow mostly occurs as a delayed process where flow erosion first causes root exposure until residual anchoring balances hydrodynamic forces on the part of the plant that is exposed to the stream. Because a given plant exposure time to the action of the stream is needed before uprooting occurs (time-to-uprooting), this uprooting mechanism has been denominated Type II, in contrast to Type I, which mostly affect early stage seedlings and is rather instantaneous. In this work, we propose a stochastic framework that describes a (deterministic) mechanical fatigue process perturbed by a (stochastic) process noise, where collapse occurs after a given exposure time. We test the model using the experimental data of Edmaier (2014) and Edmaier et al. (submitted), who investigated vegetation uprooting by flow in the limit of low plant stem-to-sediment size ratio by inducing parallel riverbed erosion within an experimental flume. We first identify the proper timescale and lengthscale for rescaling the model. Then, we show that it describes well all the empirical cumulative distribution functions (cdf) of time-to-uprooting obtained under constant riverbed erosion rate and assuming additive gaussian process noise. By this mean, we explore the level of determinism and stochasticity affecting the time-to-uprooting for Avena sativa in relation to root anchoring and flow drag forces. We eventually ascribe the overall dynamics of the Type II uprooting mechanism to the memory of the plant-soil system that is stored by root anchoring, and discuss related implications thereof. References Edmaier, K., Uprooting mechansims of juvenile vegetation by flow erosion, Ph.D. thesis, EPFL, 2014. Edmaier, K., Crouzy, B. and P. Perona. Experimental characterization of vegetation uprooting by flow. J. of Geophys. Res. - Biogeosci., submitted
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Advanced multivariable control of a turboexpander plant
DOE Office of Scientific and Technical Information (OSTI.GOV)
Altena, D.; Howard, M.; Bullin, K.
1998-12-31
This paper describes an application of advanced multivariable control on a natural gas plant and compares its performance to the previous conventional feed-back control. This control algorithm utilizes simple models from existing plant data and/or plant tests to hold the process at the desired operating point in the presence of disturbances and changes in operating conditions. The control software is able to accomplish this due to effective handling of process variable interaction, constraint avoidance and feed-forward of measured disturbances. The economic benefit of improved control lies in operating closer to the process constraints while avoiding significant violations. The South Texasmore » facility where this controller was implemented experienced reduced variability in process conditions which increased liquids recovery because the plant was able to operate much closer to the customer specified impurity constraint. An additional benefit of this implementation of multivariable control is the ability to set performance criteria beyond simple setpoints, including process variable constraints, relative variable merit and optimizing use of manipulated variables. The paper also details the control scheme applied to the complex turboexpander process and some of the safety features included to improve reliability.« less
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The effects of psammophilous plants on sand dune dynamics
NASA Astrophysics Data System (ADS)
Bel, Golan; Ashkenazy, Yosef
2014-07-01
Mathematical models of sand dune dynamics have considered different types of sand dune cover. However, despite the important role of psammophilous plants (plants that flourish in moving-sand environments) in dune dynamics, the incorporation of their effects into mathematical models of sand dunes remains a challenging task. Here we propose a nonlinear physical model for the role of psammophilous plants in the stabilization and destabilization of sand dunes. There are two main mechanisms by which the wind affects these plants: (i) sand drift results in the burial and exposure of plants, a process that is known to result in an enhanced growth rate, and (ii) strong winds remove shoots and rhizomes and seed them in nearby locations, enhancing their growth rate. Our model describes the temporal evolution of the fractions of surface cover of regular vegetation, biogenic soil crust, and psammophilous plants. The latter reach their optimal growth under either (i) specific sand drift or (ii) specific wind power. The model exhibits complex bifurcation diagrams and dynamics, which explain observed phenomena, and it predicts new dune stabilization scenarios. Depending on the climatological conditions, it is possible to obtain one, two, or, predicted here for the first time, three stable dune states. Our model shows that the development of the different cover types depends on the precipitation rate and the wind power and that the psammophilous plants are not always the first to grow and stabilize the dunes.
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Remote sensing of the energetic status of plants and ecosystems: optical and odorous signals
NASA Astrophysics Data System (ADS)
Penuelas, J.; Bartrons, M.; Llusia, J.; Filella, I.
2016-12-01
The optical and odorous signals emitted by plants and ecosystems present consistent relationships. They offer promising prospects for continuous local and global monitoring of the energetic status of plants and ecosystems, and therefore of their processing of energy and matter. We will discuss how the energetic status of plants (and ecosystems) resulting from the balance between the supply and demand of reducing power can be assessed biochemically, by the cellular NADPH/NADP ratio, optically, by using the photochemical reflectance index and sun-induced fluorescence as indicators of the dissipation of excess energy and associated physiological processes, and "odorously", by the emission of volatile organic compounds such as isoprenoids, as indicators of an excess of reducing equivalents and also of enhancement of protective converging physiological processes. These signals thus provide information on the energetic status, associated health status, and the functioning of plants and ecosystems. We will present the links among the three signals and will especially discuss the possibility of remotely sense the optical signals linked to carbon uptake and VOCs exchange by plants and ecosystems. These signals and their integration may have multiple applications for environmental and agricultural monitoring, for example, by extending the spatial coverage of carbon-flux and VOCs emission observations to most places and times, and/or for improving the process-based modeling of carbon fixation and isoprenoid emissions from terrestrial vegetation on plant, ecosystemic and global scales. Considerable challenges remain for a wide-scale and routine implementation of these biochemical, optical, and odorous signals for ecosystemic and/or agronomic monitoring and modeling, but its interest for making further steps forward in global ecology, agricultural applications, global carbon cycle, atmospheric science, and earth science warrants further research efforts in this line.
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Aspen Modeling of the Bayer Process
NASA Astrophysics Data System (ADS)
Langa, J. M.; Russell, T. G.; O'Neill, G. A.; Gacka, P.; Shah, V. B.; Stephenson, J. L.; Snyder, J. G.
The ASPEN simulator was used to model Alcoa's Pt. Comfort Bayer refinery. All areas of the refinery including the lakes and powerhouse were modeled. Each area model was designed to be run stand alone or integrated with others for a full plant model.
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Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of Plants
Wahabzada, Mirwaes; Mahlein, Anne-Katrin; Bauckhage, Christian; Steiner, Ulrike; Oerke, Erich-Christian; Kersting, Kristian
2016-01-01
Modern phenotyping and plant disease detection methods, based on optical sensors and information technology, provide promising approaches to plant research and precision farming. In particular, hyperspectral imaging have been found to reveal physiological and structural characteristics in plants and to allow for tracking physiological dynamics due to environmental effects. In this work, we present an approach to plant phenotyping that integrates non-invasive sensors, computer vision, as well as data mining techniques and allows for monitoring how plants respond to stress. To uncover latent hyperspectral characteristics of diseased plants reliably and in an easy-to-understand way, we “wordify” the hyperspectral images, i.e., we turn the images into a corpus of text documents. Then, we apply probabilistic topic models, a well-established natural language processing technique that identifies content and topics of documents. Based on recent regularized topic models, we demonstrate that one can track automatically the development of three foliar diseases of barley. We also present a visualization of the topics that provides plant scientists an intuitive tool for hyperspectral imaging. In short, our analysis and visualization of characteristic topics found during symptom development and disease progress reveal the hyperspectral language of plant diseases. PMID:26957018
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Berner, Logan T; Law, Beverly E
2016-01-19
Plant trait measurements are needed for evaluating ecological responses to environmental conditions and for ecosystem process model development, parameterization, and testing. We present a standardized dataset integrating measurements from projects conducted by the Terrestrial Ecosystem Research and Regional Analysis- Pacific Northwest (TERRA-PNW) research group between 1999 and 2014 across Oregon and Northern California, where measurements were collected for scaling and modeling regional terrestrial carbon processes with models such as Biome-BGC and the Community Land Model. The dataset contains measurements of specific leaf area, leaf longevity, leaf carbon and nitrogen for 35 tree and shrub species derived from more than 1,200 branch samples collected from over 200 forest plots, including several AmeriFlux sites. The dataset also contains plot-level measurements of forest composition, structure (e.g., tree biomass), and productivity, as well as measurements of soil structure (e.g., bulk density) and chemistry (e.g., carbon). Publically-archiving regional datasets of standardized, co-located, and geo-referenced plant trait measurements will advance the ability of earth system models to capture species-level climate sensitivity at regional to global scales.
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NASA Astrophysics Data System (ADS)
Berner, Logan T.; Law, Beverly E.
2016-01-01
Plant trait measurements are needed for evaluating ecological responses to environmental conditions and for ecosystem process model development, parameterization, and testing. We present a standardized dataset integrating measurements from projects conducted by the Terrestrial Ecosystem Research and Regional Analysis- Pacific Northwest (TERRA-PNW) research group between 1999 and 2014 across Oregon and Northern California, where measurements were collected for scaling and modeling regional terrestrial carbon processes with models such as Biome-BGC and the Community Land Model. The dataset contains measurements of specific leaf area, leaf longevity, leaf carbon and nitrogen for 35 tree and shrub species derived from more than 1,200 branch samples collected from over 200 forest plots, including several AmeriFlux sites. The dataset also contains plot-level measurements of forest composition, structure (e.g., tree biomass), and productivity, as well as measurements of soil structure (e.g., bulk density) and chemistry (e.g., carbon). Publically-archiving regional datasets of standardized, co-located, and geo-referenced plant trait measurements will advance the ability of earth system models to capture species-level climate sensitivity at regional to global scales.
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Sierra-de-Grado, Rosario; Pando, Valentín; Martínez-Zurimendi, Pablo; Peñalvo, Alejandro; Báscones, Esther; Moulia, Bruno
2008-06-01
Stem straightness is an important selection trait in Pinus pinaster Ait. breeding programs. Despite the stability of stem straightness rankings in provenance trials, the efficiency of breeding programs based on a quantitative index of stem straightness remains low. An alternative approach is to analyze biomechanical processes that underlie stem form. The rationale for this selection method is that genetic differences in the biomechanical processes that maintain stem straightness in young plants will continue to control stem form throughout the life of the tree. We analyzed the components contributing most to genetic differences among provenances in stem straightening processes by kinetic analysis and with a biomechanical model defining the interactions between the variables involved (Fournier's model). This framework was tested on three P. pinaster provenances differing in adult stem straightness and growth. One-year-old plants were tilted at 45 degrees, and individual stem positions and sizes were recorded weekly for 5 months. We measured the radial extension of reaction wood and the anatomical features of wood cells in serial stem cross sections. The integral effect of reaction wood on stem leaning was computed with Fournier's model. Responses driven by both primary and secondary growth were involved in the stem straightening process, but secondary-growth-driven responses accounted for most differences among provenances. Plants from the straight-stemmed provenance showed a greater capacity for stem straightening than plants from the sinuous provenances mainly because of (1) more efficient reaction wood (higher maturation strains) and (2) more pronounced secondary-growth-driven autotropic decurving. These two process-based traits are thus good candidates for early selection of stem straightness, but additional tests on a greater number of genotypes over a longer period are required.
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NASA Astrophysics Data System (ADS)
Bras, R. L.; Istanbulluoglu, E.
2004-12-01
Topography acts as a template for numerous landscape processes that includes hydrologic, ecologic and biologic phenomena. These processes not only interact with each other but also contribute to shaping the landscape as they influence geomorphic processes. We have investigated the effects of vegetation on known geomorphic relations, thresholds for channel initiation and landform evolution, using both analytical and numerical approaches. Vegetation is assumed to form a uniform ground cover. Runoff erosion is modeled based on power function of excess shear stress, in which shear stress efficiency is inversely proportional to vegetation cover. Plant effect on slope stability is represented by additional cohesion provided by plant roots. Vegetation cover is assumed to reduce sediment transport rates due to physical creep processes (rainsplash, dry ravel, and expansion and contraction of sediments) according to a negative exponential relationship. Vegetation grows as a function of both available cover and unoccupied space by plants, and is killed by geomorphic disturbances (runoff erosion and landsliding), and wildfires. Analytical results suggest that, in an equilibrium basin with a fixed vegetation cover, plants may cause a transition in the dominant erosion process at the channel head. A runoff erosion dominated landscape, under none or loose vegetation cover, may become landslide dominated under a denser vegetation cover. The sign of the predicted relationship between drainage density and vegetation cover depends on the relative influence of vegetation on different erosion phenomena. With model parameter values representative of the Oregon Coast Range (OCR), numerical experiments conducted using the CHILD model. Numerical experiments reveal the importance of vegetation disturbances on the landscape structure. Simulated landscapes resemble real-world catchments in the OCR when vegetation disturbances are considered.
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Fluvial processes and vegetation - Glimpses of the past, the present, and perhaps the future
Osterkamp, W.R.; Hupp, C.R.
2010-01-01
Most research before 1960 into interactions among fluvial processes, resulting landforms, and vegetation was descriptive. Since then, however, research has become more detailed and quantitative permitting numerical modeling and applications including agricultural-erosion abatement and rehabilitation of altered bottomlands. Although progress was largely observational, the empiricism increasingly yielded to objective recognition of how vegetation interacts with and influences geomorphic process. A review of advances relating fluvial processes and vegetation during the last 50 years centers on hydrologic reconstructions from tree rings, plant indicators of flow- and flood-frequency parameters, hydrologic controls on plant species, regulation of sediment movement by vegetation, vegetative controls on mass movement, and relations between plant cover and sediment movement. Extension of present studies of vegetation as a regulator of bottomland hydrologic and geomorphic processes may become markedly more sophisticated and widespread than at present. Research emphases that are likely to continue include vegetative considerations for erosion modeling, response of riparian-zone forests to disturbance such as dams and water diversion, the effect of vegetation on channel and bottomland dynamics, and rehabilitation of stream corridors. Research topics that presently are receiving attention are the effect of woody vegetation on the roughness of stream corridors and, hence, processes of flood conveyance and flood-plain sedimentation, the development of a theoretical basis for rehabilitation projects as opposed to fully empirical approaches, the effect of invasive plant species on the dynamics of bottomland vegetation, the quantification of below-surface biomass and related soil-stability factors for use in erosion-prediction models, and the effect of impoundments on downstream narrowing of channels and accompanying encroachment of vegetation. Bottomland vegetation partially controls and is controlled by fluvial-geomorphic processes. The purposes of this paper are to identify and review investigations that have related vegetation to bottomland features and processes, to distinguish the present status of these investigations, and to anticipate future research into how hydrologic and fluvial-geomorphic processes of bottomlands interact with vegetation.
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Domínguez-Tello, Antonio; Arias-Borrego, Ana; García-Barrera, Tamara; Gómez-Ariza, José Luis
2017-10-01
The trihalomethanes (TTHMs) and others disinfection by-products (DBPs) are formed in drinking water by the reaction of chlorine with organic precursors contained in the source water, in two consecutive and linked stages, that starts at the treatment plant and continues in second stage along the distribution system (DS) by reaction of residual chlorine with organic precursors not removed. Following this approach, this study aimed at developing a two-stage empirical model for predicting the formation of TTHMs in the water treatment plant and subsequently their evolution along the water distribution system (WDS). The aim of the two-stage model was to improve the predictive capability for a wide range of scenarios of water treatments and distribution systems. The two-stage model was developed using multiple regression analysis from a database (January 2007 to July 2012) using three different treatment processes (conventional and advanced) in the water supply system of Aljaraque area (southwest of Spain). Then, the new model was validated using a recent database from the same water supply system (January 2011 to May 2015). The validation results indicated no significant difference in the predictive and observed values of TTHM (R 2 0.874, analytical variance <17%). The new model was applied to three different supply systems with different treatment processes and different characteristics. Acceptable predictions were obtained in the three distribution systems studied, proving the adaptability of the new model to the boundary conditions. Finally the predictive capability of the new model was compared with 17 other models selected from the literature, showing satisfactory results prediction and excellent adaptability to treatment processes.
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Wang, Zhenhong
2017-01-01
The current rates of biodiversity loss have exceeded the rates observed during the earth’s major extinction events, which spurs the studies of the ecological relationships between biodiversity and ecosystem functions, stability, and services to determine the consequences of biodiversity loss. Plant species richness-productivity relationship (SRPR) is crucial to the understanding of these relationships in plants. Most ecologists have reached a widespread consensus that the loss of plant diversity undoubtedly impairs ecosystem functions, and have proposed many processes to explain the SRPR. However, none of the available studies has satisfactorily described the forms and mechanisms clarifying the SRPR. Observed results of the SRPR forms are inconsistent, and studies have long debated the ecological processes explaining the SRPR. Here, I have developed a simple model that combines the positive and/or negative effects of sixteen ecological processes on the SRPR and models that describe the dynamics of complementary-selection effect, density effect, and the interspecific competitive stress influenced by other ecological processes. I can regulate the strengths of the effects of these ecological processes to derive the asymptotic, positive, humped, negative, and irregular forms of the SRPR, and verify these forms using the observed data. The results demonstrated that the different strengths of the ecological processes determine the forms of the SRPR. The forms of the SRPR can change with variations in the strengths of the ecological processes. The dynamic characteristics of the complementary-selection effect, density effect, and the interspecific competitive stress on the SRPR are diverse, and are dependent on the strengths and variation of the ecological processes. This report explains the diverse forms of the SRPR, clarifies the integrative effects of the different ecological processes on the SRPR, and deepens our understanding of the interactions that occur among these ecological processes. PMID:29140995
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Feasibilities of a Coal-Biomass to Liquids Plant in Southern West Virginia
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bhattacharyya, Debangsu; DVallance, David; Henthorn, Greg
This project has generated comprehensive and realistic results of feasibilities for a coal-biomass to liquids (CBTL) plant in southern West Virginia; and evaluated the sensitivity of the analyses to various anticipated scenarios and parametric uncertainties. Specifically the project has addressed economic feasibility, technical feasibility, market feasibility, and financial feasibility. In the economic feasibility study, a multi-objective siting model was developed and was then used to identify and rank the suitable facility sites. Spatial models were also developed to assess the biomass and coal feedstock availabilities and economics. Environmental impact analysis was conducted mainly to assess life cycle analysis and greenhousemore » gas emission. Uncertainty and sensitivity analysis were also investigated in this study. Sensitivity analyses on required selling price (RSP) and greenhouse gas (GHG) emissions of CBTL fuels were conducted according to feedstock availability and price, biomass to coal mix ratio, conversion rate, internal rate of return (IRR), capital cost, operational and maintenance cost. The study of siting and capacity showed that feedstock mixed ratio limited the CBTL production. The price of coal had a more dominant effect on RSP than that of biomass. Different mix ratios in the feedstock and conversion rates led to RSP ranging from $104.3 - $157.9/bbl. LCA results indicated that GHG emissions ranged from 80.62 kg CO 2 eq to 101.46 kg CO2 eq/1,000 MJ of liquid fuel at various biomass to coal mix ratios and conversion rates if carbon capture and storage (CCS) was applied. Most of water and fossil energy were consumed in conversion process. Compared to petroleum-derived-liquid fuels, the reduction in GHG emissions could be between -2.7% and 16.2% with CBTL substitution. As for the technical study, three approaches of coal and biomass to liquids, direct, indirect and hybrid, were considered in the analysis. The process models including conceptual design, process modeling and process validation were developed and validated for different cases. Equipment design and capital costs were investigated on capital coast estimation and economical model validation. Material and energy balances and techno-economic analysis on base case were conducted for evaluation of projects. Also, sensitives studies of direct and indirect approaches were both used to evaluate the CBTL plant economic performance. In this study, techno-economic analysis were conducted in Aspen Process Economic Analyzer (APEA) environment for indirect, direct, and hybrid CBTL plants with CCS based on high fidelity process models developed in Aspen Plus and Excel. The process thermal efficiency ranges from 45% to 67%. The break-even oil price ranges from $86.1 to $100.6 per barrel for small scale (10000 bbl/day) CBTL plants and from $65.3 to $80.5 per barrel for large scale (50000 bbl/day) CBTL plants. Increasing biomass/coal ratio from 8/92 to 20/80 would increase the break-even oil price of indirect CBTL plant by $3/bbl and decrease the break-even oil price of direct CBTL plant by about $1/bbl. The order of carbon capture penalty is direct > indirect > hybrid. The order of capital investment is hybrid (with or without shale gas utilization) > direct (without shale gas utilization) > indirect > direct (with shale gas utilization). The order of thermal efficiency is direct > hybrid > indirect. The order of break-even oil price is hybrid (without shale gas utilization) > direct (without shale gas utilization) > hybrid (with shale gas utilization) > indirect > direct (with shale gas utilization).« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Bhattacharyya, D.; Turton, R.; Zitney, S.
In this presentation, development of a plant-wide dynamic model of an advanced Integrated Gasification Combined Cycle (IGCC) plant with CO2 capture will be discussed. The IGCC reference plant generates 640 MWe of net power using Illinois No.6 coal as the feed. The plant includes an entrained, downflow, General Electric Energy (GEE) gasifier with a radiant syngas cooler (RSC), a two-stage water gas shift (WGS) conversion process, and two advanced 'F' class combustion turbines partially integrated with an elevated-pressure air separation unit (ASU). A subcritical steam cycle is considered for heat recovery steam generation. Syngas is selectively cleaned by a SELEXOLmore » acid gas removal (AGR) process. Sulfur is recovered using a two-train Claus unit with tail gas recycle to the AGR. A multistage intercooled compressor is used for compressing CO2 to the pressure required for sequestration. Using Illinois No.6 coal, the reference plant generates 640 MWe of net power. The plant-wide steady-state and dynamic IGCC simulations have been generated using the Aspen Plus{reg_sign} and Aspen Plus Dynamics{reg_sign} process simulators, respectively. The model is generated based on the Case 2 IGCC configuration detailed in the study available in the NETL website1. The GEE gasifier is represented with a restricted equilibrium reactor model where the temperature approach to equilibrium for individual reactions can be modified based on the experimental data. In this radiant-only configuration, the syngas from the Radiant Syngas Cooler (RSC) is quenched in a scrubber. The blackwater from the scrubber bottom is further cleaned in the blackwater treatment plant. The cleaned water is returned back to the scrubber and also used for slurry preparation. The acid gas from the sour water stripper (SWS) is sent to the Claus plant. The syngas from the scrubber passes through a sour shift process. The WGS reactors are modeled as adiabatic plug flow reactors with rigorous kinetics based on the mid-life activity of the shift-catalyst. The SELEXOL unit consists of the H2S and CO2 absorbers that are designed to meet the stringent environmental limits and requirements of other associated units. The model also considers the stripper for recovering H2S that is sent as a feed to a split-flow Claus unit. The tail gas from the Claus unit is recycled to the SELEXOL unit. The cleaned syngas is sent to the GE 7FB gas turbine. This turbine is modeled as per published data in the literature. Diluent N2 is used from the elevated-pressure ASU for reducing the NOx formation. The heat recovery steam generator (HRSG) is modeled by considering generation of high-pressure, intermediate-pressure, and low-pressure steam. All of the vessels, reactors, heat exchangers, and the columns have been sized. The basic IGCC process control structure has been synthesized by standard guidelines and existing practices. The steady-state simulation is solved in sequential-modular mode in Aspen Plus{reg_sign} and consists of more than 300 unit operations, 33 design specs, and 16 calculator blocks. The equation-oriented dynamic simulation consists of more than 100,000 equations solved using a multi-step Gear's integrator in Aspen Plus Dynamics{reg_sign}. The challenges faced in solving the dynamic model and key transient results from this dynamic model will also be discussed.« less
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Gago, Jorge; Martínez-Núñez, Lourdes; Landín, Mariana; Flexas, Jaume; Gallego, Pedro P.
2014-01-01
Background Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. Methodology and Principal Findings In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122–130 µmol m−2 s−1. Conclusions Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work. PMID:24465829
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Gago, Jorge; Martínez-Núñez, Lourdes; Landín, Mariana; Flexas, Jaume; Gallego, Pedro P
2014-01-01
Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122-130 µmol m(-2) s(-1). Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work.
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Flores-Alsina, Xavier; Kazadi Mbamba, Christian; Solon, Kimberly; Vrecko, Darko; Tait, Stephan; Batstone, Damien J; Jeppsson, Ulf; Gernaey, Krist V
2015-11-15
There is a growing interest within the Wastewater Treatment Plant (WWTP) modelling community to correctly describe physico-chemical processes after many years of mainly focusing on biokinetics. Indeed, future modelling needs, such as a plant-wide phosphorus (P) description, require a major, but unavoidable, additional degree of complexity when representing cationic/anionic behaviour in Activated Sludge (AS)/Anaerobic Digestion (AD) systems. In this paper, a plant-wide aqueous phase chemistry module describing pH variations plus ion speciation/pairing is presented and interfaced with industry standard models. The module accounts for extensive consideration of non-ideality, including ion activities instead of molar concentrations and complex ion pairing. The general equilibria are formulated as a set of Differential Algebraic Equations (DAEs) instead of Ordinary Differential Equations (ODEs) in order to reduce the overall stiffness of the system, thereby enhancing simulation speed. Additionally, a multi-dimensional version of the Newton-Raphson algorithm is applied to handle the existing multiple algebraic inter-dependencies. The latter is reinforced with the Simulated Annealing method to increase the robustness of the solver making the system not so dependent of the initial conditions. Simulation results show pH predictions when describing Biological Nutrient Removal (BNR) by the activated sludge models (ASM) 1, 2d and 3 comparing the performance of a nitrogen removal (WWTP1) and a combined nitrogen and phosphorus removal (WWTP2) treatment plant configuration under different anaerobic/anoxic/aerobic conditions. The same framework is implemented in the Benchmark Simulation Model No. 2 (BSM2) version of the Anaerobic Digestion Model No. 1 (ADM1) (WWTP3) as well, predicting pH values at different cationic/anionic loads. In this way, the general applicability/flexibility of the proposed approach is demonstrated, by implementing the aqueous phase chemistry module in some of the most frequently used WWTP process simulation models. Finally, it is shown how traditional wastewater modelling studies can be complemented with a rigorous description of aqueous phase and ion chemistry (pH, speciation, complexation). Copyright © 2015 Elsevier Ltd. All rights reserved.
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A kinetic model of municipal sludge degradation during non-catalytic wet oxidation.
Prince-Pike, Arrian; Wilson, David I; Baroutian, Saeid; Andrews, John; Gapes, Daniel J
2015-12-15
Wet oxidation is a successful process for the treatment of municipal sludge. In addition, the resulting effluent from wet oxidation is a useful carbon source for subsequent biological nutrient removal processes in wastewater treatment. Owing to limitations with current kinetic models, this study produced a kinetic model which predicts the concentrations of key intermediate components during wet oxidation. The model was regressed from lab-scale experiments and then subsequently validated using data from a wet oxidation pilot plant. The model was shown to be accurate in predicting the concentrations of each component, and produced good results when applied to a plant 500 times larger in size. A statistical study was undertaken to investigate the validity of the regressed model parameters. Finally the usefulness of the model was demonstrated by suggesting optimum operating conditions such that volatile fatty acids were maximised. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Reactive Scheduling in Multipurpose Batch Plants
NASA Astrophysics Data System (ADS)
Narayani, A.; Shaik, Munawar A.
2010-10-01
Scheduling is an important operation in process industries for improving resource utilization resulting in direct economic benefits. It has a two-fold objective of fulfilling customer orders within the specified time as well as maximizing the plant profit. Unexpected disturbances such as machine breakdown, arrival of rush orders and cancellation of orders affect the schedule of the plant. Reactive scheduling is generation of a new schedule which has minimum deviation from the original schedule in spite of the occurrence of unexpected events in the plant operation. Recently, Shaik & Floudas (2009) proposed a novel unified model for short-term scheduling of multipurpose batch plants using unit-specific event-based continuous time representation. In this paper, we extend the model of Shaik & Floudas (2009) to handle reactive scheduling.
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Susan E. Meyer; Dana Quinney; Jay Weaver
2006-01-01
Population viability analysis (PVA) is a valuable tool for rare plant conservation, but PVA for plants with persistent seed banks is difficult without reliable information on seed bank processes. We modeled the population dynamics of the Snake River Plains ephemeral Lepidium papilliferum using data from an 11-yr artificial seed bank experiment to estimate age-specific...
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NASA Astrophysics Data System (ADS)
Istanbulluoglu, Erkan; Bras, Rafael L.
2005-06-01
Topography acts as a template for numerous landscape processes that include hydrologic, ecologic, and biologic phenomena. These processes not only interact with each other but also contribute to shaping the landscape as they influence geomorphic processes. We have investigated the effects of vegetation on thresholds for channel initiation and landform evolution using both analytical and numerical approaches. Vegetation is assumed to form a uniform ground cover. Runoff erosion is modeled based on a power function of excess shear stress, in which shear stress efficiency is inversely proportional to vegetation cover. This approach is validated using data. Plant effect on slope stability is represented by additional cohesion provided by plant roots. Vegetation cover is assumed to reduce sediment transport rates due to physical creep processes (rainsplash, dry ravel, and expansion and contraction of sediments) according to a negative exponential relationship. Vegetation grows as a function of both available cover and unoccupied space by plants and is killed by geomorphic disturbances (runoff erosion and landsliding) and wildfires. Analytical results suggest that in an equilibrium basin with a fixed vegetation cover, plants may cause a transition in the dominant erosion process at the channel head. A runoff erosion-dominated landscape, under none or poor vegetation cover, may become landslide dominated under a denser vegetation cover. The sign of the predicted relationship between drainage density and vegetation cover depends on the relative influence of vegetation on different erosion phenomena. With model parameter values representative of the Oregon Coast Range (OCR), numerical experiments conducted using the Channel Hillslope Integrated Landscape Development (CHILD) model confirm the findings based on the analytical theory. A highly dissected fluvial landscape emerges when surface is assumed bare. When vegetation cover is modeled, landscape relief increases, resulting in hollow erosion dominated by landsliding. Interestingly, our simulations underscore the importance of vegetation disturbances by geomorphic events and wildfires on the landscape structure. Simulated landscapes resemble real-world catchments in the OCR when such disturbances are considered.
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ASPEN simulation of a fixed-bed integrated gasification combined-cycle power plant
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stone, K.R.
1986-03-01
A fixed-bed integrated gasification combined-cycle (IGCC) power plant has been modeled using the Advanced System for Process ENgineering (ASPEN). The ASPEN simulation is based on a conceptual design of a 509-MW IGCC power plant that uses British Gas Corporation (BGC)/Lurgi slagging gasifiers and the Lurgi acid gas removal process. The 39.3-percent thermal efficiency of the plant that was calculated by the simulation compares very favorably with the 39.4 percent that was reported by EPRI. The simulation addresses only thermal performance and does not calculate capital cost or process economics. Portions of the BGC-IGCC simulation flowsheet are based on the SLAGGERmore » fixed-bed gasifier model (Stefano May 1985), and the Kellogg-Rust-Westinghouse (KRW) iGCC, and the Texaco-IGCC simulations (Stone July 1985) that were developed at the Department of Energy (DOE), Morgantown Energy Technology Center (METC). The simulation runs in 32 minutes of Central Processing Unit (CPU) time on the VAX-11/780. The BGC-IGCC simulation was developed to give accurate mass and energy balances and to track coal tars and environmental species such as SO/sub x/ and NO/sub x/ for a fixed-bed, coal-to-electricity system. This simulation is the third in a series of three IGCC simulations that represent fluidized-bed, entrained-flow, and fixed-bed gasification processes. Alternate process configurations can be considered by adding, deleting, or rearranging unit operation blocks. The gasifier model is semipredictive; it can properly respond to a limited range of coal types and gasifier operating conditions. However, some models in the flowsheet are based on correlations that were derived from the EPRI study, and are therefore limited to coal types and operating conditions that are reasonably close to those given in the EPRI design. 4 refs., 7 figs., 2 tabs.« less
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An Evaluative Review of Simulated Dynamic Smart 3d Objects
NASA Astrophysics Data System (ADS)
Romeijn, H.; Sheth, F.; Pettit, C. J.
2012-07-01
Three-dimensional (3D) modelling of plants can be an asset for creating agricultural based visualisation products. The continuum of 3D plants models ranges from static to dynamic objects, also known as smart 3D objects. There is an increasing requirement for smarter simulated 3D objects that are attributed mathematically and/or from biological inputs. A systematic approach to plant simulation offers significant advantages to applications in agricultural research, particularly in simulating plant behaviour and the influences of external environmental factors. This approach of 3D plant object visualisation is primarily evident from the visualisation of plants using photographed billboarded images, to more advanced procedural models that come closer to simulating realistic virtual plants. However, few programs model physical reactions of plants to external factors and even fewer are able to grow plants based on mathematical and/or biological parameters. In this paper, we undertake an evaluation of plant-based object simulation programs currently available, with a focus upon the components and techniques involved in producing these objects. Through an analytical review process we consider the strengths and weaknesses of several program packages, the features and use of these programs and the possible opportunities in deploying these for creating smart 3D plant-based objects to support agricultural research and natural resource management. In creating smart 3D objects the model needs to be informed by both plant physiology and phenology. Expert knowledge will frame the parameters and procedures that will attribute the object and allow the simulation of dynamic virtual plants. Ultimately, biologically smart 3D virtual plants that react to changes within an environment could be an effective medium to visually represent landscapes and communicate land management scenarios and practices to planners and decision-makers.
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Optimal plant nitrogen use improves model representation of vegetation response to elevated CO2
NASA Astrophysics Data System (ADS)
Caldararu, Silvia; Kern, Melanie; Engel, Jan; Zaehle, Sönke
2017-04-01
Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as optimal biomass allocation between above- and belowground components in response to nutrient and water availability. The underlying hypothesis is that plants adjust their use of nitrogen in response to environmental conditions and nutrient availability in order to maximise biomass growth. We show that for two FACE (Free Air CO2 enrichment) experiments, the Duke forest and Oak Ridge forest sites, the model can better predict vegetation responses over the duration of the experiment when optimal processes are included. Specifically, under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration as well as increased biomass allocation to fine roots, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry predict a quick onset of N limitation.Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as optimal biomass allocation between above- and belowground components in response to nutrient and water availability. The underlying hypothesis is that plants adjust their use of nitrogen in response to environmental conditions and nutrient availability in order to maximise biomass growth. We show that for two FACE (Free Air CO2 enrichment) experiments, the Duke forest and Oak Ridge forest sites, the model can better predict vegetation responses over the duration of the experiment when optimal processes are included. Specifically, under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration as well as increased biomass allocation to fine roots, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry predict a quick onset of N limitation.
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Jofre, J; Ollé, E; Ribas, F; Vidal, A; Lucena, F
1995-01-01
The presence of bacteriophages at different stages in three drinking water treatment plants was evaluated to study the usefulness of phages as model organisms for assessing the efficiency of the processes. The bacteriophages tested were somatic coliphages, F-specific coliphages, and phages infecting Bacteroides fragilis. The presence of enteroviruses and currently used bacterial indicators was also determined. Most bacteriophages were removed during the prechlorination-flocculation-sedimentation step. In these particular treatment plants, which include prechlorination, phages were, in general, more resistant to the treatment processes than present bacterial indicators, with the exception, in some cases, of clostridia. Bacteriophages infecting B. fragilis were found to be more resistant to water treatment than either somatic or F-specific coliphages or even clostridia. Enteric viruses were found only in untreated water in low numbers, and consequently, the efficiency of the plants in the removal of viruses could not be evaluated with precision. The numbers and frequencies of detection of the various microorganisms in water samples taken in the distribution network served by the three plants confirm the results found in the finished water at the plants. PMID:7574632
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Station Blackout: A case study in the interaction of mechanistic and probabilistic safety analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Curtis Smith; Diego Mandelli; Cristian Rabiti
2013-11-01
The ability to better characterize and quantify safety margins is important to improved decision making about nuclear power plant design, operation, and plant life extension. As research and development (R&D) in the light-water reactor (LWR) Sustainability (LWRS) Program and other collaborative efforts yield new data, sensors, and improved scientific understanding of physical processes that govern the aging and degradation of plant SSCs needs and opportunities to better optimize plant safety and performance will become known. The purpose of the Risk Informed Safety Margin Characterization (RISMC) Pathway R&D is to support plant decisions for risk-informed margin management with the aim tomore » improve economics, reliability, and sustain safety of current NPPs. In this paper, we describe the RISMC analysis process illustrating how mechanistic and probabilistic approaches are combined in order to estimate a safety margin. We use the scenario of a “station blackout” wherein offsite power and onsite power is lost, thereby causing a challenge to plant safety systems. We describe the RISMC approach, illustrate the station blackout modeling, and contrast this with traditional risk analysis modeling for this type of accident scenario.« less
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Benchmark Simulation Model No 2: finalisation of plant layout and default control strategy.
Nopens, I; Benedetti, L; Jeppsson, U; Pons, M-N; Alex, J; Copp, J B; Gernaey, K V; Rosen, C; Steyer, J-P; Vanrolleghem, P A
2010-01-01
The COST/IWA Benchmark Simulation Model No 1 (BSM1) has been available for almost a decade. Its primary purpose has been to create a platform for control strategy benchmarking of activated sludge processes. The fact that the research work related to the benchmark simulation models has resulted in more than 300 publications worldwide demonstrates the interest in and need of such tools within the research community. Recent efforts within the IWA Task Group on "Benchmarking of control strategies for WWTPs" have focused on an extension of the benchmark simulation model. This extension aims at facilitating control strategy development and performance evaluation at a plant-wide level and, consequently, includes both pretreatment of wastewater as well as the processes describing sludge treatment. The motivation for the extension is the increasing interest and need to operate and control wastewater treatment systems not only at an individual process level but also on a plant-wide basis. To facilitate the changes, the evaluation period has been extended to one year. A prolonged evaluation period allows for long-term control strategies to be assessed and enables the use of control handles that cannot be evaluated in a realistic fashion in the one week BSM1 evaluation period. In this paper, the finalised plant layout is summarised and, as was done for BSM1, a default control strategy is proposed. A demonstration of how BSM2 can be used to evaluate control strategies is also given.
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Markov modeling and reliability analysis of urea synthesis system of a fertilizer plant
NASA Astrophysics Data System (ADS)
Aggarwal, Anil Kr.; Kumar, Sanjeev; Singh, Vikram; Garg, Tarun Kr.
2015-12-01
This paper deals with the Markov modeling and reliability analysis of urea synthesis system of a fertilizer plant. This system was modeled using Markov birth-death process with the assumption that the failure and repair rates of each subsystem follow exponential distribution. The first-order Chapman-Kolmogorov differential equations are developed with the use of mnemonic rule and these equations are solved with Runga-Kutta fourth-order method. The long-run availability, reliability and mean time between failures are computed for various choices of failure and repair rates of subsystems of the system. The findings of the paper are discussed with the plant personnel to adopt and practice suitable maintenance policies/strategies to enhance the performance of the urea synthesis system of the fertilizer plant.
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Kim, Tania N; Underwood, Nora; Inouye, Brian D
2013-08-01
Insect herbivores can affect plant abundance and community composition, and theory suggests that herbivores influence plant communities by altering interspecific interactions among plants. Because the outcome of interspecific interactions is influenced by the per capita competitive ability of plants, density dependence, and intrinsic rates of increase, measuring herbivore effects on all these processes is necessary to understand the mechanisms by which herbivores influence plant communities. We fit alternative competition models to data from a response surface experiment conducted over four years to examine how herbivores affected the outcome of competition between two perennial plants, Solidago altissima and Solanum carolinense. Within a growing season, herbivores reduced S. carolinense plant size but did not affect the size of S. altissima, which exhibited compensatory growth. Across seasons, herbivores did not affect S. carolinense density or biomass but reduced both the density and population growth of S. altissima. The best-fit models indicated that the effects of herbivores varied with year. In some years, herbivores increased the per capita competitive effect of S. altissima on S. carolinense; in other years, herbivores influenced the intrinsic rate of increase of S. altissima. We examined possible herbivore effects on the longer-term outcome of competition (over the time scale of a typical old-field habitat), using simulations based on the best-fit models. In the absence of herbivores, plant coexistence was observed. In the presence of herbivores, S. carolinense was excluded by S. altissima in 72.3% of the simulations. We demonstrate that herbivores can influence the outcome of competition through changes in both per capita competitive effects and intrinsic rates of increase. We discuss the implications of these results for ecological succession and biocontrol.
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Lohraseb, Iman; Collins, Nicholas C.
2017-01-01
Abstract There is a growing consensus in the literature that rising temperatures influence the rates of biomass accumulation by shortening the development of plant organs and the whole plant and by altering the rates of respiration and photosynthesis. A model describing the net effects of these processes on biomass would be useful, but would need to reconcile reported differences in the effects of night and day temperature on plant productivity. In this study, the working hypothesis was that the temperature responses of CO2 assimilation and plant development rates were divergent, and that their net effects could explain observed differences in biomass accumulation. In wheat (Triticum aestivum) plants, we followed the temperature responses of photosynthesis, respiration and leaf elongation, and confirmed that their responses diverged. We measured the amount of carbon assimilated per ‘unit of plant development’ in each scenario and compared it to the biomass that accumulated in growing leaves and grains. Our results suggested that, up to a temperature optimum, the rate of any developmental process increased with temperature more rapidly than that of CO2 assimilation and that this discrepancy, summarised by the CO2 assimilation rate per unit of plant development, could explain the observed reductions in biomass accumulation in plant organs under high temperatures. The model described the effects of night and day temperature equally well, and offers a simple framework for describing the effects of temperature on plant growth. PMID:28069595
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Manufacturing Economics of Plant-Made Biologics: Case Studies in Therapeutic and Industrial Enzymes
Tusé, Daniel; McDonald, Karen A.
2014-01-01
Production of recombinant biologics in plants has received considerable attention as an alternative platform to traditional microbial and animal cell culture. Industrially relevant features of plant systems include proper eukaryotic protein processing, inherent safety due to lack of adventitious agents, more facile scalability, faster production (transient systems), and potentially lower costs. Lower manufacturing cost has been widely claimed as an intuitive feature of the platform by the plant-made biologics community, even though cost information resides within a few private companies and studies accurately documenting such an advantage have been lacking. We present two technoeconomic case studies representing plant-made enzymes for diverse applications: human butyrylcholinesterase produced indoors for use as a medical countermeasure and cellulases produced in the field for the conversion of cellulosic biomass into ethanol as a fuel extender. Production economics were modeled based on results reported with the latest-generation expression technologies on Nicotiana host plants. We evaluated process unit operations and calculated bulk active and per-dose or per-unit costs using SuperPro Designer modeling software. Our analyses indicate that substantial cost advantages over alternative platforms can be achieved with plant systems, but these advantages are molecule/product-specific and depend on the relative cost-efficiencies of alternative sources of the same product. PMID:24977145
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Manufacturing economics of plant-made biologics: case studies in therapeutic and industrial enzymes.
Tusé, Daniel; Tu, Tiffany; McDonald, Karen A
2014-01-01
Production of recombinant biologics in plants has received considerable attention as an alternative platform to traditional microbial and animal cell culture. Industrially relevant features of plant systems include proper eukaryotic protein processing, inherent safety due to lack of adventitious agents, more facile scalability, faster production (transient systems), and potentially lower costs. Lower manufacturing cost has been widely claimed as an intuitive feature of the platform by the plant-made biologics community, even though cost information resides within a few private companies and studies accurately documenting such an advantage have been lacking. We present two technoeconomic case studies representing plant-made enzymes for diverse applications: human butyrylcholinesterase produced indoors for use as a medical countermeasure and cellulases produced in the field for the conversion of cellulosic biomass into ethanol as a fuel extender. Production economics were modeled based on results reported with the latest-generation expression technologies on Nicotiana host plants. We evaluated process unit operations and calculated bulk active and per-dose or per-unit costs using SuperPro Designer modeling software. Our analyses indicate that substantial cost advantages over alternative platforms can be achieved with plant systems, but these advantages are molecule/product-specific and depend on the relative cost-efficiencies of alternative sources of the same product.
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Parameterization of sparse vegetation in thermal images of natural ground landscapes
NASA Astrophysics Data System (ADS)
Agassi, Eyal; Ben-Yosef, Nissim
1997-10-01
The radiant statistics of thermal images of desert terrain scenes and their temporal behavior have been fully understood and well modeled. Unlike desert scenes, most natural terrestrial landscapes contain vegetative objects. A plant is a living object that regulates its temperature through evapotranspiration of leaf stomata, and plant interaction with the outside world is influenced by its physiological processes. Therefore, the heat balance equation for a vegetative object differs from that for an inorganic surface element. Despite this difficulty, plants can be incorporated into the desert surface model when an effective heat conduction parameter is associated with vegetation. Due to evapotranspiration, the effective heat conduction of plants during daytime is much higher than at night. As a result, plants (mainly trees and bushes) are usually the coldest objects in the scene in the daytime while they are not necessarily the warmest objects at night. The parameterization of vegetative objects in terms of effective heat conduction enables the extension of the desert terrain model for scenes with sparse vegetation and the estimation of their radiant statistics and their diurnal behavior. The effective heat conduction image can serve as a tool for vegetation type classification and assessment of the dominant physical process that determinate thermal image properties.
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Plant interactions alter the predictions of metabolic scaling theory.
Lin, Yue; Berger, Uta; Grimm, Volker; Huth, Franka; Weiner, Jacob
2013-01-01
Metabolic scaling theory (MST) is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of -4/3 between mean individual biomass and density during density-dependent mortality (self-thinning). Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms' internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric), and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than -4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.
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Predicting Changes in Arctic Tundra Vegetation: Towards an Understanding of Plant Trait Uncertainty
NASA Astrophysics Data System (ADS)
Euskirchen, E. S.; Serbin, S.; Carman, T.; Iversen, C. M.; Salmon, V.; Helene, G.; McGuire, A. D.
2017-12-01
Arctic tundra plant communities are currently undergoing unprecedented changes in both composition and distribution under a warming climate. Predicting how these dynamics may play out in the future is important since these vegetation shifts impact both biogeochemical and biogeophysical processes. More precise estimates of these future vegetation shifts is a key challenge due to both a scarcity of data with which to parameterize vegetation models, particularly in the Arctic, as well as a limited understanding of the importance of each of the model parameters and how they may vary over space and time. Here, we incorporate newly available field data from arctic Alaska into a dynamic vegetation model specifically developed to take into account a particularly wide array of plant species as well as the permafrost soils of the arctic tundra (the Terrestrial Ecosystem Model with Dynamic Vegetation and Dynamic Organic Soil, Terrestrial Ecosystem Model; DVM-DOS-TEM). We integrate the model within the Predicative Ecosystem Analyzer (PEcAn), an open-source integrated ecological bioinformatics toolbox that facilitates the flows of information into and out of process models and model-data integration. We use PEcAn to evaluate the plant functional traits that contribute most to model variability based on a sensitivity analysis. We perform this analysis for the dominant types of tundra in arctic Alaska, including heath, shrub, tussock and wet sedge tundra. The results from this analysis will help inform future data collection in arctic tundra and reduce model uncertainty, thereby improving our ability to simulate Arctic vegetation structure and function in response to global change.
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Xie, Wen-Ming; Zeng, Raymond J; Li, Wen-Wei; Wang, Guo-Xiang; Zhang, Li-Min
2018-05-31
Reversed A 2 O process (anoxic-anaerobic-aerobic) and conventional A 2 O process (anaerobic-anoxic-aerobic) are widely used in many wastewater treatment plants (WWTPs) in Asia. However, at present, there are still no consistent results to figure out which process has better total phosphorous (TP) removal performance and the mechanism for this difference was not clear yet. In this study, the treatment performances of both processes were compared in the same full-scale WWTP and the TP removal dynamics was analyzed by a modeling method. The treatment performance of full-scale WWTP showed the TP removal efficiency of the reversed A 2 O process was more efficient than in the conventional A 2 O process. The modeling results further reveal that the TP removal depends highly on the concentration and composition of influent COD. It had more efficient TP removal than the conventional A 2 O process only under conditions of sufficient influent COD and high fermentation products content. This study may lay a foundation for appropriate selection and optimization of treatment processes to suit practical wastewater properties.
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NASA Astrophysics Data System (ADS)
Haslinger, Edith; Goldbrunner, Johann; Dietzel, Martin; Leis, Albrecht; Boch, Ronny; Knauss, Ralf; Hippler, Dorothee; Shirbaz, Andrea; Fröschl, Heinz; Wyhlidal, Stefan; Plank, Otmar; Gold, Marlies; Elster, Daniel
2017-04-01
During the exploitation of thermal water for the use in a geothermal plant a series of hydrochemical reactions such as solution and precipitation processes (scaling) or corrosion processes can be caused by pressure and temperature changes and degassing of the thermal water. Operators of hydrogeothermal plants are often confronted with precipitations in water-bearing parts of their plant, such as heat exchangers and pipes, which result in considerable costs for cleaning or remediation or the use of inhibitors. In the worst case, scaling and corrosion can lead to the abandonment of the system. The effects of the fluids on the technical facilities of hydrogeothermal plants are usually difficult to predict. This applies in particular to the long-term effects in the exploitation and use as well as the aspect of the reinjection of the fluids. In publications and guides for thermal water use in Austria, it is emphasized that the hydrochemical conditions have to be checked during the operation of geothermal plants, but precise directives and thus guidance for operators as well as a scientific investigations on this topic are almost completely missing today. The aim of the research project NoScale was the assessment of deep thermal water bodies in different geological reservoirs in Austria and Bavaria and therefore different hydrochemical compositions with regard to their scaling and corrosion potential in geothermal use. In the course of parallel chemical and mineralogical laboratory investigations, conclusions were drawn about the effects of thermal water on different technical components of hydrogeothermal plants and on the other hand a data basis for the model simulation of the relevant hydrochemical processes was developed. Subsequently, on the basis of detailed hydrochemical model calculations, possible effects of the use of the thermal waters on the technical components of the geothermal plants were shown. This approach of complex process modeling, detailed laboratory studies and experimental approaches has not been followed in Austria so far. The research results contribute significantly to the increased visibility of potential risks of the exploitation and use of thermal water. Thus, the project NoScale supports the operators of hydrogeothermal plants to assess risks of scaling in corrosion already in the pre-drilling phase, which leads to a much more energy and cost efficient operation.
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Model parameters for representative wetland plant functional groups
Williams, Amber S.; Kiniry, James R.; Mushet, David M.; Smith, Loren M.; McMurry, Scott T.; Attebury, Kelly; Lang, Megan; McCarty, Gregory W.; Shaffer, Jill A.; Effland, William R.; Johnson, Mari-Vaughn V.
2017-01-01
Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (k), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process-based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on-the-ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and k variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (Eleocharis macrostachya), reed canary grass (Phalaris arundinacea), smartweed (Polygonum spp.), cattail (Typha spp.), and hardstem bulrush (Schoenoplectus acutus). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process-based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in adjacent areas as they affect wetlands.
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Statistical design and analysis for plant cover studies with multiple sources of observation errors
Wright, Wilson; Irvine, Kathryn M.; Warren, Jeffrey M .; Barnett, Jenny K.
2017-01-01
Effective wildlife habitat management and conservation requires understanding the factors influencing distribution and abundance of plant species. Field studies, however, have documented observation errors in visually estimated plant cover including measurements which differ from the true value (measurement error) and not observing a species that is present within a plot (detection error). Unlike the rapid expansion of occupancy and N-mixture models for analysing wildlife surveys, development of statistical models accounting for observation error in plants has not progressed quickly. Our work informs development of a monitoring protocol for managed wetlands within the National Wildlife Refuge System.Zero-augmented beta (ZAB) regression is the most suitable method for analysing areal plant cover recorded as a continuous proportion but assumes no observation errors. We present a model extension that explicitly includes the observation process thereby accounting for both measurement and detection errors. Using simulations, we compare our approach to a ZAB regression that ignores observation errors (naïve model) and an “ad hoc” approach using a composite of multiple observations per plot within the naïve model. We explore how sample size and within-season revisit design affect the ability to detect a change in mean plant cover between 2 years using our model.Explicitly modelling the observation process within our framework produced unbiased estimates and nominal coverage of model parameters. The naïve and “ad hoc” approaches resulted in underestimation of occurrence and overestimation of mean cover. The degree of bias was primarily driven by imperfect detection and its relationship with cover within a plot. Conversely, measurement error had minimal impacts on inferences. We found >30 plots with at least three within-season revisits achieved reasonable posterior probabilities for assessing change in mean plant cover.For rapid adoption and application, code for Bayesian estimation of our single-species ZAB with errors model is included. Practitioners utilizing our R-based simulation code can explore trade-offs among different survey efforts and parameter values, as we did, but tuned to their own investigation. Less abundant plant species of high ecological interest may warrant the additional cost of gathering multiple independent observations in order to guard against erroneous conclusions.
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Young, Kendal E.; Abbott, Laurie B.; Caldwell, Colleen A.; Schrader, T. Scott
2013-01-01
The key to reducing ecological and economic damage caused by invasive plant species is to locate and eradicate new invasions before they threaten native biodiversity and ecological processes. We used Landsat Enhanced Thematic Mapper Plus imagery to estimate suitable environments for four invasive plants in Big Bend National Park, southwest Texas, using a presence-only modeling approach. Giant reed (Arundo donax), Lehmann lovegrass (Eragrostis lehmanniana), horehound (Marrubium vulgare) and buffelgrass (Pennisteum ciliare) were selected for remote sensing spatial analyses. Multiple dates/seasons of imagery were used to account for habitat conditions within the study area and to capture phenological differences among targeted species and the surrounding landscape. Individual species models had high (0.91 to 0.99) discriminative ability to differentiate invasive plant suitable environments from random background locations. Average test area under the receiver operating characteristic curve (AUC) ranged from 0.91 to 0.99, indicating that plant predictive models exhibited high discriminative ability to differentiate suitable environments for invasive plant species from random locations. Omission rates ranged from <1.0 to 18%. We demonstrated that useful models estimating suitable environments for invasive plants may be created with <50 occurrence locations and that reliable modeling using presence-only datasets can be powerful tools for land managers.
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Database management systems for process safety.
Early, William F
2006-03-17
Several elements of the process safety management regulation (PSM) require tracking and documentation of actions; process hazard analyses, management of change, process safety information, operating procedures, training, contractor safety programs, pre-startup safety reviews, incident investigations, emergency planning, and compliance audits. These elements can result in hundreds of actions annually that require actions. This tracking and documentation commonly is a failing identified in compliance audits, and is difficult to manage through action lists, spreadsheets, or other tools that are comfortably manipulated by plant personnel. This paper discusses the recent implementation of a database management system at a chemical plant and chronicles the improvements accomplished through the introduction of a customized system. The system as implemented modeled the normal plant workflows, and provided simple, recognizable user interfaces for ease of use.
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Nitrogen uptake and utilization by intact plants
NASA Technical Reports Server (NTRS)
Raper, C. D., Jr.; Tolley-Henry, L. C.
1986-01-01
The results of experiments support the proposed conceptual model that relates nitrogen uptake activity by plants as a balanced interdependence between the carbon-supplying function of the shoot and the nitrogen-supplying function of the roots. The data are being used to modify a dynamic simulation of plant growth, which presently describes carbon flows through the plant, to describe nitrogen uptake and assimilation within the plant system. Although several models have been proposed to predict nitrogen uptake and partitioning, they emphasize root characteristics affecting nutrient uptake and relay on empirical methods to describe the relationship between nitrogen and carbon flows within the plant. Researchers, on the other hand, propose to continue to attempt a mechanistic solution in which the effects of environment on nitrogen (as well as carbon) assimilation are incorporated through their direct effects on photosynthesis, respiration, and aging processes.
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NASA Astrophysics Data System (ADS)
Qian, Xiaoshan
2018-01-01
The traditional model of evaporation process parameters have continuity and cumulative characteristics of the prediction error larger issues, based on the basis of the process proposed an adaptive particle swarm neural network forecasting method parameters established on the autoregressive moving average (ARMA) error correction procedure compensated prediction model to predict the results of the neural network to improve prediction accuracy. Taking a alumina plant evaporation process to analyze production data validation, and compared with the traditional model, the new model prediction accuracy greatly improved, can be used to predict the dynamic process of evaporation of sodium aluminate solution components.
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The dynamic relationship between plant architecture and competition
Ford, E. David
2014-01-01
In this review, structural and functional changes are described in single-species, even-aged, stands undergoing competition for light. Theories of the competition process as interactions between whole plants have been advanced but have not been successful in explaining these changes and how they vary between species or growing conditions. This task now falls to researchers in plant architecture. Research in plant architecture has defined three important functions of individual plants that determine the process of canopy development and competition: (i) resource acquisition plasticity; (ii) morphogenetic plasticity; (iii) architectural variation in efficiency of interception and utilization of light. In this review, this research is synthesized into a theory for competition based on five groups of postulates about the functioning of plants in stands. Group 1: competition for light takes place at the level of component foliage and branches. Group 2: the outcome of competition is determined by the dynamic interaction between processes that exert dominance and processes that react to suppression. Group 3: species differences may affect both exertion of dominance and reaction to suppression. Group 4: individual plants may simultaneously exhibit, in different component parts, resource acquisition and morphogenetic plasticity. Group 5: mortality is a time-delayed response to suppression. Development of architectural models when combined with field investigations is identifying research needed to develop a theory of architectural influences on the competition process. These include analyses of the integration of foliage and branch components into whole-plant growth and precise definitions of environmental control of morphogenetic plasticity and its interaction with acquisition of carbon for plant growth. PMID:24987396
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The dynamic relationship between plant architecture and competition.
Ford, E David
2014-01-01
In this review, structural and functional changes are described in single-species, even-aged, stands undergoing competition for light. Theories of the competition process as interactions between whole plants have been advanced but have not been successful in explaining these changes and how they vary between species or growing conditions. This task now falls to researchers in plant architecture. Research in plant architecture has defined three important functions of individual plants that determine the process of canopy development and competition: (i) resource acquisition plasticity; (ii) morphogenetic plasticity; (iii) architectural variation in efficiency of interception and utilization of light. In this review, this research is synthesized into a theory for competition based on five groups of postulates about the functioning of plants in stands. Group 1: competition for light takes place at the level of component foliage and branches. Group 2: the outcome of competition is determined by the dynamic interaction between processes that exert dominance and processes that react to suppression. Group 3: species differences may affect both exertion of dominance and reaction to suppression. Group 4: individual plants may simultaneously exhibit, in different component parts, resource acquisition and morphogenetic plasticity. Group 5: mortality is a time-delayed response to suppression. Development of architectural models when combined with field investigations is identifying research needed to develop a theory of architectural influences on the competition process. These include analyses of the integration of foliage and branch components into whole-plant growth and precise definitions of environmental control of morphogenetic plasticity and its interaction with acquisition of carbon for plant growth.
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[Some comments on ecological field].
Wang, D
2000-06-01
Based on the data of plant ecological field studies, this paper reviewed the conception of ecological field, field eigenfunctions, graphs of ecological field and its application of ecological field theory in explaining plant interactions. It is suggested that the basic character of ecological field is material, and based on the current research level, it is not sure whether ecological field is a kind of specific field different from general physical field. The author gave some comments on the formula and estimation of parameters of basic field function-ecological potential model on ecological field. Both models have their own characteristics and advantages in specific conditions. The author emphasized that ecological field had even more meaning of ecological methodology, and applying ecological field theory in describing the types and processes of plant interactions had three characteristics: quantitative, synthetic and intuitionistic. Field graphing might provide a new way to ecological studies, especially applying the ecological field theory might give an appropriate quantitative explanation for the dynamic process of plant populations (coexistence and interference competition).
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Photogrammetry and computer-aided piping design
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keneflick, J.F.; Chirillo, R.D.
1985-02-18
Three-dimensional measurements taken from photographs of a plant model can be digitized and linked with computer-aided piping design. This can short-cut the design and construction of new plants and expedite repair and retrofitting projects. Some designers bridge the gap between model and computer by digitizing from orthographic prints obtained via orthography or the laser scanning of model sections. Such valve or fitting then processed is described in this paper. The marriage of photogrammetry and computer-aided piping design can economically produce such numerical drawings.
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Inter-species competition-facilitation in stochastic riparian vegetation dynamics.
Tealdi, Stefano; Camporeale, Carlo; Ridolfi, Luca
2013-02-07
Riparian vegetation is a highly dynamic community that lives on river banks and which depends to a great extent on the fluvial hydrology. The stochasticity of the discharge and erosion/deposition processes in fact play a key role in determining the distribution of vegetation along a riparian transect. These abiotic processes interact with biotic competition/facilitation mechanisms, such as plant competition for light, water, and nutrients. In this work, we focus on the dynamics of plants characterized by three components: (1) stochastic forcing due to river discharges, (2) competition for resources, and (3) inter-species facilitation due to the interplay between vegetation and fluid dynamics processes. A minimalist stochastic bio-hydrological model is proposed for the dynamics of the biomass of two vegetation species: one species is assumed dominant and slow-growing, the other is subdominant, but fast-growing. The stochastic model is solved analytically and the probability density function of the plant biomasses is obtained as a function of both the hydrologic and biologic parameters. The impact of the competition/facilitation processes on the distribution of vegetation species along the riparian transect is investigated and remarkable effects are observed. Finally, a good qualitative agreement is found between the model results and field data. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Dunnett, Alex J; Adjiman, Claire S; Shah, Nilay
2008-01-01
Background Lignocellulosic bioethanol technologies exhibit significant capacity for performance improvement across the supply chain through the development of high-yielding energy crops, integrated pretreatment, hydrolysis and fermentation technologies and the application of dedicated ethanol pipelines. The impact of such developments on cost-optimal plant location, scale and process composition within multiple plant infrastructures is poorly understood. A combined production and logistics model has been developed to investigate cost-optimal system configurations for a range of technological, system scale, biomass supply and ethanol demand distribution scenarios specific to European agricultural land and population densities. Results Ethanol production costs for current technologies decrease significantly from $0.71 to $0.58 per litre with increasing economies of scale, up to a maximum single-plant capacity of 550 × 106 l year-1. The development of high-yielding energy crops and consolidated bio-processing realises significant cost reductions, with production costs ranging from $0.33 to $0.36 per litre. Increased feedstock yields result in systems of eight fully integrated plants operating within a 500 × 500 km2 region, each producing between 1.24 and 2.38 × 109 l year-1 of pure ethanol. A limited potential for distributed processing and centralised purification systems is identified, requiring developments in modular, ambient pretreatment and fermentation technologies and the pipeline transport of pure ethanol. Conclusion The conceptual and mathematical modelling framework developed provides a valuable tool for the assessment and optimisation of the lignocellulosic bioethanol supply chain. In particular, it can provide insight into the optimal configuration of multiple plant systems. This information is invaluable in ensuring (near-)cost-optimal strategic development within the sector at the regional and national scale. The framework is flexible and can thus accommodate a range of processing tasks, logistical modes, by-product markets and impacting policy constraints. Significant scope for application to real-world case studies through dynamic extensions of the formulation has been identified. PMID:18662392
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Effects of ionic strength and ion pairing on (plant-wide) modelling of anaerobic digestion.
Solon, Kimberly; Flores-Alsina, Xavier; Mbamba, Christian Kazadi; Volcke, Eveline I P; Tait, Stephan; Batstone, Damien; Gernaey, Krist V; Jeppsson, Ulf
2015-03-01
Plant-wide models of wastewater treatment (such as the Benchmark Simulation Model No. 2 or BSM2) are gaining popularity for use in holistic virtual studies of treatment plant control and operations. The objective of this study is to show the influence of ionic strength (as activity corrections) and ion pairing on modelling of anaerobic digestion processes in such plant-wide models of wastewater treatment. Using the BSM2 as a case study with a number of model variants and cationic load scenarios, this paper presents the effects of an improved physico-chemical description on model predictions and overall plant performance indicators, namely effluent quality index (EQI) and operational cost index (OCI). The acid-base equilibria implemented in the Anaerobic Digestion Model No. 1 (ADM1) are modified to account for non-ideal aqueous-phase chemistry. The model corrects for ionic strength via the Davies approach to consider chemical activities instead of molar concentrations. A speciation sub-routine based on a multi-dimensional Newton-Raphson (NR) iteration method is developed to address algebraic interdependencies. The model also includes ion pairs that play an important role in wastewater treatment. The paper describes: 1) how the anaerobic digester performance is affected by physico-chemical corrections; 2) the effect on pH and the anaerobic digestion products (CO2, CH4 and H2); and, 3) how these variations are propagated from the sludge treatment to the water line. Results at high ionic strength demonstrate that corrections to account for non-ideal conditions lead to significant differences in predicted process performance (up to 18% for effluent quality and 7% for operational cost) but that for pH prediction, activity corrections are more important than ion pairing effects. Both are likely to be required when precipitation is to be modelled. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Allaby, Robin G; Kistler, Logan; Gutaker, Rafal M; Ware, Roselyn; Kitchen, James L; Smith, Oliver; Clarke, Andrew C
2015-02-01
The colonization of the human environment by plants, and the consequent evolution of domesticated forms is increasingly being viewed as a co-evolutionary plant-human process that occurred over a long time period, with evidence for the co-evolutionary relationship between plants and humans reaching ever deeper into the hominin past. This developing view is characterized by a change in emphasis on the drivers of evolution in the case of plants. Rather than individual species being passive recipients of artificial selection pressures and ultimately becoming domesticates, entire plant communities adapted to the human environment. This evolutionary scenario leads to systems level genetic expectations from models that can be explored through ancient DNA and Next Generation Sequencing approaches. Emerging evidence suggests that domesticated genomes fit well with these expectations, with periods of stable complex evolution characterized by large amounts of change associated with relatively small selective value, punctuated by periods in which changes in one-half of the plant-hominin relationship cause rapid, low-complexity adaptation in the other. A corollary of a single plant-hominin co-evolutionary process is that clues about the initiation of the domestication process may well lie deep within the hominin lineage. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Zheng, Jinshui; Peng, Donghai; Chen, Ling; Liu, Hualin; Chen, Feng; Xu, Mengci; Ju, Shouyong; Ruan, Lifang; Sun, Ming
2016-07-27
Plant-parasitic nematodes were found in 4 of the 12 clades of phylum Nematoda. These nematodes in different clades may have originated independently from their free-living fungivorous ancestors. However, the exact evolutionary process of these parasites is unclear. Here, we sequenced the genome sequence of a migratory plant nematode, Ditylenchus destructor We performed comparative genomics among the free-living nematode, Caenorhabditis elegans and all the plant nematodes with genome sequences available. We found that, compared with C. elegans, the core developmental control processes underwent heavy reduction, though most signal transduction pathways were conserved. We also found D. destructor contained more homologies of the key genes in the above processes than the other plant nematodes. We suggest that Ditylenchus spp. may be an intermediate evolutionary history stage from free-living nematodes that feed on fungi to obligate plant-parasitic nematodes. Based on the facts that D. destructor can feed on fungi and has a relatively short life cycle, and that it has similar features to both C. elegans and sedentary plant-parasitic nematodes from clade 12, we propose it as a new model to study the biology, biocontrol of plant nematodes and the interaction between nematodes and plants. © 2016 The Author(s).
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Seed germination in parasitic plants: what insights can we expect from strigolactone research?
Brun, Guillaume; Braem, Lukas; Thoiron, Séverine; Gevaert, Kris; Goormachtig, Sofie; Delavault, Philippe
2018-04-23
Obligate root-parasitic plants belonging to the Orobanchaceae family are deadly pests for major crops all over the world. Because these heterotrophic plants severely damage their hosts even before emerging from the soil, there is an unequivocal need to design early and efficient methods for their control. The germination process of these species has probably undergone numerous selective pressure events in the course of evolution, in that the perception of host-derived molecules is a necessary condition for seeds to germinate. Although most of these molecules belong to the strigolactones, structurally different molecules have been identified. Since strigolactones are also classified as novel plant hormones that regulate several physiological processes other than germination, the use of autotrophic model plant species has allowed the identification of many actors involved in the strigolactone biosynthesis, perception, and signal transduction pathways. Nevertheless, many questions remain to be answered regarding the germination process of parasitic plants. For instance, how did parasitic plants evolve to germinate in response to a wide variety of molecules, while autotrophic plants do not? What particular features are associated with their lack of spontaneous germination? In this review, we attempt to illustrate to what extent conclusions from research into strigolactones could be applied to better understand the biology of parasitic plants.
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Soil moisture dynamics modeling considering multi-layer root zone.
Kumar, R; Shankar, V; Jat, M K
2013-01-01
The moisture uptake by plant from soil is a key process for plant growth and movement of water in the soil-plant system. A non-linear root water uptake (RWU) model was developed for a multi-layer crop root zone. The model comprised two parts: (1) model formulation and (2) moisture flow prediction. The developed model was tested for its efficiency in predicting moisture depletion in a non-uniform root zone. A field experiment on wheat (Triticum aestivum) was conducted in the sub-temperate sub-humid agro-climate of Solan, Himachal Pradesh, India. Model-predicted soil moisture parameters, i.e., moisture status at various depths, moisture depletion and soil moisture profile in the root zone, are in good agreement with experiment results. The results of simulation emphasize the utility of the RWU model across different agro-climatic regions. The model can be used for sound irrigation management especially in water-scarce humid, temperate, arid and semi-arid regions and can also be integrated with a water transport equation to predict the solute uptake by plant biomass.
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ORAM-SENTINEL{trademark} demonstration at Fitzpatrick. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, L.K.; Anderson, V.M.; Mohammadi, K.
1998-06-01
New York Power Authority, in cooperation with EPRI, installed the ORAM-SENTINEL{trademark} software at James A. Fitzpatrick (JAF) Nuclear Power Plant. This software incorporates models of safety systems and support systems that are used for defense-in-depth in the plant during outage and on-line periods. A secondary goal was to include some pre-analyzed risk results to validate the methodology for quantitative assessment of the plant risks during proposed on-line maintenance. During the past year, New York Power Authority personnel have become familiar with the formal computerized Safety Assessment process associated with on-line and outage maintenance. The report describes techniques and lessons learnedmore » during development of the ORAM-SENTINEL model at JAF. It overviews the systems important to the Safety Function Assessment Process and provides details on development of the Plant Transient Assessment process using the station emergency operating procedures. The assessment results are displayed by color (green, yellow, orange, red) to show decreasing safety conditions. The report describes use of the JAF Probabilistic Safety Assessment within the ORAM-SENTINEL code to calculate an instantaneous core damage frequency and the criteria by which this frequency is translated to a color indicator.« less
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Modelling the impacts of pests and diseases on agricultural systems.
Donatelli, M; Magarey, R D; Bregaglio, S; Willocquet, L; Whish, J P M; Savary, S
2017-07-01
The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems. Yield loss data collected in various current environments may no longer represent a adequate reference to develop tactical, decision-oriented, models for plant diseases and pests and their impacts, because of the ongoing changes in climate patterns. Process-based agricultural simulation modelling, on the other hand, appears to represent a viable methodology to estimate the impacts of these potential effects. A new generation of tools based on state-of-the-art knowledge and technologies is needed to allow systems analysis including key processes and their dynamics over appropriate suitable range of environmental variables. This paper offers a brief overview of the current state of development in coupling pest and disease models to crop models, and discusses technical and scientific challenges. We propose a five-stage roadmap to improve the simulation of the impacts caused by plant diseases and pests; i) improve the quality and availability of data for model inputs; ii) improve the quality and availability of data for model evaluation; iii) improve the integration with crop models; iv) improve the processes for model evaluation; and v) develop a community of plant pest and disease modelers.
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2012-09-01
ecological processes involve the invasion of non-native (exotic) species (USEPA 1999). Through direct biotic interactions (predation and competition) and...indirect interactions ( ecological engineering and habitat modification), invasive species can disrupt the natural population dynamics of native...species (USEPA 1999). Invasives can include noxious plants (i.e., plants that are listed by a state because of their unfavorable economic or ecological
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Pound, Michael P.; French, Andrew P.; Murchie, Erik H.; Pridmore, Tony P.
2014-01-01
Increased adoption of the systems approach to biological research has focused attention on the use of quantitative models of biological objects. This includes a need for realistic three-dimensional (3D) representations of plant shoots for quantification and modeling. Previous limitations in single-view or multiple-view stereo algorithms have led to a reliance on volumetric methods or expensive hardware to record plant structure. We present a fully automatic approach to image-based 3D plant reconstruction that can be achieved using a single low-cost camera. The reconstructed plants are represented as a series of small planar sections that together model the more complex architecture of the leaf surfaces. The boundary of each leaf patch is refined using the level-set method, optimizing the model based on image information, curvature constraints, and the position of neighboring surfaces. The reconstruction process makes few assumptions about the nature of the plant material being reconstructed and, as such, is applicable to a wide variety of plant species and topologies and can be extended to canopy-scale imaging. We demonstrate the effectiveness of our approach on data sets of wheat (Triticum aestivum) and rice (Oryza sativa) plants as well as a unique virtual data set that allows us to compute quantitative measures of reconstruction accuracy. The output is a 3D mesh structure that is suitable for modeling applications in a format that can be imported in the majority of 3D graphics and software packages. PMID:25332504
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Adaptive model predictive process control using neural networks
Buescher, K.L.; Baum, C.C.; Jones, R.D.
1997-08-19
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.
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Adaptive model predictive process control using neural networks
Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.
1997-01-01
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.
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Native Plant Uptake Model for Radioactive Waste Disposal Areas at the Nevada Test Site
DOE Office of Scientific and Technical Information (OSTI.GOV)
BROWN,THERESA J.; WIRTH,SHARON
1999-09-01
This report defines and defends the basic framework, methodology, and associated input parameters for modeling plant uptake of radionuclides for use in Performance Assessment (PA) activities of Radioactive Waste Management Sites (RWMS) at the Nevada Test Site (NTS). PAs are used to help determine whether waste disposal configurations meet applicable regulatory standards for the protection of human health, the environment, or both. Plants adapted to the arid climate of the NTS are able to rapidly capture infiltrating moisture. In addition to capturing soil moisture, plant roots absorb nutrients, minerals, and heavy metals, transporting them within the plant to the above-groundmore » biomass. In this fashion, plant uptake affects the movement of radionuclides. The plant uptake model presented reflects rooting characteristics important to plant uptake, biomass turnover rates, and the ability of plants to uptake radionuclides from the soil. Parameters are provided for modeling plant uptake and estimating surface contaminant flux due to plant uptake under both current and potential future climate conditions with increased effective soil moisture. The term ''effective moisture'' is used throughout this report to indicate the soil moisture that is available to plants and is intended to be inclusive of all the variables that control soil moisture at a site (e.g., precipitation, temperature, soil texture, and soil chemistry). Effective moisture is a concept used to simplify a number of complex, interrelated soil processes for which there are too little data to model actual plant available moisture. The PA simulates both the flux of radionuclides across the land surface and the potential dose to humans from that flux. Surface flux is modeled here as the amount of soil contamination that is transferred from the soil by roots and incorporated into aboveground biomass. Movement of contaminants to the surface is the only transport mechanism evaluated with the model presented here. Parameters necessary for estimating surface contaminant flux due to native plants expected to inhabit the NTS RWMSS are developed in this report. The model is specific to the plant communities found at the NTS and is designed for both short-term (<1,000 years) and long-term (>1,000 years) modeling efforts. While the model has been crafted for general applicability to any NTS PA, the key radionuclides considered are limited to the transuranic (TRU) wastes disposed of at the NTS.« less
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Predicting green: really radical (plant) predictive processing
Friston, Karl
2017-01-01
In this article we account for the way plants respond to salient features of their environment under the free-energy principle for biological systems. Biological self-organization amounts to the minimization of surprise over time. We posit that any self-organizing system must embody a generative model whose predictions ensure that (expected) free energy is minimized through action. Plants respond in a fast, and yet coordinated manner, to environmental contingencies. They pro-actively sample their local environment to elicit information with an adaptive value. Our main thesis is that plant behaviour takes place by way of a process (active inference) that predicts the environmental sources of sensory stimulation. This principle, we argue, endows plants with a form of perception that underwrites purposeful, anticipatory behaviour. The aim of the article is to assess the prospects of a radical predictive processing story that would follow naturally from the free-energy principle for biological systems; an approach that may ultimately bear upon our understanding of life and cognition more broadly. PMID:28637913
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NASA Astrophysics Data System (ADS)
Jaiswal, D.; Long, S.; Parton, W. J.; Hartman, M.
2012-12-01
A coupled modeling system of crop growth model (BioCro) and biogeochemical model (DayCent) has been developed to assess the two-way interactions between plant growth and biogeochemistry. Crop growth in BioCro is simulated using a detailed mechanistic biochemical and biophysical multi-layer canopy model and partitioning of dry biomass into different plant organs according to phenological stages. Using hourly weather records, the model partitions light between dynamically changing sunlit and shaded portions of the canopy and computes carbon and water exchange with the atmosphere and through the canopy for each hour of the day, each day of the year. The model has been parameterized for the bioenergy crops sugarcane, Miscanthus and switchgrass, and validation has shown it to predict growth cycles and partitioning of biomass to a high degree of accuracy. As such it provides an ideal input for a soil biogeochemical model. DayCent is an established model for predicting long-term changes in soil C & N and soil-atmosphere exchanges of greenhouse gases. At present, DayCent uses a relatively simple productivity model. In this project BioCro has replaced this simple model to provide DayCent with a productivity and growth model equal in detail to its biogeochemistry. Dynamic coupling of these two models to produce CroCent allows for differential C: N ratios of litter fall (based on rates of senescence of different plant organs) and calibration of the model for realistic plant productivity in a mechanistic way. A process-based approach to modeling plant growth is needed for bioenergy crops because research on these crops (especially second generation feedstocks) has started only recently, and detailed agronomic information for growth, yield and management is too limited for effective empirical models. The coupled model provides means to test and improve the model against high resolution data, such as that obtained by eddy covariance and explore yield implications of different crop and soil management.
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Exploring Third-Grade Student Model-Based Explanations about Plant Relationships within an Ecosystem
NASA Astrophysics Data System (ADS)
Zangori, Laura; Forbes, Cory T.
2015-12-01
Elementary students should have opportunities to develop scientific models to reason and build understanding about how and why plants depend on relationships within an ecosystem for growth and survival. However, scientific modeling practices are rarely included within elementary science learning environments and disciplinary content is often treated as discrete pieces separate from scientific practice. Elementary students have few, if any, opportunities to reason about how individual organisms, such as plants, hold critical relationships with their surrounding environment. The purpose of this design-based research study is to build a learning performance to identify and explore the third-grade students' baseline understanding of and their reasoning about plant-ecosystem relationships when engaged in the practices of modeling. The developed learning performance integrated scientific content and core scientific activity to identify and measure how students build knowledge about the role of plants in ecosystems through the practices of modeling. Our findings indicate that the third-grade students' ideas about plant growth include abiotic and biotic relationships. Further, they used their models to reason about how and why these relationships were necessary to maintain plant stasis. However, while the majority of the third-grade students were able to identify and reason about plant-abiotic relationships, a much smaller group reasoned about plant-abiotic-animal relationships. Implications from the study suggest that modeling serves as a tool to support elementary students in reasoning about system relationships, but they require greater curricular and instructional support in conceptualizing how and why ecosystem relationships are necessary for plant growth and development. This paper is based on data from a doctoral dissertation. An earlier version of this paper was presented at the 2015 international conference for the National Association for Research in Science Teaching (NARST) Zangori, L., & Forbes, C. T. (2015). Exploring 3rd-grade student model-based explanations about plant process interactions within the hydrosphere Portions of this paper are based on that work.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
1996-12-31
Over the next four years, the Progetto Energia project will be building several cogeneration plants to help satisfy the increasing demands of Italy`s industrial users and the country`s demand for electrical power. Located at six different sites within Italy, these combined-cycle cogeneration plants will supply a total of 500 MW of electricity and 100 tons/hr of process steam to Italian industries and residences. To ensure project success, a dynamic model of the 50-MW base unit was developed. The goal established for the model was to predict the dynamic behavior of the complex thermodynamic system in order to assess equipment performancemore » and control system effectiveness for normal operation and, more importantly, abrupt load changes. In addition to fulfilling its goals, the dynamic study guided modifications to controller logic that significantly improved steam drum pressure control and bypassed steam desuperheating performance simulations of normal and abrupt transient events allowed engineers to define optimum controller gain coefficients. The dynamic study will undoubtedly reduce the associated plant start-up costs and contribute to a smooth commercial plant acceptance. As a result of the work, the control system has already been through its check-out and performance evaluation, usually performed during the plant start-up phase. Field engineers will directly benefit from this effort to identify and resolve control system {open_quotes}bugs{close_quotes} before the equipment reaches the field. High thermal efficiency, rapid dispatch and high plant availability were key reasons why the natural gas combined-cycle plant was chosen. Other favorable attributes of the combined-cycle plant contributing to the decision were: Minimal environmental impact; a simple and effective process and control philosophy to result in safe and easy plant operation; a choice of technologies and equipment proven in a large number of applications.« less
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A Game-Theoretical Model to Improve Process Plant Protection from Terrorist Attacks.
Zhang, Laobing; Reniers, Genserik
2016-12-01
The New York City 9/11 terrorist attacks urged people from academia as well as from industry to pay more attention to operational security research. The required focus in this type of research is human intention. Unlike safety-related accidents, security-related accidents have a deliberate nature, and one has to face intelligent adversaries with characteristics that traditional probabilistic risk assessment techniques are not capable of dealing with. In recent years, the mathematical tool of game theory, being capable to handle intelligent players, has been used in a variety of ways in terrorism risk assessment. In this article, we analyze the general intrusion detection system in process plants, and propose a game-theoretical model for security management in such plants. Players in our model are assumed to be rational and they play the game with complete information. Both the pure strategy and the mixed strategy solutions are explored and explained. We illustrate our model by an illustrative case, and find that in our case, no pure strategy but, instead, a mixed strategy Nash equilibrium exists. © 2016 Society for Risk Analysis.
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A consistent modelling methodology for secondary settling tanks in wastewater treatment.
Bürger, Raimund; Diehl, Stefan; Nopens, Ingmar
2011-03-01
The aim of this contribution is partly to build consensus on a consistent modelling methodology (CMM) of complex real processes in wastewater treatment by combining classical concepts with results from applied mathematics, and partly to apply it to the clarification-thickening process in the secondary settling tank. In the CMM, the real process should be approximated by a mathematical model (process model; ordinary or partial differential equation (ODE or PDE)), which in turn is approximated by a simulation model (numerical method) implemented on a computer. These steps have often not been carried out in a correct way. The secondary settling tank was chosen as a case since this is one of the most complex processes in a wastewater treatment plant and simulation models developed decades ago have no guarantee of satisfying fundamental mathematical and physical properties. Nevertheless, such methods are still used in commercial tools to date. This particularly becomes of interest as the state-of-the-art practice is moving towards plant-wide modelling. Then all submodels interact and errors propagate through the model and severely hamper any calibration effort and, hence, the predictive purpose of the model. The CMM is described by applying it first to a simple conversion process in the biological reactor yielding an ODE solver, and then to the solid-liquid separation in the secondary settling tank, yielding a PDE solver. Time has come to incorporate established mathematical techniques into environmental engineering, and wastewater treatment modelling in particular, and to use proven reliable and consistent simulation models. Copyright © 2011 Elsevier Ltd. All rights reserved.
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NASA Astrophysics Data System (ADS)
Mohanty, Itishree; Chintha, Appa Rao; Kundu, Saurabh
2018-06-01
The optimization of process parameters and composition is essential to achieve the desired properties with minimal additions of alloying elements in microalloyed steels. In some cases, it may be possible to substitute such steels for those which are more richly alloyed. However, process control involves a larger number of parameters, making the relationship between structure and properties difficult to assess. In this work, neural network models have been developed to estimate the mechanical properties of steels containing Nb + V or Nb + Ti. The outcomes have been validated by thermodynamic calculations and plant data. It has been shown that subtle thermodynamic trends can be captured by the neural network model. Some experimental rolling data have also been used to support the model, which in addition has been applied to calculate the costs of optimizing microalloyed steel. The generated pareto fronts identify many combinations of strength and elongation, making it possible to select composition and process parameters for a range of applications. The ANN model and the optimization model are being used for prediction of properties in a running plant and for development of new alloys, respectively.
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Plants as models for the study of human pathogenesis.
Guttman, David S
2004-05-01
There are many common disease mechanisms used by bacterial pathogens of plants and humans. They use common means of attachment, secretion and genetic regulation. They share many virulence factors, such as extracellular polysaccharides and some type III secreted effectors. Plant and human innate immune systems also share many similarities. Many of these shared bacterial virulence mechanisms are homologous, but even more appear to have independently converged on a common function. This combination of homologous and analogous systems reveals conserved and critical steps in the disease process. Given these similarities, and the many experimental advantages of plant biology, including ease of replication, stringent genetic and reproductive control, and high throughput with low cost, it is proposed that plants would make excellent models for the study of human pathogenesis.
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How important are the descriptions of vegetation in distributed hydrologic models?
NASA Astrophysics Data System (ADS)
Cuntz, Matthias; Thober, Stephan; Zink, Matthias; Rakovec, Oldrich; Samaniego, Luis
2016-04-01
The land surface transforms incoming, absorbed radiation into other energy forms and radiation with longer wavelengths. The land surface emits long-wave radiation, stores energy in the soil, the biomass and the air in the boundary layer, and exchanges sensible and latent heat with the atmosphere. The latter, latent heat consists of evaporation from the soil and canopy and transpiration by plants. Plants enhance in this picture the absorption of incoming radiation and decrease the resistance for evaporation of deeper soil water. Transpiration by plants is therefore either energy-limited by low incoming radiation or water-limited by small soil moisture. In the extreme cases, all available energy will be used for evapotranspiration in cold regions and all available water will be used for evapotranspiration in arid regions. Very simple formulations of latent heat, which include plant processes only very indirectly, work well in hydrologic models for these limiting cases. These simple formulations seem to work also surprisingly well in temperate regions. Hydrologic models have, however, considerable problems in semi-arid regions where the vegetation influence on latent heat should be largest. But the models have to deal with much more problems in these regions. For example data scarcity in the Mediterranean leads to very large model uncertainty due to the forcing data. Water supply is also often very regulated in semi-arid regions. Variability in river discharge can hence be largely driven by the anthropogenic influence rather than natural meteorological variations in these regions. Here we will show for Europe the areas and times when the descriptions of plant processes are important for hydrologic models. We will compare differences in model uncertainties that come from 1. different formulations of evapotranspiration, 2. different descriptions of soil-plant interactions, and 3. uncertainty in the model's input data. It can be seen that model uncertainty stemming from uncertain input data is similar or larger in magnitude than the uncertainty coming from the descriptions of the vegetation in the models. Acquisition of better input data should thus go hand in hand with more sophisticated descriptions of the land surface.
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Functional and Structural Optimality in Plant Growth: A Crop Modelling Case Study
NASA Astrophysics Data System (ADS)
Caldararu, S.; Purves, D. W.; Smith, M. J.
2014-12-01
Simple mechanistic models of vegetation processes are essential both to our understanding of plant behaviour and to our ability to predict future changes in vegetation. One concept that can take us closer to such models is that of plant optimality, the hypothesis that plants aim to achieve an optimal state. Conceptually, plant optimality can be either structural or functional optimality. A structural constraint would mean that plants aim to achieve a certain structural characteristic such as an allometric relationship or nutrient content that allows optimal function. A functional condition refers to plants achieving optimal functionality, in most cases by maximising carbon gain. Functional optimality conditions are applied on shorter time scales and lead to higher plasticity, making plants more adaptable to changes in their environment. In contrast, structural constraints are optimal given the specific environmental conditions that plants are adapted to and offer less flexibility. We exemplify these concepts using a simple model of crop growth. The model represents annual cycles of growth from sowing date to harvest, including both vegetative and reproductive growth and phenology. Structural constraints to growth are represented as an optimal C:N ratio in all plant organs, which drives allocation throughout the vegetative growing stage. Reproductive phenology - i.e. the onset of flowering and grain filling - is determined by a functional optimality condition in the form of maximising final seed mass, so that vegetative growth stops when the plant reaches maximum nitrogen or carbon uptake. We investigate the plants' response to variations in environmental conditions within these two optimality constraints and show that final yield is most affected by changes during vegetative growth which affect the structural constraint.
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Apple miRNAs and tasiRNAs with novel regulatory networks
USDA-ARS?s Scientific Manuscript database
MiRNAs, negatively affecting gene expression at the post-transcriptional levels, have been shown to control numerous genes involved in various biological and metabolic processes. To date, the identification of miRNAs in plants focused on certain model plants, such as Arabidopsis and rice. Investig...
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Trapote, Arturo; García, Mariano; Prats, Daniel
2016-12-01
Siloxanes present in the biogas produced during anaerobic digestion in wastewater treatment plants (WWTPs) can damage the mechanism of cogeneration heat engines and obstruct the process of energy valorization. The objective of this research is to detect the presence of siloxanes in the biogas and evaluate a procedure for their elimination. A breakthrough curve of a synthetic decamethylcyclopentasiloxane on an experimental bed of activated carbon was modeled and the theoretical mathematical model of the adsorption process was adjusted. As a result, the constants of the model were obtained: the mass transfer constant, Henry's equilibrium constant, and the Eddy diffusion. The procedure developed allows the adsorption equilibrium of siloxanes on activated carbon to be predicted, and makes it possible to lay the basis for the design of an appropriate activated carbon module for the elimination of siloxanes in a WWTP.
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Validation of X1 motorcycle model in industrial plant layout by using WITNESSTM simulation software
NASA Astrophysics Data System (ADS)
Hamzas, M. F. M. A.; Bareduan, S. A.; Zakaria, M. Z.; Tan, W. J.; Zairi, S.
2017-09-01
This paper demonstrates a case study on simulation, modelling and analysis for X1 Motorcycles Model. In this research, a motorcycle assembly plant has been selected as a main place of research study. Simulation techniques by using Witness software were applied to evaluate the performance of the existing manufacturing system. The main objective is to validate the data and find out the significant impact on the overall performance of the system for future improvement. The process of validation starts when the layout of the assembly line was identified. All components are evaluated to validate whether the data is significance for future improvement. Machine and labor statistics are among the parameters that were evaluated for process improvement. Average total cycle time for given workstations is used as criterion for comparison of possible variants. From the simulation process, the data used are appropriate and meet the criteria for two-sided assembly line problems.
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Modeling Lolium perenne L. roots in the presence of empirical black holes
USDA-ARS?s Scientific Manuscript database
Plant root models are designed for understanding structural or functional aspects of root systems. When a process is not thoroughly understood, a black box object is used. However, when a process exists but empirical data do not indicate its existence, you have a black hole. The object of this re...
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Operator agency in process intervention: tampering versus application of tacit knowledge
NASA Astrophysics Data System (ADS)
Van Gestel, P.; Pons, D. J.; Pulakanam, V.
2015-09-01
Statistical process control (SPC) theory takes a negative view of adjustment of process settings, which is termed tampering. In contrast, quality and lean programmes actively encourage operators to acts of intervention and personal agency in the improvement of production outcomes. This creates a conflict that requires operator judgement: How does one differentiate between unnecessary tampering and needful intervention? Also, difficult is that operators apply tacit knowledge to such judgements. There is a need to determine where in a given production process the operators are applying tacit knowledge, and whether this is hindering or aiding quality outcomes. The work involved the conjoint application of systems engineering, statistics, and knowledge management principles, in the context of a case study. Systems engineering was used to create a functional model of a real plant. Actual plant data were analysed with the statistical methods of ANOVA, feature selection, and link analysis. This identified the variables to which the output quality was most sensitive. These key variables were mapped back to the functional model. Fieldwork was then directed to those areas to prospect for operator judgement activities. A natural conversational approach was used to determine where and how operators were applying judgement. This contrasts to the interrogative approach of conventional knowledge management. Data are presented for a case study of a meat rendering plant. The results identify specific areas where operators' tacit knowledge and mental model contribute to quality outcomes and untangles the motivations behind their agency. Also evident is how novice and expert operators apply their knowledge differently. Novices were focussed on meeting throughput objectives, and their incomplete understanding of the plant characteristics led them to inadvertently sacrifice quality in the pursuit of productivity in certain situations. Operators' responses to the plant are affected by their individual mental models of the plant, which differ between operators and have variable validity. Their behaviour is also affected by differing interpretations of how their personal agency should be applied to the achievement of production objectives. The methodology developed here is an integration of systems engineering, statistical analysis, and knowledge management. It shows how to determine where in a given production process the operator intervention is occurring, how it affects quality outcomes, and what tacit knowledge operators are using. It thereby assists the continuous quality improvement processes in a different way to SPC. A second contribution is the provision of a novel methodology for knowledge management, one that circumvents the usual codification barriers to knowledge management.
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2014-01-01
Wheat (Triticum aestivum L.)/faba bean (Vicia faba L.) intercropping shows significant overyielding and high nitrogen (N)-use efficiency, but the dynamics of plant interactions have rarely been estimated. The objective of the present study was to investigate the temporal dynamics of competitive N acquisition between intercropped wheat and faba bean with the logistic model. Wheat and faba bean were grown together or alone with limited N supply in pots. Data of shoot and root biomass and N content measured from 14 samplings were fitted to logistic models to determine instantaneous rates of growth and N uptake. The superiority of instantaneous biomass production and N uptake shifted from faba bean to wheat with their growth. Moreover, the shift of superiority on N uptake occurred 7–12 days earlier than that of biomass production. Interspecific competition stimulated intercropped wheat to have a much earlier and stronger superiority on instantaneous N uptake compared with isolated wheat. The modeling methodology characterized the temporal dynamics of biomass production and N uptake of intercropped wheat and faba bean in different planting systems, which helps to understand the underlying process of plant interaction for intercropping plants. PMID:25541699
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Li, Chunjie; Dong, Yan; Li, Haigang; Shen, Jianbo; Zhang, Fusuo
2014-01-01
Wheat (Triticum aestivum L.)/faba bean (Vicia faba L.) intercropping shows significant overyielding and high nitrogen (N)-use efficiency, but the dynamics of plant interactions have rarely been estimated. The objective of the present study was to investigate the temporal dynamics of competitive N acquisition between intercropped wheat and faba bean with the logistic model. Wheat and faba bean were grown together or alone with limited N supply in pots. Data of shoot and root biomass and N content measured from 14 samplings were fitted to logistic models to determine instantaneous rates of growth and N uptake. The superiority of instantaneous biomass production and N uptake shifted from faba bean to wheat with their growth. Moreover, the shift of superiority on N uptake occurred 7-12 days earlier than that of biomass production. Interspecific competition stimulated intercropped wheat to have a much earlier and stronger superiority on instantaneous N uptake compared with isolated wheat. The modeling methodology characterized the temporal dynamics of biomass production and N uptake of intercropped wheat and faba bean in different planting systems, which helps to understand the underlying process of plant interaction for intercropping plants.
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Development of a model to select plants with optimum metal phytoextraction potential.
Guala, Sebastián D; Vega, Flora A; Covelo, Emma F
2011-07-01
The aim of the present study is to propose a nonlinear model which provides an indicator for the maximum phytoextraction of metals to help in the decision-making process. Research into different species and strategies plays an important role in the application of phytoextraction techniques to the remediation of contaminated soil. Also, the convenience of species according to their biomass and pollutant accumulation capacities has gained important space in discussions regarding remediation strategies, whether to choose species with low accumulation capacities and high biomass or high accumulation capacities with low biomass. The effects of heavy metals in soil on plant growth are studied by means of a nonlinear interaction model which relates the dynamics of the uptake of heavy metals by plants to heavy metal deposed in soil. The model, presented theoretically, provides an indicator for the maximum phytoextraction of metals which depends on adjustable parameters of both the plant and the environmental conditions. Finally, in order to clarify its applicability, a series of experimental results found in the literature are presented to show how the model performs consistently with real data. The inhibition of plant growth due to heavy metal concentration can be predicted by a simple kinetic model. The model proposed in this study makes it possible to characterize the nonlinear behaviour of the soil-plant interaction with heavy metal pollution in order to establish maximum uptake values for heavy metals in the harvestable part of plants.
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Mathieu, Amélie; Vidal, Tiphaine; Jullien, Alexandra; Wu, QiongLi; Chambon, Camille; Bayol, Benoit; Cournède, Paul-Henry
2018-06-19
Functional-structural plant models (FSPMs) describe explicitly the interactions between plants and their environment at organ to plant scale. However, the high level of description of the structure or model mechanisms makes this type of model very complex and hard to calibrate. A two-step methodology to facilitate the calibration process is proposed here. First, a global sensitivity analysis method was applied to the calibration loss function. It provided first-order and total-order sensitivity indexes that allow parameters to be ranked by importance in order to select the most influential ones. Second, the Akaike information criterion (AIC) was used to quantify the model's quality of fit after calibration with different combinations of selected parameters. The model with the lowest AIC gives the best combination of parameters to select. This methodology was validated by calibrating the model on an independent data set (same cultivar, another year) with the parameters selected in the second step. All the parameters were set to their nominal value; only the most influential ones were re-estimated. Sensitivity analysis applied to the calibration loss function is a relevant method to underline the most significant parameters in the estimation process. For the studied winter oilseed rape model, 11 out of 26 estimated parameters were selected. Then, the model could be recalibrated for a different data set by re-estimating only three parameters selected with the model selection method. Fitting only a small number of parameters dramatically increases the efficiency of recalibration, increases the robustness of the model and helps identify the principal sources of variation in varying environmental conditions. This innovative method still needs to be more widely validated but already gives interesting avenues to improve the calibration of FSPMs.
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NASA Astrophysics Data System (ADS)
Lowman, L.; Barros, A. P.
2017-12-01
Data assimilation (DA) is the widely accepted procedure for estimating parameters within predictive models because of the adaptability and uncertainty quantification offered by Bayesian methods. DA applications in phenology modeling offer critical insights into how extreme weather or changes in climate impact the vegetation life cycle. Changes in leaf onset and senescence, root phenology, and intermittent leaf shedding imply large changes in the surface radiative, water, and carbon budgets at multiple scales. Models of leaf phenology require concurrent atmospheric and soil conditions to determine how biophysical plant properties respond to changes in temperature, light and water demand. Presently, climatological records for fraction of photosynthetically active radiation (FPAR) and leaf area index (LAI), the modelled states indicative of plant phenology, are not available. Further, DA models are typically trained on short periods of record (e.g. less than 10 years). Using limited records with a DA framework imposes non-stationarity on estimated parameters and the resulting predicted model states. This talk discusses how uncertainty introduced by the inherent non-stationarity of the modeled processes propagates through a land-surface hydrology model coupled to a predictive phenology model. How water demand is accounted for in the upscaling of DA model inputs and analysis period serves as a key source of uncertainty in the FPAR and LAI predictions. Parameters estimated from different DA effectively calibrate a plant water-use strategy within the land-surface hydrology model. For example, when extreme droughts are included in the DA period, the plants are trained to uptake water, transpire, and assimilate carbon under favorable conditions and quickly shut down at the onset of water stress.
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Can Microbial Ecology and Mycorrhizal Functioning Inform Climate Change Models?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hofmockel, Kirsten; Hobbie, Erik
Our funded research focused on soil organic matter dynamics and plant-microbe interactions by examining the role of belowground processes and mechanisms across scales, including decomposition of organic molecules, microbial interactions, and plant-microbe interactions associated with a changing climate. Research foci included mycorrhizal mediated priming of soil carbon turnover, organic N use and depolymerization by free-living microbes and mycorrhizal fungi, and the use of isotopes as additional constraints for improved modeling of belowground processes. This work complemented the DOE’s mandate to understand both the consequences of atmospheric and climatic change for key ecosystems and the feedbacks on C cycling.
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NASA Astrophysics Data System (ADS)
Paul, Andrea; Meyer, Klas; Ruiken, Jan-Paul; Illner, Markus; Müller, David-Nicolas; Esche, Erik; Wozny, Günther; Westad, Frank; Maiwald, Michael
2017-03-01
A major industrial reaction based on homogeneous catalysis is hydroformylation for the production of aldehydes from alkenes and syngas. Hydroformylation in microemulsions, which is currently under investigation at Technische Universität Berlin on a mini-plant scale, was identified as a cost efficient approach which also enhances product selectivity. Herein, we present the application of online Raman spectroscopy on the reaction of 1-dodecene to 1-tridecanal within a microemulsion. To achieve a good representation of the operation range in the mini-plant with regard to concentrations of the reactants a design of experiments was used. Based on initial Raman spectra partial least squares regression (PLSR) models were calibrated for the prediction of 1-dodecene and 1-tridecanal. Limits of predictions arise from nonlinear correlations between Raman intensity and mass fractions of compounds in the microemulsion system. Furthermore, the prediction power of PLSR models becomes limited due to unexpected by-product formation. Application of the lab-scale derived calibration spectra and PLSR models on online spectra from a mini-plant operation yielded promising estimations of 1-tridecanal and acceptable predictions of 1-dodecene mass fractions suggesting Raman spectroscopy as a suitable technique for process analytics in microemulsions.
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Strotbek, Christoph; Krinninger, Stefan; Frank, Wolfgang
2013-01-01
To comprehensively understand the major processes in plant biology, it is necessary to study a diverse set of species that represent the complexity of plants. This research will help to comprehend common conserved mechanisms and principles, as well as to elucidate those mechanisms that are specific to a particular plant clade. Thereby, we will gain knowledge about the invention and loss of mechanisms and their biological impact causing the distinct specifications throughout the plant kingdom. Since the establishment of transgenic plants, these studies concentrate on the elucidation of gene functions applying an increasing repertoire of molecular techniques. In the last two decades, the moss Physcomitrella patens joined the established set of plant models based on its evolutionary position bridging unicellular algae and vascular plants and a number of specific features alleviating gene function analysis. Here, we want to provide an overview of the specific features of P. patens making it an interesting model for many research fields in plant biology, to present the major achievements in P. patens genetic engineering, and to introduce common techniques to scientists who intend to use P. patens as a model in their research activities.
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A new framework to increase the efficiency of large-scale solar power plants.
NASA Astrophysics Data System (ADS)
Alimohammadi, Shahrouz; Kleissl, Jan P.
2015-11-01
A new framework to estimate the spatio-temporal behavior of solar power is introduced, which predicts the statistical behavior of power output at utility scale Photo-Voltaic (PV) power plants. The framework is based on spatio-temporal Gaussian Processes Regression (Kriging) models, which incorporates satellite data with the UCSD version of the Weather and Research Forecasting model. This framework is designed to improve the efficiency of the large-scale solar power plants. The results are also validated from measurements of the local pyranometer sensors, and some improvements in different scenarios are observed. Solar energy.
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Model-free adaptive control of advanced power plants
Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang
2015-08-18
A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.
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Pesticide uptake in potatoes: model and field experiments.
Juraske, Ronnie; Vivas, Carmen S Mosquera; Velásquez, Alexander Erazo; Santos, Glenda García; Moreno, Mónica B Berdugo; Gomez, Jaime Diaz; Binder, Claudia R; Hellweg, Stefanie; Dallos, Jairo A Guerrero
2011-01-15
A dynamic model for uptake of pesticides in potatoes is presented and evaluated with measurements performed within a field trial in the region of Boyacá, Colombia. The model takes into account the time between pesticide applications and harvest, the time between harvest and consumption, the amount of spray deposition on soil surface, mobility and degradation of pesticide in soil, diffusive uptake and persistence due to crop growth and metabolism in plant material, and loss due to food processing. Food processing steps included were cleaning, washing, storing, and cooking. Pesticide concentrations were measured periodically in soil and potato samples from the beginning of tuber formation until harvest. The model was able to predict the magnitude and temporal profile of the experimentally derived pesticide concentrations well, with all measurements falling within the 90% confidence interval. The fraction of chlorpyrifos applied on the field during plant cultivation that eventually is ingested by the consumer is on average 10(-4)-10(-7), depending on the time between pesticide application and ingestion and the processing step considered.
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NASA Astrophysics Data System (ADS)
Opitz, Florian; Treffinger, Peter
2016-04-01
Electric arc furnaces (EAF) are complex industrial plants whose actual behavior depends upon numerous factors. Due to its energy intensive operation, the EAF process has always been subject to optimization efforts. For these reasons, several models have been proposed in literature to analyze and predict different modes of operation. Most of these models focused on the processes inside the vessel itself. The present paper introduces a dynamic, physics-based model of a complete EAF plant which consists of the four subsystems vessel, electric system, electrode regulation, and off-gas system. Furthermore the solid phase is not treated to be homogenous but a simple spatial discretization is employed. Hence it is possible to simulate the energy input by electric arcs and fossil fuel burners depending on the state of the melting progress. The model is implemented in object-oriented, equation-based language Modelica. The simulation results are compared to literature data.
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Derived heuristics-based consistent optimization of material flow in a gold processing plant
NASA Astrophysics Data System (ADS)
Myburgh, Christie; Deb, Kalyanmoy
2018-01-01
Material flow in a chemical processing plant often follows complicated control laws and involves plant capacity constraints. Importantly, the process involves discrete scenarios which when modelled in a programming format involves if-then-else statements. Therefore, a formulation of an optimization problem of such processes becomes complicated with nonlinear and non-differentiable objective and constraint functions. In handling such problems using classical point-based approaches, users often have to resort to modifications and indirect ways of representing the problem to suit the restrictions associated with classical methods. In a particular gold processing plant optimization problem, these facts are demonstrated by showing results from MATLAB®'s well-known fmincon routine. Thereafter, a customized evolutionary optimization procedure which is capable of handling all complexities offered by the problem is developed. Although the evolutionary approach produced results with comparatively less variance over multiple runs, the performance has been enhanced by introducing derived heuristics associated with the problem. In this article, the development and usage of derived heuristics in a practical problem are presented and their importance in a quick convergence of the overall algorithm is demonstrated.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Sari Izumo; Hideo Usui; Mitsuo Tachibana
Evaluation models for determining the manpower needs for dismantling various types of equipment in uranium refining and conversion plant (URCP) have been developed. The models are widely applicable to other uranium handling facilities. Additionally, a simplified model was developed for easily and accurately calculating the manpower needs for dismantling dry conversion process-related equipment (DP equipment). It is important to evaluate beforehand project management data such as manpower needs to prepare an optimized decommissioning plan and implement effective dismantling activity. The Japan Atomic Energy Agency (JAEA) has developed the project management data evaluation system for dismantling activities (PRODIA code), which canmore » generate project management data using evaluation models. For preparing an optimized decommissioning plan, these evaluation models should be established based on the type of nuclear facility and actual dismantling data. In URCP, the dry conversion process of reprocessed uranium and others was operated until 1999, and the equipment related to the main process was dismantled from 2008 to 2011. Actual data such as manpower for dismantling were collected during the dismantling activities, and evaluation models were developed using the collected actual data on the basis of equipment classification considering the characteristics of uranium handling facility. (authors)« less
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Berner, Logan T.; Law, Beverly E.
2016-01-01
Plant trait measurements are needed for evaluating ecological responses to environmental conditions and for ecosystem process model development, parameterization, and testing. We present a standardized dataset integrating measurements from projects conducted by the Terrestrial Ecosystem Research and Regional Analysis- Pacific Northwest (TERRA-PNW) research group between 1999 and 2014 across Oregon and Northern California, where measurements were collected for scaling and modeling regional terrestrial carbon processes with models such as Biome-BGC and the Community Land Model. The dataset contains measurements of specific leaf area, leaf longevity, leaf carbon and nitrogen for 35 tree and shrub species derived from more than 1,200 branch samples collected from over 200 forest plots, including several AmeriFlux sites. The dataset also contains plot-level measurements of forest composition, structure (e.g., tree biomass), and productivity, as well as measurements of soil structure (e.g., bulk density) and chemistry (e.g., carbon). Publically-archiving regional datasets of standardized, co-located, and geo-referenced plant trait measurements will advance the ability of earth system models to capture species-level climate sensitivity at regional to global scales. PMID:26784559
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Berner, Logan T.; Law, Beverly E.
2016-01-19
Plant trait measurements are needed for evaluating ecological responses to environmental conditions and for ecosystem process model development, parameterization, and testing. Here, we present a standardized dataset integrating measurements from projects conducted by the Terrestrial Ecosystem Research and Regional Analysis- Pacific Northwest (TERRA-PNW) research group between 1999 and 2014 across Oregon and Northern California, where measurements were collected for scaling and modeling regional terrestrial carbon processes with models such as Biome-BGC and the Community Land Model. The dataset contains measurements of specific leaf area, leaf longevity, leaf carbon and nitrogen for 35 tree and shrub species derived from more thanmore » 1,200 branch samples collected from over 200 forest plots, including several AmeriFlux sites. The dataset also contains plot-level measurements of forest composition, structure (e.g., tree biomass), and productivity, as well as measurements of soil structure (e.g., bulk density) and chemistry (e.g., carbon). Publically-archiving regional datasets of standardized, co-located, and geo-referenced plant trait measurements will advance the ability of earth system models to capture species-level climate sensitivity at regional to global scales.« less
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Life in the dark: Roots and how they regulate plant-soil interactions
NASA Astrophysics Data System (ADS)
Wu, Y.; Chou, C.; Peruzzo, L.; Riley, W. J.; Hao, Z.; Petrov, P.; Newman, G. A.; Versteeg, R.; Blancaflor, E.; Ma, X.; Dafflon, B.; Brodie, E.; Hubbard, S. S.
2017-12-01
Roots play a key role in regulating interactions between soil and plants, an important biosphere process critical for soil development and health, global food security, carbon sequestration, and the cycling of elements (water, carbon, nutrients, and environmental contaminants). However, their underground location has hindered studies of plant roots and the role they play in regulating plant-soil interactions. Technological limitations for root phenotyping and the lack of an integrated approach capable of linking root development, its environmental adaptation/modification with subsequent impact on plant health and productivity are major challenges faced by scientists as they seek to understand the plant's hidden half. To overcome these challenges, we combine novel experimental methods with numerical simulations, and conduct controlled studies to explore the dynamic growth of crop roots. We ask how roots adapt to and change the soil environment and their subsequent impacts on plant health and productivity. Specifically, our efforts are focused on (1) developing novel geophysical approaches for non-invasive plant root and rhizosphere characterization; (2) correlating root developments with key canopy traits indicative of plant health and productivity; (3) developing numerical algorithms for novel geophysical root signal processing; (4) establishing plant growth models to explore root-soil interactions and above and below ground traits co-variabilities; and (5) exploring how root development modifies rhizosphere physical, hydrological, and geochemical environments for adaptation and survival. Our preliminary results highlight the potential of using electro-geophysical methods to quantifying key rhizosphere traits, the capability of the ecosys model for mechanistic plant growth simulation and traits correlation exploration, and the combination of multi-physics and numerical approach for a systematic understanding of root growth dynamics, impacts on soil physicochemical environments, and plant health and productivity.
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Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa
2013-04-09
Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.
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Nonlinear model predictive control for chemical looping process
DOE Office of Scientific and Technical Information (OSTI.GOV)
Joshi, Abhinaya; Lei, Hao; Lou, Xinsheng
A control system for optimizing a chemical looping ("CL") plant includes a reduced order mathematical model ("ROM") that is designed by eliminating mathematical terms that have minimal effect on the outcome. A non-linear optimizer provides various inputs to the ROM and monitors the outputs to determine the optimum inputs that are then provided to the CL plant. An estimator estimates the values of various internal state variables of the CL plant. The system has one structure adapted to control a CL plant that only provides pressure measurements in the CL loops A and B, a second structure adapted to amore » CL plant that provides pressure measurements and solid levels in both loops A, and B, and a third structure adapted to control a CL plant that provides full information on internal state variables. A final structure provides a neural network NMPC controller to control operation of loops A and B.« less
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Ashrafi, Omid; Yerushalmi, Laleh; Haghighat, Fariborz
2013-03-01
Greenhouse gas (GHG) emission in wastewater treatment plants of the pulp-and-paper industry was estimated by using a dynamic mathematical model. Significant variations were shown in the magnitude of GHG generation in response to variations in operating parameters, demonstrating the limited capacity of steady-state models in predicting the time-dependent emissions of these harmful gases. The examined treatment systems used aerobic, anaerobic, and hybrid-anaerobic/aerobic-biological processes along with chemical coagulation/flocculation, anaerobic digester, nitrification and denitrification processes, and biogas recovery. The pertinent operating parameters included the influent substrate concentration, influent flow rate, and temperature. Although the average predictions by the dynamic model were only 10 % different from those of steady-state model during 140 days of operation of the examined systems, the daily variations of GHG emissions were different up to ± 30, ± 19, and ± 17 % in the aerobic, anaerobic, and hybrid systems, respectively. The variations of process variables caused fluctuations in energy generation from biogas recovery by ± 6, ± 7, and ± 4 % in the three examined systems, respectively. The lowest variations were observed in the hybrid system, showing the stability of this particular process design.
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Collins, Nicholas C; Parent, Boris
2017-01-09
There is a growing consensus in the literature that rising temperatures influence the rate of biomass accumulation by shortening the development of plant organs and the whole plant and by altering rates of respiration and photosynthesis. A model describing the net effects of these processes on biomass would be useful, but would need to reconcile reported differences in the effects of night and day temperature on plant productivity. In this study, the working hypothesis was that the temperature responses of CO 2 assimilation and plant development rates were divergent, and that their net effects could explain observed differences in biomass accumulation. In wheat (Triticum aestivum) plants, we followed the temperature responses of photosynthesis, respiration and leaf elongation, and confirmed that their responses diverged. We measured the amount of carbon assimilated per "unit of plant development" in each scenario and compared it to the biomass that accumulated in growing leaves and grains. Our results suggested that, up to a temperature optimum, the rate of any developmental process increased with temperature more rapidly than that of CO 2 assimilation and that this discrepancy, summarised by the CO 2 assimilation rate per unit of plant development, could explain the observed reductions in biomass accumulation in plant organs under high temperatures. The model described the effects of night and day temperature equally well, and offers a simple framework for describing the effects of temperature on plant growth. Published by Oxford University Press on behalf of the Annals of Botany Company.
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USDA-ARS?s Scientific Manuscript database
Background/Question/Methods Global climate change models predict increasing drought during the growing season, which will alter many ecosystem processes including soil CO2 efflux (JCO2), with potential consequences for carbon retention in soils. Soil moisture, soil temperature and plant traits such...
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A SIMPLE CELLULAR AUTOMATON MODEL FOR HIGH-LEVEL VEGETATION DYNAMICS
We have produced a simple two-dimensional (ground-plan) cellular automata model of vegetation dynamics specifically to investigate high-level community processes. The model is probabilistic, with individual plant behavior determined by physiologically-based rules derived from a w...
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NASA Astrophysics Data System (ADS)
Petersen, Steven L.
Western juniper has rapidly expanded into sagebrush steppe communities in the Intermountain West during the past 120 years. This expansion has occurred across a wide range of soil types and topographic positions. These plant communities, however, are typically treated in current peer-reviewed literature generically. The focus of this research is to investigate watershed level response to Western juniper encroachment at multiple topographic positions. Data collected from plots used to measure vegetation, soil moisture, and infiltration rates show that intercanopy sites within encroached Western juniper communities generally exhibit a significant decrease in intercanopy plant density and cover, decreased infiltration rates, increased water sediment content, and lower soil moisture content. High-resolution remotely sensed imagery and Geographic Information Systems were used with these plot level measurements to characterize and model the landscape-scale response for both biotic and abiotic components of a Western juniper encroached ecosystem. These data and their analyses included an inventory of plant density, plant cover, bare ground, gap distance and cover, a plant community classification of intercanopy patches and juniper canopy cover, soil moisture estimation, solar insulation prediction, slope and aspect. From these data, models were built that accurately predicted shrub density and shrub cover throughout the watershed study area, differentiated by aspect. We propose a new model of process-based plant community dynamics associated with current state-and-transition theory. This model is developed from field measurements and spatially explicit information that characterize the relationship between the matrix mountain big sagebrush plant community and intercanopy plant community patterns occurring within a Western juniper dominated woodland at a landscape scale. Model parameters (states, transitions, and thresholds) are developed based on differences in shrub density and cover, steady-state infiltration rates, water sediment content, and percent bare ground in response to juniper competition and topographic position. Results from both analysis of variance and multivariate hierarchical cluster analysis indicate that states, transitions, and thresholds can be accurately predicted for intercanopy areas occurring within the study area. In theory, this model and the GIS-based layers produced from this research can be used together to predict states, transitions, and thresholds for any location within the extent of the study area. This is a valuable tool for assessing sites at risk and those that have exceeded the ability to self-repair.
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NASA Astrophysics Data System (ADS)
van Oorschot, M.; Kleinhans, M. G.; Geerling, G. W.; Egger, G.; Leuven, R. S. E. W.; Middelkoop, H.
2017-08-01
Invasive alien plant species negatively impact native plant communities by out-competing species or changing abiotic and biotic conditions in their introduced range. River systems are especially vulnerable to biological invasions, because waterways can function as invasion corridors. Understanding interactions of invasive and native species and their combined effects on river dynamics is essential for developing cost-effective management strategies. However, numerical models for simulating long-term effects of these processes are lacking. This paper investigates how an invasive alien plant species affects native riparian vegetation and hydro-morphodynamics. A morphodynamic model has been coupled to a dynamic vegetation model that predicts establishment, growth and mortality of riparian trees. We introduced an invasive alien species with life-history traits based on Japanese Knotweed (Fallopia japonica), and investigated effects of low- and high propagule pressure on invasion speed, native vegetation and hydro-morphodynamic processes. Results show that high propagule pressure leads to a decline in native species cover due to competition and the creation of unfavorable native colonization sites. With low propagule pressure the invader facilitates native seedling survival by creating favorable hydro-morphodynamic conditions at colonization sites. With high invader abundance, water levels are raised and sediment transport is reduced during the growing season. In winter, when the above-ground invader biomass is gone, results are reversed and the floodplain is more prone to erosion. Invasion effects thus depend on seasonal above- and below ground dynamic vegetation properties and persistence of the invader, on the characteristics of native species it replaces, and the combined interactions with hydro-morphodynamics.
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NASA Astrophysics Data System (ADS)
Guler Yigitoglu, Askin
In the context of long operation of nuclear power plants (NPPs) (i.e., 60-80 years, and beyond), investigation of the aging of passive systems, structures and components (SSCs) is important to assess safety margins and to decide on reactor life extension as indicated within the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. In the traditional probabilistic risk assessment (PRA) methodology, evaluating the potential significance of aging of passive SSCs on plant risk is challenging. Although passive SSC failure rates can be added as initiating event frequencies or basic event failure rates in the traditional event-tree/fault-tree methodology, these failure rates are generally based on generic plant failure data which means that the true state of a specific plant is not reflected in a realistic manner on aging effects. Dynamic PRA methodologies have gained attention recently due to their capability to account for the plant state and thus address the difficulties in the traditional PRA modeling of aging effects of passive components using physics-based models (and also in the modeling of digital instrumentation and control systems). Physics-based models can capture the impact of complex aging processes (e.g., fatigue, stress corrosion cracking, flow-accelerated corrosion, etc.) on SSCs and can be utilized to estimate passive SSC failure rates using realistic NPP data from reactor simulation, as well as considering effects of surveillance and maintenance activities. The objectives of this dissertation are twofold: The development of a methodology for the incorporation of aging modeling of passive SSC into a reactor simulation environment to provide a framework for evaluation of their risk contribution in both the dynamic and traditional PRA; and the demonstration of the methodology through its application to pressurizer surge line pipe weld and steam generator tubes in commercial nuclear power plants. In the proposed methodology, a multi-state physics based model is selected to represent the aging process. The model is modified via sojourn time approach to reflect the operational and maintenance history dependence of the transition rates. Thermal-hydraulic parameters of the model are calculated via the reactor simulation environment and uncertainties associated with both parameters and the models are assessed via a two-loop Monte Carlo approach (Latin hypercube sampling) to propagate input probability distributions through the physical model. The effort documented in this thesis towards this overall objective consists of : i) defining a process for selecting critical passive components and related aging mechanisms, ii) aging model selection, iii) calculating the probability that aging would cause the component to fail, iv) uncertainty/sensitivity analyses, v) procedure development for modifying an existing PRA to accommodate consideration of passive component failures, and, vi) including the calculated failure probability in the modified PRA. The proposed methodology is applied to pressurizer surge line pipe weld aging and steam generator tube degradation in pressurized water reactors.
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Photosynthetic Control of Atmospheric Carbonyl Sulfide during the Growing Season
NASA Technical Reports Server (NTRS)
Campbell, J. Elliott; Carmichael, Gregory R.; Chai, T.; Mena-Carrasco, M.; Tang, Y.; Blake, D. R.; Blake, N. J.; Vay, Stephanie A.; Collatz, G. James; Baker, I.;
2008-01-01
Climate models incorporate photosynthesis-climate feedbacks, yet we lack robust tools for large-scale assessments of these processes. Recent work suggests that carbonyl sulfide (COS), a trace gas consumed by plants, could provide a valuable constraint on photosynthesis. Here we analyze airborne observations of COS and carbon dioxide concentrations during the growing season over North America with a three-dimensional atmospheric transport model. We successfully modeled the persistent vertical drawdown of atmospheric COS using the quantitative relation between COS and photosynthesis that has been measured in plant chamber experiments. Furthermore, this drawdown is driven by plant uptake rather than other continental and oceanic fluxes in the model. These results provide quantitative evidence that COS gradients in the continental growing season may have broad use as a measurement-based photosynthesis tracer.
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Plant hormone signaling during development: insights from computational models.
Oliva, Marina; Farcot, Etienne; Vernoux, Teva
2013-02-01
Recent years have seen an impressive increase in our knowledge of the topology of plant hormone signaling networks. The complexity of these topologies has motivated the development of models for several hormones to aid understanding of how signaling networks process hormonal inputs. Such work has generated essential insights into the mechanisms of hormone perception and of regulation of cellular responses such as transcription in response to hormones. In addition, modeling approaches have contributed significantly to exploring how spatio-temporal regulation of hormone signaling contributes to plant growth and patterning. New tools have also been developed to obtain quantitative information on hormone distribution during development and to test model predictions, opening the way for quantitative understanding of the developmental roles of hormones. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Tim Seipel; Christoph Kueffer; Lisa J. Rew; Curtis C. Daehler; Aníbal Pauchard; Bridgett J. Naylor; Jake M. Alexander; Peter J. Edwards; Catherine G. Parks; Jose Ramon Arevalo; Lohengrin A. Cavieres; Hansjorg Dietz; Gabi Jakobs; Keith McDougall; Rudiger Otto; Neville. Walsh
2012-01-01
We compared the distribution of non-native plant species along roads in eight mountainous regions. Within each region, abundance of plant species was recorded at 41-84 sites along elevational gradients using 100-m2 plots located 0, 25 and 75 m from roadsides. We used mixed-effects models to examine how local variation in species richness and...
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Human Systems Integration Synthesis Model for Ship Design
2012-09-01
this process. Specifically, I thank Dr. Paulo for both planting the seed that led to this thesis and giving me the opportunity to participate in the...manufacturing systems, refineries, and nuclear power plants must also rely on up-to-date knowledge of situation parameters and any patterns among...safety hazards were many due to exposure to toxic fuel, increased probability of fires, and steam plant explosions. In order to address the
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Model-based pH monitor for sensor assessment.
van Schagen, Kim; Rietveld, Luuk; Veersma, Alex; Babuska, Robert
2009-01-01
Owing to the nature of the treatment processes, monitoring the processes based on individual online measurements is difficult or even impossible. However, the measurements (online and laboratory) can be combined with a priori process knowledge, using mathematical models, to objectively monitor the treatment processes and measurement devices. The pH measurement is a commonly used measurement at different stages in the drinking water treatment plant, although it is a unreliable instrument, requiring significant maintenance. It is shown that, using a grey-box model, it is possible to assess the measurement devices effectively, even if detailed information of the specific processes is unknown.
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NASA Astrophysics Data System (ADS)
Miara, A.; Vorosmarty, C. J.; Stewart, R. J.; Wollheim, W. M.; Rosenzweig, B.
2012-12-01
In the Northeast US, approximately 80% of the available capacity of thermoelectric plants is dependent on the constant availability of water for cooling. Cooling is a necessary process whereby the waste thermal load of a power plant is released and the working fluid (typically steam) condensed to allow the continuation of the thermodynamic cycle and the extraction of electrical power through the action of turbines. Power plants rely on a minimum flow at a certain temperature, determined by the individual plant engineering design, to be sufficiently low for their cooling. Any change in quantity or temperature of water could reduce thermal efficiencies. As a result of the cooling process, power plants emit thermal pollution into receiving waters, which is harmful to freshwater aquatic ecosystems including its resident life forms and their biodiversity. The Clean Water Act of 1972 (CWA) was established to limit thermal pollution, particularly when rivers reach high temperatures. When river temperatures approach the threshold limit, the power plants that use freshwater for cooling are forced to reduce their thermal load and thus their output to comply with the regulations. Here we describe a model that quantifies, in a regional context, thermal pollution and estimates efficiency losses as a result of fluctuating river temperatures and flow. It does this using available data, standard engineering equations describing the heat cycle of power plants and their water use, and assumptions about the operations of the plant. In this presentation, we demonstrate the model by analyzing contrasting climates with and without the CWA, focusing on the productivity of 366 thermoelectric plants that rely on water for cooling in the Northeast between the years 2000-2010. When the CWA was imposed on all simulated power plants, the model shows that during the average winter and summer, 94% and 71% of required generation was met from the power plants, respectively. This suggests that if all power plants were to comply with the CWA and if temperatures do increase in the future as is expected under greenhouse warming, electric power generation in the Northeast may become limited, particularly in the summer. To avoid a potential energy gap, back-up generators and other electric infrastructure, such as hydropower, may have to come online in order to meet the total electric demand. Furthermore, it is clear that the methodology and steps taken in the model are required to more accurately understand, estimate and evaluate the relationship between energy production, environmental and energy policy and biodiversity under forecasted and historic climate conditions. Our ongoing work uses this model to explore various future scenarios of policy, climate and natural resource management in the Northeastern US for the period 2010-2100.
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Edlund, Alan M; Jones, Justin; Lewis, Randolph; Quinn, Jason C
2018-05-25
Major ampullate spider silk represents a promising protein-based biomaterial with diverse commercial potential ranging from textiles to medical devices due to its excellent physical and thermal properties. Recent advancements in synthetic biology have facilitated the development of recombinant spider silk proteins from Escherichia coli (E. coli). This study specifically investigates the economic feasibility and environmental impact of synthetic spider silk manufacturing. Pilot scale data was used to validate an engineering process model that includes all of the required sub-processing steps for synthetic fiber manufacture: production, harvesting, purification, drying, and spinning. Modeling was constructed modularly to support assessment of alternative downstream processing technologies. The techno-economic analysis indicates a minimum sale price from pioneer and optimized E. coli plants of $761 kg -1 and $23 kg -1 with greenhouse gas emissions of 572 kg CO 2-eq. kg -1 and 55 kg CO 2-eq. kg -1 , respectively. Elevated costs and emissions from the pioneer plant can be directly tied to the high material consumption and low protein yield. Decreased production costs associated with the optimized plant includes improved protein yield, process optimization, and an N th plant assumption. Discussion focuses on the commercial potential of spider silk, the production performance requirements for commercialization, and the impact of alternative technologies on the system. Copyright © 2018 Elsevier B.V. All rights reserved.
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Biological mode of action of a nitrophenolates-based biostimulant: case study
Przybysz, Arkadiusz; Gawrońska, Helena; Gajc-Wolska, Janina
2014-01-01
The challenges facing modern plant production involve (i) responding to the demand for food and resources of plant origin from the world's rapidly growing population, (ii) coping with the negative impact of stressful conditions mainly due to anthropopressure, and (iii) meeting consumers' new requirements and preferences for food that is high in nutritive value, natural, and free from harmful chemical additives. Despite employing the most modern plant cultivation technologies and the progress that has been made in breeding programs, the genetically-determined crop potential is still far from being fully exploited. Consequently yield and quality are often reduced, making production less, both profitable and attractive. There is an increasing desire to reduce the chemical input in agriculture and there has been a change toward integrated plant management and sustainable, environmentally-friendly systems. Biostimulants are a category of relatively new products of diverse formulations that positively affect a plant's vital processes and whose impact is usually more evident under stressful conditions. In this paper, information is provided on the mode of action of a nitrophenolates-based biostimulant, Atonik, in model species and economically important crops grown under both field and controlled conditions in a growth chamber. The effects of Atonik on plant morphology, physiology, biochemistry (crops and model plant) and yield and yield parameters (crops) is demonstrated. Effects of other biostimulants on studied in this work processes/parameters are also presented in discussion. PMID:25566287
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Biological mode of action of a nitrophenolates-based biostimulant: case study.
Przybysz, Arkadiusz; Gawrońska, Helena; Gajc-Wolska, Janina
2014-01-01
The challenges facing modern plant production involve (i) responding to the demand for food and resources of plant origin from the world's rapidly growing population, (ii) coping with the negative impact of stressful conditions mainly due to anthropopressure, and (iii) meeting consumers' new requirements and preferences for food that is high in nutritive value, natural, and free from harmful chemical additives. Despite employing the most modern plant cultivation technologies and the progress that has been made in breeding programs, the genetically-determined crop potential is still far from being fully exploited. Consequently yield and quality are often reduced, making production less, both profitable and attractive. There is an increasing desire to reduce the chemical input in agriculture and there has been a change toward integrated plant management and sustainable, environmentally-friendly systems. Biostimulants are a category of relatively new products of diverse formulations that positively affect a plant's vital processes and whose impact is usually more evident under stressful conditions. In this paper, information is provided on the mode of action of a nitrophenolates-based biostimulant, Atonik, in model species and economically important crops grown under both field and controlled conditions in a growth chamber. The effects of Atonik on plant morphology, physiology, biochemistry (crops and model plant) and yield and yield parameters (crops) is demonstrated. Effects of other biostimulants on studied in this work processes/parameters are also presented in discussion.
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NASA Astrophysics Data System (ADS)
Tikhomirov, A. A.; Ushakova, S. A.; Manukovsky, N. S.; Lisovsky, G. M.; Kudenko, Yu A.; Kovalev, V. S.; Gribovksaya, I. V.; Tirranen, L. S.; Zolotukkhin, I. G.; Gros, J. B.; Lasseur, Ch.
Biological life support systems (LSS) with highly closed intrasystem mass ex change mass ex change hold much promise for long-term human life support at planetary stations (Moon, Mars, etc.). The paper considers problems of biosynthesis of higher plants' biomass and "biological incineration" of plant wastes in a working physical model of biological LSS. The plant wastes are "biologically incinerated" in a special heterotroph block involving Californian worms, mushrooms and straw. The block processes plant wastes (straw, haulms) to produce soil-like substrate (SLS) on which plants (wheat, radish) are grown. Gas ex change in such a system consists of respiratory gas ex change of SLS and photosynthesis and respiration of plants. Specifics of gas ex change dynamics of high plants -SLS complex has been considered. Relationship between such a gas ex change and photosynthetic active radiation (PAR) and age of plants has been established. SLS fertility has been shown to depend on its thickness and phase of maturity. The biogenic elements (potassium, phosphorus, nitrogen) in Liebig minimum have been found to include nitrogen which is the first to impair plants' growth in disruption of the process conditions. The SLS microflora has been found to have different kinds of ammonifying and denitrifying bacteria which is indicative of intensive transformation of nitrogen-containing compounds. The number of physiological groups of microorganisms in SLS was, on the whole, steady. As a result, organic substances -products of ex change of plants and microorganisms were not accumulated in the medium, but mineralized and assimilated by the biocenosis. Experiments showed that the developed model of a man-made ecosystem realized complete utilization of plant wastes and involved them into the intrasystem turnover. In multiple recycle of the mat ter (more than 5 cycles) under the irradiance intensity of 150 W/m2 PAR and the SLS mass (dry weight) of 17.7 -19.9 kg/m2 average total harvest of the plant mass was 2.14 kg/m2, the seed harvest was 0.85 kg/m2 (dry weight). The paper considers opportunities of using the technologies considered in biological LSS with long-term human presence.
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Cormier, Marc-André; Werner, Roland A; Sauer, Peter E; Gröcke, Darren R; Leuenberger, Markus C; Wieloch, Thomas; Schleucher, Jürgen; Kahmen, Ansgar
2018-04-01
Hydrogen (H) isotope ratio (δ 2 H) analyses of plant organic compounds have been applied to assess ecohydrological processes in the environment despite a large part of the δ 2 H variability observed in plant compounds not being fully elucidated. We present a conceptual biochemical model based on empirical H isotope data that we generated in two complementary experiments that clarifies a large part of the unexplained variability in the δ 2 H values of plant organic compounds. The experiments demonstrate that information recorded in the δ 2 H values of plant organic compounds goes beyond hydrological signals and can also contain important information on the carbon and energy metabolism of plants. Our model explains where 2 H-fractionations occur in the biosynthesis of plant organic compounds and how these 2 H-fractionations are tightly coupled to a plant's carbon and energy metabolism. Our model also provides a mechanistic basis to introduce H isotopes in plant organic compounds as a new metabolic proxy for the carbon and energy metabolism of plants and ecosystems. Such a new metabolic proxy has the potential to be applied in a broad range of disciplines, including plant and ecosystem physiology, biogeochemistry and palaeoecology. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.
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Demey, D; Vanderhaegen, B; Vanhooren, H; Liessens, J; Van Eyck, L; Hopkins, L; Vanrolleghem, P A
2001-01-01
In this paper, the practical implementation and validation of advanced control strategies, designed using model based techniques, at an industrial wastewater treatment plant is demonstrated. The plant under study is treating the wastewater of a large pharmaceutical production facility. The process characteristics of the wastewater treatment were quantified by means of tracer tests, intensive measurement campaigns and the use of on-line sensors. In parallel, a dynamical model of the complete wastewater plant was developed according to the specific kinetic characteristics of the sludge and the highly varying composition of the industrial wastewater. Based on real-time data and dynamic models, control strategies for the equalisation system, the polymer dosing and phosphorus addition were established. The control strategies are being integrated in the existing SCADA system combining traditional PLC technology with robust PC based control calculations. The use of intelligent control in wastewater treatment offers a wide spectrum of possibilities to upgrade existing plants, to increase the capacity of the plant and to eliminate peaks. This can result in a more stable and secure overall performance and, finally, in cost savings. The use of on-line sensors has a potential not only for monitoring concentrations, but also for manipulating flows and concentrations. This way the performance of the plant can be secured.
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NASA Astrophysics Data System (ADS)
Ise, T.; Litton, C. M.; Giardina, C. P.; Ito, A.
2009-12-01
Plant partitioning of carbon (C) to above- vs. belowground, to growth vs. respiration, and to short vs. long lived tissues exerts a large influence on ecosystem structure and function with implications for the global C budget. Importantly, outcomes of process-based terrestrial vegetation models are likely to vary substantially with different C partitioning algorithms. However, controls on C partitioning patterns remain poorly quantified, and studies have yielded variable, and at times contradictory, results. A recent meta-analysis of forest studies suggests that the ratio of net primary production (NPP) and gross primary production (GPP) is fairly conservative across large scales. To illustrate the effect of this unique meta-analysis-based partitioning scheme (MPS), we compared an application of MPS to a terrestrial satellite-based (MODIS) GPP to estimate NPP vs. two global process-based vegetation models (Biome-BGC and VISIT) to examine the influence of C partitioning on C budgets of woody plants. Due to the temperature dependence of maintenance respiration, NPP/GPP predicted by the process-based models increased with latitude while the ratio remained constant with MPS. Overall, global NPP estimated with MPS was 17 and 27% lower than the process-based models for temperate and boreal biomes, respectively, with smaller differences in the tropics. Global equilibrium biomass of woody plants was then calculated from the NPP estimates and tissue turnover rates from VISIT. Since turnover rates differed greatly across tissue types (i.e., metabolically active vs. structural), global equilibrium biomass estimates were sensitive to the partitioning scheme employed. The MPS estimate of global woody biomass was 7-21% lower than that of the process-based models. In summary, we found that model output for NPP and equilibrium biomass was quite sensitive to the choice of C partitioning schemes. Carbon use efficiency (CUE; NPP/GPP) by forest biome and the globe. Values are means for 2001-2006.
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Comparison of the Light-Harvesting Networks of Plant and Cyanobacterial Photosystem I
Şener, Melih K.; Jolley, Craig; Ben-Shem, Adam; Fromme, Petra; Nelson, Nathan; Croce, Roberta; Schulten, Klaus
2005-01-01
With the availability of structural models for photosystem I (PSI) in cyanobacteria and plants it is possible to compare the excitation transfer networks in this ubiquitous photosystem from two domains of life separated by over one billion years of divergent evolution, thus providing an insight into the physical constraints that shape the networks' evolution. Structure-based modeling methods are used to examine the excitation transfer kinetics of the plant PSI-LHCI supercomplex. For this purpose an effective Hamiltonian is constructed that combines an existing cyanobacterial model for structurally conserved chlorophylls with spectral information for chlorophylls in the Lhca subunits. The plant PSI excitation migration network thus characterized is compared to its cyanobacterial counterpart investigated earlier. In agreement with observations, an average excitation transfer lifetime of ∼49 ps is computed for the plant PSI-LHCI supercomplex with a corresponding quantum yield of 95%. The sensitivity of the results to chlorophyll site energy assignments is discussed. Lhca subunits are efficiently coupled to the PSI core via gap chlorophylls. In contrast to the chlorophylls in the vicinity of the reaction center, previously shown to optimize the quantum yield of the excitation transfer process, the orientational ordering of peripheral chlorophylls does not show such optimality. The finding suggests that after close packing of chlorophylls was achieved, constraints other than efficiency of the overall excitation transfer process precluded further evolution of pigment ordering. PMID:15994896
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Waste heat recovery options in a large gas-turbine combined power plant
NASA Astrophysics Data System (ADS)
Upathumchard, Ularee
This study focuses on power plant heat loss and how to utilize the waste heat in energy recovery systems in order to increase the overall power plant efficiency. The case study of this research is a 700-MW natural gas combined cycle power plant, located in a suburban area of Thailand. An analysis of the heat loss of the combustion process, power generation process, lubrication system, and cooling system has been conducted to evaluate waste heat recovery options. The design of the waste heat recovery options depends to the amount of heat loss from each system and its temperature. Feasible waste heat sources are combustion turbine (CT) room ventilation air and lubrication oil return from the power plant. The following options are being considered in this research: absorption chillers for cooling with working fluids Ammonia-Water and Water-Lithium Bromide (in comparison) and Organic Rankine Cycle (ORC) with working fluids R134a and R245fa. The absorption cycles are modeled in three different stages; single-effect, double-effect and half-effect. ORC models used are simple ORC as a baseline, ORC with internal regenerator, ORC two-phase flash expansion ORC and ORC with multiple heat sources. Thermodynamic models are generated and each system is simulated using Engineering Equation Solver (EES) to define the most suitable waste heat recovery options for the power plant. The result will be synthesized and evaluated with respect to exergy utilization efficiency referred as the Second Law effectiveness and net output capacity. Results of the models give recommendation to install a baseline ORC of R134a and a double-effect water-lithium bromide absorption chiller, driven by ventilation air from combustion turbine compartment. The two technologies yield reasonable economic payback periods of 4.6 years and 0.7 years, respectively. The fact that this selected power plant is in its early stage of operation allows both models to economically and effectively perform waste heat recovery during the power plant's life span. Furthermore, the recommendation from this research will be submitted to the Electricity Generating Authority of Thailand (EGAT) for implementation. This study will also be used as an example for other power plants in Thailand to consider waste energy utilization to improve plant efficiency and sustain fuel resources in the future.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Zitney, S.E.
Emerging fossil energy power generation systems must operate with unprecedented efficiency and near-zero emissions, while optimizing profitably amid cost fluctuations for raw materials, finished products, and energy. To help address these challenges, the fossil energy industry will have to rely increasingly on the use advanced computational tools for modeling and simulating complex process systems. In this paper, we present the computational research challenges and opportunities for the optimization of fossil energy power generation systems across the plant lifecycle from process synthesis and design to plant operations. We also look beyond the plant gates to discuss research challenges and opportunities formore » enterprise-wide optimization, including planning, scheduling, and supply chain technologies.« less
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RUIZ-RAMOS, MARGARITA; MÍNGUEZ, M. INÉS
2006-01-01
• Background Plant structural (i.e. architectural) models explicitly describe plant morphology by providing detailed descriptions of the display of leaf and stem surfaces within heterogeneous canopies and thus provide the opportunity for modelling the functioning of plant organs in their microenvironments. The outcome is a class of structural–functional crop models that combines advantages of current structural and process approaches to crop modelling. ALAMEDA is such a model. • Methods The formalism of Lindenmayer systems (L-systems) was chosen for the development of a structural model of the faba bean canopy, providing both numerical and dynamic graphical outputs. It was parameterized according to the results obtained through detailed morphological and phenological descriptions that capture the detailed geometry and topology of the crop. The analysis distinguishes between relationships of general application for all sowing dates and stem ranks and others valid only for all stems of a single crop cycle. • Results and Conclusions The results reveal that in faba bean, structural parameterization valid for the entire plant may be drawn from a single stem. ALAMEDA was formed by linking the structural model to the growth model ‘Simulation d'Allongement des Feuilles’ (SAF) with the ability to simulate approx. 3500 crop organs and components of a group of nine plants. Model performance was verified for organ length, plant height and leaf area. The L-system formalism was able to capture the complex architecture of canopy leaf area of this indeterminate crop and, with the growth relationships, generate a 3D dynamic crop simulation. Future development and improvement of the model are discussed. PMID:16390842
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Adaptive control and noise suppression by a variable-gain gradient algorithm
NASA Technical Reports Server (NTRS)
Merhav, S. J.; Mehta, R. S.
1987-01-01
An adaptive control system based on normalized LMS filters is investigated. The finite impulse response of the nonparametric controller is adaptively estimated using a given reference model. Specifically, the following issues are addressed: The stability of the closed loop system is analyzed and heuristically established. Next, the adaptation process is studied for piecewise constant plant parameters. It is shown that by introducing a variable-gain in the gradient algorithm, a substantial reduction in the LMS adaptation rate can be achieved. Finally, process noise at the plant output generally causes a biased estimate of the controller. By introducing a noise suppression scheme, this bias can be substantially reduced and the response of the adapted system becomes very close to that of the reference model. Extensive computer simulations validate these and demonstrate assertions that the system can rapidly adapt to random jumps in plant parameters.
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NASA Astrophysics Data System (ADS)
Guédez, R.; Arnaudo, M.; Topel, M.; Zanino, R.; Hassar, Z.; Laumert, B.
2016-05-01
Nowadays, direct steam generation concentrated solar tower plants suffer from the absence of a cost-effective thermal energy storage integration. In this study, the prefeasibility of a combined sensible and latent thermal energy storage configuration has been performed from thermodynamic and economic standpoints as a potential storage option. The main advantage of such concept with respect to only sensible or only latent choices is related to the possibility to minimize the thermal losses during system charge and discharge processes by reducing the temperature and pressure drops occurring all along the heat transfer process. Thermodynamic models, heat transfer models, plant integration and control strategies for both a pressurized tank filled with sphere-encapsulated salts and high temperature concrete storage blocks were developed within KTH in-house tool DYESOPT for power plant performance modeling. Once implemented, cross-validated and integrated the new storage model in an existing DYESOPT power plant layout, a sensitivity analysis with regards of storage, solar field and power block sizes was performed to determine the potential impact of integrating the proposed concept. Even for a storage cost figure of 50 USD/kWh, it was found that the integration of the proposed storage configuration can enhance the performance of the power plants by augmenting its availability and reducing its levelized cost of electricity. As expected, it was also found that the benefits are greater for the cases of smaller power block sizes. Specifically, for a power block of 80 MWe a reduction in levelized electricity costs of 8% was estimated together with an increase in capacity factor by 30%, whereas for a power block of 126 MWe the benefits found were a 1.5% cost reduction and 16% availability increase.
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NASA Technical Reports Server (NTRS)
1984-01-01
A solar pond electric power generation subsystem, an electric power transformer and switch yard, a large solar pond, a water treatment plant, and numerous storage and evaporation ponds. Because a solar pond stores thermal energy over a long period of time, plant operation at any point in time is dependent upon past operation and future perceived generation plans. This time or past history factor introduces a new dimension in the design process. The design optimization of a plant must go beyond examination of operational state points and consider the seasonal variations in solar, solar pond energy storage, and desired plant annual duty-cycle profile. Models or design tools will be required to optimize a plant design. These models should be developed in order to include a proper but not excessive level of detail. The model should be targeted to a specific objective and not conceived as a do everything analysis tool, i.e., system design and not gradient-zone stability.
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Relationships between Gene Structure and Genome Instability in Flowering Plants.
Bennetzen, Jeffrey L; Wang, Xuewen
2018-03-05
Flowering plant (angiosperm) genomes are exceptional in their variability with respect to genome size, ploidy, chromosome number, gene content, and gene arrangement. Gene movement, although observed in some of the earliest plant genome comparisons, has been relatively underinvestigated. We present herein a description of several interesting properties of plant gene and genome structure that are pertinent to the successful movement of a gene to a new location. These considerations lead us to propose a model that can explain the frequent success of plant gene mobility, namely that Small Insulated Genes Move Around (SIGMAR). The SIGMAR model is then compared with known processes for gene mobilization, and predictions of the SIGMAR model are formulated to encourage future experimentation. The overall results indicate that the frequent gene movement in angiosperm genomes is partly an outcome of the unusual properties of angiosperm genes, especially their small size and insulation from epigenetic silencing. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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Global asymptotic stability of plant-seed bank models.
Eager, Eric Alan; Rebarber, Richard; Tenhumberg, Brigitte
2014-07-01
Many plant populations have persistent seed banks, which consist of viable seeds that remain dormant in the soil for many years. Seed banks are important for plant population dynamics because they buffer against environmental perturbations and reduce the probability of extinction. Viability of the seeds in the seed bank can depend on the seed's age, hence it is important to keep track of the age distribution of seeds in the seed bank. In this paper we construct a general density-dependent plant-seed bank model where the seed bank is age-structured. We consider density dependence in both seedling establishment and seed production, since previous work has highlighted that overcrowding can suppress both of these processes. Under certain assumptions on the density dependence, we prove that there is a globally stable equilibrium population vector which is independent of the initial state. We derive an analytical formula for the equilibrium population using methods from feedback control theory. We apply these results to a model for the plant species Cirsium palustre and its seed bank.
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NASA Astrophysics Data System (ADS)
Volo, T. J.; Vivoni, E. R.; Martin, C. A.; Wang, Z.; Ruddell, B.
2012-12-01
Through the past several decades, rapid population growth in the arid American Southwest has dramatically changed patterns of plant-available water through municipal and residential irrigation systems that provide supplemental water to designed and managed urban landscape vegetation. Urban irrigation, including diversion of rainwater and addition of imported water, has thereby enabled the transformation of areas once covered by bare soil and low water-use, native desert plant species to large tracts of exotic, high water-use turf grass and shade trees. Despite the large percentage of residential water appropriated to irrigation purposes, models of urban hydrology often fail to include the impact that this anthropogenic input has on water, energy, and biomass conditions. This study utilizes two one-dimensional soil moisture models to examine the importance of representing different processes in a quantitative urban ecohydrology model under irrigation scenarios. Such processes include sub-daily energy fluxes, vertical redistribution of soil moisture, saturation- and infiltration-excess runoff mechanisms, seasonally variable irrigation scheduling, and soil moisture control on evapotranspiration rates. The analysis is informed by soil moisture observations from an experimental sensor network in the Phoenix, Arizona metropolitan area. The network includes data from several different landscape and irrigation treatments representative of pre- and post-development conditions in the region. By interpreting soil moisture levels in terms of plant water stress, this study analyzes the effectiveness of urban irrigation practices in arid climates. Furthermore, by identifying the necessary hydrologic processes to represent in an urban ecohydrology model, our results inform future work in adapting a distributed hydrologic model to desert urban settings where irrigation plays a significant role in minimizing plant water stress. An appropriate model of water and energy balances, calibrated using local meteorological forcing, can facilitate discussions with water managers and homeowners regarding optimal irrigation frequency, volume, duration, and seasonality for individual landscapes, while also aiding in water-efficient landscape design for growing cities in desert regions.
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Synthetic spider silk sustainability verification by techno-economic and life cycle analysis
NASA Astrophysics Data System (ADS)
Edlund, Alan
Major ampullate spider silk represents a promising biomaterial with diverse commercial potential ranging from textiles to medical devices due to the excellent physical and thermal properties from the protein structure. Recent advancements in synthetic biology have facilitated the development of recombinant spider silk proteins from Escherichia coli (E. coli), alfalfa, and goats. This study specifically investigates the economic feasibility and environmental impact of synthetic spider silk manufacturing. Pilot scale data was used to validate an engineering process model that includes all of the required sub-processing steps for synthetic fiber manufacture: production, harvesting, purification, drying, and spinning. Modeling was constructed modularly to support assessment of alternative protein production methods (alfalfa and goats) as well as alternative down-stream processing technologies. The techno-economic analysis indicates a minimum sale price from pioneer and optimized E. coli plants at 761 kg-1 and 23 kg-1 with greenhouse gas emissions of 572 kg CO2-eq. kg-1 and 55 kg CO2-eq. kg-1, respectively. Spider silk sale price estimates from goat pioneer and optimized results are 730 kg-1 and 54 kg-1, respectively, with pioneer and optimized alfalfa plants are 207 kg-1 and 9.22 kg-1 respectively. Elevated costs and emissions from the pioneer plant can be directly tied to the high material consumption and low protein yield. Decreased production costs associated with the optimized plants include improved protein yield, process optimization, and an Nth plant assumption. Discussion focuses on the commercial potential of spider silk, the production performance requirements for commercialization, and impact of alternative technologies on the sustainability of the system.
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Chemical process simulation has long been used as a design tool in the development of chemical plants, and has long been considered a means to evaluate different design options. With the advent of large scale computer networks and interface models for program components, it is po...
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Santos, Mario, E-mail: mgsantoss@gmail.com; Freitas, Raul, E-mail: raulfreitas@portugalmail.com; Crespi, Antonio L., E-mail: aluis.crespi@gmail.com
2011-10-15
This study assesses the potential of an integrated methodology for predicting local trends in invasive exotic plant species (invasive richness) using indirect, regional information on human disturbance. The distribution of invasive plants was assessed in North Portugal using herbarium collections and local environmental, geophysical and socio-economic characteristics. Invasive richness response to anthropogenic disturbance was predicted using a dynamic model based on a sequential modeling process (stochastic dynamic methodology-StDM). Derived scenarios showed that invasive richness trends were clearly associated with ongoing socio-economic change. Simulations including scenarios of growing urbanization showed an increase in invasive richness while simulations in municipalities with decreasingmore » populations showed stable or decreasing levels of invasive richness. The model simulations demonstrate the interest and feasibility of using this methodology in disturbance ecology. - Highlights: {yields} Socio-economic data indicate human induced disturbances. {yields} Socio-economic development increase disturbance in ecosystems. {yields} Disturbance promotes opportunities for invasive plants.{yields} Increased opportunities promote richness of invasive plants.{yields} Increase in richness of invasive plants change natural ecosystems.« less
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A System for Modelling Cell–Cell Interactions during Plant Morphogenesis
Dupuy, Lionel; Mackenzie, Jonathan; Rudge, Tim; Haseloff, Jim
2008-01-01
Background and aims During the development of multicellular organisms, cells are capable of interacting with each other through a range of biological and physical mechanisms. A description of these networks of cell–cell interactions is essential for an understanding of how cellular activity is co-ordinated in regionalized functional entities such as tissues or organs. The difficulty of experimenting on living tissues has been a major limitation to describing such systems, and computer modelling appears particularly helpful to characterize the behaviour of multicellular systems. The experimental difficulties inherent to the multitude of parallel interactions that underlie cellular morphogenesis have led to the need for computer models. Methods A new generic model of plant cellular morphogenesis is described that expresses interactions amongst cellular entities explicitly: the plant is described as a multi-scale structure, and interactions between distinct entities is established through a topological neighbourhood. Tissues are represented as 2D biphasic systems where the cell wall responds to turgor pressure through a viscous yielding of the cell wall. Key Results This principle was used in the development of the CellModeller software, a generic tool dedicated to the analysis and modelling of plant morphogenesis. The system was applied to three contrasting study cases illustrating genetic, hormonal and mechanical factors involved in plant morphogenesis. Conclusions Plant morphogenesis is fundamentally a cellular process and the CellModeller software, through its underlying generic model, provides an advanced research tool to analyse coupled physical and biological morphogenetic mechanisms. PMID:17921524
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The plant perceptron connects environment to development.
Scheres, Ben; van der Putten, Wim H
2017-03-15
Plants cope with the environment in a variety of ways, and ecological analyses attempt to capture this through life-history strategies or trait-based categorization. These approaches are limited because they treat the trade-off mechanisms that underlie plant responses as a black box. Approaches that involve the molecular or physiological analysis of plant responses to the environment have elucidated intricate connections between developmental and environmental signals, but in only a few well-studied model species. By considering diversity in the plant response to the environment as the adaptation of an information-processing network, new directions can be found for the study of life-history strategies, trade-offs and evolution in plants.
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Diffusion of biostimulators into plant tissues
NASA Astrophysics Data System (ADS)
Kolomazník, Karel; Pecha, Jiří; Friebrová, Veronika; Janáčová, Dagmar; Vašek, Vladimír
2012-09-01
Biostimulators are substances able to enhance the immune system of cultivated crops and support plant metabolism. Their utilization helps to reduce the amount of chemicals used in agriculture. To perform the desired effect, a biostimulator must be able to penetrate into the plant tissue. The time of penetration however, is limited, since the biostimulator must remain in a liquid state. This is of great importance—especially in field conditions, where the treated plants are exposed to different weather condition and other extrinsic factors. A mathematical model based on diffusion mechanisms has been elaborated to describe the biostimulator transport process from penetration of the leaves into the plant's inner tissues. By means of the effective diffusion coefficient of the prepared specific protein hydrolyzate, this model can be used to estimate the time necessary for the uptake of the minimal active amount of the biostimulator.
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Energy models characterize the energy system, its evolution, and its interactions with the broader economy. The energy system consists of primary resources, including both fossil fuels and renewables; power plants, refineries, and other technologies to process and convert these r...
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Coupled Modeling of Rhizosphere and Reactive Transport Processes
NASA Astrophysics Data System (ADS)
Roque-Malo, S.; Kumar, P.
2017-12-01
The rhizosphere, as a bio-diverse plant root-soil interface, hosts many hydrologic and biochemical processes, including nutrient cycling, hydraulic redistribution, and soil carbon dynamics among others. The biogeochemical function of root networks, including the facilitation of nutrient cycling through absorption and rhizodeposition, interaction with micro-organisms and fungi, contribution to biomass, etc., plays an important role in myriad Critical Zone processes. Despite this knowledge, the role of the rhizosphere on watershed-scale ecohydrologic functions in the Critical Zone has not been fully characterized, and specifically, the extensive capabilities of reactive transport models (RTMs) have not been applied to these hydrobiogeochemical dynamics. This study uniquely links rhizospheric processes with reactive transport modeling to couple soil biogeochemistry, biological processes, hydrologic flow, hydraulic redistribution, and vegetation dynamics. Key factors in the novel modeling approach are: (i) bi-directional effects of root-soil interaction, such as simultaneous root exudation and nutrient absorption; (ii) multi-state biomass fractions in soil (i.e. living, dormant, and dead biological and root materials); (iii) expression of three-dimensional fluxes to represent both vertical and lateral interconnected flows and processes; and (iv) the potential to include the influence of non-stationary external forcing and climatic factors. We anticipate that the resulting model will demonstrate the extensive effects of plant root dynamics on ecohydrologic functions at the watershed scale and will ultimately contribute to a better characterization of efflux from both agricultural and natural systems.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Ghimire, Bardan; Riley, William J.; Koven, Charles D.
In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However, current Earth System Models (ESMs) do not mechanistically represent functional nitrogen allocation for photosynthesis or the linkage between nitrogen uptake and root traits. The current version of CLM (4.5) links nitrogen availability and plant productivity via (1) an instantaneous downregulation of potential photosynthesis rates based on soil mineral nitrogen availability, and (2) apportionment of soil nitrogen between plants and competing nitrogen consumers assumed to be proportional to their relative N demands. However, plants do not photosynthesize at potential rates and then downregulate; instead photosynthesis ratesmore » are governed by nitrogen that has been allocated to the physiological processes underpinning photosynthesis. Furthermore, the role of plant roots in nutrient acquisition has also been largely ignored in ESMs. We therefore present a new plant nitrogen model for CLM4.5 with (1) improved representations of linkages between leaf nitrogen and plant productivity based on observed relationships in a global plant trait database and (2) plant nitrogen uptake based on root-scale Michaelis-Menten uptake kinetics. Our model improvements led to a global bias reduction in GPP, LAI, and biomass of 70%, 11%, and 49%, respectively. Furthermore, water use efficiency predictions were improved conceptually, qualitatively, and in magnitude. The new model's GPP responses to nitrogen deposition, CO 2 fertilization, and climate also differed from the baseline model. The mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers led to overall improvements in global carbon cycling predictions.« less
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Ghimire, Bardan; Riley, William J.; Koven, Charles D.; ...
2016-05-01
In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However, current Earth System Models (ESMs) do not mechanistically represent functional nitrogen allocation for photosynthesis or the linkage between nitrogen uptake and root traits. The current version of CLM (4.5) links nitrogen availability and plant productivity via (1) an instantaneous downregulation of potential photosynthesis rates based on soil mineral nitrogen availability, and (2) apportionment of soil nitrogen between plants and competing nitrogen consumers assumed to be proportional to their relative N demands. However, plants do not photosynthesize at potential rates and then downregulate; instead photosynthesis ratesmore » are governed by nitrogen that has been allocated to the physiological processes underpinning photosynthesis. Furthermore, the role of plant roots in nutrient acquisition has also been largely ignored in ESMs. We therefore present a new plant nitrogen model for CLM4.5 with (1) improved representations of linkages between leaf nitrogen and plant productivity based on observed relationships in a global plant trait database and (2) plant nitrogen uptake based on root-scale Michaelis-Menten uptake kinetics. Our model improvements led to a global bias reduction in GPP, LAI, and biomass of 70%, 11%, and 49%, respectively. Furthermore, water use efficiency predictions were improved conceptually, qualitatively, and in magnitude. The new model's GPP responses to nitrogen deposition, CO 2 fertilization, and climate also differed from the baseline model. The mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers led to overall improvements in global carbon cycling predictions.« less
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NASA Astrophysics Data System (ADS)
Ghimire, Bardan; Riley, William J.; Koven, Charles D.; Mu, Mingquan; Randerson, James T.
2016-06-01
In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However, current Earth System Models (ESMs) do not mechanistically represent functional nitrogen allocation for photosynthesis or the linkage between nitrogen uptake and root traits. The current version of CLM (4.5) links nitrogen availability and plant productivity via (1) an instantaneous downregulation of potential photosynthesis rates based on soil mineral nitrogen availability, and (2) apportionment of soil nitrogen between plants and competing nitrogen consumers assumed to be proportional to their relative N demands. However, plants do not photosynthesize at potential rates and then downregulate; instead photosynthesis rates are governed by nitrogen that has been allocated to the physiological processes underpinning photosynthesis. Furthermore, the role of plant roots in nutrient acquisition has also been largely ignored in ESMs. We therefore present a new plant nitrogen model for CLM4.5 with (1) improved representations of linkages between leaf nitrogen and plant productivity based on observed relationships in a global plant trait database and (2) plant nitrogen uptake based on root-scale Michaelis-Menten uptake kinetics. Our model improvements led to a global bias reduction in GPP, LAI, and biomass of 70%, 11%, and 49%, respectively. Furthermore, water use efficiency predictions were improved conceptually, qualitatively, and in magnitude. The new model's GPP responses to nitrogen deposition, CO2 fertilization, and climate also differed from the baseline model. The mechanistic representation of leaf-level nitrogen allocation and a theoretically consistent treatment of competition with belowground consumers led to overall improvements in global carbon cycling predictions.
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Zalabák, David; Pospíšilová, Hana; Šmehilová, Mária; Mrízová, Katarína; Frébort, Ivo; Galuszka, Petr
2013-01-01
Cytokinins (CKs) are ubiquitous phytohormones that participate in development, morphogenesis and many physiological processes throughout plant kingdom. In higher plants, mutants and transgenic cells and tissues with altered activity of CK metabolic enzymes or perception machinery, have highlighted their crucial involvement in different agriculturally important traits, such as productivity, increased tolerance to various stresses and overall plant morphology. Furthermore, recent precise metabolomic analyses have elucidated the specific occurrence and distinct functions of different CK types in various plant species. Thus, smooth manipulation of active CK levels in a spatial and temporal way could be a very potent tool for plant biotechnology in the future. This review summarises recent advances in cytokinin research ranging from transgenic alteration of CK biosynthetic, degradation and glucosylation activities and CK perception to detailed elucidation of molecular processes, in which CKs work as a trigger in model plants. The first attempts to improve the quality of crop plants, focused on cereals are discussed, together with proposed mechanism of action of the responses involved. Copyright © 2011 Elsevier Inc. All rights reserved.
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Improving plant bioaccumulation science through consistent reporting of experimental data.
Fantke, Peter; Arnot, Jon A; Doucette, William J
2016-10-01
Experimental data and models for plant bioaccumulation of organic contaminants play a crucial role for assessing the potential human and ecological risks associated with chemical use. Plants are receptor organisms and direct or indirect vectors for chemical exposures to all other organisms. As new experimental data are generated they are used to improve our understanding of plant-chemical interactions that in turn allows for the development of better scientific knowledge and conceptual and predictive models. The interrelationship between experimental data and model development is an ongoing, never-ending process needed to advance our ability to provide reliable quality information that can be used in various contexts including regulatory risk assessment. However, relatively few standard experimental protocols for generating plant bioaccumulation data are currently available and because of inconsistent data collection and reporting requirements, the information generated is often less useful than it could be for direct applications in chemical assessments and for model development and refinement. We review existing testing guidelines, common data reporting practices, and provide recommendations for revising testing guidelines and reporting requirements to improve bioaccumulation knowledge and models. This analysis provides a list of experimental parameters that will help to develop high quality datasets and support modeling tools for assessing bioaccumulation of organic chemicals in plants and ultimately addressing uncertainty in ecological and human health risk assessments. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Energy recovery from thermal treatment of dewatered sludge in wastewater treatment plants.
Yang, Qingfeng; Dussan, Karla; Monaghan, Rory F D; Zhan, Xinmin
Sewage sludge is a by-product generated from municipal wastewater treatment (WWT) processes. This study examines the conversion of sludge via energy recovery from gasification/combustion for thermal treatment of dewatered sludge. The present analysis is based on a chemical equilibrium model of thermal conversion of previously dewatered sludge with moisture content of 60-80%. Prior to combustion/gasification, sludge is dried to a moisture content of 25-55% by two processes: (1) heat recovered from syngas/flue gas cooling and (2) heat recovered from syngas combustion. The electricity recovered from the combined heat and power process can be reused in syngas cleaning and in the WWT plant. Gas temperature, total heat and electricity recoverable are evaluated using the model. Results show that generation of electricity from dewatered sludge with low moisture content (≤ 70%) is feasible within a self-sufficient sludge treatment process. Optimal conditions for gasification correspond to an equivalence ratio of 2.3 and dried sludge moisture content of 25%. Net electricity generated from syngas combustion can account for 0.071 kWh/m(3) of wastewater treated, which is up to 25.4-28.4% of the WWT plant's total energy consumption.
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Evaluation of Terrestrial Carbon Cycle with the Land Use Harmonization Dataset
NASA Astrophysics Data System (ADS)
Sasai, T.; Nemani, R. R.
2017-12-01
CO2 emission by land use and land use change (LULUC) has still had a large uncertainty (±50%). We need to more accurately reveal a role of each LULUC process on terrestrial carbon cycle, and to develop more complicated land cover change model, leading to improve our understanding of the mechanism of global warming. The existing biosphere model studies do not necessarily have enough major LULUC process in the model description (e.g., clear cutting and residual soil carbon). The issue has the potential for causing an underestimation of the effect of LULUC on the global carbon exchange. In this study, the terrestrial biosphere model was modified with several LULUC processes according to the land use harmonization data set. The global mean LULUC emission from the year 1850 to 2000 was 137.2 (PgC 151year-1), and we found the noticeable trend in tropical region. As with the case of primary production in the existing studies, our results emphasized the role of tropical forest on wood productization and residual soil organic carbon by cutting. Global mean NEP was decreased by LULUC. NEP is largely affected by decreasing leaf biomass (photosynthesis) by deforestation process and increasing plant growth rate by regrowth process. We suggested that the model description related to deforestation, residual soil decomposition, wood productization and plant regrowth is important to develop a biosphere model for estimating long-term global carbon cycle.
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Archaeological data reveal slow rates of evolution during plant domestication.
Purugganan, Michael D; Fuller, Dorian Q
2011-01-01
Domestication is an evolutionary process of species divergence in which morphological and physiological changes result from the cultivation/tending of plant or animal species by a mutualistic partner, most prominently humans. Darwin used domestication as an analogy to evolution by natural selection although there is strong debate on whether this process of species evolution by human association is an appropriate model for evolutionary study. There is a presumption that selection under domestication is strong and most models assume rapid evolution of cultivated species. Using archaeological data for 11 species from 60 archaeological sites, we measure rates of evolution in two plant domestication traits--nonshattering and grain/seed size increase. Contrary to previous assumptions, we find the rates of phenotypic evolution during domestication are slow, and significantly lower or comparable to those observed among wild species subjected to natural selection. Our study indicates that the magnitudes of the rates of evolution during the domestication process, including the strength of selection, may be similar to those measured for wild species. This suggests that domestication may be driven by unconscious selection pressures similar to that observed for natural selection, and the study of the domestication process may indeed prove to be a valid model for the study of evolutionary change. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.
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Vieira, A.
2010-01-01
Background: In relation to pharmacognosy, an objective of many ethnobotanical studies is to identify plant species to be further investigated, for example, tested in disease models related to the ethnomedicinal application. To further warrant such testing, research evidence for medicinal applications of these plants (or of their major phytochemical constituents and metabolic derivatives) is typically analyzed in biomedical databases. Methods: As a model of this process, the current report presents novel information regarding traditional anti-inflammation and anti-infection medicinal plant use. This information was obtained from an interview-based ethnobotanical study; and was compared with current biomedical evidence using the Medline® database. Results: Of the 8 anti-infection plant species identified in the ethnobotanical study, 7 have related activities reported in the database; and of the 6 anti-inflammation plants, 4 have related activities in the database. Conclusion: Based on novel and complimentary results from the ethnobotanical and biomedical database analyses, it is suggested that some of these plants warrant additional investigation of potential anti-inflammatory or anti-infection activities in related disease models, and also additional studies in other population groups. PMID:21589754
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Altundag, Huseyin; Albayrak, Sinem; Dundar, Mustafa S; Tuzen, Mustafa; Soylak, Mustafa
2015-11-01
The main aim of this study was an investigation of the influence of selected soil and plant properties on the bioaccessibility of trace elements and hence their potential impacts on human health in urban environments. Two artificial digestion models were used to determine trace element levels passing from soil and plants to man for bioavailability study. Soil and plant samples were collected from various regions of the province of Sakarya, Turkey. Digestive process is started by addition of soil and plant samples to an artificial digestion model based on human physiology. Bioavailability % values are obtained from the ratio of the amount of element passing to human digestion to element content of soil and plants. According to bioavailability % results, element levels passing from soil samples to human digestion were B = Cr = Cu = Fe = Pb = Li < Al < Ni < Co < Ba < Mn < Sr < Cd < Na < Zn < Tl, while element levels passing from plant samples to human digestion were Cu = Fe = Ni = Pb = Tl = Na = Li < Co < Al < Sr < Ba < Mn < Cd < Cr < Zn < B. It was checked whether the results obtained reached harmful levels to human health by examining the literature.
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Zhu, Qing; Riley, William J; Tang, Jinyun
2017-04-01
Terrestrial plants assimilate anthropogenic CO 2 through photosynthesis and synthesizing new tissues. However, sustaining these processes requires plants to compete with microbes for soil nutrients, which therefore calls for an appropriate understanding and modeling of nutrient competition mechanisms in Earth System Models (ESMs). Here, we survey existing plant-microbe competition theories and their implementations in ESMs. We found no consensus regarding the representation of nutrient competition and that observational and theoretical support for current implementations are weak. To reconcile this situation, we applied the Equilibrium Chemistry Approximation (ECA) theory to plant-microbe nitrogen competition in a detailed grassland 15 N tracer study and found that competition theories in current ESMs fail to capture observed patterns and the ECA prediction simplifies the complex nature of nutrient competition and quantitatively matches the 15 N observations. Since plant carbon dynamics are strongly modulated by soil nutrient acquisition, we conclude that (1) predicted nutrient limitation effects on terrestrial carbon accumulation by existing ESMs may be biased and (2) our ECA-based approach may improve predictions by mechanistically representing plant-microbe nutrient competition. © 2016 by the Ecological Society of America.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, J.; Mowrey, J.
1995-12-01
This report describes the design, development and testing of process controls for selected system operations in the Browns Ferry Nuclear Plant (BFNP) Reactor Water Cleanup System (RWCU) using a Computer Simulation Platform which simulates the RWCU System and the BFNP Integrated Computer System (ICS). This system was designed to demonstrate the feasibility of the soft control (video touch screen) of nuclear plant systems through an operator console. The BFNP Integrated Computer System, which has recently. been installed at BFNP Unit 2, was simulated to allow for operator control functions of the modeled RWCU system. The BFNP Unit 2 RWCU systemmore » was simulated using the RELAP5 Thermal/Hydraulic Simulation Model, which provided the steady-state and transient RWCU process variables and simulated the response of the system to control system inputs. Descriptions of the hardware and software developed are also included in this report. The testing and acceptance program and results are also detailed in this report. A discussion of potential installation of an actual RWCU process control system in BFNP Unit 2 is included. Finally, this report contains a section on industry issues associated with installation of process control systems in nuclear power plants.« less
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Epigenetic processes in flowering plant reproduction.
Wang, Guifeng; Köhler, Claudia
2017-02-01
Seeds provide up to 70% of the energy intake of the human population, emphasizing the relevance of understanding the genetic and epigenetic mechanisms controlling seed formation. In flowering plants, seeds are the product of a double fertilization event, leading to the formation of the embryo and the endosperm surrounded by maternal tissues. Analogous to mammals, plants undergo extensive epigenetic reprogramming during both gamete formation and early seed development, a process that is supposed to be required to enforce silencing of transposable elements and thus to maintain genome stability. Global changes of DNA methylation, histone modifications, and small RNAs are closely associated with epigenome programming during plant reproduction. Here, we review current knowledge on chromatin changes occurring during sporogenesis and gametogenesis, as well as early seed development in major flowering plant models. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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Community exposure to asbestos from a vermiculite exfoliation plant in NE Minneapolis.
Kelly, James; Pratt, Gregory C; Johnson, Jean; Messing, Rita B
2006-11-01
Western Mineral Products/W. R. Grace operated a vermiculite plant in a mixed industrial/residential area of northeast Minneapolis from 1936 to 1989. The plant processed vermiculite ore contaminated with amphibole asbestos from a mine in Libby, MT. Air monitoring in the early 1970s found fiber concentrations in excess of 10 fibers per cubic centimeter of air (f/cc), indicating that worker exposure to asbestos was occasionally 100 times the current occupational standard. Residents of the surrounding community also had direct contact with vermiculite processing wastes (containing up to 10% amphibole asbestos) that were made freely available. Children played on waste piles and neighborhood residents hauled the wastes away for home use. In total, 259 contaminated residential properties have been found to date. Reported emission factors and plant process data were used as inputs to model airborne emissions from the plant over several operating scenarios using the U.S. Environmental Protection Agency (EPA) ISC-Prime model. Results estimate short-term air concentrations of asbestos fibers in residential areas nearest the plant may have at times exceeded current occupational standards. Exposure estimates for other pathways were derived primarily from assessments done in Libby by the U.S. EPA. The Northeast Minneapolis Community Vermiculite Investigation (NMCVI) was conducted by the Minnesota Department of Health to identify and characterize the exposures of a cohort of over 6000 people who live or lived in Northeast Minneapolis and may have been exposed to asbestos. This cohort is now being investigated in a respiratory health screening study conducted by the University of Minnesota and the Minnesota Department of Health.
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RIP-ET: A riparian evapotranspiration package for MODFLOW-2005
Maddock, Thomas; Baird, Kathryn J.; Hanson, R.T.; Schmid, Wolfgang; Ajami, Hoori
2012-01-01
A new evapotranspiration package for the U.S. Geological Survey's groundwater-flow model, MODFLOW, is documented. The Riparian Evapotranspiration Package (RIP-ET) provides flexibility in simulating riparian and wetland transpiration not provided by the Evapotranspiration (EVT) or Segmented Function Evapotranspiration (ETS1) Packages for MODFLOW 2005. This report describes how the RIP-ET package was conceptualized and provides input instructions, listings and explanations of the source code, and an example. Traditional approaches to modeling evapotranspiration (ET) processes assume a piecewise linear relationship between ET flux and hydraulic head. The RIP-ET replaces this traditional relationship with a segmented, nonlinear dimensionless curve that reflects the eco-physiology of riparian and wetland ecosystems. Evapotranspiration losses from these ecosystems are dependent not only on hydraulic head, but on the plant types present. User-defined plant functional groups (PFGs) are used to elucidate the interaction between plant transpiration and groundwater conditions. Five generalized plant functional groups based on transpiration rates, plant rooting depth, and water tolerance ranges are presented: obligate wetland, shallow-rooted riparian, deep-rooted riparian, transitional riparian and bare ground/open water. Plant functional groups can be further divided into subgroups (PFSGs) based on plant size, density or other characteristics. The RIP-ET allows for partial habitat coverage and mixtures of plant functional subgroups to be present in a single model cell. RIP-ET also distinguishes between plant transpiration and bare-ground evaporation. Habitat areas are designated by polygons; each polygon can contain a mixture of PFSGs and bare ground, and is assigned a surface elevation. This process requires a determination of fractional coverage for each of the plant functional subgroups present in a polygon to account for the mixture of coverage types and resulting transpiration. The fractional cover within a cell has two components: (1) the polygonal fraction of active habitat (excluding area of bare ground, dead trees, or brush) in a cell, and (2) fraction of plant type area or bare ground area in a polygon. RIP-ET determines the transpiration rate for each plant functional group and evaporation from bare ground/open water in a cell, the total ET in the cell, and the total ET rate over the region of simulation.
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Real-time Adaptive Control Using Neural Generalized Predictive Control
NASA Technical Reports Server (NTRS)
Haley, Pam; Soloway, Don; Gold, Brian
1999-01-01
The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.
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Analysing growth and development of plants jointly using developmental growth stages
Dambreville, Anaëlle; Lauri, Pierre-Éric; Normand, Frédéric; Guédon, Yann
2015-01-01
Background and Aims Plant growth, the increase of organ dimensions over time, and development, the change in plant structure, are often studied as two separate processes. However, there is structural and functional evidence that these two processes are strongly related. The aim of this study was to investigate the co-ordination between growth and development using mango trees, which have well-defined developmental stages. Methods Developmental stages, determined in an expert way, and organ sizes, determined from objective measurements, were collected during the vegetative growth and flowering phases of two cultivars of mango, Mangifera indica. For a given cultivar and growth unit type (either vegetative or flowering), a multistage model based on absolute growth rate sequences deduced from the measurements was first built, and then growth stages deduced from the model were compared with developmental stages. Key Results Strong matches were obtained between growth stages and developmental stages, leading to a consistent definition of integrative developmental growth stages. The growth stages highlighted growth asynchronisms between two topologically connected organs, namely the vegetative axis and its leaves. Conclusions Integrative developmental growth stages emphasize that developmental stages are closely related to organ growth rates. The results are discussed in terms of the possible physiological processes underlying these stages, including plant hydraulics, biomechanics and carbohydrate partitioning. PMID:25452250
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Parametric Modeling for Fluid Systems
NASA Technical Reports Server (NTRS)
Pizarro, Yaritzmar Rosario; Martinez, Jonathan
2013-01-01
Fluid Systems involves different projects that require parametric modeling, which is a model that maintains consistent relationships between elements as is manipulated. One of these projects is the Neo Liquid Propellant Testbed, which is part of Rocket U. As part of Rocket U (Rocket University), engineers at NASA's Kennedy Space Center in Florida have the opportunity to develop critical flight skills as they design, build and launch high-powered rockets. To build the Neo testbed; hardware from the Space Shuttle Program was repurposed. Modeling for Neo, included: fittings, valves, frames and tubing, between others. These models help in the review process, to make sure regulations are being followed. Another fluid systems project that required modeling is Plant Habitat's TCUI test project. Plant Habitat is a plan to develop a large growth chamber to learn the effects of long-duration microgravity exposure to plants in space. Work for this project included the design and modeling of a duct vent for flow test. Parametric Modeling for these projects was done using Creo Parametric 2.0.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Ladd-Lively, Jennifer L
2014-01-01
The objective of this work was to determine the feasibility of using on-line multivariate statistical process control (MSPC) for safeguards applications in natural uranium conversion plants. Multivariate statistical process control is commonly used throughout industry for the detection of faults. For safeguards applications in uranium conversion plants, faults could include the diversion of intermediate products such as uranium dioxide, uranium tetrafluoride, and uranium hexafluoride. This study was limited to a 100 metric ton of uranium (MTU) per year natural uranium conversion plant (NUCP) using the wet solvent extraction method for the purification of uranium ore concentrate. A key component inmore » the multivariate statistical methodology is the Principal Component Analysis (PCA) approach for the analysis of data, development of the base case model, and evaluation of future operations. The PCA approach was implemented through the use of singular value decomposition of the data matrix where the data matrix represents normal operation of the plant. Component mole balances were used to model each of the process units in the NUCP. However, this approach could be applied to any data set. The monitoring framework developed in this research could be used to determine whether or not a diversion of material has occurred at an NUCP as part of an International Atomic Energy Agency (IAEA) safeguards system. This approach can be used to identify the key monitoring locations, as well as locations where monitoring is unimportant. Detection limits at the key monitoring locations can also be established using this technique. Several faulty scenarios were developed to test the monitoring framework after the base case or normal operating conditions of the PCA model were established. In all of the scenarios, the monitoring framework was able to detect the fault. Overall this study was successful at meeting the stated objective.« less
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USDA-ARS?s Scientific Manuscript database
Listeria monocytogenes is a foodborne pathogen that has been associated with poultry products. This organism is ubiquitous in nature and has been found to enter poultry further processing plants on incoming raw product. Once in the plant, L. monocytogenes can become a long term persistent colonize...
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Proceedings of the 1984 IEEE international conference on systems, man and cybernetics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1984-01-01
This conference contains papers on artificial intelligence, pattern recognition, and man-machine systems. Topics considered include concurrent minimization, a robot programming system, system modeling and simulation, camera calibration, thermal power plants, image processing, fault diagnosis, knowledge-based systems, power systems, hydroelectric power plants, expert systems, and electrical transients.
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USDA-ARS?s Scientific Manuscript database
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed twelve controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinan...
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SOS based robust H(∞) fuzzy dynamic output feedback control of nonlinear networked control systems.
Chae, Seunghwan; Nguang, Sing Kiong
2014-07-01
In this paper, a methodology for designing a fuzzy dynamic output feedback controller for discrete-time nonlinear networked control systems is presented where the nonlinear plant is modelled by a Takagi-Sugeno fuzzy model and the network-induced delays by a finite state Markov process. The transition probability matrix for the Markov process is allowed to be partially known, providing a more practical consideration of the real world. Furthermore, the fuzzy controller's membership functions and premise variables are not assumed to be the same as the plant's membership functions and premise variables, that is, the proposed approach can handle the case, when the premise of the plant are not measurable or delayed. The membership functions of the plant and the controller are approximated as polynomial functions, then incorporated into the controller design. Sufficient conditions for the existence of the controller are derived in terms of sum of square inequalities, which are then solved by YALMIP. Finally, a numerical example is used to demonstrate the validity of the proposed methodology.
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Refining and end use study of coal liquids II - linear programming analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lowe, C.; Tam, S.
1995-12-31
A DOE-funded study is underway to determine the optimum refinery processing schemes for producing transportation fuels that will meet CAAA regulations from direct and indirect coal liquids. The study consists of three major parts: pilot plant testing of critical upgrading processes, linear programming analysis of different processing schemes, and engine emission testing of final products. Currently, fractions of a direct coal liquid produced form bituminous coal are being tested in sequence of pilot plant upgrading processes. This work is discussed in a separate paper. The linear programming model, which is the subject of this paper, has been completed for themore » petroleum refinery and is being modified to handle coal liquids based on the pilot plant test results. Preliminary coal liquid evaluation studies indicate that, if a refinery expansion scenario is adopted, then the marginal value of the coal liquid (over the base petroleum crude) is $3-4/bbl.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Bostick, Devin; Stoffregen, Torsten; Rigby, Sean
This topical report presents the techno-economic evaluation of a 550 MWe supercritical pulverized coal (PC) power plant utilizing Illinois No. 6 coal as fuel, integrated with 1) a previously presented (for a subcritical PC plant) Linde-BASF post-combustion CO 2 capture (PCC) plant incorporating BASF’s OASE® blue aqueous amine-based solvent (LB1) [Ref. 6] and 2) a new Linde-BASF PCC plant incorporating the same BASF OASE® blue solvent that features an advanced stripper interstage heater design (SIH) to optimize heat recovery in the PCC process. The process simulation and modeling for this report is performed using Aspen Plus V8.8. Technical information frommore » the PCC plant is determined using BASF’s proprietary thermodynamic and process simulation models. The simulations developed and resulting cost estimates are first validated by reproducing the results of DOE/NETL Case 12 representing a 550 MWe supercritical PC-fired power plant with PCC incorporating a monoethanolamine (MEA) solvent as used in the DOE/NETL Case 12 reference [Ref. 2]. The results of the techno-economic assessment are shown comparing two specific options utilizing the BASF OASE® blue solvent technology (LB1 and SIH) to the DOE/NETL Case 12 reference. The results are shown comparing the energy demand for PCC, the incremental fuel requirement, and the net higher heating value (HHV) efficiency of the PC power plant integrated with the PCC plant. A comparison of the capital costs for each PCC plant configuration corresponding to a net 550 MWe power generation is also presented. Lastly, a cost of electricity (COE) and cost of CO 2 captured assessment is shown illustrating the substantial cost reductions achieved with the Linde-BASF PCC plant utilizing the advanced SIH configuration in combination with BASF’s OASE® blue solvent technology as compared to the DOE/NETL Case 12 reference. The key factors contributing to the reduction of COE and the cost of CO 2 captured, along with quantification of the magnitude of the reductions achieved by each of these factors, are also discussed. Additionally, a high-level techno-economic analysis of one more highly advanced Linde-BASF PCC configuration case (LB1-CREB) is also presented to demonstrate the significant impact of innovative PCC plant process design improvements on further reducing COE and cost of CO 2 captured for overall plant cost and performance comparison purposes. Overall, the net efficiency of the integrated 550 MWe supercritical PC power plant with CO 2 capture is increased from 28.4% with the DOE/NETL Case 12 reference to 30.9% with the Linde-BASF PCC plant previously presented utilizing the BASF OASE® blue solvent [Ref. 6], and is further increased to 31.4% using Linde-BASF PCC plant with BASF OASE® blue solvent and an advanced SIH configuration. The Linde-BASF PCC plant incorporating the BASF OASE® blue solvent also results in significantly lower overall capital costs, thereby reducing the COE and cost of CO 2 captured from $147.25/MWh and $56.49/MT CO 2, respectively, for the reference DOE/NETL Case 12 plant, to $128.49/MWh and $41.85/MT CO 2 for process case LB1, respectively, and $126.65/MWh and $40.66/MT CO 2 for process case SIH, respectively. With additional innovative Linde-BASF PCC process configuration improvements, the COE and cost of CO2 captured can be further reduced to $125.51/MWh and $39.90/MT CO 2 for LB1-CREB. Most notably, the Linde-BASF process options presented here have already demonstrated the potential to lower the cost of CO2 captured below the DOE target of $40/MT CO 2 at the 550 MWe scale for second generation PCC technologies.« less
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Systems Analysis of Physical Absorption of CO2 in Ionic Liquids for Pre-Combustion Carbon Capture.
Zhai, Haibo; Rubin, Edward S
2018-04-17
This study develops an integrated technical and economic modeling framework to investigate the feasibility of ionic liquids (ILs) for precombustion carbon capture. The IL 1-hexyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide is modeled as a potential physical solvent for CO 2 capture at integrated gasification combined cycle (IGCC) power plants. The analysis reveals that the energy penalty of the IL-based capture system comes mainly from the process and product streams compression and solvent pumping, while the major capital cost components are the compressors and absorbers. On the basis of the plant-level analysis, the cost of CO 2 avoided by the IL-based capture and storage system is estimated to be $63 per tonne of CO 2 . Technical and economic comparisons between IL- and Selexol-based capture systems at the plant level show that an IL-based system could be a feasible option for CO 2 capture. Improving the CO 2 solubility of ILs can simplify the capture process configuration and lower the process energy and cost penalties to further enhance the viability of this technology.
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Drawing lines and borders: how the dehiscent fruit of Arabidopsis is patterned.
Dinneny, José R; Yanofsky, Martin F
2005-01-01
The advent of fruits marked a key innovation in the evolution of flowering plants and helped generate a diverse array of mechanisms for seed dispersal. In the model plant, Arabidopsis thaliana, seed dispersal occurs through a process known as "pod-shatter" in which the fruit structure falls to pieces upon light mechanical pressures. This dispersal mechanism is dependent on the careful patterning of tissues in the fruit, which perform diverse functions that enable the fruit to open at maturation. Using the genetic power of Arabidopsis, many of the molecular components that help specify these tissues have been identified. Studies of the interactions among these genes have revealed a regulatory network that limits processes such as cell-cell separation and lignification to discreet regions of the fruit. Knowledge of these processes in a model fruit creates a foundation on which to build an understanding of the evolution of fruit form in other species and provides tools to engineer shatter-resistant seed pods to prevent crop loss in plants of agronomic importance such as canola. Copyright 2004 Wiley Periodicals, Inc.
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Plant-wide (BSM2) evaluation of reject water treatment with a SHARON-Anammox process.
Volcke, E I P; Gernaey, K V; Vrecko, D; Jeppsson, U; van Loosdrecht, M C M; Vanrolleghem, P A
2006-01-01
In wastewater treatment plants (WWTPs) equipped with sludge digestion and dewatering systems, the reject water originating from these facilities contributes significantly to the nitrogen load of the activated sludge tanks, to which it is typically recycled. In this paper, the impact of reject water streams on the performance of a WWTP is assessed in a simulation study, using the Benchmark Simulation Model no. 2 (BSM2), that includes the processes describing sludge treatment and in this way allows for plant-wide evaluation. Comparison of performance of a WWTP without reject water with a WWTP where reject water is recycled to the primary clarifier, i.e. the BSM2 plant, shows that the ammonium load of the influent to the primary clarifier is 28% higher in the case of reject water recycling. This results in violation of the effluent total nitrogen limit. In order to relieve the main wastewater treatment plant, reject water treatment with a combined SHARON-Anammox process seems a promising option. The simulation results indicate that significant improvements of the effluent quality of the main wastewater treatment plant can be realized. An economic evaluation of the different scenarios is performed using an Operating Cost Index (OCI).
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NASA Astrophysics Data System (ADS)
Bartholomeus, Ruud P.; Witte, Jan-Philip M.; van Bodegom, Peter M.; van Dam, Jos C.; Aerts, Rien
2008-10-01
SummaryEffects of insufficient soil aeration on the functioning of plants form an important field of research. A well-known and frequently used utility to express oxygen stress experienced by plants is the Feddes-function. This function reduces root water uptake linearly between two constant pressure heads, representing threshold values for minimum and maximum oxygen deficiency. However, the correctness of this expression has never been evaluated and constant critical values for oxygen stress are likely to be inappropriate. On theoretical grounds it is expected that oxygen stress depends on various abiotic and biotic factors. In this paper, we propose a fundamentally different approach to assess oxygen stress: we built a plant physiological and soil physical process-based model to calculate the minimum gas filled porosity of the soil ( ϕgas_min) at which oxygen stress occurs. First, we calculated the minimum oxygen concentration in the gas phase of the soil needed to sustain the roots through (micro-scale) diffusion with just enough oxygen to respire. Subsequently, ϕgas_min that corresponds to this minimum oxygen concentration was calculated from diffusion from the atmosphere through the soil (macro-scale). We analyzed the validity of constant critical values to represent oxygen stress in terms of ϕgas_min, based on model simulations in which we distinguished different soil types and in which we varied temperature, organic matter content, soil depth and plant characteristics. Furthermore, in order to compare our model results with the Feddes-function, we linked root oxygen stress to root water uptake (through the sink term variable F, which is the ratio of actual and potential uptake). The simulations showed that ϕgas_min is especially sensitive to soil temperature, plant characteristics (root dry weight and maintenance respiration coefficient) and soil depth but hardly to soil organic matter content. Moreover, ϕgas_min varied considerably between soil types and was larger in sandy soils than in clayey soils. We demonstrated that F of the Feddes-function indeed decreases approximately linearly, but that actual oxygen stress already starts at drier conditions than according to the Feddes-function. How much drier is depended on the factors indicated above. Thus, the Feddes-function might cause large errors in the prediction of transpiration reduction and growth reduction through oxygen stress. We made our method easily accessible to others by implementing it in SWAP, a user-friendly soil water model that is coupled to plant growth. Since constant values for ϕgas_min in plant and hydrological modeling appeared to be inappropriate, an integrated approach, including both physiological and physical processes, should be used instead. Therefore, we advocate using our method in all situations where oxygen stress could occur.
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Hemoglobins, programmed cell death and somatic embryogenesis.
Hill, Robert D; Huang, Shuanglong; Stasolla, Claudio
2013-10-01
Programmed cell death (PCD) is a universal process in all multicellular organisms. It is a critical component in a diverse number of processes ranging from growth and differentiation to response to stress. Somatic embryogenesis is one such process where PCD is significantly involved. Nitric oxide is increasingly being recognized as playing a significant role in regulating PCD in both mammalian and plant systems. Plant hemoglobins scavenge NO, and evidence is accumulating that events that modify NO levels in plants also affect hemoglobin expression. Here, we review the process of PCD, describing the involvement of NO and plant hemoglobins in the process. NO is an effector of cell death in both plants and vertebrates, triggering the cascade of events leading to targeted cell death that is a part of an organism's response to stress or to tissue differentiation and development. Expression of specific hemoglobins can alter this response in plants by scavenging the NO, thus, interrupting the death process. Somatic embryogenesis is used as a model system to demonstrate how cell-specific expression of different classes of hemoglobins can alter the embryogenic process, affecting hormone synthesis, cell metabolite levels and genes associated with PCD and embryogenic competence. We propose that plant hemoglobins influence somatic embryogenesis and PCD through cell-specific expression of a distinct plant hemoglobin. It is based on the premise that both embryogenic competence and PCD are strongly influenced by cellular NO levels. Increases in cellular NO levels result in elevated Zn(2+) and reactive-oxygen species associated with PCD, but they also result in decreased expression of MYC2, a transcription factor that is a negative effector of indoleacetic acid synthesis, a hormone that positively influences embryogenic competence. Cell-specific hemoglobin expression reduces NO levels as a result of NO scavenging, resulting in cell survival. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
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Prediction of wastewater treatment plants performance based on artificial fish school neural network
NASA Astrophysics Data System (ADS)
Zhang, Ruicheng; Li, Chong
2011-10-01
A reliable model for wastewater treatment plant is essential in providing a tool for predicting its performance and to form a basis for controlling the operation of the process. This would minimize the operation costs and assess the stability of environmental balance. For the multi-variable, uncertainty, non-linear characteristics of the wastewater treatment system, an artificial fish school neural network prediction model is established standing on actual operation data in the wastewater treatment system. The model overcomes several disadvantages of the conventional BP neural network. The results of model calculation show that the predicted value can better match measured value, played an effect on simulating and predicting and be able to optimize the operation status. The establishment of the predicting model provides a simple and practical way for the operation and management in wastewater treatment plant, and has good research and engineering practical value.
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The resilience and functional role of moss in boreal and arctic ecosystems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Turetsky, Merritt; Bond-Lamberty, Benjamin; Euskirchen, Eugenie S.
2012-08-24
Mosses in boreal and arctic ecosystems are ubiquitous components of plant communities, represent an important component of plant diversity, and strongly influence the cycling of water, nutrients, energy and carbon. Here we use a literature review and synthesis as well as model simulations to explore the role of moss in ecological stability and resilience. Our literature review of moss community responses to disturbance showed all possible responses (increases, decreases, no change) within most disturbance categories in boreal and arctic regions. Our modeling simulations suggest that loss of moss within northern plant communities will reduce soil carbon accumulation primarily by influencingmore » decomposition rates and soil nitrogen availability. While two models (HPM and STM-TEM) showed a significant effect of moss removal, results from the Biome-BGC and DVM-TEM models suggest that northern, moss-rich ecosystems would need to experience extreme perturbation before mosses were eliminated. We highlight a number of issues that have not been adequately explored in moss communities, such as functional redundancy and singularity, relationships between response and effect traits, phenotypical plasticity in traits, and whether the effects of moss on ecosystem processes scale with local abundance. We also suggest that as more models explore issues related to ecological resilience, issues related to both parameter and conceptual uncertainty should be addressed: are the models more limited by uncertainty in the parameterization of the processes included or by what is not represented in the model at all? It seems clear from our review that mosses need to be incorporated into models as one or more plant functional types, but more empirical work is needed to determine how to best aggregate species.« less
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Modeling Endoplasmic Reticulum Network Maintenance in a Plant Cell.
Lin, Congping; White, Rhiannon R; Sparkes, Imogen; Ashwin, Peter
2017-07-11
The endoplasmic reticulum (ER) in plant cells forms a highly dynamic network of complex geometry. ER network morphology and dynamics are influenced by a number of biophysical processes, including filament/tubule tension, viscous forces, Brownian diffusion, and interactions with many other organelles and cytoskeletal elements. Previous studies have indicated that ER networks can be thought of as constrained minimal-length networks acted on by a variety of forces that perturb and/or remodel the network. Here, we study two specific biophysical processes involved in remodeling. One is the dynamic relaxation process involving a combination of tubule tension and viscous forces. The other is the rapid creation of cross-connection tubules by direct or indirect interactions with cytoskeletal elements. These processes are able to remodel the ER network: the first reduces network length and complexity whereas the second increases both. Using live cell imaging of ER network dynamics in tobacco leaf epidermal cells, we examine these processes on ER network dynamics. Away from regions of cytoplasmic streaming, we suggest that the dynamic network structure is a balance between the two processes, and we build an integrative model of the two processes for network remodeling. This model produces quantitatively similar ER networks to those observed in experiments. We use the model to explore the effect of parameter variation on statistical properties of the ER network. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.
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Responses of Aquatic Plants to Eutrophication in Rivers: A Revised Conceptual Model
O’Hare, Matthew T.; Baattrup-Pedersen, Annette; Baumgarte, Inga; Freeman, Anna; Gunn, Iain D. M.; Lázár, Attila N.; Sinclair, Raeannon; Wade, Andrew J.; Bowes, Michael J.
2018-01-01
Compared to research on eutrophication in lakes, there has been significantly less work carried out on rivers despite the importance of the topic. However, over the last decade, there has been a surge of interest in the response of aquatic plants to eutrophication in rivers. This is an area of applied research and the work has been driven by the widespread nature of the impacts and the significant opportunities for system remediation. A conceptual model has been put forward to describe how aquatic plants respond to eutrophication. Since the model was created, there have been substantial increases in our understanding of a number of the underlying processes. For example, we now know the threshold nutrient concentrations at which nutrients no longer limit algal growth. We also now know that the physical habitat template of rivers is a primary selector of aquatic plant communities. As such, nutrient enrichment impacts on aquatic plant communities are strongly influenced, both directly and indirectly, by physical habitat. A new conceptual model is proposed that incorporates these findings. The application of the model to management, system remediation, target setting, and our understanding of multi-stressor systems is discussed. We also look to the future and the potential for new numerical models to guide management. PMID:29755484
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The components of crop productivity: measuring and modeling plant metabolism
NASA Technical Reports Server (NTRS)
Bugbee, B.
1995-01-01
Several investigators in the CELSS program have demonstrated that crop plants can be remarkably productive in optimal environments where plants are limited only by incident radiation. Radiation use efficiencies of 0.4 to 0.7 g biomass per mol of incident photons have been measured for crops in several laboratories. Some early published values for radiation use efficiency (1 g mol-1) were inflated due to the effect of side lighting. Sealed chambers are the basic research module for crop studies for space. Such chambers allow the measurement of radiation and CO2 fluxes, thus providing values for three determinants of plant growth: radiation absorption, photosynthetic efficiency (quantum yield), and respiration efficiency (carbon use efficiency). Continuous measurement of each of these parameters over the plant life cycle has provided a blueprint for daily growth rates, and is the basis for modeling crop productivity based on component metabolic processes. Much of what has been interpreted as low photosynthetic efficiency is really the result of reduced leaf expansion and poor radiation absorption. Measurements and models of short-term (minutes to hours) and long-term (days to weeks) plant metabolic rates have enormously improved our understanding of plant environment interactions in ground-based growth chambers and are critical to understanding plant responses to the space environment.
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Optimality Based Dynamic Plant Allocation Model: Predicting Acclimation Response to Climate Change
NASA Astrophysics Data System (ADS)
Srinivasan, V.; Drewry, D.; Kumar, P.; Sivapalan, M.
2009-12-01
Allocation of assimilated carbon to different plant parts determines the future plant status and is important to predict long term (months to years) vegetated land surface fluxes. Plants have the ability to modify their allometry and exhibit plasticity by varying the relative proportions of the structural biomass contained in each of its tissue. The ability of plants to be plastic provides them with the potential to acclimate to changing environmental conditions in order to enhance their probability of survival. Allometry based allocation models and other empirical allocation models do not account for plant plasticity cause by acclimation due to environmental changes. In the absence of a detailed understanding of the various biophysical processes involved in plant growth and development an optimality approach is adopted here to predict carbon allocation in plants. Existing optimality based models of plant growth are either static or involve considerable empiricism. In this work, we adopt an optimality based approach (coupled with limitations on plant plasticity) to predict the dynamic allocation of assimilated carbon to different plant parts. We explore the applicability of this approach using several optimization variables such as net primary productivity, net transpiration, realized growth rate, total end of growing season reproductive biomass etc. We use this approach to predict the dynamic nature of plant acclimation in its allocation of carbon to different plant parts under current and future climate scenarios. This approach is designed as a growth sub-model in the multi-layer canopy plant model (MLCPM) and is used to obtain land surface fluxes and plant properties over the growing season. The framework of this model is such that it retains the generality and can be applied to different types of ecosystems. We test this approach using the data from free air carbon dioxide enrichment (FACE) experiments using soybean crop at the Soy-FACE research site. Our results show that there are significant changes in the allocation patterns of vegetation when subjected to elevated CO2 indicating that our model is able to account for plant plasticity arising from acclimation. Soybeans when grown under elevated CO2, increased their allocation to structural components such as leaves and decreased their allocation to reproductive biomass. This demonstrates that plant acclimation causes lower than expected crop yields when grown under elevated CO2. Our findings can have serious implications in estimating future crop yields under climate change scenarios where it is widely expected that rising CO2 will fully offset losses due to climate change.
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NASA Astrophysics Data System (ADS)
Peng, Fei; Xian, Xue; You, Quangang; Huang, Cuihua; Dong, Siyang; Liao, Jie; Duan, Hanchen; Wang, Tao
2017-04-01
Grassland in the Qinghai-Tibet Plateau (QTP) provides tremendous carbon (C) sinks and is the important ground for grazing. Grassland degradation, the loss of plant coverage and the emergence of sand activities, results in substantial reduction in soil organic carbon (SOC). To demonstrate the specific degradation pattern of SOC and elucidate underlying mechanisms, a sequence of five degradation stages over the whole grassland in the QTP were investigated. The survey and laboratory data were analyzed by three structural equation modeling (SEM) analysis. One of the analysis focused on the biological processes while the other two included both the biological and physical processes. Soil temperature had no significant change but soil moisture decreased in all layers. The above and the below-ground plant production decreased and the dominant plant functional group shifted from sedge and grass to forbs. The SOC concentration declined about 40-50% in the very severely degraded comparing with intact alpine grassland.All the three models were successfully fitted with R2 about 0.50. Three biological processes can explain the SOC change. The decrease in soil moisture suppressed C output through soil respiration (Rs) thus lower the SOC loss with land degradation. Decline in the plant production due to a decrease in coverage or to the change in relative abundance of sedge, forbs and grass directly or indirectly reduce the C input and finally lead to the 40-50% loss in SOC. The significant pathways from soil microclimate and soil properties to SOC in the black box model, only one significant pathway from soil properties to SOC indicate that physical processes like the wind and water erosion might control the SOC loss with land degradation in the alpine grassland in the QTP.
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Dynamic Simulation of a Helium Liquefier
NASA Astrophysics Data System (ADS)
Maekawa, R.; Ooba, K.; Nobutoki, M.; Mito, T.
2004-06-01
Dynamic behavior of a helium liquefier has been studied in detail with a Cryogenic Process REal-time SimulaTor (C-PREST) at the National Institute for Fusion Science (NIFS). The C-PREST is being developed to integrate large-scale helium cryogenic plant design, operation and maintenance for optimum process establishment. As a first step of simulations of cooldown to 4.5 K with the helium liquefier model is conducted, which provides a plant-process validation platform. The helium liquefier consists of seven heat exchangers, a liquid-nitrogen (LN2) precooler, two expansion turbines and a liquid-helium (LHe) reservoir. Process simulations are fulfilled with sequence programs, which were implemented with C-PREST based on an existing liquefier operation. The interactions of a JT valve, a JT-bypass valve and a reservoir-return valve have been dynamically simulated. The paper discusses various aspects of refrigeration process simulation, including its difficulties such as a balance between complexity of the adopted models and CPU time.
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Pallas, B; Loi, C; Christophe, A; Cournède, P H; Lecoeur, J
2011-04-01
There is increasing interest in the development of plant growth models representing the complex system of interactions between the different determinants of plant development. These approaches are particularly relevant for grapevine organogenesis, which is a highly plastic process dependent on temperature, solar radiation, soil water deficit and trophic competition. The extent to which three plant growth models were able to deal with the observed plasticity of axis organogenesis was assessed. In the first model, axis organogenesis was dependent solely on temperature, through thermal time. In the second model, axis organogenesis was modelled through functional relationships linking meristem activity and trophic competition. In the last model, the rate of phytomer appearence on each axis was modelled as a function of both the trophic status of the plant and the direct effect of soil water content on potential meristem activity. The model including relationships between trophic competition and meristem behaviour involved a decrease in the root mean squared error (RMSE) for the simulations of organogenesis by a factor nine compared with the thermal time-based model. Compared with the model in which axis organogenesis was driven only by trophic competition, the implementation of relationships between water deficit and meristem behaviour improved organogenesis simulation results, resulting in a three times divided RMSE. The resulting model can be seen as a first attempt to build a comprehensive complete plant growth model simulating the development of the whole plant in fluctuating conditions of temperature, solar radiation and soil water content. We propose a new hypothesis concerning the effects of the different determinants of axis organogenesis. The rate of phytomer appearance according to thermal time was strongly affected by the plant trophic status and soil water deficit. Furthermore, the decrease in meristem activity when soil water is depleted does not result from source/sink imbalances.
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Putting the Spotlight Back on Plant Suspension Cultures
Santos, Rita B.; Abranches, Rita; Fischer, Rainer; Sack, Markus; Holland, Tanja
2016-01-01
Plant cell suspension cultures have several advantages that make them suitable for the production of recombinant proteins. They can be cultivated under aseptic conditions using classical fermentation technology, they are easy to scale-up for manufacturing, and the regulatory requirements are similar to those established for well-characterized production systems based on microbial and mammalian cells. It is therefore no surprise that taliglucerase alfa (Elelyso®)—the first licensed recombinant pharmaceutical protein derived from plants—is produced in plant cell suspension cultures. But despite this breakthrough, plant cells are still largely neglected compared to transgenic plants and the more recent plant-based transient expression systems. Here, we revisit plant cell suspension cultures and highlight recent developments in the field that show how the rise of plant cells parallels that of Chinese hamster ovary cells, currently the most widespread and successful manufacturing platform for biologics. These developments include medium optimization, process engineering, statistical experimental designs, scale-up/scale-down models, and process analytical technologies. Significant yield increases for diverse target proteins will encourage a gold rush to adopt plant cells as a platform technology, and the first indications of this breakthrough are already on the horizon. PMID:27014320
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USDA-ARS?s Scientific Manuscript database
Computer simulation is a useful tool for benchmarking the electrical and fuel energy consumption and water use in a fluid milk plant. In this study, a computer simulation model of the fluid milk process based on high temperature short time (HTST) pasteurization was extended to include models for pr...
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Study of a risk-based piping inspection guideline system.
Tien, Shiaw-Wen; Hwang, Wen-Tsung; Tsai, Chih-Hung
2007-02-01
A risk-based inspection system and a piping inspection guideline model were developed in this study. The research procedure consists of two parts--the building of a risk-based inspection model for piping and the construction of a risk-based piping inspection guideline model. Field visits at the plant were conducted to develop the risk-based inspection and strategic analysis system. A knowledge-based model had been built in accordance with international standards and local government regulations, and the rational unified process was applied for reducing the discrepancy in the development of the models. The models had been designed to analyze damage factors, damage models, and potential damage positions of piping in the petrochemical plants. The purpose of this study was to provide inspection-related personnel with the optimal planning tools for piping inspections, hence, to enable effective predictions of potential piping risks and to enhance the better degree of safety in plant operations that the petrochemical industries can be expected to achieve. A risk analysis was conducted on the piping system of a petrochemical plant. The outcome indicated that most of the risks resulted from a small number of pipelines.
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Nutrient cycle benchmarks for earth system land model
NASA Astrophysics Data System (ADS)
Zhu, Q.; Riley, W. J.; Tang, J.; Zhao, L.
2017-12-01
Projecting future biosphere-climate feedbacks using Earth system models (ESMs) relies heavily on robust modeling of land surface carbon dynamics. More importantly, soil nutrient (particularly, nitrogen (N) and phosphorus (P)) dynamics strongly modulate carbon dynamics, such as plant sequestration of atmospheric CO2. Prevailing ESM land models all consider nitrogen as a potentially limiting nutrient, and several consider phosphorus. However, including nutrient cycle processes in ESM land models potentially introduces large uncertainties that could be identified and addressed by improved observational constraints. We describe the development of two nutrient cycle benchmarks for ESM land models: (1) nutrient partitioning between plants and soil microbes inferred from 15N and 33P tracers studies and (2) nutrient limitation effects on carbon cycle informed by long-term fertilization experiments. We used these benchmarks to evaluate critical hypotheses regarding nutrient cycling and their representation in ESMs. We found that a mechanistic representation of plant-microbe nutrient competition based on relevant functional traits best reproduced observed plant-microbe nutrient partitioning. We also found that for multiple-nutrient models (i.e., N and P), application of Liebig's law of the minimum is often inaccurate. Rather, the Multiple Nutrient Limitation (MNL) concept better reproduces observed carbon-nutrient interactions.
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NASA Astrophysics Data System (ADS)
Koch, Axelle; Schröder, Natalie; Pohlmeier, Andreas; Garré, Sarah; Vanderborght, Jan; Javaux, Mathieu
2017-04-01
Measuring water extraction by plant would allow us to better understand root water uptake processes and how soil and plant properties affect them. Yet, direct measurement of root water uptake is still challenging and determining its distribution requires coupling experimentation and modelling. In this study, we investigated how the 3D monitoring of a tracer movement in a sand container with a lupine plant could inform us about root water uptake process. A sand column (10 cm height, 5 cm inner diameter) planted with an 18-day-old white lupine was subject to a tracer experiment with a chemically inert tracer (1 mmol/L Gd-DTPA2-) applied for 6 days. Then the tracer and water fluxes were stopped. The plume was monitored in 3-D for 7 days by Magnetic Resonance Imaging (Haber-Pohlmeier et al, unp). In addition the breakthrough curve at the outlet was also measured. We used a biophysical 3-D soil-plant model: R-SWMS (Javaux et al, 2008) to extract information from this experiment. First, we ran a virtual experiment to check the assumption that Gd concentration increase around roots is proportional to the extracted soil water during the same period. We also investigated whether this type of experiment helps discriminate different root hydraulic properties with a sensitivity analysis. Then, we compared the experimental and simulated Gd concentration patterns. A preliminary (qualitative) assessment showed that measured Gd distribution patterns were better represented by the model at day 7, where the main driver of the concentration distribution was root and not soil heterogeneity (which is not taken into account in the model). The main spatial and temporal features of the transport where adequately reproduced by the model in particular during the last day. The distribution of the tracer was shown to be sensitive to the root hydraulic properties. To conclude, information about root water uptake distributions and so about root hydraulic properties could be deduced from Gd concentration maps. Keywords: R-SWMS; Modelling; MRI; Root Water Uptake; Gadolinium
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NASA Astrophysics Data System (ADS)
Rodionova, N. S.; Popov, E. S.; Pozhidaeva, E. A.; Pynzar, S. S.; Ryaskina, L. O.
2018-05-01
The aim of this study is to develop a mathematical model of the heat exchange process of LT-processing to estimate the dynamics of temperature field changes and optimize the regime parameters, due to the non-stationarity process, the physicochemical and thermophysical properties of food systems. The application of LT-processing, based on the use of low-temperature modes in thermal culinary processing of raw materials with preliminary vacuum packaging in a polymer heat- resistant film is a promising trend in the development of technics and technology in the catering field. LT-processing application of food raw materials guarantees the preservation of biologically active substances in food environments, which are characterized by a certain thermolability, as well as extend the shelf life and high consumer characteristics of food systems that are capillary-porous bodies. When performing the mathematical modeling of the LT-processing process, the packet of symbolic mathematics “Maple” was used, as well as the mathematical packet flexPDE that uses the finite element method for modeling objects with distributed parameters. The processing of experimental results was evaluated with the help of the developed software in the programming language Python 3.4. To calculate and optimize the parameters of the LT processing process of polycomponent food systems, the differential equation of non-stationary thermal conductivity was used, the solution of which makes it possible to identify the temperature change at any point of the solid at different moments. The present study specifies data on the thermophysical characteristics of the polycomponent food system based on plant raw materials, with the help of which the physico-mathematical model of the LT- processing process has been developed. The obtained mathematical model allows defining of the dynamics of the temperature field in different sections of the LT-processed polycomponent food systems on the basis of calculating the evolution profiles of temperature fields, which enable one to analyze the efficiency of the regime parameters of heat treatment.
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Bedward, Michael; Penman, Trent D.; Doherty, Michael D.; Weber, Rodney O.; Gill, A. Malcolm; Cary, Geoffrey J.
2016-01-01
The influence of plant traits on forest fire behaviour has evolutionary, ecological and management implications, but is poorly understood and frequently discounted. We use a process model to quantify that influence and provide validation in a diverse range of eucalypt forests burnt under varying conditions. Measured height of consumption was compared to heights predicted using a surface fuel fire behaviour model, then key aspects of our model were sequentially added to this with and without species-specific information. Our fully specified model had a mean absolute error 3.8 times smaller than the otherwise identical surface fuel model (p < 0.01), and correctly predicted the height of larger (≥1 m) flames 12 times more often (p < 0.001). We conclude that the primary endogenous drivers of fire severity are the species of plants present rather than the surface fuel load, and demonstrate the accuracy and versatility of the model for quantifying this. PMID:27529789
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Zylstra, Philip; Bradstock, Ross A; Bedward, Michael; Penman, Trent D; Doherty, Michael D; Weber, Rodney O; Gill, A Malcolm; Cary, Geoffrey J
2016-01-01
The influence of plant traits on forest fire behaviour has evolutionary, ecological and management implications, but is poorly understood and frequently discounted. We use a process model to quantify that influence and provide validation in a diverse range of eucalypt forests burnt under varying conditions. Measured height of consumption was compared to heights predicted using a surface fuel fire behaviour model, then key aspects of our model were sequentially added to this with and without species-specific information. Our fully specified model had a mean absolute error 3.8 times smaller than the otherwise identical surface fuel model (p < 0.01), and correctly predicted the height of larger (≥1 m) flames 12 times more often (p < 0.001). We conclude that the primary endogenous drivers of fire severity are the species of plants present rather than the surface fuel load, and demonstrate the accuracy and versatility of the model for quantifying this.
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Economic evaluation of United States ethanol production from ligno-cellulosic feedstocks
NASA Astrophysics Data System (ADS)
Choi, Youn-Sang
This paper evaluates the economic feasibility and economy-wide impacts of the U. S. ethanol production from lignocellulosic feedstocks (LCF) using Tennessee Valley Authority's (TVA's) dilute acid hydrolysis process. A nonlinear mathematical programming model of a single ethanol producer, whose objective is profit maximization, is developed. Because of differences in their chemical composition and production process, lignocellulosic feedstocks are divided into two groups: Biomass feedstocks, which refer to crop residues, energy crops and woody biomass, and municipal solid waste (MSW). Biomass feedstocks are more productive and less costly in producing ethanol and co-products, while MSW generates an additional income to the producer from a tipping fee and recycling. The analysis suggests that, regardless of types of feedstocks used, TVA's conversion process can enhance the economic viability of ethanol production as long as furfural is produced from the hemicellulose fraction of feedstocks as a co-product. The high price of furfural makes it a major factor in determining the economic feasibility of ethanol production. Along with evaluating economic feasibility of LCF-to-ethanol production, the optimal size of a plant producing ethanol using TVA's conversion process is estimated. The larger plant would have the advantage of economies of scale, but also have a disadvantage of increased collection and transportation costs for bulky biomass from more distant locations. We assume that the plant is located in the state of Missouri and utilizes only feedstocks produced in the state. The results indicate that the size of a plant using Biomass feedstocks is much bigger than one using MSW. The difference of plant sizes results from plant location and feedstock availability. One interesting finding is that energy crops are not feasible feedstocks for LCF-to-ethanol production due to their high price. Next, a static CGE model is developed to estimate the U.S. economy-wide impacts of the current ethanol production with a government subsidy and the LCF-to-ethanol production using TVA's dilute acid hydrolysis process. The model is innovative in three ways. First, a production subsidy is explicitly included in the model. Second, co-products are explicitly accounted for in ethanol production. Third, ethanol and gasoline are treated as perfect demand substitutes, as are the co-products and the manufacturing sector's output. The CGE model shows that current ethanol production expands grain crop production by creating an additional demand. In contrast, LCF-to-ethanol production has adverse impacts on grain crop production because Biomass feedstocks substitute for grain in the production of ethanol. The LCF-to-ethanol production also discourages the manufacturing industry because co-products displace a part of intermediate input demand for manufacturing outputs. It is also found that, even though ethanol production using TVA's conversion technology with MSW is economically viable, it is not favorable to the economy. Finally, the results suggest that ethanol production from Biomass feedstocks using TVA's dilute acid hydrolysis process is beneficial to the U.S. economy.
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Forest biomass supply logistics for a power plant using the discrete-event simulation approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mobini, Mahdi; Sowlati, T.; Sokhansanj, Shahabaddine
This study investigates the logistics of supplying forest biomass to a potential power plant. Due to the complexities in such a supply logistics system, a simulation model based on the framework of Integrated Biomass Supply Analysis and Logistics (IBSAL) is developed in this study to evaluate the cost of delivered forest biomass, the equilibrium moisture content, and carbon emissions from the logistics operations. The model is applied to a proposed case of 300 MW power plant in Quesnel, BC, Canada. The results show that the biomass demand of the power plant would not be met every year. The weighted averagemore » cost of delivered biomass to the gate of the power plant is about C$ 90 per dry tonne. Estimates of equilibrium moisture content of delivered biomass and CO2 emissions resulted from the processes are also provided.« less
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Facing technological challenges of Solar Updraft Power Plants
NASA Astrophysics Data System (ADS)
Lupi, F.; Borri, C.; Harte, R.; Krätzig, W. B.; Niemann, H.-J.
2015-01-01
The Solar Updraft Power Plant technology addresses a very challenging idea of combining two kinds of renewable energy: wind and solar. The working principle is simple: a Solar Updraft Power Plant (SUPP) consists of a collector area to heat the air due to the wide-banded ultra-violet solar radiation, the high-rise solar tower to updraft the heated air to the atmosphere, and in between the power conversion unit, where a system of coupled turbines and generators transforms the stream of heated air into electric power. A good efficiency of the power plant can only be reached with extra-large dimensions of the tower and/or the collector area. The paper presents an up-to-date review of the SUPP technology, focusing on the multi-physics modeling of the power plant, on the structural behavior of the tower and, last but not least, on the modeling of the stochastic wind loading process.
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Heavy metal tolerance in plants: A model evolutionary system.
Macnair, M R
1987-12-01
Evolved tolerance to toxic concentrations of heavy metals in plants inhabiting spoil heaps of mines is a well known phenomenon that has been the subject of much research in the last two decades. These plants are useful models for studying processes involved in the early stages of the speciation of edaphic endemics. Recent work has revealed the importance of several phenomena in the differentiation of tolerant populations, including natural selection, founder effects and 'hitch-hiking', and has demonstrated the early evolution of morphological differentiation and reproductive isolating mechanisms. Further studies of the biochemistry and molecular biology of heavy metal tolerance will help to show why some plant groups, such as Agrostis, are far more prone to evolve tolerance than others. Copyright © 1987. Published by Elsevier Ltd.
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Selected bibliography on the modeling and control of plant processes
NASA Technical Reports Server (NTRS)
Viswanathan, M. M.; Julich, P. M.
1972-01-01
A bibliography of information pertinent to the problem of simulating plants is presented. Detailed simulations of constituent pieces are necessary to justify simple models which may be used for analysis. Thus, this area of study is necessary to support the Earth Resources Program. The report sums up the present state of the problem of simulating vegetation. This area holds the hope of major benefits to mankind through understanding the ecology of a region and in improving agricultural yield.
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Pagliari, Laura; Martini, Marta; Loschi, Alberto; Musetti, Rita
2016-10-01
Phytoplasmas are phloem-inhabiting plant pathogens that affect over one thousand plant species, representing a severe threat to agriculture. The absence of an effective curative strategy and the economic importance of many affected crops make a priority of studying how plants respond to phytoplasma infection. Nevertheless, the study of phytoplasmas has been hindered by the extreme difficulty of culturing them in vitro and by impediments to natural host plant surveys such as low phytoplasma titre, long plant life cycle and poor knowledge of natural host-plant biology. Stating correspondence between macroscopic symptoms of phytoplasma infected Arabidopsis thaliana and those observed in natural host plants, over the last decade some authors have started to use this plant as a model for studying phytoplasma-plant interactions. Nevertheless, the morphological and ultrastructural modifications occurring in A. thaliana tissues following phytoplasma infection have never been described in detail. In this work, we adopted a combined-microscopy approach to verify if A. thaliana can be considered a reliable model for the study of phytoplasma-plant interactions at the microscopical level. The consistent presence of phytoplasma in infected phloem allowed detailed study of the infection process and the relationship established by phytoplasmas with different components of the sieve elements. In infected A. thaliana, phytoplasmas induced strong disturbances of host plant development that were mainly due to phloem disorganization and impairment. Light microscopy showed collapse, necrosis and hyperplasia of phloem cells. TEM observations of sieve elements identified two common plant-responses to phytoplasma infection: phloem protein agglutination and callose deposition. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Fernández-Arévalo, T; Lizarralde, I; Fdz-Polanco, F; Pérez-Elvira, S I; Garrido, J M; Puig, S; Poch, M; Grau, P; Ayesa, E
2017-07-01
The growing development of technologies and processes for resource treatment and recovery is offering endless possibilities for creating new plant-wide configurations or modifying existing ones. However, the configurations' complexity, the interrelation between technologies and the influent characteristics turn decision-making into a complex or unobvious process. In this frame, the Plant-Wide Modelling (PWM) library presented in this paper allows a thorough, comprehensive and refined analysis of different plant configurations that are basic aspects in decision-making from an energy and resource recovery perspective. In order to demonstrate the potential of the library and the need to run simulation analyses, this paper carries out a comparative analysis of WWTPs, from a techno-economic point of view. The selected layouts were (1) a conventional WWTP based on a modified version of the Benchmark Simulation Model No. 2, (2) an upgraded or retrofitted WWTP, and (3) a new Wastewater Resource Recovery Facilities (WRRF) concept denominated as C/N/P decoupling WWTP. The study was based on a preliminary analysis of the organic matter and nutrient energy use and recovery options, a comprehensive mass and energy flux distribution analysis in each configuration in order to compare and identify areas for improvement, and a cost analysis of each plant for different influent COD/TN/TP ratios. Analysing the plants from a standpoint of resources and energy utilization, a low utilization of the energy content of the components could be observed in all configurations. In the conventional plant, the COD used to produce biogas was around 29%, the upgraded plant was around 36%, and 34% in the C/N/P decoupling WWTP. With regard to the self-sufficiency of plants, achieving self-sufficiency was not possible in the conventional plant, in the upgraded plant it depended on the influent C/N ratio, and in the C/N/P decoupling WWTP layout self-sufficiency was feasible for almost all influents, especially at high COD concentrations. The plant layouts proposed in this paper are just a sample of the possibilities offered by current technologies. Even so, the library presented here is generic and can be used to construct any other plant layout, provided that a model is available. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Rawal, Shilpa; Singh, Pavneet; Gupta, Ayush; Mohanty, Sujata
2014-01-01
Intake of food and nutrition plays a major role in affecting aging process and longevity. However, the precise mechanisms underlying the ageing process are still unclear. To this respect, diet has been considered to be a determinant of ageing process. In order to better illustrate this, we used Drosophila melanogaster as a model and fed them orally with different concentrations of two commonly used Indian medicinal plant products, Curcuma longa (rhizome) and Emblica officinalis (fruit). The results revealed significant increase in life span of Drosophila flies on exposure to both the plant products, more efficiently by C. Longa than by E. officinalis. In order to understand whether the increase in lifespan was due to high-antioxidant properties of these medicinal plants, we performed enzymatic assays to assess the SOD and catalase activities in case of both treated and control Drosophila flies. Interestingly, the results support the free radical theory of aging as both these plant derivatives show high reactive oxygen species (ROS) scavenging activities.
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Rawal, Shilpa; Singh, Pavneet; Gupta, Ayush; Mohanty, Sujata
2014-01-01
Intake of food and nutrition plays a major role in affecting aging process and longevity. However, the precise mechanisms underlying the ageing process are still unclear. To this respect, diet has been considered to be a determinant of ageing process. In order to better illustrate this, we used Drosophila melanogaster as a model and fed them orally with different concentrations of two commonly used Indian medicinal plant products, Curcuma longa (rhizome) and Emblica officinalis (fruit). The results revealed significant increase in life span of Drosophila flies on exposure to both the plant products, more efficiently by C. Longa than by E. officinalis. In order to understand whether the increase in lifespan was due to high-antioxidant properties of these medicinal plants, we performed enzymatic assays to assess the SOD and catalase activities in case of both treated and control Drosophila flies. Interestingly, the results support the free radical theory of aging as both these plant derivatives show high reactive oxygen species (ROS) scavenging activities. PMID:24967413
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Suk Kim, Jong; McKellar, Michael; Bragg-Sitton, Shannon M.
This report has been prepared as part of an effort to design and build a modeling and simulation (M&S) framework to assess the economic viability of a nuclear-renewable hybrid energy system (N-R HES). In order to facilitate dynamic M&S of such an integrated system, research groups in multiple national laboratories have been developing various subsystems as dynamic physics-based components using the Modelica programming language. In fiscal year (FY) 2015, Idaho National Laboratory (INL) performed a dynamic analysis of two region-specific N-R HES configurations, including the gas-to-liquid (natural gas to Fischer-Tropsch synthetic fuel) and brackish water reverse osmosis desalination plants asmore » industrial processes. In FY 2016, INL has developed two additional subsystems in the Modelica framework: a high-temperature steam electrolysis (HTSE) plant and a gas turbine power plant (GTPP). HTSE has been proposed as a high priority industrial process to be integrated with a light water reactor (LWR) in an N-R HES. This integrated energy system would be capable of dynamically apportioning thermal and electrical energy (1) to provide responsive generation to the power grid and (2) to produce alternative industrial products (i.e., hydrogen and oxygen) without generating any greenhouse gases. A dynamic performance analysis of the LWR/HTSE integration case was carried out to evaluate the technical feasibility (load-following capability) and safety of such a system operating under highly variable conditions requiring flexible output. To support the dynamic analysis, the detailed dynamic model and control design of the HTSE process, which employs solid oxide electrolysis cells, have been developed to predict the process behavior over a large range of operating conditions. As first-generation N-R HES technology will be based on LWRs, which provide thermal energy at a relatively low temperature, complementary temperature-boosting technology was suggested for integration with the HTSE process that requires higher temperature input. Simulation results involving several case studies show that the suggested control scheme could maintain the controlled variables (including the steam utilization factor, cathode stream inlet composition, and temperatures of the process streams at various locations) within desired limits under various plant operating conditions. The results also indicate that the proposed HTSE plant could provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess plant capacity within an N-R HES. A natural-gas fired GTPP has been proposed as a secondary energy supply to be included in an N-R HES. This auxiliary generator could be used to cover rapid dynamics in grid demand that cannot be met by the remainder of the N-R HES. To evaluate the operability and controllability of the proposed process during transients between load (demand) levels, the dynamic model and control design were developed. Special attention was given to the design of feedback controllers to regulate the power frequency, and exhaust gas and turbine firing temperatures. Several case studies were performed to investigate the system responses to the major disturbance (power load demand) in such a control system. The simulation results show that the performance of the proposed control strategies was satisfactory under each test when the GTPP experienced high rapid variations in the load.« less
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An overview of challenges in modeling heat and mass transfer for living on Mars.
Yamashita, Masamichi; Ishikawa, Yoji; Kitaya, Yoshiaki; Goto, Eiji; Arai, Mayumi; Hashimoto, Hirofumi; Tomita-Yokotani, Kaori; Hirafuji, Masayuki; Omori, Katsunori; Shiraishi, Atsushi; Tani, Akira; Toki, Kyoichiro; Yokota, Hiroki; Fujita, Osamu
2006-09-01
Engineering a life-support system for living on Mars requires the modeling of heat and mass transfer. This report describes the analysis of heat and mass transfer phenomena in a greenhouse dome, which is being designed as a pressurized life-support system for agricultural production on Mars. In this Martian greenhouse, solar energy will be converted into chemical energy in plant biomass. Agricultural products will be harvested for food and plant cultivation, and waste materials will be processed in a composting microbial ecosystem. Transpired water from plants will be condensed and recycled. In our thermal design and analysis for the Martian greenhouse, we addressed the question of whether temperature and pressure would be maintained in the appropriate range for humans as well as plants. Energy flow and material circulation should be controlled to provide an artificial ecological system on Mars. In our analysis, we assumed that the greenhouse would be maintained at a subatmospheric pressure under 1/3-G gravitational force with 1/2 solar light intensity on Earth. Convection of atmospheric gases will be induced inside the greenhouse, primarily by heating from sunlight. Microclimate (thermal and gas species structure) could be generated locally around plant bodies, which would affect gas transport. Potential effects of those environmental factors are discussed on the phenomena including plant growth and plant physiology and focusing on transport processes. Fire safety is a crucial issue and we evaluate its impact on the total gas pressure in the greenhouse dome.
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Plant uptake of elements in soil and pore water: field observations versus model assumptions.
Raguž, Veronika; Jarsjö, Jerker; Grolander, Sara; Lindborg, Regina; Avila, Rodolfo
2013-09-15
Contaminant concentrations in various edible plant parts transfer hazardous substances from polluted areas to animals and humans. Thus, the accurate prediction of plant uptake of elements is of significant importance. The processes involved contain many interacting factors and are, as such, complex. In contrast, the most common way to currently quantify element transfer from soils into plants is relatively simple, using an empirical soil-to-plant transfer factor (TF). This practice is based on theoretical assumptions that have been previously shown to not generally be valid. Using field data on concentrations of 61 basic elements in spring barley, soil and pore water at four agricultural sites in mid-eastern Sweden, we quantify element-specific TFs. Our aim is to investigate to which extent observed element-specific uptake is consistent with TF model assumptions and to which extent TF's can be used to predict observed differences in concentrations between different plant parts (root, stem and ear). Results show that for most elements, plant-ear concentrations are not linearly related to bulk soil concentrations, which is congruent with previous studies. This behaviour violates a basic TF model assumption of linearity. However, substantially better linear correlations are found when weighted average element concentrations in whole plants are used for TF estimation. The highest number of linearly-behaving elements was found when relating average plant concentrations to soil pore-water concentrations. In contrast to other elements, essential elements (micronutrients and macronutrients) exhibited relatively small differences in concentration between different plant parts. Generally, the TF model was shown to work reasonably well for micronutrients, whereas it did not for macronutrients. The results also suggest that plant uptake of elements from sources other than the soil compartment (e.g. from air) may be non-negligible. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Plant leaf traits, canopy processes, and global atmospheric chemistry interactions.
NASA Astrophysics Data System (ADS)
Guenther, A. B.
2017-12-01
Plants produce and emit a diverse array of volatile metabolites into the atmosphere that participate in chemical reactions that influence distributions of air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. It is now widely accepted that accurate estimates of these emissions are required as inputs for regional air quality and global climate models. Predicting these emissions is complicated by the large number of volatile organic compounds, driving variables (e.g., temperature, solar radiation, abiotic and biotic stresses) and processes operating across a range of scales. Modeling efforts to characterize emission magnitude and variations will be described along with an assessment of the observations available for parameterizing and evaluating these models including discussion of the limitations and challenges associated with existing model approaches. A new approach for simulating canopy scale organic emissions on regional to global scales will be described and compared with leaf, canopy and regional scale flux measurements. The importance of including additional compounds and processes as well as improving estimates of existing ones will also be discussed.
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EIA model documentation: Petroleum market model of the national energy modeling system
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
1995-12-28
The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. Documentation of the model is in accordance with EIA`s legal obligation to provide adequate documentation in support of its models. The PMM models petroleum refining activities, the marketing of petroleum products to consumption regions, the production of natural gas liquids in gas processing plants, and domestic methanol production. The PMM projects petroleum product prices and sources of supplymore » for meeting petroleum product demand. The sources of supply include crude oil, both domestic and imported; other inputs including alcohols and ethers; natural gas plant liquids production; petroleum product imports; and refinery processing gain. In addition, the PMM estimates domestic refinery capacity expansion and fuel consumption. Product prices are estimated at the Census division level and much of the refining activity information is at the Petroleum Administration for Defense (PAD) District level.« less
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Yocgo, Rosita E; Geza, Ephifania; Chimusa, Emile R; Mazandu, Gaston K
2017-11-23
Advances in forward and reverse genetic techniques have enabled the discovery and identification of several plant defence genes based on quantifiable disease phenotypes in mutant populations. Existing models for testing the effect of gene inactivation or genes causing these phenotypes do not take into account eventual uncertainty of these datasets and potential noise inherent in the biological experiment used, which may mask downstream analysis and limit the use of these datasets. Moreover, elucidating biological mechanisms driving the induced disease resistance and influencing these observable disease phenotypes has never been systematically tackled, eliciting the need for an efficient model to characterize completely the gene target under consideration. We developed a post-gene silencing bioinformatics (post-GSB) protocol which accounts for potential biases related to the disease phenotype datasets in assessing the contribution of the gene target to the plant defence response. The post-GSB protocol uses Gene Ontology semantic similarity and pathway dataset to generate enriched process regulatory network based on the functional degeneracy of the plant proteome to help understand the induced plant defence response. We applied this protocol to investigate the effect of the NPR1 gene silencing to changes in Arabidopsis thaliana plants following Pseudomonas syringae pathovar tomato strain DC3000 infection. Results indicated that the presence of a functionally active NPR1 reduced the plant's susceptibility to the infection, with about 99% of variability in Pseudomonas spore growth between npr1 mutant and wild-type samples. Moreover, the post-GSB protocol has revealed the coordinate action of target-associated genes and pathways through an enriched process regulatory network, summarizing the potential target-based induced disease resistance mechanism. This protocol can improve the characterization of the gene target and, potentially, elucidate induced defence response by more effectively utilizing available phenotype information and plant proteome functional knowledge.
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The GP problem: quantifying gene-to-phenotype relationships.
Cooper, Mark; Chapman, Scott C; Podlich, Dean W; Hammer, Graeme L
2002-01-01
In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.
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Modeling the plant uptake of organic chemicals, including the soil-air-plant pathway.
Collins, Chris D; Finnegan, Eilis
2010-02-01
The soil-air-plant pathway is potentially important in the vegetative accumulation of organic pollutants from contaminated soils. While a number of qualitative frameworks exist for the prediction of plant accumulation of organic chemicals by this pathway, there are few quantitative models that incorporate this pathway. The aim of the present study was to produce a model that included this pathway and could quantify its contribution to the total plant contamination for a range of organic pollutants. A new model was developed from three submodels for the processes controlling plant contamination via this pathway: aerial deposition, soil volatilization, and systemic translocation. Using the combined model, the soil-air-plant pathway was predicted to account for a significant proportion of the total shoot contamination for those compounds with log K(OA) > 9 and log K(AW) < -3. For those pollutants with log K(OA) < 9 and log K(AW) > -3 there was a higher deposition of pollutant via the soil-air-plant pathway than for those chemicals with log K(OA) > 9 and log K(AW) < -3, but this was an insignificant proportion of the total shoot contamination because of the higher mobility of these compounds via the soil-root-shoot pathway. The incorporation of the soil-air-plant pathway into the plant uptake model did not significantly improve the prediction of the contamination of vegetation from polluted soils when compared across a range of studies. This was a result of the high variability between the experimental studies where the bioconcentration factors varied by 2 orders of magnitude at an equivalent log K(OA). One potential reason for this is the background air concentration of the pollutants under study. It was found background air concentrations would dominate those from soil volatilization in many situations unless there was a soil hot spot of contamination, i.e., >100 mg kg(-1).
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Development of a Robust Identifier for NPPs Transients Combining ARIMA Model and EBP Algorithm
NASA Astrophysics Data System (ADS)
Moshkbar-Bakhshayesh, Khalil; Ghofrani, Mohammad B.
2014-08-01
This study introduces a novel identification method for recognition of nuclear power plants (NPPs) transients by combining the autoregressive integrated moving-average (ARIMA) model and the neural network with error backpropagation (EBP) learning algorithm. The proposed method consists of three steps. First, an EBP based identifier is adopted to distinguish the plant normal states from the faulty ones. In the second step, ARIMA models use integrated (I) process to convert non-stationary data of the selected variables into stationary ones. Subsequently, ARIMA processes, including autoregressive (AR), moving-average (MA), or autoregressive moving-average (ARMA) are used to forecast time series of the selected plant variables. In the third step, for identification the type of transients, the forecasted time series are fed to the modular identifier which has been developed using the latest advances of EBP learning algorithm. Bushehr nuclear power plant (BNPP) transients are probed to analyze the ability of the proposed identifier. Recognition of transient is based on similarity of its statistical properties to the reference one, rather than the values of input patterns. More robustness against noisy data and improvement balance between memorization and generalization are salient advantages of the proposed identifier. Reduction of false identification, sole dependency of identification on the sign of each output signal, selection of the plant variables for transients training independent of each other, and extendibility for identification of more transients without unfavorable effects are other merits of the proposed identifier.
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NASA Technical Reports Server (NTRS)
Miller, Adam M.; Edeen, Marybeth; Sirko, Robert J.
1992-01-01
This paper describes the approach and results of an effort to characterize plant growth under various environmental conditions at the Johnson Space Center variable pressure growth chamber. Using a field of applied mathematics and statistics known as design of experiments (DOE), we developed a test plan for varying environmental parameters during a lettuce growth experiment. The test plan was developed using a Box-Behnken approach to DOE. As a result of the experimental runs, we have developed empirical models of both the transpiration process and carbon dioxide assimilation for Waldman's Green lettuce over specified ranges of environmental parameters including carbon dioxide concentration, light intensity, dew-point temperature, and air velocity. This model also predicts transpiration and carbon dioxide assimilation for different ages of the plant canopy.
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AVESTAR Center for Operational Excellence of Electricity Generation Plants
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zitney, Stephen
2012-08-29
To address industry challenges in attaining operational excellence for electricity generation plants, the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) has launched a world-class facility for Advanced Virtual Energy Simulation Training and Research (AVESTARTM). This presentation will highlight the AVESTARTM Center simulators, facilities, and comprehensive training, education, and research programs focused on the operation and control of high-efficiency, near-zero-emission electricity generation plants. The AVESTAR Center brings together state-of-the-art, real-time, high-fidelity dynamic simulators with full-scope operator training systems (OTSs) and 3D virtual immersive training systems (ITSs) into an integrated energy plant and control room environment. AVESTAR’s initial offeringmore » combines--for the first time--a “gasification with CO2 capture” process simulator with a “combined-cycle” power simulator together in a single OTS/ITS solution for an integrated gasification combined cycle (IGCC) power plant with carbon dioxide (CO2) capture. IGCC systems are an attractive technology option for power generation, especially when capturing and storing CO2 is necessary to satisfy emission targets. The AVESTAR training program offers a variety of courses that merge classroom learning, simulator-based OTS learning in a control-room operations environment, and immersive learning in the interactive 3D virtual plant environment or ITS. All of the courses introduce trainees to base-load plant operation, control, startups, and shutdowns. Advanced courses require participants to become familiar with coordinated control, fuel switching, power-demand load shedding, and load following, as well as to problem solve equipment and process malfunctions. Designed to ensure work force development, training is offered for control room and plant field operators, as well as engineers and managers. Such comprehensive simulator-based instruction allows for realistic training without compromising worker, equipment, and environmental safety. It also better prepares operators and engineers to manage the plant closer to economic constraints while minimizing or avoiding the impact of any potentially harmful, wasteful, or inefficient events. The AVESTAR Center is also used to augment graduate and undergraduate engineering education in the areas of process simulation, dynamics, control, and safety. Students and researchers gain hands-on simulator-based training experience and learn how the commercial-scale power plants respond dynamically to changes in manipulated inputs, such as coal feed flow rate and power demand. Students also analyze how the regulatory control system impacts power plant performance and stability. In addition, students practice start-up, shutdown, and malfunction scenarios. The 3D virtual ITSs are used for plant familiarization, walk-through, equipment animations, and safety scenarios. To further leverage the AVESTAR facilities and simulators, NETL and its university partners are pursuing an innovative and collaborative R&D program. In the area of process control, AVESTAR researchers are developing enhanced strategies for regulatory control and coordinated plant-wide control, including gasifier and gas turbine lead, as well as advanced process control using model predictive control (MPC) techniques. Other AVESTAR R&D focus areas include high-fidelity equipment modeling using partial differential equations, dynamic reduced order modeling, optimal sensor placement, 3D virtual plant simulation, and modern grid. NETL and its partners plan to continue building the AVESTAR portfolio of dynamic simulators, immersive training systems, and advanced research capabilities to satisfy industry’s growing need for training and experience with the operation and control of clean energy plants. Future dynamic simulators under development include natural gas combined cycle (NGCC) and supercritical pulverized coal (SCPC) plants with post-combustion CO2 capture. These dynamic simulators are targeted for use in establishing a Virtual Carbon Capture Center (VCCC), similar in concept to the DOE’s National Carbon Capture Center for slipstream testing. The VCCC will enable developers of CO2 capture technologies to integrate, test, and optimize the operation of their dynamic capture models within the context of baseline power plant dynamic models. The objective is to provide hands-on, simulator-based “learn-by-operating” test platforms to accelerate the scale-up and deployment of CO2 capture technologies. Future AVESTAR plans also include pursuing R&D on the dynamics, operation, and control of integrated electricity generation and storage systems for the modern grid era. Special emphasis will be given to combining load-following energy plants with renewable and distributed generating supplies and fast-ramping energy storage systems to provide near constant baseload power.« less
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NASA Astrophysics Data System (ADS)
Leitner, Daniel; Bodner, Gernot; Raoof, Amir
2013-04-01
Understanding root-soil interactions is of high importance for environmental and agricultural management. Root uptake is an essential component in water and solute transport modeling. The amount of groundwater recharge and solute leaching significantly depends on the demand based plant extraction via its root system. Plant uptake however not only responds to the potential demand, but in most situations is limited by supply form the soil. The ability of the plant to access water and solutes in the soil is governed mainly by root distribution. Particularly under conditions of heterogeneous distribution of water and solutes in the soil, it is essential to capture the interaction between soil and roots. Root architecture models allow studying plant uptake from soil by describing growth and branching of root axes in the soil. Currently root architecture models are able to respond dynamically to water and nutrient distribution in the soil by directed growth (tropism), modified branching and enhanced exudation. The porous soil medium as rooting environment in these models is generally described by classical macroscopic water retention and sorption models, average over the pore scale. In our opinion this simplified description of the root growth medium implies several shortcomings for better understanding root-soil interactions: (i) It is well known that roots grow preferentially in preexisting pores, particularly in more rigid/dry soil. Thus the pore network contributes to the architectural form of the root system; (ii) roots themselves can influence the pore network by creating preferential flow paths (biopores) which are an essential element of structural porosity with strong impact on transport processes; (iii) plant uptake depend on both the spatial location of water/solutes in the pore network as well as the spatial distribution of roots. We therefore consider that for advancing our understanding in root-soil interactions, we need not only to extend our root models, but also improve the description of the rooting environment. Until now there have been no attempts to couple root architecture and pore network models. In our work we present a first attempt to join both types of models using the root architecture model of Leitner et al., (2010) and a pore network model presented by Raoof et al. (2010). The two main objectives of coupling both models are: (i) Representing the effect of root induced biopores on flow and transport processes: For this purpose a fixed root architecture created by the root model is superimposed as a secondary root induced pore network to the primary soil network, thus influencing the final pore topology in the network generation. (ii) Representing the influence of pre-existing pores on root branching: Using a given network of (rigid) pores, the root architecture model allocates its root axes into these preexisting pores as preferential growth paths with thereby shape the final root architecture. The main objective of our study is to reveal the potential of using a pore scale description of the plant growth medium for an improved representation of interaction processes at the interface of root and soil. References Raoof, A., Hassanizadeh, S.M. 2010. A New Method for Generating Pore-Network Models. Transp. Porous Med. 81, 391-407. Leitner, D, Klepsch, S., Bodner, G., Schnepf, S. 2010. A dynamic root system growth model based on L-Systems. Tropisms and coupling to nutrient uptake from soil. Plant Soil 332, 177-192.
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USDA-ARS?s Scientific Manuscript database
Listeria monocytogenes enters a poultry further processing plant with raw product and colonizes the plant as a resident in floor drains. We have shown that L. monocytogenes can escape floor drains, becoming airborne during wash down, creating potential for contamination of fully cooked product. Li...
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Petroleum Market Model of the National Energy Modeling System
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
1997-01-01
The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. The PMM models petroleum refining activities, the marketing of petroleum products to consumption regions. The production of natural gas liquids in gas processing plants, and domestic methanol production. The PMM projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil, both domestic and imported; other inputs including alcoholsmore » and ethers; natural gas plant liquids production; petroleum product imports; and refinery processing gain. In addition, the PMM estimates domestic refinery capacity expansion and fuel consumption. Product prices are estimated at the Census division level and much of the refining activity information is at the Petroleum Administration for Defense (PAD) District level. This report is organized as follows: Chapter 2, Model Purpose; Chapter 3, Model Overview and Rationale; Chapter 4, Model Structure; Appendix A, Inventory of Input Data, Parameter Estimates, and Model Outputs; Appendix B, Detailed Mathematical Description of the Model; Appendix C, Bibliography; Appendix D, Model Abstract; Appendix E, Data Quality; Appendix F, Estimation methodologies; Appendix G, Matrix Generator documentation; Appendix H, Historical Data Processing; and Appendix I, Biofuels Supply Submodule.« less
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NASA Astrophysics Data System (ADS)
Bouda, M.
2017-12-01
Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, RSA has not been included because of its three-dimensional complexity, which makes RSA modelling generally too computationally costly. This work builds upon the recently introduced "RSA stencil," a process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA in response to heterogeneous soil moisture profiles. In validations using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, the RSA stencil predicts plant water potentials within 2% of the outputs of full 3D models, despite its trivial computational cost. In transient simulations, the RSA stencil yields improved predictions of water uptake and soil moisture profiles compared to a 1D model based on root fraction alone. Here I show how the RSA stencil can be calibrated to time-series observations of soil moisture and transpiration to yield a water uptake PFT definition for use in terrestrial models. This model-data integration exercise aims to improve LSM predictions of soil moisture dynamics and, under water-limiting conditions, surface fluxes. These improvements can be expected to significantly impact predictions of downstream variables, including surface fluxes, climate-vegetation feedbacks and soil nutrient cycling.
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Winter wheat: A model for the simulation of growth and yield in winter wheat
NASA Technical Reports Server (NTRS)
Baker, D. N.; Smika, D. E.; Black, A. L.; Willis, W. O.; Bauer, A. (Principal Investigator)
1981-01-01
The basic ideas and constructs for a general physical/physiological process level winter wheat simulation model are documented. It is a materials balance model which calculates daily increments of photosynthate production and respiratory losses in the crop canopy. The partitioning of the resulting dry matter to the active growing tissues in the plant each day, transpiration and the uptake of nitrogen from the soil profile are simulated. It incorporates the RHIZOS model which simulates, in two dimensions, the movement of water, roots, and soluble nutrients through the soil profile. It records the time of initiation of each of the plant organs. These phenological events are calculated from temperature functions with delays resulting from physiological stress. Stress is defined mathematically as an imbalance in the metabolite supply; demand ratio. Physiological stress is also the basis for the calculation of rates of tiller and floret abortion. Thus, tillering and head differentiation are modeled as the resulants of the two processes, morphogenesis and abortion, which may be occurring simulaneously.
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Improving Energy Efficiency for the Vehicle Assembly Industry: A Discrete Event Simulation Approach
NASA Astrophysics Data System (ADS)
Oumer, Abduaziz; Mekbib Atnaw, Samson; Kie Cheng, Jack; Singh, Lakveer
2016-11-01
This paper presented a Discrete Event Simulation (DES) model for investigating and improving energy efficiency in vehicle assembly line. The car manufacturing industry is one of the highest energy consuming industries. Using Rockwell Arena DES package; a detailed model was constructed for an actual vehicle assembly plant. The sources of energy considered in this research are electricity and fuel; which are the two main types of energy sources used in a typical vehicle assembly plant. The model depicts the performance measurement for process- specific energy measures of painting, welding, and assembling processes. Sound energy efficiency model within this industry has two-fold advantage: reducing CO2 emission and cost reduction associated with fuel and electricity consumption. The paper starts with an overview of challenges in energy consumption within the facilities of automotive assembly line and highlights the parameters for energy efficiency. The results of the simulation model indicated improvements for energy saving objectives and reduced costs.
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Petroleum Market Model of the National Energy Modeling System. Part 1
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. The PMM models petroleum refining activities, the marketing of petroleum products to consumption regions, the production of natural gas liquids in gas processing plants, and domestic methanol production. The PMM projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil, both domestic and imported; other inputs including alcoholsmore » and ethers; natural gas plant liquids production; petroleum product imports; and refinery processing gain. In addition, the PMM estimates domestic refinery capacity expansion and fuel consumption. Product prices are estimated at the Census division level and much of the refining activity information is at the Petroleum Administration for Defense (PAD) District level.« less
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Implications of plant acclimation for future climate-carbon cycle feedbacks
NASA Astrophysics Data System (ADS)
Mercado, Lina; Kattge, Jens; Cox, Peter; Sitch, Stephen; Knorr, Wolfgang; Lloyd, Jon; Huntingford, Chris
2010-05-01
The response of land ecosystems to climate change and associated feedbacks are a key uncertainty in future climate prediction (Friedlingstein et al. 2006). However global models generally do not account for the acclimation of plant physiological processes to increased temperatures. Here we conduct a first global sensitivity study whereby we modify the Joint UK land Environment Simulator (JULES) to account for temperature acclimation of two main photosynthetic parameters, Vcmax and Jmax (Kattge and Knorr 2007) and plant respiration (Atkin and Tjoelker 2003). The model is then applied over the 21st Century within the IMOGEN framework (Huntingford et al. 2004). Model simulations will provide new and improved projections of biogeochemical cycling, forest resilience, and thus more accurate projections of climate-carbon cycle feedbacks and the future evolution of the Earth System. Friedlingstein P, Cox PM, Betts R et al. (2006) Climate-carbon cycle feedback analysis, results from the C4MIP model intercomparison. Journal of Climate, 19, 3337-3353. Kattge J and Knorr W (2007): Temperature acclimation in a biochemical model of photosynthesis: a reanalysis of data from 36 species. Plant, Cell and Environment 30, 1176-1190 Atkin O.K and Tjoelker, M. G. (2003): Thermal acclimation and the dynamic response of plant respiration to temperature. Trends in Plant Science 8 (7), 343-351 Huntingford C, et al. (2004) Using a GCM analogue model to investigate the potential for Amazonian forest dieback. Theoretical and Applied Climatology, 78, 177-185.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Fang, Yilin; Leung, L. Ruby; Duan, Zhuoran
The Amazon basin experienced periodic droughts in the past, and climate models projected more intense and frequent droughts in the future. How tropical forests respond to drought may depend on water availability, which is modulated by landscape heterogeneity. Using the one-dimensional ACME Land Model (ALM) and the three-dimensional ParFlow variably saturated flow model, a series of numerical experiments were performed for the Asu catchment in central Amazon to elucidate processes that influence water available for plant use and provide insights for improving Earth system models. Results from ParFlow show that topography has a dominant influence on groundwater table and runoffmore » through lateral flow. Without any representations of lateral processes, ALM simulates very different seasonal variations in groundwater table and runoff compared to ParFlow even if it is able to reproduce the long-term spatial average groundwater table of ParFlow through simple parameter calibration. In the ParFlow simulations, the groundwater table is evidently deeper and the soil saturation is lower in the plateau compared to the valley. However, even in the plateau during the dry season in the drought year of 2005, plant transpiration is not water stressed in the ParFlow simulations as the soil saturation is still sufficient to maintain a soil matric potential for the stomata to be fully open. This finding is insensitive to uncertainty in atmospheric forcing and soil parameters, but the empirical wilting formulation used in the models is an important factor that should be addressed using observations and modeling of coupled plant hydraulics-soil hydrology processes in future studies.« less
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NASA Astrophysics Data System (ADS)
Tseng, C.; Lin, Y.
2013-12-01
Nitrogen balance involves many mechanisms and plays an important role to maintain the function of nature. Fertilizer application in agriculture activity is usually seen as a common and significant nitrogen input to environment. Improper fertilizer application on paddy field can result in great amount of various types of nitrogen losses. Hence, it is essential to understand and quantify the nitrogen dynamics in paddy field for fertilizer management and pollution control. In this study, we develop a model which considers major transformation processes of nitrogen (e.g. volatilization, nitrification, denitrification and plant uptake). In addition, we measured different types of nitrogen in plants, soil and water at plant growth stages in an experimental-scale paddy field in Taiwan. The measurement includes total nitrogen in plants and soil, and ammonium-N (NH4+-N), nitrate-N (NO3--N) and organic nitrogen in water. The measured data were used to calibrate the model parameters and validate the model for nitrogen balance simulation. The results showed that the model can accurately estimate the temporal dynamics of nitrogen balance in paddy field during the whole growth stage. This model might be helpful and useful for future fertilizer management and pollution control in paddy field.
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Integrated assessment of water-power grid systems under changing climate
NASA Astrophysics Data System (ADS)
Yan, E.; Zhou, Z.; Betrie, G.
2017-12-01
Energy and water systems are intrinsically interconnected. Due to an increase in climate variability and extreme weather events, interdependency between these two systems has been recently intensified resulting significant impacts on both systems and energy output. To address this challenge, an Integrated Water-Energy Systems Assessment Framework (IWESAF) is being developed to integrate multiple existing or developed models from various sectors. In this presentation, we are focusing on recent improvement in model development of thermoelectric power plant water use simulator, power grid operation and cost optimization model, and model integration that facilitate interaction among water and electricity generation under extreme climate events. A process based thermoelectric power water use simulator includes heat-balance, climate, and cooling system modules that account for power plant characteristics, fuel types, and cooling technology. The model is validated with more than 800 power plants of fossil-fired, nuclear and gas-turbine power plants with different cooling systems. The power grid operation and cost optimization model was implemented for a selected regional in the Midwest. The case study will be demonstrated to evaluate the sensitivity and resilience of thermoelectricity generation and power grid under various climate and hydrologic extremes and potential economic consequences.
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Federal Register 2010, 2011, 2012, 2013, 2014
2013-12-03
... WIPP PA process culminates in a series of computer simulations that model the physical attributes of... and Processes LWA Land Withdrawal Act MSHA Mine Safety and Health Administration NMED New Mexico... Agency's technical review process was to determine whether, with the new design, the WIPP adequately...
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Campos, Marcelo Lattarulo; Carvalho, Rogério Falleiros; Benedito, Vagner Augusto
2010-01-01
Hormones are molecules involved in virtually every step of plant development and studies in this field have been shaping plant physiology for more than a century. The model plant Arabidopsis thaliana, long used as a tool to study plant hormones, lacks significant important developmental traits, such as fleshy climacteric fruit, compound leaf and multicellular trichomes, suggesting the necessity for alternative plant models. An attractive option often used is tomato, a species also of major economic importance, being ideal to bring together basic and applied plant sciences. The tomato Micro-Tom (MT) cultivar makes it possible to combine the direct benefits of studying a crop species with the fast life cycle and small size required for a suitable biological model. However, few obscure questions are constantly addressed to MT, creating a process herein called “MT mystification”. In this work we present evidence clarifying these questions and show the potential of MT, aiming to demystify it. To corroborate our ideas we showed that, by making use of MT, our laboratory demonstrated straightforwardly new hormonal functions and also characterized a novel antagonistic hormonal interaction between jasmonates and brassinosteroids in the formation of anti-herbivory traits in tomato. PMID:20037476
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Efficiencies of power plants, quasi-static models and the geometric-mean temperature
NASA Astrophysics Data System (ADS)
Johal, Ramandeep S.
2017-02-01
Observed efficiencies of industrial power plants are often approximated by the square-root formula: 1 - √ T -/ T +, where T +( T -) is the highest (lowest) temperature achieved in the plant. This expression can be derived within finite-time thermodynamics, or, by entropy generation minimization, based on finite rates for the processes. In these analyses, a closely related quantity is the optimal value of the intermediate temperature for the hot stream, given by the geometric-mean value: √ T +/ T -. In this paper, instead of finite-time models, we propose to model the operation of plants by quasi-static work extraction models, with one reservoir (source/sink) as finite, while the other as practically infinite. No simplifying assumption is made on the nature of the finite system. This description is consistent with two model hypotheses, each yielding a specific value of the intermediate temperature, say T 1 and T 2. The lack of additional information on validity of the hypothesis that may be actually realized, motivates to approach the problem as an exercise in inductive inference. Thus we define an expected value of the intermediate temperature as the equally weighted mean: ( T 1 + T 2)/2. It is shown that the expected value is very closely given by the geometric-mean value for almost all of the observed power plants.
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Inverse modeling of the biodegradation of emerging organic contaminants in the soil-plant system.
Hurtado, Carlos; Trapp, Stefan; Bayona, Josep M
2016-08-01
Understanding the processes involved in the uptake and accumulation of organic contaminants into plants is very important to assess the possible human risk associated with. Biodegradation of emerging contaminants in plants has been observed, but kinetical studies are rare. In this study, we analyse experimental data on the uptake of emerging organic contaminants into lettuce derived in a greenhouse experiment. Measured soil, root and leaf concentrations from four contaminants were selected within the applicability domain of a steady-state two-compartment standard plant uptake model: bisphenol A (BPA), carbamazepine (CBZ), triclosan (TCS) and caffeine (CAF). The model overestimated concentrations in most cases, when no degradation rates in plants were entered. Subsequently, biodegradation rates were fitted so that the measured concentrations were met. Obtained degradation kinetics are in the order, BPA < CAF ≈ TCS < CBZ in roots, and BPA ≈ TCS < CBZ < CAF in leaves. Kinetics determined by inverse modeling are, despite the inherent uncertainty, indicative of the dissipation rates. The advantage of the procedure that is additional knowledge can be gained from existing experimental data. Dissipation kinetics found via inverse modeling is not a conclusive proof for biodegradation and confirmation by experimental studies is needed. Copyright © 2016. Published by Elsevier Ltd.
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Wilcox, D.A.; Xie, Y.
2007-01-01
Integrated, GIS-based, wetland predictive models were constructed to assist in predicting the responses of wetland plant communities to proposed new water-level regulation plans for Lake Ontario. The modeling exercise consisted of four major components: 1) building individual site wetland geometric models; 2) constructing generalized wetland geometric models representing specific types of wetlands (rectangle model for drowned river mouth wetlands, half ring model for open embayment wetlands, half ellipse model for protected embayment wetlands, and ellipse model for barrier beach wetlands); 3) assigning wetland plant profiles to the generalized wetland geometric models that identify associations between past flooding / dewatering events and the regulated water-level changes of a proposed water-level-regulation plan; and 4) predicting relevant proportions of wetland plant communities and the time durations during which they would be affected under proposed regulation plans. Based on this conceptual foundation, the predictive models were constructed using bathymetric and topographic wetland models and technical procedures operating on the platform of ArcGIS. An example of the model processes and outputs for the drowned river mouth wetland model using a test regulation plan illustrates the four components and, when compared against other test regulation plans, provided results that met ecological expectations. The model results were also compared to independent data collected by photointerpretation. Although data collections were not directly comparable, the predicted extent of meadow marsh in years in which photographs were taken was significantly correlated with extent of mapped meadow marsh in all but barrier beach wetlands. The predictive model for wetland plant communities provided valuable input into International Joint Commission deliberations on new regulation plans and was also incorporated into faunal predictive models used for that purpose.
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Proposed standards for peer-reviewed publication of computer code
USDA-ARS?s Scientific Manuscript database
Computer simulation models are mathematical abstractions of physical systems. In the area of natural resources and agriculture, these physical systems encompass selected interacting processes in plants, soils, animals, or watersheds. These models are scientific products and have become important i...
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NASA Astrophysics Data System (ADS)
Staudt, K.; Leifeld, J.; Bretscher, D.; Fuhrer, J.
2012-04-01
The Swiss inventory submission under the United Nations Framework Convention on Climate Change (UNFCCC) reports on changes in soil organic carbon stocks under different land-uses and land-use changes. The approach currently employed for cropland and grassland soils combines Tier 1 and Tier 2 methods and is considered overly simplistic. As the UNFCC encourages countries to develop Tier 3 methods for national greenhouse gas reporting, we aim to build up a model-based inventory of soil organic carbon in agricultural soils in Switzerland. We conducted a literature research on currently employed higher-tier methods using process-based models in four countries: Denmark, Sweden, Finland and the USA. The applied models stem from two major groups differing in complexity - those belonging to the group of general ecosystem models that include a plant-growth submodel, e.g. Century, and those that simulate soil organic matter turnover but not plant-growth, e.g. ICBM. For the latter group, carbon inputs to the soil from plant residues and roots have to be determined separately. We will present some aspects of the development of a model-based inventory of soil organic carbon in agricultural soils in Switzerland. Criteria for model evaluation are, among others, modeled land-use classes and land-use changes, spatial and temporal resolution, and coverage of relevant processes. For model parameterization and model evaluation at the field scale, data from several long-term agricultural experiments and monitoring sites in Switzerland is available. A subsequent regional application of a model requires the preparation of regional input data for the whole country - among others spatio-temporal meteorological data, agricultural and soil data. Following the evaluation of possible models and of available data, preference for application in the Swiss inventory will be given to simpler model structures, i.e. models without a plant-growth module. Thus, we compared different allometric relations for the estimation of plant carbon inputs to the soil from yield data that are usually provided with the models. Calculated above- and below-ground carbon inputs vary substantially between methods and exhibit different sensitivities to yield data. As a benchmark, inputs to the soil from above- and below-ground crop residues are calculated with the IPCC default method. Furthermore, the suitability of these estimation methods for Swiss conditions is tested.
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Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World.
Di Silvestre, Dario; Bergamaschi, Andrea; Bellini, Edoardo; Mauri, PierLuigi
2018-06-03
The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.
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Impacts of flare emissions from an ethylene plant shutdown to regional air quality
NASA Astrophysics Data System (ADS)
Wang, Ziyuan; Wang, Sujing; Xu, Qiang; Ho, Thomas
2016-08-01
Critical operations of chemical process industry (CPI) plants such as ethylene plant shutdowns could emit a huge amount of VOCs and NOx, which may result in localized and transient ozone pollution events. In this paper, a general methodology for studying dynamic ozone impacts associated with flare emissions from ethylene plant shutdowns has been developed. This multi-scale simulation study integrates process knowledge of plant shutdown emissions in terms of flow rate and speciation together with regional air-quality modeling to quantitatively investigate the sensitivity of ground-level ozone change due to an ethylene plant shutdown. The study shows the maximum hourly ozone increments can vary significantly by different plant locations and temporal factors including background ozone data and solar radiation intensity. It helps provide a cost-effective air-quality control strategy for industries by choosing the optimal starting time of plant shutdown operations in terms of minimizing the induced ozone impact (reduced from 34.1 ppb to 1.2 ppb in the performed case studies). This study provides valuable technical supports for both CPI and environmental policy makers on cost-effective air-quality controls in the future.
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Development Of Simulation Model For Fluid Catalytic Cracking
NASA Astrophysics Data System (ADS)
Ghosh, Sobhan
2010-10-01
Fluid Catalytic Cracking (FCC) is the most widely used secondary conversion process in the refining industry, for producing gasoline, olefins, and middle distillate from heavier petroleum fractions. There are more than 500 units in the world with a total processing capacity of about 17 to 20% of the crude capacity. FCC catalyst is the highest consumed catalyst in the process industry. On one hand, FCC is quite flexible with respect to it's ability to process wide variety of crudes with a flexible product yield pattern, and on the other hand, the interdependence of the major operating parameters makes the process extremely complex. An operating unit is self balancing and some fluctuations in the independent parameters are automatically adjusted by changing the temperatures and flow rates at different sections. However, a good simulation model is very useful to the refiner to get the best out of the process, in terms of selection of the best catalyst, to cope up with the day to day changing of the feed quality and the demands of different products from FCC unit. In addition, a good model is of great help in designing the process units and peripherals. A simple empirical model is often adequate to monitor the day to day operations, but they are not of any use in handling the other problems such as, catalyst selection or, design / modification of the plant. For this, a kinetic based rigorous model is required. Considering the complexity of the process, large number of chemical species undergoing "n" number of parallel and consecutive reactions, it is virtually impossible to develop a simulation model based on the kinetic parameters. The most common approach is to settle for a semi empirical model. We shall take up the key issues for developing a FCC model and the contribution of such models in the optimum operation of the plant.
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Al-Momani, Shireen; Qi, Da; Ren, Zhe; Jones, Andrew R
2018-06-15
Phosphorylation is one of the most prevalent post-translational modifications and plays a key role in regulating cellular processes. We carried out a bioinformatics analysis of pre-existing phosphoproteomics data, to profile two model species representing the largest subclasses in flowering plants the dicot Arabidopsis thaliana and the monocot Oryza sativa, to understand the extent to which phosphorylation signaling and function is conserved across evolutionary divergent plants. We identified 6537 phosphopeptides from 3189 phosphoproteins in Arabidopsis and 2307 phosphopeptides from 1613 phosphoproteins in rice. We identified phosphorylation motifs, finding nineteen pS motifs and two pT motifs shared in rice and Arabidopsis. The majority of shared motif-containing proteins were mapped to the same biological processes with similar patterns of fold enrichment, indicating high functional conservation. We also identified shared patterns of crosstalk between phosphoserines with enrichment for motifs pSXpS, pSXXpS and pSXXXpS, where X is any amino acid. Lastly, our results identified several pairs of motifs that are significantly enriched to co-occur in Arabidopsis proteins, indicating cross-talk between different sites, but this was not observed in rice. Our results demonstrate that there are evolutionary conserved mechanisms of phosphorylation-mediated signaling in plants, via analysis of high-throughput phosphorylation proteomics data from key monocot and dicot species: rice and Arabidposis thaliana. The results also suggest that there is increased crosstalk between phosphorylation sites in A. thaliana compared with rice. The results are important for our general understanding of cell signaling in plants, and the ability to use A. thaliana as a general model for plant biology. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Azadi, Paratoo
2015-09-24
The Complex Carbohydrate Research Center (CCRC) of the University of Georgia holds a symposium yearly that highlights a broad range of carbohydrate research topics. The 8th Annual Georgia Glycoscience Symposium entitled “Integrating Models of Plant Cell Wall Structure, Biosynthesis and Assembly” was held on April 7, 2014 at the CCRC. The focus of symposium was on the role of glycans in plant cell wall structure and synthesis. The goal was to have world leaders in conjunction with graduate students, postdoctoral fellows and research scientists to propose the newest plant cell wall models. The symposium program closely followed the DOE’s missionmore » and was specifically designed to highlight chemical and biochemical structures and processes important for the formation and modification of renewable plant cell walls which serve as the basis for biomaterial and biofuels. The symposium was attended by both senior investigators in the field as well as students including a total attendance of 103, which included 80 faculty/research scientists, 11 graduate students and 12 Postdoctoral students.« less
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NASA Astrophysics Data System (ADS)
Holmberg, Madeleine; Paille, Christel; Lasseur, Christophe
The ESA project Micro Ecological Life Support System Alternative (MELiSSA) is an ecosystem of micro-organisms and higher plants, constructed with the objective of being operated as a tool to understand artificial ecosystems to be used for a long-term or permanent manned planetary base (e.g. Moon or Mars). The purpose of such a system is to provide for generation of food, water recycling, atmospheric regeneration and waste management within defined standards of quality and reliability. As MELiSSA consists of individual compartments which are connected to each other, the robustness of the system is fully dependent on the control of each compartment, as well as the flow management between them. Quality of consumables and reliability of the ecosystem rely on the knowledge, understanding and control of each of the components. This includes the full understanding of all processes related to the higher plants. To progress in that direction, this paper focuses on the mechanical processes driving the gas and liquid exchanges between the plant leaf and its environment. The process responsible for the mass transfer on the surface of plant leaves is diffusion. The diffusion flux is dependent on the behaviour of the stoma of the leaf and also on the leaf boundary layer (BL). In this paper, the physiology of the leaf is briefly examined in order to relate parameters such as light quality, light quantity, CO2 concentration, temperature, leaf water potential, humidity, vapour pressure deficit (VPD) gradients and pollutants to the opening or closing of stomata. The diffusion process is described theoretically and the description is compared to empirical approaches. The variables of the BL are examined and the effect airflow in the compartment has on the BL is investigated. Also presented is the impact changes in different environmental parameters may have on the fluid exchanges. Finally, some tests, to evaluate the accuracy of the concluded model, are suggested.
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Compositional Models of Glass/Melt Properties and their Use for Glass Formulation
Vienna, John D.; USA, Richland Washington
2014-12-18
Nuclear waste glasses must simultaneously meet a number of criteria related to their processability, product quality, and cost factors. The properties that must be controlled in glass formulation and waste vitrification plant operation tend to vary smoothly with composition allowing for glass property-composition models to be developed and used. Models have been fit to the key glass properties. The properties are transformed so that simple functions of composition (e.g., linear, polynomial, or component ratios) can be used as model forms. The model forms are fit to experimental data designed statistically to efficiently cover the composition space of interest. Examples ofmore » these models are found in literature. The glass property-composition models, their uncertainty definitions, property constraints, and optimality criteria are combined to formulate optimal glass compositions, control composition in vitrification plants, and to qualify waste glasses for disposal. An overview of current glass property-composition modeling techniques is summarized in this paper along with an example of how those models are applied to glass formulation and product qualification at the planned Hanford high-level waste vitrification plant.« less
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Magargal, Kate E; Parker, Ashley K; Vernon, Kenneth Blake; Rath, Will; Codding, Brian F
2017-07-08
The expansion of Numic speaking populations into the Great Basin required individuals to adapt to a relatively unproductive landscape. Researchers have proposed numerous social and subsistence strategies to explain how and why these settlers were able to replace any established populations, including private property and intensive plant processing. Here we evaluate these hypotheses and propose a new strategy involving the use of landscape fire to increase resource encounter rates. Implementing a novel, spatially explicit, multi-scalar prey choice model, we examine how individual decisions approximating each alternative strategy (private property, anthropogenic fire, and intensive plant processing) would aggregate at the patch and band level to confer an overall benefit to this colonizing population. Analysis relies on experimental data reporting resource profitability and abundance, ecological data on the historic distribution of vegetation patches, and ethnohistoric data on the distribution of Numic bands. Model results show that while resource privatization and landscape fires produce a substantial advantage, intensified plant processing garners the greatest benefit. The relative benefits of alternative strategies vary significantly across ecological patches resulting in variation across ethnographic band ranges. Combined, a Numic strategy including all three alternatives would substantially increase subsistence yields. The application of a strategy set that includes landscape fire, privatization and intensified processing of seeds and nuts, explains why the Numa were able to outcompete local populations. This approach provides a framework to help explain how individual decisions can result in such population replacement events throughout human history. © 2017 Wiley Periodicals, Inc.
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Descriptive and sensitivity analyses of WATBALI: A dynamic soil water model
NASA Technical Reports Server (NTRS)
Hildreth, W. W. (Principal Investigator)
1981-01-01
A soil water computer model that uses the IBM Continuous System Modeling Program III to solve the dynamic equations representing the soil, plant, and atmospheric physical or physiological processes considered is presented and discussed. Using values describing the soil-plant-atmosphere characteristics, the model predicts evaporation, transpiration, drainage, and soil water profile changes from an initial soil water profile and daily meteorological data. The model characteristics and simulations that were performed to determine the nature of the response to controlled variations in the input are described the results of the simulations are included and a change that makes the response of the model more closely represent the observed characteristics of evapotranspiration and profile changes for dry soil conditions is examined.
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NASA Astrophysics Data System (ADS)
Still, C. J.; Griffith, D.; Edwards, E.; Forrestel, E.; Lehmann, C.; Anderson, M.; Craine, J.; Pau, S.; Osborne, C.
2014-12-01
Variation in plant species traits, such as photosynthetic and hydraulic properties, can indicate vulnerability or resilience to climate change, and feed back to broad-scale spatial and temporal patterns in biogeochemistry, demographics, and biogeography. Yet, predicting how vegetation will respond to future environmental changes is severely limited by the inability of our models to represent species-level trait variation in processes and properties, as current generation process-based models are mostly based on the generalized and abstracted concept of plant functional types (PFTs) which were originally developed for hydrological modeling. For example, there are close to 11,000 grass species, but most vegetation models have only a single C4 grass and one or two C3 grass PFTs. However, while species trait databases are expanding rapidly, they have been produced mostly from unstructured research, with a focus on easily researched traits that are not necessarily the most important for determining plant function. Additionally, implementing realistic species-level trait variation in models is challenging. Combining related and ecologically similar species in these models might ameliorate this limitation. Here we argue for an intermediate, lineage-based approach to PFTs, which draws upon recent advances in gene sequencing and phylogenetic modeling, and where trait complex variations and anatomical features are constrained by a shared evolutionary history. We provide an example of this approach with grass lineages that vary in photosynthetic pathway (C3 or C4) and other functional and structural traits. We use machine learning approaches and geospatial databases to infer the most important environmental controls and climate niche variation for the distribution of grass lineages, and utilize a rapidly expanding grass trait database to demonstrate examples of lineage-based grass PFTs. For example, grasses in the Andropogoneae are typically tall species that dominate wet and seasonally burned ecosystems, whereas Chloridoideae grasses are associated with semi-arid regions. These two C4 lineages are expected to respond quite differently to climate change, but are often modelled as a single PFT.
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Potential use of advanced process control for safety purposes during attack of a process plant.
Whiteley, James R
2006-03-17
Many refineries and commodity chemical plants employ advanced process control (APC) systems to improve throughputs and yields. These APC systems utilize empirical process models for control purposes and enable operation closer to constraints than can be achieved with traditional PID regulatory feedback control. Substantial economic benefits are typically realized from the addition of APC systems. This paper considers leveraging the control capabilities of existing APC systems to minimize the potential impact of a terrorist attack on a process plant (e.g., petroleum refinery). Two potential uses of APC are described. The first is a conventional application of APC and involves automatically moving the process to a reduced operating rate when an attack first begins. The second is a non-conventional application and involves reconfiguring the APC system to optimize safety rather than economics. The underlying intent in both cases is to reduce the demands on the operator to allow focus on situation assessment and optimal response planning. An overview of APC is provided along with a brief description of the modifications required for the proposed new applications of the technology.
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de Langre, Emmanuel
2012-03-15
The modeling of fluid-structure interactions, such as flow-induced vibrations, is a well-developed field of mechanical engineering. Many methods exist, and it seems natural to apply them to model the behavior of plants, and potentially other cantilever-like biological structures, under flow. Overcoming this disciplinary divide, and the application of such models to biological systems, will significantly advance our understanding of ecological patterns and processes and improve our predictive capabilities. Nonetheless, several methodological issues must first be addressed, which I describe here using two practical examples that have strong similarities: one from agricultural sciences and the other from nuclear engineering. Very similar issues arise in both: individual and collective behavior, small and large space and time scales, porous modeling, standard and extreme events, trade-off between the surface of exchange and individual or collective risk of damage, variability, hostile environments and, in some aspects, evolution. The conclusion is that, although similar issues do exist, which need to be exploited in some detail, there is a significant gap that requires new developments. It is obvious that living plants grow in and adapt to their environment, which certainly makes plant biomechanics fundamentally distinct from classical mechanical engineering. Moreover, the selection processes in biology and in human engineering are truly different, making the issue of safety different as well. A thorough understanding of these similarities and differences is needed to work efficiently in the application of a mechanistic approach to ecology.
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Cornelissen, J H C; Quested, H M; van Logtestijn, R S P; Pérez-Harguindeguy, N; Gwynn-Jones, D; Díaz, S; Callaghan, T V; Press, M C; Aerts, R
2006-03-01
Plant traits have become popular as predictors of interspecific variation in important ecosystem properties and processes. Here we introduce foliar pH as a possible new plant trait, and tested whether (1) green leaf pH or leaf litter pH correlates with biochemical and structural foliar traits that are linked to biogeochemical cycling; (2) there is consistent variation in green leaf pH or leaf litter pH among plant types as defined by nutrient uptake mode and higher taxonomy; (3) green leaf pH can predict a significant proportion of variation in leaf digestibility among plant species and types; (4) leaf litter pH can predict a significant proportion of variation in leaf litter decomposability among plant species and types. We found some evidence in support of all four hypotheses for a wide range of species in a subarctic flora, although cryptogams (fern allies and a moss) tended to weaken the patterns by showing relatively poor leaf digestibility or litter decomposability at a given pH. Among seed plant species, green leaf pH itself explained only up to a third of the interspecific variation in leaf digestibility and leaf litter up to a quarter of the interspecific variation in leaf litter decomposability. However, foliar pH substantially improved the power of foliar lignin and/or cellulose concentrations as predictors of these processes when added to regression models as a second variable. When species were aggregated into plant types as defined by higher taxonomy and nutrient uptake mode, green-specific leaf area was a more powerful predictor of digestibility or decomposability than any of the biochemical traits including pH. The usefulness of foliar pH as a new predictive trait, whether or not in combination with other traits, remains to be tested across more plant species, types and biomes, and also in relation to other plant or ecosystem traits and processes.
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ERIC Educational Resources Information Center
Weaver, Kim M.
2005-01-01
In this unit, elementary students design and build a lunar plant growth chamber using the Engineering Design Process. The purpose of the unit is to help students understand and apply the design process as it relates to plant growth on the moon. This guide includes six lessons, which meet a number of national standards and benchmarks in…
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Tawussi, Frank; Gupta, Dharmendra K; Mühr-Ebert, Elena L; Schneider, Stephanie; Bister, Stefan; Walther, Clemens
2017-11-01
Bioavailability and plant uptake of radionuclides depend on various factors. Transfer into different plant parts depends on chemical and physical processes, which need to be known for realistic ingestion dose modelling when these plants are used for food. Within the scope of the present work, the plutonium uptake by potato plants (Solanum tuberosum L.) was investigated in hydroponic solution of low concentration [Pu] = 10 -9 mol L -1 . Particular attention was paid to the speciation of radionuclides in the solution which was modelled by the speciation code PHREEQC. The speciation, the solubility and therefore the plant availability of radionuclides mainly depend on the pH value and the redox potential of the solution. During the contamination period, the redox potential did not change significantly. In contrast, the pH value showed characteristic changes depending on exudates excreted by the plants. Plant roots took up high amounts of plutonium (37%-50% of the added total amount). In addition to the uptake into the roots, the radionuclides can also adsorb to the exterior root surface. The solution-to-plant transfer factor showed values between 0.03 and 0.80 (Bq kg -1 / Bq L -1 ) for the potato tubers. By addition of the complexing agent EDTA (10 -4 mol L-1), the plutonium uptake from solution increased by 58% in tubers and by 155% in shoots/leaves. The results showed that excreted substances by plants affect bioavailability of radionuclides at low concentration, on the one hand. On the other hand, the uptake of plutonium by roots and the accumulation in different plant parts can lead to non-negligible ingestion doses, even at low concentration. We are aware of the limited transferability of data obtained in hydroponic solutions to plants growing in soil. However, the aim of this study is twofold: First we want to investigate the influence of Pu speciation on plant uptake in a rather well defined system which can be modelled using available thermodynamic data. Second, techniques developed here shall be applied to the investigation of plants growing in soil in the future. The present work contributes to the basic understanding how plant induced effects on nutrient solution influence bioavailability of radionuclides and fosters the need for more detailed investigations of the complex uptake and accumulation processes of radionuclides into plants. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Wet Oxidation as a Waste Treatment Method in Closed Systems
NASA Technical Reports Server (NTRS)
Onisko, B. L.; Wydeven, T.
1982-01-01
The chemistry of the wet oxidation process was investigated in relation to production of plant nutrients from plant and human waste materials as required for a closed life support system. Hydroponically grown lettuce plants were used as a model plant waste, and oxygen gas was used as an oxidant. Organic nitrogen content was decreased 88-100%, depending on feed material. Production of ammonia and nitrogen gas accounted for all of the observed decrease in organic nitrogen content. No nitrous oxide (N2O) was detected. The implications of these results for closed life support systems are discussed.
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Wet oxidation as a waste treatment in closed systems
NASA Technical Reports Server (NTRS)
Onisko, B. L.; Wydeven, T.
1981-01-01
The chemistry of the wet oxidation process has been investigated in relation to production of plant nutrients from plant and human waste materials as required for a closed life-support system. Hydroponically grown lettuce plants were used as a model plant waste and oxygen gas was used as oxidant. Organic nitrogen content was decreased 88-100% depending on feed material. Production of ammonia and nitrogen gas account for all of the observed decrease in organic nitrogen content. No nitrous oxide (N2O) was detected. The implications of these results for closed life-support systems are discussed.
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Wullschleger, Stan D.; Epstein, Howard E.; Box, Elgene O.; Euskirchen, Eugénie S.; Goswami, Santonu; Iversen, Colleen M.; Kattge, Jens; Norby, Richard J.; van Bodegom, Peter M.; Xu, Xiaofeng
2014-01-01
Background Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. Scope Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation. Conclusions Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait–environment relationships. Surprisingly, despite being important to land–atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings. PMID:24793697
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Modelling microbial exchanges between forms of soil nitrogen in contrasting ecosystems
NASA Astrophysics Data System (ADS)
Pansu, M.; Machado, D.; Bottner, P.; Sarmiento, L.
2014-02-01
Although nitrogen (N) is often combined with carbon (C) in organic molecules, C passes from the air to the soil through plant photosynthesis, whereas N passes from the soil to plants through a chain of microbial conversions. However, dynamic models do not fully consider the microorganisms at the centre of exchange processes between organic and mineral forms of N. This study monitored the transfer of 14C and 15N between plant materials, microorganisms, humified compartments, and inorganic forms in six very different ecosystems along an altitudinal transect. The microbial conversions of the 15N forms appear to be strongly linked to the previously modelled C cycle, and the same equations and parameters can be used to model both C and N cycles. The only difference is in the modelling of the flows between microbial and inorganic forms. The processes of mineralization and immobilization of N appear to be regulated by a two-way microbial exchange depending on the C : N ratios of microorganisms and available substrates. The MOMOS (Modelling of Organic Matter of Soils) model has already been validated for the C cycle and also appears to be valid for the prediction of microbial transformations of N forms. This study shows that the hypothesis of microbial homeostasis can give robust predictions at global scale. However, the microbial populations did not appear to always be independent of the external constraints. At some altitudes their C : N ratio could be better modelled as decreasing during incubation and increasing with increasing C storage in cold conditions. The ratio of potentially mineralizable-15N/inorganic-15N and the 15N stock in the plant debris and the microorganisms was modelled as increasing with altitude, whereas the 15N storage in stable humus was modelled as decreasing with altitude. This predicts that there is a risk that mineralization of organic reserves in cold areas may increase global warming.
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High Temperature Modification of SNCR Technology and its Impact on NOx Removal Process
NASA Astrophysics Data System (ADS)
Blejchař, Tomáš; Konvička, Jaroslav; von der Heide, Bernd; Malý, Rostislav; Maier, Miloš
2018-06-01
SNCR (Selective non-catalytic reduction) Technology is currently being used to reach the emission limit for nitrogen oxides at fossil fuel fired power plant and/or heating plant and optimum temperature for SNCR process is in range 850 - 1050°C. Modified SNCR technology is able to reach reduction 60% of nitrogen oxides at temperature up to 1250°C. So the technology can also be installed where the flue gas temperature is too high in combustion chamber. Modified SNCR was tested using generally known SNCR chemistry implemented in CFD (Computation fluid dynamics) code. CFD model was focused on detail simulation of reagent injection and influence of flue gas temperature. Than CFD simulation was compared with operating data of boiler where the modified SNCR technology is installed. By comparing the experiment results with the model, the effect on nitrous oxides removal process and temperature of flue gas at the injection region.
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TOOKUIL: A case study in user interface development for safety code application
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gray, D.L.; Harkins, C.K.; Hoole, J.G.
1997-07-01
Traditionally, there has been a very high learning curve associated with using nuclear power plant (NPP) analysis codes. Even for seasoned plant analysts and engineers, the process of building or modifying an input model for present day NPP analysis codes is tedious, error prone, and time consuming. Current cost constraints and performance demands place an additional burden on today`s safety analysis community. Advances in graphical user interface (GUI) technology have been applied to obtain significant productivity and quality assurance improvements for the Transient Reactor Analysis Code (TRAC) input model development. KAPL Inc. has developed an X Windows-based graphical user interfacemore » named TOOKUIL which supports the design and analysis process, acting as a preprocessor, runtime editor, help system, and post processor for TRAC. This paper summarizes the objectives of the project, the GUI development process and experiences, and the resulting end product, TOOKUIL.« less
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Feldman, Max J.; Paul, Rachel E.; Banan, Darshi; ...
2017-06-23
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. For this research, we have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reducedmore » under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Feldman, Max J.; Paul, Rachel E.; Banan, Darshi
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. For this research, we have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reducedmore » under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.« less
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Paul, Rachel E.; Sebastian, Jose; Yee, Muh-Ching; Jiang, Hui; Lipka, Alexander E.; Brutnell, Thomas P.; Dinneny, José R.; Leakey, Andrew D. B.
2017-01-01
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development. PMID:28644860
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Feldman, Max J; Paul, Rachel E; Banan, Darshi; Barrett, Jennifer F; Sebastian, Jose; Yee, Muh-Ching; Jiang, Hui; Lipka, Alexander E; Brutnell, Thomas P; Dinneny, José R; Leakey, Andrew D B; Baxter, Ivan
2017-06-01
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.
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Validation of a multi-phase plant-wide model for the description of the aeration process in a WWTP.
Lizarralde, I; Fernández-Arévalo, T; Beltrán, S; Ayesa, E; Grau, P
2018-02-01
This paper introduces a new mathematical model built under the PC-PWM methodology to describe the aeration process in a full-scale WWTP. This methodology enables a systematic and rigorous incorporation of chemical and physico-chemical transformations into biochemical process models, particularly for the description of liquid-gas transfer to describe the aeration process. The mathematical model constructed is able to reproduce biological COD and nitrogen removal, liquid-gas transfer and chemical reactions. The capability of the model to describe the liquid-gas mass transfer has been tested by comparing simulated and experimental results in a full-scale WWTP. Finally, an exploration by simulation has been undertaken to show the potential of the mathematical model. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Analysing growth and development of plants jointly using developmental growth stages.
Dambreville, Anaëlle; Lauri, Pierre-Éric; Normand, Frédéric; Guédon, Yann
2015-01-01
Plant growth, the increase of organ dimensions over time, and development, the change in plant structure, are often studied as two separate processes. However, there is structural and functional evidence that these two processes are strongly related. The aim of this study was to investigate the co-ordination between growth and development using mango trees, which have well-defined developmental stages. Developmental stages, determined in an expert way, and organ sizes, determined from objective measurements, were collected during the vegetative growth and flowering phases of two cultivars of mango, Mangifera indica. For a given cultivar and growth unit type (either vegetative or flowering), a multistage model based on absolute growth rate sequences deduced from the measurements was first built, and then growth stages deduced from the model were compared with developmental stages. Strong matches were obtained between growth stages and developmental stages, leading to a consistent definition of integrative developmental growth stages. The growth stages highlighted growth asynchronisms between two topologically connected organs, namely the vegetative axis and its leaves. Integrative developmental growth stages emphasize that developmental stages are closely related to organ growth rates. The results are discussed in terms of the possible physiological processes underlying these stages, including plant hydraulics, biomechanics and carbohydrate partitioning. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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NASA Astrophysics Data System (ADS)
Tikhomirov, Alexander A.; Ushakova, Sofya; Velichko, Vladimir; Tikhomirova, Natalia; Shikhov, Valentin; Trifonov, Sergey V.
2016-07-01
A promising way to develop future biotechnical life support systems (BTLSS) is to construct experimental models and establish the cycling intended for a fraction of a human. Being of relatively low cost, such models provide an opportunity to test effectively closed process that could be further transferred to the real BTLSS with humans. Researchers of the IBP SB RAS are developing an adequate BTLSS model with the loops closed to a high degree. To attain high closure of mass exchange processes, plants in the phototrophic compartment are cultivated under intensive lighting conditions, created by using modern LED irradiators of enhanced power, equipped with lens optics. The higher plant compartment has been renewed and broadened by including soybean plants, which improve the vegetable part of the human diet and make it more diverse. It is very important that the operation of the physicochemical installation for waste mineralization fully matches the composition of the atmosphere of plant growth chambers: the purified gaseous components of this installation enter the common atmosphere of the system, without causing any deviations from the norm in the gaseous composition. This proves the eco-friendliness of the developed physicochemical method of waste mineralization and shows that the gaseous components resulting from waste mineralization can be included in the system mass exchange. A system for including human respiration into the gas exchange of the BTLSS has been developed and tested; the associated gas exchange and water exchange dynamics have been analyzed. Results of the functioning of the experimental model of the BTLSS for several months are proposed for discussion in order to get insight into the formation of dynamic characteristics of cycling processes and factors determining them. The study was supported by the grant of the Russian Science Foundation (Project 14-14-00599) and carried out at the IBP SB RAS.
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Interface design in the process industries
NASA Technical Reports Server (NTRS)
Beaverstock, M. C.; Stassen, H. G.; Williamson, R. A.
1977-01-01
Every operator runs his plant in accord with his own mental model of the process. In this sense, one characteristic of an ideal man-machine interface is that it be in harmony with that model. With this theme in mind, the paper first reviews the functions of the process operator and compares them with human operators involved in control situations previously studied outside the industrial environment (pilots, air traffic controllers, helmsmen, etc.). A brief history of the operator interface in the process industry and the traditional methodology employed in its design is then presented. Finally, a much more fundamental approach utilizing a model definition of the human operator's behavior is presented.
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Fault detection and diagnosis in an industrial fed-batch cell culture process.
Gunther, Jon C; Conner, Jeremy S; Seborg, Dale E
2007-01-01
A flexible process monitoring method was applied to industrial pilot plant cell culture data for the purpose of fault detection and diagnosis. Data from 23 batches, 20 normal operating conditions (NOC) and three abnormal, were available. A principal component analysis (PCA) model was constructed from 19 NOC batches, and the remaining NOC batch was used for model validation. Subsequently, the model was used to successfully detect (both offline and online) abnormal process conditions and to diagnose the root causes. This research demonstrates that data from a relatively small number of batches (approximately 20) can still be used to monitor for a wide range of process faults.
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Principles of an enhanced MBR-process with mechanical cleaning.
Rosenberger, S; Helmus, F P; Krause, S; Bareth, A; Meyer-Blumenroth, U
2011-01-01
Up to date, different physical and chemical cleaning protocols are necessary to limit membrane fouling in membrane bioreactors. This paper deals with a mechanical cleaning process, which aims at the avoidance of hypochlorite and other critical chemicals in MBR with submerged flat sheet modules. The process basically consists of the addition of plastic particles into the loop circulation within submerged membrane modules. Investigations of two pilot plants are presented: Pilot plant 1 is equipped with a 10 m(2) membrane module and operated with a translucent model suspension; pilot plant 2 is equipped with four 50 m(2) membrane modules and operated with pretreated sewage. Results of pilot plant 1 show that the establishment of a fluidised bed with regular particle distribution is possible for a variety of particles. Particles with maximum densities of 1.05 g/cm(3) and between 3 and 5 mm diameter form a stable fluidised bed almost regardless of activated sludge concentration, viscosity and reactor geometry. Particles with densities between 1.05 g/cm(3) and 1.2 g/cm(3) form a stable fluidised bed, if the velocity at the reactor bottom is sufficiently high. Activities within pilot plant 2 focused on plant optimisation and the development of an adequate particle retention system.
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NASA Astrophysics Data System (ADS)
Christoffersen, B. O.; Xu, C.; Fisher, R.; Fyllas, N.; Gloor, M.; Fauset, S.; Galbraith, D.; Koven, C.; Knox, R. G.; Kueppers, L. M.; Chambers, J. Q.; Meir, P.; McDowell, N. G.
2016-12-01
A major challenge of Earth System Models (ESMs) is to capture the diversity of individual-level responses to changes in water availability. Yet, decades of research in plant physiological ecology have given us a means to quantify central tendencies and variances of plant hydraulic traits. If ESMs possessed the relevant hydrodynamic process structure, these traits could be incorporated into improved predictions of community- and ecosystem-level processes such as tree mortality. We present a model of plant hydraulics in which all parameters are biologically-interpretable and measurable traits, such as turgor loss point πtlp, bulk elastic modulus ɛ, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50 % loss of conductivity for both xylem (P50,x) and stomata (P50,gs). We applied this scheme to tropical forests by incorporating it into both an individual-based model `Trait Forest Simulator' (TFS) and the `Functionally Assembled Terrestrial Ecosystem Simulator' (FATES; derived from CLM(ED)), and explore the consequences of variability in plant hydraulic traits on simulated leaf water potential, a potentially powerful predictor of tree mortality. We show that, independent of the difference between P50,gs and P50,x, or the hydraulic safety margin (HSM), diversity in hydraulic traits can increase or decrease whole-ecosystem resistance to hydraulic failure, and thus ecosystem-level responses to drought. Key uncertainties remaining concern how coordination and trade-offs in hydraulic traits are parameterized. We conclude that inclusion of such a physiologically-based plant hydraulics scheme in ESMs will greatly improve the capability of ESMs to predict functional trait filtering within ecosystems in responding to environmental change.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard
Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less
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Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard; ...
2017-06-06
Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less
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A review of model applications for structured soils: b) Pesticide transport.
Köhne, John Maximilian; Köhne, Sigrid; Simůnek, Jirka
2009-02-16
The past decade has seen considerable progress in the development of models simulating pesticide transport in structured soils subject to preferential flow (PF). Most PF pesticide transport models are based on the two-region concept and usually assume one (vertical) dimensional flow and transport. Stochastic parameter sets are sometimes used to account for the effects of spatial variability at the field scale. In the past decade, PF pesticide models were also coupled with Geographical Information Systems (GIS) and groundwater flow models for application at the catchment and larger regional scales. A review of PF pesticide model applications reveals that the principal difficulty of their application is still the appropriate parameterization of PF and pesticide processes. Experimental solution strategies involve improving measurement techniques and experimental designs. Model strategies aim at enhancing process descriptions, studying parameter sensitivity, uncertainty, inverse parameter identification, model calibration, and effects of spatial variability, as well as generating model emulators and databases. Model comparison studies demonstrated that, after calibration, PF pesticide models clearly outperform chromatographic models for structured soils. Considering nonlinear and kinetic sorption reactions further enhanced the pesticide transport description. However, inverse techniques combined with typically available experimental data are often limited in their ability to simultaneously identify parameters for describing PF, sorption, degradation and other processes. On the other hand, the predictive capacity of uncalibrated PF pesticide models currently allows at best an approximate (order-of-magnitude) estimation of concentrations. Moreover, models should target the entire soil-plant-atmosphere system, including often neglected above-ground processes such as pesticide volatilization, interception, sorption to plant residues, root uptake, and losses by runoff. The conclusions compile progress, problems, and future research choices for modelling pesticide displacement in structured soils.
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NASA Astrophysics Data System (ADS)
Gong, Jinnan; Wang, Ben; Jia, Xin; Feng, Wei; Zha, Tianshan; Kellomäki, Seppo; Peltola, Heli
2018-01-01
We used process-based modelling to investigate the roles of carbon-flux (C-flux) components and plant-interspace heterogeneities in regulating soil CO2 exchanges (FS) in a dryland ecosystem with sparse vegetation. To simulate the diurnal and seasonal dynamics of FS, the modelling considered simultaneously the CO2 production, transport and surface exchanges (e.g. biocrust photosynthesis, respiration and photodegradation). The model was parameterized and validated with multivariate data measured during the years 2013-2014 in a semiarid shrubland ecosystem in Yanchi, northwestern China. The model simulation showed that soil rewetting could enhance CO2 dissolution and delay the emission of CO2 produced from rooting zone. In addition, an ineligible fraction of respired CO2 might be removed from soil volumes under respiration chambers by lateral water flows and root uptakes. During rewetting, the lichen-crusted soil could shift temporally from net CO2 source to sink due to the activated photosynthesis of biocrust but the restricted CO2 emissions from subsoil. The presence of plant cover could decrease the root-zone CO2 production and biocrust C sequestration but increase the temperature sensitivities of these fluxes. On the other hand, the sensitivities of root-zone emissions to water content were lower under canopy, which may be due to the advection of water flows from the interspace to canopy. To conclude, the complexity and plant-interspace heterogeneities of soil C processes should be carefully considered to extrapolate findings from chamber to ecosystem scales and to predict the ecosystem responses to climate change and extreme climatic events. Our model can serve as a useful tool to simulate the soil CO2 efflux dynamics in dryland ecosystems.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
McCorkle, D.; Yang, C.; Jordan, T.
2007-06-01
Modeling and simulation tools are becoming pervasive in the process engineering practice of designing advanced power generation facilities. These tools enable engineers to explore many what-if scenarios before cutting metal or constructing a pilot scale facility. While such tools enable investigation of crucial plant design aspects, typical commercial process simulation tools such as Aspen Plus®, gPROMS®, and HYSYS® still do not explore some plant design information, including computational fluid dynamics (CFD) models for complex thermal and fluid flow phenomena, economics models for policy decisions, operational data after the plant is constructed, and as-built information for use in as-designed models. Softwaremore » tools must be created that allow disparate sources of information to be integrated if environments are to be constructed where process simulation information can be accessed. At the Department of Energy’s (DOE) National Energy Technology Laboratory (NETL), the Advanced Process Engineering Co-Simulator (APECS) has been developed as an integrated software suite that combines process simulation (e.g., Aspen Plus) and high-fidelity equipment simulation (e.g., Fluent® CFD), together with advanced analysis capabilities including case studies, sensitivity analysis, stochastic simulation for risk/uncertainty analysis, and multi-objective optimization. In this paper, we discuss the initial phases of integrating APECS with the immersive and interactive virtual engineering software, VE-Suite, developed at Iowa State University and Ames Laboratory. VE-Suite utilizes the ActiveX (OLE Automation) controls in Aspen Plus wrapped by the CASI library developed by Reaction Engineering International to run the process simulation and query for unit operation results. This integration permits any application that uses the VE-Open interface to integrate with APECS co-simulations, enabling construction of the comprehensive virtual engineering environment needed for the rapid engineering of advanced power generation facilities.« less
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Arnan, Xavier; Molowny-Horas, Roberto; Rodrigo, Anselm; Retana, Javier
2012-01-01
Secondary seed dispersal is an important plant-animal interaction, which is central to understanding plant population and community dynamics. Very little information is still available on the effects of dispersal on plant demography and, particularly, for ant-seed dispersal interactions. As many other interactions, seed dispersal by animals involves costs (seed predation) and benefits (seed dispersal), the balance of which determines the outcome of the interaction. Separate quantification of each of them is essential in order to understand the effects of this interaction. To address this issue, we have successfully separated and analyzed the costs and benefits of seed dispersal by seed-harvesting ants on the plant population dynamics of three shrub species with different traits. To that aim a stochastic, spatially-explicit individually-based simulation model has been implemented based on actual data sets. The results from our simulation model agree with theoretical models of plant response dependent on seed dispersal, for one plant species, and ant-mediated seed predation, for another one. In these cases, model predictions were close to the observed values at field. Nonetheless, these ecological processes did not affect in anyway a third species, for which the model predictions were far from the observed values. This indicates that the balance between costs and benefits associated to secondary seed dispersal is clearly related to specific traits. This study is one of the first works that analyze tradeoffs of secondary seed dispersal on plant population dynamics, by disentangling the effects of related costs and benefits. We suggest analyzing the effects of interactions on population dynamics as opposed to merely analyzing the partners and their interaction strength. PMID:22880125
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NASA Astrophysics Data System (ADS)
Beverly, D.; Speckman, H. N.; Klatt, A. L.; Ewers, B. E.
2016-12-01
Whole-plant hydraulic conductance is now used in many processed-based ecohydrological models running at the plot to regional scales. Many models, such as Dynamic Global Vegetation Model (DGVM), predict entire ecosystem evapotranspiration (ET) based on a single unvarying plant conductance parameter that assumes no variation in plant traits. However, whole-plant conductance varies in space, time, and with topography. Understanding this variation increases model predictive power for stand and ecosystem level estimates of ET, ultimately reducing uncertainty in predictions of the water balance. We hypothesize that whole-plant conductance (Kw) is water limited in the up-slope stands due to water flow paths and energy limited in down-slope stands due to shading. To test this hypothesis in two adjacent stands in the Medicine Bow Mountains of southern Wyoming. Both mixed conifer stands were south-facing, with the upper stand being 300 m above the down-slope stand. Whole-plant conductance was quantified measuring sapflow (Js) and leaf water potential (WPL) throughout the growing season. To quantify Js, each stand was instrumented with 30 Granier-type sapflow sensors. Leaf-water potentials were measured in monthly 48-hour campaigns sampling every 3 hours. The upper slope stand exhibited significantly lower Kw (approximately 35% lower in spruce and pine) and decreased throughout the growing season, driven by drying soils resulting in lower predawn WPL. In contrast, the down-slope stand Kw peaked in July before decreasing for rest of the summer. Down-slope predawn WPL maintained a consistent predawn WPL until October reflecting consistent water input from the upper slopes and ground water. Including this topographical variation in whole-plant conductance will increase the predictive power of models simulating evapotranspiration at the watershed scale.
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Towards a comprehensive greenhouse gas emissions inventory for biosolids.
Alvarez-Gaitan, J P; Short, Michael D; Lundie, Sven; Stuetz, Richard
2016-06-01
Effective handling and treatment of the solids fraction from advanced wastewater treatment operations carries a substantial burden for water utilities relative to the total economic and environmental impacts from modern day wastewater treatment. While good process-level data for a range of wastewater treatment operations are becoming more readily available, there remains a dearth of high quality operational data for solids line processes in particular. This study seeks to address this data gap by presenting a suite of high quality, process-level life cycle inventory data covering a range of solids line wastewater treatment processes, extending from primary treatment through to biosolids reuse in agriculture. Within the study, the impacts of secondary treatment technology and key parameters such as sludge retention time, activated sludge age and primary-to-waste activated sludge ratio (PS:WAS) on the life cycle inventory data of solids processing trains for five model wastewater treatment plant configurations are presented. BioWin(®) models are calibrated with real operational plant data and estimated electricity consumption values were reconciled against overall plant energy consumption. The concept of "representative crop" is also introduced in order to reduce the uncertainty associated with nitrous oxide emissions and soil carbon sequestration offsets under biosolids land application scenarios. Results indicate that both the treatment plant biogas electricity offset and the soil carbon sequestration offset from land-applied biosolids, represent the main greenhouse gas mitigation opportunities. In contrast, fertiliser offsets are of relatively minor importance in terms of the overall life cycle emissions impacts. Results also show that fugitive methane emissions at the plant, as well as nitrous oxide emissions both at the plant and following agricultural application of biosolids, are significant contributors to the overall greenhouse gas balance and combined are higher than emissions associated with transportation. Sensitivity analyses for key parameters including digester PS:WAS and sludge retention time, and assumed biosolids nitrogen content and agricultural availability also provide additional robustness and comprehensiveness to our inventory data and will facilitate more customised user analyses. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Integrated control system for electron beam processes
NASA Astrophysics Data System (ADS)
Koleva, L.; Koleva, E.; Batchkova, I.; Mladenov, G.
2018-03-01
The ISO/IEC 62264 standard is widely used for integration of the business systems of a manufacturer with the corresponding manufacturing control systems based on hierarchical equipment models, functional data and manufacturing operations activity models. In order to achieve the integration of control systems, formal object communication models must be developed, together with manufacturing operations activity models, which coordinate the integration between different levels of control. In this article, the development of integrated control system for electron beam welding process is presented as part of a fully integrated control system of an electron beam plant, including also other additional processes: surface modification, electron beam evaporation, selective melting and electron beam diagnostics.
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Arnell, Magnus; Astals, Sergi; Åmand, Linda; Batstone, Damien J; Jensen, Paul D; Jeppsson, Ulf
2016-07-01
Anaerobic co-digestion is an emerging practice at wastewater treatment plants (WWTPs) to improve the energy balance and integrate waste management. Modelling of co-digestion in a plant-wide WWTP model is a powerful tool to assess the impact of co-substrate selection and dose strategy on digester performance and plant-wide effects. A feasible procedure to characterise and fractionate co-substrates COD for the Benchmark Simulation Model No. 2 (BSM2) was developed. This procedure is also applicable for the Anaerobic Digestion Model No. 1 (ADM1). Long chain fatty acid inhibition was included in the ADM1 model to allow for realistic modelling of lipid rich co-substrates. Sensitivity analysis revealed that, apart from the biodegradable fraction of COD, protein and lipid fractions are the most important fractions for methane production and digester stability, with at least two major failure modes identified through principal component analysis (PCA). The model and procedure were tested on bio-methane potential (BMP) tests on three substrates, each rich on carbohydrates, proteins or lipids with good predictive capability in all three cases. This model was then applied to a plant-wide simulation study which confirmed the positive effects of co-digestion on methane production and total operational cost. Simulations also revealed the importance of limiting the protein load to the anaerobic digester to avoid ammonia inhibition in the digester and overloading of the nitrogen removal processes in the water train. In contrast, the digester can treat relatively high loads of lipid rich substrates without prolonged disturbances. Copyright © 2016 Elsevier Ltd. All rights reserved.
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USDA-ARS?s Scientific Manuscript database
A plant trial was conducted at a 54 MGPY dry grind fuel ethanol facility to evaluate the use of enhanced water removal from whole stillage by enzyme addition during fermentation. Laboratory data had previously shown significant improvements in water removal that could potentially result in significa...
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Building Leaves and an Understanding of Photosynthesis
ERIC Educational Resources Information Center
Littlejohn, Patty
2007-01-01
Where does cellular respiration take place? How does a plant make food and in turn use the food to produce its own energy? Do animals carry on this process also? To help students answer these and other questions, have them build a model leaf, plant cell, and animal cell. This hands-on project allows students to see and manipulate the reactants and…
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Viaud, Gautier; Loudet, Olivier; Cournède, Paul-Henry
2017-01-01
A promising method for characterizing the phenotype of a plant as an interaction between its genotype and its environment is to use refined organ-scale plant growth models that use the observation of architectural traits, such as leaf area, containing a lot of information on the whole history of the functioning of the plant. The Phenoscope, a high-throughput automated platform, allowed the acquisition of zenithal images of Arabidopsis thaliana over twenty one days for 4 different genotypes. A novel image processing algorithm involving both segmentation and tracking of the plant leaves allows to extract areas of the latter. First, all the images in the series are segmented independently using a watershed-based approach. A second step based on ellipsoid-shaped leaves is then applied on the segments found to refine the segmentation. Taking into account all the segments at every time, the whole history of each leaf is reconstructed by choosing recursively through time the most probable segment achieving the best score, computed using some characteristics of the segment such as its orientation, its distance to the plant mass center and its area. These results are compared to manually extracted segments, showing a very good accordance in leaf rank and that they therefore provide low-biased data in large quantity for leaf areas. Such data can therefore be exploited to design an organ-scale plant model adapted from the existing GreenLab model for A. thaliana and subsequently parameterize it. This calibration of the model parameters should pave the way for differentiation between the Arabidopsis genotypes. PMID:28123392
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Meng, Jun; Liu, Dong; Sun, Chao; Luan, Yushi
2014-12-30
MicroRNAs (miRNAs) are a family of non-coding RNAs approximately 21 nucleotides in length that play pivotal roles at the post-transcriptional level in animals, plants and viruses. These molecules silence their target genes by degrading transcription or suppressing translation. Studies have shown that miRNAs are involved in biological responses to a variety of biotic and abiotic stresses. Identification of these molecules and their targets can aid the understanding of regulatory processes. Recently, prediction methods based on machine learning have been widely used for miRNA prediction. However, most of these methods were designed for mammalian miRNA prediction, and few are available for predicting miRNAs in the pre-miRNAs of specific plant species. Although the complete Solanum lycopersicum genome has been published, only 77 Solanum lycopersicum miRNAs have been identified, far less than the estimated number. Therefore, it is essential to develop a prediction method based on machine learning to identify new plant miRNAs. A novel classification model based on a support vector machine (SVM) was trained to identify real and pseudo plant pre-miRNAs together with their miRNAs. An initial set of 152 novel features related to sequential structures was used to train the model. By applying feature selection, we obtained the best subset of 47 features for use with the Back Support Vector Machine-Recursive Feature Elimination (B-SVM-RFE) method for the classification of plant pre-miRNAs. Using this method, 63 features were obtained for plant miRNA classification. We then developed an integrated classification model, miPlantPreMat, which comprises MiPlantPre and MiPlantMat, to identify plant pre-miRNAs and their miRNAs. This model achieved approximately 90% accuracy using plant datasets from nine plant species, including Arabidopsis thaliana, Glycine max, Oryza sativa, Physcomitrella patens, Medicago truncatula, Sorghum bicolor, Arabidopsis lyrata, Zea mays and Solanum lycopersicum. Using miPlantPreMat, 522 Solanum lycopersicum miRNAs were identified in the Solanum lycopersicum genome sequence. We developed an integrated classification model, miPlantPreMat, based on structure-sequence features and SVM. MiPlantPreMat was used to identify both plant pre-miRNAs and the corresponding mature miRNAs. An improved feature selection method was proposed, resulting in high classification accuracy, sensitivity and specificity.
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NASA Astrophysics Data System (ADS)
West, J. B.; Ehleringer, J. R.; Cerling, T.
2006-12-01
Understanding how the biosphere responds to change it at the heart of biogeochemistry, ecology, and other Earth sciences. The dramatic increase in human population and technological capacity over the past 200 years or so has resulted in numerous, simultaneous changes to biosphere structure and function. This, then, has lead to increased urgency in the scientific community to try to understand how systems have already responded to these changes, and how they might do so in the future. Since all biospheric processes exhibit some patchiness or patterns over space, as well as time, we believe that understanding the dynamic interactions between natural systems and human technological manipulations can be improved if these systems are studied in an explicitly spatial context. We present here results of some of our efforts to model the spatial variation in the stable isotope ratios (δ2H and δ18O) of plants over large spatial extents, and how these spatial model predictions compare to spatially explicit data. Stable isotopes trace and record ecological processes and as such, if modeled correctly over Earth's surface allow us insights into changes in biosphere states and processes across spatial scales. The data-model comparisons show good agreement, in spite of the remaining uncertainties (e.g., plant source water isotopic composition). For example, inter-annual changes in climate are recorded in wine stable isotope ratios. Also, a much simpler model of leaf water enrichment driven with spatially continuous global rasters of precipitation and climate normals largely agrees with complex GCM modeling that includes leaf water δ18O. Our results suggest that modeling plant stable isotope ratios across large spatial extents may be done with reasonable accuracy, including over time. These spatial maps, or isoscapes, can now be utilized to help understand spatially distributed data, as well as to help guide future studies designed to understand ecological change across landscapes.
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Ecological and evolutionary consequences of niche construction for its agent.
Kylafis, Grigoris; Loreau, Michel
2008-10-01
Niche construction can generate ecological and evolutionary feedbacks that have been underinvestigated so far. We present an eco-evolutionary model that incorporates the process of niche construction to reveal its effects on the ecology and evolution of the niche-constructing agent. We consider a simple plant-soil nutrient ecosystem in which plants have the ability to increase the input of inorganic nutrient as an example of positive niche construction. On an ecological time scale, the model shows that niche construction allows the persistence of plants under infertile soil conditions that would otherwise lead to their extinction. This expansion of plants' niche, however, requires a high enough rate of niche construction and a high enough initial plant biomass to fuel the positive ecological feedback between plants and their soil environment. On an evolutionary time scale, we consider that the rates of niche construction and nutrient uptake coevolve in plants while a trade-off constrains their values. Different evolutionary outcomes are possible depending on the shape of the trade-off. We show that niche construction results in an evolutionary feedback between plants and their soil environment such that plants partially regulate soil nutrient content. The direct benefit accruing to plants, however, plays a crucial role in the evolutionary advantage of niche construction.