Integration of Dynamic Models in Range Operations
NASA Technical Reports Server (NTRS)
Bardina, Jorge; Thirumalainambi, Rajkumar
2004-01-01
This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.
Dynamical many-body localization in an integrable model
NASA Astrophysics Data System (ADS)
Keser, Aydin Cem; Ganeshan, Sriram; Refael, Gil; Galitski, Victor
2016-08-01
We investigate dynamical many-body localization and delocalization in an integrable system of periodically-kicked, interacting linear rotors. The linear-in-momentum Hamiltonian makes the Floquet evolution operator analytically tractable for arbitrary interactions. One of the hallmarks of this model is that depending on certain parameters, it manifests both localization and delocalization in momentum space. We present a set of "emergent" integrals of motion, which can serve as a fundamental diagnostic of dynamical localization in the interacting case. We also propose an experimental scheme, involving voltage-biased Josephson junctions, to realize such many-body kicked models.
Integrative Analysis of Metabolic Models – from Structure to Dynamics
Hartmann, Anja; Schreiber, Falk
2015-01-01
The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the context of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM2 – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato. PMID:25674560
Integrating microbial diversity in soil carbon dynamic models parameters
NASA Astrophysics Data System (ADS)
Louis, Benjamin; Menasseri-Aubry, Safya; Leterme, Philippe; Maron, Pierre-Alain; Viaud, Valérie
2015-04-01
Faced with the numerous concerns about soil carbon dynamic, a large quantity of carbon dynamic models has been developed during the last century. These models are mainly in the form of deterministic compartment models with carbon fluxes between compartments represented by ordinary differential equations. Nowadays, lots of them consider the microbial biomass as a compartment of the soil organic matter (carbon quantity). But the amount of microbial carbon is rarely used in the differential equations of the models as a limiting factor. Additionally, microbial diversity and community composition are mostly missing, although last advances in soil microbial analytical methods during the two past decades have shown that these characteristics play also a significant role in soil carbon dynamic. As soil microorganisms are essential drivers of soil carbon dynamic, the question about explicitly integrating their role have become a key issue in soil carbon dynamic models development. Some interesting attempts can be found and are dominated by the incorporation of several compartments of different groups of microbial biomass in terms of functional traits and/or biogeochemical compositions to integrate microbial diversity. However, these models are basically heuristic models in the sense that they are used to test hypotheses through simulations. They have rarely been confronted to real data and thus cannot be used to predict realistic situations. The objective of this work was to empirically integrate microbial diversity in a simple model of carbon dynamic through statistical modelling of the model parameters. This work is based on available experimental results coming from a French National Research Agency program called DIMIMOS. Briefly, 13C-labelled wheat residue has been incorporated into soils with different pedological characteristics and land use history. Then, the soils have been incubated during 104 days and labelled and non-labelled CO2 fluxes have been measured at ten
Human growth and body weight dynamics: an integrative systems model.
Rahmandad, Hazhir
2014-01-01
Quantifying human weight and height dynamics due to growth, aging, and energy balance can inform clinical practice and policy analysis. This paper presents the first mechanism-based model spanning full individual life and capturing changes in body weight, composition and height. Integrating previous empirical and modeling findings and validated against several additional empirical studies, the model replicates key trends in human growth including A) Changes in energy requirements from birth to old ages. B) Short and long-term dynamics of body weight and composition. C) Stunted growth with chronic malnutrition and potential for catch up growth. From obesity policy analysis to treating malnutrition and tracking growth trajectories, the model can address diverse policy questions. For example I find that even without further rise in obesity, the gap between healthy and actual Body Mass Indexes (BMIs) has embedded, for different population groups, a surplus of 14%-24% in energy intake which will be a source of significant inertia in obesity trends. In another analysis, energy deficit percentage needed to reduce BMI by one unit is found to be relatively constant across ages. Accompanying documented and freely available simulation model facilitates diverse applications customized to different sub-populations.
Integrated Turbine-Based Combined Cycle Dynamic Simulation Model
NASA Technical Reports Server (NTRS)
Haid, Daniel A.; Gamble, Eric J.
2011-01-01
A Turbine-Based Combined Cycle (TBCC) dynamic simulation model has been developed to demonstrate all modes of operation, including mode transition, for a turbine-based combined cycle propulsion system. The High Mach Transient Engine Cycle Code (HiTECC) is a highly integrated tool comprised of modules for modeling each of the TBCC systems whose interactions and controllability affect the TBCC propulsion system thrust and operability during its modes of operation. By structuring the simulation modeling tools around the major TBCC functional modes of operation (Dry Turbojet, Afterburning Turbojet, Transition, and Dual Mode Scramjet) the TBCC mode transition and all necessary intermediate events over its entire mission may be developed, modeled, and validated. The reported work details the use of the completed model to simulate a TBCC propulsion system as it accelerates from Mach 2.5, through mode transition, to Mach 7. The completion of this model and its subsequent use to simulate TBCC mode transition significantly extends the state-of-the-art for all TBCC modes of operation by providing a numerical simulation of the systems, interactions, and transient responses affecting the ability of the propulsion system to transition from turbine-based to ramjet/scramjet-based propulsion while maintaining constant thrust.
Architecture for Integrated Medical Model Dynamic Probabilistic Risk Assessment
NASA Technical Reports Server (NTRS)
Jaworske, D. A.; Myers, J. G.; Goodenow, D.; Young, M.; Arellano, J. D.
2016-01-01
Probabilistic Risk Assessment (PRA) is a modeling tool used to predict potential outcomes of a complex system based on a statistical understanding of many initiating events. Utilizing a Monte Carlo method, thousands of instances of the model are considered and outcomes are collected. PRA is considered static, utilizing probabilities alone to calculate outcomes. Dynamic Probabilistic Risk Assessment (dPRA) is an advanced concept where modeling predicts the outcomes of a complex system based not only on the probabilities of many initiating events, but also on a progression of dependencies brought about by progressing down a time line. Events are placed in a single time line, adding each event to a queue, as managed by a planner. Progression down the time line is guided by rules, as managed by a scheduler. The recently developed Integrated Medical Model (IMM) summarizes astronaut health as governed by the probabilities of medical events and mitigation strategies. Managing the software architecture process provides a systematic means of creating, documenting, and communicating a software design early in the development process. The software architecture process begins with establishing requirements and the design is then derived from the requirements.
Integrated dynamic landscape analysis and modeling system (IDLAMS) : programmer's manual.
Klaus, C. M.; Li, Z.; Majerus, K. A.; Sundell, R. C.; Sydelko, P. J.; Vogt, M. C.
1999-02-24
The Integrated Dynamic Landscape Analysis and Modeling System (IDLAMS) is a prototype, integrated land management technology developed through a joint effort between Argonne National Laboratory (ANL) and the US Army Corps of Engineers Construction Engineering Research Laboratories (USACERL). Dr. Ronald C. Sundell, Ms. Pamela J. Sydelko, and Ms. Kimberly A. Majerus were the principal investigators (PIs) for this project. Dr. Zhian Li was the primary software developer. Dr. Jeffrey M. Keisler, Mr. Christopher M. Klaus, and Mr. Michael C. Vogt developed the decision analysis component of this project. It was developed with funding support from the Strategic Environmental Research and Development Program (SERDP), a land/environmental stewardship research program with participation from the US Department of Defense (DoD), the US Department of Energy (DOE), and the US Environmental Protection Agency (EPA). IDLAMS predicts land conditions (e.g., vegetation, wildlife habitats, and erosion status) by simulating changes in military land ecosystems for given training intensities and land management practices. It can be used by military land managers to help predict the future ecological condition for a given land use based on land management scenarios of various levels of training intensity. It also can be used as a tool to help land managers compare different land management practices and further determine a set of land management activities and prescriptions that best suit the needs of a specific military installation.
Integrated dynamic landscape analysis and modeling system (IDLAMS) : installation manual.
Li, Z.; Majerus, K. A.; Sundell, R. C.; Sydelko, P. J.; Vogt, M. C.
1999-02-24
The Integrated Dynamic Landscape Analysis and Modeling System (IDLAMS) is a prototype, integrated land management technology developed through a joint effort between Argonne National Laboratory (ANL) and the US Army Corps of Engineers Construction Engineering Research Laboratories (USACERL). Dr. Ronald C. Sundell, Ms. Pamela J. Sydelko, and Ms. Kimberly A. Majerus were the principal investigators (PIs) for this project. Dr. Zhian Li was the primary software developer. Dr. Jeffrey M. Keisler, Mr. Christopher M. Klaus, and Mr. Michael C. Vogt developed the decision analysis component of this project. It was developed with funding support from the Strategic Environmental Research and Development Program (SERDP), a land/environmental stewardship research program with participation from the US Department of Defense (DoD), the US Department of Energy (DOE), and the US Environmental Protection Agency (EPA). IDLAMS predicts land conditions (e.g., vegetation, wildlife habitats, and erosion status) by simulating changes in military land ecosystems for given training intensities and land management practices. It can be used by military land managers to help predict the future ecological condition for a given land use based on land management scenarios of various levels of training intensity. It also can be used as a tool to help land managers compare different land management practices and further determine a set of land management activities and prescriptions that best suit the needs of a specific military installation.
NASA Astrophysics Data System (ADS)
Hoy, Jerad; Poulter, Benjamin; Emmett, Kristen; Cross, Molly; Al-Chokhachy, Robert; Maneta, Marco
2016-04-01
Integrated terrestrial ecosystem models simulate the dynamics and feedbacks between climate, vegetation, disturbance, and hydrology and are used to better understand biogeography and biogeochemical cycles. Extending dynamic vegetation models to the aquatic interface requires coupling surface and sub-surface runoff to catchment routing schemes and has the potential to enhance how researchers and managers investigate how changes in the environment might impact the availability of water resources for human and natural systems. In an effort towards creating such a coupled model, we developed catchment-based hydrologic routing and stream temperature model to pair with LPJ-GUESS, a dynamic global vegetation model. LPJ-GUESS simulates detailed stand-level vegetation dynamics such as growth, carbon allocation, and mortality, as well as various physical and hydrologic processes such as canopy interception and through-fall, and can be applied at small spatial scales, i.e., 1 km. We demonstrate how the coupled model can be used to investigate the effects of transient vegetation dynamics and CO2 on seasonal and annual stream discharge and temperature regimes. As a direct management application, we extend the modeling framework to predict habitat suitability for fish habitat within the Greater Yellowstone Ecosystem, a 200,000 km2 region that provides critical habitat for a range of aquatic species. The model is used to evaluate, quantitatively, the effects of management practices aimed to enhance hydrologic resilience to climate change, and benefits for water storage and fish habitat in the coming century.
Integration of nitrogen dynamics into a global terrestrial ecosystem model
Yang, Xiaojuan; Wittig, Victoria; Jain, Atul; Post, Wilfred M
2009-01-01
A comprehensive model of terrestrial N dynamics has been developed and coupled with the geographically explicit terrestrial C cycle component of the Integrated Science Assessment Model (ISAM). The coupled C-N cycle model represents all the major processes in the N cycle and all major interactions between C and N that affect plant productivity and soil and litter decomposition. Observations from the LIDET data set were compiled for calibration and evaluation of the decomposition submodel within ISAM. For aboveground decomposition, the calibration is accomplished by optimizing parameters related to four processes: the partitioning of leaf litter between metabolic and structural material, the effect of lignin on decomposition, the climate control on decomposition and N mineralization and immobilization. For belowground decomposition, the calibrated processes include the partitioning of root litter between decomposable and resistant material as a function of litter quality, N mineralization and immobilization. The calibrated model successfully captured both the C and N dynamics during decomposition for all major biomes and a wide range of climate conditions. Model results show that net N immobilization and mineralization during litter decomposition are dominantly controlled by initial N concentration of litter and the mass remaining during decomposition. The highest and lowest soil organicNstorage are in tundra (1.24 KgNm2) and desert soil (0.06 Kg N m2). The vegetation N storage is highest in tropical forests (0.5 Kg N m2), and lowest in tundra and desert (<0.03 Kg N m2). N uptake by vegetation is highest in warm and moist regions, and lowest in cold and dry regions. Higher rates of N leaching are found in tropical regions and subtropical regions where soil moisture is higher. The global patterns of vegetation and soil N, N uptake and N leaching estimated with ISAM are consistent with measurements and previous modeling studies. This gives us confidence that ISAM
NASA Technical Reports Server (NTRS)
Connolly, Joseph W.; Friedlander, David; Kopasakis, George
2015-01-01
This paper covers the development of an integrated nonlinear dynamic simulation for a variable cycle turbofan engine and nozzle that can be integrated with an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. A previously developed variable cycle turbofan engine model is used for this study and is enhanced here to include variable guide vanes allowing for operation across the supersonic flight regime. The primary focus of this study is to improve the fidelity of the model's thrust response by replacing the simple choked flow equation convergent-divergent nozzle model with a MacCormack method based quasi-1D model. The dynamic response of the nozzle model using the MacCormack method is verified by comparing it against a model of the nozzle using the conservation element/solution element method. A methodology is also presented for the integration of the MacCormack nozzle model with the variable cycle engine.
NASA Technical Reports Server (NTRS)
Connolly, Joseph W.; Friedlander, David; Kopasakis, George
2014-01-01
This paper covers the development of an integrated nonlinear dynamic simulation for a variable cycle turbofan engine and nozzle that can be integrated with an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. A previously developed variable cycle turbofan engine model is used for this study and is enhanced here to include variable guide vanes allowing for operation across the supersonic flight regime. The primary focus of this study is to improve the fidelity of the model's thrust response by replacing the simple choked flow equation convergent-divergent nozzle model with a MacCormack method based quasi-1D model. The dynamic response of the nozzle model using the MacCormack method is verified by comparing it against a model of the nozzle using the conservation element/solution element method. A methodology is also presented for the integration of the MacCormack nozzle model with the variable cycle engine.
Integration of biomass data in the dynamic vegetation model ORCHIDEE
NASA Astrophysics Data System (ADS)
Delbart, N.; Viovy, N.; Ciais, P.; Le Toan, T.
2009-04-01
Dynamic vegetation models (DVMs) are aimed at estimating exchanges between the terrestrial vegetated surface and the atmosphere, and the spatial distribution of natural vegetation types. For this purpose, DVMs use the climatic data alone to feed the vegetation process equations. As dynamic models, they can also give predictions under the current and the future climatic conditions. However, they currently lack accuracy in locating carbon stocks, sinks and sources, and in getting the correct magnitude. Consequently they have been essentially used to compare the vegetation responses under different scenarii. The assimilation of external data such as remote sensing data has been shown to improve the simulations. For example, the land cover maps are used to force the correct distribution of plant functional types (PFTs), and the leaf area index data is used to force the photosynthesis processes. This study concerns the integration of biomass data within the DVM ORCHIDEE. The objective here is to have the living carbon stocks with the correct magnitude and the correct location. Carbon stocks depend on interplay of carbon assimilated by photosynthesis, and carbon lost by respiration, mortality and disturbance. Biomass data can therefore be used as one essential constraint on this interplay. In this study, we use a large database provided by in-situ measurements of carbon stocks and carbon fluxes of old growth forests to constraint this interplay. For each PFT, we first adjust the simulated photosynthesis by reducing the mean error with the in situ measurements. Then we proceed similarly to adjust the autotrophic respiration. We then compare the biomass measured, and adjust the mortality processes in the model. Second, when processes are adjusted for each PFT to minimize the mean error on the carbon stock, biomass measurements can be assimilated. This assimilation is based on the hypothesis that the main variable explaining the biomass level at a given location is the age
Dynamic Coupling of Alaska Based Ecosystem and Geophysical Models into an Integrated Model
NASA Astrophysics Data System (ADS)
Bennett, A.; Carman, T. B.
2012-12-01
As scientific models and the challenges they address have grown in complexity and scope, so has interest in dynamically coupling or integrating these models. Dynamic model coupling presents software engineering challenges stemming from differences in model architectures, differences in development styles between modeling groups, and memory and run time performance concerns. The Alaska Integrated Ecosystem Modeling (AIEM) project aims to dynamically couple three independently developed scientific models so that each model can exchange run-time data with each of the other models. The models being coupled are a stochastic fire dynamics model (ALFRESCO), a permafrost model (GIPL), and a soil and vegetation model (DVM-DOS-TEM). The scientific research objectives of the AIEM project are to: 1) use the coupled models for increasing our understanding of climate change and other stressors on landscape level physical and ecosystem processes, and; 2) provide support for resource conservation planning and decision making. The objectives related to the computer models themselves are modifiability, maintainability, and performance of the coupled and individual models. Modifiability and maintainability are especially important in a research context because source codes must be continually adapted to address new scientific concepts. Performance is crucial to delivering results in a timely manner. To achieve the objectives while addressing the challenges in dynamic model coupling, we have designed an architecture that emphasizes high cohesion for each individual model and loose coupling between the models. Each model will retain the ability to run independently, or to be available as a linked library to the coupled model. Performance is facilitated by parallelism in the spatial dimension. With close collaboration among modeling groups, the methodology described here has demonstrated the feasibility of coupling complex ecological and geophysical models to provide managers with more
Efficient Fully Implicit Time Integration Methods for Modeling Cardiac Dynamics
Rose, Donald J.; Henriquez, Craig S.
2013-01-01
Implicit methods are well known to have greater stability than explicit methods for stiff systems, but they often are not used in practice due to perceived computational complexity. This paper applies the Backward Euler method and a second-order one-step two-stage composite backward differentiation formula (C-BDF2) for the monodomain equations arising from mathematically modeling the electrical activity of the heart. The C-BDF2 scheme is an L-stable implicit time integration method and easily implementable. It uses the simplest Forward Euler and Backward Euler methods as fundamental building blocks. The nonlinear system resulting from application of the Backward Euler method for the monodomain equations is solved for the first time by a nonlinear elimination method, which eliminates local and non-symmetric components by using a Jacobian-free Newton solver, called Newton-Krylov solver. Unlike other fully implicit methods proposed for the monodomain equations in the literature, the Jacobian of the global system after the nonlinear elimination has much smaller size, is symmetric and possibly positive definite, which can be solved efficiently by standard optimal solvers. Numerical results are presented demonstrating that the C-BDF2 scheme can yield accurate results with less CPU times than explicit methods for both a single patch and spatially extended domains. PMID:19126449
Modelling the dynamics of motion integration with a new luminance-gated diffusion mechanism.
Tlapale, Emilien; Masson, Guillaume S; Kornprobst, Pierre
2010-08-01
The dynamics of motion integration show striking similarities when observed at neuronal, psychophysical, and oculomotor levels. Based on the inter-relation and complementary insights given by those dynamics, our goal was to test how basic mechanisms of dynamical cortical processing can be incorporated in a dynamical model to solve several aspects of 2D motion integration and segmentation. Our model is inspired by the hierarchical processing stages of the primate visual cortex: we describe the interactions between several layers processing local motion and form information through feedforward, feedback, and inhibitive lateral connections. Also, following perceptual studies concerning contour integration and physiological studies of receptive fields, we postulate that motion estimation takes advantage of another low-level cue, which is luminance smoothness along edges or surfaces, in order to gate recurrent motion diffusion. With such a model, we successfully reproduced the temporal dynamics of motion integration on a wide range of simple motion stimuli: line segments, rotating ellipses, plaids, and barber poles. Furthermore, we showed that the proposed computational rule of luminance-gated diffusion of motion information is sufficient to explain a large set of contextual modulations of motion integration and segmentation in more elaborated stimuli such as chopstick illusions, simulated aperture problems, or rotating diamonds. As a whole, in this paper we proposed a new basal luminance-driven motion integration mechanism as an alternative to less parsimonious models, we carefully investigated the dynamics of motion integration, and we established a distinction between simple and complex stimuli according to the kind of information required to solve their ambiguities.
Inclusion of Vertical Dynamics in Vertically-integrated Models for CO2 Storage
NASA Astrophysics Data System (ADS)
Guo, B.; Bandilla, K.; Celia, M. A.
2012-12-01
Mathematical models of different complexity are needed to answer a range of questions for geological sequestration of carbon dioxide (CO2). One category of simplified models is based on vertical integration, which reduces the three-dimensional problem to two dimensions. Usually, these models assume that brine and CO2 are in vertical equilibrium. This type of model is useful and accurate for simulation times that are large relative to the time for buoyant segregation. But, vertical-equilibrium models are inappropriate in some situations, for instance, in the early stage of injection, when brine and CO2 have not fully segregated. Therefore, for these situations, the vertical equilibrium assumption needs to be relaxed and vertical dynamics needs to be included in the governing equations. To avoid significant increases of computational effort due to the inclusion of vertical dynamics, a multi-scale algorithm can be constructed where the vertically integrated equations are still used to model the (dominant) horizontal flow processes with the vertical reconstruction included as a dynamic problem. Such an approach allows each vertical column of grid cells to be solved independently, as a one-dimensional problem, during the dynamic reconstruction step. Because the top and bottom boundaries usually correspond to impermeable caprock, the total flow for these one-dimensional problems is zero and counter-current flow driven only by buoyancy and capillarity is involved. Solutions for this kind of problem are relatively simple and require little computational effort. With careful coupling between the vertical calculations and the horizontally integrated equations, an efficient algorithm can be developed to simulate a fairly wide range of problems including those with significant vertical dynamics. When vertical dynamics become insignificant, then usual vertical equilibrium reconstruction is used in the vertically integrated models. This new algorithm provides an intermediate
Maeda, Kazuhiro; Fukano, Yuya; Yamamichi, Shunsuke; Nitta, Daichi; Kurata, Hiroyuki
2011-05-01
Computer simulation is an important technique to capture the dynamics of biochemical networks. Numerical optimization is the key to estimate the values of kinetic parameters so that the dynamic model reproduces the behaviors of the existing experimental data. It is required to develop general strategies for the optimization of complex biochemical networks with a huge space of search parameters, under the condition that kinetic and quantitative data are hardly available. We propose an integrative and practical strategy for optimizing a complex dynamic model by using qualitative and incomplete experimental data. The key technologies are the divide and conquer method for reducing the search space, handling of multiple objective functions representing different types of biological behaviors, and design of rule-based objective functions that are suitable for qualitative and error-prone experimental data. This strategy is applied to optimizing a dynamic model of the yeast cell cycle to demonstrate the feasibility of it.
NASA Astrophysics Data System (ADS)
Becker, S.; Losch, M.; Brockmann, J. M.; Freiwald, G.; Schuh, W.-D.
2014-11-01
Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography—the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99-110, 2012; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie 2012). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the
The Integrated Storage-Flux Model For Groundwater Storage and Baseflow Dynamics
NASA Astrophysics Data System (ADS)
Lee, D.; Lee, J.
2002-12-01
The integrated storage-flux model is proposed based on the storage-flux relations and tested against the Richards equation in the idealized stream-aquifer system. The groundwater storage-baseflow relation and soil water storage-effective infiltration relation are identified by numerical analysis of the Richards equation under the steady-state conditions. The relationship between groundwater and baseflow exhibits a linear relation, while the relationship between soil water storage and effective rainfall is appeared to be the inverse linear relation. This inverse linear relation agrees with the results of Duffy (1996) and Lee (1993) who investigated the storage-flux relations on the hillslope terrain. The integrated storage-flux model is constructed by coupling the storage-flux relation with water balance equation. The coefficients of the integrated storage-flux model are based on the steady-state storage-flux relations and are calibrated against the response of the Richards equation. Under the step input condition, the dynamic response of the integrated storage-flux model agrees favorably with that of Richards equation. The development of the integrated storage-flux model has implication for predicting the groundwater storage and baseflow when the limited hydro-geologic data are available. Acknowledgement This research was supported by a grant (2-2-1) from Sustainable Water Resources Research Center of 21st Century Frontier Research Program.
HepatoDyn: A Dynamic Model of Hepatocyte Metabolism That Integrates 13C Isotopomer Data
Foguet, Carles; Selivanov, Vitaly A.; Fanchon, Eric; Guinovart, Joan J.; de Atauri, Pedro; Cascante, Marta
2016-01-01
The liver performs many essential metabolic functions, which can be studied using computational models of hepatocytes. Here we present HepatoDyn, a highly detailed dynamic model of hepatocyte metabolism. HepatoDyn includes a large metabolic network, highly detailed kinetic laws, and is capable of dynamically simulating the redox and energy metabolism of hepatocytes. Furthermore, the model was coupled to the module for isotopic label propagation of the software package IsoDyn, allowing HepatoDyn to integrate data derived from 13C based experiments. As an example of dynamical simulations applied to hepatocytes, we studied the effects of high fructose concentrations on hepatocyte metabolism by integrating data from experiments in which rat hepatocytes were incubated with 20 mM glucose supplemented with either 3 mM or 20 mM fructose. These experiments showed that glycogen accumulation was significantly lower in hepatocytes incubated with medium supplemented with 20 mM fructose than in hepatocytes incubated with medium supplemented with 3 mM fructose. Through the integration of extracellular fluxes and 13C enrichment measurements, HepatoDyn predicted that this phenomenon can be attributed to a depletion of cytosolic ATP and phosphate induced by high fructose concentrations in the medium. PMID:27124774
Application-Oriented Confidentiality and Integrity Dynamic Union Security Model Based on MLS Policy
NASA Astrophysics Data System (ADS)
Xue, Mingfu; Hu, Aiqun; He, Chunlong
We propose a new security model based on MLS Policy to achieve a better security performance on confidentiality, integrity and availability. First, it realizes a combination of BLP model and Biba model through a two-dimensional independent adjustment of integrity and confidentiality. And, the subject's access range is adjusted dynamically according to the security label of related objects and the subject's access history. Second, the security level of the trusted subject is extended to writing and reading privilege range respectively, following the principle of least privilege. Third, it adjusts the objects' security levels after adding confidential information to prevent the information disclosure. Fourth, it uses application-oriented logic to protect specific applications to avoid the degradation of security levels. Thus, it can ensure certain applications operate smoothly. Lastly, examples are presented to show the effectiveness and usability of the proposed model.
NASA Astrophysics Data System (ADS)
Case, M. J.; Kim, J. B.
2015-12-01
Assessing changes in vegetation is increasingly important for conservation planning in the face of climate change. Dynamic global vegetation models (DGVMs) are important tools for assessing such changes. DGVMs have been applied at regional scales to create projections of range expansions and contractions of plant functional types. Many DGVMs use a number of algorithms to determine the biogeography of plant functional types. One such DGVM, MC2, uses a series of decision trees based on bioclimatic thresholds while others, such as LPJ, use constraining emergent properties with a limited set of bioclimatic threshold-based rules. Although both approaches have been used widely, we demonstrate that these biogeography outputs perform poorly at continental scales when compared to existing potential vegetation maps. Specifically, we found that with MC2, the algorithm for determining leaf physiognomy is too simplistic to capture arid and semi-arid vegetation in much of the western U.S., as well as is the algorithm for determining the broadleaf and needleleaf mix in the Southeast. With LPJ, we found that the bioclimatic thresholds used to allow seedling establishment are too broad and fail to capture regional-scale biogeography of the plant functional types. In response, we demonstrate a new approach to determining the biogeography of plant functional types by integrating the climatic thresholds produced for individual tree species by a series of climate envelope models with the biogeography algorithms of MC2 and LPJ. Using this approach, we find that MC2 and LPJ perform considerably better when compared to potential vegetation maps.
Zheng, Liying; Li, Kang; Shetye, Snehal; Zhang, Xudong
2014-09-22
This manuscript presents a new subject-specific musculoskeletal dynamic modeling approach that integrates high-accuracy dynamic stereo-radiography (DSX) joint kinematics and surface-based full-body motion data. We illustrate this approach by building a model in OpenSim for a patient who participated in a meniscus transplantation efficacy study, incorporating DSX data of the tibiofemoral joint kinematics. We compared this DSX-incorporated (DSXI) model to a default OpenSim model built using surface-measured data alone. The architectures and parameters of the two models were identical, while the differences in (time-averaged) tibiofemoral kinematics were of the order of magnitude of 10° in rotation and 10mm in translation. Model-predicted tibiofemoral compressive forces and knee muscle activations were compared against literature data acquired from instrumented total knee replacement components (Fregly et al., 2012) and the patient's EMG recording. The comparison demonstrated that the incorporation of DSX data improves the veracity of musculoskeletal dynamic modeling.
Integrated earth system dynamic modeling for life cycle impact assessment of ecosystem services.
Arbault, Damien; Rivière, Mylène; Rugani, Benedetto; Benetto, Enrico; Tiruta-Barna, Ligia
2014-02-15
Despite the increasing awareness of our dependence on Ecosystem Services (ES), Life Cycle Impact Assessment (LCIA) does not explicitly and fully assess the damages caused by human activities on ES generation. Recent improvements in LCIA focus on specific cause-effect chains, mainly related to land use changes, leading to Characterization Factors (CFs) at the midpoint assessment level. However, despite the complexity and temporal dynamics of ES, current LCIA approaches consider the environmental mechanisms underneath ES to be independent from each other and devoid of dynamic character, leading to constant CFs whose representativeness is debatable. This paper takes a step forward and is aimed at demonstrating the feasibility of using an integrated earth system dynamic modeling perspective to retrieve time- and scenario-dependent CFs that consider the complex interlinkages between natural processes delivering ES. The GUMBO (Global Unified Metamodel of the Biosphere) model is used to quantify changes in ES production in physical terms - leading to midpoint CFs - and changes in human welfare indicators, which are considered here as endpoint CFs. The interpretation of the obtained results highlights the key methodological challenges to be solved to consider this approach as a robust alternative to the mainstream rationale currently adopted in LCIA. Further research should focus on increasing the granularity of environmental interventions in the modeling tools to match current standards in LCA and on adapting the conceptual approach to a spatially-explicit integrated model.
Integrated earth system dynamic modeling for life cycle impact assessment of ecosystem services.
Arbault, Damien; Rivière, Mylène; Rugani, Benedetto; Benetto, Enrico; Tiruta-Barna, Ligia
2014-02-15
Despite the increasing awareness of our dependence on Ecosystem Services (ES), Life Cycle Impact Assessment (LCIA) does not explicitly and fully assess the damages caused by human activities on ES generation. Recent improvements in LCIA focus on specific cause-effect chains, mainly related to land use changes, leading to Characterization Factors (CFs) at the midpoint assessment level. However, despite the complexity and temporal dynamics of ES, current LCIA approaches consider the environmental mechanisms underneath ES to be independent from each other and devoid of dynamic character, leading to constant CFs whose representativeness is debatable. This paper takes a step forward and is aimed at demonstrating the feasibility of using an integrated earth system dynamic modeling perspective to retrieve time- and scenario-dependent CFs that consider the complex interlinkages between natural processes delivering ES. The GUMBO (Global Unified Metamodel of the Biosphere) model is used to quantify changes in ES production in physical terms - leading to midpoint CFs - and changes in human welfare indicators, which are considered here as endpoint CFs. The interpretation of the obtained results highlights the key methodological challenges to be solved to consider this approach as a robust alternative to the mainstream rationale currently adopted in LCIA. Further research should focus on increasing the granularity of environmental interventions in the modeling tools to match current standards in LCA and on adapting the conceptual approach to a spatially-explicit integrated model. PMID:24291626
Options of system integrated environment modelling in the predicated dynamic cyberspace
Janková, Martina; Dvořák, Jiří
2015-03-10
In this article there are briefly mentioned some selected options of contemporary conception of cybernetic system models in the corresponding and possible integratable environment with modern system dynamics thinking and all this in the cyberspace of possible projecting of predicted system characteristics. The key to new capabilities of system integration modelling in the considered cyberspace is mainly the ability to improve the environment and the system integration options, all this with the aim of modern control in the hierarchically arranged dynamic cyberspace, e.g. in the currently desired electronic business with information. The aim of this article is to assess generally the trends in the use of modern modelling methods considering the cybernetics applications verified in practice, modern concept of project management and also the potential integration of artificial intelligence in the new projecting and project management of integratable and intelligent models, e.g. with the optimal structures and adaptable behaviour.The article results from the solution of a specific research partial task at the faculty; especially the moments proving that the new economics will be based more and more on information, knowledge system defined cyberspace of modern management, are stressed in the text.
NASA Astrophysics Data System (ADS)
Xu, Xiaoming; Du, Ziqiang; Zhang, Hong
2016-10-01
Land use and land cover change (LULCC) is a widely researched topic in related studies. A number of models have been established to simulate LULCC patterns. However, the integration of the system dynamic (SD) and the cellular automata (CA) model have been rarely employed in LULCC simulations, although it allows for combining the advantages of each approach and therefore improving the simulation accuracy. In this study, we integrated an SD model and a CA model to predict LULCC under three future development scenarios in Northern Shanxi province of China, a typical agro-pastoral transitional zone. The results indicated that our integrated approach represented the impacts of natural and socioeconomic factors on LULCC well, and could accurately simulate the magnitude and spatial pattern of LULCC. The modeling scenarios illustrated that different development pathways would lead to various LULCC patterns. This study demonstrated the advantages of the integration approach for simulating LULCC and suggests that LULCC is affected to a large degree by natural and socioeconomic factors.
Construction and evaluation of an integrated dynamical model of visual motion perception.
Tlapale, Émilien; Dosher, Barbara Anne; Lu, Zhong-Lin
2015-07-01
Although numerous models describe the individual neural mechanisms that may be involved in the perception of visual motion, few of them have been constructed to take arbitrary stimuli and map them to a motion percept. Here, we propose an integrated dynamical motion model (IDM), which is sufficiently general to handle diverse moving stimuli, yet sufficiently precise to account for a wide-ranging set of empirical observations made on a family of random dot kinematograms. In particular, we constructed models of the cortical areas involved in motion detection, motion integration and perceptual decision. We analyzed their parameters through dynamical simulations and numerical continuation to constrain their proper ranges. Then, empirical data from a family of random dot kinematograms experiments with systematically varying direction distribution, presentation duration and stimulus size, were used to evaluate our model and estimate corresponding model parameters. The resulting model provides an excellent account of a demanding set of parametrically varied behavioral effects on motion perception, providing both quantitative and qualitative elements of evaluation.
Morselli, Melissa; Ghirardello, Davide; Semplice, Matteo; Raspa, Giuseppe; Di Guardo, Antonio
2012-05-01
Growing attention is devoted to understand the influence of the short-term variations in air concentrations on the environmental fate of semivolatile organic compounds (SVOCs) such as polycyclic aromatic hydrocarbons (PAHs). These variations are ascribable to factors such as temperature-mediated air-surface exchange and variability of planetary boundary layer (PBL) height and structure. But when investigating the fate of SVOCs at a local scale, further variability can derive from specific point source contributions. In this context, a new modeling approach (AirPlus) which integrates a previously developed model (AirFug) with an air dispersion model (AERMOD) is presented. The integrated model is illustrated for two PAHs in a Northern Italy scenario. Results show how chemical contributions deriving from background advective inflows, local emissions and a point source interact in an hourly-varying meteorological scenario to determine air concentration rapid changes and the consequent response of the soil compartment.
An integrated network-based mechanistic model for tumor growth dynamics under drug administration.
Ribeiro, Danilo; Pinto, Jose M
2009-04-01
Cancer chemotherapy complexity ranges from the routes that the drug must follow before reaching the tumor site (pharmacokinetics), to the drug effects on tumor depletion (pharmacodynamics). Previous researchers, in their majority, have focused either on the pharmacokinetics (PK) or on the pharmacodynamics (PD) aspects of chemotherapy. Moreover, models that account for the molecular mechanisms of cancer development have limited scope in addressing the protein signals involved in tumor progression. For instance, the recently developed models for the p53 network, for which a number of mutations have been reported, must be integrated for further understanding of the disease. Here, we propose an integrated model that is composed of a compartmental PK/PD representation for drug therapy that incorporates p53 and cell cycle regulation. In particular, the dynamics of p53 and its network components, such as Mdm2, pRb, cyclin-cdk's, are modeled under drug administration. The results show that the proposed model is a realistic representation of the physiological expectations in a multi-scale, integrative approach.
Development of a plant-wide dynamic model of an integrated gasification combined cycle (IGCC) plant
Bhattacharyya, D.; Turton, R.; Zitney, S.
2009-01-01
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 SELEXOL 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
Nothing to sneeze at: a dynamic and integrative computational model of an influenza A virion.
Reddy, Tyler; Shorthouse, David; Parton, Daniel L; Jefferys, Elizabeth; Fowler, Philip W; Chavent, Matthieu; Baaden, Marc; Sansom, Mark S P
2015-03-01
The influenza virus is surrounded by an envelope composed of a lipid bilayer and integral membrane proteins. Understanding the structural dynamics of the membrane envelope provides biophysical insights into aspects of viral function, such as the wide-ranging survival times of the virion in different environments. We have combined experimental data from X-ray crystallography, nuclear magnetic resonance spectroscopy, cryo-electron microscopy, and lipidomics to build a model of the intact influenza A virion. This is the basis of microsecond-scale coarse-grained molecular dynamics simulations of the virion, providing simulations at different temperatures and with varying lipid compositions. The presence of the Forssman glycolipid alters a number of biophysical properties of the virion, resulting in reduced mobility of bilayer lipid and protein species. Reduced mobility in the virion membrane may confer physical robustness to changes in environmental conditions. Our simulations indicate that viral spike proteins do not aggregate and thus are competent for multivalent immunoglobulin G interactions.
NASA Astrophysics Data System (ADS)
Aalaei, Amin; Davoudpour, Hamid
2012-11-01
This article presents designing a new mathematical model for integrating dynamic cellular manufacturing into supply chain system with an extensive coverage of important manufacturing features consideration of multiple plants location, multi-markets allocation, multi-period planning horizons with demand and part mix variation, machine capacity, and the main constraints are demand of markets satisfaction in each period, machine availability, machine time-capacity, worker assignment, available time of worker, production volume for each plant and the amounts allocated to each market. The aim of the proposed model is to minimize holding and outsourcing costs, inter-cell material handling cost, external transportation cost, procurement & maintenance and overhead cost of machines, setup cost, reconfiguration cost of machines installation and removal, hiring, firing and salary worker costs. Aimed to prove the potential benefits of such a design, presented an example is shown using a proposed model.
Munsky, Brian; Fox, Zachary; Neuert, Gregor
2015-01-01
The production and degradation of RNA transcripts is inherently subject to biological noise that arises from small gene copy numbers in individual cells. As a result, cellular RNA levels can exhibit large fluctuations over time and from one cell to the next. This article presents a range of precise single-molecule experimental techniques, based upon RNA fluorescence in situ hybridization, which can be used to measure the fluctuations of RNA at the single-cell level. A class of models for gene activation and deactivation is postulated in order to capture complex stochastic effects of chromatin modifications or transcription factor interactions. A computational tool, known the Finite State Projection approach, is introduced to accurately and efficiently analyze these models in order to predict how probability distributions of RNA change over time in response to changing environmental conditions. These single-molecule experiments, discrete stochastic models, and computational analyses are systematically integrated to identify models of gene regulation dynamics. To illustrate the power and generality of our integrated experimental and computational approach, we explore cases that include different models for three different RNA types (sRNA, mRNA and nascent RNA), three different experimental techniques and three different biological species (bacteria, yeast and human cells). PMID:26079925
NASA Technical Reports Server (NTRS)
Perry, Bruce; Anderson, Molly
2015-01-01
The Cascade Distillation Subsystem (CDS) is a rotary multistage distiller being developed to serve as the primary processor for wastewater recovery during long-duration space missions. The CDS could be integrated with a system similar to the International Space Station (ISS) Water Processor Assembly (WPA) to form a complete Water Recovery System (WRS) for future missions. Independent chemical process simulations with varying levels of detail have previously been developed using Aspen Custom Modeler (ACM) to aid in the analysis of the CDS and several WPA components. The existing CDS simulation could not model behavior during thermal startup and lacked detailed analysis of several key internal processes, including heat transfer between stages. The first part of this paper describes modifications to the ACM model of the CDS that improve its capabilities and the accuracy of its predictions. Notably, the modified version of the model can accurately predict behavior during thermal startup for both NaCl solution and pretreated urine feeds. The model is used to predict how changing operating parameters and design features of the CDS affects its performance, and conclusions from these predictions are discussed. The second part of this paper describes the integration of the modified CDS model and the existing WPA component models into a single WRS model. The integrated model is used to demonstrate the effects that changes to one component can have on the dynamic behavior of the system as a whole.
A Decision Support Systems Using A Combined Dynamic Model For Integrated Watershed Management
NASA Astrophysics Data System (ADS)
Kudo, E.; Ostrowski, M.
In this context A Decision Support System (DSS) is presented using a combined dy- namic model for Integrated Watershed Management (IWM) in a small urbanized basin in Japan. In order to improve today's often unsustainable watershed management, the causes of water problems, which interact with each other, must be identified and adequate actions must be chosen to solve the problems. To achieve the ultimate goal of sustain- able development (SD) for water it is essential to develop and apply generic DSSs. A DSS is frequently defined as a combination of a management information system, a model base and an evaluation / assessment module. The EU Water Framework Di- rectives recently established have a narrow time schedule requiring fast action into this direction, which does hardly allow to develop completely new tolls. Thus we are trying to combine different existing dynamic models that incorporate an urban man- agement model, a water quality analysis model, a groundwater analysis model and a water supply model including geographical information system data. With this com- bined model, the most appropriate and sustainable water management plan in an urban area will be developed while considering land use, ground water level, allocation of drainage system, sewerage, water supply works, water quality, and quantity. Because of sharing input data, using this combined model requires less data than using sev- eral separate models. The DSS can also be used to determine the optimum location of gages and monitoring sites. As a case study, the research will deal with the Taguri-river basin in Japan. This basin is located near Tokyo. Although the area in this basin has about 8 km2 only, there are densely build-up areas, paddy fields, and non-developed areas. The river is polluted due to wastewater from point resources: households, and non-point resources: roads and fields, etc. Overpumping of aquifers results in sinking groundwater tables and land subsidence. Moreover, a decrease
Dynamics of riparian plant communities, a new integrative ecohydrological modelling approach
NASA Astrophysics Data System (ADS)
García-Arias, Alicia; Francés, Félix
2015-04-01
The Riparian Vegetation Dynamic Model (RVDM) integrates the impacts of the hydrological extremes on the vegetation, the vegetation evolution and the competition between different vegetation classes. Considering a daily time step and a detailed spatial resolution, RVDM allows the analysis of the dynamic vegetation distribution in riverine areas during a simulated period. The riparian vegetation wellbeing and distribution are considered to be conditioned by the river hydrodynamics in RVDM. Using biomass loss functions, the stress caused by hydrological extreme events is translated into changes on the distribution of the vegetation. These extreme events are considered as removal and asphyxia associated to floods, and wilt related to droughts. The variables considered to determine the impacts are water shear stress, water table elevation and the soil moisture, respectively. RVDM includes the modelling of the natural evolution of the vegetation. The potential recruitment in bared areas, the plant growth and the succession/retrogression between plant categories are included in the model conceptualization. The recruitment takes place when seeds presence, germination and seedlings establishment overcome, so it depends on the plant reproductive period and the environmental conditions. Light use efficiency determines the vegetation growth in terms of biomass production while the soil moisture limits this biomass production and the successional evolution. Finally, the competition modelling considers the advantages between successional patterns under the specific soil moisture conditions of each unit area. Several meteorological, morphological, hydrological and hydraulic inputs are required. In addition, an initial vegetation condition is required for RVDM to start the simulation period. The model results on new vegetation maps that are considered as new inputs in the next model step. Following this approach the model simulates iteratively al the processes day by day. This
Dynamics of the exponential integrate-and-fire model with slow currents and adaptation.
Barranca, Victor J; Johnson, Daniel C; Moyher, Jennifer L; Sauppe, Joshua P; Shkarayev, Maxim S; Kovačič, Gregor; Cai, David
2014-08-01
In order to properly capture spike-frequency adaptation with a simplified point-neuron model, we study approximations of Hodgkin-Huxley (HH) models including slow currents by exponential integrate-and-fire (EIF) models that incorporate the same types of currents. We optimize the parameters of the EIF models under the external drive consisting of AMPA-type conductance pulses using the current-voltage curves and the van Rossum metric to best capture the subthreshold membrane potential, firing rate, and jump size of the slow current at the neuron's spike times. Our numerical simulations demonstrate that, in addition to these quantities, the approximate EIF-type models faithfully reproduce bifurcation properties of the HH neurons with slow currents, which include spike-frequency adaptation, phase-response curves, critical exponents at the transition between a finite and infinite number of spikes with increasing constant external drive, and bifurcation diagrams of interspike intervals in time-periodically forced models. Dynamics of networks of HH neurons with slow currents can also be approximated by corresponding EIF-type networks, with the approximation being at least statistically accurate over a broad range of Poisson rates of the external drive. For the form of external drive resembling realistic, AMPA-like synaptic conductance response to incoming action potentials, the EIF model affords great savings of computation time as compared with the corresponding HH-type model. Our work shows that the EIF model with additional slow currents is well suited for use in large-scale, point-neuron models in which spike-frequency adaptation is important. PMID:24443127
Marshall, Deborah A; Burgos-Liz, Lina; Pasupathy, Kalyan S; Padula, William V; IJzerman, Maarten J; Wong, Peter K; Higashi, Mitchell K; Engbers, Jordan; Wiebe, Samuel; Crown, William; Osgood, Nathaniel D
2016-02-01
In the era of the Information Age and personalized medicine, healthcare delivery systems need to be efficient and patient-centred. The health system must be responsive to individual patient choices and preferences about their care, while considering the system consequences. While dynamic simulation modelling (DSM) and big data share characteristics, they present distinct and complementary value in healthcare. Big data and DSM are synergistic-big data offer support to enhance the application of dynamic models, but DSM also can greatly enhance the value conferred by big data. Big data can inform patient-centred care with its high velocity, volume, and variety (the three Vs) over traditional data analytics; however, big data are not sufficient to extract meaningful insights to inform approaches to improve healthcare delivery. DSM can serve as a natural bridge between the wealth of evidence offered by big data and informed decision making as a means of faster, deeper, more consistent learning from that evidence. We discuss the synergies between big data and DSM, practical considerations and challenges, and how integrating big data and DSM can be useful to decision makers to address complex, systemic health economics and outcomes questions and to transform healthcare delivery.
Integrating Agent Models of Subsistence Farming With Dynamic Models of Water Distribution
NASA Astrophysics Data System (ADS)
Bithell, M.; Brasington, J.
2004-12-01
Subsistence farming communities are dependent on the landscape to provide the resource base upon which their societies can be built. A key component of this is the role of climate, and the feedback between rainfall, crop growth and land clearance, and their coupling to the hydrological cycle. Temporal fluctuations in rainfall on timescales from annual through to decadal and longer, and the associated changes in in the spatial distribution of water availability mediated by the soil-type, slope and landcover determine the locations within the landscape that can support agriculture, and control sustainability of farming practices. We seek to make an integrated modelling system to represent land use change by coupling an agent based model of subsistence farming, and the associated exploitation of natural resources, to a realistic representation of the hydrology at the catchment scale, using TOPMODEL to map the spatial distribution of crop water stress for given time-series of rainfall. In this way we can, for example, investigate how demographic changes and associated removal of forest cover influence the possibilities for field locations within the catchment, through changes in ground water availability. The framework for this modelling exercise will be presented and preliminary results from this system will be discussed.
An Integrated Model of Market-Driven Dynamics of Carbon in Exurban Landscapes
NASA Astrophysics Data System (ADS)
Brown, D. G.; Sun, S.; Currie, W.; Nassauer, J. I.; Page, S. E.; Parker, D. C.; Riolo, R. L.; Robinson, D. T.
2012-12-01
As coupled human-environment system, exurban land-use systems and their ecological and social outcomes are driven by interactions between the human actors and natural processes at play. Carbon storage in exurban land-use systems is driven by interactions among market forces driving land-use change, developer and resident decisions about land cover and land management, and ecosystem processes affecting ecosystem function. Whether or not vegetation in these landscapes contribute to carbon sinks that mitigate global change, and their future trajectory, depends on dynamics in both human and biophysical processes. Understanding these interactions in a coupled human and natural system might best be advanced by iterating between data collection efforts on various aspects of the system (including the states and changes in the social and natural aspects of the system) and modeling in ways that explicitly represents social and natural processes and their interactions. A challenge is to build models that are both explicable based on existing process knowledge and supportable by existing or newly collected data. We coupled an agent-based model of developer and resident decision making about landscape structure and management with a biogeochemical model of carbon flux and storage to evaluate the drivers of and possible mechanisms to achieve increased carbon storage. Model-based experiments demonstrate the (a) effects of various residential land management strategies on carbon storage, suggesting that removals of litter have a larger effect on overall carbon storage than additions of fertilizer and irrigation; (b) effects of subsidies or payments for increased carbon storage paid to developers can result in choices about development types that result in increased carbon storage, but that the effects are highly sensitive to the price of carbon and the basis for calculating payments. The experiments highlight the need for integrated modeling, but also point to specific needs for
NASA Technical Reports Server (NTRS)
Lee, Hyongki; Kim, Jin-woo; Lu, Zhong; Jung, Hahn Chul; Shum, C. K.; Alsdorf, Doug
2012-01-01
Wetland loss in Louisiana has been accelerating due primarily to anthropogenic and nature processes, and is being advocated as a problem with national importance. Accurate measurement or modeling of wetland-wide water level changes, its varying extent, its storage and discharge changes resulting in part from sediment loads, erosion and subsidence are fundamental to assessment of hurricane-induced flood hazards and wetland ecology. Here, we use innovative method to integrate interferometric SAR (InSAR) and satellite radar altimetry for measuring absolute or geocentric water level changes and applied the methodology to remote areas of swamp forest in coastal Louisiana. Coherence analysis of InSAR pairs suggested that the HH polarization is preferred for this type of observation, and polarimetric analysis can help to identi:fy double-bonnce backscattering areas in the wetland. Envisat radar altimeter-measured 18- Hz (along-track sampling of 417 m) water level data processed with regional stackfile method have been used to provide vertical references for water bodies separated by levees. The high-resolution (approx.40 m) relative water changes measured from ALOS PALSAR L-band and Radarsat-l C-band InSAR are then integrated with Envisat radar altimetry to obtain absolute water level. The resulting water level time series were validated with in situ gauge observations within the swamp forest. Furthermore, we compare our water elevation changes with 2D flood modeling from LISFLOOD hydrodynamic model. Our study demonstrates that this new technique allows retrospective reconstruction and concurrent monitoring of water conditions and flow dynamics in wetlands, especially those lacking gauge networks.
Sušnik, Janez; Vamvakeridou-Lyroudia, Lydia S; Savić, Dragan A; Kapelan, Zoran
2012-12-01
A System Dynamics Model (SDM) assessing water scarcity and potential impacts of socio-economic policies in a complex hydrological system is developed. The model, simulating water resources deriving from numerous catchment sources and demand from four sectors (domestic, industrial, agricultural, external pumping), contains multiple feedback loops and sub-models. The SDM is applied to the Merguellil catchment, Tunisia; the first time such an integrated model has been developed for the water scarce Kairouan region. The application represents an early step in filling a critical research gap. The focus of this paper is to a) assess the applicability of SDM for assessment of the evolution of a water-scarce catchment and b) to analyse the current and future behaviour of the catchment to evaluate water scarcity, focusing on understanding trends to inform policy. Baseline results indicate aquifer over-exploitation, agreeing with observed trends. If current policy and social behaviour continue, serious aquifer depletion is possible in the not too distant future, with implications for the economy and environment. This is unlikely to occur because policies preventing depletion will be implemented. Sensitivity tests were carried out to show which parameters most impacted aquifer behaviour. Results show non-linear model behaviour. Some tests showed negligible change in behaviour. Others showed unrealistic exponential changes in demand, revenue and aquifer water volume. Policy-realistic parameters giving the greatest positive impact on model behaviour were those controlling per-capita domestic water demand and the pumped volume to coastal cities. All potentially beneficial policy options should be considered, giving the best opportunity for preservation of Kairouan aquifer water quantity/quality, ecologically important habitats and the agricultural socio-economic driver of regional development. SDM is a useful tool for assessing the potential impacts of possible policy measures
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2012-12-01
Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil
NASA Astrophysics Data System (ADS)
Li, G. Q.; Zhu, Z. H.
2015-12-01
Dynamic modeling of tethered spacecraft with the consideration of elasticity of tether is prone to the numerical instability and error accumulation over long-term numerical integration. This paper addresses the challenges by proposing a globally stable numerical approach with the nodal position finite element method (NPFEM) and the implicit, symplectic, 2-stage and 4th order Gaussian-Legendre Runge-Kutta time integration. The NPFEM eliminates the numerical error accumulation by using the position instead of displacement of tether as the state variable, while the symplectic integration enforces the energy and momentum conservation of the discretized finite element model to ensure the global stability of numerical solution. The effectiveness and robustness of the proposed approach is assessed by an elastic pendulum problem, whose dynamic response resembles that of tethered spacecraft, in comparison with the commonly used time integrators such as the classical 4th order Runge-Kutta schemes and other families of non-symplectic Runge-Kutta schemes. Numerical results show that the proposed approach is accurate and the energy of the corresponding numerical model is conservative over the long-term numerical integration. Finally, the proposed approach is applied to the dynamic modeling of deorbiting process of tethered spacecraft over a long period.
NASA Astrophysics Data System (ADS)
Lee, Han Soo; Yamashita, Takao; Hsu, John R.-C.; Ding, Fei
2013-01-01
In August 2009, Typhoon Morakot caused massive flooding and devastating mudslides in the southern Taiwan triggered by extremely heavy rainfall (2777 mm in 4 days) which occurred during its passage. It was one of the deadliest typhoons that have ever attacked Taiwan in recent years. In this study, numerical simulations are performed for the storm surge and ocean surface waves, together with dynamic meteorological fields such as wind, pressure and precipitation induced by Typhoon Morakot, using an atmosphere-waves-ocean integrated modelling system. The wave-induced dissipation stress from breaking waves, whitecapping and depth-induced wave breaking, is parameterized and included in the wave-current interaction process, in addition to its influence on the storm surge level in shallow water along the coast of Taiwan. The simulated wind and pressure field captures the characteristics of the observed meteorological field. The spatial distribution of the accumulated rainfall within 4 days, from 00:00 UTC 6 August to 00:00 UTC 10 August 2009, shows similar patterns as the observed values. The 4-day accumulated rainfall of 2777 mm at the A-Li Shan mountain weather station for the same period depicted a high correlation with the observed value of 2780 mm/4 days. The effects of wave-induced dissipation stress in the wave-current interaction resulted in increased surge heights on the relatively shallow western coast of Taiwan, where the bottom slope of the bathymetry ranges from mild to moderate. The results also show that wave-breaking has to be considered for accurate storm surge prediction along the east coast of Taiwan over the narrow bank of surf zone with a high horizontal resolution of the model domain.
Predicting carbon dynamics in integrated production systems in Brazil using the CQESTR model
Technology Transfer Automated Retrieval System (TEKTRAN)
Process-based carbon models are research tools to predict management impact on soil organic carbon (SOC) and options to increase SOC stocks and reduce CO2. The CQESTR model was used to examine the effect of soil management practices, including integrated crop-livestock system (iCLS), and various sc...
Romano, Alessandro
2016-01-01
This article is a first application of an integrable nonautonomous Lotka–Volterra (LV) model to the study of tourism dynamics. In particular, we analyze the interaction in terms of touristic flows among three Italian regions. Confirming an hypothesis advanced by recent theoretical works, we find that these regions not only compete against each other, but at times they also proceed in mutualism. Moreover, the kind and the intensity of the interaction changes over time, suggesting that dynamic models can play a vital role in the study of touristic flows. PMID:27661615
Niemi, J K; Sevón-Aimonen, M-L; Stygar, A H; Partanen, K
2015-08-01
The selection of animals for improved performance affects the profitability of pig fattening and has environmental consequences. The goal of this paper was to examine how changes in genetic and market parameters impact the biophysical (feeding patterns, timing of slaughter, nitrogen excretion) and economic (return per pig space unit) results describing pig fattening in a Finnish farm. The analysis can be viewed as focusing on terminal line breeding goals. An integrated model using recursive stochastic dynamic programming and a biological pig growth model was used to estimate biophysical results and economic values. Combining these models allowed us to provide more accurate estimates for the value of genetic improvement and, thus, provide better feedback to animal breeding programs than the traditional approach, which is based on fixed management patterns. Besides the benchmark scenario, the results were simulated for 5 other scenarios. In each scenario, genotype was improved regarding daily growth potential, carcass lean meat content, or the parameters of the Gompertz growth curve (maturing rate [], adult weight of protein [α], and adult weight of lipid mass []). The change in each parameter was equal to approximately 1 SD genetic improvement (ceteris paribus). Increasing , , daily growth potential, or carcass lean meat content increased the return on pig space unit by €12.60, €7.60, €4.10, or €2.90 per year, respectively, whereas an increase in decreased the return by €3.10. The genetic improvement in and resulted in the highest decrease in nitrogen excretion calculated in total or per kilogram of carcass gain but only under the optimal feeding pattern. Simulated changes in the Gompertz growth function parameters imply greater changes in ADG and lean meat content than changes in scenarios focusing on improving ADG and lean meat content directly. The economic value of genetic improvements as well as the quantity of nitrogen excreted during the fattening
Niemi, J K; Sevón-Aimonen, M-L; Stygar, A H; Partanen, K
2015-08-01
The selection of animals for improved performance affects the profitability of pig fattening and has environmental consequences. The goal of this paper was to examine how changes in genetic and market parameters impact the biophysical (feeding patterns, timing of slaughter, nitrogen excretion) and economic (return per pig space unit) results describing pig fattening in a Finnish farm. The analysis can be viewed as focusing on terminal line breeding goals. An integrated model using recursive stochastic dynamic programming and a biological pig growth model was used to estimate biophysical results and economic values. Combining these models allowed us to provide more accurate estimates for the value of genetic improvement and, thus, provide better feedback to animal breeding programs than the traditional approach, which is based on fixed management patterns. Besides the benchmark scenario, the results were simulated for 5 other scenarios. In each scenario, genotype was improved regarding daily growth potential, carcass lean meat content, or the parameters of the Gompertz growth curve (maturing rate [], adult weight of protein [α], and adult weight of lipid mass []). The change in each parameter was equal to approximately 1 SD genetic improvement (ceteris paribus). Increasing , , daily growth potential, or carcass lean meat content increased the return on pig space unit by €12.60, €7.60, €4.10, or €2.90 per year, respectively, whereas an increase in decreased the return by €3.10. The genetic improvement in and resulted in the highest decrease in nitrogen excretion calculated in total or per kilogram of carcass gain but only under the optimal feeding pattern. Simulated changes in the Gompertz growth function parameters imply greater changes in ADG and lean meat content than changes in scenarios focusing on improving ADG and lean meat content directly. The economic value of genetic improvements as well as the quantity of nitrogen excreted during the fattening
Integrated Model of VET Dynamics: Social and Economic Benefits for All. CRLRA Discussion Paper.
ERIC Educational Resources Information Center
Falk, Ian
The model currently used to represent the impacts of Australia's technical and further education (TAFE) programs implies a one-way flow of impact from TAFE to student to community. It may be argued that TAFE could better serve its clients by developing a social capital-based, two-way, reciprocal dynamic of vocational education and training (VET)…
Acceleration of the KINETICS Integrated Dynamical/Chemical Computational Model Using MPI
NASA Technical Reports Server (NTRS)
Grossman, Max; Willacy, Karen; Allen, Mark
2011-01-01
Understanding the evolution of a planet's atmosphere not only provides a better theoretical understanding of planetary physics and the formation of planets, but also grants useful insight into Earth's own atmosphere. One of the tools used at JPL for the modeling of planetary atmospheres and protostellar disks is KINETICS. KINETICS can simulate years of complex dynamics and chemistry.
ERIC Educational Resources Information Center
Decuyper, Stefan; Dochy, Filip; Van den Bossche, Piet
2010-01-01
In this article we present an integrative model of team learning. Literature shows that effective team learning requires the establishment of a dialogical space amongst team members, in which communicative behaviours such as "sharing", "co-construction" and "constructive conflict" are balanced. However, finding this balance is not enough.…
NASA Technical Reports Server (NTRS)
Chavez, Frank R.; Schmidt, David K.
1992-01-01
The development of an approach to the determination of the dynamic characteristics of hypersonic vehicles which is intentionally generic and basic is given. The approach involves a 2D hypersonic aerodynamic analysis utilizing Newtonian theory, coupled with a 1D aero/thermoanalysis of the flow in a scramjet-type propulsion system. In addition, the airframe is considered to be elastic, and the structural dynamics are characterized in terms of a simple lumped-mass model of the invacuo vibration modes. The vibration modes are coupled to the rigid-body modes through the aero/propulsive forces acting on the structure. The control effectors considered on a generic study configuration include aerodynamic pitch-control surfaces, as well as engine fuel flow and diffuser area ratio. The study configuration is shown to be highly statically unstable in pitch, and to exhibit strong airframe/engine/elastic coupling in the aeroelastic and attitude dynamics, as well as the engine responses.
Liu, Hui; Benoit, Gaboury; Liu, Tao; Liu, Yong; Guo, Huaicheng
2015-05-15
A reliable system simulation to relate socioeconomic development with water environment and to comprehensively represent a watershed's dynamic features is important. In this study, after identifying lake watershed system processes, we developed a system dynamics modeling framework for managing lake water quality at the watershed scale. Two reinforcing loops (Development and Investment Promotion) and three balancing loops (Pollution, Resource Consumption, and Pollution Control) were constituted. Based on this work, we constructed Stock and Flow Diagrams that embedded a pollutant load model and a lake water quality model into a socioeconomic system dynamics model. The Dianchi Lake in Yunnan Province, China, which is the sixth largest and among the most severely polluted freshwater lakes in China, was employed as a case study to demonstrate the applicability of the model. Water quality parameters considered in the model included chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). The business-as-usual (BAU) scenario and three alternative management scenarios on spatial adjustment of industries and population (S1), wastewater treatment capacity construction (S2), and structural adjustment of agriculture (S3), were simulated to assess the effectiveness of certain policies in improving water quality. Results showed that S2 is most effective scenario, and the COD, TN, and TP concentrations in Caohai in 2030 are 52.5, 10.9, and 0.8 mg/L, while those in Waihai are 9.6, 1.2, and 0.08 mg/L, with sustained development in the watershed. Thus, the model can help support the decision making required in development and environmental protection strategies.
NASA Astrophysics Data System (ADS)
Koo, M. S.; Park, H.; Park, S. H.; Hong, S. Y.
2014-12-01
The Global/Regional Integrated Model system (GRIMs)-double Fourier series (DFS) spectral dynamical core has been developed to overcome the limitation of traditional spectral model using spherical harmonics in terms of computational cost at very high resolution. Recently, the GRIMs-DFS dynamical core was updated in two respects: (1) better scalability on high-performance computing platform; and (2) reduction of numerical time-stepping error. To improve the parallel efficiency, the archived wave domain was designed not to be sliced in the meridional direction, but to be decomposed in the horizontal and vertical directions. Although the computational cost slightly increased due to the requirement of temporary work array, the revised DFS dynamical core yielded higher scalability in terms of the wall-clock-time than the original one. In addition, its efficiency gain became greater with the increase of horizontal resolution when the number of processors is increased. The Robert-Asselin-Williams (RAW) time filter has been proposed as a simple improvement to the widely used Robert-Asselin filter, in order to reduce time-stepping errors in semi-implicit leapfrog integration. This new approach was implemented into the GRIMs-DFS dynamical core and its impact was quantitatively evaluated on medium-range forecast and seasonal ensemble prediction frameworks. Preliminary results showed that the RAW time-filter properly reduced spurious light rainfalls that might be produced from unphysical computational mode generated by leap-frog time stepping. Further details will be presented in the conference.
Cieslak, Mikolaj; Seleznyova, Alla N.; Hanan, Jim
2011-01-01
Background and Aims Functional–structural modelling can be used to increase our understanding of how different aspects of plant structure and function interact, identify knowledge gaps and guide priorities for future experimentation. By integrating existing knowledge of the different aspects of the kiwifruit (Actinidia deliciosa) vine's architecture and physiology, our aim is to develop conceptual and mathematical hypotheses on several of the vine's features: (a) plasticity of the vine's architecture; (b) effects of organ position within the canopy on its size; (c) effects of environment and horticultural management on shoot growth, light distribution and organ size; and (d) role of carbon reserves in early shoot growth. Methods Using the L-system modelling platform, a functional–structural plant model of a kiwifruit vine was created that integrates architectural development, mechanistic modelling of carbon transport and allocation, and environmental and management effects on vine and fruit growth. The branching pattern was captured at the individual shoot level by modelling axillary shoot development using a discrete-time Markov chain. An existing carbon transport resistance model was extended to account for several source/sink components of individual plant elements. A quasi-Monte Carlo path-tracing algorithm was used to estimate the absorbed irradiance of each leaf. Key Results Several simulations were performed to illustrate the model's potential to reproduce the major features of the vine's behaviour. The model simulated vine growth responses that were qualitatively similar to those observed in experiments, including the plastic response of shoot growth to local carbon supply, the branching patterns of two Actinidia species, the effect of carbon limitation and topological distance on fruit size and the complex behaviour of sink competition for carbon. Conclusions The model is able to reproduce differences in vine and fruit growth arising from various
NASA Astrophysics Data System (ADS)
Aubry, Serge
1994-02-01
Many models for structures in condensed matter can be associated with Hamiltonian dynamical systems with discrete time. This connection is due to the fact that both models are defined by the minimisation or the extremalisation of the same variational form called “free energy” in the first case and “action” in the second case. Thus, the results obtained for the first class of problems turn out to have applications for the second class and vice-versa, but however, with a physical interpretation which is totally different. For example, the breaking of the KAM tori and the occurrence of chaos in the standard map turns out to correspond to a pinning transition and the occurrence of chaotic metastable states in the associated Frenkel-Kontorowa models. The anti-integrable limit for structural problems is a very natural limit where the “atoms” of the structure become disconnected. It corresponds to a highly singular limit for the associated dynamical system which up to now did not focus much attention. The associated dynamical system becomes undeterministic and just reduces to a Bernoulli shift. Nevertheless, a perturbation theorem can be established at this limit which proves the persistence of chaotic trajectories when the dynamical system returns to be deterministic. This result is extended to a large class of dynamical systems with discrete time including non-Hamiltonian systems. An anti-integrable limit can also be found in the adiabatic Holstein model describing electrons coupled to phonons at several dimensions and some extensions which are not apparently connected to any dynamical system. Then the anti-integrable limit is obtained when the electronic kinetic energy vanishes. Treating this kinetic energy in an exact perturbation theory, allows one to prove new results concerning the existence of bipolaronic, polaronic and mixed polaronic-bipolaronic insulators. The possible extension of the KAM theory to the small electron-phonon coupling regime and
Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations
NASA Technical Reports Server (NTRS)
Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.
2012-01-01
Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.
NASA Astrophysics Data System (ADS)
Zhang, Sheng-Fei; Xu, Jun-Bo; Wen, Hao; Bhattacharjee, Subir
2011-08-01
Heavy crude oil consists of thousands of compounds, a significant fraction of which have fairly large molecular weights and complex structures. Our work aims at constructing a meso-scale platform to explore this complex fluid in terms of microstructure, phase behavior, stability and rheology. In the present study, we focus on the treatment of the structures of fused aromatic rings as rigid body fragments in fractions such as asphaltenes and resins. To derive the rotational motion of rigid bodies in a non-conservative force field, we conduct a comparison of three rigid body rotational algorithms integrated into a standard dissipative particle dynamics (DPD) simulation. The simulation results confirm the superiority of the Quaternion method. To ease any doubt concerning the introduction of rigid bodies into DPD, the performance of the Quaternion method was tested carefully. Finally, the aggregation dynamics of asphaltene in very diluted toluene was investigated. The nanoaggregates are found to experience forming, breaking up and reforming. The sizes of the asphaltene monomer and nanoaggregate are identified. The diffusion coefficient of diluted asphaltene in toluene is similar to that found experimentally. All these results verify the rotational algorithm and encourage us to extend this platform to study the rheological and colloidal characteristics of heavy crude oils in the future.
Integrating Dynamic Data and Sensors with Semantic 3D City Models in the Context of Smart Cities
NASA Astrophysics Data System (ADS)
Chaturvedi, K.; Kolbe, T. H.
2016-10-01
Smart cities provide effective integration of human, physical and digital systems operating in the built environment. The advancements in city and landscape models, sensor web technologies, and simulation methods play a significant role in city analyses and improving quality of life of citizens and governance of cities. Semantic 3D city models can provide substantial benefits and can become a central information backbone for smart city infrastructures. However, current generation semantic 3D city models are static in nature and do not support dynamic properties and sensor observations. In this paper, we propose a new concept called Dynamizer allowing to represent highly dynamic data and providing a method for injecting dynamic variations of city object properties into the static representation. The approach also provides direct capability to model complex patterns based on statistics and general rules and also, real-time sensor observations. The concept is implemented as an Application Domain Extension for the CityGML standard. However, it could also be applied to other GML-based application schemas including the European INSPIRE data themes and national standards for topography and cadasters like the British Ordnance Survey Mastermap or the German cadaster standard ALKIS.
NASA Astrophysics Data System (ADS)
Liu, Ming; Zhao, Lindu
2012-08-01
Demand for emergency resources is usually uncertain and varies quickly in anti-bioterrorism system. Besides, emergency resources which had been allocated to the epidemic areas in the early rescue cycle will affect the demand later. In this article, an integrated and dynamic optimisation model with time-varying demand based on the epidemic diffusion rule is constructed. The heuristic algorithm coupled with the MATLAB mathematical programming solver is adopted to solve the optimisation model. In what follows, the application of the optimisation model as well as a short sensitivity analysis of the key parameters in the time-varying demand forecast model is presented. The results show that both the model and the solution algorithm are useful in practice, and both objectives of inventory level and emergency rescue cost can be controlled effectively. Thus, it can provide some guidelines for decision makers when coping with emergency rescue problem with uncertain demand, and offers an excellent reference when issues pertain to bioterrorism.
An integrated muscle mechanic-fluid dynamic model of lamprey swimming
NASA Astrophysics Data System (ADS)
Hsu, Chia-Yu; Tytell, Eric; Fauci, Lisa
2009-11-01
In an effort towards a detailed understanding of the generation and control of vertebrate locomotion, including the role of the CPG and its interactions with reflexive feedback, muscle mechanics, and external fluid dynamics, we study a simple vertebrate, the lamprey. Lamprey body undulations are a result of a wave of neural activation that passes from head to tail, causing a wave of muscle activation. These active forces are mediated by passive structural forces. We present recent results from a model that fully couples a viscous, incompressible fluid with nonlinear muscle mechanics. We measure the dependence of the phase lag between activation wave and mechanical wave as a function of model parameters, such as body stiffness and muscle strength. Simulation results are compared to experiments utilizing both real and synthetic lamprey.
Integrated Dynamic Gloabal Modeling of Land Use, Energy and Economic Growth
Atul Jain, University of Illinois, Urbana-Champaign, IL Brian O'Neill, NCAR, Boulder, CO
2009-10-14
The overall objective of this collaborative project is to integrate an existing general equilibrium energy-economic growth model with a biogeochemical cycles and biophysical models in order to more fully explore the potential contribution of land use-related activities to future emissions scenarios. Land cover and land use change activities, including deforestation, afforestation, and agriculture management, are important source of not only CO2, but also non-CO2 GHGs. Therefore, contribution of land-use emissions to total emissions of GHGs is important, and consequently their future trends are relevant to the estimation of climate change and its mitigation. This final report covers the full project period of the award, beginning May 2006, which includes a sub-contract to Brown University later transferred to the National Center for Atmospheric Research (NCAR) when Co-PI Brian O'Neill changed institutional affiliations.
Sehr, Christiana; Kremling, Andreas; Marin-Sanguino, Alberto
2015-01-01
During the last 10 years, systems biology has matured from a fuzzy concept combining omics, mathematical modeling and computers into a scientific field on its own right. In spite of its incredible potential, the multilevel complexity of its objects of study makes it very difficult to establish a reliable connection between data and models. The great number of degrees of freedom often results in situations, where many different models can explain/fit all available datasets. This has resulted in a shift of paradigm from the initially dominant, maybe naive, idea of inferring the system out of a number of datasets to the application of different techniques that reduce the degrees of freedom before any data set is analyzed. There is a wide variety of techniques available, each of them can contribute a piece of the puzzle and include different kinds of experimental information. But the challenge that remains is their meaningful integration. Here we show some theoretical results that enable some of the main modeling approaches to be applied sequentially in a complementary manner, and how this workflow can benefit from evolutionary reasoning to keep the complexity of the problem in check. As a proof of concept, we show how the synergies between these modeling techniques can provide insight into some well studied problems: Ammonia assimilation in bacteria and an unbranched linear pathway with end-product inhibition. PMID:26501332
NASA Astrophysics Data System (ADS)
Nguyen, Gia Luong Huu
Fuel cells can produce electricity with high efficiency, low pollutants, and low noise. With the advent of fuel cell technologies, fuel cell systems have since been demonstrated as reliable power generators with power outputs from a few watts to a few megawatts. With proper equipment, fuel cell systems can produce heating and cooling, thus increased its overall efficiency. To increase the acceptance from electrical utilities and building owners, fuel cell systems must operate more dynamically and integrate well with renewable energy resources. This research studies the dynamic performance of fuel cells and the integration of fuel cells with other equipment in three levels: (i) the fuel cell stack operating on hydrogen and reformate gases, (ii) the fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit, and (iii) the hybrid energy system consisting of photovoltaic panels, fuel cell system, and energy storage. In the first part, this research studied the steady-state and dynamic performance of a high temperature PEM fuel cell stack. Collaborators at Aalborg University (Aalborg, Denmark) conducted experiments on a high temperature PEM fuel cell short stack at steady-state and transients. Along with the experimental activities, this research developed a first-principles dynamic model of a fuel cell stack. The dynamic model developed in this research was compared to the experimental results when operating on different reformate concentrations. Finally, the dynamic performance of the fuel cell stack for a rapid increase and rapid decrease in power was evaluated. The dynamic model well predicted the performance of the well-performing cells in the experimental fuel cell stack. The second part of the research studied the dynamic response of a high temperature PEM fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit with high thermal integration. After verifying the model performance with the
Shankaran, Harish; Zhang, Yi; Chrisler, William B.; Ewald, Jonathan A.; Wiley, H. S.; Resat, Haluk
2012-10-02
The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models for deconvolving the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor dephosphorylation rates at the cell surface and early endosomes are comparable. We validated the last finding by measuring EGFR dephosphorylation rates at various times following ligand addition both in whole cells, and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. Further, the mathematical model described here can be extended to determine receptor dimer abundances in cells co-expressing various levels of ErbB receptors. This study demonstrates that an iterative cycle of
Gevaert, Veerle; Verdonck, Frederik; De Baets, Bernard
2012-08-15
The Water Framework Directive (WFD) has the objective of a catchment-oriented water quality protection for all European waters with the purpose of achieving a good ecological and chemical quality status by the year 2015. To that end, necessary measures should be identified and implemented, with the aim of progressively reducing pollution from priority substances. The objective of this paper is to demonstrate how a dynamic model of the integrated urban wastewater system (IUWS) can be used to test different emission reduction strategies for organic priority pollutants (PPs) in a semi-hypothetical case study on di(2-ethylhexyl)phthalate (DEHP). The IUWS is composed of coupled entities: sources, urban catchment surface (run-off/infiltration), sewer system, stormwater treatment unit, wastewater treatment plant (WWTP) including sludge handling, and receiving surface water (river). State-of-the-art dynamic fate models were selected from literature and extended with an organic pollutant fate sub-model. Dynamic DEHP release profiles were estimated using a dynamic model input generator and fed to the model to predict the fate and concentration of DEHP in each IUWS sub-system. The model was then used to test eight scenarios on environmental performance, namely (1) reduction of impervious urban area, (2) reduction of infiltration in the sewer system, (3) input reduction (excluding the main pollutant sources), (4) separating the combined sewer system, (5) treatment of stormwater by stormwater infiltration ponds (separate sewer systems), (6) placement of retention basins at main sewer junctions, (7) sand filtration of secondary effluent, and (8) pre-precipitation of phosphorous. The simulation results revealed that the most effective measure in terms of river water quality improvement for DEHP (annual average and spikiness reduction) and PP concentration in the disposed WWTP sludge, is reducing release of this substance into the environment, not surprisingly. In general, this
MacLeod, Miles; Nersessian, Nancy J
2015-02-01
In this paper we draw upon rich ethnographic data of two systems biology labs to explore the roles of explanation and understanding in large-scale systems modeling. We illustrate practices that depart from the goal of dynamic mechanistic explanation for the sake of more limited modeling goals. These processes use abstract mathematical formulations of bio-molecular interactions and data fitting techniques which we call top-down abstraction to trade away accurate mechanistic accounts of large-scale systems for specific information about aspects of those systems. We characterize these practices as pragmatic responses to the constraints many modelers of large-scale systems face, which in turn generate more limited pragmatic non-mechanistic forms of understanding of systems. These forms aim at knowledge of how to predict system responses in order to manipulate and control some aspects of them. We propose that this analysis of understanding provides a way to interpret what many systems biologists are aiming for in practice when they talk about the objective of a "systems-level understanding."
Modelling land cover dynamics: integration of fine-scale land cover data with landscape attributes
NASA Astrophysics Data System (ADS)
Mertens, Benoît; Lambin, Eric
Land cover change detection based on remote sensing data allows the identification of major processes of change and, by inference, the characterization of land use dynamics. Empirical diagnostic models of land use/cover change can be developed from these observations. To grasp the complexity of landscape mosaics and changes in land use, fine-scale land cover and socio-economic data are required. Case studies need to be representative of conditions at a broader scale, and selected where sufficient knowledge on social and ecological processes leading to land use changes exists. For this reason, collaboration between remote sensing specialists and human ecologists conducting long-term field-based land use studies is extremely productive. Continental-scale analysis of Africa was conducted to detect land cover change "hot spots". Fine-scale analyses were performed for validation purposes and to understand better the land cover change processes. Spatial statistical models of land cover change can be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to support the implementation of appropriate policy responses to, for example, land degradation that would lead to the depletion of essential resources. Results of a spatial model of deforestation in southern Cameroon are discussed.
NASA Astrophysics Data System (ADS)
Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin
2014-06-01
Objective. Most BCIs have to undergo a calibration session in which data is recorded to train decoders with machine learning. Only recently zero-training methods have become a subject of study. This work proposes a probabilistic framework for BCI applications which exploit event-related potentials (ERPs). For the example of a visual P300 speller we show how the framework harvests the structure suitable to solve the decoding task by (a) transfer learning, (b) unsupervised adaptation, (c) language model and (d) dynamic stopping. Approach. A simulation study compares the proposed probabilistic zero framework (using transfer learning and task structure) to a state-of-the-art supervised model on n = 22 subjects. The individual influence of the involved components (a)-(d) are investigated. Main results. Without any need for a calibration session, the probabilistic zero-training framework with inter-subject transfer learning shows excellent performance—competitive to a state-of-the-art supervised method using calibration. Its decoding quality is carried mainly by the effect of transfer learning in combination with continuous unsupervised adaptation. Significance. A high-performing zero-training BCI is within reach for one of the most popular BCI paradigms: ERP spelling. Recording calibration data for a supervised BCI would require valuable time which is lost for spelling. The time spent on calibration would allow a novel user to spell 29 symbols with our unsupervised approach. It could be of use for various clinical and non-clinical ERP-applications of BCI.
Liu, J.; Liu, S.; Loveland, T.R.; Tieszen, L.L.
2008-01-01
Land cover change is one of the key driving forces for ecosystem carbon (C) dynamics. We present an approach for using sequential remotely sensed land cover observations and a biogeochemical model to estimate contemporary and future ecosystem carbon trends. We applied the General Ensemble Biogeochemical Modelling System (GEMS) for the Laurentian Plains and Hills ecoregion in the northeastern United States for the period of 1975-2025. The land cover changes, especially forest stand-replacing events, were detected on 30 randomly located 10-km by 10-km sample blocks, and were assimilated by GEMS for biogeochemical simulations. In GEMS, each unique combination of major controlling variables (including land cover change history) forms a geo-referenced simulation unit. For a forest simulation unit, a Monte Carlo process is used to determine forest type, forest age, forest biomass, and soil C, based on the Forest Inventory and Analysis (FIA) data and the U.S. General Soil Map (STATSGO) data. Ensemble simulations are performed for each simulation unit to incorporate input data uncertainty. Results show that on average forests of the Laurentian Plains and Hills ecoregion have been sequestrating 4.2 Tg C (1 teragram = 1012 gram) per year, including 1.9 Tg C removed from the ecosystem as the consequences of land cover change. ?? 2008 Elsevier B.V.
NASA Astrophysics Data System (ADS)
Poulter, B.; Ciais, P.; Joetzjer, E.; Maignan, F.; Luyssaert, S.; Barichivich, J.
2015-12-01
Accurately estimating forest biomass and forest carbon dynamics requires new integrated remote sensing, forest inventory, and carbon cycle modeling approaches. Presently, there is an increasing and urgent need to reduce forest biomass uncertainty in order to meet the requirements of carbon mitigation treaties, such as Reducing Emissions from Deforestation and forest Degradation (REDD+). Here we describe a new parameterization and assimilation methodology used to estimate tropical forest biomass using the ORCHIDEE-CAN dynamic global vegetation model. ORCHIDEE-CAN simulates carbon uptake and allocation to individual trees using a mechanistic representation of photosynthesis, respiration and other first-order processes. The model is first parameterized using forest inventory data to constrain background mortality rates, i.e., self-thinning, and productivity. Satellite remote sensing data for forest structure, i.e., canopy height, is used to constrain simulated forest stand conditions using a look-up table approach to match canopy height distributions. The resulting forest biomass estimates are provided for spatial grids that match REDD+ project boundaries and aim to provide carbon estimates for the criteria described in the IPCC Good Practice Guidelines Tier 3 category. With the increasing availability of forest structure variables derived from high-resolution LIDAR, RADAR, and optical imagery, new methodologies and applications with process-based carbon cycle models are becoming more readily available to inform land management.
NASA Astrophysics Data System (ADS)
Lyu, Jingyuan; Spincemaille, Pascal; Wang, Yi; Zhou, Yihang; Ren, Fuquan; Ying, Leslie
2014-05-01
Dynamic contrast enhanced MRI requires high spatial resolution for morphological information and high temporal resolution for contrast pharmacokinetics. The current techniques usually have to compromise the spatial information for the required temporal resolution. This paper presents a novel method that effectively integrates sparse sampling, parallel imaging, partial separable (PS) model, and sparsity constraints for highly accelerated DCE-MRI. Phased array coils were used to continuously acquire data from a stack of variable-density spiral trajectory with a golden angle. In reconstruction, the sparsity constraints, the coil sensitivities, spatial and temporal bases of the PS model are jointly estimated through alternating optimization. Experimental results from in vivo DCE liver imaging data show that the proposed method is able to achieve high spatial and temporal resolutions at the same time.
Hayashi, Takehiko I; Imaizumi, Yoshitaka; Yokomizo, Hiroyuki; Tatarazako, Norihisa; Suzuki, Noriyuki
2016-01-01
Application of herbicides to paddy fields in Japan has strong seasonality, and their environmental concentrations exhibit clear spatiotemporal variation. The authors developed an approach that combines a multimedia environmental exposure model (Grid-Catchment Integrated Modeling System) and density dynamics models for algae. This approach enabled assessment of ecological risk when the exposure concentration shows spatiotemporal variation. First, risk maps of 5 herbicides (pretilachlor, butachlor, simetryn, mefenacet, and esprocarb) were created from the spatial predictions of environmental concentrations and 50% inhibitory concentrations of the herbicides. Simulations of algal density dynamics at high-risk sites were then conducted by incorporating the predicted temporal dynamics of the environmental concentration of each herbicide at the sites. The results suggested that the risk of pretilachlor was clearly the highest of the 5 herbicides, in terms of both the spatial distributions and the temporal durations. The present study highlights the importance of integrating exposure models and effect models to clarify spatial and temporal risk and to develop management plans for chemical exposure that shows high spatiotemporal variation. PMID:26183805
Hayashi, Takehiko I; Imaizumi, Yoshitaka; Yokomizo, Hiroyuki; Tatarazako, Norihisa; Suzuki, Noriyuki
2016-01-01
Application of herbicides to paddy fields in Japan has strong seasonality, and their environmental concentrations exhibit clear spatiotemporal variation. The authors developed an approach that combines a multimedia environmental exposure model (Grid-Catchment Integrated Modeling System) and density dynamics models for algae. This approach enabled assessment of ecological risk when the exposure concentration shows spatiotemporal variation. First, risk maps of 5 herbicides (pretilachlor, butachlor, simetryn, mefenacet, and esprocarb) were created from the spatial predictions of environmental concentrations and 50% inhibitory concentrations of the herbicides. Simulations of algal density dynamics at high-risk sites were then conducted by incorporating the predicted temporal dynamics of the environmental concentration of each herbicide at the sites. The results suggested that the risk of pretilachlor was clearly the highest of the 5 herbicides, in terms of both the spatial distributions and the temporal durations. The present study highlights the importance of integrating exposure models and effect models to clarify spatial and temporal risk and to develop management plans for chemical exposure that shows high spatiotemporal variation.
A System Dynamics Model for Integrated Decision Making: The Durham-Orange Light Rail Project
EPA’s Sustainable and Healthy Communities Research Program (SHC) is conducting transdisciplinary research to inform and empower decision-makers. EPA tools and approaches are being developed to enable communities to effectively weigh and integrate human health, socioeconomic, envi...
Jung, Jinwoo; Lee, Jewon; Song, Hanjung
2011-03-01
This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performed simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-μm single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with ± 2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.
Jung, Jinwoo; Lee, Jewon; Song, Hanjung
2011-03-15
This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performed simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-{mu}m single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with {+-}2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.
NASA Astrophysics Data System (ADS)
Wang, Qianxi; Manmi, Kawa; Calvisi, Michael L.
2015-02-01
Ultrasound contrast agents (UCAs) are microbubbles stabilized with a shell typically of lipid, polymer, or protein and are emerging as a unique tool for noninvasive therapies ranging from gene delivery to tumor ablation. While various models have been developed to describe the spherical oscillations of contrast agents, the treatment of nonspherical behavior has received less attention. However, the nonspherical dynamics of contrast agents are thought to play an important role in therapeutic applications, for example, enhancing the uptake of therapeutic agents across cell membranes and tissue interfaces, and causing tissue ablation. In this paper, a model for nonspherical contrast agent dynamics based on the boundary integral method is described. The effects of the encapsulating shell are approximated by adapting Hoff's model for thin-shell, spherical contrast agents. A high-quality mesh of the bubble surface is maintained by implementing a hybrid approach of the Lagrangian method and elastic mesh technique. The numerical model agrees well with a modified Rayleigh-Plesset equation for encapsulated spherical bubbles. Numerical analyses of the dynamics of UCAs in an infinite liquid and near a rigid wall are performed in parameter regimes of clinical relevance. The oscillation amplitude and period decrease significantly due to the coating. A bubble jet forms when the amplitude of ultrasound is sufficiently large, as occurs for bubbles without a coating; however, the threshold amplitude required to incite jetting increases due to the coating. When a UCA is near a rigid boundary subject to acoustic forcing, the jet is directed towards the wall if the acoustic wave propagates perpendicular to the boundary. When the acoustic wave propagates parallel to the rigid boundary, the jet direction has components both along the wave direction and towards the boundary that depend mainly on the dimensionless standoff distance of the bubble from the boundary. In all cases, the jet
NASA Technical Reports Server (NTRS)
Thorp, Scott A.
1992-01-01
This presentation will discuss the development of a NASA Geometry Exchange Specification for transferring aerodynamic surface geometry between LeRC systems and grid generation software used for computational fluid dynamics research. The proposed specification is based on a subset of the Initial Graphics Exchange Specification (IGES). The presentation will include discussion of how the NASA-IGES standard will accommodate improved computer aided design inspection methods and reverse engineering techniques currently being developed. The presentation is in viewgraph format.
Uddin, Sardar M. Z.; Qin, Yi-Xian
2015-01-01
Disuse osteopenia and bone loss have been extensively reported in long duration space mission and long term bed rest. The pathology of the bone loss is similar to osteoporosis but highly confined to weight bearing bones. The current anabolic and/or anti-resorptive drugs have systemic effects and are costly over extended time, with concerns of long term fracture risk. This study use Low Intensity Pulsed Ultrasound (LIPUS) as a non-invasive acoustic force and anabolic stimulus to countermeasure disuse induced bone loss. Four-month old C57BL/6 mice were randomized to five groups, 1) age-matched (AM), 2) non-suspended sham (NS), 3) nonsuspended –LIPUS (NU), 4) suspended sham (SS), and 5) suspended-LIPUS (SU) groups. After four weeks of suspension, µCT analyses showed significant decreases in trabecular bone volume fraction (BV/TV) (−36%, p<0.005), bone tissue mineral density (TMD) (−3%, p<0.05), trabecular thickness (Tb.Th) (−12.5%, p<0.005), and increase in bone surface/bone volume (+BS/BV) (+16%, p<0.005), relative to age-matched (AM). Application of LIPUS for 20 min/day for 5 days/week, significantly increased TMD (+3%, p<0.05), Tb.Th (+6%, p<0.05), and decreased BS/BV (−10%, p<0.005), relative to suspension alone (SS) mice. Histomorphometry analyses showed a breakdown of bone microstructure under disuse conditions consist with µCT results. In comparison to SS mice, LIPUS treated bone showed increased structural integrity with increased bone formation rates at metaphysical endosteal and trabecular surfaces (+0.104±0.07 vs 0.031±0.30 µm3/µm2/d) relative to SS. Four-point bending mechanical tests of disused SS femurs showed reduced elastic modulus (−53%, p<0.05), yield (−33%, p<0.05) and ultimate strength (−45%, p<0.05) at the femoral diaphysis relative to AM bone. LIPUS stimulation mitigated the adverse effects of disuse on bone elastic modulus (+42%, p<0.05), yield strength (+29%, p<0.05), and ultimate strength (+39%, p<0.05) relative to SS
Park, Stephen; Li, Yebo
2015-05-01
Microalgal growth and systemic productivity is not only affected by environmental conditions such as temperature, irradiance, and nutrient concentrations, but also by physical processes such as fluid flow and particulate sedimentation. Modeling and simulating the system is a cost-effective way to predict the growth behavior under various environmental and physical conditions while determining effective engineering approaches to maximize productivity. Many mathematical models have been proposed to describe microalgal growth, while computational fluid dynamics (CFD) have been used to model the behavior of many fluid systems. Integrating the growth kinetics into a CFD model can help researchers understand the impact of a variety of parameters and determine what measures can be taken to overcome some obstacles in the aquaculture industry--self-shading, biomass sedimentation, and contamination--which prevent the production of high biomass yields. The aim of this study was to integrate physical and environmental effects to predict space- and time-dependent algal growth in industrial scale raceways. A commercial CFD software, ANSYS-Fluent 14.5, was used to solve the proposed models in regards to fluid flow, heat transfer, and nutrient balance. User-defined functions written in C language were used to incorporate the kinetic equations into a three-dimensional standard k-ε turbulence model of an open channel raceway system driven by a single paddlewheel. Simulated results were compared with light intensity, temperature, nutrient concentration, and algal biomass data acquired for 56 day from an industrial scale raceway pond constructed for the growth of Nannochloropsis salina and were observed to be in good agreement with one another. There was up to a 17.6% increase in simulated productivity when the incoming CO2 concentration was increased from 0.0006 to 0.150 g L(-1), while the effect of paddlewheel velocity was not significant. Sensitivity analysis showed that the model
NASA Astrophysics Data System (ADS)
Buenemann, Michaela
Despite a longstanding universal concern about and intensive research into woody plant encroachment (WPE)---the replacement of grasslands by shrub- and woodlands---our accumulated understanding of the process has either not been translated into sustainable rangeland management strategies or with only limited success. In order to increase our scientific insights into WPE, move us one step closer toward the sustainable management of rangelands affected by or vulnerable to the process, and identify needs for a future global research agenda, this dissertation presents an unprecedented critical, qualitative and quantitative assessment of the existing literature on the topic and evaluates the utility of an integrative remote sensing, GIS, and spatial modeling approach for quantifying the spatio-temporal dynamics of WPE. Findings from this research suggest that gaps in our current understanding of WPE and difficulties in devising sustainable rangeland management strategies are in part due to the complex spatio-temporal web of interactions between geoecological and anthropogenic variables involved in the process as well as limitations of presently available data and techniques. However, an in-depth analysis of the published literature also reveals that aforementioned problems are caused by two further crucial factors: the absence of information acquisition and reporting standards and the relative lack of long-term, large-scale, multi-disciplinary research efforts. The methodological framework proposed in this dissertation yields data that are easily standardized according to various criteria and facilitates the integration of spatially explicit data generated by a variety of studies. This framework may thus provide one common ground for scientists from a diversity of fields. Also, it has utility for both research and management. Specifically, this research demonstrates that the application of cutting-edge remote sensing techniques (Multiple Endmember Spectral Mixture
Wang, Kun; D'Argenio, David Z.; Acosta, Edward P.; Sheth, Anandi N.; Delille, Cecile; Lennox, Jeffrey L.; Kerstner-Wood, Corenna; Ofotokun, Ighovwerha
2014-01-01
Background Lopinavir (LPV)/ritonavir (RTV) co-formulation (LPV/RTV) is a widely used protease inhibitor (PI) based regimen to treat HIV-infection. As with all PIs, the trough concentration (Ctrough) is a primary determinant of response, but the optimum exposure remains poorly defined. The primary objective was to develop an integrated LPV population pharmacokinetic model to investigate the influence of α-1-acid glycoprotein (AAG) and link total and free LPV exposure to pharmacodynamic changes in HIV-1 RNA and assess viral dynamic and drug efficacy parameters. Methods Data from 35 treatment-naïve HIV-infected patients initiating therapy with LPV/RTV 400/100 mg orally twice daily across two studies were used for model development and simulations using ADAPT. Total LPV (LPVt) and RTV concentrations were measured by high-performance liquid chromatography (HPLC) with ultraviolet (UV) detection. Free LPV (LPVf) concentrations were measured using equilibrium dialysis and mass spectrometry. Results LPVt typical value of clearance (CLLPVt/F) was 4.73 L/h and distribution volume (VLPVt/F) was 55.7 L. Clearance (CLLPVf/F) and distibution volume (Vf/F) for LPVf were 596 L/h and 6370 L, respectively. Virion clearance rate was 0.0350 h-1. Simulated LPVLPVt Ctrough at 90% (EC90) and 95% (EC95) maximum response were 316 and 726 ng/mL, respectively. Conclusion The pharmacokinetic/pharmacodynamic model provides a useful tool to quantitatively describe the relationship between LPV/RTV exposure and viral response. This comprehensive modeling and simulation approach could be used as a surrogate assessment of ARV where adequate early phase dose-ranging studies are lacking in order to define target trough concentrations and possibly refine dosing recommendations. PMID:24311282
NASA Astrophysics Data System (ADS)
Munsky, Brian
2015-03-01
MAPK signal-activated transcription plays central roles in myriad biological processes including stress adaptation responses and cell fate decisions. Recent single-cell and single-molecule experiments have advanced our ability to quantify the spatial, temporal, and stochastic fluctuations for such signals and their downstream effects on transcription regulation. This talk explores how integrating such experiments with discrete stochastic computational analyses can yield quantitative and predictive understanding of transcription regulation in both space and time. We use single-molecule mRNA fluorescence in situ hybridization (smFISH) experiments to reveal locations and numbers of multiple endogenous mRNA species in 100,000's of individual cells, at different times and under different genetic and environmental perturbations. We use finite state projection methods to precisely and efficiently compute the full joint probability distributions of these mRNA, which capture measured spatial, temporal and correlative fluctuations. By combining these experimental and computational tools with uncertainty quantification, we systematically compare models of varying complexity and select those which give optimally precise and accurate predictions in new situations. We use these tools to explore two MAPK-activated gene regulation pathways. In yeast adaptation to osmotic shock, we analyze Hog1 kinase activation of transcription for three different genes STL1 (osmotic stress), CTT1 (oxidative stress) and HSP12 (heat shock). In human osteosarcoma cells under serum induction, we analyze ERK activation of c-Fos transcription.
NASA Astrophysics Data System (ADS)
Kurz, W. A.; Beukema, S. J.; Robinson, D. C.; Apps, M. J.
2001-12-01
Forest inventories and growth and yield projection systems are an integral part of modern forest management. This information is commonly used for the long-term planning of annual allowable cuts and timber supply analysis. A strategy for the use of such information in a comprehensive, regional carbon budget model was developed and implemented for British Columbia, Canada. Data readily accessible from forest information systems include the area, stratification and attributes (including merchantable volume) of forests. Growth and yield tables or empirical models provide the required information on stand dynamics. Disturbance statistics (harvest, fire, insects) describe the dynamics of the forest area. Temporary and permanent sample plots provide millions of tree measurements that were used in the conversion of volume to biomass estimates. Methods previously developed for the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS2) were used to calculate belowground biomass and to establish the various dead organic matter pools. Inventory data are nearly complete, except for a small portion of the total forest area. Land-use change statistics are available for forest roads, but not yet for other causes of land-use change. A modified version of the CBM-CFS2 was used to calculate C stocks and stock changes for the period 2000 to 2032. Results indicate that ecosystem C stocks in the timber harvest land base are changing very little, with between-year variability of - 20 to + 20 Tg C / year. In contrast, ecosystem C stocks in the non-timber harvest land base are increasing at a rate of about 100 Tg C / year, largely because of the absence of harvesting and the assumed rates of future fire and insect disturbances, which could be the result of protection efforts. Actual disturbance rates, observed in future years, could have large impacts on C stock changes. Annual changes in C stocks will also be influenced by climate variability. Growth and yield models predict
A climate game based on a Multi-Actor Dynamic Integrated Assessment Model (MADIAM)
NASA Astrophysics Data System (ADS)
Weber, M.; Hasselmann, K.
2003-04-01
In November 2002 a special exhibition on climate issues opened in the German Museum for Science and Techniques ('Deutsches Museum') in Munich. Within this exposition we present an interactive game in which visitors control future climate policy by adopting the role of either the government, a CEO (Chief Executive Officer) of a global company or a typical private household of an industrialized country. The players endeavor to maintain a sustainable climate in the future (global goal) while pursuing their own individual welfare goals. Task of the exhibition visitor is to combine the personal interests of the actor he is adopting with the global goal. The individual goal of government is maintain economic growth while avoiding conflicts due to inter-regional or societal inequalities. The CEO seeks to maximize total profits (business earnings). The goal of households is to maximize wages and interest earnings. The evolution of the economic system and climate is governed by the decisions of the actors. Government sets economic side conditions in terms of carbon taxes, subsidies for R&D or market infusion support for climate-friendly technologies, and transfers development aid to less advanced regions. The CEOs decide how much to invest in a number of alternative investment options and in which region. Households influences the economy by their purchasing and savings decisions. The model considers four regions, three real actors (mentioned above) and two different goods (climate-adverse and a climate-friendly). We introduce four different kinds of energy (coal, oil/gas, nuclear, renewable). A World Bank handles money flows. At different points in time the actors can cooperate with other actors in order to reach the global goal Stochastic elements regarding future technology and future climate are included. A touch-screen monitor with user friendly interface is used to present animations and videos. An animated climate scientist uses a climate simulator to compute future
Davis, Amy J; Hooten, Mevin B; Phillips, Michael L; Doherty, Paul F
2014-01-01
Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short-term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage-grouse (Centrocercus minimus). The long-term population index data available for Gunnison sage-grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage-grouse to be variable and slightly declining over the past 16 years. PMID:25540687
Davis, Amy J.; Hooten, Mevin B.; Phillips, Michael L.; Doherty, Paul F.
2014-01-01
Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short-term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage-grouse (Centrocercus minimus). The long-term population index data available for Gunnison sage-grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage-grouse to be variable and slightly declining over the past 16 years.
Owen, Nick A; Griffiths, Howard
2013-12-01
A system dynamics (SD) approach was taken to model crassulacean acid metabolism (CAM) expression from measured biochemical and physiological constants. SD emphasizes state-dependent feedback interaction to describe the emergent properties of a complex system. These mechanisms maintain biological systems with homeostatic limits on a temporal basis. Previous empirical studies on CAM have correlated biological constants (e.g. enzyme kinetic parameters) with expression over the CAM diel cycle. The SD model integrates these constants within the architecture of the CAM 'system'. This allowed quantitative causal connections to be established between biological inputs and the four distinct phases of CAM delineated by gas exchange and malic acid accumulation traits. Regulation at flow junctions (e.g. stomatal and mesophyll conductance, and malic acid transport across the tonoplast) that are subject to feedback control (e.g. stomatal aperture, malic acid inhibition of phosphoenolpyruvate carboxylase, and enzyme kinetics) was simulated. Simulated expression for the leaf-succulent Kalanchoë daigremontiana and more succulent tissues of Agave tequilana showed strong correlation with measured gas exchange and malic acid accumulation (R(2) = 0.912 and 0.937, respectively, for K. daigremontiana and R(2) = 0.928 and 0.942, respectively, for A. tequilana). Sensitivity analyses were conducted to quantitatively identify determinants of diel CO2 uptake. The transition in CAM expression from low to high volume/area tissues (elimination of phase II-IV carbon-uptake signatures) was achieved largely by the manipulation three input parameters. PMID:23992169
Owen, Nick A; Griffiths, Howard
2013-12-01
A system dynamics (SD) approach was taken to model crassulacean acid metabolism (CAM) expression from measured biochemical and physiological constants. SD emphasizes state-dependent feedback interaction to describe the emergent properties of a complex system. These mechanisms maintain biological systems with homeostatic limits on a temporal basis. Previous empirical studies on CAM have correlated biological constants (e.g. enzyme kinetic parameters) with expression over the CAM diel cycle. The SD model integrates these constants within the architecture of the CAM 'system'. This allowed quantitative causal connections to be established between biological inputs and the four distinct phases of CAM delineated by gas exchange and malic acid accumulation traits. Regulation at flow junctions (e.g. stomatal and mesophyll conductance, and malic acid transport across the tonoplast) that are subject to feedback control (e.g. stomatal aperture, malic acid inhibition of phosphoenolpyruvate carboxylase, and enzyme kinetics) was simulated. Simulated expression for the leaf-succulent Kalanchoë daigremontiana and more succulent tissues of Agave tequilana showed strong correlation with measured gas exchange and malic acid accumulation (R(2) = 0.912 and 0.937, respectively, for K. daigremontiana and R(2) = 0.928 and 0.942, respectively, for A. tequilana). Sensitivity analyses were conducted to quantitatively identify determinants of diel CO2 uptake. The transition in CAM expression from low to high volume/area tissues (elimination of phase II-IV carbon-uptake signatures) was achieved largely by the manipulation three input parameters.
A global unified metamodel of the biosphere (GUMBO) was developed to simulate the integrated earth system and assess the dynamics and values of ecosystem services. It is a `metamodel' in that it represents a synthesis and a simplification of several existing dynamic gl...
NASA Technical Reports Server (NTRS)
Kerstman, Eric; Minard, Charles; Saile, Lynn; Freiere deCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David
2010-01-01
The goals of the Integrated Medical Model (IMM) are to develop an integrated, quantified, evidence-based decision support tool useful to crew health and mission planners and to help align science, technology, and operational activities intended to optimize crew health, safety, and mission success. Presentation slides address scope and approach, beneficiaries of IMM capabilities, history, risk components, conceptual models, development steps, and the evidence base. Space adaptation syndrome is used to demonstrate the model's capabilities.
Vezzaro, L; Sharma, A K; Ledin, A; Mikkelsen, P S
2015-03-15
The estimation of micropollutant (MP) fluxes in stormwater systems is a fundamental prerequisite when preparing strategies to reduce stormwater MP discharges to natural waters. Dynamic integrated models can be important tools in this step, as they can be used to integrate the limited data provided by monitoring campaigns and to evaluate the performance of different strategies based on model simulation results. This study presents an example where six different control strategies, including both source-control and end-of-pipe treatment, were compared. The comparison focused on fluxes of heavy metals (copper, zinc) and organic compounds (fluoranthene). MP fluxes were estimated by using an integrated dynamic model, in combination with stormwater quality measurements. MP sources were identified by using GIS land usage data, runoff quality was simulated by using a conceptual accumulation/washoff model, and a stormwater retention pond was simulated by using a dynamic treatment model based on MP inherent properties. Uncertainty in the results was estimated with a pseudo-Bayesian method. Despite the great uncertainty in the MP fluxes estimated by the runoff quality model, it was possible to compare the six scenarios in terms of discharged MP fluxes, compliance with water quality criteria, and sediment accumulation. Source-control strategies obtained better results in terms of reduction of MP emissions, but all the simulated strategies failed in fulfilling the criteria based on emission limit values. The results presented in this study shows how the efficiency of MP pollution control strategies can be quantified by combining advanced modeling tools (integrated stormwater quality model, uncertainty calibration).
Vezzaro, L; Sharma, A K; Ledin, A; Mikkelsen, P S
2015-03-15
The estimation of micropollutant (MP) fluxes in stormwater systems is a fundamental prerequisite when preparing strategies to reduce stormwater MP discharges to natural waters. Dynamic integrated models can be important tools in this step, as they can be used to integrate the limited data provided by monitoring campaigns and to evaluate the performance of different strategies based on model simulation results. This study presents an example where six different control strategies, including both source-control and end-of-pipe treatment, were compared. The comparison focused on fluxes of heavy metals (copper, zinc) and organic compounds (fluoranthene). MP fluxes were estimated by using an integrated dynamic model, in combination with stormwater quality measurements. MP sources were identified by using GIS land usage data, runoff quality was simulated by using a conceptual accumulation/washoff model, and a stormwater retention pond was simulated by using a dynamic treatment model based on MP inherent properties. Uncertainty in the results was estimated with a pseudo-Bayesian method. Despite the great uncertainty in the MP fluxes estimated by the runoff quality model, it was possible to compare the six scenarios in terms of discharged MP fluxes, compliance with water quality criteria, and sediment accumulation. Source-control strategies obtained better results in terms of reduction of MP emissions, but all the simulated strategies failed in fulfilling the criteria based on emission limit values. The results presented in this study shows how the efficiency of MP pollution control strategies can be quantified by combining advanced modeling tools (integrated stormwater quality model, uncertainty calibration). PMID:25532057
Enabling model customization and integration
NASA Astrophysics Data System (ADS)
Park, Minho; Fishwick, Paul A.
2003-09-01
Until fairly recently, the idea of dynamic model content and presentation were treated synonymously. For example, if one was to take a data flow network, which captures the dynamics of a target system in terms of the flow of data through nodal operators, then one would often standardize on rectangles and arrows for the model display. The increasing web emphasis on XML, however, suggests that the network model can have its content specified in an XML language, and then the model can be represented in a number of ways depending on the chosen style. We have developed a formal method, based on styles, that permits a model to be specified in XML and presented in 1D (text), 2D, and 3D. This method allows for customization and personalization to exert their benefits beyond e-commerce, to the area of model structures used in computer simulation. This customization leads naturally to solving the bigger problem of model integration - the act of taking models of a scene and integrating them with that scene so that there is only one unified modeling interface. This work focuses mostly on customization, but we address the integration issue in the future work section.
Integration of physiology and fluid dynamics.
Schmalzriedt, Sven; Jenne, Marc; Mauch, Klaus; Reuss, Matthias
2003-01-01
The purpose of strategies for the integration of fluid dynamics and physiology is the development of more reliable simulation tools to accelerate the process of scale-up. The rigorous mathematical modeling of the richly interactive relationship between the dynamic response of biosystems and the physical environment changing in time and space must rest on the link between coupled momentum, energy and mass balances and structured modeling of the biophase. With the exponential increase in massive computer capabilities hard- and software tools became available for simulation strategies based on such holistic integration approaches. The review discusses fundamental aspects of application of computational fluid dynamics (CFD) to three-dimensional two-phase turbulence flow in stirred tank bioreactors. Examples of coupling momentum and material balance equations with simple unstructured kinetic models for the behavior of the biophase are used to illustrate the application of these strategies to the selection of suitable impeller configurations. The examples reviewed in this paper include distribution of carbon and energy source in fed batch cultures as well as dissolved oxygen fields during aerobic fermentations. A more precise forecasting of the impact of the multitude of interactions must, however, rest upon a rigorous understanding of the response of the cell factory to the complex dynamic stimulation due to space- and time-dependent concentration fields. The paper also introduces some ideas for fast and very fast experimental observations of intracellular pool concentrations based on stimulus response methods. These observations finally lead to a more complex integration approach based on the coupling of CFD and structured metabolic models.
Tian, Shiying; Youssef, Mohamed A; Skaggs, R Wayne; Amatya, Devendra M; Chescheir, G M
2012-01-01
We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model, which was adapted mainly from the 3-PG model. The forest growth model estimates net primary production, C allocation, and litterfall using physiology-based methods regulated by air temperature, water deficit, stand age, and soil N conditions. The performance of the newly developed DRAINMOD-FOREST model was evaluated using a long-term (21-yr) data set collected from an artificially drained loblolly pine ( L.) plantation in eastern North Carolina, USA. Results indicated that the DRAINMOD-FOREST accurately predicted annual, monthly, and daily drainage, as indicated by Nash-Sutcliffe coefficients of 0.93, 0.87, and 0.75, respectively. The model also predicted annual net primary productivity and dynamics of leaf area index reasonably well. Predicted temporal changes in the organic matter pool on the forest floor and in forest soil were reasonable compared to published literature. Both predicted annual and monthly nitrate export were in good agreement with field measurements, as indicated by Nash-Sutcliffe coefficients above 0.89 and 0.79 for annual and monthly predictions, respectively. This application of DRAINMOD-FOREST demonstrated its capability for predicting hydrology and C and N dynamics in drained forests under limited silvicultural practices.
Spatial integration and cortical dynamics.
Gilbert, C D; Das, A; Ito, M; Kapadia, M; Westheimer, G
1996-01-01
Cells in adult primary visual cortex are capable of integrating information over much larger portions of the visual field than was originally thought. Moreover, their receptive field properties can be altered by the context within which local features are presented and by changes in visual experience. The substrate for both spatial integration and cortical plasticity is likely to be found in a plexus of long-range horizontal connections, formed by cortical pyramidal cells, which link cells within each cortical area over distances of 6-8 mm. The relationship between horizontal connections and cortical functional architecture suggests a role in visual segmentation and spatial integration. The distribution of lateral interactions within striate cortex was visualized with optical recording, and their functional consequences were explored by using comparable stimuli in human psychophysical experiments and in recordings from alert monkeys. They may represent the substrate for perceptual phenomena such as illusory contours, surface fill-in, and contour saliency. The dynamic nature of receptive field properties and cortical architecture has been seen over time scales ranging from seconds to months. One can induce a remapping of the topography of visual cortex by making focal binocular retinal lesions. Shorter-term plasticity of cortical receptive fields was observed following brief periods of visual stimulation. The mechanisms involved entailed, for the short-term changes, altering the effectiveness of existing cortical connections, and for the long-term changes, sprouting of axon collaterals and synaptogenesis. The mutability of cortical function implies a continual process of calibration and normalization of the perception of visual attributes that is dependent on sensory experience throughout adulthood and might further represent the mechanism of perceptual learning. Images Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 PMID:8570604
NASA Astrophysics Data System (ADS)
Scheller, R. M.; Hua, D.; Bolstad, P. V.
2008-12-01
Total forest carbon (C) storage is determined by forest succession, multiple interacting disturbances, climate and the edaphic properties of a site or region, including soil texture and depth. How these complex processes interact will determine forest carbon dynamics at landscape and regional scales. We have developed a new succession extension for the LANDIS-II forest landscape simulation model that incorporates the belowground soil C dynamics of the Century soil model. This extension simulates three primary soil organic matter (SOM) pools (fast, slow, passive), litter dynamics, and nitrogen (N) feedbacks to overstory production. The extension was validated against data from the Willow Creek experimental forest in Wisconsin, USA. We subsequently initialized the full model to simulate forest dynamics of 10,000 ha of the surrounding forest landscape. We simulated a representative harvest regime and a historic wind throw regime (50 year wind rotation period, including light, moderate, and extreme events), two common disturbances in mesic forests of the Lake States. We also simulated forest change and total C storage assuming no atmospheric N deposition and N deposition equivalent to 2008 rates. Our results indicate a strong feedback from harvesting to litter C and the fast and slow SOM pools. The passive SOM pool was not significantly altered. Wind disturbance had a negligible effect on all pools. Simulations without N deposition significantly underestimated contemporary forest productivity and the system was more sensitive to disturbances when N deposition was excluded. In conclusion, we have developed a robust model of above and belowground C and N cycling that can readily plug into an existing forest modeling framework to simulate landscape and regional scale forest dynamics and the interactions among forest disturbances, climate change, and soil processes.
An Integrated Crustal Dynamics Simulator
NASA Astrophysics Data System (ADS)
Xing, H. L.; Mora, P.
2007-12-01
Numerical modelling offers an outstanding opportunity to gain an understanding of the crustal dynamics and complex crustal system behaviour. This presentation provides our long-term and ongoing effort on finite element based computational model and software development to simulate the interacting fault system for earthquake forecasting. A R-minimum strategy based finite-element computational model and software tool, PANDAS, for modelling 3-dimensional nonlinear frictional contact behaviour between multiple deformable bodies with the arbitrarily-shaped contact element strategy has been developed by the authors, which builds up a virtual laboratory to simulate interacting fault systems including crustal boundary conditions and various nonlinearities (e.g. from frictional contact, materials, geometry and thermal coupling). It has been successfully applied to large scale computing of the complex nonlinear phenomena in the non-continuum media involving the nonlinear frictional instability, multiple material properties and complex geometries on supercomputers, such as the South Australia (SA) interacting fault system, South California fault model and Sumatra subduction model. It has been also extended and to simulate the hot fractured rock (HFR) geothermal reservoir system in collaboration of Geodynamics Ltd which is constructing the first geothermal reservoir system in Australia and to model the tsunami generation induced by earthquakes. Both are supported by Australian Research Council.
Better HMC integrators for dynamical simulations
M.A. Clark, Balint Joo, A.D. Kennedy, P.J. Silva
2010-06-01
We show how to improve the molecular dynamics step of Hybrid Monte Carlo, both by tuning the integrator using Poisson brackets measurements and by the use of force gradient integrators. We present results for moderate lattice sizes.
NASA Astrophysics Data System (ADS)
Shi, Shanshan; Zhao, Bin
2015-04-01
Due to their low vapor pressure, semi-volatile organic compounds (SVOCs) can absorb onto other compartments in indoor environments, including settled dust. Incidental ingestion of settled dust-bound SVOCs contributes to the majority of daily non-dietary exposure to some SVOCs by human beings. With this pathway in mind, an integrated kinetic model to estimate indoor SVOC was developed to better predict the mass-fraction of SVOC associated with settled dust, which is important to accurately assess the non-dietary ingestion exposure to SVOC. In this integrated kinetic model, the aerosol dynamics were considered, including particle penetration, deposition and resuspension. The newly developed model was evaluated by comparing the predicted mass-fraction of SVOC associated with the settled dust (Xdust) and the measured Xdust from previous studies. Sixty Xdust values of thirty-eight different SVOCs measured in residences located in seven countries from four continents were involved in the model evaluation. The Xdust value predicted by the integrated kinetic model correlated linearly with the measured Xdust: y = 0.93x + 0.09 (R2 = 0.73), which indicates that the predicted Xdust by the integrated kinetic model are in good match with the measured data. This model may be utilized to predict SVOC concentrations in different indoor compartments, including dust-bound SVOC.
Sun, Huaiwei; Zhu, Yan; Yang, Jinzhong; Wang, Xiugui
2015-11-01
As the amount of water resources that can be utilized for agricultural production is limited, the reuse of treated wastewater (TWW) for irrigation is a practical solution to alleviate the water crisis in China. The process-based models, which estimate nitrogen dynamics under irrigation, are widely used to investigate the best irrigation and fertilization management practices in developed and developing countries. However, for modeling such a complex system for wastewater reuse, it is critical to conduct a sensitivity analysis to determine numerous input parameters and their interactions that contribute most to the variance of the model output for the development of process-based model. In this study, application of a comprehensive global sensitivity analysis for nitrogen dynamics was reported. The objective was to compare different global sensitivity analysis (GSA) on the key parameters for different model predictions of nitrogen and crop growth modules. The analysis was performed as two steps. Firstly, Morris screening method, which is one of the most commonly used screening method, was carried out to select the top affected parameters; then, a variance-based global sensitivity analysis method (extended Fourier amplitude sensitivity test, EFAST) was used to investigate more thoroughly the effects of selected parameters on model predictions. The results of GSA showed that strong parameter interactions exist in crop nitrogen uptake, nitrogen denitrification, crop yield, and evapotranspiration modules. Among all parameters, one of the soil physical-related parameters named as the van Genuchten air entry parameter showed the largest sensitivity effects on major model predictions. These results verified that more effort should be focused on quantifying soil parameters for more accurate model predictions in nitrogen- and crop-related predictions, and stress the need to better calibrate the model in a global sense. This study demonstrates the advantages of the GSA on a
Li, Liang; Chen, Zhiqiang; Cong, Wenxiang; Wang, Ge
2015-03-01
Spectral CT with photon counting detectors can significantly improve CT performance by reducing image noise and dose, increasing contrast resolution and material specificity, as well as enabling functional and molecular imaging with existing and emerging probes. However, the current photon counting detector architecture is difficult to balance the number of energy bins and the statistical noise in each energy bin. Moreover, the hardware support for multi-energy bins demands a complex circuit which is expensive. In this paper, we promote a new scheme known as hybrid detectors that combine the dynamic-threshold-based counting and integrating modes. In this scheme, an energy threshold can be dynamically changed during a spectral CT scan, which can be considered as compressive sensing along the spectral dimension. By doing so, the number of energy bins can be retrospectively specified, even in a spatially varying fashion. To establish the feasibility and merits of such hybrid detectors, we develop a tensor-based PRISM algorithm to reconstruct a spectral CT image from dynamic dual-energy data, and perform experiments with simulated and real data, producing very promising results.
Integrated modeling: a look back
NASA Astrophysics Data System (ADS)
Briggs, Clark
2015-09-01
This paper discusses applications and implementation approaches used for integrated modeling of structural systems with optics over the past 30 years. While much of the development work focused on control system design, significant contributions were made in system modeling and computer-aided design (CAD) environments. Early work appended handmade line-of-sight models to traditional finite element models, such as the optical spacecraft concept from the ACOSS program. The IDEAS2 computational environment built in support of Space Station collected a wider variety of existing tools around a parametric database. Later, IMOS supported interferometer and large telescope mission studies at JPL with MATLAB modeling of structural dynamics, thermal analysis, and geometric optics. IMOS's predecessor was a simple FORTRAN command line interpreter for LQG controller design with additional functions that built state-space finite element models. Specialized language systems such as CAESY were formulated and prototyped to provide more complex object-oriented functions suited to control-structure interaction. A more recent example of optical modeling directly in mechanical CAD is used to illustrate possible future directions. While the value of directly posing the optical metric in system dynamics terms is well understood today, the potential payoff is illustrated briefly via project-based examples. It is quite likely that integrated structure thermal optical performance (STOP) modeling could be accomplished in a commercial off-the-shelf (COTS) tool set. The work flow could be adopted, for example, by a team developing a small high-performance optical or radio frequency (RF) instrument.
NASA Astrophysics Data System (ADS)
Teoh, Lay Eng; Khoo, Hooi Ling
2013-09-01
This study deals with two major aspects of airlines, i.e. supply and demand management. The aspect of supply focuses on the mathematical formulation of an optimal fleet management model to maximize operational profit of the airlines while the aspect of demand focuses on the incorporation of mode choice modeling as parts of the developed model. The proposed methodology is outlined in two-stage, i.e. Fuzzy Analytic Hierarchy Process is first adopted to capture mode choice modeling in order to quantify the probability of probable phenomena (for aircraft acquisition/leasing decision). Then, an optimization model is developed as a probabilistic dynamic programming model to determine the optimal number and types of aircraft to be acquired and/or leased in order to meet stochastic demand during the planning horizon. The findings of an illustrative case study show that the proposed methodology is viable. The results demonstrate that the incorporation of mode choice modeling could affect the operational profit and fleet management decision of the airlines at varying degrees.
NASA Astrophysics Data System (ADS)
Bouwman, A. F.; Bierkens, M. F. P.; Griffioen, J.; Hefting, M. M.; Middelburg, J. J.; Middelkoop, H.; Slomp, C. P.
2013-01-01
In river basins, soils, groundwater, riparian zones and floodplains, streams, rivers, lakes and reservoirs act as successive filters in which the hydrology, ecology and biogeochemical processing are strongly coupled and together act to retain a significant fraction of the nutrients transported. This paper compares existing river ecology concepts with current approaches to describe river biogeochemistry, and assesses the value of these concepts and approaches for understanding the impacts of interacting global change disturbances on river biogeochemistry. Through merging perspectives, concepts, and modeling techniques, we propose integrated model approaches that encompass both aquatic and terrestrial components in heterogeneous landscapes. In this model framework, existing ecological and biogeochemical concepts are extended with a balanced approach for assessing nutrient and sediment delivery, on the one hand, and nutrient in-stream retention on the other hand.
NASA Astrophysics Data System (ADS)
Bouwman, A. F.; Bierkens, M. F. P.; Griffioen, J.; Hefting, M. M.; Middelburg, J. J.; Middelkoop, H.; Slomp, C. P.
2012-07-01
In river basins, soils, groundwater, riparian zones, streams, rivers, lakes and reservoirs act as successive filters in which the hydrology, ecology and biogeochemical processing are strongly coupled and together act to retain a significant fraction of the nutrients transported. This paper compares existing river ecology concepts with current approaches to describe river biogeochemistry, and assesses the value of these concepts and approaches for understanding the impacts of interacting global change disturbances on river biogeochemistry. Through merging perspectives, concepts, modeling techniques, we propose integrated model approaches that encompass both aquatic and terrestrial components in heterogeneous landscapes. In this model framework, existing ecological and biogeochemistry concepts are extended with a balanced approach for assessing nutrient and sediment delivery on the one hand, and nutrient in-stream retention on the other hand.
NASA Astrophysics Data System (ADS)
Blumstock, M. E.; Tetzlaff, D.; Nuetzmann, G.; Malcolm, I.; Soulsby, C.
2015-12-01
We combined multiple tracers with continuous groundwater level monitoring in a modelling framework to understand the spatio-temporal dynamics of influences of groundwater on runoff generation in a 3.2km2 catchment in the Scottish Highlands. The montane catchment is underlain by granite and metasediments and has extensive (70%) cover of diverse drift deposits which are up to 40m deep. Flat valley bottom areas fringing the stream channel are characterised by peat soil (0.5-4m deep) which cover about 20% of the catchment and receive drainage from upslope areas. Previous field and modelling work has identified dominant sources of runoff at the catchment-scale and the associated landscape controls on their dynamics and associated transit times. Whilst these studies have emphasised the importance of riparian wetlands as the dominant source of runoff, groundwater discharge provides both an important source of water to these wetlands throughout most of the year, as well as a direct flux into the channel network to sustain the lowest flows. Synoptic hydrogeochemical surveys were carried out on four occasions as flows declined during a 10 year return drought period. Samples were analysed for major anions, cations and water isotopes. Stream chemistry changes showed marked spatial variability implying geochemical differences in the bedrock geology and the distribution of storage in drift deposits. Temporal dynamics inferred heterogeneous montane groundwater bodies contributing to runoff generation differentially during the recession. Modelling confirmed that largest sources of groundwater appear to be located in drifts in the lower catchment where the most marked increase in weathering-derived ions occurred and depleted, non-fractionated isotope signatures implied deeper inflows.
An Integrated Model Recontextualized
ERIC Educational Resources Information Center
O'Meara, KerryAnn; Saltmarsh, John
2016-01-01
In this commentary, authors KerryAnn O'Meara and John Saltmarsh reflect on their 2008 "Journal of Higher Education Outreach and Engagement" article "An Integrated Model for Advancing the Scholarship of Engagement: Creating Academic Homes for the Engaged Scholar," reprinted in this 20th anniversary issue of "Journal of…
NASA Technical Reports Server (NTRS)
Butler, Douglas J.; Kerstman, Eric
2010-01-01
This slide presentation reviews the goals and approach for the Integrated Medical Model (IMM). The IMM is a software decision support tool that forecasts medical events during spaceflight and optimizes medical systems during simulations. It includes information on the software capabilities, program stakeholders, use history, and the software logic.
NASA Astrophysics Data System (ADS)
Forkel, Matthias; Carvalhais, Nuno; Schaphoff, Sibyll; von Bloh, Werner; Thurner, Martin; Thonicke, Kirsten
2014-05-01
Recently produced satellite datasets of vegetation greenness demonstrate a widespread greening of the earth in the last three decades. These positive trends in vegetation greenness are related to changes in leaf area, vegetation cover and photosynthetic activity. Climatic changes, CO2 fertilization, disturbances and other land cover changes are potential drivers of these greening trends. Nevertheless, different satellite datasets show different magnitudes and trends in vegetation greenness. This fact raises the question about the reliability of these datasets. On the other hand, global vegetation models can be potentially used to assess the effects of environmental drivers on vegetation greenness and thus to explore the environmental reliability of these datasets. Unfortunately, current vegetation models have several weaknesses in reproducing observed temporal dynamics in vegetation greenness. Our aim is to integrate multiple earth observation data sets in a dynamic global vegetation model in order to 1) improve the model's capability to reproduce observed dynamics and spatial patterns of vegetation greenness and 2) to assess the spatial and temporal importance of environmental drivers for the seasonal to decadal variability of vegetation greenness. For this purpose, we developed a data integration system for the LPJmL dynamic global vegetation model (LPJmL-DIS). We implemented a new phenology scheme in LPJmL to better represent observed temporal dynamics of FAPAR (fraction of absorbed photosynthetic active radiation). Model parameters were globally optimized using a genetic optimization algorithm. The model optimization was performed globally against 30 year FAPAR time series (GIMMS3g dataset), against 10 year albedo time series (MODIS) and global patterns of gross primary production as up-scaled from FLUXNET eddy covariance measurements. Additionally, we directly prescribed satellite observations of land and tree cover in LPJmL to better represent global
Vortmeier, Gerrit; DeLuca, Stephanie H; Els-Heindl, Sylvia; Chollet, Constance; Scheidt, Holger A; Beck-Sickinger, Annette G; Meiler, Jens; Huster, Daniel
2015-01-01
The peptide hormone ghrelin activates the growth hormone secretagogue receptor 1a, also known as the ghrelin receptor. This 28-residue peptide is acylated at Ser3 and is the only peptide hormone in the human body that is lipid-modified by an octanoyl group. Little is known about the structure and dynamics of membrane-associated ghrelin. We carried out solid-state NMR studies of ghrelin in lipid vesicles, followed by computational modeling of the peptide using Rosetta. Isotropic chemical shift data of isotopically labeled ghrelin provide information about the peptide's secondary structure. Spin diffusion experiments indicate that ghrelin binds to membranes via its lipidated Ser3. Further, Phe4, as well as electrostatics involving the peptide's positively charged residues and lipid polar headgroups, contribute to the binding energy. Other than the lipid anchor, ghrelin is highly flexible and mobile at the membrane surface. This observation is supported by our predicted model ensemble, which is in good agreement with experimentally determined chemical shifts. In the final ensemble of models, residues 8-17 form an α-helix, while residues 21-23 and 26-27 often adopt a polyproline II helical conformation. These helices appear to assist the peptide in forming an amphipathic conformation so that it can bind to the membrane. PMID:25803439
Integrated Environmental Control Model
1999-09-03
IECM is a powerful multimedia engineering software program for simulating an integrated coal-fired power plant. It provides a capability to model various conventional and advanced processes for controlling air pollutant emissions from coal-fired power plants before, during, or after combustion. The principal purpose of the model is to calculate the performance, emissions, and cost of power plant configurations employing alternative environmental control methods. The model consists of various control technology modules, which may be integratedmore » into a complete utility plant in any desired combination. In contrast to conventional deterministic models, the IECM offers the unique capability to assign probabilistic values to all model input parameters, and to obtain probabilistic outputs in the form of cumulative distribution functions indicating the likelihood of dofferent costs and performance results. A Graphical Use Interface (GUI) facilitates the configuration of the technologies, entry of data, and retrieval of results.« less
A dynamic integrated fault diagnosis method for power transformers.
Gao, Wensheng; Bai, Cuifen; Liu, Tong
2015-01-01
In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified.
A Dynamic Integrated Fault Diagnosis Method for Power Transformers
Gao, Wensheng; Liu, Tong
2015-01-01
In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified. PMID:25685841
NASA Technical Reports Server (NTRS)
Bellan, J.
1979-01-01
A practical situation of an enclosure fire is presented and why the need for a fire dynamic model is addressed. The difficulties in establishing a model are discussed, along with a brief review of enclosure fire models available. The approximation of the practical situation and the model developed are presented.
NASA Astrophysics Data System (ADS)
Newton, J.; Devol, A.; Kawase, M.; Alford, M.; Warner, M.; Mickett, J.; Ruef, W.; Bassin, C.
2008-12-01
Hood Canal (Washington State, USA) is a classic fjord estuary with a shallow sill and sluggish circulation. Recent increases in summer bottom water hypoxia have led to a comprehensive scientific study to support management initiated corrective actions. Through this program, 4 autonomous moored profiling systems (ORCA buoys) and moored ADCPs have been deployed in Hood Canal, maintained as part of NANOOS. Each buoy system collects high frequency (bi-hourly) profiles of chemical, physical, and biological variables using meteorological sensors and an underwater instrument package. A major fish kill occurred in southern Hood Canal on September 19, 2006, near a marine preserve. Moored profiler data suggest this fish kill was caused by the combination of the gradual summer depletion of deep- water oxygen, followed by the annual intrusion of dense Pacific Ocean water, which displaced the oxygen poor water to just under the pycnocline. Finally an upwelling-favorable wind event moved the surface water layer northwards resulting in outcrops of low oxygen water at the surface. Within 12 hours the surface oxygen concentration decreased to ~0.6 mg/L. The event lasted ~24 hours and ended abruptly. ROMS model output simulated the outcropping dynamics of the subsurface (low oxygen) waters to the surface during southerly winds. In addition to these dynamics, current meter data reveal a seasonal subsurface jet of low oxygen water advecting toward the fish kill area from the lower, shallower, and more populated region of Hood Canal. These data provide insights into the mechanisms of the fish kills and also provide fisheries managers with real-time data to help mitigate such events.
Integrative modeling of the cardiac ventricular myocyte
Winslow, Raimond L.; Cortassa, Sonia; O'Rourke, Brian; Hashambhoy, Yasmin L.; Rice, John Jeremy; Greenstein, Joseph L.
2011-01-01
Cardiac electrophysiology is a discipline with a rich 50-year history of experimental research coupled with integrative modeling which has enabled us to achieve a quantitative understanding of the relationships between molecular function and the integrated behavior of the cardiac myocyte in health and disease. In this paper, we review the development of integrative computational models of the cardiac myocyte. We begin with a historical overview of key cardiac cell models that helped shape the field. We then narrow our focus to models of the cardiac ventricular myocyte and describe these models in the context of their subcellular functional systems including dynamic models of voltage-gated ion channels, mitochondrial energy production, ATP-dependent and electrogenic membrane transporters, intracellular Ca dynamics, mechanical contraction, and regulatory signal transduction pathways. We describe key advances and limitations of the models as well as point to new directions for future modeling research. PMID:20865780
NASA Astrophysics Data System (ADS)
Bocaniov, Serghei A.; Scavia, Donald
2016-06-01
Hypoxia or low bottom water dissolved oxygen (DO) is a world-wide problem of management concern requiring an understanding and ability to monitor and predict its spatial and temporal dynamics. However, this is often made difficult in large lakes and coastal oceans because of limited spatial and temporal coverage of field observations. We used a calibrated and validated three-dimensional ecological model of Lake Erie to extend a statistical relationship between hypoxic extent and bottom water DO concentrations to explore implications of the broader temporal and spatial development and dissipation of hypoxia. We provide the first numerical demonstration that hypoxia initiates in the nearshore, not the deep portion of the basin, and that the threshold used to define hypoxia matters in both spatial and temporal dynamics and in its sensitivity to climate. We show that existing monitoring programs likely underestimate both maximum hypoxic extent and the importance of low oxygen in the nearshore, discuss implications for ecosystem and drinking water protection, and recommend how these results could be used to efficiently and economically extend monitoring programs.
Integrated Assessment Modeling
Edmonds, James A.; Calvin, Katherine V.; Clarke, Leon E.; Janetos, Anthony C.; Kim, Son H.; Wise, Marshall A.; McJeon, Haewon C.
2012-10-31
This paper discusses the role of Integrated Assessment models (IAMs) in climate change research. IAMs are an interdisciplinary research platform, which constitutes a consistent scientific framework in which the large-scale interactions between human and natural Earth systems can be examined. In so doing, IAMs provide insights that would otherwise be unavailable from traditional single-discipline research. By providing a broader view of the issue, IAMs constitute an important tool for decision support. IAMs are also a home of human Earth system research and provide natural Earth system scientists information about the nature of human intervention in global biogeophysical and geochemical processes.
ERIC Educational Resources Information Center
Walsh, Jim; McGehee, Richard
2013-01-01
A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…
Horizontal integration and cortical dynamics.
Gilbert, C D
1992-07-01
We have discussed several results that lead to a view that cells in the visual system are endowed with dynamic properties, influenced by context, expectation, and long-term modifications of the cortical network. These observations will be important for understanding how neuronal ensembles produce a system that perceives, remembers, and adapts to injury. The advantage to being able to observe changes at early stages in a sensory pathway is that one may be able to understand the way in which neuronal ensembles encode and represent images at the level of their receptive field properties, of cortical topographies, and of the patterns of connections between cells participating in a network.
NASA Astrophysics Data System (ADS)
Castelletti, A.; Galelli, S.; Goedbloed, A.
2015-12-01
Retention basins and urban reservoirs are increasingly used to support drinking water supply in large metropolitan contexts, since they make use of a resource, i.e., stormwater, that would be otherwise wasted, thus limiting the amount of water extracted from natural systems or produced with energy-intensive techniques. Yet, the operation of these infrastructures faces a twofold challenge. First, the presence of large impervious areas in urban catchments results in high discharge peaks and runoff volumes and a fast runoff response to rainfall, with consequent very short times of concentration. Second, stormwater transports large amount of pollutants to the receiving water bodies. This paper contributes a novel High-Performance Integrated Control framework to support the real-time operation of urban water supply storages affected by water quality problems. We use a 3D hydrodynamic, high-fidelity, simulation model to predict the main water quality dynamics and inform a real-time controller based on Model Predictive Control. We integrate the simulation model into the control scheme by a model reduction process, where the high-fidelity simulator is first used to identify and then replaced by a low-order dynamic emulator, which runs orders of magnitude faster. The framework is used to design the hourly operation of Marina Reservoir, a 3.2 Mm3 stormwater-fed reservoir located in the centre of Singapore operated for drinking water supply and flood control. Because of its recent formation from a former estuary, the reservoir suffers from high salinity levels, whose dynamics is modelled with Delft3D-FLOW. Results show that the real-time operation designed by our framework drops the minimum salinity levels of nearly 30% while reducing the average annual deficit of drinking water supply by about two times the active storage of the reservoir. Such a win-win solution is obtained by means of a model reduction process that reduced the dimensionality of Delft3D-FLOW by three orders
Jensen, Dan B; Hogeveen, Henk; De Vries, Albert
2016-09-01
Rapid detection of dairy cow mastitis is important so corrective action can be taken as soon as possible. Automatically collected sensor data used to monitor the performance and the health state of the cow could be useful for rapid detection of mastitis while reducing the labor needs for monitoring. The state of the art in combining sensor data to predict clinical mastitis still does not perform well enough to be applied in practice. Our objective was to combine a multivariate dynamic linear model (DLM) with a naïve Bayesian classifier (NBC) in a novel method using sensor and nonsensor data to detect clinical cases of mastitis. We also evaluated reductions in the number of sensors for detecting mastitis. With the DLM, we co-modeled 7 sources of sensor data (milk yield, fat, protein, lactose, conductivity, blood, body weight) collected at each milking for individual cows to produce one-step-ahead forecasts for each sensor. The observations were subsequently categorized according to the errors of the forecasted values and the estimated forecast variance. The categorized sensor data were combined with other data pertaining to the cow (week in milk, parity, mastitis history, somatic cell count category, and season) using Bayes' theorem, which produced a combined probability of the cow having clinical mastitis. If this probability was above a set threshold, the cow was classified as mastitis positive. To illustrate the performance of our method, we used sensor data from 1,003,207 milkings from the University of Florida Dairy Unit collected from 2008 to 2014. Of these, 2,907 milkings were associated with recorded cases of clinical mastitis. Using the DLM/NBC method, we reached an area under the receiver operating characteristic curve of 0.89, with a specificity of 0.81 when the sensitivity was set at 0.80. Specificities with omissions of sensor data ranged from 0.58 to 0.81. These results are comparable to other studies, but differences in data quality, definitions of
Jensen, Dan B; Hogeveen, Henk; De Vries, Albert
2016-09-01
Rapid detection of dairy cow mastitis is important so corrective action can be taken as soon as possible. Automatically collected sensor data used to monitor the performance and the health state of the cow could be useful for rapid detection of mastitis while reducing the labor needs for monitoring. The state of the art in combining sensor data to predict clinical mastitis still does not perform well enough to be applied in practice. Our objective was to combine a multivariate dynamic linear model (DLM) with a naïve Bayesian classifier (NBC) in a novel method using sensor and nonsensor data to detect clinical cases of mastitis. We also evaluated reductions in the number of sensors for detecting mastitis. With the DLM, we co-modeled 7 sources of sensor data (milk yield, fat, protein, lactose, conductivity, blood, body weight) collected at each milking for individual cows to produce one-step-ahead forecasts for each sensor. The observations were subsequently categorized according to the errors of the forecasted values and the estimated forecast variance. The categorized sensor data were combined with other data pertaining to the cow (week in milk, parity, mastitis history, somatic cell count category, and season) using Bayes' theorem, which produced a combined probability of the cow having clinical mastitis. If this probability was above a set threshold, the cow was classified as mastitis positive. To illustrate the performance of our method, we used sensor data from 1,003,207 milkings from the University of Florida Dairy Unit collected from 2008 to 2014. Of these, 2,907 milkings were associated with recorded cases of clinical mastitis. Using the DLM/NBC method, we reached an area under the receiver operating characteristic curve of 0.89, with a specificity of 0.81 when the sensitivity was set at 0.80. Specificities with omissions of sensor data ranged from 0.58 to 0.81. These results are comparable to other studies, but differences in data quality, definitions of
Glacial integrative modelling.
Ganopolski, Andrey
2003-09-15
Understanding the mechanisms of past climate changes requires modelling of the complex interaction between all major components of the Earth system: atmosphere, ocean, cryosphere, lithosphere and biosphere. This paper reviews attempts at such an integrative approach to modelling climate changes during the glacial age. In particular, the roles of different factors in shaping glacial climate are compared based on the results of simulations with an Earth-system model of intermediate complexity, CLIMBER-2. It is shown that ice sheets, changes in atmospheric compositions, vegetation cover, and reorganization of the ocean thermohaline circulation play important roles in glacial climate changes. Another example of this approach is the modelling of two major types of abrupt glacial climate changes: Dansgaard-Oeschger and Heinrich events. Our results corroborate some of the early proposed mechanisms, which relate abrupt climate changes to the internal instability of the ocean thermohaline circulation and ice sheets. At the same time, it is shown that realistic representation of the temporal evolution of the palaeoclimatic background is crucial to simulate observed features of the glacial abrupt climate changes.
Glacial integrative modelling.
Ganopolski, Andrey
2003-09-15
Understanding the mechanisms of past climate changes requires modelling of the complex interaction between all major components of the Earth system: atmosphere, ocean, cryosphere, lithosphere and biosphere. This paper reviews attempts at such an integrative approach to modelling climate changes during the glacial age. In particular, the roles of different factors in shaping glacial climate are compared based on the results of simulations with an Earth-system model of intermediate complexity, CLIMBER-2. It is shown that ice sheets, changes in atmospheric compositions, vegetation cover, and reorganization of the ocean thermohaline circulation play important roles in glacial climate changes. Another example of this approach is the modelling of two major types of abrupt glacial climate changes: Dansgaard-Oeschger and Heinrich events. Our results corroborate some of the early proposed mechanisms, which relate abrupt climate changes to the internal instability of the ocean thermohaline circulation and ice sheets. At the same time, it is shown that realistic representation of the temporal evolution of the palaeoclimatic background is crucial to simulate observed features of the glacial abrupt climate changes. PMID:14558899
The path integral formulation of climate dynamics.
Navarra, Antonio; Tribbia, Joe; Conti, Giovanni
2013-01-01
The chaotic nature of the atmospheric dynamics has stimulated the applications of methods and ideas derived from statistical dynamics. For instance, ensemble systems are used to make weather predictions recently extensive, which are designed to sample the phase space around the initial condition. Such an approach has been shown to improve substantially the usefulness of the forecasts since it allows forecasters to issue probabilistic forecasts. These works have modified the dominant paradigm of the interpretation of the evolution of atmospheric flows (and oceanic motions to some extent) attributing more importance to the probability distribution of the variables of interest rather than to a single representation. The ensemble experiments can be considered as crude attempts to estimate the evolution of the probability distribution of the climate variables, which turn out to be the only physical quantity relevant to practice. However, little work has been done on a direct modeling of the probability evolution itself. In this paper it is shown that it is possible to write the evolution of the probability distribution as a functional integral of the same kind introduced by Feynman in quantum mechanics, using some of the methods and results developed in statistical physics. The approach allows obtaining a formal solution to the Fokker-Planck equation corresponding to the Langevin-like equation of motion with noise. The method is very general and provides a framework generalizable to red noise, as well as to delaying differential equations, and even field equations, i.e., partial differential equations with noise, for example, general circulation models with noise. These concepts will be applied to an example taken from a simple ENSO model.
The path integral formulation of climate dynamics.
Navarra, Antonio; Tribbia, Joe; Conti, Giovanni
2013-01-01
The chaotic nature of the atmospheric dynamics has stimulated the applications of methods and ideas derived from statistical dynamics. For instance, ensemble systems are used to make weather predictions recently extensive, which are designed to sample the phase space around the initial condition. Such an approach has been shown to improve substantially the usefulness of the forecasts since it allows forecasters to issue probabilistic forecasts. These works have modified the dominant paradigm of the interpretation of the evolution of atmospheric flows (and oceanic motions to some extent) attributing more importance to the probability distribution of the variables of interest rather than to a single representation. The ensemble experiments can be considered as crude attempts to estimate the evolution of the probability distribution of the climate variables, which turn out to be the only physical quantity relevant to practice. However, little work has been done on a direct modeling of the probability evolution itself. In this paper it is shown that it is possible to write the evolution of the probability distribution as a functional integral of the same kind introduced by Feynman in quantum mechanics, using some of the methods and results developed in statistical physics. The approach allows obtaining a formal solution to the Fokker-Planck equation corresponding to the Langevin-like equation of motion with noise. The method is very general and provides a framework generalizable to red noise, as well as to delaying differential equations, and even field equations, i.e., partial differential equations with noise, for example, general circulation models with noise. These concepts will be applied to an example taken from a simple ENSO model. PMID:23840577
Integrated Medical Model Overview
NASA Technical Reports Server (NTRS)
Myers, J.; Boley, L.; Foy, M.; Goodenow, D.; Griffin, D.; Keenan, A.; Kerstman, E.; Melton, S.; McGuire, K.; Saile, L.; Shah, R.; Garcia, Y.; Sirmons. B.; Walton, M.; Reyes, D.
2015-01-01
The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project.
An Integrated Vehicle Modeling Environment
NASA Technical Reports Server (NTRS)
Totah, Joseph J.; Kinney, David J.; Kaneshige, John T.; Agabon, Shane
1999-01-01
This paper describes an Integrated Vehicle Modeling Environment for estimating aircraft geometric, inertial, and aerodynamic characteristics, and for interfacing with a high fidelity, workstation based flight simulation architecture. The goals in developing this environment are to aid in the design of next generation intelligent fight control technologies, conduct research in advanced vehicle interface concepts for autonomous and semi-autonomous applications, and provide a value-added capability to the conceptual design and aircraft synthesis process. Results are presented for three aircraft by comparing estimates generated by the Integrated Vehicle Modeling Environment with known characteristics of each vehicle under consideration. The three aircraft are a modified F-15 with moveable canards attached to the airframe, a mid-sized, twin-engine commercial transport concept, and a small, single-engine, uninhabited aerial vehicle. Estimated physical properties and dynamic characteristics are correlated with those known for each aircraft over a large portion of the flight envelope of interest. These results represent the completion of a critical step toward meeting the stated goals for developing this modeling environment.
NASA Astrophysics Data System (ADS)
Bouchoms, Samuel; Van Oost, Kristof; Vanacker, Veerle
2015-04-01
erosion and export rates, both modern and averaged over the last millennium, fall into the published range. Mean erosion rate over the last 1000 years equals 4.6 t/ha over the entire catchment while the export rate is 1.2 t/ha. (ii) Carbon content in the erosion areas is well predicted for lower soil layers (from 20 to 80 cm) where no significant differences were found between observational and modeled C content. There is though a significant difference for the top soil where modeled mean is 0.92% compared to the 0.8% in observations. (iii) erosion and deposition's spatial patterns are relatively well represented: correspondence between erosion areas as extracted from the digital soil map and modeled erosion maps higher for slightly truncated areas than in high truncation areas (55% of the modeled erosions pixels correspond to a non-depositional area compared to 37%). Correspondence between the model and the soil map increases with the total deposition ranging from 19% to 30% Yet, the model overestimated the carbon content in depositional areas, where statistical differences between observed and modeled carbon amount were found for each soil layers. This indicates that other factors, not accounted for by the model, influence carbon turnover for these sites. They may have a different dynamic than eroding places, cycling carbon faster or transferring it quicker to higher depth. Overall, the results indicates that the model performs relatively well in predicting sediment fluxes and carbon amount on long time scale during transient simulation. They underline the importance of developing an integrated approach to understand the dynamic and interactions at the landscape scale.
Dynamical Modelling of Meteoroid Streams
NASA Astrophysics Data System (ADS)
Clark, David; Wiegert, P. A.
2012-10-01
Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required questionable assumptions and significant simplifications. Extending on the approach of Vaubaillon et al. (2005)1, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of frequency based on model parameter changes. To assist in model analysis we are developing interactive software to permit the “turning of knobs” of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. With this tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform cometary surface attributes and temporal activity. The software uses a single model definition and implementation throughout model verification, sample particle bin generation and integration, and analysis. It supports the adjustment with feedback of both independent and independent model values, with the intent of providing an interface supporting multivariate analysis. Propagations of measurement uncertainties and model parameter precisions are tracked rigorously throughout. We maintain a separation of the model itself from the abstract concepts of model definition, parameter manipulation, and real-time analysis and visualization. Therefore we are able to quickly adapt to fundamental model changes. It is hoped the tool will also be of use in other solar system dynamics problems. 1 Vaubaillon, J.; Colas, F.; Jorda, L. (2005) A new method to predict meteor showers. I. Description of the model. Astronomy and
Dynamic management of integrated residential energy systems
NASA Astrophysics Data System (ADS)
Muratori, Matteo
dissertation presents a bottom-up highly resolved model of a generic residential energy eco-system in the United States. The model is able to capture the entire energy footprint of an individual household, to include all appliances, space conditioning systems, in-home charging of plug-in electric vehicles, and any other energy needs, viewing residential and transportation energy needs as an integrated continuum. The residential energy eco-system model is based on a novel bottom-up approach that quantifies consumer energy use behavior. The incorporation of stochastic consumer behaviors allows capturing the electricity consumption of each residential specific end-use, providing an accurate estimation of the actual amount of available controllable resources, and for a better understanding of the potential of residential demand response programs. A dynamic energy management framework is then proposed to manage electricity consumption inside each residential energy eco-system. Objective of the dynamic energy management framework is to optimize the scheduling of all the controllable appliances and in-home charging of plug-in electric vehicles to minimize cost. Such an automated energy management framework is used to simulate residential demand response programs, and evaluate their impact on the electric power infrastructure. For instance, time-varying electricity pricing might lead to synchronization of the individual residential demands, creating pronounced rebound peaks in the aggregate demand that are higher and steeper than the original demand peaks that the time-varying electricity pricing structure intended to eliminate. The modeling tools developed in this study can serve as a virtual laboratory for investigating fundamental economic and policy-related questions regarding the interplay of individual consumers with energy use. The models developed allow for evaluating the impact of different energy policies, technology adoption, and electricity price structures on the total
NASA Astrophysics Data System (ADS)
Jarosław, J.; Szporak, S.; Verbeiren, B.; Batelaan, O.
2012-04-01
The effective protection of wetlands demands knowledge of hydrological processes, which can be appropriately analysed using distributed models. It is eminent that the calibration and verification of distributed models of catchments with significant wetland coverage have to focus on wetland-specific issues such as the hydrological response of natural vegetation, i.e. parameterisation and dynamics of vegetation. An important and useful parameter describing vegetation canopy structure in terrestrial ecosystems is the Leaf Area Index (LAI), which is closely related to photosynthesis, net primary productivity, evapotranspiration and interception storage capacity. LAI can be estimated with remote sensing data, its suitability to derive the actual state of vegetation is high. This study focuses on improving the interception capacity calculation in the distributed hydrological model WetSpa. The main objective is to integrate seasonal LAI data. Not only field measurements, but also remote sensing derived LAI data is integrated into a WetSpa model for the Upper Biebrza catchment (northeast Poland). Biebrza National Park is characterized by a significant coverage of wetland and large variation in vegetation types. The use of remote sensing derived LAI values considerably improves the assessment of the actual status of vegetation and its seasonal dynamics. Landsat Thematic Mapper images are used to represent the different vegetation stages during the growing season (near LAI minimum and LAI maximum). They are analysed and processed to estimate the interception storage capacity of plant communities typical for Biebrza River valley. LAI of different plant communities has been measured using LAI-2000, and empirical relationships between these measurements and several spectral vegetation indices were established using linear and non-linear regression analysis. The vegetation indices with the highest correlation and the strongest linear relationship regarding LAI are NDVI (R2 = 0
NASA Astrophysics Data System (ADS)
Curtu, Rodica; Mantilla, Ricardo; Fonley, Morgan; Cunha, Luciana K.; Small, Scott J.; Jay, Laurent O.; Krajewski, Witold F.
2014-09-01
We present a system of ordinary differential equations (ODEs) capable of reproducing simultaneously the aggregated behavior of changes in water storage in the hillslope surface, the unsaturated and the saturated soil layers and the channel that drains the hillslope. The system of equations can be viewed as a two-state integral-balance model for soil moisture and groundwater dynamics. Development of the model was motivated by the need for landscape representation through hillslopes and channels organized following stream drainage network topology. Such a representation, with the basic discretization unit of a hillslope, allows ODEs-based simulation of the water transport in a basin. This, in turn, admits the use of highly efficient numerical solvers that enable space-time scaling studies. The goal of this paper is to investigate whether a nonlinear ODE system can effectively replicate observations of water storage in the unsaturated and saturated layers of the soil. Our first finding is that a previously proposed ODE hillslope model, based on readily available data, is capable of reproducing streamflow fluctuations but fails to reproduce the interactions between the surface and subsurface components at the hillslope scale. However, the more complex ODE model that we present in this paper achieves this goal. In our model, fluxes in the soil are described using a Taylor expansion of the underlying storage flux relationship. We tested the model using data collected in the Shale Hills watershed, a 7.9-ha forested site in central Pennsylvania, during an artificial drainage experiment in August 1974 where soil moisture in the unsaturated zone, groundwater dynamics and surface runoff were monitored. The ODE model can be used as an alternative to spatially explicit hillslope models, based on systems of partial differential equations, which require more computational power to resolve fluxes at the hillslope scale. Therefore, it is appropriate to be coupled to runoff routing
Bhattacharyya, Samit; Bauch, Chris T
2012-06-01
In non-mandatory vaccination policies, individual choice can be a major driver of vaccine uptake. Choice thereby influences whether public health targets can be achieved. Individual vaccinating decisions can be influenced by perceptions of vaccine risks or infection risks. There is also the potential for non-vaccinators to strategically 'free-ride' on herd immunity provided by vaccinators. This strategic interaction between individuals generates a social dilemma--a conflict between self-interest and what is best for the group as a whole. Game theory and related mathematical approaches that couple mechanistic models of vaccinating decisions with mechanistic models of disease spread can capture this social dilemma and address relevant questions. The past decade has seen significant growth in the theoretical literature developing and analyzing such models. Here, we argue that using these models to address specific public health challenges will require more work that integrates information from empirical studies into the development and validation of such models, as well as more collaboration between mathematical modelers, psychologists, economists and public health experts.
Dynamical modelling of meteoroid streams
NASA Astrophysics Data System (ADS)
Clark, D. L.; Wiegert, P. A.
2014-07-01
Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required significant assumptions and simplifications. Extending on the approach of Vaubaillon et al. 2005, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of weights based on model parameter changes. To assist in model analysis we are developing interactive software to permit the "turning of knobs" of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. Using the tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform and time-variant cometary surface attributes and processes.
NASA Astrophysics Data System (ADS)
Rokni Lamooki, Gholam Reza; Shirazi, Amir H.; Mani, Ali R.
2015-05-01
Thyroid's main chemical reactions are employed to develop a mathematical model. The presented model is based on differential equations where their dynamics reflects many aspects of thyroid's behavior. Our main focus here is the well known, but not well understood, phenomenon so called as Wolff-Chaikoff effect. It is shown that the inhibitory effect of intake iodide on the rate of one single enzyme causes a similar effect as Wolff-Chaikoff. Besides this issue, the presented model is capable of revealing other complex phenomena of thyroid hormones homeostasis.
Adaptive Urban Dispersion Integrated Model
Wissink, A; Chand, K; Kosovic, B; Chan, S; Berger, M; Chow, F K
2005-11-03
Numerical simulations represent a unique predictive tool for understanding the three-dimensional flow fields and associated concentration distributions from contaminant releases in complex urban settings (Britter and Hanna 2003). Utilization of the most accurate urban models, based on fully three-dimensional computational fluid dynamics (CFD) that solve the Navier-Stokes equations with incorporated turbulence models, presents many challenges. We address two in this work; first, a fast but accurate way to incorporate the complex urban terrain, buildings, and other structures to enforce proper boundary conditions in the flow solution; second, ways to achieve a level of computational efficiency that allows the models to be run in an automated fashion such that they may be used for emergency response and event reconstruction applications. We have developed a new integrated urban dispersion modeling capability based on FEM3MP (Gresho and Chan 1998, Chan and Stevens 2000), a CFD model from Lawrence Livermore National Lab. The integrated capability incorporates fast embedded boundary mesh generation for geometrically complex problems and full three-dimensional Cartesian adaptive mesh refinement (AMR). Parallel AMR and embedded boundary gridding support are provided through the SAMRAI library (Wissink et al. 2001, Hornung and Kohn 2002). Embedded boundary mesh generation has been demonstrated to be an automatic, fast, and efficient approach for problem setup. It has been used for a variety of geometrically complex applications, including urban applications (Pullen et al. 2005). The key technology we introduce in this work is the application of AMR, which allows the application of high-resolution modeling to certain important features, such as individual buildings and high-resolution terrain (including important vegetative and land-use features). It also allows the urban scale model to be readily interfaced with coarser resolution meso or regional scale models. This talk
NASA Technical Reports Server (NTRS)
Townsend, Alan R.; Asner, Gregory P.; Bustamante, Mercedes M. C.
2001-01-01
Moist tropical forests comprise one of the world's largest and most diverse biomes, and exchange more carbon, water, and energy with the atmosphere than any other ecosystem. In recent decades, tropical forests have also become one of the globe's most threatened biomes, subjected to exceptionally high rates of deforestation and land degradation. Thus, the importance of and threats to tropical forests are undeniable, yet our understanding of basic ecosystem processes in both intact and disturbed portions of the moist tropics remains poorer than for almost any other major biome. Our approach in this project was to take a multi-scale, multi-tool approach to address two different problems. First, we wanted to test if land-use driven changes in the cycles of probable limiting nutrients in forest systems were a key driver in the frequently observed pattern of declining pasture productivity and carbon stocks. Given the enormous complexity of land use change in the tropics, in which one finds a myriad of different land use types and intensities overlain on varying climates and soil types, we also wanted to see if new remote sensing techniques would allow some novel links between parameters which could be sensed remotely, and key biogeochemical variables which cannot. Second, we addressed to general questions about the role of tropical forests in the global carbon cycle. First, we used a new approach for quantifying and minimizing non-biological artifacts in the NOAA/NASA AVHRR Pathfinder time series of surface reflectance data so that we could address potential links between Amazonian forest dynamics and ENSO cycles. Second, we showed that the disequilibrium in C-13 exchanged between land and atmosphere following tropical deforestation probably has a significant impact on the use of 13-CO2 data to predict regional fluxes in the global carbon cycle.
Moonsamy, Suri; Dash, Radha Charan; Soliman, Mahmoud E S
2014-04-23
Using integrated in-silico computational techniques, including homology modeling, structure-based and pharmacophore-based virtual screening, molecular dynamic simulations, per-residue energy decomposition analysis and atom-based 3D-QSAR analysis, we proposed ten novel compounds as potential CCR5-dependent HIV-1 entry inhibitors. Via validated docking calculations, binding free energies revealed that novel leads demonstrated better binding affinities with CCR5 compared to maraviroc, an FDA-approved HIV-1 entry inhibitor and in clinical use. Per-residue interaction energy decomposition analysis on the averaged MD structure showed that hydrophobic active residues Trp86, Tyr89 and Tyr108 contributed the most to inhibitor binding. The validated 3D-QSAR model showed a high cross-validated rcv2 value of 0.84 using three principal components and non-cross-validated r2 value of 0.941. It was also revealed that almost all compounds in the test set and training set yielded a good predicted value. Information gained from this study could shed light on the activity of a new series of lead compounds as potential HIV entry inhibitors and serve as a powerful tool in the drug design and development machinery.
Simulation of quantum dynamics with integrated photonics
NASA Astrophysics Data System (ADS)
Sansoni, Linda; Sciarrino, Fabio; Mataloni, Paolo; Crespi, Andrea; Ramponi, Roberta; Osellame, Roberto
2012-12-01
In recent years, quantum walks have been proposed as promising resources for the simulation of physical quantum systems. In fact it is widely adopted to simulate quantum dynamics. Up to now single particle quantum walks have been experimentally demonstrated by different approaches, while only few experiments involving many-particle quantum walks have been realized. Here we simulate the 2-particle dynamics on a discrete time quantum walk, built on an array of integrated waveguide beam splitters. The polarization independence of the quantum walk circuit allowed us to exploit the polarization entanglement to encode the symmetry of the two-photon wavefunction, thus the bunching-antibunching behavior of non interacting bosons and fermions has been simulated. We have also characterized the possible distinguishability and decoherence effects arising in such a structure. This study is necessary in view of the realization of a quantum simulator based on an integrated optical array built on a large number of beam splitters.
NASA Astrophysics Data System (ADS)
Charpentier, Arthur; Durand, Marilou
2015-07-01
In this paper, we investigate questions arising in Parsons and Geist (Bull Seismol Soc Am 102:1-11, 2012). Pseudo causal models connecting magnitudes and waiting times are considered, through generalized regression. We do use conditional model (magnitude given previous waiting time, and conversely) as an extension to joint distribution model described in Nikoloulopoulos and Karlis (Environmetrics 19: 251-269, 2008). On the one hand, we fit a Pareto distribution for earthquake magnitudes, where the tail index is a function of waiting time following previous earthquake; on the other hand, waiting times are modeled using a Gamma or a Weibull distribution, where parameters are functions of the magnitude of the previous earthquake. We use those two models, alternatively, to generate the dynamics of earthquake occurrence, and to estimate the probability of occurrence of several earthquakes within a year or a decade.
Mesoscale ocean dynamics modeling
mHolm, D.; Alber, M.; Bayly, B.; Camassa, R.; Choi, W.; Cockburn, B.; Jones, D.; Lifschitz, A.; Margolin, L.; Marsden, L.; Nadiga, B.; Poje, A.; Smolarkiewicz, P.; Levermore, D.
1996-05-01
This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The ocean is a very complex nonlinear system that exhibits turbulence on essentially all scales, multiple equilibria, and significant intrinsic variability. Modeling the ocean`s dynamics at mesoscales is of fundamental importance for long-time-scale climate predictions. A major goal of this project has been to coordinate, strengthen, and focus the efforts of applied mathematicians, computer scientists, computational physicists and engineers (at LANL and a consortium of Universities) in a joint effort addressing the issues in mesoscale ocean dynamics. The project combines expertise in the core competencies of high performance computing and theory of complex systems in a new way that has great potential for improving ocean models now running on the Connection Machines CM-200 and CM-5 and on the Cray T3D.
Model for macroevolutionary dynamics.
Maruvka, Yosef E; Shnerb, Nadav M; Kessler, David A; Ricklefs, Robert E
2013-07-01
The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21-87], which neglects extinction, or a simple birth-death (speciation-extinction) process. Here, we extend the more recent development of a generic, neutral speciation-extinction (of species)-origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom-sized taxonomic groups. The model's predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution. PMID:23781101
Model for macroevolutionary dynamics.
Maruvka, Yosef E; Shnerb, Nadav M; Kessler, David A; Ricklefs, Robert E
2013-07-01
The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21-87], which neglects extinction, or a simple birth-death (speciation-extinction) process. Here, we extend the more recent development of a generic, neutral speciation-extinction (of species)-origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom-sized taxonomic groups. The model's predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution.
Implicit integration methods for dislocation dynamics
Gardner, D. J.; Woodward, C. S.; Reynolds, D. R.; Hommes, G.; Aubry, S.; Arsenlis, A.
2015-01-20
In dislocation dynamics simulations, strain hardening simulations require integrating stiff systems of ordinary differential equations in time with expensive force calculations, discontinuous topological events, and rapidly changing problem size. Current solvers in use often result in small time steps and long simulation times. Faster solvers may help dislocation dynamics simulations accumulate plastic strains at strain rates comparable to experimental observations. Here, this paper investigates the viability of high order implicit time integrators and robust nonlinear solvers to reduce simulation run times while maintaining the accuracy of the computed solution. In particular, implicit Runge-Kutta time integrators are explored as a waymore » of providing greater accuracy over a larger time step than is typically done with the standard second-order trapezoidal method. In addition, both accelerated fixed point and Newton's method are investigated to provide fast and effective solves for the nonlinear systems that must be resolved within each time step. Results show that integrators of third order are the most effective, while accelerated fixed point and Newton's method both improve solver performance over the standard fixed point method used for the solution of the nonlinear systems.« less
Implicit integration methods for dislocation dynamics
Gardner, D. J.; Woodward, C. S.; Reynolds, D. R.; Hommes, G.; Aubry, S.; Arsenlis, A.
2015-01-20
In dislocation dynamics simulations, strain hardening simulations require integrating stiff systems of ordinary differential equations in time with expensive force calculations, discontinuous topological events, and rapidly changing problem size. Current solvers in use often result in small time steps and long simulation times. Faster solvers may help dislocation dynamics simulations accumulate plastic strains at strain rates comparable to experimental observations. Here, this paper investigates the viability of high order implicit time integrators and robust nonlinear solvers to reduce simulation run times while maintaining the accuracy of the computed solution. In particular, implicit Runge-Kutta time integrators are explored as a way of providing greater accuracy over a larger time step than is typically done with the standard second-order trapezoidal method. In addition, both accelerated fixed point and Newton's method are investigated to provide fast and effective solves for the nonlinear systems that must be resolved within each time step. Results show that integrators of third order are the most effective, while accelerated fixed point and Newton's method both improve solver performance over the standard fixed point method used for the solution of the nonlinear systems.
NASA Astrophysics Data System (ADS)
Garcon, V.; Paulmier, A.; Bretagnon, M.; Campos, F.; Dewitte, B.; Illig, S.; Maes, C.; Depretz de Gesincourt, O.; Scouarnec, L.; Grelet, J.; Coppola, L.; Oschlies, A.; Leblond, N.; Quispe, J.; Carrasco, E.
2015-12-01
In the current context of the ocean deoxygenation, OMZs are known to play a key-role on the evolution of climate (greenhouse gases) and on the ecosystems and fisheries (nitrogen loss, respiratory barrier, sulfidic events) at both local and global scales. One of the objectives of the AMOP (Activities of research dedicated to the Minimum of Oxygen in the eastern Pacific) project is to document the mechanisms associated with the OMZ variability from hourly to decadal timescales. The hypothesis is that the variability scale ranges are different at the oxycline compared to the OMZ core, and directly impact the OMZ recycling behavior acting as either a preservation or remineralization layer. Results from a mooring deployment off Callao put in evidence three main time scales of OMZ variability- intra daily, intra monthly and intra seasonally. A coupled model ROM-BioEBUS configuration of the Peruvian OMZ shows there is a marked longitudinal variability in the characteristics of the oxygen spectrum, indicative of a strong influence of mesoscale activity in shaping the OMZ structure offshore. Mooring data highlight oxygenation events occurring near the oxycline rather than within the core, and inducing a shift of the OMZ regime from organic matter preservation towards remineralisation.
Effect of dynamical interactions on integrated properties of globular clusters
NASA Astrophysics Data System (ADS)
Zhuang, Yulong; Zhang, Fenghui; Anders, Peter; Ruan, Zhifeng; Cheng, Liantao; Kang, Xiaoyu
2015-02-01
Globular clusters (GCs) are generally treated as natural validators of simple stellar population (SSP) models. However, there are still some differences between real GCs and SSPs. In this work, we use a direct N-body simulation code NBODY6 to study the influences of dynamical interactions, metallicity and primordial binaries on Milky Way GCs' integrated properties. Our models start with N = 100 000 stars, covering a metallicity range Z = 0.0001 ˜ 0.02, a subset of our models contain primordial binaries, resulting in a binary fraction as currently observed at a model age of GCs. Stellar evolution and external tidal field representative for an average Milky Way GC are taken into consideration. The integrated colours and Lick indices are calculated using BaSeL and Bluered stellar spectral libraries separately. By including dynamical interactions, our model clusters show integrated features (i.e. colours up to 0.01 mag bluer, Hβ up to 0.1 Å greater and [MgFe]' 0.05 Å smaller) making the clusters appear slightly younger than the model clusters without dynamical interactions. This effect is caused mainly by the preferential loss of low-mass stars which have a stronger contribution to redder passbands as well as different spectral features compared to higher mass stars. In addition, this effect is larger at lower metallicities. On the contrary, the incorporation of primordial binaries reduces this effect.
NASA Technical Reports Server (NTRS)
Glaese, John R.; Tobbe, Patrick A.
1986-01-01
The Space Station Mechanism Test Bed consists of a hydraulically driven, computer controlled six degree of freedom (DOF) motion system with which docking, berthing, and other mechanisms can be evaluated. Measured contact forces and moments are provided to the simulation host computer to enable representation of orbital contact dynamics. This report describes the development of a generalized math model which represents the relative motion between two rigid orbiting vehicles. The model allows motion in six DOF for each body, with no vehicle size limitation. The rotational and translational equations of motion are derived. The method used to transform the forces and moments from the sensor location to the vehicles' centers of mass is also explained. Two math models of docking mechanisms, a simple translational spring and the Remote Manipulator System end effector, are presented along with simulation results. The translational spring model is used in an attempt to verify the simulation with compensated hardware in the loop results.
NASA Astrophysics Data System (ADS)
Robinson, Patrick J.
Gasification has been used in industry on a relatively limited scale for many years, but it is emerging as the premier unit operation in the energy and chemical industries. The switch from expensive and insecure petroleum to solid hydrocarbon sources (coal and biomass) is occurring due to the vast amount of domestic solid resources, national security and global warming issues. Gasification (or partial oxidation) is a vital component of "clean coal" technology. Sulfur and nitrogen emissions can be reduced, overall energy efficiency is increased and carbon dioxide recovery and sequestration are facilitated. Gasification units in an electric power generation plant produce a fuel gas for driving combustion turbines. Gasification units in a chemical plant generate synthesis gas, which can be used to produce a wide spectrum of chemical products. Future plants are predicted to be hybrid power/chemical plants with gasification as the key unit operation. The coupling of an Integrated Gasification Combined Cycle (IGCC) with a methanol plant can handle swings in power demand by diverting hydrogen gas from a combustion turbine and synthesis gas from the gasifier to a methanol plant for the production of an easily-stored, hydrogen-consuming liquid product. An additional control degree of freedom is provided with this hybrid plant, fundamentally improving the controllability of the process. The idea is to base-load the gasifier and use the more responsive gas-phase units to handle disturbances. During the summer days, power demand can fluctuate up to 50% over a 12-hour period. The winter provides a different problem where spikes of power demand can go up 15% within the hour. The following dissertation develops a hybrid IGCC / methanol plant model, validates the steady-state results with a National Energy Technical Laboratory study, and tests a proposed control structure to handle these significant disturbances. All modeling was performed in the widely used chemical process
Modelling MIZ dynamics in a global model
NASA Astrophysics Data System (ADS)
Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto
2016-04-01
Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.
Ibáñez, J; Lavado Contador, J F; Schnabel, S; Martínez Valderrama, J
2016-02-15
An integrated dynamic model was used to evaluate the influence of climatic, soil, pastoral, economic and managerial factors on sheet erosion in rangelands of SW Spain (dehesas). This was achieved by means of a variance-based sensitivity analysis. Topsoil erodibility, climate change and a combined factor related to soil water storage capacity and the pasture production function were the factors which influenced water erosion the most. Of them, climate change is the main source of uncertainty, though in this study it caused a reduction in the mean and the variance of long-term erosion rates. The economic and managerial factors showed scant influence on soil erosion, meaning that it is unlikely to find such influence in the study area for the time being. This is because the low profitability of the livestock business maintains stocking rates at low levels. However, the potential impact of livestock, through which economic and managerial factors affect soil erosion, proved to be greater in absolute value than the impact of climate change. Therefore, if changes in some economic or managerial factors led to higher stocking rates in the future, significant increases in erosion rates would be expected.
Integrated Urban Dispersion Modeling Capability
Kosovic, B; Chan, S T
2003-11-03
Numerical simulations represent a unique predictive tool for developing a detailed understanding of three-dimensional flow fields and associated concentration distributions from releases in complex urban settings (Britter and Hanna 2003). The accurate and timely prediction of the atmospheric dispersion of hazardous materials in densely populated urban areas is a critical homeland and national security need for emergency preparedness, risk assessment, and vulnerability studies. The main challenges in high-fidelity numerical modeling of urban dispersion are the accurate prediction of peak concentrations, spatial extent and temporal evolution of harmful levels of hazardous materials, and the incorporation of detailed structural geometries. Current computational tools do not include all the necessary elements to accurately represent hazardous release events in complex urban settings embedded in high-resolution terrain. Nor do they possess the computational efficiency required for many emergency response and event reconstruction applications. We are developing a new integrated urban dispersion modeling capability, able to efficiently predict dispersion in diverse urban environments for a wide range of atmospheric conditions, temporal and spatial scales, and release event scenarios. This new computational fluid dynamics capability includes adaptive mesh refinement and it can simultaneously resolve individual buildings and high-resolution terrain (including important vegetative and land-use features), treat complex building and structural geometries (e.g., stadiums, arenas, subways, airplane interiors), and cope with the full range of atmospheric conditions (e.g. stability). We are developing approaches for seamless coupling with mesoscale numerical weather prediction models to provide realistic forcing of the urban-scale model, which is critical to its performance in real-world conditions.
Dynamic management of integrated residential energy systems
NASA Astrophysics Data System (ADS)
Muratori, Matteo
dissertation presents a bottom-up highly resolved model of a generic residential energy eco-system in the United States. The model is able to capture the entire energy footprint of an individual household, to include all appliances, space conditioning systems, in-home charging of plug-in electric vehicles, and any other energy needs, viewing residential and transportation energy needs as an integrated continuum. The residential energy eco-system model is based on a novel bottom-up approach that quantifies consumer energy use behavior. The incorporation of stochastic consumer behaviors allows capturing the electricity consumption of each residential specific end-use, providing an accurate estimation of the actual amount of available controllable resources, and for a better understanding of the potential of residential demand response programs. A dynamic energy management framework is then proposed to manage electricity consumption inside each residential energy eco-system. Objective of the dynamic energy management framework is to optimize the scheduling of all the controllable appliances and in-home charging of plug-in electric vehicles to minimize cost. Such an automated energy management framework is used to simulate residential demand response programs, and evaluate their impact on the electric power infrastructure. For instance, time-varying electricity pricing might lead to synchronization of the individual residential demands, creating pronounced rebound peaks in the aggregate demand that are higher and steeper than the original demand peaks that the time-varying electricity pricing structure intended to eliminate. The modeling tools developed in this study can serve as a virtual laboratory for investigating fundamental economic and policy-related questions regarding the interplay of individual consumers with energy use. The models developed allow for evaluating the impact of different energy policies, technology adoption, and electricity price structures on the total
Seeing the System: Dynamics and Complexity of Technology Integration in Secondary Schools
ERIC Educational Resources Information Center
Howard, Sarah K.; Thompson, Kate
2016-01-01
This paper introduces system dynamics modeling to understand, visualize and explore technology integration in schools, through the development of a theoretical model of technology-related change in teachers' practice. Technology integration is a dynamic social practice, within the social system of education. It is difficult, if not nearly…
Battery electrochemical nonlinear/dynamic SPICE model
Glass, M.C.
1996-12-31
An Integrated Battery Model has been produced which accurately represents DC nonlinear battery behavior together with transient dynamics. The NiH{sub 2} battery model begins with a given continuous-function electrochemical math model. The math model for the battery consists of the sum of two electrochemical process DC currents, which are a function of the battery terminal voltage. This paper describes procedures for realizing a voltage-source SPICE model which implements the electrochemical equations using behavioral sources. The model merges the essentially DC non-linear behavior of the electrochemical model, together with the empirical AC dynamic terminal impedance from measured data. Thus the model integrates the short-term linear impedance behavior, with the long-term nonlinear DC resistance behavior. The long-duration non-Faradaic capacitive behavior of the battery is represented by a time constant. Outputs of the model include battery voltage/current, state-of-charge, and charge-current efficiency.
Integrated Workforce Modeling System
NASA Technical Reports Server (NTRS)
Moynihan, Gary P.
2000-01-01
There are several computer-based systems, currently in various phases of development at KSC, which encompass some component, aspect, or function of workforce modeling. These systems may offer redundant capabilities and/or incompatible interfaces. A systems approach to workforce modeling is necessary in order to identify and better address user requirements. This research has consisted of two primary tasks. Task 1 provided an assessment of existing and proposed KSC workforce modeling systems for their functionality and applicability to the workforce planning function. Task 2 resulted in the development of a proof-of-concept design for a systems approach to workforce modeling. The model incorporates critical aspects of workforce planning, including hires, attrition, and employee development.
Integrable discrete PT symmetric model.
Ablowitz, Mark J; Musslimani, Ziad H
2014-09-01
An exactly solvable discrete PT invariant nonlinear Schrödinger-like model is introduced. It is an integrable Hamiltonian system that exhibits a nontrivial nonlinear PT symmetry. A discrete one-soliton solution is constructed using a left-right Riemann-Hilbert formulation. It is shown that this pure soliton exhibits unique features such as power oscillations and singularity formation. The proposed model can be viewed as a discretization of a recently obtained integrable nonlocal nonlinear Schrödinger equation.
Kalantari, A S; Cabrera, V E
2012-10-01
The objective of this study was to determine the effect of reproductive performance on dairy cattle herd value. Herd value was defined as the herd's average retention payoff (RPO). Individual cow RPO is the expected profit from keeping the cow compared with immediate replacement. First, a daily dynamic programming model was developed to calculate the RPO of all cow states in a herd. Second, a daily Markov chain model was applied to estimate the herd demographics. Finally, the herd value was calculated by aggregating the RPO of all cows in the herd. Cow states were described by 5 milk yield classes (76, 88, 100, 112, and 124% with respect to the average), 9 lactations, 750 d in milk, and 282 d in pregnancy. Five different reproductive programs were studied (RP1 to RP5). Reproductive program 1 used 100% timed artificial insemination (TAI; 42% conception rate for first TAI and 30% for second and later services) and the other programs combined TAI with estrus detection. The proportion of cows receiving artificial insemination after estrus detection ranged from 30 to 80%, and conception rate ranged from 25 to 35%. These 5 reproductive programs were categorized according to their 21-d pregnancy rate (21-d PR), which is an indication of the rate that eligible cows become pregnant every 21 d. The 21-d PR was 17% for RP1, 14% for RP2, 16% for RP3, 18% for RP4, and 20% for RP5. Results showed a positive relationship between 21-d PR and herd value. The most extreme herd value difference between 2 reproductive programs was $77/cow per yr for average milk yield (RP5 - RP2), $13/cow per yr for lowest milk yield (RP5 - RP1), and $160/cow per yr for highest milk yield (RP5 - RP2). Reproductive programs were ranked based on their calculated herd value. With the exception of the best reproductive program (RP5), all other programs showed some level of ranking change according to milk yield. The most dramatic ranking change was observed in RP1, which moved from being the worst ranked
Modeling Soil Freezing Dynamics
NASA Astrophysics Data System (ADS)
Flerchinger, G. N.; Seyfried, M. S.; Hardegree, S. P.
2002-12-01
Seasonally frozen soil strongly influences runoff and erosion on large areas of land around the world. In many areas, rain or snowmelt on seasonally frozen soil is the single leading cause of severe runoff and erosion events. As soils freeze, ice blocks the soil pores, greatly diminishing the permeability of the soil. This is aggravated by the tendency of water to migrate to the freezing front, causing elevated ice content and frost heave. Freezing and thawing of the soil are controlled by the complex interactions of heat and water transfer at the soil surface governed by meteorological and environmental conditions at the soil-atmosphere interface. Soil freezing dynamics including liquid water content, infiltration, and runoff simulated by the Simultaneous Heat and Water (SHAW) Model were tested at three field locations in southwest Idaho. Sites included: three soil types at the Orchard Field Test Site; bare and sagebrush-covered runoff plots at the Lower Sheep Creek site on the Reynolds Creek Experimental Watershed; and runoff plots on steep mountainous slopes on the Boise Front. Detailed simulations of soil freezing and thawing were conducted specifically to examine the dynamics of liquid water content during freezing and thawing. Freezing/thawing processes, including liquid water content and runoff, were simulated well.
Integrating Models and Observations
NASA Technical Reports Server (NTRS)
Womebarger, Amy
2011-01-01
For the past ten years, the coronal loops community has held bi-annual workshops to discuss the analysis of coronal loop observations and the latest efforts to model the loop structures. During this time, several heating scenarios have been proposed to explain loop observations. These heating scenarios rely on different heating frequencies, locations, and durations, as well as different loop sub-structure. Often the scenarios are developed to explain an observation, hence all heating scenarios match some observational criteria. The key to discriminating between the competing heating scenarios is to first identify the distinguishing observables. For instance, both effectively steady and nanoflare-heating scenarios can produce quasi-steady intensities. Observing quasi-steady intensities, then, does not help determine which heating scenario is most likely. These heating scenarios may, however, predict different velocities or different emission measure distributions. In this talk, I will discuss a few of the expected observations for some simple heating scenarios. I will ask the modeling community to calculate similar observations for the different heating scenarios to generate a standard list of expected observations. After the community develops this list, comparisons with actual loop observations can then distinguish the most likely heating scenario.
Multistage integration model for human egomotion perception.
Zacharias, G L; Miao, A X; Warren, R
1995-01-01
Human computational vision models that attempt to account for the dynamic perception of egomotion and relative depth typically assume a common three-stage process: first, compute the optical flow field based on the dynamically changing image; second, estimate the egomotion states based on the flow; and third, estimate the relative depth/shape based on the egomotion states and possibly on a model of the viewed surface. We propose a model more in line with recent work in human vision, employing multistage integration. Here the dynamic image is first processed to generate spatial and temporal image gradients that drive a mutually interconnected state estimator and depth/shape estimator. The state estimator uses the image gradient information in combination with a depth/shape estimate of the viewed surface and an assumed model of the viewer's dynamics to generate current state estimates; in tandem, the depth/shape estimator uses the image gradient information in combination with the viewer's state estimate and assumed shape model to generate current depth/shape estimates. In this paper, we describe the model and compare model predictions with empirical data.
Models for medical practice integration.
Harris, R M
1994-08-01
Decreased physician income, increased administrative burdens, and interference with the compassionate delivery of high-quality medical care are threatening the independent practice of medicine in solo and small group practices. Many established physicians, and the hospitals with which they relate, are searching for organizational models that, by integrating some or all aspects of their practices, will preserve incomes and reduce regulatory and administrative burdens. This article will describe several "practice integration models," pointing out advantages and disadvantages to physicians in established practices. (Many of the same arguments could be made for physicians new to practice, with different emphasis). The continuum of integration models is shown in figure 1, page 19. The group practice without walls and its two submodels, the independent group practice without walls (IGWW) and the affiliated medical practice corporation (AMPC) are more recent and more effective models and will be covered in depth in the article.
NASA Astrophysics Data System (ADS)
Zehe, Erwin; Jackisch, Conrad; Blume, Theresa; Haßler, Sibylle; Allroggen, Niklas; Tronicke, Jens
2013-04-01
The CAOS Research Unit recently proposed a hierarchical classification scheme to subdivide a catchment into what we vaguely name classes of functional entities that puts the gradients driving mass and energy flows and their controls on top of the hierarchy and the arrangement of landscape attributes controlling flow resistances along these driving gradients (for instance soil types and apparent preferential pathways) at the second level. We name these functional entities lead topology classes, to highlight that they are characterized by a spatially ordered arrangement of landscape elements along a superordinate driving gradient. Our idea is that these lead topology classes have a distinct way how their structural and textural architecture controls the interplay of storage dynamics and integral response behavior that is typical for all members of a class, but is dissimilar between different classes. This implies that we might gain exemplary understanding of the typical dynamic behavior of the class, when thoroughly studying a few class members. We propose that the main integral catchment functions mass export and drainage, mass redistribution and storage, energy exchange with the atmosphere, as well as energy redistribution and storage - result from spatially organized interactions of processes within lead topologies that operate at different scale levels and partly dominate during different conditions. We distinguish: 1) Lead topologies controlling the land surface energy balance during radiation driven conditions at the plot/pedon scale level. In this case energy fluxes dominate and deplete a vertical temperature gradient that is build up by depleting a gradient in radiation fluxes. Water is a facilitator in this concert due to the high specific heat of vaporization. Slow vertical water fluxes in soil dominate, which are driven by vertical gradients in atmospheric water potential, chemical potential in the plant and in soil hydraulic potentials. 2) Lead topologies
NASA Astrophysics Data System (ADS)
Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.
2016-01-01
Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.
Separations and safeguards model integration.
Cipiti, Benjamin B.; Zinaman, Owen
2010-09-01
Research and development of advanced reprocessing plant designs can greatly benefit from the development of a reprocessing plant model capable of transient solvent extraction chemistry. This type of model can be used to optimize the operations of a plant as well as the designs for safeguards, security, and safety. Previous work has integrated a transient solvent extraction simulation module, based on the Solvent Extraction Process Having Interaction Solutes (SEPHIS) code developed at Oak Ridge National Laboratory, with the Separations and Safeguards Performance Model (SSPM) developed at Sandia National Laboratory, as a first step toward creating a more versatile design and evaluation tool. The goal of this work was to strengthen the integration by linking more variables between the two codes. The results from this integrated model show expected operational performance through plant transients. Additionally, ORIGEN source term files were integrated into the SSPM to provide concentrations, radioactivity, neutron emission rate, and thermal power data for various spent fuels. This data was used to generate measurement blocks that can determine the radioactivity, neutron emission rate, or thermal power of any stream or vessel in the plant model. This work examined how the code could be expanded to integrate other separation steps and benchmark the results to other data. Recommendations for future work will be presented.
Path integral Liouville dynamics for thermal equilibrium systems
Liu, Jian
2014-06-14
We show a new imaginary time path integral based method—path integral Liouville dynamics (PILD), which can be derived from the equilibrium Liouville dynamics [J. Liu and W. H. Miller, J. Chem. Phys. 134, 104101 (2011)] in the Wigner phase space. Numerical tests of PILD with the simple (white noise) Langevin thermostat have been made for two strongly anharmonic model problems. Since implementation of PILD does not request any specific form of the potential energy surface, the results suggest that PILD offers a potentially useful approach for general condensed phase molecular systems to have the two important properties: conserves the quantum canonical distribution and recovers exact thermal correlation functions (of even nonlinear operators, i.e., nonlinear functions of position or momentum operators) in the classical, high temperature, and harmonic limits.
Dynamic metabolic models in context: biomass backtracking.
Tummler, Katja; Kühn, Clemens; Klipp, Edda
2015-08-01
Mathematical modeling has proven to be a powerful tool to understand and predict functional and regulatory properties of metabolic processes. High accuracy dynamic modeling of individual pathways is thereby opposed by simplified but genome scale constraint based approaches. A method that links these two powerful techniques would greatly enhance predictive power but is so far lacking. We present biomass backtracking, a workflow that integrates the cellular context in existing dynamic metabolic models via stoichiometrically exact drain reactions based on a genome scale metabolic model. With comprehensive examples, for different species and environmental contexts, we show the importance and scope of applications and highlight the improvement compared to common boundary formulations in existing metabolic models. Our method allows for the contextualization of dynamic metabolic models based on all available information. We anticipate this to greatly increase their accuracy and predictive power for basic research and also for drug development and industrial applications.
Cellular automata modeling of pedestrian's crossing dynamics.
Zhang, Jin; Wang, Hui; Li, Ping
2004-07-01
Cellular automata modeling techniques and the characteristics of mixed traffic flow were used to derive the 2-dimensional model presented here for simulation of pedestrian's crossing dynamics. A conception of "stop point" is introduced to deal with traffic obstacles and resolve conflicts among pedestrians or between pedestrians and the other vehicles on the crosswalk. The model can be easily extended, is very efficient for simulation of pedestrian's crossing dynamics, can be integrated into traffic simulation software, and has been proved feasible by simulation experiments.
Default Mode Dynamics for Global Functional Integration
Menon, David K.; Manktelow, Anne E.; Sahakian, Barbara J.; Stamatakis, Emmanuel A.
2015-01-01
The default mode network (DMN) has been traditionally assumed to hinder behavioral performance in externally focused, goal-directed paradigms and to provide no active contribution to human cognition. However, recent evidence suggests greater DMN activity in an array of tasks, especially those that involve self-referential and memory-based processing. Although data that robustly demonstrate a comprehensive functional role for DMN remains relatively scarce, the global workspace framework, which implicates the DMN in global information integration for conscious processing, can potentially provide an explanation for the broad range of higher-order paradigms that report DMN involvement. We used graph theoretical measures to assess the contribution of the DMN to global functional connectivity dynamics in 22 healthy volunteers during an fMRI-based n-back working-memory paradigm with parametric increases in difficulty. Our predominant finding is that brain modularity decreases with greater task demands, thus adapting a more global workspace configuration, in direct relation to increases in reaction times to correct responses. Flexible default mode regions dynamically switch community memberships and display significant changes in their nodal participation coefficient and strength, which may reflect the observed whole-brain changes in functional connectivity architecture. These findings have important implications for our understanding of healthy brain function, as they suggest a central role for the DMN in higher cognitive processing. SIGNIFICANCE STATEMENT The default mode network (DMN) has been shown to increase its activity during the absence of external stimulation, and hence was historically assumed to disengage during goal-directed tasks. Recent evidence, however, implicates the DMN in self-referential and memory-based processing. We provide robust evidence for this network's active contribution to working memory by revealing dynamic reconfiguration in its
Dynamical modeling of tidal streams
Bovy, Jo
2014-11-01
I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its 'track') in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of 'orphan' streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.
Dynamical Modeling of Tidal Streams
NASA Astrophysics Data System (ADS)
Bovy, Jo
2014-11-01
I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its "track") in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of "orphan" streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.
Choi, Hyung-Seok; Kim, Youngchul; Cho, Kwang-Hyun; Park, Taesung
2013-01-01
Since eukaryotic transcription is regulated by sets of Transcription Factors (TFs) having various transcriptional time delays, identification of temporal combinations of activated TFs is important to reconstruct Transcriptional Regulatory Networks (TRNs). Our methods combine time course microarray data, information on physical binding between the TFs and their targets and the regulatory sequences of genes using a log-linear model to reconstruct dynamic functional TRNs of the yeast cell cycle and human apoptosis. In conclusion, our results suggest that the proposed dynamic motif search method is more effective in reconstructing TRNs than the static motif search method.
Papaleo, Elena
2015-01-01
In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations. PMID:26075210
Papaleo, Elena
2015-01-01
In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.
Dynamic Network Mechanisms of Relational Integration
Parkin, Beth L.; Hellyer, Peter J.; Leech, Robert
2015-01-01
A prominent hypothesis states that specialized neural modules within the human lateral frontopolar cortices (LFPCs) support “relational integration” (RI), the solving of complex problems using inter-related rules. However, it has been proposed that LFPC activity during RI could reflect the recruitment of additional “domain-general” resources when processing more difficult problems in general as opposed to RI specifically. Moreover, theoretical research with computational models has demonstrated that RI may be supported by dynamic processes that occur throughout distributed networks of brain regions as opposed to within a discrete computational module. Here, we present fMRI findings from a novel deductive reasoning paradigm that controls for general difficulty while manipulating RI demands. In accordance with the domain-general perspective, we observe an increase in frontoparietal activation during challenging problems in general as opposed to RI specifically. Nonetheless, when examining frontoparietal activity using analyses of phase synchrony and psychophysiological interactions, we observe increased network connectivity during RI alone. Moreover, dynamic causal modeling with Bayesian model selection identifies the LFPC as the effective connectivity source. Based on these results, we propose that during RI an increase in network connectivity and a decrease in network metastability allows rules that are coded throughout working memory systems to be dynamically bound. This change in connectivity state is top-down propagated via a hierarchical system of domain-general networks with the LFPC at the apex. In this manner, the functional network perspective reconciles key propositions of the globalist, modular, and computational accounts of RI within a single unified framework. PMID:25995457
Miyata, Tatsuhiko; Ikuta, Yasuhiro; Hirata, Fumio
2011-01-28
We propose the thermodynamic integration along a spatial reaction coordinate using the molecular dynamics simulation combined with the three-dimensional reference interaction site model theory. This method provides a free energy calculation in solution along the reaction coordinate defined by the Cartesian coordinates of the solute atoms. The proposed method is based on the blue moon algorithm which can, in principle, handle any reaction coordinate as far as it is defined by the solute atom positions. In this article, we apply the present method to the complex formation process of the crown ether 18-Crown-6 (18C6) with the potassium ion in an aqueous solution. The separation between the geometric centers of these two molecules is taken to be the reaction coordinate for this system. The potential of mean force (PMF) becomes the maximum at the separation between the molecular centers being ∼4 Å, which can be identified as the free energy barrier in the process of the molecular recognition. In a separation further than the free energy barrier, the PMF is slightly reduced to exhibit a plateau. In the region closer than the free energy barrier, approach of the potassium ion to the center of 18C6 also decreases the PMF. When the potassium ion is accommodated at the center of 18C6, the free energy is lower by -5.7 ± 0.7 kcal/mol than that at the above mentioned plateau or converged state. By comparing the results with those from the free energy calculation along the coupling parameters obtained in our previous paper [T. Miyata, Y. Ikuta, and F. Hirata, J. Chem. Phys. 133, 044114 (2010)], it is found that the effective interaction in water between 18C6 and the potassium ion vanishes beyond the molecular-center-separation of 10 Å. Furthermore, the conformation of 18C6 is found to be significantly changed depending upon the 18C6-K(+) distance. A proper conformational sampling and an accurate solvent treatment are crucial for realizing the accurate PMF, and we believe
Dispersive models describing mosquitoes’ population dynamics
NASA Astrophysics Data System (ADS)
Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.
2016-08-01
The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.
An integrated neuromechanical model of insect locomotion
NASA Astrophysics Data System (ADS)
Kukillaya, Raghavendra
We develop a biologically-plausible feedforward neuromechanical model for running insects that includes a simplified hexapedal leg geometry with agonist-antagonist muscle pairs actuating each leg joint. It is driven by a neural network modeling the central pattern generator (CPG) and the motoneurons which activate the muscles. This final goal is achieved in three stages. First, a relatively simple mechanical hexapedal model is constructed in which the joint torques are produced via actuated linear torsional springs with constant stiffness. In the second stage, this system is upgraded to a muscle-actuated hexapedal model in which each joint is actuated by a pair of agonist-antagonist Hill-type muscles. Muscles are driven by stylized action potentials that are characteristic of fast motoneurons, and modeled using an activation function and nonlinear length and shortening velocity dependence. In the final stage, the full neuromechanical model is obtained by integrating the above muscle-actuated hexapedal model with a CPG-motoneuron complex, feedforward input to the muscles now being supplied by action potentials from motoneurons. Restricting to dynamics in the horizontal plane and neglecting leg masses, we reduce the model (at each stage) to three degrees of freedom describing translational and yawing motions of the body. Collectively for all the models, parameter values are based on measurements from depressor motoneurons and muscles, and observations of kinematics and dynamics of the cockroach Blaberus discoidalis. Specifically, actuation inputs for the mechanical and muscle-actuated models are chosen to approximately achieve joint torques that are consistent with measured ground reaction forces. This is done by optimizing the time-dependent torque-free joint angles in the first model, and by optimizing motoneuronal outputs and muscle force levels in the second and third models. We show that the model (at each stage) has stable double-tripod gaits over the animal
Uncertainty and Sensitivity in Surface Dynamics Modeling
NASA Astrophysics Data System (ADS)
Kettner, Albert J.; Syvitski, James P. M.
2016-05-01
Papers for this special issue on 'Uncertainty and Sensitivity in Surface Dynamics Modeling' heralds from papers submitted after the 2014 annual meeting of the Community Surface Dynamics Modeling System or CSDMS. CSDMS facilitates a diverse community of experts (now in 68 countries) that collectively investigate the Earth's surface-the dynamic interface between lithosphere, hydrosphere, cryosphere, and atmosphere, by promoting, developing, supporting and disseminating integrated open source software modules. By organizing more than 1500 researchers, CSDMS has the privilege of identifying community strengths and weaknesses in the practice of software development. We recognize, for example, that progress has been slow on identifying and quantifying uncertainty and sensitivity in numerical modeling of earth's surface dynamics. This special issue is meant to raise awareness for these important subjects and highlight state-of-the-art progress.
An integrated communications demand model
NASA Astrophysics Data System (ADS)
Doubleday, C. F.
1980-11-01
A computer model of communications demand is being developed to permit dynamic simulations of the long-term evolution of demand for communications media in the U.K. to be made under alternative assumptions about social, economic and technological trends in British Telecom's business environment. The context and objectives of the project and the potential uses of the model are reviewed, and four key concepts in the demand for communications media, around which the model is being structured are discussed: (1) the generation of communications demand; (2) substitution between media; (3) technological convergence; and (4) competition. Two outline perspectives on the model itself are given.
Exiting prostitution: an integrated model.
Baker, Lynda M; Dalla, Rochelle L; Williamson, Celia
2010-05-01
Exiting street-level prostitution is a complex, convoluted process. Few studies have described this process within any formal conceptual framework. This article reviews two general models and two prostitution-specific models and their applicability to the exiting process. Barriers encountered as women attempt to leave the streets are identified. Based on the four models, the barriers, the prostitution literature, and the authors' experience with prostituted women, a new integrated six-stage model that is comprehensive in scope and sensitive to women's attempts to exit prostitution is offered as a foundation for continued research on the process of women leaving the streets.
Modeling biological pathway dynamics with timed automata.
Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N
2014-05-01
Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience. PMID:24808226
Spinon dynamics in quantum integrable antiferromagnets
NASA Astrophysics Data System (ADS)
Vlijm, R.; Caux, J.-S.
2016-05-01
The excitations of the Heisenberg antiferromagnetic spin chain in zero field are known as spinons. As pairwise-created fractionalized excitations, spinons are important in the understanding of inelastic neutron scattering experiments in (quasi-)one-dimensional materials. In the present paper, we consider the real space-time dynamics of spinons originating from a local spin flip on the antiferromagnetic ground state of the (an)isotropic Heisenberg spin-1/2 model and the Babujan-Takhtajan spin-1 model. By utilizing algebraic Bethe ansatz methods at finite system size to compute the expectation value of the local magnetization and spin-spin correlations, spinons are visualized as propagating domain walls in the antiferromagnetic spin ordering with anisotropy dependent behavior. The spin-spin correlation after the spin flip displays a light cone, satisfying the Lieb-Robinson bound for the propagation of correlations at the spinon velocity.
Morales-Rodriguez, Ricardo; Meyer, Anne S; Gernaey, Krist V; Sin, Gürkan
2011-01-01
In this study a number of different process flowsheets were generated and their feasibility evaluated using simulations of dynamic models. A dynamic modeling framework was used for the assessment of operational scenarios such as, fed-batch, continuous and continuous with recycle configurations. Each configuration was evaluated against the following benchmark criteria, yield (kg ethanol/kg dry-biomass), final product concentration and number of unit operations required in the different process configurations. The results show that simultaneous saccharification and co-fermentation (SSCF) operating in continuous mode with a recycle of the SSCF reactor effluent, results in the best productivity of bioethanol among the proposed process configurations, with a yield of 0.18 kg ethanol/kgdry-biomass.
Distributed Energy Resources and Dynamic Microgrid: An Integrated Assessment
NASA Astrophysics Data System (ADS)
Shang, Duo Rick
The overall goal of this thesis is to improve understanding in terms of the benefit of DERs to both utility and to electricity end-users when integrated in power distribution system. To achieve this goal, a series of two studies was conducted to assess the value of DERs when integrated with new power paradigms. First, the arbitrage value of DERs was examined in markets with time-variant electricity pricing rates (e.g., time of use, real time pricing) under a smart grid distribution paradigm. This study uses a stochastic optimization model to estimate the potential profit from electricity price arbitrage over a five-year period. The optimization process involves two types of PHEVs (PHEV-10, and PHEV-40) under three scenarios with different assumptions on technology performance, electricity market and PHEV owner types. The simulation results indicate that expected arbitrage profit is not a viable option to engage PHEVs in dispatching and in providing ancillary services without more favorable policy and PHEV battery technologies. Subsidy or change in electricity tariff or both are needed. Second, it examined the concept of dynamic microgrid as a measure to improve distribution resilience, and estimates the prices of this emerging service. An economic load dispatch (ELD) model is developed to estimate the market-clearing price in a hypothetical community with single bid auction electricity market. The results show that the electricity market clearing price on the dynamic microgrid is predominantly decided by power output and cost of electricity of each type of DGs. At circumstances where CHP is the only source, the electricity market clearing price in the island is even cheaper than the on-grid electricity price at normal times. Integration of PHEVs in the dynamic microgrid will increase electricity market clearing prices. It demonstrates that dynamic microgrid is an economically viable alternative to enhance grid resilience.
NASA Astrophysics Data System (ADS)
Thomas, R. Q.; Hurtt, G. C.; Dubayah, R. O.; Ranson, K. J.; Ollinger, S. V.; Aber, J. D.
2006-12-01
Lidar remote sensing data have been shown to effectively represent forest structure, constrain estimates of carbon stocks and, when used to initialize a height-structured ecosystem model fluxes, constrain fluxes. Here we use large-footprint lidar data from the NASA Laser Vegetation Imaging Sensor (LVIS) to initialize the height-structured Ecosystem Demography (ED) model to study forest structure and dynamics at Hubbard Brook Experimental Forest (HBEF). HBEF is in the White Mountains of New Hampshire and includes heterogeneity in elevation dependent abiotic factors (i.e. temperature, precipitation, and soil depth), which are important drivers in a well documented decline in biomass and species change with elevation. We produced an estimate of the forest structure and fluxes in 1999 across all elevations at HBEF by first spinning up the model with elevation dependent climate and soil characteristics and then initializing the model using 1999 LVIS canopy height data. We validated the initialized model estimates against extensive field data and demonstrated that above ground carbon stocks, basal area, and species composition were within 1, 5 and 7%, respectively, of the field data at all elevations. Model projections were validated using data from a second LVIS acquisition obtained in 2003, accounting for the effects of both model uncertainty and lidar uncertainty. The additional constraint provided by including elevation dependent abiotic heterogeneity in the model initialization suggests that the forest is closer to a mature state than when initialized without the heterogeneity. We conclude that together lidar data and a height-structured ecosystem model give more information about forest structure and dynamics because together they account for critical fine scale heterogeneity.
An integrated model of ring pack performance
NASA Technical Reports Server (NTRS)
Keribar, R.; Dursunkaya, Z.; Flemming, M. F.
1991-01-01
This paper describes an integrated model developed for the detailed characterization and simulation of piston ring pack behavior in internal combustion engines and the prediction of ring pack performance. The model includes comprehensive and coupled treatments of (1) ring-liner hydrodynamic and boundary lubrication and friction; (2) ring axial, radial, and (toroidal) twist dynamics; (3) inter-ring gas dynamics and blowby. The physics of each of these highly inter-related phenomena are represented by submodels, which are intimately coupled to form a design-oriented predictive tool aimed at the calculation of ring film thicknesses, ring motions, land pressures, engine friction, and blowby. The paper also describes the results of a series of analytical studies investigating effects of engine speed and load and ring pack design parameters, on ring motions, film thicknesses, and inter-ring pressures, as well as ring friction and blowby.
NASA Astrophysics Data System (ADS)
Bloom, A. A.; Williams, M.
2015-03-01
Many of the key processes represented in global terrestrial carbon models remain largely unconstrained. For instance, plant allocation patterns and residence times of carbon pools are poorly known globally, except perhaps at a few intensively studied sites. As a consequence of data scarcity, carbon models tend to be underdetermined, and so can produce similar net fluxes with very different parameters and internal dynamics. To address these problems, we propose a series of ecological and dynamic constraints (EDCs) on model parameters and initial conditions, as a means to constrain ecosystem variable inter-dependencies in the absence of local data. The EDCs consist of a range of conditions on (a) carbon pool turnover and allocation ratios, (b) steady-state proximity, and (c) growth and decay of model carbon pools. We use a simple ecosystem carbon model in a model-data fusion framework to determine the added value of these constraints in a data-poor context. Based only on leaf area index (LAI) time series and soil carbon data, we estimate net ecosystem exchange (NEE) for (a) 40 synthetic experiments and (b) three AmeriFlux tower sites. For the synthetic experiments, we show that EDCs lead to an overall 34% relative error reduction in model parameters, and a 65% reduction in the 3 yr NEE 90% confidence range. In the application at AmeriFlux sites all NEE estimates were made independently of NEE measurements. Compared to these observations, EDCs resulted in a 69-93% reduction in 3 yr cumulative NEE median biases (-0.26 to +0.08 kg C m-2), in comparison to standard 3 yr median NEE biases (-1.17 to -0.84 kg C m-2). In light of these findings, we advocate the use of EDCs in future model-data fusion analyses of the terrestrial carbon cycle.
NASA Astrophysics Data System (ADS)
Bloom, A. A.; Williams, M.
2014-08-01
Many of the key processes represented in global terrestrial carbon models remain largely unconstrained. For instance, plant allocation patterns and residence times of carbon pools are poorly known globally, except perhaps at a few intensively studied sites. As a consequence of data scarcity, carbon models tend to be underdetermined, and so can produce similar net fluxes with very different parameters and internal dynamics. To address these problems, we propose a series of ecological and dynamic constraints (EDCs) on model parameters and initial conditions, as a means to constrain ecosystem variable inter-dependencies in the absence of local data. The EDCs consist of a range of conditions on (a) carbon pool turnover and allocation ratios, (b) steady state proximity, and (c) growth and decay of model carbon pools. We use a simple ecosystem carbon model in a model-data fusion framework to determine the added value of these constraints in a data-poor context. Based only on leaf area index (LAI) time series and soil carbon data, we estimate net ecosystem exchange (NEE) for (a) 40 synthetic experiments and (b) three AMERIFLUX tower sites. For the synthetic experiments, we show that EDCs lead to an an overall 34% relative error reduction in model parameters, and a 65% reduction in the 3 yr NEE 90% confidence range. In the application at AMERIFLUX sites all NEE estimates were made independently of NEE measurements. Compared to these observations, EDCs resulted in a 69-93% reduction in 3 yr cumulative NEE median biases (-0.26 to +0.08 kg C m-2), in comparison to standard 3 yr median NEE biases (-1.17 to -0.84 kg C m-2). In light of these findings, we advocate the use of EDCs in future model-data fusion analyses of the terrestrial carbon cycle.
Analysis of integral lift-fan engine dynamics
NASA Technical Reports Server (NTRS)
Szuch, J. R.
1973-01-01
An integral lift-fan engine being considered for VTOL applications was simulated using the hybrid computer. A contractor-proposed fuel control and a simple model of the roll dynamics of a hovering VTOL airplane were used in the simulation. Both steady-state and transient data were generated. The desired engine time constant of 0.20 second was achieved for thrust increments less than 10 precent of the design thrust. For roll angle demands less than 10 deg, roll angle overshoot was acceptable with more than 84 percent of the demand achieved in 1 second.
Optogenetic perturbations reveal the dynamics of an oculomotor integrator
Gonçalves, Pedro J.; Arrenberg, Aristides B.; Hablitzel, Bastian; Baier, Herwig; Machens, Christian K.
2014-01-01
Many neural systems can store short-term information in persistently firing neurons. Such persistent activity is believed to be maintained by recurrent feedback among neurons. This hypothesis has been fleshed out in detail for the oculomotor integrator (OI) for which the so-called “line attractor” network model can explain a large set of observations. Here we show that there is a plethora of such models, distinguished by the relative strength of recurrent excitation and inhibition. In each model, the firing rates of the neurons relax toward the persistent activity states. The dynamics of relaxation can be quite different, however, and depend on the levels of recurrent excitation and inhibition. To identify the correct model, we directly measure these relaxation dynamics by performing optogenetic perturbations in the OI of zebrafish expressing halorhodopsin or channelrhodopsin. We show that instantaneous, inhibitory stimulations of the OI lead to persistent, centripetal eye position changes ipsilateral to the stimulation. Excitatory stimulations similarly cause centripetal eye position changes, yet only contralateral to the stimulation. These results show that the dynamics of the OI are organized around a central attractor state—the null position of the eyes—which stabilizes the system against random perturbations. Our results pose new constraints on the circuit connectivity of the system and provide new insights into the mechanisms underlying persistent activity. PMID:24616666
Mattsson, Brady J.; Runge, M.C.; Devries, J.H.; Boomer, G.S.; Eadie, J.M.; Haukos, D.A.; Fleskes, J.P.; Koons, D.N.; Thogmartin, W.E.; Clark, R.G.
2012-01-01
We developed and evaluated the performance of a metapopulation model enabling managers to examine, for the first time, the consequences of alternative management strategies involving habitat conditions and hunting on both harvest opportunity and carrying capacity (i.e., equilibrium population size in the absence of harvest) for migratory waterfowl at a continental scale. Our focus is on the northern pintail (Anas acuta; hereafter, pintail), which serves as a useful model species to examine the potential for integrating waterfowl harvest and habitat management in North America. We developed submodel structure capturing important processes for pintail populations during breeding, fall migration, winter, and spring migration while encompassing spatial structure representing three core breeding areas and two core nonbreeding areas. A number of continental-scale predictions from our baseline parameterization (e.g., carrying capacity of 5.5 million, equilibrium population size of 2.9 million and harvest rate of 12% at maximum sustained yield [MSY]) were within 10% of those from the pintail harvest strategy under current use by the U.S. Fish and Wildlife Service. To begin investigating the interaction of harvest and habitat management, we examined equilibrium population conditions for pintail at the continental scale across a range of harvest rates while perturbing model parameters to represent: (1) a 10% increase in breeding habitat quality in the Prairie Pothole population (PR); and (2) a 10% increase in nonbreeding habitat quantity along in the Gulf Coast (GC). Based on our model and analysis, a greater increase in carrying capacity and sustainable harvest was seen when increasing a proxy for habitat quality in the Prairie Pothole population. This finding and underlying assumptions must be critically evaluated, however, before specific management recommendations can be made. To make such recommendations, we require (1) extended, refined submodels with additional
Mattsson, B.J.; Runge, M.C.; Devries, J.H.; Boomer, G.S.; Eadie, J.M.; Haukos, D.A.; Fleskes, J.P.; Koons, D.N.; Thogmartin, W.E.; Clark, R.G.
2012-01-01
We developed and evaluated the performance of a metapopulation model enabling managers to examine, for the first time, the consequences of alternative management strategies involving habitat conditions and hunting on both harvest opportunity and carrying capacity (i.e., equilibrium population size in the absence of harvest) for migratory waterfowl at a continental scale. Our focus is on the northern pintail (Anas acuta; hereafter, pintail), which serves as a useful model species to examine the potential for integrating waterfowl harvest and habitat management in North America. We developed submodel structure capturing important processes for pintail populations during breeding, fall migration, winter, and spring migration while encompassing spatial structure representing three core breeding areas and two core nonbreeding areas. A number of continental-scale predictions from our baseline parameterization (e.g., carrying capacity of 5.5 million, equilibrium population size of 2.9 million and harvest rate of 12% at maximum sustained yield [MSY]) were within 10% of those from the pintail harvest strategy under current use by the U.S. Fish and Wildlife Service. To begin investigating the interaction of harvest and habitat management, we examined equilibrium population conditions for pintail at the continental scale across a range of harvest rates while perturbing model parameters to represent: (1) a 10% increase in breeding habitat quality in the Prairie Pothole population (PR); and (2) a 10% increase in nonbreeding habitat quantity along in the Gulf Coast (GC). Based on our model and analysis, a greater increase in carrying capacity and sustainable harvest was seen when increasing a proxy for habitat quality in the Prairie Pothole population. This finding and underlying assumptions must be critically evaluated, however, before specific management recommendations can be made. To make such recommendations, we require (1) extended, refined submodels with additional
The integrated environmental control model
Rubin, E.S.; Berkenpas, M.B.; Kalagnanam, J.R.
1995-11-01
The capability to estimate the performance and cost of emission control systems is critical to a variety of planning and analysis requirements faced by utilities, regulators, researchers and analysts in the public and private sectors. The computer model described in this paper has been developed for DOe to provide an up-to-date capability for analyzing a variety of pre-combustion, combustion, and post-combustion options in an integrated framework. A unique capability allows performance and costs to be modeled probabilistically, which allows explicit characterization of uncertainties and risks.
Path integral for (2+1)-dimensional Shape Dynamics
NASA Astrophysics Data System (ADS)
González, A.; Ocampo, H.
2015-03-01
We studied the path integral quantization for the Shape Dynamics formulation of General Relativity in the 2+1 torus universe. We show that the Shape Dynamics path integral on the reduced phase space is equivalent with the previous results obtained for the ADM 2+1 gravity and we found that the Shape Dynamics Hamiltonian allows us to establish a straightforward relation between reduced systems in the (τ, V)-form and the τ-form through the York time gauge fixing.
An integrated network model of psychotic symptoms.
Looijestijn, Jasper; Blom, Jan Dirk; Aleman, André; Hoek, Hans W; Goekoop, Rutger
2015-12-01
The full body of research on the nature of psychosis and its determinants indicates that a considerable number of factors are relevant to the development of hallucinations, delusions, and other positive symptoms, ranging from neurodevelopmental parameters and altered connectivity of brain regions to impaired cognitive functioning and social factors. We aimed to integrate these factors in a single mathematical model based on network theory. At the microscopic level this model explains positive symptoms of psychosis in terms of experiential equivalents of robust, high-frequency attractor states of neural networks. At the mesoscopic level it explains them in relation to global brain states, and at the macroscopic level in relation to social-network structures and dynamics. Due to the scale-free nature of biological networks, all three levels are governed by the same general laws, thereby allowing for an integrated model of biological, psychological, and social phenomena involved in the mediation of positive symptoms of psychosis. This integrated network model of psychotic symptoms (INMOPS) is described together with various possibilities for application in clinical practice.
An integrated network model of psychotic symptoms.
Looijestijn, Jasper; Blom, Jan Dirk; Aleman, André; Hoek, Hans W; Goekoop, Rutger
2015-12-01
The full body of research on the nature of psychosis and its determinants indicates that a considerable number of factors are relevant to the development of hallucinations, delusions, and other positive symptoms, ranging from neurodevelopmental parameters and altered connectivity of brain regions to impaired cognitive functioning and social factors. We aimed to integrate these factors in a single mathematical model based on network theory. At the microscopic level this model explains positive symptoms of psychosis in terms of experiential equivalents of robust, high-frequency attractor states of neural networks. At the mesoscopic level it explains them in relation to global brain states, and at the macroscopic level in relation to social-network structures and dynamics. Due to the scale-free nature of biological networks, all three levels are governed by the same general laws, thereby allowing for an integrated model of biological, psychological, and social phenomena involved in the mediation of positive symptoms of psychosis. This integrated network model of psychotic symptoms (INMOPS) is described together with various possibilities for application in clinical practice. PMID:26432501
Adaptive integral dynamic surface control of a hypersonic flight vehicle
NASA Astrophysics Data System (ADS)
Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick
2015-07-01
In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.
A LAGRANGIAN INTEGRATOR FOR PLANETARY ACCRETION AND DYNAMICS (LIPAD)
Levison, Harold F.; Duncan, Martin J.; Thommes, Edward
2012-10-01
We present the first particle-based Lagrangian code that can follow the collisional/accretional/dynamical evolution of a large number of kilometer-sized planetesimals through the entire growth process of becoming planets. We refer to it as the Lagrangian Integrator for Planetary Accretion and Dynamics or LIPAD. LIPAD is built on top of SyMBA, which is a symplectic N-body integrator. In order to handle the very large number of planetesimals required by planet formation simulations, we introduce the concept of a tracer particle. Each tracer is intended to represent a large number of disk particles on roughly the same orbit and size as one another and is characterized by three numbers: the physical radius, the bulk density, and the total mass of the disk particles represented by the tracer. We developed statistical algorithms that follow the velocity and size evolution of the tracers due to close gravitational encounters and physical collisions with one another. The tracers mainly dynamically interact with the larger objects (planetary embryos) in the normal N-body way. LIPAD's greatest strength is that it can accurately model the wholesale redistribution of planetesimals due to gravitational interaction with the embryos, which has recently been shown to significantly affect the growth rate of planetary embryos. We verify the code via a comprehensive set of tests that compare our results with those of Eulerian and/or direct N-body codes.
Launch Vehicle Dynamics Demonstrator Model
NASA Technical Reports Server (NTRS)
1963-01-01
Launch Vehicle Dynamics Demonstrator Model. The effect of vibration on launch vehicle dynamics was studied. Conditions included three modes of instability. The film includes close up views of the simulator fuel tank with and without stability control. [Entire movie available on DVD from CASI as Doc ID 20070030984. Contact help@sti.nasa.gov
NASA Technical Reports Server (NTRS)
Nagaraja, K. S.; Kraft, R. H.
1999-01-01
The HSCT Flight Controls Group has developed longitudinal control laws, utilizing PTC aeroelastic flexible models to minimize aeroservoelastic interaction effects, for a number of flight conditions. The control law design process resulted in a higher order controller and utilized a large number of sensors distributed along the body for minimizing the flexibility effects. Processes were developed to implement these higher order control laws for performing the dynamic gust loads and flutter analyses. The processes and its validation were documented in Reference 2, for selected flight condition. The analytical results for additional flight conditions are presented in this document for further validation.
Integrated computer simulation on FIR FEL dynamics
Furukawa, H.; Kuruma, S.; Imasaki, K.
1995-12-31
An integrated computer simulation code has been developed to analyze the RF-Linac FEL dynamics. First, the simulation code on the electron beam acceleration and transport processes in RF-Linac: (LUNA) has been developed to analyze the characteristics of the electron beam in RF-Linac and to optimize the parameters of RF-Linac. Second, a space-time dependent 3D FEL simulation code (Shipout) has been developed. The RF-Linac FEL total simulations have been performed by using the electron beam data from LUNA in Shipout. The number of particles using in a RF-Linac FEL total simulation is approximately 1000. The CPU time for the simulation of 1 round trip is about 1.5 minutes. At ILT/ILE, Osaka, a 8.5MeV RF-Linac with a photo-cathode RF-gun is used for FEL oscillation experiments. By using 2 cm wiggler, the FEL oscillation in the wavelength approximately 46 {mu}m are investigated. By the simulations using LUNA with the parameters of an ILT/ILE experiment, the pulse shape and the energy spectra of the electron beam at the end of the linac are estimated. The pulse shape of the electron beam at the end of the linac has sharp rise-up and it slowly decays as a function of time. By the RF-linac FEL total simulations with the parameters of an ILT/ILE experiment, the dependencies of the start up of the FEL oscillations on the pulse shape of the electron beam at the end of the linac are estimated. The coherent spontaneous emission effects and the quick start up of FEL oscillations have been observed by the RF-Linac FEL total simulations.
Somatosensory integration controlled by dynamic thalamocortical feed-forward inhibition.
Gabernet, Laetitia; Jadhav, Shantanu P; Feldman, Daniel E; Carandini, Matteo; Scanziani, Massimo
2005-10-20
The temporal features of tactile stimuli are faithfully represented by the activity of neurons in the somatosensory cortex. However, the cellular mechanisms that enable cortical neurons to report accurate temporal information are not known. Here, we show that in the rodent barrel cortex, the temporal window for integration of thalamic inputs is under the control of thalamocortical feed-forward inhibition and can vary from 1 to 10 ms. A single thalamic fiber can trigger feed-forward inhibition and contacts both excitatory and inhibitory cortical neurons. The dynamics of feed-forward inhibition exceed those of each individual synapse in the circuit and are captured by a simple disynaptic model of the thalamocortical projection. The variations in the integration window produce changes in the temporal precision of cortical responses to whisker stimulation. Hence, feed-forward inhibitory circuits, classically known to sharpen spatial contrast of tactile inputs, also increase the temporal resolution in the somatosensory cortex.
Integrating influenza antigenic dynamics with molecular evolution
Bedford, Trevor; Suchard, Marc A; Lemey, Philippe; Dudas, Gytis; Gregory, Victoria; Hay, Alan J; McCauley, John W; Russell, Colin A; Smith, Derek J; Rambaut, Andrew
2014-01-01
Influenza viruses undergo continual antigenic evolution allowing mutant viruses to evade host immunity acquired to previous virus strains. Antigenic phenotype is often assessed through pairwise measurement of cross-reactivity between influenza strains using the hemagglutination inhibition (HI) assay. Here, we extend previous approaches to antigenic cartography, and simultaneously characterize antigenic and genetic evolution by modeling the diffusion of antigenic phenotype over a shared virus phylogeny. Using HI data from influenza lineages A/H3N2, A/H1N1, B/Victoria and B/Yamagata, we determine patterns of antigenic drift across viral lineages, showing that A/H3N2 evolves faster and in a more punctuated fashion than other influenza lineages. We also show that year-to-year antigenic drift appears to drive incidence patterns within each influenza lineage. This work makes possible substantial future advances in investigating the dynamics of influenza and other antigenically-variable pathogens by providing a model that intimately combines molecular and antigenic evolution. DOI: http://dx.doi.org/10.7554/eLife.01914.001 PMID:24497547
Cotangent Models for Integrable Systems
NASA Astrophysics Data System (ADS)
Kiesenhofer, Anna; Miranda, Eva
2016-07-01
We associate cotangent models to a neighbourhood of a Liouville torus in symplectic and Poisson manifolds focusing on b-Poisson/b-symplectic manifolds. The semilocal equivalence with such models uses the corresponding action-angle theorems in these settings: the theorem of Liouville-Mineur-Arnold for symplectic manifolds and an action-angle theorem for regular Liouville tori in Poisson manifolds (Laurent- Gengoux et al., IntMath Res Notices IMRN 8: 1839-1869, 2011). Our models comprise regular Liouville tori of Poisson manifolds but also consider the Liouville tori on the singular locus of a b-Poisson manifold. For this latter class of Poisson structures we define a twisted cotangent model. The equivalence with this twisted cotangent model is given by an action-angle theorem recently proved by the authors and Scott (Math. Pures Appl. (9) 105(1):66-85, 2016). This viewpoint of cotangent models provides a new machinery to construct examples of integrable systems, which are especially valuable in the b-symplectic case where not many sources of examples are known. At the end of the paper we introduce non-degenerate singularities as lifted cotangent models on b-symplectic manifolds and discuss some generalizations of these models to general Poisson manifolds.
SSME structural dynamic model development
NASA Technical Reports Server (NTRS)
Foley, M. J.; Tilley, D. M.; Welch, C. T.
1983-01-01
A mathematical model of the Space Shuttle Main Engine (SSME) as a complete assembly, with detailed emphasis on LOX and High Fuel Turbopumps is developed. The advantages of both complete engine dynamics, and high fidelity modeling are incorporated. Development of this model, some results, and projected applications are discussed.
Modeling emotional dynamics : currency versus field.
Sallach, D .L.; Decision and Information Sciences; Univ. of Chicago
2008-08-01
Randall Collins has introduced a simplified model of emotional dynamics in which emotional energy, heightened and focused by interaction rituals, serves as a common denominator for social exchange: a generic form of currency, except that it is active in a far broader range of social transactions. While the scope of this theory is attractive, the specifics of the model remain unconvincing. After a critical assessment of the currency theory of emotion, a field model of emotion is introduced that adds expressiveness by locating emotional valence within its cognitive context, thereby creating an integrated orientation field. The result is a model which claims less in the way of motivational specificity, but is more satisfactory in modeling the dynamic interaction between cognitive and emotional orientations at both individual and social levels.
Coastal Ecosystem Integrated Compartment Model (ICM): Modeling Framework
NASA Astrophysics Data System (ADS)
Meselhe, E. A.; White, E. D.; Reed, D.
2015-12-01
The Integrated Compartment Model (ICM) was developed as part of the 2017 Coastal Master Plan modeling effort. It is a comprehensive and numerical hydrodynamic model coupled to various geophysical process models. Simplifying assumptions related to some of the flow dynamics are applied to increase the computational efficiency of the model. The model can be used to provide insights about coastal ecosystems and evaluate restoration strategies. It builds on existing tools where possible and incorporates newly developed tools where necessary. It can perform decadal simulations (~ 50 years) across the entire Louisiana coast. It includes several improvements over the approach used to support the 2012 Master Plan, such as: additional processes in the hydrology, vegetation, wetland and barrier island morphology subroutines, increased spatial resolution, and integration of previously disparate models into a single modeling framework. The ICM includes habitat suitability indices (HSIs) to predict broad spatial patterns of habitat change, and it provides an additional integration to a dynamic fish and shellfish community model which quantitatively predicts potential changes in important fishery resources. It can be used to estimate the individual and cumulative effects of restoration and protection projects on the landscape, including a general estimate of water levels associated with flooding. The ICM is also used to examine possible impacts of climate change and future environmental scenarios (e.g. precipitation, Eustatic sea level rise, subsidence, tropical storms, etc.) on the landscape and on the effectiveness of restoration projects. The ICM code is publically accessible, and coastal restoration and protection groups interested in planning-level modeling are encouraged to explore its utility as a computationally efficient tool to examine ecosystem response to future physical or ecological changes, including the implementation of restoration and protection strategies.
Hypnosis, suggestion, and suggestibility: an integrative model.
Lynn, Steven Jay; Laurence, Jean-Roch; Kirsch, Irving
2015-01-01
This article elucidates an integrative model of hypnosis that integrates social, cultural, cognitive, and neurophysiological variables at play both in and out of hypnosis and considers their dynamic interaction as determinants of the multifaceted experience of hypnosis. The roles of these variables are examined in the induction and suggestion stages of hypnosis, including how they are related to the experience of involuntariness, one of the hallmarks of hypnosis. It is suggested that studies of the modification of hypnotic suggestibility; cognitive flexibility; response sets and expectancies; the default-mode network; and the search for the neurophysiological correlates of hypnosis, more broadly, in conjunction with research on social psychological variables, hold much promise to further understanding of hypnosis.
Wang, Shuo; Xu, Ling; Yang, Fenglin; Wang, He
2014-02-15
Considering the limitation of the traditional method to assess the ecological carrying capacity and the complexity of the water ecological system, we used system dynamics, ANN, and CA-Markov to model a water ecological system. The social component was modeled according to Granger causality test by system dynamics. The natural component consists of the water resource and water environmental capacity, which were forecasted through the prediction of precipitation and change in land use cover. The interaction of the social component and the natural component mainly reflected environmental policies, such as the imposition of an environmental fee and environmental tax based on their values. Simulation results showed the different assessments on water ecological carrying capacity under the two policies. The population grew (2.9 million), and less pollution (86,632.37 t COD and 2854.5 t NH4N) was observed with the imposition of environmental tax compared with the imposition of an environmental fee (2.85 million population, 10,8381 t COD and 3543 t NH4N) at the same GDP level of 585 billion CNY in 2030. According to the causality loop, we discussed the different states under the policies and the reasons that caused the differences in water ecological carrying capacity state. According to game theory, we explained the limitation of the environmental fee policy on the basis of marginal benefit and cost. The externality was cleared up by the environmental tax policy.
NASA Technical Reports Server (NTRS)
Adams, Neil S.; Bollenbacher, Gary
1992-01-01
This report discusses the development and underlying mathematics of a rigid-body computer model of a proposed cryogenic on-orbit liquid depot storage, acquisition, and transfer spacecraft (COLD-SAT). This model, referred to in this report as the COLD-SAT dynamic model, consists of both a trajectory model and an attitudinal model. All disturbance forces and torques expected to be significant for the actual COLD-SAT spacecraft are modeled to the required degree of accuracy. Control and experimental thrusters are modeled, as well as fluid slosh. The model also computes microgravity disturbance accelerations at any specified point in the spacecraft. The model was developed by using the Boeing EASY5 dynamic analysis package and will run on Apollo, Cray, and other computing platforms.
Dynamic Modeling of ALS Systems
NASA Technical Reports Server (NTRS)
Jones, Harry
2002-01-01
The purpose of dynamic modeling and simulation of Advanced Life Support (ALS) systems is to help design them. Static steady state systems analysis provides basic information and is necessary to guide dynamic modeling, but static analysis is not sufficient to design and compare systems. ALS systems must respond to external input variations and internal off-nominal behavior. Buffer sizing, resupply scheduling, failure response, and control system design are aspects of dynamic system design. We develop two dynamic mass flow models and use them in simulations to evaluate systems issues, optimize designs, and make system design trades. One model is of nitrogen leakage in the space station, the other is of a waste processor failure in a regenerative life support system. Most systems analyses are concerned with optimizing the cost/benefit of a system at its nominal steady-state operating point. ALS analysis must go beyond the static steady state to include dynamic system design. All life support systems exhibit behavior that varies over time. ALS systems must respond to equipment operating cycles, repair schedules, and occasional off-nominal behavior or malfunctions. Biological components, such as bioreactors, composters, and food plant growth chambers, usually have operating cycles or other complex time behavior. Buffer sizes, material stocks, and resupply rates determine dynamic system behavior and directly affect system mass and cost. Dynamic simulation is needed to avoid the extremes of costly over-design of buffers and material reserves or system failure due to insufficient buffers and lack of stored material.
Integrated modeling of advanced optical systems
NASA Astrophysics Data System (ADS)
Briggs, Hugh C.; Needels, Laura; Levine, B. Martin
1993-02-01
This poster session paper describes an integrated modeling and analysis capability being developed at JPL under funding provided by the JPL Director's Discretionary Fund and the JPL Control/Structure Interaction Program (CSI). The posters briefly summarize the program capabilities and illustrate them with an example problem. The computer programs developed under this effort will provide an unprecedented capability for integrated modeling and design of high performance optical spacecraft. The engineering disciplines supported include structural dynamics, controls, optics and thermodynamics. Such tools are needed in order to evaluate the end-to-end system performance of spacecraft such as OSI, POINTS, and SMMM. This paper illustrates the proof-of-concept tools that have been developed to establish the technology requirements and demonstrate the new features of integrated modeling and design. The current program also includes implementation of a prototype tool based upon the CAESY environment being developed under the NASA Guidance and Control Research and Technology Computational Controls Program. This prototype will be available late in FY-92. The development plan proposes a major software production effort to fabricate, deliver, support and maintain a national-class tool from FY-93 through FY-95.
Session 6: Dynamic Modeling and Systems Analysis
NASA Technical Reports Server (NTRS)
Csank, Jeffrey; Chapman, Jeffryes; May, Ryan
2013-01-01
These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators
Aircraft Dynamic Modeling in Turbulence
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.; Cunninham, Kevin
2012-01-01
A method for accurately identifying aircraft dynamic models in turbulence was developed and demonstrated. The method uses orthogonal optimized multisine excitation inputs and an analytic method for enhancing signal-to-noise ratio for dynamic modeling in turbulence. A turbulence metric was developed to accurately characterize the turbulence level using flight measurements. The modeling technique was demonstrated in simulation, then applied to a subscale twin-engine jet transport aircraft in flight. Comparisons of modeling results obtained in turbulent air to results obtained in smooth air were used to demonstrate the effectiveness of the approach.
Model describes subsea control dynamics
Not Available
1988-02-01
A mathematical model of the hydraulic control systems for subsea completions and their umbilicals has been developed and applied successfully to Jabiru and Challis field production projects in the Timor Sea. The model overcomes the limitations of conventional linear steady state models and yields for the hydraulic system an accurate description of its dynamic response, including the valve shut-in times and the pressure transients. Results of numerical simulations based on the model are in good agreement with measurements of the dynamic response of the tree valves and umbilicals made during land testing.
Mattsson, Brady J.; Runge, M.C.; Devries, J.H.; Boomer, G.S.; Eadie, J.M.; Haukos, D.A.; Fleskes, J.P.; Koons, D.N.; Thogmartin, W.E.; Clark, R.G.
2012-01-01
We developed and evaluated the performance of a metapopulation model enabling managers to examine, for the first time, the consequences of alternative management strategies involving habitat conditions and hunting on both harvest opportunity and carrying capacity (i.e., equilibrium population size in the absence of harvest) for migratory waterfowl at a continental scale. Our focus is on the northern pintail (Anas acuta; hereafter, pintail), which serves as a useful model species to examine the potential for integrating waterfowl harvest and habitatmanagement in North America. We developed submodel structure capturing important processes for pintail populations during breeding, fall migration, winter, and spring migration while encompassing spatial structure representing three core breeding areas and two core nonbreeding areas. A number of continental-scale predictions from our baseline parameterization (e.g., carrying capacity of 5.5 million, equilibrium population size of 2.9 million and harvest rate of 12% at maximum sustained yield [MSY]) were within 10% of those from the pintail harvest strategy under current use by the U.S. Fish and Wildlife Service. To begin investigating the interaction of harvest and habitatmanagement, we examined equilibrium population conditions for pintail at the continental scale across a range of harvest rates while perturbing model parameters to represent: (1) a 10% increase in breeding habitat quality in the Prairie Pothole population (PR); and (2) a 10% increase in nonbreeding habitat quantity along in the Gulf Coast (GC). Based on our model and analysis, a greater increase in carrying capacity and sustainable harvest was seen when increasing a proxy for habitat quality in the Prairie Pothole population. This finding and underlying assumptions must be critically evaluated, however, before specific management recommendations can be made. To make such recommendations, we require (1) extended, refined submodels with additional
ERIC Educational Resources Information Center
Journal of Science and Mathematics Education in Southeast Asia, 1981
1981-01-01
Instructions (with diagrams and parts list) are provided for constructing an eye model with a pliable lens made from a plastic bottle which can vary its convexity to accommodate changing positions of an object being viewed. Also discusses concepts which the model can assist in developing. (Author/SK)
Integrated Resource Planning Model (IRPM)
Graham, T. B.
2010-04-01
The Integrated Resource Planning Model (IRPM) is a decision-support software product for resource-and-capacity planning. Users can evaluate changing constraints on schedule performance, projected cost, and resource use. IRPM is a unique software tool that can analyze complex business situations from a basic supply chain to an integrated production facility to a distributed manufacturing complex. IRPM can be efficiently configured through a user-friendly graphical interface to rapidly provide charts, graphs, tables, and/or written results to summarize postulated business scenarios. There is not a similar integrated resource planning software package presently available. Many different businesses (from government to large corporations as well as medium-to-small manufacturing concerns) could save thousands of dollars and hundreds of labor hours in resource and schedule planning costs. Those businesses also could avoid millions of dollars of revenue lost from fear of overcommitting or from penalties and lost future business for failing to meet promised delivery by using IRPM to perform what-if business-case evaluations. Tough production planning questions that previously were left unanswered can now be answered with a high degree of certainty. Businesses can anticipate production problems and have solutions in hand to deal with those problems. IRPM allows companies to make better plans, decisions, and investments.
NASA Astrophysics Data System (ADS)
Naylor, S.; Letsinger, S. L.; Ficklin, D. L.; Ellett, K. M.; Olyphant, G. A.; Dufficy, A. L.
2015-12-01
Understanding the timing and magnitude of shallow groundwater recharge is critical for determining water balance and analyzing aquifer sensitivity for water resource planning. We analyzed data from six hydrometeorological monitoring stations using HYDRUS 1D to achieve physically based estimates of water-table recharge in various glaciated terrains in Indiana (USA). The models simulated runoff, root-water uptake, and flow through heterogeneous soil profiles to quantify water flux at the water table. Calibration by inverse modeling of data collected in 2013 yielded optimized hydraulic parameters that allowed accurate simulation of observed soil moisture (root mean square error was generally within 3%). The model validation period confirmed accurate simulation of soil moisture as well as correspondence between modeled recharge and observed water-table fluctuations. Additional modelling over a three-year study period indicated that diffuse water-table recharge in the region can be reasonably approximated as 35% of precipitation, but interannual and monthly variability can be significant depending on the glacial setting and pedological development. Soil parent material and horizon characteristics have a strong influence on average annual recharge primarily through their control on Ks, with clay-rich till parent materials producing values as low as 16% and coarse-grained outwash parent materials producing values as high as 58% of precipitation. The combined modelling and monitoring data reveal distinct seasonality of recharge, with most recharge occurring in the winter (seasonal mean of all sites was 66% of precipitation) and lesser but interannually stable amounts in the spring (44%), summer (13%), and autumn (16%). This ongoing research underscores the value of combining vadose zone characterization with hydrometeorological monitoring to more effectively represent how surface energy and moisture budgets influence the dynamics of surface water-groundwater interactions.
A Dynamic Integration Method for Borderland Database using OSM data
NASA Astrophysics Data System (ADS)
Zhou, X.-G.; Jiang, Y.; Zhou, K.-X.; Zeng, L.
2013-11-01
Spatial data is the fundamental of borderland analysis of the geography, natural resources, demography, politics, economy, and culture. As the spatial region used in borderland researching usually covers several neighboring countries' borderland regions, the data is difficult to achieve by one research institution or government. VGI has been proven to be a very successful means of acquiring timely and detailed global spatial data at very low cost. Therefore VGI will be one reasonable source of borderland spatial data. OpenStreetMap (OSM) has been known as the most successful VGI resource. But OSM data model is far different from the traditional authoritative geographic information. Thus the OSM data needs to be converted to the scientist customized data model. With the real world changing fast, the converted data needs to be updated. Therefore, a dynamic integration method for borderland data is presented in this paper. In this method, a machine study mechanism is used to convert the OSM data model to the user data model; a method used to select the changed objects in the researching area over a given period from OSM whole world daily diff file is presented, the change-only information file with designed form is produced automatically. Based on the rules and algorithms mentioned above, we enabled the automatic (or semiautomatic) integration and updating of the borderland database by programming. The developed system was intensively tested.
Generalized Gibbs ensemble in integrable lattice models
NASA Astrophysics Data System (ADS)
Vidmar, Lev; Rigol, Marcos
2016-06-01
The generalized Gibbs ensemble (GGE) was introduced ten years ago to describe observables in isolated integrable quantum systems after equilibration. Since then, the GGE has been demonstrated to be a powerful tool to predict the outcome of the relaxation dynamics of few-body observables in a variety of integrable models, a process we call generalized thermalization. This review discusses several fundamental aspects of the GGE and generalized thermalization in integrable systems. In particular, we focus on questions such as: which observables equilibrate to the GGE predictions and who should play the role of the bath; what conserved quantities can be used to construct the GGE; what are the differences between generalized thermalization in noninteracting systems and in interacting systems mappable to noninteracting ones; why is it that the GGE works when traditional ensembles of statistical mechanics fail. Despite a lot of interest in these questions in recent years, no definite answers have been given. We review results for the XX model and for the transverse field Ising model. For the latter model, we also report original results and show that the GGE describes spin-spin correlations over the entire system. This makes apparent that there is no need to trace out a part of the system in real space for equilibration to occur and for the GGE to apply. In the past, a spectral decomposition of the weights of various statistical ensembles revealed that generalized eigenstate thermalization occurs in the XX model (hard-core bosons). Namely, eigenstates of the Hamiltonian with similar distributions of conserved quantities have similar expectation values of few-spin observables. Here we show that generalized eigenstate thermalization also occurs in the transverse field Ising model.
Generalized Gibbs ensemble in integrable lattice models
NASA Astrophysics Data System (ADS)
Vidmar, Lev; Rigol, Marcos
2016-06-01
The generalized Gibbs ensemble (GGE) was introduced ten years ago to describe observables in isolated integrable quantum systems after equilibration. Since then, the GGE has been demonstrated to be a powerful tool to predict the outcome of the relaxation dynamics of few-body observables in a variety of integrable models, a process we call generalized thermalization. This review discusses several fundamental aspects of the GGE and generalized thermalization in integrable systems. In particular, we focus on questions such as: which observables equilibrate to the GGE predictions and who should play the role of the bath; what conserved quantities can be used to construct the GGE; what are the differences between generalized thermalization in noninteracting systems and in interacting systems mappable to noninteracting ones; why is it that the GGE works when traditional ensembles of statistical mechanics fail. Despite a lot of interest in these questions in recent years, no definite answers have been given. We review results for the XX model and for the transverse field Ising model. For the latter model, we also report original results and show that the GGE describes spin–spin correlations over the entire system. This makes apparent that there is no need to trace out a part of the system in real space for equilibration to occur and for the GGE to apply. In the past, a spectral decomposition of the weights of various statistical ensembles revealed that generalized eigenstate thermalization occurs in the XX model (hard-core bosons). Namely, eigenstates of the Hamiltonian with similar distributions of conserved quantities have similar expectation values of few-spin observables. Here we show that generalized eigenstate thermalization also occurs in the transverse field Ising model.
NASA Astrophysics Data System (ADS)
Runge, Jeffrey A.; Kovach, Adrienne I.; Churchill, James H.; Kerr, Lisa A.; Morrison, John R.; Beardsley, Robert C.; Berlinsky, David L.; Chen, Changsheng; Cadrin, Steven X.; Davis, Cabell S.; Ford, Kathryn H.; Grabowski, Jonathan H.; Howell, W. Huntting; Ji, Rubao; Jones, Rebecca J.; Pershing, Andrew J.; Record, Nicholas R.; Thomas, Andrew C.; Sherwood, Graham D.; Tallack, Shelly M. L.; Townsend, David W.
2010-10-01
We put forward a combined observing and modeling strategy for evaluating effects of environmental forcing on the dynamics of spatially structured cod populations spawning in the western Gulf of Maine. Recent work indicates at least two genetically differentiated complexes in this region: a late spring spawning, coastal population centered in Ipswich Bay, and a population that spawns in winter inshore and on nearshore banks in the Gulf of Maine and off southern New England. The two populations likely differ in trophic interactions and in physiological and behavioral responses to different winter and spring environments. Coupled physical-biological modeling has advanced to the point where within-decade forecasting of environmental conditions for recruitment to each of the two populations is feasible. However, the modeling needs to be supported by hydrographic, primary production and zooplankton data collected by buoys, and by data from remote sensing and fixed station sampling. Forecasts of environmentally driven dispersal and growth of planktonic early life stages, combined with an understanding of possible population-specific predator fields, usage of coastal habitat by juveniles and adult resident and migratory patterns, can be used to develop scenarios for spatially explicit population responses to multiple forcings, including climate change, anthropogenic impacts on nearshore juvenile habitat, connectivity among populations and management interventions such as regional fisheries closures.
Korman, Josh; Martell, Steven J.D.; Walters, Carl J.; Makinster, Andrew S.; Coggins, Lewis G.; Yard, Michael D.; Persons, William R.
2012-01-01
We used an integrated assessment model to examine effects of flow from Glen Canyon Dam, Arizona, USA, on recruitment of nonnative rainbow trout (Oncorhynchus mykiss) in the Colorado River and to estimate downstream migration from Glen Canyon to Marble Canyon, a reach used by endangered native fish. Over a 20-year period, recruitment of rainbow trout in Glen Canyon increased with the annual flow volume and when hourly flow variation was reduced and after two of three controlled floods. The model predicted that approximately 16 000 trout·year–1 emigrated to Marble Canyon and that the majority of trout in this reach originate from Glen Canyon. For most models that were examined, over 70% of the variation in emigration rates was explained by variation in recruitment in Glen Canyon, suggesting that flow from the dam controls in large part the extent of potential negative interactions between rainbow trout and native fish. Controlled floods and steadier flows, which were originally aimed at partially restoring conditions before the dam (greater native fish abundance and larger sand bars), appear to have been more beneficial to nonnative rainbow trout than to native fish.
Error dynamics in shell models for turbulence
NASA Astrophysics Data System (ADS)
De Cruz, Lesley; Vannitsem, Stéphane
2013-04-01
A deep understanding of the error dynamics in turbulent systems is crucial to estimate the horizon of predictability, and to quantify the impact of initial-condition (IC) and model errors on the statistical characteristics of ensemble prediction systems. We present a study of the dynamics of combined IC and model errors in a turbulent system. We use the Sabra shell model [1], a spectral model which captures the characteristic properties of a turbulent system using a low number of variables (of the order of 50). The analytical properties of the short-term error dynamics in the Sabra shell model are investigated using the methodology described in Ref. [2], and compared to numerical results. Of particular interest is the property of a dissipative system that the mean squared error (MSE) reaches a minimum shortly after the introduction of an IC error. The distribution of the minimum-error times is investigated, and the spatial-scale dependence of the error dynamics is discussed. At longer time scales, our simulations confirm the well-known fact that an arbitrarily small error in the initial conditions contaminates the integral scale in a time that is independent of the scale of the initial error. Finally, we report on the error dynamics in the presence of a crossover between 3D and 2D turbulence, known to characterise the atmosphere. References [1] V. S. L'vov, E. Podivilov, A. Pomyalov, I. Procaccia, and D. Vandembroucq. Improved shell model of turbulence. Physical Review E, 58:1811-1822, August 1998. [2] C. Nicolis, R. A. P. Perdigao, and S. Vannitsem. Dynamics of Prediction Errors under the Combined Effect of Initial Condition and Model Errors. Journal of Atmospheric Sciences, 66:766, 2009.
Nonlinear Dynamic Models in Advanced Life Support
NASA Technical Reports Server (NTRS)
Jones, Harry
2002-01-01
To facilitate analysis, ALS systems are often assumed to be linear and time invariant, but they usually have important nonlinear and dynamic aspects. Nonlinear dynamic behavior can be caused by time varying inputs, changes in system parameters, nonlinear system functions, closed loop feedback delays, and limits on buffer storage or processing rates. Dynamic models are usually cataloged according to the number of state variables. The simplest dynamic models are linear, using only integration, multiplication, addition, and subtraction of the state variables. A general linear model with only two state variables can produce all the possible dynamic behavior of linear systems with many state variables, including stability, oscillation, or exponential growth and decay. Linear systems can be described using mathematical analysis. Nonlinear dynamics can be fully explored only by computer simulations of models. Unexpected behavior is produced by simple models having only two or three state variables with simple mathematical relations between them. Closed loop feedback delays are a major source of system instability. Exceeding limits on buffer storage or processing rates forces systems to change operating mode. Different equilibrium points may be reached from different initial conditions. Instead of one stable equilibrium point, the system may have several equilibrium points, oscillate at different frequencies, or even behave chaotically, depending on the system inputs and initial conditions. The frequency spectrum of an output oscillation may contain harmonics and the sums and differences of input frequencies, but it may also contain a stable limit cycle oscillation not related to input frequencies. We must investigate the nonlinear dynamic aspects of advanced life support systems to understand and counter undesirable behavior.
An integral representation of functions in gas-kinetic models
NASA Astrophysics Data System (ADS)
Perepelitsa, Misha
2016-08-01
Motivated by the theory of kinetic models in gas dynamics, we obtain an integral representation of lower semicontinuous functions on {{{R}}^d,} {d≥1}. We use the representation to study the problem of compactness of a family of the solutions of the discrete time BGK model for the compressible Euler equations. We determine sufficient conditions for strong compactness of moments of kinetic densities, in terms of the measures from their integral representations.
Model of THz Magnetization Dynamics
Bocklage, Lars
2016-01-01
Magnetization dynamics can be coherently controlled by THz laser excitation, which can be applied in ultrafast magnetization control and switching. Here, transient magnetization dynamics are calculated for excitation with THz magnetic field pulses. We use the ansatz of Smit and Beljers, to formulate dynamic properties of the magnetization via partial derivatives of the samples free energy density, and extend it to solve the Landau-Lifshitz-equation to obtain the THz transients of the magnetization. The model is used to determine the magnetization response to ultrafast multi- and single-cycle THz pulses. Control of the magnetization trajectory by utilizing the THz pulse shape and polarization is demonstrated. PMID:26956997
Structural dynamics system model reduction
NASA Technical Reports Server (NTRS)
Chen, J. C.; Rose, T. L.; Wada, B. K.
1987-01-01
Loads analysis for structural dynamic systems is usually performed by finite element models. Because of the complexity of the structural system, the model contains large number of degree-of-freedom. The large model is necessary since details of the stress, loads and responses due to mission environments are computed. However, a simplified model is needed for other tasks such as pre-test analysis for modal testing, and control-structural interaction studies. A systematic method of model reduction for modal test analysis is presented. Perhaps it will be of some help in developing a simplified model for the control studies.
Cowan, J.H., Jr. . Chesapeake Biological Lab.); Rose, K.A. )
1991-01-01
We have used a bioenergetically-driven, individual-based model (IBM) of striped bass as a framework for synthesizing available information on population biology and quantifying, in a relative sense, factors that potentially affect year class success. The IBM has been configured to simulate environmental conditions experienced by several striped bass populations; i.e., in the Potomac River, MD; in Hudson River, NY; in the Santee-Cooper River System, SC, and; in the San Joaquin-Sacramento River System CA. These sites represent extremes in the geographic distribution and thus, environmental variability of striped bass spawning. At each location, data describing the physio-chemical and biological characteristics of the spawning population and nursery area are being collected and synthesized by means of a prioritized, directed field sampling program that is organized by the individual-based recruitment model. Here, we employ the striped bass IBM configured for the Potomac River, MD from spawning into the larval period to evaluate the potential for maternal contribution to affect larva survival and growth. Model simulations in which the size distribution and spawning day of females are altered indicate that larva survival is enhanced (3.3-fold increase) when a high fraction of females in the spawning population are large. Larva stage duration also is less ({bar X} = 18.4 d and 22.2 d) when large and small females, respectively, are mothers in simulations. Although inconclusive, these preliminary results for Potomac River striped bass suggest that the effects of female size, timing of spawning nad maternal contribution on recruitment dynamics potentially are important and illustrate our approach to the study of recruitment in striped bass. We hope to use the model, field collections and management alternatives that vary from site to site, in an iterative manner for some time to come. 54 refs., 4 figs., 1 tab.
NASA Astrophysics Data System (ADS)
Zehe, Erwin; Jackisch, Conrad; Blume, Theresa; Haßler, Sibylle; Allroggen, Niklas; Tronicke, Jens
2013-04-01
The CAOS Research Unit recently proposed a hierarchical classification scheme to subdivide a catchment into what we vaguely name classes of functional entities that puts the gradients driving mass and energy flows and their controls on top of the hierarchy and the arrangement of landscape attributes controlling flow resistances along these driving gradients (for instance soil types and apparent preferential pathways) at the second level. We name these functional entities lead topology classes, to highlight that they are characterized by a spatially ordered arrangement of landscape elements along a superordinate driving gradient. Our idea is that these lead topology classes have a distinct way how their structural and textural architecture controls the interplay of storage dynamics and integral response behavior that is typical for all members of a class, but is dissimilar between different classes. This implies that we might gain exemplary understanding of the typical dynamic behavior of the class, when thoroughly studying a few class members. We propose that the main integral catchment functions mass export and drainage, mass redistribution and storage, energy exchange with the atmosphere, as well as energy redistribution and storage - result from spatially organized interactions of processes within lead topologies that operate at different scale levels and partly dominate during different conditions. We distinguish: 1) Lead topologies controlling the land surface energy balance during radiation driven conditions at the plot/pedon scale level. In this case energy fluxes dominate and deplete a vertical temperature gradient that is build up by depleting a gradient in radiation fluxes. Water is a facilitator in this concert due to the high specific heat of vaporization. Slow vertical water fluxes in soil dominate, which are driven by vertical gradients in atmospheric water potential, chemical potential in the plant and in soil hydraulic potentials. 2) Lead topologies
NASA Astrophysics Data System (ADS)
Pérez, Alejandro; Tuckerman, Mark E.
2011-08-01
Higher order factorization schemes are developed for path integral molecular dynamics in order to improve the convergence of estimators for physical observables as a function of the Trotter number. The methods are based on the Takahashi-Imada and Susuki decompositions of the Boltzmann operator. The methods introduced improve the averages of the estimators by using the classical forces needed to carry out the dynamics to construct a posteriori weighting factors for standard path integral molecular dynamics. The new approaches are straightforward to implement in existing path integral codes and carry no significant overhead. The Suzuki higher order factorization was also used to improve the end-to-end distance estimator in open path integral molecular dynamics. The new schemes are tested in various model systems, including an ab initio path integral molecular dynamics calculation on the hydrogen molecule and a quantum water model. The proposed algorithms have potential utility for reducing the cost of path integral molecular dynamics calculations of bulk systems.
Fractional Relativistic Yamaleev Oscillator Model and Its Dynamical Behaviors
NASA Astrophysics Data System (ADS)
Luo, Shao-Kai; He, Jin-Man; Xu, Yan-Li; Zhang, Xiao-Tian
2016-07-01
In the paper we construct a new kind of fractional dynamical model, i.e. the fractional relativistic Yamaleev oscillator model, and explore its dynamical behaviors. We will find that the fractional relativistic Yamaleev oscillator model possesses Lie algebraic structure and satisfies generalized Poisson conservation law. We will also give the Poisson conserved quantities of the model. Further, the relation between conserved quantities and integral invariants of the model is studied and it is proved that, by using the Poisson conserved quantities, we can construct integral invariants of the model. Finally, the stability of the manifold of equilibrium states of the fractional relativistic Yamaleev oscillator model is studied. The paper provides a general method, i.e. fractional generalized Hamiltonian method, for constructing a family of fractional dynamical models of an actual dynamical system.
Baadhe, Rama Raju; Mekala, Naveen Kumar; Palagiri, Satwik Reddy; Parcha, Sreenivasa Rao
2012-07-01
In this case study, we designed a farnesyl pyrophosphate (FPP) biosynthetic network using hybrid functional Petri net with extension (HFPNe) which is derived from traditional Petri net theory and allows easy modeling with graphical approach of various types of entities in the networks together. Our main objective is to improve the production of FPP in yeast, which is further converted to amorphadiene (AD), a precursor of artemisinin (antimalarial drug). Natively, mevalonate (MEV) pathway is present in yeast. Methyl erythritol phosphate pathways (MEP) are present only in higher plant plastids and eubacteria, but not present in yeast. IPP and DAMP are common isomeric intermediate in these two pathways, which immediately yields FPP. By integrating these two pathways in yeast, we augmented the FPP synthesis approximately two folds higher (431.16 U/pt) than in MEV pathway alone (259.91 U/pt) by using HFPNe technique. Further enhanced FPP levels converted to AD by amorphadiene synthase gene yielding 436.5 U/pt of AD which approximately two folds higher compared to the AD (258.5 U/pt) synthesized by MEV pathway exclusively. Simulation and validation processes performed using these models are reliable with identified biological information and data. PMID:22350871
Comer, Clinton S; Harrison, Patti Kelly; Harrison, David W
2015-01-01
Arousal theory as discussed within the present paper refers to those mechanisms and neural systems involved in central nervous system activation and more specifically the systems involved in cortical activation. Historical progress in the evolution of arousal theory has led to a better understanding of the functional neural systems involved in arousal or activation processes and ultimately contributed much to our current theories of emotion. Despite evidence for the dynamic interplay between the left and right cerebral hemispheres, the concepts of cerebral balance and dynamic activation have been emphasized in the neuropsychological literature. A conceptual model is proposed herein that incorporates the unique contributions from multiple neuropsychological theories of arousal and emotion. It is argued that the cerebral hemispheres may play oppositional roles in emotion partially due to the differences in their functional specializations and in their persistence upon activation. In the presence of a threat or provocation, the right hemisphere may activate survival relevant responses partially derived from hemispheric specializations in arousal and emotional processing, including the mobilization of sympathetic drive to promote heightened blood pressure, heart rate, glucose mobilization and respiratory support necessary for the challenge. Oppositional processes and mechanisms are discussed, which may be relevant to the regulatory control over the survival response; however, the capacity of these systems is necessarily limited. A limited capacity mechanism is proposed, which is familiar within other physiological systems, including that providing for the prevention of muscular damage under exceptional demand. This capacity theory is proposed, wherein a link may be expected between exceptional stress within a neural system and damage to the neural system. These mechanisms are proposed to be relevant to emotion and emotional disorders. Discussion is provided on the
Comer, Clinton S; Harrison, Patti Kelly; Harrison, David W
2015-01-01
Arousal theory as discussed within the present paper refers to those mechanisms and neural systems involved in central nervous system activation and more specifically the systems involved in cortical activation. Historical progress in the evolution of arousal theory has led to a better understanding of the functional neural systems involved in arousal or activation processes and ultimately contributed much to our current theories of emotion. Despite evidence for the dynamic interplay between the left and right cerebral hemispheres, the concepts of cerebral balance and dynamic activation have been emphasized in the neuropsychological literature. A conceptual model is proposed herein that incorporates the unique contributions from multiple neuropsychological theories of arousal and emotion. It is argued that the cerebral hemispheres may play oppositional roles in emotion partially due to the differences in their functional specializations and in their persistence upon activation. In the presence of a threat or provocation, the right hemisphere may activate survival relevant responses partially derived from hemispheric specializations in arousal and emotional processing, including the mobilization of sympathetic drive to promote heightened blood pressure, heart rate, glucose mobilization and respiratory support necessary for the challenge. Oppositional processes and mechanisms are discussed, which may be relevant to the regulatory control over the survival response; however, the capacity of these systems is necessarily limited. A limited capacity mechanism is proposed, which is familiar within other physiological systems, including that providing for the prevention of muscular damage under exceptional demand. This capacity theory is proposed, wherein a link may be expected between exceptional stress within a neural system and damage to the neural system. These mechanisms are proposed to be relevant to emotion and emotional disorders. Discussion is provided on the
IAQ evaluation by dynamic modeling
Meckler, M.
1995-12-01
The current ASHRAE Standard 62-1989, in addition to the ventilation rate (VR) procedure, now contains an alternative procedure in Appendix E to achieve acceptable indoor air quality (IAQ). In this article, the author develops a dynamic model for each of the seven most commonly used HVAC systems listed in Appendix E of ASHRAE Standard 62-1989 and demonstrates how these dynamic models work by providing an illustrative example. In this example, the author estimates the concentration of formaldehyde as a function of time in an office occupancy for three types of filters and outlines how to choose filters to decrease outside air flow requirements.
Integrated Hydrosystem Modeling of the California Basin
NASA Astrophysics Data System (ADS)
Davison, J. H.; Hwang, H. T.; Sudicky, E. A.; Mallia, D.; Lin, J. C.
2015-12-01
The Western United States is facing one of the worst droughts on record. Climate change projections predict warmer temperatures, higher evapotranspiration rates, and no foreseeable increase in precipitation. California, in particular, has supplemented their decreased surface water supplies by mining deep groundwater. However, this supply of groundwater is limited, especially with reduced recharge. These combined factors place California's water-demanding society at dire risk. In an effort to quantify California's risks, we present a fully integrated water cycle model that captures the dynamics of the subsurface, land surface, and atmospheric domains over the entire California basin. Our water cycle model combines HydroGeoSphere (HGS), a 3-D control-volume finite element model that accommodates variably-saturated subsurface and surface water flow with evapotranspiration processes to the Weather Research and Forecasting (WRF) model, a 3-D finite difference nonhydrostatic mesoscale atmospheric simulator. The two-way coupling within our model, referred to as HGS-WRF, tightly integrates the water cycling processes by passing precipitation and potential evapotranspiration data from WRF to HGS, while exchanging actual evapotranspiration and soil saturation data from HGS to WRF. Furthermore, HGS-WRF implements a flexible coupling method that allows each model to use a unique mesh while maintaining mass conservation within and between domains. Our simulation replicated field measured evapotranspiration fluxes and showed a strong correlation between the soil saturation (depth to groundwater table) and latent heat fluxes. Altogether, the HGS-WRF California basin model is currently the most complete water resource simulation framework as it combines groundwater, surface water, the unsaturated zone, and the atmosphere into one coupled system.
Pfeffer, A; Das, S; Lawless, D; Ng, B
2006-10-10
Many dynamic systems involve a number of entities that are largely independent of each other but interact with each other via a subset of state variables. We present global/local dynamic models (GLDMs) to capture these kinds of systems. In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself. We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics. We have applied GLDMs to an asymmetric urban warfare environment, in which enemy units form teams to attack important targets, and the task is to detect such teams as they form. Experimental results for this application show that global/local particle filtering outperforms ordinary particle filtering and factored particle filtering.
Multiscale modeling of nucleosome dynamics.
Sharma, Shantanu; Ding, Feng; Dokholyan, Nikolay V
2007-03-01
Nucleosomes form the fundamental building blocks of chromatin. Subtle modifications of the constituent histone tails mediate chromatin stability and regulate gene expression. For this reason, it is important to understand structural dynamics of nucleosomes at atomic levels. We report a novel multiscale model of the fundamental chromatin unit, a nucleosome, using a simplified model for rapid discrete molecular dynamics simulations and an all-atom model for detailed structural investigation. Using a simplified structural model, we perform equilibrium simulations of a single nucleosome at various temperatures. We further reconstruct all-atom nucleosome structures from simulation trajectories. We find that histone tails bind to nucleosomal DNA via strong salt-bridge interactions over a wide range of temperatures, suggesting a mechanism of chromatin structural organization whereby histone tails regulate inter- and intranucleosomal assemblies via binding with nucleosomal DNA. We identify specific regions of the histone core H2A/H2B-H4/H3-H3/H4-H2B/H2A, termed "cold sites", which retain a significant fraction of contacts with adjoining residues throughout the simulation, indicating their functional role in nucleosome organization. Cold sites are clustered around H3-H3, H2A-H4 and H4-H2A interhistone interfaces, indicating the necessity of these contacts for nucleosome stability. Essential dynamics analysis of simulation trajectories shows that bending across the H3-H3 is a prominent mode of intranucleosomal dynamics. We postulate that effects of salts on mononucleosomes can be modeled in discrete molecular dynamics by modulating histone-DNA interaction potentials. Local fluctuations in nucleosomal DNA vary significantly along the DNA sequence, suggesting that only a fraction of histone-DNA contacts make strong interactions dominating mononucleosomal dynamics. Our findings suggest that histone tails have a direct functional role in stabilizing higher-order chromatin
Nonsmooth dynamics in spiking neuron models
NASA Astrophysics Data System (ADS)
Coombes, S.; Thul, R.; Wedgwood, K. C. A.
2012-11-01
Large scale studies of spiking neural networks are a key part of modern approaches to understanding the dynamics of biological neural tissue. One approach in computational neuroscience has been to consider the detailed electrophysiological properties of neurons and build vast computational compartmental models. An alternative has been to develop minimal models of spiking neurons with a reduction in the dimensionality of both parameter and variable space that facilitates more effective simulation studies. In this latter case the single neuron model of choice is often a variant of the classic integrate-and-fire model, which is described by a nonsmooth dynamical system. In this paper we review some of the more popular spiking models of this class and describe the types of spiking pattern that they can generate (ranging from tonic to burst firing). We show that a number of techniques originally developed for the study of impact oscillators are directly relevant to their analysis, particularly those for treating grazing bifurcations. Importantly we highlight one particular single neuron model, capable of generating realistic spike trains, that is both computationally cheap and analytically tractable. This is a planar nonlinear integrate-and-fire model with a piecewise linear vector field and a state dependent reset upon spiking. We call this the PWL-IF model and analyse it at both the single neuron and network level. The techniques and terminology of nonsmooth dynamical systems are used to flesh out the bifurcation structure of the single neuron model, as well as to develop the notion of Lyapunov exponents. We also show how to construct the phase response curve for this system, emphasising that techniques in mathematical neuroscience may also translate back to the field of nonsmooth dynamical systems. The stability of periodic spiking orbits is assessed using a linear stability analysis of spiking times. At the network level we consider linear coupling between voltage
NASA Astrophysics Data System (ADS)
Johnson, Margaret E.; Hummer, Gerhard
2014-07-01
We present a new algorithm for simulating reaction-diffusion equations at single-particle resolution. Our algorithm is designed to be both accurate and simple to implement, and to be applicable to large and heterogeneous systems, including those arising in systems biology applications. We combine the use of the exact Green's function for a pair of reacting particles with the approximate free-diffusion propagator for position updates to particles. Trajectory reweighting in our free-propagator reweighting (FPR) method recovers the exact association rates for a pair of interacting particles at all times. FPR simulations of many-body systems accurately reproduce the theoretically known dynamic behavior for a variety of different reaction types. FPR does not suffer from the loss of efficiency common to other path-reweighting schemes, first, because corrections apply only in the immediate vicinity of reacting particles and, second, because by construction the average weight factor equals one upon leaving this reaction zone. FPR applications include the modeling of pathways and networks of protein-driven processes where reaction rates can vary widely and thousands of proteins may participate in the formation of large assemblies. With a limited amount of bookkeeping necessary to ensure proper association rates for each reactant pair, FPR can account for changes to reaction rates or diffusion constants as a result of reaction events. Importantly, FPR can also be extended to physical descriptions of protein interactions with long-range forces, as we demonstrate here for Coulombic interactions.
Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios
Jarman, Kenneth D.; Brothers, Alan J.; Whitney, Paul D.; Young, Jonathan; Niesen, David A.
2010-06-06
The practice of choosing a single modeling paradigm for predictive analysis can limit the scope and relevance of predictions and their utility to decision-making processes. Considering multiple modeling methods simultaneously may improve this situation, but a better solution provides a framework for directly integrating different, potentially complementary modeling paradigms to enable more comprehensive modeling and predictions, and thus better-informed decisions. The primary challenges of this kind of model integration are to bridge language and conceptual gaps between modeling paradigms, and to determine whether natural and useful linkages can be made in a formal mathematical manner. To address these challenges in the context of two specific modeling paradigms, we explore mathematical and computational options for linking System Dynamics (SD) and Bayesian network (BN) models and incorporating data into the integrated models. We demonstrate that integrated SD/BN models can naturally be described as either state space equations or Dynamic Bayes Nets, which enables the use of many existing computational methods for simulation and data integration. To demonstrate, we apply our model integration approach to techno-social models of insurgent-led attacks and security force counter-measures centered on improvised explosive devices.
Dynamic Clamp Analysis of Synaptic Integration in Sympathetic Ganglia
Horn, J. P.; Kullmann, P. H. M.
2008-01-01
Advances in modern neuroscience require the identification of principles that connect different levels of experimental analysis, from molecular mechanisms to explanations of cellular functions, then to circuits, and, ultimately, to systems and behavior. Here, we examine how synaptic organization of the sympathetic ganglia may enable them to function as use-dependent amplifiers of preganglionic activity and how the gain of this amplification may be modulated by metabotropic signaling mechanisms. The approach combines a general computational model of ganglionic integration together with experimental tests of the model using the dynamic clamp method. In these experiments, we recorded intracellularly from dissociated bullfrog sympathetic neurons and then mimicked physiological synapses with virtual computer-generated synapses. It thus became possible to analyze the synaptic gain by recording cellular responses to complex patterns of synaptic activity that normally arise in vivo from convergent nicotinic and muscarinic synapses. The results of these studies are significant because they illustrate how gain generated through ganglionic integration may contribute to the feedback control of important autonomic behaviors, in particular to the control of the blood pressure. We dedicate this paper to the memory of Professor Vladimir Skok, whose rich legacy in synaptic physiology helped establish the modern paradigm for connecting multiple levels of analysis in studies of the nervous system. PMID:19756262
Gradient navigation model for pedestrian dynamics
NASA Astrophysics Data System (ADS)
Dietrich, Felix; Köster, Gerta
2014-06-01
We present a microscopic ordinary differential equation (ODE)-based model for pedestrian dynamics: the gradient navigation model. The model uses a superposition of gradients of distance functions to directly change the direction of the velocity vector. The velocity is then integrated to obtain the location. The approach differs fundamentally from force-based models needing only three equations to derive the ODE system, as opposed to four in, e.g., the social force model. Also, as a result, pedestrians are no longer subject to inertia. Several other advantages ensue: Model-induced oscillations are avoided completely since no actual forces are present. The derivatives in the equations of motion are smooth and therefore allow the use of fast and accurate high-order numerical integrators. At the same time, the existence and uniqueness of the solution to the ODE system follow almost directly from the smoothness properties. In addition, we introduce a method to calibrate parameters by theoretical arguments based on empirically validated assumptions rather than by numerical tests. These parameters, combined with the accurate integration, yield simulation results with no collisions of pedestrians. Several empirically observed system phenomena emerge without the need to recalibrate the parameter set for each scenario: obstacle avoidance, lane formation, stop-and-go waves, and congestion at bottlenecks. The density evolution in the latter is shown to be quantitatively close to controlled experiments. Likewise, we observe a dependence of the crowd velocity on the local density that compares well with benchmark fundamental diagrams.
NASA Astrophysics Data System (ADS)
Marsh, Jeffrey; Culshaw, Nicholas
2014-05-01
granulite-amphibolite nappe structurally overlying the eclogite-bearing domains indicate that the hot nappe was emplaced over the orogenic core along kilometer-scale, pegmatite-rich, amphibolite-facies shear zones by ca. 1100 Ma. Thus, petrochronological data constrain a sequence of nappe emplacement, HP metamorphism, and migmatization evolving over ~15-20 Myrs, apparently marking a transition in the deep crustal dynamics from a predominantly thickening phase to a thermally weakened lateral flow phase. Ongoing diffusion modeling of chemical gradients in garnet crystals, reaction coronas, and symplectites should yield tighter constraints on the duration of HT residence and cooling/exhumation rates.
Predictive models of battle dynamics
NASA Astrophysics Data System (ADS)
Jelinek, Jan
2001-09-01
The application of control and game theories to improve battle planning and execution requires models, which allow military strategists and commanders to reliably predict the expected outcomes of various alternatives over a long horizon into the future. We have developed probabilistic battle dynamics models, whose building blocks in the form of Markov chains are derived from the first principles, and applied them successfully in the design of the Model Predictive Task Commander package. This paper introduces basic concepts of our modeling approach and explains the probability distributions needed to compute the transition probabilities of the Markov chains.
Observability in dynamic evolutionary models.
López, I; Gámez, M; Carreño, R
2004-02-01
In the paper observability problems are considered in basic dynamic evolutionary models for sexual and asexual populations. Observability means that from the (partial) knowledge of certain phenotypic characteristics the whole evolutionary process can be uniquely recovered. Sufficient conditions are given to guarantee observability for both sexual and asexual populations near an evolutionarily stable state.
Nonlinear Dynamic Model Explains The Solar Dynamic
NASA Astrophysics Data System (ADS)
Kuman, Maria
Nonlinear mathematical model in torus representation describes the solar dynamic. Its graphic presentation shows that without perturbing force the orbits of the planets would be circles; only perturbing force could elongate the circular orbits into ellipses. Since the Hubble telescope found that the planetary orbits of other stars in the Milky Way are also ellipses, powerful perturbing force must be present in our galaxy. Such perturbing force is the Sagittarius Dwarf Galaxy with its heavy Black Hole and leftover stars, which we see orbiting around the center of our galaxy. Since observations of NASA's SDO found that magnetic fields rule the solar activity, we can expect when the planets align and their magnetic moments sum up, the already perturbed stars to reverse their magnetic parity (represented graphically as periodic looping through the hole of the torus). We predict that planets aligned on both sides of the Sun, when their magnetic moments sum-up, would induce more flares in the turbulent equatorial zone, which would bulge. When planets align only on one side of the Sun, the strong magnetic gradient of their asymmetric pull would flip the magnetic poles of the Sun. The Sun would elongate pole-to-pole, emit some energy through the poles, and the solar activity would cease. Similar reshaping and emission was observed in stars called magnetars and experimentally observed in super-liquid fast-spinning Helium nanodroplets. We are certain that NASA's SDO will confirm our predictions.
NASA Astrophysics Data System (ADS)
Landry, J.-S.; Price, D. T.; Ramankutty, N.; Parrott, L.; Matthews, H. D.
2015-12-01
Insects defoliate and kill plants in many ecosystems worldwide. The consequences of these natural processes on terrestrial ecology and nutrient cycling are well established, and their potential climatic effects resulting from modified land-atmosphere exchanges of carbon, energy, and water are increasingly being recognized. We developed a Marauding Insect Module (MIM) to quantify, in the Integrated BIosphere Simulator (IBIS), the consequences of insect activity on biogeochemical and biogeophysical fluxes, also accounting for the effects of altered vegetation dynamics. MIM can simulate damage from broadleaf defoliators, needleleaf defoliators, and bark beetles, with the resulting impacts being estimated by IBIS based on the new, insect-modified state of the vegetation. MIM further accounts for the physical presence and gradual fall of insect-killed dead standing trees. The design of MIM should facilitate the addition of other insect types besides the ones already included and could guide the development of similar modules for other process-based vegetation models. After describing IBIS-MIM, we illustrate the usefulness of the model by presenting results spanning daily to centennial timescales for vegetation dynamics and cycling of carbon, energy, and water following a simulated outbreak of the mountain pine beetle. We then show that these simulated impacts agree with many previous studies based on field measurements, satellite data, or modelling. MIM and similar tools should therefore be of great value in assessing the wide array of impacts resulting from insect-induced plant damage in the Earth system.
Models of the Dynamic Deformations of Polymers
NASA Astrophysics Data System (ADS)
Merzhievsky, Lev; Voronin, Mihail; Korchagina, Anna
2013-06-01
In the process of deformation under the influence of external loading polymeric mediums show the complicated behavior connected with features of their structure. For amorphous polymers distinguish three physical conditions - glasslike, highlyelastic and viscoplastic. To each of the listed conditions there corresponds to mikro - meso- and macrostructural mechanisms of irreversible deformation. In the report the review of results of construction of models for the description of dynamic and shock-wave deformation of the polymers which are based on developed authors representations about mechanisms of irreversible deformation is made. Models include the formulation of the equations of conservation laws, considering effect of a relaxation of shear stresses in the process of deformation. For closing of models the equations of states with nonspherical tensor of deformations and relation for time of a relaxation of shear stresses are constructed. With using of the formulated models a number of problems of dynamic and shock wave deformations has been solved. The results are compared with corresponding experimental date. Development of the used approach are in summary discussed. To taking into account memory and fractal properties of real polymers is supposed of derivatives and integrals of a fractional order to use. Examples of constitutive equations with derivatives of a fractional order are presented. This work is supported by the Integration project of the Siberian Branch of the Russian Academy of Science 64 and grant RFBR 12-01-00726.
Model based control of dynamic atomic force microscope
Lee, Chibum; Salapaka, Srinivasa M.
2015-04-15
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H{sub ∞} control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
Model based control of dynamic atomic force microscope.
Lee, Chibum; Salapaka, Srinivasa M
2015-04-01
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
NASA Astrophysics Data System (ADS)
Nakaten, N.; Kempka, T.; Green, M.; Preshelkova, A.; Merachev, D.; Schlüter, R.; Azzam, R.
2012-04-01
World-wide coal reserves can provide energy supply for several hundred years. Underground coal gasification (UCG) offers an economic and sustainable approach to convert these coal reserves into syngas. As combustion of fossil fuels releases CO2 emissions into the atmosphere, the present study considers a coupling of UCG with CO2 capture and its subsequent storage (CCS) in the previously converted seams, thereby offering a low carbon solution to coal fired power generation. The aim of the present study is to develop a technical-economic model in order to evaluate costeffectiveness, energy demand and CO2 emissions for a coupled UCG-CCS process. The model consists of five dynamic submodels which take into account the processes of air separation (ASU), UCG, syngas processing, electricity production and CCS. Capital (CAPEX) and operational expenditure (OPEX) of these process stages are combined to establish the overall levelised costs of electricity generation (COE). Therefore, the modeling approach developed within the present study allows for a comparison of the COE of the coupled processes with different technologies for electricity production. The influence of parameters relevant for COE (e.g. seam thickness and depth as well as syngas quality) and CO2 emissions (e.g. quality of coal, plant efficiency) were analysed in the context of a sensitivity analysis. Within the UCG&CO2STORAGE project, funded by the EU Research Fund for Coal and Steel (RFCS), a theoretical UCG-CCS feasibility study is being performed for the Dobrudzha coal basin, the selected study area in northeast of Bulgaria. The concealed coalfield is of carboniferous age with high rank bituminous coals. The tectonic conditions in the area are complicated and some of the faults determine coal formation distribution. Explored are four coal formations, but only three of them (Krupen, Gurkovo, Makedonka) are of interest for the project. Investigated for the Dobrudzha coal deposit were 120 geological sections
An Integrated Bayesian Model for DIF Analysis
ERIC Educational Resources Information Center
Soares, Tufi M.; Goncalves, Flavio B.; Gamerman, Dani
2009-01-01
In this article, an integrated Bayesian model for differential item functioning (DIF) analysis is proposed. The model is integrated in the sense of modeling the responses along with the DIF analysis. This approach allows DIF detection and explanation in a simultaneous setup. Previous empirical studies and/or subjective beliefs about the item…
Dynamic Model of Mesoscale Eddies
NASA Astrophysics Data System (ADS)
Dubovikov, Mikhail S.
2003-04-01
Oceanic mesoscale eddies which are analogs of well known synoptic eddies (cyclones and anticyclones), are studied on the basis of the turbulence model originated by Dubovikov (Dubovikov, M.S., "Dynamical model of turbulent eddies", Int. J. Mod. Phys.B7, 4631-4645 (1993).) and further developed by Canuto and Dubovikov (Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: I. General formalism", Phys. Fluids8, 571-586 (1996a) (CD96a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: II. Sheardriven flows", Phys. Fluids8, 587-598 (1996b) (CD96b); Canuto, V.M., Dubovikov, M.S., Cheng, Y. and Dienstfrey, A., "A dynamical model for turbulence: III. Numerical results", Phys. Fluids8, 599-613 (1996c)(CD96c); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "A dynamical model for turbulence: IV. Buoyancy-driven flows", Phys. Fluids9, 2118-2131 (1997a) (CD97a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: V. The effect of rotation", Phys. Fluids9, 2132-2140 (1997b) (CD97b); Canuto, V.M., Dubovikov, M.S. and Wielaard, D.J., "A dynamical model for turbulence: VI. Two dimensional turbulence", Phys. Fluids9, 2141-2147 (1997c) (CD97c); Canuto, V.M. and Dubovikov, M.S., "Physical regimes and dimensional structure of rotating turbulence", Phys. Rev. Lett. 78, 666-669 (1997d) (CD97d); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "Turbulent convection in a spectral model", Phys. Rev. Lett. 78, 662-665 (1997e) (CD97e); Canuto, V.M. and Dubovikov, M.S., "A new approach to turbulence", Int. J. Mod. Phys.12, 3121-3152 (1997f) (CD97f); Canuto, V.M. and Dubovikov, M.S., "Two scaling regimes for rotating Raleigh-Benard convection", Phys. Rev. Letters78, 281-284, (1998) (CD98); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: VII. The five invariants for shear driven flows", Phys. Fluids11, 659-664 (1999a) (CD99a); Canuto, V.M., Dubovikov, M.S. and Yu, G., "A dynamical model for turbulence: VIII. IR and UV
NASA Astrophysics Data System (ADS)
Henry, Pierre-Yves; Aberle, Jochen; Dijkstra, Jasper; Myrhaug, Dag
2016-04-01
-force. Point measurements of turbulence were realized by two ADVs which were located upstream and downstream of the surrogate. Detailed motions of the surrogate were recorded by two cameras above and next to the flume. Image processing allowed for the characterization of the mean deformation and the different modes of horizontal and vertical 'vibration' of the surrogate. The experimental results were compared to numerical simulations obtained from an updated version of the Dynveg code developed by Deltares. The results showed a clear correlation between the cylinder's movements and the (drag) force fluctuations. Due to the swaying motion of the surrogate, the turbulence spectrum is significantly affected when the flow passes the plant model. The succession of several motion modes are observed as the velocity increases, affecting the dominant frequencies in the drag force spectrum and the overall drag. These preliminary results emphasise the importance of the dynamics of the plant flow interactions, and provide an example of the use of new methodologies to provide deeper insights into the physics of complex flows.
Chaos in integrate-and-fire dynamical systems
NASA Astrophysics Data System (ADS)
Coombes, S.
2000-02-01
Integrate-and-fire (IF) mechanisms are often studied within the context of neural dynamics. From a mathematical perspective they represent a minimal yet biologically realistic model of a spiking neuron. The non-smooth nature of the dynamics leads to extremely rich spike train behavior capable of explaining a variety of biological phenomenon including phase-locked states, mode-locking, bursting and pattern formation. The conditions under which chaotic spike trains may be generated in synaptically interacting networks of neural oscillators is an important open question. Using techniques originally introduced for the study of impact oscillators we develop the notion of a Liapunov exponent for IF systems. In the strong coupling regime a network may undergo a discrete Turing-Hopf bifurcation of the firing times from a synchronous state to a state with periodic or quasiperiodic variations of the interspike intervals on closed orbits. Away from the bifurcation point these invariant circles may break up. We establish numerically that in this case the largest IF Liapunov exponent becomes positive. Hence, one route to chaos in networks of synaptically coupled IF neurons is via the breakup of invariant circles.
On whole Abelian model dynamics
Chauca, J.; Doria, R.
2012-09-24
Physics challenge is to determine the objects dynamics. However, there are two ways for deciphering the part. The first one is to search for the ultimate constituents; the second one is to understand its behaviour in whole terms. Therefore, the parts can be defined either from elementary constituents or as whole functions. Historically, science has been moving through the first aspect, however, quarks confinement and complexity are interrupting this usual approach. These relevant facts are supporting for a systemic vision be introduced. Our effort here is to study on the whole meaning through gauge theory. Consider a systemic dynamics oriented through the U(1) - systemic gauge parameter which function is to collect a fields set {l_brace}A{sub {mu}I}{r_brace}. Derive the corresponding whole gauge invariant Lagrangian, equations of motion, Bianchi identities, Noether relationships, charges and Ward-Takahashi equations. Whole Lorentz force and BRST symmetry are also studied. These expressions bring new interpretations further than the usual abelian model. They are generating a systemic system governed by 2N+ 10 classical equations plus Ward-Takahashi identities. A whole dynamics based on the notions of directive and circumstance is producing a set determinism where the parts dynamics are inserted in the whole evolution. A dynamics based on state, collective and individual equations with a systemic interdependence.
Modeling wildfire incident complexity dynamics.
Thompson, Matthew P
2013-01-01
Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management.
Dynamic kirigami structures for integrated solar tracking
NASA Astrophysics Data System (ADS)
Lamoureux, Aaron; Lee, Kyusang; Shlian, Matthew; Forrest, Stephen R.; Shtein, Max
2015-09-01
Optical tracking is often combined with conventional flat panel solar cells to maximize electrical power generation over the course of a day. However, conventional trackers are complex and often require costly and cumbersome structural components to support system weight. Here we use kirigami (the art of paper cutting) to realize novel solar cells where tracking is integral to the structure at the substrate level. Specifically, an elegant cut pattern is made in thin-film gallium arsenide solar cells, which are then stretched to produce an array of tilted surface elements which can be controlled to within +/-1°. We analyze the combined optical and mechanical properties of the tracking system, and demonstrate a mechanically robust system with optical tracking efficiencies matching conventional trackers. This design suggests a pathway towards enabling new applications for solar tracking, as well as inspiring a broader range of optoelectronic and mechanical devices.
Dynamic kirigami structures for integrated solar tracking
Lamoureux, Aaron; Lee, Kyusang; Shlian, Matthew; Forrest, Stephen R.; Shtein, Max
2015-01-01
Optical tracking is often combined with conventional flat panel solar cells to maximize electrical power generation over the course of a day. However, conventional trackers are complex and often require costly and cumbersome structural components to support system weight. Here we use kirigami (the art of paper cutting) to realize novel solar cells where tracking is integral to the structure at the substrate level. Specifically, an elegant cut pattern is made in thin-film gallium arsenide solar cells, which are then stretched to produce an array of tilted surface elements which can be controlled to within ±1°. We analyze the combined optical and mechanical properties of the tracking system, and demonstrate a mechanically robust system with optical tracking efficiencies matching conventional trackers. This design suggests a pathway towards enabling new applications for solar tracking, as well as inspiring a broader range of optoelectronic and mechanical devices. PMID:26348820
Dynamic kirigami structures for integrated solar tracking.
Lamoureux, Aaron; Lee, Kyusang; Shlian, Matthew; Forrest, Stephen R; Shtein, Max
2015-01-01
Optical tracking is often combined with conventional flat panel solar cells to maximize electrical power generation over the course of a day. However, conventional trackers are complex and often require costly and cumbersome structural components to support system weight. Here we use kirigami (the art of paper cutting) to realize novel solar cells where tracking is integral to the structure at the substrate level. Specifically, an elegant cut pattern is made in thin-film gallium arsenide solar cells, which are then stretched to produce an array of tilted surface elements which can be controlled to within ±1°. We analyze the combined optical and mechanical properties of the tracking system, and demonstrate a mechanically robust system with optical tracking efficiencies matching conventional trackers. This design suggests a pathway towards enabling new applications for solar tracking, as well as inspiring a broader range of optoelectronic and mechanical devices. PMID:26348820
Dynamic kirigami structures for integrated solar tracking.
Lamoureux, Aaron; Lee, Kyusang; Shlian, Matthew; Forrest, Stephen R; Shtein, Max
2015-09-08
Optical tracking is often combined with conventional flat panel solar cells to maximize electrical power generation over the course of a day. However, conventional trackers are complex and often require costly and cumbersome structural components to support system weight. Here we use kirigami (the art of paper cutting) to realize novel solar cells where tracking is integral to the structure at the substrate level. Specifically, an elegant cut pattern is made in thin-film gallium arsenide solar cells, which are then stretched to produce an array of tilted surface elements which can be controlled to within ±1°. We analyze the combined optical and mechanical properties of the tracking system, and demonstrate a mechanically robust system with optical tracking efficiencies matching conventional trackers. This design suggests a pathway towards enabling new applications for solar tracking, as well as inspiring a broader range of optoelectronic and mechanical devices.
Resilience, Integrity and Ecosystem Dynamics: Bridging Ecosystem Theory and Management
NASA Astrophysics Data System (ADS)
Müller, Felix; Burkhard, Benjamin; Kroll, Franziska
In this paper different approaches to elucidate ecosystem dynamics are described, illustrated and interrelated. Ecosystem development is distinguished into two separate sequences, a complexifying phase which is characterized by orientor optimization and a destruction based phase which follows disturbances. The two developmental pathways are integrated in a modified illustration of the "adaptive cycle". Based on these fundamentals, the recent definitions of resilience, adaptability and vulnerability are discussed and a modified comprehension is proposed. Thereafter, two case studies about wetland dynamics are presented to demonstrate both, the consequences of disturbance and the potential of ecosystem recovery. In both examples ecosystem integrity is used as a key indicator variable. Based on the presented results the relativity and the normative loading of resilience quantification is worked out. The paper ends with the suggestion that the features of adaptability could be used as an integrative guideline for the analysis of ecosystem dynamics and as a well-suited concept for ecosystem management.
Resilience, Integrity and Ecosystem Dynamics: Bridging Ecosystem Theory and Management
NASA Astrophysics Data System (ADS)
Müller, Felix; Burkhard, Benjamin; Kroll, Franziska
In this paper different approaches to elucidate ecosystem dynamics are described, illustrated and interrelated. Ecosystem development is distinguished into two separate sequences, a complexifying phase which is characterized by orientor optimization and a destruction based phase which follows disturbances. The two developmental pathways are integrated in a modified illustration of the “adaptive cycle”. Based on these fundamentals, the recent definitions of resilience, adaptability and vulnerability are discussed and a modified comprehension is proposed. Thereafter, two case studies about wetland dynamics are presented to demonstrate both, the consequences of disturbance and the potential of ecosystem recovery. In both examples ecosystem integrity is used as a key indicator variable. Based on the presented results the relativity and the normative loading of resilience quantification is worked out. The paper ends with the suggestion that the features of adaptability could be used as an integrative guideline for the analysis of ecosystem dynamics and as a well-suited concept for ecosystem management.
NASA Astrophysics Data System (ADS)
Pioch, Nicholas J.; Lofdahl, Corey; Sao Pedro, Michael; Krikeles, Basil; Morley, Liam
2007-04-01
To foster shared battlespace awareness in Air Operations Centers supporting the Joint Forces Commander and Joint Force Air Component Commander, BAE Systems is developing a Commander's Model Integration and Simulation Toolkit (CMIST), an Integrated Development Environment (IDE) for model authoring, integration, validation, and debugging. CMIST is built on the versatile Eclipse framework, a widely used open development platform comprised of extensible frameworks that enable development of tools for building, deploying, and managing software. CMIST provides two distinct layers: 1) a Commander's IDE for supporting staff to author models spanning the Political, Military, Economic, Social, Infrastructure, Information (PMESII) taxonomy; integrate multiple native (third-party) models; validate model interfaces and outputs; and debug the integrated models via intuitive controls and time series visualization, and 2) a PMESII IDE for modeling and simulation developers to rapidly incorporate new native simulation tools and models to make them available for use in the Commander's IDE. The PMESII IDE provides shared ontologies and repositories for world state, modeling concepts, and native tool characterization. CMIST includes extensible libraries for 1) reusable data transforms for semantic alignment of native data with the shared ontology, and 2) interaction patterns to synchronize multiple native simulations with disparate modeling paradigms, such as continuous-time system dynamics, agent-based discrete event simulation, and aggregate solution methods such as Monte Carlo sampling over dynamic Bayesian networks. This paper describes the CMIST system architecture, our technical approach to addressing these semantic alignment and synchronization problems, and initial results from integrating Political-Military-Economic models of post-war Iraq spanning multiple modeling paradigms.
Global dynamic modeling of a transmission system
NASA Technical Reports Server (NTRS)
Choy, F. K.; Qian, W.
1993-01-01
The work performed on global dynamic simulation and noise correlation of gear transmission systems at the University of Akron is outlined. The objective is to develop a comprehensive procedure to simulate the dynamics of the gear transmission system coupled with the effects of gear box vibrations. The developed numerical model is benchmarked with results from experimental tests at NASA Lewis Research Center. The modal synthesis approach is used to develop the global transient vibration analysis procedure used in the model. Modal dynamic characteristics of the rotor-gear-bearing system are calculated by the matrix transfer method while those of the gear box are evaluated by the finite element method (NASTRAN). A three-dimensional, axial-lateral coupled bearing model is used to couple the rotor vibrations with the gear box motion. The vibrations between the individual rotor systems are coupled through the nonlinear gear mesh interactions. The global equations of motion are solved in modal coordinates and the transient vibration of the system is evaluated by a variable time-stepping integration scheme. The relationship between housing vibration and resulting noise of the gear transmission system is generated by linear transfer functions using experimental data. A nonlinear relationship of the noise components to the fundamental mesh frequency is developed using the hypercoherence function. The numerically simulated vibrations and predicted noise of the gear transmission system are compared with the experimental results from the gear noise test rig at NASA Lewis Research Center. Results of the comparison indicate that the global dynamic model developed can accurately simulate the dynamics of a gear transmission system.
Global dynamic modeling of a transmission system
NASA Astrophysics Data System (ADS)
Choy, F. K.; Qian, W.
1993-04-01
The work performed on global dynamic simulation and noise correlation of gear transmission systems at the University of Akron is outlined. The objective is to develop a comprehensive procedure to simulate the dynamics of the gear transmission system coupled with the effects of gear box vibrations. The developed numerical model is benchmarked with results from experimental tests at NASA Lewis Research Center. The modal synthesis approach is used to develop the global transient vibration analysis procedure used in the model. Modal dynamic characteristics of the rotor-gear-bearing system are calculated by the matrix transfer method while those of the gear box are evaluated by the finite element method (NASTRAN). A three-dimensional, axial-lateral coupled bearing model is used to couple the rotor vibrations with the gear box motion. The vibrations between the individual rotor systems are coupled through the nonlinear gear mesh interactions. The global equations of motion are solved in modal coordinates and the transient vibration of the system is evaluated by a variable time-stepping integration scheme. The relationship between housing vibration and resulting noise of the gear transmission system is generated by linear transfer functions using experimental data. A nonlinear relationship of the noise components to the fundamental mesh frequency is developed using the hypercoherence function. The numerically simulated vibrations and predicted noise of the gear transmission system are compared with the experimental results from the gear noise test rig at NASA Lewis Research Center. Results of the comparison indicate that the global dynamic model developed can accurately simulate the dynamics of a gear transmission system.
Evolution models with extremal dynamics.
Kärenlampi, Petri P
2016-08-01
The random-neighbor version of the Bak-Sneppen biological evolution model is reproduced, along with an analogous model of random replicators, the latter eventually experiencing topology changes. In the absence of topology changes, both types of models self-organize to a critical state. Species extinctions in the replicator system degenerates the self-organization to a random walk, as does vanishing of species interaction for the BS-model. A replicator model with speciation is introduced, experiencing dramatic topology changes. It produces a variety of features, but self-organizes to a possibly critical state only in a few special cases. Speciation-extinction dynamics interfering with self-organization, biological macroevolution probably is not a self-organized critical system. PMID:27626090
Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model
NASA Astrophysics Data System (ADS)
Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin
2016-04-01
-1361. - Frolking S, Roulet NT, Tuittila E, Bubier JL, Quillet A, Talbot J, Richard PJH. 2010. A new model of Holocene peatland net primary production, decomposition, water balance, and peat accumulation. Earth Syst. Dynam., 1, 1-21, doi:10.5194/esd-1-1-2010, 2010. - Hilbert DW, Roulet N, Moore T. 2000. Modelling and analysis of peatlands as dynamical systems. Journal of Ecology 88: 230-242. - Kleinen T, Brovkin V, Schuldt RJ. 2012. A dynamic model of wetland extent and peat accumulation: results for the Holocene. Biogeosciences 9: 235-248. - Kokfelt U, Reuss N, Struyf E, Sonesson M, Rundgren M, Skog G, Rosen P, Hammarlund D. 2010. Wetland development, permafrost history and nutrient cycling inferred from late Holocene peat and lake sediment records in subarctic Sweden. Journal of Paleolimnology 44: 327-342. - Loisel J, et al. 2014. A database and synthesis of northern peatland soil properties and Holocene carbon and nitrogen accumulation. Holocene 24: 1028-1042. - Sitch S, et al. 2008. Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs). Global Change Biology 14: 2015-2039. - Smith B, Prentice IC, Sykes MT. 2001. Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecology and Biogeography 10: 621-637. - Tang J, et al. 2015. Carbon budget estimation of a subarctic catchment using a dynamic ecosystem model at high spatial resolution. Biogeosciences 12: 2791-2808. - Wania R, Ross I, Prentice IC. 2009a. Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes. Global Biogeochemical Cycles 23.
Nonlinear robust control of integrated vehicle dynamics
NASA Astrophysics Data System (ADS)
He, Zhengyi; Ji, Xuewu
2012-02-01
A new methodology to design the vehicle GCC (global chassis control) nonlinear controller is developed in this paper. Firstly, to handle the nonlinear coupling between sprung and unsprung masses, the vehicle is treated as a mechanical system of two-rigid-bodies which has 6 DOF (degree of freedom), including longitudinal, lateral, yaw, vertical, roll and pitch dynamics. The system equation is built in the yaw frame based on Lagrange's method, and it has been proved that the derived system remains the important physical properties of the general mechanical system. Then the GCC design problem is formulated as the trajectory tracking problem for a cascade system, with a Lagrange's system interconnecting with a linear system. The nonlinear robust control design problem of this cascade interconnected system is divided into two H ∞ control problems with respect to the two sub-systems. The parameter uncertainties in the system are tackled by adaptive theory, while the external uncertainties and disturbances are dealt with the H ∞ control theory. And the passivity of the mechanical system is applied to construct the solution of nonlinear H ∞ control problem. Finally, the effectiveness of the proposed controller is validated by simulation results even during the emergency manoeuvre.
NASA Astrophysics Data System (ADS)
Defourny, Pierre; Verbeeck, Hans; Moreau, Inès; De Weirdt, Marjolein; Verhegghen, Astrid; Kibambe-Lubamba, Jean-Paul; Jungers, Quentin; Maignan, Fabienne; Najdovski, Nicolas; Poulter, Benjamin; MacBean, Natasha; Peylin, Philippe
2014-05-01
Vegetation is a major carbon sink and is as such a key component of the international response to climate change caused by the build-up of greenhouse gases in the atmosphere. However, anthropogenic disturbances like deforestation are the primary mechanism that changes ecosystems from carbon sinks to sources, and are hardly included in the current carbon modelling approaches. Moreover, in tropical regions, the seasonal/interannual variability of carbon fluxes is still uncertain and a weak or even no seasonality is taken into account in global vegetation models. In the context of climate change and mitigation policies like "Reducing Emissions from Deforestation and Forest Degradation in Developing Countries" (REDD), it is particularly important to be able to quantify and forecast the vegetation dynamics and carbon fluxes in these regions. The overall objective of the VEGECLIM project is to increase our knowledge on the terrestrial carbon cycle in tropical regions and to improve the forecast of the vegetation dynamics and carbon stocks and fluxes under different climate-change and deforestation scenarios. Such an approach aims to determine whether the African terrestrial carbon balance will remain a net sink or could become a carbon source by the end of the century, according to different climate-change and deforestation scenarios. The research strategy is to integrate the information of the land surface characterizations obtained from 13 years of consistent SPOT-VEGETATION time series (land cover, vegetation phenology through vegetation indices such as the Enhanced Vegetation Index (EVI)) as well as in-situ carbon flux data into the process based ORCHIDEE global vegetation model, capable of simulating vegetation dynamics and carbon balance. Key challenge of this project was to bridge the gap between the land cover and the land surface model teams. Several improvements of the ORCHIDEE model have been realized such as a new seasonal leaf dynamics for tropical evergreen
Quantum tunneling splittings from path-integral molecular dynamics
NASA Astrophysics Data System (ADS)
Mátyus, Edit; Wales, David J.; Althorpe, Stuart C.
2016-03-01
We illustrate how path-integral molecular dynamics can be used to calculate ground-state tunnelling splittings in molecules or clusters. The method obtains the splittings from ratios of density matrix elements between the degenerate wells connected by the tunnelling. We propose a simple thermodynamic integration scheme for evaluating these elements. Numerical tests on fully dimensional malonaldehyde yield tunnelling splittings in good overall agreement with the results of diffusion Monte Carlo calculations.
Integrating Visualizations into Modeling NEST Simulations.
Nowke, Christian; Zielasko, Daniel; Weyers, Benjamin; Peyser, Alexander; Hentschel, Bernd; Kuhlen, Torsten W
2015-01-01
Modeling large-scale spiking neural networks showing realistic biological behavior in their dynamics is a complex and tedious task. Since these networks consist of millions of interconnected neurons, their simulation produces an immense amount of data. In recent years it has become possible to simulate even larger networks. However, solutions to assist researchers in understanding the simulation's complex emergent behavior by means of visualization are still lacking. While developing tools to partially fill this gap, we encountered the challenge to integrate these tools easily into the neuroscientists' daily workflow. To understand what makes this so challenging, we looked into the workflows of our collaborators and analyzed how they use the visualizations to solve their daily problems. We identified two major issues: first, the analysis process can rapidly change focus which requires to switch the visualization tool that assists in the current problem domain. Second, because of the heterogeneous data that results from simulations, researchers want to relate data to investigate these effectively. Since a monolithic application model, processing and visualizing all data modalities and reflecting all combinations of possible workflows in a holistic way, is most likely impossible to develop and to maintain, a software architecture that offers specialized visualization tools that run simultaneously and can be linked together to reflect the current workflow, is a more feasible approach. To this end, we have developed a software architecture that allows neuroscientists to integrate visualization tools more closely into the modeling tasks. In addition, it forms the basis for semantic linking of different visualizations to reflect the current workflow. In this paper, we present this architecture and substantiate the usefulness of our approach by common use cases we encountered in our collaborative work.
Integrating Visualizations into Modeling NEST Simulations
Nowke, Christian; Zielasko, Daniel; Weyers, Benjamin; Peyser, Alexander; Hentschel, Bernd; Kuhlen, Torsten W.
2015-01-01
Modeling large-scale spiking neural networks showing realistic biological behavior in their dynamics is a complex and tedious task. Since these networks consist of millions of interconnected neurons, their simulation produces an immense amount of data. In recent years it has become possible to simulate even larger networks. However, solutions to assist researchers in understanding the simulation's complex emergent behavior by means of visualization are still lacking. While developing tools to partially fill this gap, we encountered the challenge to integrate these tools easily into the neuroscientists' daily workflow. To understand what makes this so challenging, we looked into the workflows of our collaborators and analyzed how they use the visualizations to solve their daily problems. We identified two major issues: first, the analysis process can rapidly change focus which requires to switch the visualization tool that assists in the current problem domain. Second, because of the heterogeneous data that results from simulations, researchers want to relate data to investigate these effectively. Since a monolithic application model, processing and visualizing all data modalities and reflecting all combinations of possible workflows in a holistic way, is most likely impossible to develop and to maintain, a software architecture that offers specialized visualization tools that run simultaneously and can be linked together to reflect the current workflow, is a more feasible approach. To this end, we have developed a software architecture that allows neuroscientists to integrate visualization tools more closely into the modeling tasks. In addition, it forms the basis for semantic linking of different visualizations to reflect the current workflow. In this paper, we present this architecture and substantiate the usefulness of our approach by common use cases we encountered in our collaborative work. PMID:26733860
Technology Transfer Automated Retrieval System (TEKTRAN)
AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic and water quality (H/WQ) simulation components under the Java Connection Framework (JCF) and the Object Modeling System (OMS) environmental modeling framework. AgES-W is implicitly scala...
Modeling Wildfire Incident Complexity Dynamics
Thompson, Matthew P.
2013-01-01
Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management. PMID:23691014
Low level constraints on dynamic contour path integration.
Hall, Sophie; Bourke, Patrick; Guo, Kun
2014-01-01
Contour integration is a fundamental visual process. The constraints on integrating discrete contour elements and the associated neural mechanisms have typically been investigated using static contour paths. However, in our dynamic natural environment objects and scenes vary over space and time. With the aim of investigating the parameters affecting spatiotemporal contour path integration, we measured human contrast detection performance of a briefly presented foveal target embedded in dynamic collinear stimulus sequences (comprising five short 'predictor' bars appearing consecutively towards the fovea, followed by the 'target' bar) in four experiments. The data showed that participants' target detection performance was relatively unchanged when individual contour elements were separated by up to 2° spatial gap or 200 ms temporal gap. Randomising the luminance contrast or colour of the predictors, on the other hand, had similar detrimental effect on grouping dynamic contour path and subsequent target detection performance. Randomising the orientation of the predictors reduced target detection performance greater than introducing misalignment relative to the contour path. The results suggest that the visual system integrates dynamic path elements to bias target detection even when the continuity of path is disrupted in terms of spatial (2°), temporal (200 ms), colour (over 10 colours) and luminance (-25% to 25%) information. We discuss how the findings can be largely reconciled within the functioning of V1 horizontal connections.
INTEGRATED FISCHER TROPSCH MODULAR PROCESS MODEL
Donna Post Guillen; Richard Boardman; Anastasia M. Gribik; Rick A. Wood; Robert A. Carrington
2007-12-01
With declining petroleum reserves, increased world demand, and unstable politics in some of the world’s richest oil producing regions, the capability for the U.S. to produce synthetic liquid fuels from domestic resources is critical to national security and economic stability. Coal, biomass and other carbonaceous materials can be converted to liquid fuels using several conversion processes. The leading candidate for large-scale conversion of coal to liquid fuels is the Fischer Tropsch (FT) process. Process configuration, component selection, and performance are interrelated and dependent on feed characteristics. This paper outlines a flexible modular approach to model an integrated FT process that utilizes a library of key component models, supporting kinetic data and materials and transport properties allowing rapid development of custom integrated plant models. The modular construction will permit rapid assessment of alternative designs and feed stocks. The modeling approach consists of three thrust areas, or “strands” – model/module development, integration of the model elements into an end to end integrated system model, and utilization of the model for plant design. Strand 1, model/module development, entails identifying, developing, and assembling a library of codes, user blocks, and data for FT process unit operations for a custom feedstock and plant description. Strand 2, integration development, provides the framework for linking these component and subsystem models to form an integrated FT plant simulation. Strand 3, plant design, includes testing and validation of the comprehensive model and performing design evaluation analyses.
Modeling of non-spherical droplet dynamics
NASA Astrophysics Data System (ADS)
Deng, Zheng-Tao; Liaw, Goang-Shin; Chou, Lynn C.
1993-07-01
A two-dimensional time-dependent computer code based on the modified Arbitrary Lagrangian Eulerian (ALE) technique, has been developed to simulate non-spherical droplet dynamics and evaporation under convective flows at real rocket combustion chamber conditions. The equations of mass, momentum, energy and species are simultaneously solved for both liquid and gas phases with an accurate dynamic interface tracking. The jump boundary conditions across the deforming droplet surface are obtained by applying the integral forms of conservation of mass, momentum, and energy. At each time step, the interface geometry and flow properties at the droplet surface are implicitly solved by satisfying the interface boundary conditions. A Lagrangian technique was developed to track the arbitrarily moving interface between the liquid droplet and the external gas. An elliptic grid generator is adopted to dynamically reconstruct grids both inside and outside the droplet surface. This code has been used to study droplet oscillation, droplet deformation/breakup, nonspherical droplet evaporation in both low and high pressure convective flows. This presentation briefly describes the numerical algorithm for modeling of the nonspherical droplet dynamics and demonstrates the representative simulation results of nonspherical droplet evaporation at low and high pressure convective flows. Potential applications of this code to rocket combustor design and performance predictions are discussed.
Data modeling of network dynamics
NASA Astrophysics Data System (ADS)
Jaenisch, Holger M.; Handley, James W.; Faucheux, Jeffery P.; Harris, Brad
2004-01-01
This paper highlights Data Modeling theory and its use for text data mining as a graphical network search engine. Data Modeling is then used to create a real-time filter capable of monitoring network traffic down to the port level for unusual dynamics and changes in business as usual. This is accomplished in an unsupervised fashion without a priori knowledge of abnormal characteristics. Two novel methods for converting streaming binary data into a form amenable to graphics based search and change detection are introduced. These techniques are then successfully applied to 1999 KDD Cup network attack data log-on sessions to demonstrate that Data Modeling can detect attacks without prior training on any form of attack behavior. Finally, two new methods for data encryption using these ideas are proposed.
An integrative computational model of multiciliary beating.
Yang, Xingzhou; Dillon, Robert H; Fauci, Lisa J
2008-05-01
The coordinated beating of motile cilia is responsible for ovum transport in the oviduct, transport of mucus in the respiratory tract, and is the basis of motility in many single-celled organisms. The beating of a single motile cilium is achieved by the ATP-driven activation cycles of thousands of dynein molecular motors that cause neighboring microtubule doublets within the ciliary axoneme to slide relative to each other. The precise nature of the spatial and temporal coordination of these individual motors is still not completely understood. The emergent geometry and dynamics of ciliary beating is a consequence of the coupling of these internal force-generating motors, the passive elastic properties of the axonemal structure, and the external viscous, incompressible fluid. Here, we extend our integrative model of a single cilium that couples internal force generation with the surrounding fluid to the investigation of multiciliary interaction. This computational model allows us to predict the geometry of beating, along with the detailed description of the time-dependent flow field both near and away from the cilia. We show that synchrony and metachrony can, indeed, arise from hydrodynamic coupling. We also investigate the effects of viscosity and neighboring cilia on ciliary beat frequency. Moreover, since we have precise flow information, we also measure the dependence of the total flow pumped per cilium per beat upon parameters such as viscosity and ciliary spacing.
Integrated Environmental Modelling: human decisions, human challenges
Glynn, Pierre D.
2015-01-01
Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to issues with frequent, sharply distinguished, feedbacks. Unfortunately, human behaviour is not adapted to the more diffusely experienced problems that IEM typically seeks to address. Twelve biases are identified that affect IEM (and science in general). These biases are supported by personal observations and by the findings of behavioural scientists. A process for critical analysis is proposed that addresses some human challenges of IEM and solicits explicit description of (1) represented processes and information, (2) unrepresented processes and information, and (3) accounting for, and cognizance of, potential human biases. Several other suggestions are also made that generally complement maintaining attitudes of watchful humility, open-mindedness, honesty and transparent accountability. These suggestions include (1) creating a new area of study in the behavioural biogeosciences, (2) using structured processes for engaging the modelling and stakeholder communities in IEM, and (3) using ‘red teams’ to increase resilience of IEM constructs and use.
Mobile Technology Integrated Pedagogical Model
ERIC Educational Resources Information Center
Khan, Arshia
2014-01-01
Integrated curricula and experiential learning are the main ingredients to the recipe to improve student learning in higher education. In the academic computer science world it is mostly assumed that this experiential learning takes place at a business as an internship experience. The intent of this paper is to schism the traditional understanding…
MOS integrated circuit fault modeling
NASA Technical Reports Server (NTRS)
Sievers, M.
1985-01-01
Three digital simulation techniques for MOS integrated circuit faults were examined. These techniques embody a hierarchy of complexity bracketing the range of simulation levels. The digital approaches are: transistor-level, connector-switch-attenuator level, and gate level. The advantages and disadvantages are discussed. Failure characteristics are also described.
NASA Astrophysics Data System (ADS)
Landry, Jean-Sébastien; Price, David T.; Ramankutty, Navin; Parrott, Lael; Damon Matthews, H.
2016-04-01
Insects defoliate and kill plants in many ecosystems worldwide. The consequences of these natural processes on terrestrial ecology and nutrient cycling are well established, and their potential climatic effects resulting from modified land-atmosphere exchanges of carbon, energy, and water are increasingly being recognized. We developed a Marauding Insect Module (MIM) to quantify, in the Integrated BIosphere Simulator (IBIS), the consequences of insect activity on biogeochemical and biogeophysical fluxes, also accounting for the effects of altered vegetation dynamics. MIM can simulate damage from three different insect functional types: (1) defoliators on broadleaf deciduous trees, (2) defoliators on needleleaf evergreen trees, and (3) bark beetles on needleleaf evergreen trees, with the resulting impacts being estimated by IBIS based on the new, insect-modified state of the vegetation. MIM further accounts for the physical presence and gradual fall of insect-killed dead standing trees. The design of MIM should facilitate the addition of other insect types besides the ones already included and could guide the development of similar modules for other process-based vegetation models. After describing IBIS-MIM, we illustrate the usefulness of the model by presenting results spanning daily to centennial timescales for vegetation dynamics and cycling of carbon, energy, and water in a simplified setting and for bark beetles only. More precisely, we simulated 100 % mortality events from the mountain pine beetle for three locations in western Canada. We then show that these simulated impacts agree with many previous studies based on field measurements, satellite data, or modelling. MIM and similar tools should therefore be of great value in assessing the wide array of impacts resulting from insect-induced plant damage in the Earth system.
Volume Dynamics Propulsion System Modeling for Supersonics Vehicle Research
NASA Technical Reports Server (NTRS)
Kopasakis, George; Connolly, Joseph W.; Paxson, Daniel E.; Ma, Peter
2008-01-01
Under the NASA Fundamental Aeronautics Program, the Supersonics Project is working to overcome the obstacles to supersonic commercial flight. The proposed vehicles are long slim body aircraft with pronounced aero-servo-elastic modes. These modes can potentially couple with propulsion system dynamics; leading to performance challenges such as aircraft ride quality and stability. Other disturbances upstream of the engine generated from atmospheric wind gusts, angle of attack, and yaw can have similar effects. In addition, for optimal propulsion system performance, normal inlet-engine operations are required to be closer to compressor stall and inlet unstart. To study these phenomena an integrated model is needed that includes both airframe structural dynamics as well as the propulsion system dynamics. This paper covers the propulsion system component volume dynamics modeling of a turbojet engine that will be used for an integrated vehicle Aero-Propulso-Servo-Elastic model and for propulsion efficiency studies.
Volume Dynamics Propulsion System Modeling for Supersonics Vehicle Research
NASA Technical Reports Server (NTRS)
Kopasakis, George; Connolly, Joseph W.; Paxson, Daniel E.; Ma, Peter
2010-01-01
Under the NASA Fundamental Aeronautics Program the Supersonics Project is working to overcome the obstacles to supersonic commercial flight. The proposed vehicles are long slim body aircraft with pronounced aero-servo-elastic modes. These modes can potentially couple with propulsion system dynamics; leading to performance challenges such as aircraft ride quality and stability. Other disturbances upstream of the engine generated from atmospheric wind gusts, angle of attack, and yaw can have similar effects. In addition, for optimal propulsion system performance, normal inlet-engine operations are required to be closer to compressor stall and inlet unstart. To study these phenomena an integrated model is needed that includes both airframe structural dynamics as well as the propulsion system dynamics. This paper covers the propulsion system component volume dynamics modeling of a turbojet engine that will be used for an integrated vehicle Aero-Propulso-Servo-Elastic model and for propulsion efficiency studies.
Using models in Integrated Ecosystem Assessment of coastal areas
NASA Astrophysics Data System (ADS)
Solidoro, Cosimo; Bandelj, Vinko; Cossarini, Gianpiero; Melaku Canu, Donata; Libralato, Simone
2014-05-01
Numerical Models can greatly contribute to integrated ecological assessment of coastal and marine systems. Indeed, models can: i) assist in the identification of efficient sampling strategy; ii) provide space interpolation and time extrapolation of experiemtanl data which are based on the knowedge on processes dynamics and causal realtionships which is coded within the model, iii) provide estimates of hardly measurable indicators. Furthermore model can provide indication on potential effects of implementation of alternative management policies. Finally, by providing a synthetic representation of an ideal system, based on its essential dynamic, model return a picture of ideal behaviour of a system in the absence of external perturbation, alteration, noise, which might help in the identification of reference behaivuor. As an important example, model based reanalyses of biogeochemical and ecological properties are an urgent need for the estimate of the environmental status and the assessment of efficacy of conservation and environmental policies, also with reference to the enforcement of the European MSFD. However, the use of numerical models, and particularly of ecological models, in modeling and in environmental management still is far from be the rule, possibly because of a lack in realizing the benefits which a full integration of modeling and montoring systems might provide, possibly because of a lack of trust in modeling results, or because many problems still exists in the development, validation and implementation of models. For istance, assessing the validity of model results is a complex process that requires the definition of appropriate indicators, metrics, methodologies and faces with the scarcity of real-time in-situ biogeochemical data. Furthermore, biogeochemical models typically consider dozens of variables which are heavily undersampled. Here we show how the integration of mathematical model and monitoring data can support integrated ecosystem
Distance functions in dynamic integration of data mining techniques
NASA Astrophysics Data System (ADS)
Puuronen, Seppo J.; Tsymbal, Alexey; Terziyan, Vagan
2000-04-01
One of the most important directions in the improvement of data mining and knowledge discovery is the integration of multiple data mining techniques. An integration method needs to be able either to evaluate and select the most appropriate data mining technique or to combine two or more techniques efficiently. A recent integration method for the dynamic integration of multiple data mining techniques is based on the assumption that each of the data mining techniques is the best one inside a certain subarea of the whole domain area. This method uses an instance-based learning approach to collect information about the competence areas of the mining techniques and applies a distance function to determine how close a new instance is to each instance of the training set. The nearest instance or instances are used to predict the performance of the data mining techniques. Because the quality of the integration depends heavily on the suitability of the used distance function, our goal is to analyze the characteristics of different distance functions. In this paper we investigate several distance functions as the very commonly used Euclidean distance function, the Heterogeneous Euclidean- Overlap Metric (HEOM), and the Heterogeneous Value Difference Metric (HVDM), among others. We analyze the effects of the use of different distance functions to the accuracy achieved by dynamic integration when the parameters describing datasets vary. We include also results of our experiments with different datasets which include both nominal and continuous attributes.
COLD-SAT Dynamic Model Computer Code
NASA Technical Reports Server (NTRS)
Bollenbacher, G.; Adams, N. S.
1995-01-01
COLD-SAT Dynamic Model (CSDM) computer code implements six-degree-of-freedom, rigid-body mathematical model for simulation of spacecraft in orbit around Earth. Investigates flow dynamics and thermodynamics of subcritical cryogenic fluids in microgravity. Consists of three parts: translation model, rotation model, and slosh model. Written in FORTRAN 77.
Integrated system dynamics toolbox for water resources planning.
Reno, Marissa Devan; Passell, Howard David; Malczynski, Leonard A.; Peplinski, William J.; Tidwell, Vincent Carroll; Coursey, Don (University of Chicago, Chicago, IL); Hanson, Jason (University of New Mexico, Albuquerque, NM); Grimsrud, Kristine (University of New Mexico, Albuquerque, NM); Thacher, Jennifer (University of New Mexico, Albuquerque, NM); Broadbent, Craig (University of New Mexico, Albuquerque, NM); Brookshire, David; Chemak, Janie; Cockerill, Kristan; Aragon, Carlos , Socorro, NM); Hallett, Heather (New Mexico Univeristy of Technology and Mining , Socorro, NM); Vivoni, Enrique (New Mexico Univeristy of Technology and Mining , Socorro, NM); Roach, Jesse
2006-12-01
Public mediated resource planning is quickly becoming the norm rather than the exception. Unfortunately, supporting tools are lacking that interactively engage the public in the decision-making process and integrate over the myriad values that influence water policy. In the pages of this report we document the first steps toward developing a specialized decision framework to meet this need; specifically, a modular and generic resource-planning ''toolbox''. The technical challenge lies in the integration of the disparate systems of hydrology, ecology, climate, demographics, economics, policy and law, each of which influence the supply and demand for water. Specifically, these systems, their associated processes, and most importantly the constitutive relations that link them must be identified, abstracted, and quantified. For this reason, the toolbox forms a collection of process modules and constitutive relations that the analyst can ''swap'' in and out to model the physical and social systems unique to their problem. This toolbox with all of its modules is developed within the common computational platform of system dynamics linked to a Geographical Information System (GIS). Development of this resource-planning toolbox represents an important foundational element of the proposed interagency center for Computer Aided Dispute Resolution (CADRe). The Center's mission is to manage water conflict through the application of computer-aided collaborative decision-making methods. The Center will promote the use of decision-support technologies within collaborative stakeholder processes to help stakeholders find common ground and create mutually beneficial water management solutions. The Center will also serve to develop new methods and technologies to help federal, state and local water managers find innovative and balanced solutions to the nation's most vexing water problems. The toolbox is an important step toward achieving the technology development goals of this center.
Dynamics of the standard model
Donoghue, J.F.; Golowich, E.; Holstein, B.R.
1992-01-01
Given the remarkable successes of the standard model, it is appropriate that books in the field no longer dwell on the development of our current understanding of high-energy physics but rather present the world as we now know it. Dynamics of the Standard Model by Donoghue, Golowich, and Holstein takes just this approach. Instead of showing the confusion of the 60s and 70s, the authors present the enlightenment of the 80s. They start by describing the basic features and structure of the standard model and then concentrate on the techniques whereby the model can be applied to the physical world, connecting the theory to the experimental results that are the source of its success. Because they do not dwell on ancient (pre-1980) history, the authors of this book are able to go into much more depth in describing how the model can be tied to experiment, and much of the information presented has been accessible previously only in journal articles in a highly technical form. Though all of the authors are card-carrying theorists they go out of their way to stress applications and phenomenology and to show the reader how real-life calculations of use to experimentalists are done and can be applied to physical situations: what assumptions are made in doing them and how well they work. This is of great value both to the experimentalist seeking a deeper understanding of how the standard model can be connected to data and to the theorist wanting to see how detailed the phenomenological predictions of the standard model are and how well the model works. Furthermore, the authors constantly go beyond the lowest-order predictions of the standard model to discuss the corrections to it, as well as higher-order processes, some of which are now experimentally accessible and others of which will take well into the decade to uncover.
Bio-Inspired Neural Model for Learning Dynamic Models
NASA Technical Reports Server (NTRS)
Duong, Tuan; Duong, Vu; Suri, Ronald
2009-01-01
A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.
Characterizing forest ecosystem dynamics through modelling and remote sensing observations
NASA Technical Reports Server (NTRS)
Ranson, K. J.; Smith, J. A.; Hall, F. G.
1988-01-01
To gain a better understanding of northern/boreal forest dynamics over a range of spatial and temporal scales, an approach to integrate models of forest growth, soil processes and radiative transfer with remote sensing observations was developed. The integrated model and remote sensing can be used to examine descriptors of ecosystem dynamics. To examine the scaling of vegetation pattern from the local to the regional domain, distributions of area and perimeters of vegetation community associations were determined from satellite and aircraft images. Relationships between computed fractal dimensions (1.5 to 1.8) and succession history for managed and unmanaged areas are being explored.
An efficient model of drillstring dynamics
NASA Astrophysics Data System (ADS)
Butlin, T.; Langley, R. S.
2015-11-01
High amplitude vibration regimes can cause significant damage to oilwell drillstrings: torsional stick-slip oscillation, forward whirl and backward whirl are each associated with different kinds of damage. There is a need for models of drillstring dynamics that can predict this variety of phenomena that are: efficient enough to carry out parametric studies; simple enough to provide insight into the underlying physics, and which retain sufficient detail to correlate to real drillstrings. The modelling strategy presented in this paper attempts to balance these requirements. It includes the dynamics of the full length of the drillstring over a wide bandwidth but assumes that the main nonlinear effects are due to spatially localised regions of strong nonlinearity, for example at the drillbit cutting interface and at stabilisers where the borehole wall clearance is smallest. The equations of motion can be formed in terms of this reduced set of degrees of freedom, coupled to the nonlinear contact laws and solved by time-domain integration. Two implementations of this approach are presented, using (1) digital filters and (2) a finite element model to describe the linear dynamics. Choosing a sampling period that is less than the group delay between nonlinear degrees of freedom results in a decoupled set of equations that can be solved very efficiently. Several cases are presented which demonstrate a variety of phenomena, including stick-slip oscillation; forward whirl and backward whirl. Parametric studies are shown which reveal the conditions which lead to high amplitude vibration regimes, and an analytic regime boundary is derived for torsional stick-slip oscillation. The digital filter and finite element models are shown to be in good agreement and are similarly computationally efficient. The digital filter approach has the advantage of more intuitive interpretation, while the finite element model is more readily implemented using existing software packages.
AFDM: An Advanced Fluid-Dynamics Model
Bohl, W.R.; Parker, F.R. ); Wilhelm, D. . Inst. fuer Neutronenphysik und Reaktortechnik); Berthier, J. ); Goutagny, L. . Inst. de Protection et de Surete Nucleaire); Ninokata,
1990-09-01
AFDM, or the Advanced Fluid-Dynamics Model, is a computer code that investigates new approaches simulating the multiphase-flow fluid-dynamics aspects of severe accidents in fast reactors. The AFDM formalism starts with differential equations similar to those in the SIMMER-II code. These equations are modified to treat three velocity fields and supplemented with a variety of new models. The AFDM code has 12 topologies describing what material contacts are possible depending on the presence or absence of a given material in a computational cell, on the dominant liquid, and on the continuous phase. Single-phase, bubbly, churn-turbulent, cellular, and dispersed flow regimes are permitted for the pool situations modeled. Virtual mass terms are included for vapor in liquid-continuous flow. Interfacial areas between the continuous and discontinuous phases are convected to allow some tracking of phenomenological histories. Interfacial areas are also modified by models of nucleation, dynamic forces, turbulence, flashing, coalescence, and mass transfer. Heat transfer is generally treated using engineering correlations. Liquid-vapor phase transitions are handled with the nonequilibrium, heat-transfer-limited model, whereas melting and freezing processes are based on equilibrium considerations. Convection is treated using a fractional-step method of time integration, including a semi-implicit pressure iteration. A higher-order differencing option is provided to control numerical diffusion. The Los Alamos SESAME equation-of-state has been implemented using densities and temperatures as the independent variables. AFDM programming has vectorized all computational loops consistent with the objective of producing an exportable code. 24 refs., 4 figs.
Evolving neural models of path integration.
Vickerstaff, R J; Di Paolo, E A
2005-09-01
We use a genetic algorithm to evolve neural models of path integration, with particular emphasis on reproducing the homing behaviour of Cataglyphis fortis ants. This is done within the context of a complete model system, including an explicit representation of the animal's movements within its environment. We show that it is possible to produce a neural network without imposing a priori any particular system for the internal representation of the animal's home vector. The best evolved network obtained is analysed in detail and is found to resemble the bicomponent model of Mittelstaedt. Because of the presence of leaky integration, the model can reproduce the systematic navigation errors found in desert ants. The model also naturally mimics the searching behaviour that ants perform once they have reached their estimate of the nest location. The results support possible roles for leaky integration and cosine-shaped compass response functions in path integration.
Integrating molecular dynamics simulations with chemical probing experiments using SHAPE-FIT
Kirmizialtin, Serdal; Hennelly, Scott P.; Schug, Alexander; Onuchic, Jose N.; Sanbonmatsu, Karissa Y.
2016-01-01
Integration and calibration of molecular dynamics simulations with experimental data remains a challenging endeavor. We have developed a novel method to integrate chemical probing experiments with molecular simulations of RNA molecules by using a native structure-based model. Selective 2’-hydroxyl acylation by primer extension (SHAPE) characterizes the mobility of each residue in the RNA. Our method, SHAPE-FIT, automatically optimizes the potential parameters of the forcefield according to measured reactivities from SHAPE. The optimized parameter set allows simulations of dynamics highly consistent with SHAPE probing experiments. Such atomistic simulations, thoroughly grounded in experiment, can open a new window on RNA structure-function relations. PMID:25726467
Characterizing and Modeling Citation Dynamics
Eom, Young-Ho; Fortunato, Santo
2011-01-01
Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well. PMID:21966387
Integrating population dynamics into mapping human exposure to seismic hazard
NASA Astrophysics Data System (ADS)
Freire, S.; Aubrecht, C.
2012-11-01
Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.
Dynamically Evolving Models of Clusters
NASA Astrophysics Data System (ADS)
Bode, Paul W.; Berrington, Robert C.; Cohn, Haldan N.; Lugger, Phyllis M.
1993-12-01
An N-body method, with up to N=10(5) particles, is used to simulate the dynamical evolution of clusters of galaxies. Each galaxy is represented as an extended structure containing many particles, and the gravitational potential arises from the particles alone. The clusters initially contain 50 or 100 galaxies with masses distributed according to a Schechter function. Mass is apportioned between the galaxies and a smoothly distributed common group halo, or intra-cluster background. The fraction of the total cluster mass initially in this background is varied from 50% to 90%. The models begin in a virialized state. We will be presenting a videotape which contains animations of a number of these models. The animations show important physical processes, such as stripping, merging, and dynamical friction, as they take place, thus allowing one to observe the interplay of these processes in the global evolution of the system. When the galaxies have substantial dark halos (background mass fraction <=75%) a large, centrally located merger remnant is created. The galaxy number density profile around this dominant member becomes cusped, approaching an isothermal distribution. At the same time, the number of multiple nuclei increases. Comparing the 50-galaxy models to MKW/AWM clusters, the values of Delta M12 and the peculiar velocities of the first-ranked galaxies are best fit by a mix of model ages in the range 8--11 Gyr. The growth in luminosity of the first-ranked galaxy during this amount of time is consistent only with weak cannibalism.
Coelho, Rui Moura; Lemos, João Miranda; Alho, Irina; Valério, Duarte; Ferreira, Arlindo R; Costa, Luís; Vinga, Susana
2016-02-21
Bone is a common site for the development of metastasis, as its microenvironment provides the necessary conditions for the growth and proliferation of cancer cells. Several mathematical models to describe the bone remodeling process and how osteoclasts and osteoblasts coupled action ensures bone homeostasis have been proposed and further extended to include the effect of cancer cells. The model proposed here includes the influence of the parathyroid hormone (PTH) as capable of triggering and regulating the bone remodeling cycle. It also considers the secretion of PTH-related protein (PTHrP) by cancer cells, which stimulates the production of receptor activator of nuclear factor kappa-B ligand (RANKL) by osteoblasts that activates osteoclasts, increasing bone resorption and the subsequent release of growth factors entrapped in the bone matrix, which induce tumor growth, giving rise to a self-perpetuating cycle known as the vicious cycle of bone metastases. The model additionally describes how the presence of metastases contributes to the decoupling between bone resorption and formation. Moreover, the effects of anti-cancer and anti-resorptive treatments, through chemotherapy and the administration of bisphosphonates or denosumab, are also included, along with their corresponding pharmacokinetics (PK) and pharmacodynamics (PD). The simulated models, available at http://sels.tecnico.ulisboa.pt/software/, are able to describe bone remodeling cycles, the growth of bone metastases and how treatment can effectively reduce tumor burden on bone and prevent loss of bone strength.
NASA Astrophysics Data System (ADS)
Roda, M.; Spalla, M. I.; Marotta, A. M.
2012-04-01
A numerical modelling approach is used to validate the physical and geological reliability of the ablative subduction mechanism during Alpine convergence in order to interpret the tectonic and metamorphic evolution of an inner portion of the Alpine belt: the Austroalpine Domain. The model predictions and the natural data for the Austroalpine of the Western Alps agree very well in terms of P-T peak conditions, relative chronology of peak and exhumation events, P-T-t paths, thermal gradients and the tectonic evolution of the continental rocks. These findings suggest that a pre-collisional evolution of this domain, with the burial of the continental rocks (induced by ablative subduction of the overriding Adria plate) and their exhumation (driven by an upwelling flow generated in a hydrated mantle wedge) could be a valid mechanism that reproduces the actual tectono-metamorphic configuration of this part of the Alps. There is less agreement between the model predictions and the natural data for the Austroalpine of the Central-Eastern Alps. Based on the natural data available in the literature, a critical discussion of the other proposed mechanisms is presented, and additional geological factors that should be considered within the numerical model are suggested to improve the fitting to the numerical results; these factors include variations in the continental and/or oceanic thickness, variation of the subduction rate and/or slab dip, the initial thermal state of the passive margin, the occurrence of continental collision and an oblique convergence.
Model Identification of Integrated ARMA Processes
ERIC Educational Resources Information Center
Stadnytska, Tetiana; Braun, Simone; Werner, Joachim
2008-01-01
This article evaluates the Smallest Canonical Correlation Method (SCAN) and the Extended Sample Autocorrelation Function (ESACF), automated methods for the Autoregressive Integrated Moving-Average (ARIMA) model selection commonly available in current versions of SAS for Windows, as identification tools for integrated processes. SCAN and ESACF can…
Functional integral approach to the Lipkin model
Kaneko, K.
1988-07-01
A quantum-mechanical formulation involving both collective and independent-particle motions in many-fermion systems is proposed by using the path-integral technique. A semiclassical method of evaluating the functional integral over both fields is described. As an illustration, the Lipkin model is utilized.
Social Ecological Model Analysis for ICT Integration
ERIC Educational Resources Information Center
Zagami, Jason
2013-01-01
ICT integration of teacher preparation programmes was undertaken by the Australian Teaching Teachers for the Future (TTF) project in all 39 Australian teacher education institutions and highlighted the need for guidelines to inform systemic ICT integration approaches. A Social Ecological Model (SEM) was used to positively inform integration…
An integrated physical and biological model for anaerobic lagoons.
Wu, Binxin; Chen, Zhenbin
2011-04-01
A computational fluid dynamics (CFD) model that integrates physical and biological processes for anaerobic lagoons is presented. In the model development, turbulence is represented using a transition k-ω model, heat conduction and solar radiation are included in the thermal model, biological oxygen demand (BOD) reduction is characterized by first-order kinetics, and methane yield rate is expressed as a linear function of temperature. A test of the model applicability is conducted in a covered lagoon digester operated under tropical climate conditions. The commercial CFD software, ANSYS-Fluent, is employed to solve the integrated model. The simulation procedures include solving fluid flow and heat transfer, predicting local resident time based on the converged flow fields, and calculating the BOD reduction and methane production. The simulated results show that monthly methane production varies insignificantly, but the time to achieve a 99% BOD reduction in January is much longer than that in July.
Dynamical Modeling of Mars' Paleoclimate
NASA Technical Reports Server (NTRS)
Richardson, Mark I.
2004-01-01
This report summarizes work undertaken under a one-year grant from the NASA Mars Fundamental Research Program. The goal of the project was to initiate studies of the response of the Martian climate to changes in planetary obliquity and orbital elements. This work was undertaken with a three-dimensional numerical climate model based on the Geophysical Fluid Dynamics Laboratory (GFDL) Skyhi General Circulation Model (GCM). The Mars GCM code was adapted to simulate various obliquity and orbital parameter states. Using a version of the model with a basic water cycle (ice caps, vapor, and clouds), we examined changes in atmospheric water abundances and in the distribution of water ice sheets on the surface. This work resulted in a paper published in the Journal of Geophysical Research - Planets. In addition, the project saw the initial incorporation of a regolith water transport and storage scheme into the model. This scheme allows for interaction between water in the pores of the near subsurface (<3m) and the atmosphere. This work was not complete by the end of the one-year grant, but is now continuing within the auspices of a three-year grant of the same title awarded by the Mars Fundamental Research Program in late 2003.
Integrated Environmental Modeling: Quantitative Microbial Risk Assessment
The presentation discusses the need for microbial assessments and presents a road map associated with quantitative microbial risk assessments, through an integrated environmental modeling approach. A brief introduction and the strengths of the current knowledge are illustrated. W...
Modeling sandhill crane population dynamics
Johnson, D.H.
1979-01-01
The impact of sport hunting on the Central Flyway population of sandhill cranes (Grus canadensis) has been a subject of controversy for several years. A recent study (Buller 1979) presented new and important information on sandhill crane population dynamics. The present report is intended to incorporate that and other information into a mathematical model for the purpose of assessing the long-range impact of hunting on the population of sandhill cranes.The model is a simple deterministic system that embodies density-dependent rates of survival and recruitment. The model employs four kinds of data: (1) spring population size of sandhill cranes, estimated from aerial surveys to be between 250,000 and 400,000 birds; (2) age composition in fall, estimated for 1974-76 to be 11.3% young; (3) annual harvest of cranes, estimated from a variety of sources to be about 5 to 7% of the spring population; and (4) age composition of harvested cranes, which was difficult to estimate but suggests that immatures were 2 to 4 times as vulnerable to hunting as adults.Because the true nature of sandhill crane population dynamics remains so poorly understood, it was necessary to try numerous (768 in all) combinations of survival and recruitment functions, and focus on the relatively few (37) that yielded population sizes and age structures comparable to those extant in the real population. Hunting was then applied to those simulated populations. In all combinations, hunting resulted in a lower asymptotic crane population, the decline ranging from 5 to 54%. The median decline was 22%, which suggests that a hunted sandhill crane population might be about three-fourths as large as it would be if left unhunted. Results apply to the aggregate of the three subspecies in the Central Flyway; individual subspecies or populations could be affected to a greater or lesser degree.
Clark, Michael A.; Joo, Balint; Kennedy, Anthony D.; Silva, Paolo J.
2011-10-01
We show how the integrators used for the molecular dynamics step of the Hybrid Monte Carlo algorithm can be further improved. These integrators not only approximately conserve some Hamiltonian H but conserve exactly a nearby shadow Hamiltonian H~. This property allows for a new tuning method of the molecular dynamics integrator and also allows for a new class of integrators (force-gradient integrators) which is expected to reduce significantly the computational cost of future large-scale gauge field ensemble generation.
Subcycled dynamics in the Spectral Community Atmosphere Model, version 4
Taylor, Mark; Evans, Katherine J; Hack, James J; Worley, Patrick H
2010-01-01
To gain computational efficiency, a split explicit time integration scheme has been implemented in the CAM spectral Eulerian dynamical core. In this scheme, already present in other dynamical core options within the Community Atmosphere Model, version 4 (CAM), the fluid dynamics portion of the model is subcycled to allow a longer time step for the parameterization schemes. The physics parameterization of CAM is not subject to the stability restrictions of the fluid dynamics, and thus finer spatial resolutions of the model do not require the physics time step to be reduced. A brief outline of the subcycling algorithm implementation and resulting model efficiency improvement is presented. A discussion regarding the effect of the climate statistics derived from short model runs is provided.
Laser dynamics: The system dynamics and network theory of optoelectronic integrated circuit design
NASA Astrophysics Data System (ADS)
Tarng, Tom Shinming-T. K.
Laser dynamics is the system dynamics, communication and network theory for the design of opto-electronic integrated circuit (OEIC). Combining the optical network theory and optical communication theory, the system analysis and design for the OEIC fundamental building blocks is considered. These building blocks include the direct current modulation, inject light modulation, wideband filter, super-gain optical amplifier, E/O and O/O optical bistability and current-controlled optical oscillator. Based on the rate equations, the phase diagram and phase portrait analysis is applied to the theoretical studies and numerical simulation. The OEIC system design methodologies are developed for the OEIC design. Stimulating-field-dependent rate equations are used to model the line-width narrowing/broadening mechanism for the CW mode and frequency chirp of semiconductor lasers. The momentary spectra are carrier-density-dependent. Furthermore, the phase portrait analysis and the nonlinear refractive index is used to simulate the single mode frequency chirp. The average spectra of chaos, period doubling, period pulsing, multi-loops and analog modulation are generated and analyzed. The bifurcation-chirp design chart with modulation depth and modulation frequency as parameters is provided for design purpose.
Computational social dynamic modeling of group recruitment.
Berry, Nina M.; Lee, Marinna; Pickett, Marc; Turnley, Jessica Glicken; Smrcka, Julianne D.; Ko, Teresa H.; Moy, Timothy David; Wu, Benjamin C.
2004-01-01
The Seldon software toolkit combines concepts from agent-based modeling and social science to create a computationally social dynamic model for group recruitment. The underlying recruitment model is based on a unique three-level hybrid agent-based architecture that contains simple agents (level one), abstract agents (level two), and cognitive agents (level three). This uniqueness of this architecture begins with abstract agents that permit the model to include social concepts (gang) or institutional concepts (school) into a typical software simulation environment. The future addition of cognitive agents to the recruitment model will provide a unique entity that does not exist in any agent-based modeling toolkits to date. We use social networks to provide an integrated mesh within and between the different levels. This Java based toolkit is used to analyze different social concepts based on initialization input from the user. The input alters a set of parameters used to influence the values associated with the simple agents, abstract agents, and the interactions (simple agent-simple agent or simple agent-abstract agent) between these entities. The results of phase-1 Seldon toolkit provide insight into how certain social concepts apply to different scenario development for inner city gang recruitment.
Terminal Model Of Newtonian Dynamics
NASA Technical Reports Server (NTRS)
Zak, Michail
1994-01-01
Paper presents study of theory of Newtonian dynamics of terminal attractors and repellers, focusing on issues of reversibility vs. irreversibility and deterministic evolution vs. probabilistic or chaotic evolution of dynamic systems. Theory developed called "terminal dynamics" emphasizes difference between it and classical Newtonian dynamics. Also holds promise for explaining irreversibility, unpredictability, probabilistic behavior, and chaos in turbulent flows, in thermodynamic phenomena, and in other dynamic phenomena and systems.
NASA Astrophysics Data System (ADS)
Mohammad, Yasir K.; Pavlova, Olga N.; Pavlov, Alexey N.
2016-04-01
We discuss the problem of quantifying chaotic dynamics at the input of the "integrate-and-fire" (IF) model from the output sequences of interspike intervals (ISIs) for the case when the fluctuating threshold level leads to the appearance of noise in ISI series. We propose a way to detect an ability of computing dynamical characteristics of the input dynamics and the level of noise in the output point processes. The proposed approach is based on the dependence of the largest Lyapunov exponent from the maximal orientation error used at the estimation of the averaged rate of divergence of nearby phase trajectories.
Floods and Societies: Dynamic Modeling
NASA Astrophysics Data System (ADS)
Di Baldassarre, G.; Viglione, A.; Carr, G.; Kuil, L., Jr.; Brandimarte, L.; Bloeschl, G.
2014-12-01
There is growing concern that future flood losses and fatalities might increase significantly in many regions of the world because of rapid urbanization in deltas and floodplains, in addition to sea level rise and climate change. To better anticipate long-term trajectories of future flood risk, there is a need to treat floodplains and deltas as fully coupled human-physical systems. Here we propose a novel approach to explore the long-term behavior emerging from the mutual interactions and feedbacks between physical and social systems. The implementation of our modeling framework shows that green societies, which cope with flooding by resettling out of floodplains, are more resilient to increasing flood frequency than technological societies, which deal with flooding by building levees. Also, we show that when coupled dynamics are accounted for, flood-poor periods could (paradoxically) be more dangerous than flood-rich periods.
SSME structural dynamic model development
NASA Technical Reports Server (NTRS)
Foley, Michael J.
1989-01-01
The high pressure fuel turbopump (HPFTP) is a major component of the Space Shuttle Main Engine (SSME) powerhead. The device is a three stage centrifugal pump that is directly driven by a two stage hot gas turbine. The purpose of the pump is to deliver fuel (liquid hydrogen) from the low pressure fuel turbopump (LPFTP) through the main fuel valve (MFV) to the thrust chamber coolant circuits. In doing so, the pump pressurizes the fuel from an inlet pressure of approximately 178 psi to a discharge pressure of over 6000 psi. At full power level (FPL), the pump rotates at a speed of over 37,000 rpm while generating approximately 77,000 horsepower. Obviously, a pump failure at these speeds and power levels could jeopardize the mission. Results are summarized for work in which the solutions obtained from analytical models of the fuel turbopump impellers are compared with the results obtained from dynamic tests.
Towards dynamical system models of language-related brain potentials
Gerth, Sabrina; Vasishth, Shravan
2008-01-01
Event-related brain potentials (ERP) are important neural correlates of cognitive processes. In the domain of language processing, the N400 and P600 reflect lexical-semantic integration and syntactic processing problems, respectively. We suggest an interpretation of these markers in terms of dynamical system theory and present two nonlinear dynamical models for syntactic computations where different processing strategies correspond to functionally different regions in the system’s phase space. PMID:19003488
Restoration of the Potosi Dynamic Model 2010
Adushita, Yasmin; Leetaru, Hannes
2014-09-30
In topical Report DOE/FE0002068-1 [2] technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the VW1 and the CCS1 wells, structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for Potosi Formation. Intention was for two million tons per annum (MTPA) of CO2 to be injected for 20 years. In this Task the 2010 Potosi heterogeneous model (referred to as the "Potosi Dynamic Model 2010" in this report) was re-run using a new injection scenario; 3.2 MTPA for 30 years. The extent of the Potosi Dynamic Model 2010, however, appeared too small for the new injection target. It was not sufficiently large enough to accommodate the evolution of the plume. Also, it might have overestimated the injection capacity by enhancing too much the pressure relief due to the relatively close proximity between the injector and the infinite acting boundaries. The new model, Potosi Dynamic Model 2013a, was built by extending the Potosi Dynamic Model 2010 grid to 30 miles x 30 miles (48 km by 48 km), while preserving all property modeling workflows and layering. This model was retained as the base case. Potosi Dynamic Model 2013.a gives an average CO2 injection rate of 1.4 MTPA and cumulative injection of 43 Mt in 30 years, which corresponds to 45% of the injection target. This implies that according to this preliminary model, a minimum of three (3) wells could be required to achieve the injection target. The injectivity evaluation of the Potosi formation will be revisited in topical Report 15 during which more data will be integrated in the modeling exercise. A vertical flow performance evaluation could be considered for the succeeding task to determine the appropriate tubing size, the required injection tubing head pressure (THP) and to investigate whether the corresponding well injection rate
Computational fluid dynamics modelling in cardiovascular medicine.
Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P
2016-01-01
This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges.
Computational fluid dynamics modelling in cardiovascular medicine
Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P
2016-01-01
This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards ‘digital patient’ or ‘virtual physiological human’ representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. PMID:26512019
Computational fluid dynamics modelling in cardiovascular medicine.
Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P
2016-01-01
This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. PMID:26512019
Aging and integrating spatial mental models.
Copeland, David E; Radvansky, Gabriel A
2007-09-01
Previous research examining the process of integrating spatial information has suggested that older adults retain an ability to use mental models despite declines in working memory capacity. In the current study of both older and young adults, the authors assessed whether mental model performance declines when working memory limitations affect the ability to retain the information needed to initially construct a model. Participants were presented with 3 spatial descriptions that could have been integrated to form a single mental model (e.g., K. Ehrlich & P. N. Johnson-Laird, 1982). Descriptions were continuous (i.e., AB-BC-CD) or discontinuous (i.e., AB-CD-BC) in various stimulus formats: sentences, word diagrams, and pictures. Across the experiments, older adults showed difficulty integrating information, especially in the discontinuous condition, unless pictures were used. The results suggest that older adults' use of mental models can be compromised when spatial information is presented verbally rather than visually. PMID:17874955
Modeling Insurgent Network Structure and Dynamics
NASA Astrophysics Data System (ADS)
Gabbay, Michael; Thirkill-Mackelprang, Ashley
2010-03-01
We present a methodology for mapping insurgent network structure based on their public rhetoric. Indicators of cooperative links between insurgent groups at both the leadership and rank-and-file levels are used, such as joint policy statements or joint operations claims. In addition, a targeting policy measure is constructed on the basis of insurgent targeting claims. Network diagrams which integrate these measures of insurgent cooperation and ideology are generated for different periods of the Iraqi and Afghan insurgencies. The network diagrams exhibit meaningful changes which track the evolution of the strategic environment faced by insurgent groups. Correlations between targeting policy and network structure indicate that insurgent targeting claims are aimed at establishing a group identity among the spectrum of rank-and-file insurgency supporters. A dynamical systems model of insurgent alliance formation and factionalism is presented which evolves the relationship between insurgent group dyads as a function of their ideological differences and their current relationships. The ability of the model to qualitatively and quantitatively capture insurgent network dynamics observed in the data is discussed.
An integrated framework of spatiotemporal dynamics of binocular rivalry.
Kang, Min-Suk; Blake, Randolph
2011-01-01
Fluctuations in perceptual dominance during binocular rivalry exhibit several hallmark characteristics. First, dominance switches are not periodic but, instead, stochastic: perception changes unpredictably. Second, despite being stochastic, average durations of rivalry dominance vary dependent on the strength of the rival stimuli: variations in contrast, luminance, or spatial frequency produce predictable changes in average dominance durations and, hence, in alternation rate. Third, perceptual switches originate locally and spread globally over time, sometimes as traveling waves of dominance: rivalry transitions are spatiotemporal events. This essay (1) reviews recent advances in our understanding of the bases of these three hallmark characteristics of binocular rivalry dynamics and (2) provides an integrated framework to account for those dynamics using cooperative and competitive spatial interactions among local neural circuits distributed over the visual field's retinotopic map. We close with speculations about how that framework might incorporate top-down influences on rivalry dynamics.
Quantifying chaotic dynamics from integrate-and-fire processes
Pavlov, A. N.; Pavlova, O. N.; Mohammad, Y. K.; Kurths, J.
2015-01-15
Characterizing chaotic dynamics from integrate-and-fire (IF) interspike intervals (ISIs) is relatively easy performed at high firing rates. When the firing rate is low, a correct estimation of Lyapunov exponents (LEs) describing dynamical features of complex oscillations reflected in the IF ISI sequences becomes more complicated. In this work we discuss peculiarities and limitations of quantifying chaotic dynamics from IF point processes. We consider main factors leading to underestimated LEs and demonstrate a way of improving numerical determining of LEs from IF ISI sequences. We show that estimations of the two largest LEs can be performed using around 400 mean periods of chaotic oscillations in the regime of phase-coherent chaos. Application to real data is discussed.
NASA Astrophysics Data System (ADS)
Sutrisno; Widowati; Solikhin
2016-06-01
In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well.
Development of a Stirling System Dynamic Model With Enhanced Thermodynamics
NASA Technical Reports Server (NTRS)
Regan, Timothy F.; Lewandowski, Edward J.
2005-01-01
The Stirling Convertor System Dynamic Model developed at NASA Glenn Research Center is a software model developed from first principles that includes the mechanical and mounting dynamics, the thermodynamics, the linear alternator, and the controller of a free-piston Stirling power convertor, along with the end user load. As such it represents the first detailed modeling tool for fully integrated Stirling convertor-based power systems. The thermodynamics of the model were originally a form of the isothermal Stirling cycle. In some situations it may be desirable to improve the accuracy of the Stirling cycle portion of the model. An option under consideration is to enhance the SDM thermodynamics by coupling the model with Gedeon Associates Sage simulation code. The result will be a model that gives a more accurate prediction of the performance and dynamics of the free-piston Stirling convertor. A method of integrating the Sage simulation code with the System Dynamic Model is described. Results of SDM and Sage simulation are compared to test data. Model parameter estimation and model validation are discussed.
Development and Integration of Control System Models
NASA Technical Reports Server (NTRS)
Kim, Young K.
1998-01-01
The computer simulation tool, TREETOPS, has been upgraded and used at NASA/MSFC to model various complicated mechanical systems and to perform their dynamics and control analysis with pointing control systems. A TREETOPS model of Advanced X-ray Astrophysics Facility - Imaging (AXAF-1) dynamics and control system was developed to evaluate the AXAF-I pointing performance for Normal Pointing Mode. An optical model of Shooting Star Experiment (SSE) was also developed and its optical performance analysis was done using the MACOS software.
Model Predictive Control of Integrated Gasification Combined Cycle Power Plants
B. Wayne Bequette; Priyadarshi Mahapatra
2010-08-31
The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.
Integrating model abstraction into monitoring strategies
Technology Transfer Automated Retrieval System (TEKTRAN)
This study was designed and performed to investigate the opportunities and benefits of integrating model abstraction techniques into monitoring strategies. The study focused on future applications of modeling to contingency planning and management of potential and actual contaminant release sites wi...
An introduction to Space Weather Integrated Modeling
NASA Astrophysics Data System (ADS)
Zhong, D.; Feng, X.
2012-12-01
The need for a software toolkit that integrates space weather models and data is one of many challenges we are facing with when applying the models to space weather forecasting. To meet this challenge, we have developed Space Weather Integrated Modeling (SWIM) that is capable of analysis and visualizations of the results from a diverse set of space weather models. SWIM has a modular design and is written in Python, by using NumPy, matplotlib, and the Visualization ToolKit (VTK). SWIM provides data management module to read a variety of spacecraft data products and a specific data format of Solar-Interplanetary Conservation Element/Solution Element MHD model (SIP-CESE MHD model) for the study of solar-terrestrial phenomena. Data analysis, visualization and graphic user interface modules are also presented in a user-friendly way to run the integrated models and visualize the 2-D and 3-D data sets interactively. With these tools we can locally or remotely analysis the model result rapidly, such as extraction of data on specific location in time-sequence data sets, plotting interplanetary magnetic field lines, multi-slicing of solar wind speed, volume rendering of solar wind density, animation of time-sequence data sets, comparing between model result and observational data. To speed-up the analysis, an in-situ visualization interface is used to support visualizing the data 'on-the-fly'. We also modified some critical time-consuming analysis and visualization methods with the aid of GPU and multi-core CPU. We have used this tool to visualize the data of SIP-CESE MHD model in real time, and integrated the Database Model of shock arrival, Shock Propagation Model, Dst forecasting model and SIP-CESE MHD model developed by SIGMA Weather Group at State Key Laboratory of Space Weather/CAS.
Sensory feedback in a bump attractor model of path integration.
Poll, Daniel B; Nguyen, Khanh; Kilpatrick, Zachary P
2016-04-01
Mammalian spatial navigation systems utilize several different sensory information channels. This information is converted into a neural code that represents the animal's current position in space by engaging place cell, grid cell, and head direction cell networks. In particular, sensory landmark (allothetic) cues can be utilized in concert with an animal's knowledge of its own velocity (idiothetic) cues to generate a more accurate representation of position than path integration provides on its own (Battaglia et al. The Journal of Neuroscience 24(19):4541-4550 (2004)). We develop a computational model that merges path integration with feedback from external sensory cues that provide a reliable representation of spatial position along an annular track. Starting with a continuous bump attractor model, we explore the impact of synaptic spatial asymmetry and heterogeneity, which disrupt the position code of the path integration process. We use asymptotic analysis to reduce the bump attractor model to a single scalar equation whose potential represents the impact of asymmetry and heterogeneity. Such imperfections cause errors to build up when the network performs path integration, but these errors can be corrected by an external control signal representing the effects of sensory cues. We demonstrate that there is an optimal strength and decay rate of the control signal when cues appear either periodically or randomly. A similar analysis is performed when errors in path integration arise from dynamic noise fluctuations. Again, there is an optimal strength and decay of discrete control that minimizes the path integration error.
Modeling integrated cellular machinery using hybrid Petri-Boolean networks.
Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay
2013-01-01
The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more
Integrated Modeling Tools for Thermal Analysis and Applications
NASA Technical Reports Server (NTRS)
Milman, Mark H.; Needels, Laura; Papalexandris, Miltiadis
1999-01-01
Integrated modeling of spacecraft systems is a rapidly evolving area in which multidisciplinary models are developed to design and analyze spacecraft configurations. These models are especially important in the early design stages where rapid trades between subsystems can substantially impact design decisions. Integrated modeling is one of the cornerstones of two of NASA's planned missions in the Origins Program -- the Next Generation Space Telescope (NGST) and the Space Interferometry Mission (SIM). Common modeling tools for control design and opto-mechanical analysis have recently emerged and are becoming increasingly widely used. A discipline that has been somewhat less integrated, but is nevertheless of critical concern for high precision optical instruments, is thermal analysis and design. A major factor contributing to this mild estrangement is that the modeling philosophies and objectives for structural and thermal systems typically do not coincide. Consequently the tools that are used in these discplines suffer a degree of incompatibility, each having developed along their own evolutionary path. Although standard thermal tools have worked relatively well in the past. integration with other disciplines requires revisiting modeling assumptions and solution methods. Over the past several years we have been developing a MATLAB based integrated modeling tool called IMOS (Integrated Modeling of Optical Systems) which integrates many aspects of structural, optical, control and dynamical analysis disciplines. Recent efforts have included developing a thermal modeling and analysis capability, which is the subject of this article. Currently, the IMOS thermal suite contains steady state and transient heat equation solvers, and the ability to set up the linear conduction network from an IMOS finite element model. The IMOS code generates linear conduction elements associated with plates and beams/rods of the thermal network directly from the finite element structural
Modeling for System Integration Studies (Presentation)
Orwig, K. D.
2012-05-01
This presentation describes some the data requirements needed for grid integration modeling and provides real-world examples of such data and its format. Renewable energy integration studies evaluate the operational impacts of variable generation. Transmission planning studies investigate where new transmission is needed to transfer energy from generation sources to load centers. Both use time-synchronized wind and solar energy production and load as inputs. Both examine high renewable energy penetration scenarios in the future.
CSM solutions of rotating blade dynamics using integrating matrices
NASA Technical Reports Server (NTRS)
Lakin, William D.
1992-01-01
The dynamic behavior of flexible rotating beams continues to receive considerable research attention as it constitutes a fundamental problem in applied mechanics. Further, beams comprise parts of many rotating structures of engineering significance. A topic of particular interest at the present time involves the development of techniques for obtaining the behavior in both space and time of a rotor acted upon by a simple airload loading. Most current work on problems of this type use solution techniques based on normal modes. It is certainly true that normal modes cannot be disregarded, as knowledge of natural blade frequencies is always important. However, the present work has considered a computational structural mechanics (CSM) approach to rotor blade dynamics problems in which the physical properties of the rotor blade provide input for a direct numerical solution of the relevant boundary-and-initial-value problem. Analysis of the dynamics of a given rotor system may require solution of the governing equations over a long time interval corresponding to many revolutions of the loaded flexible blade. For this reason, most of the common techniques in computational mechanics, which treat the space-time behavior concurrently, cannot be applied to the rotor dynamics problem without a large expenditure of computational resources. By contrast, the integrating matrix technique of computational mechanics has the ability to consistently incorporate boundary conditions and 'remove' dependence on a space variable. For problems involving both space and time, this feature of the integrating matrix approach thus can generate a 'splitting' which forms the basis of an efficient CSM method for numerical solution of rotor dynamics problems.
The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging
Schirner, Michael; McIntosh, Anthony R.; Jirsa, Viktor K.
2013-01-01
Abstract Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected—ideally functionally relevant—aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept. PMID:23442172
Combination of dynamic and integral methods for generating reproducible functional CBF images
Lammertsma, A.A.; Cunningham, V.J.; Deiber, M.P.; Heather, J.D.; Bloomfield, P.M.; Nutt, J.; Frackowiak, R.S.; Jones, T. )
1990-09-01
A new method to measure regional CBF is presented, applying both dynamic and integral analyses to a dynamic sequence of positron emission tomographic scans collected during and following the administration of H2(15)O (inhalation of C15O2). The dynamic analysis is used to correct continuously monitored arterial whole-blood activity for delay and dispersion relative to tissue scans. An integral analysis including corrections for this delay and dispersion is then used to calculate CBF on a pixel-by-pixel basis. Normal values and reproducibility over a 2-h period are presented, together with the results of validation and simulation studies. The results indicate that the single-tissue compartment model adequately describes the distribution of H2(15)O in the brain, without recourse to postulating a nonexchanging water pool.
International summit on integrated environmental modeling
Gaber, Noha; Geller, Gary; Glynn, Pierre; Laniak, Gerry; Voinov, Alexey; Whelan, Gene; Roger, Moore; Hughes, Andrew
2013-01-01
This report describes the International Summit on Integrated Environmental Modeling (IEM), held in Reston, VA, on 7th-9th December 2010. The meeting brought together 57 scientists and managers from leading US and European government and non-governmental organizations, universities and companies together with international organizations convened over a number of years, including: the US Environmental Protection Agency (USEPA) workshop on Collaborative Approaches to Integrated Modeling: Better Integration for Better Decisionmaking (December, 2008); the AGU Fall Meeting, San Francisco (December 2009); and the International Congress on Environmental Modeling and Software (July 2010). From these meetings there is now recognition that many separate communities are involved in developing IEM. The aim of the Summit was to bring together two key groupings, the US and Europe, with the intention of creating a community open to all.
Integrated Modelling - the next steps (Invited)
NASA Astrophysics Data System (ADS)
Moore, R. V.
2010-12-01
Integrated modelling (IM) has made considerable advances over the past decade but it has not yet been taken up as an operational tool in the way that its proponents had hoped. The reasons why will be discussed in Session U17. This talk will propose topics for a research and development programme and suggest an institutional structure which, together, could overcome the present obstacles. Their combined aim would be first to make IM into an operational tool useable by competent public authorities and commercial companies and, in time, to see it evolve into the modelling equivalent of Google Maps, something accessible and useable by anyone with a PC or an iphone and an internet connection. In a recent study, a number of government agencies, water authorities and utilities applied integrated modelling to operational problems. While the project demonstrated that IM could be used in an operational setting and had benefit, it also highlighted the advances that would be required for its widespread uptake. These were: greatly improving the ease with which models could be a) made linkable, b) linked and c) run; developing a methodology for applying integrated modelling; developing practical options for calibrating and validating linked models; addressing the science issues that arise when models are linked; extending the range of modelling concepts that can be linked; enabling interface standards to pass uncertainty information; making the interface standards platform independent; extending the range of platforms to include those for high performance computing; developing the concept of modelling components as web services; separating simulation code from the model’s GUI, so that all the results from the linked models can be viewed through a single GUI; developing scenario management systems so that that there is an audit trail of the version of each model and dataset used in each linked model run. In addition to the above, there is a need to build a set of integrated
Multiple integral representation for the trigonometric SOS model with domain wall boundaries
NASA Astrophysics Data System (ADS)
Galleas, W.
2012-05-01
Using the dynamical Yang-Baxter algebra we derive a functional equation for the partition function of the trigonometric SOS model with domain wall boundary conditions. The solution of the equation is given in terms of a multiple contour integral.
Modeling population dynamics: A quantile approach.
Chavas, Jean-Paul
2015-04-01
The paper investigates the modeling of population dynamics, both conceptually and empirically. It presents a reduced form representation that provides a flexible characterization of population dynamics. It leads to the specification of a threshold quantile autoregression (TQAR) model, which captures nonlinear dynamics by allowing lag effects to vary across quantiles of the distribution as well as with previous population levels. The usefulness of the model is illustrated in an application to the dynamics of lynx population. We find statistical evidence that the quantile autoregression parameters vary across quantiles (thus rejecting the AR model as well as the TAR model) as well as with past populations (thus rejecting the quantile autoregression QAR model). The results document the nature of dynamics and cycle in the lynx population over time. They show how both the period of the cycle and the speed of population adjustment vary with population level and environmental conditions. PMID:25661501
Multidimensional Langevin Modeling of Nonoverdamped Dynamics
NASA Astrophysics Data System (ADS)
Schaudinnus, Norbert; Bastian, Björn; Hegger, Rainer; Stock, Gerhard
2015-07-01
Based on a given time series, data-driven Langevin modeling aims to construct a low-dimensional dynamical model of the underlying system. When dealing with physical data as provided by, e.g., all-atom molecular dynamics simulations, effects due to small damping may be important to correctly describe the statistics (e.g., the energy landscape) and the dynamics (e.g., transition times). To include these effects in a dynamical model, an algorithm that propagates a second-order Langevin scheme is derived, which facilitates the treatment of multidimensional data. Adopting extensive molecular dynamics simulations of a peptide helix, a five-dimensional model is constructed that successfully forecasts the complex structural dynamics of the system. Neglect of small damping effects, on the other hand, is shown to lead to significant errors and inconsistencies.
An integrated coastal model for aeolian and hydrodynamic sediment transport
NASA Astrophysics Data System (ADS)
Baart, F.; den Bieman, J.; van Koningsveld, M.; Luijendijk, A. P.; Parteli, E. J. R.; Plant, N. G.; Roelvink, J. A.; Storms, J. E. A.; de Vries, S.; van Thiel de Vries, J. S. M.; Ye, Q.
2012-04-01
Dunes are formed by aeolian and hydrodynamic processes. Over the last decades numerical models were developed that capture our knowledge of the hydrodynamic transport of sediment near the coast. At the same time others have worked on creating numerical models for aeolian-based transport. Here we show a coastal model that integrates three existing numerical models into one online-coupled system. The XBeach model simulates storm-induced erosion (Roelvink et al., 2009). The Delft3D model (Lesser et al., 2004) is used for long term morphology and the Dune model (Durán et al., 2010) is used to simulate the aeolian transport. These three models were adapted to be able to exchange bed updates in real time. The updated models were integrated using the ESMF framework (Hill et al., 2004), a system for composing coupled modeling systems. The goal of this integrated model is to capture the relevant coastal processes at different time and spatial scales. Aeolian transport can be relevant during storms when the strong winds are generating new dunes, but also under relative mild conditions when the dunes are strengthened by transporting sand from the intertidal area to the dunes. Hydrodynamic transport is also relevant during storms, when high water in combination with waves can cause dunes to avalanche and erode. While under normal conditions the hydrodynamic transport can result in an onshore transport of sediment up to the intertidal area. The exchange of sediment in the intertidal area is a dynamic interaction between the hydrodynamic transport and the aeolian transport. This dynamic interaction is particularly important for simulating dune evolution at timescales longer than individual storm events. The main contribution of the integrated model is that it simulates the dynamic exchange of sediment between aeolian and hydrodynamic models in the intertidal area. By integrating the numerical models, we hope to develop a model that has a broader scope and applicability than
Integrated facilities modeling using QUEST and IGRIP
Davis, K.R.; Haan, E.R.
1995-08-01
A QUEST model and associated detailed IGRIP models were developed and used to simulate several workcells in a proposed Plutonium Storage Facility (PSF). The models are being used by team members assigned to the program to improve communication and to assist in evaluating concepts and in performing trade-off studies which will result in recommendations and a final design. The model was designed so that it could be changed easily. The added flexibility techniques used to make changes easily are described in this paper in addition to techniques for integrating the QUEST and IGRIP products. Many of these techniques are generic in nature and can be applied to any modeling endeavor.
Phase Behavior of Active Swimmers in Depletants: Molecular Dynamics and Integral Equation Theory
NASA Astrophysics Data System (ADS)
Das, Subir K.; Egorov, Sergei A.; Trefz, Benjamin; Virnau, Peter; Binder, Kurt
2014-05-01
We study the structure and phase behavior of a binary mixture where one of the components is self-propelling in nature. The interparticle interactions in the system are taken from the Asakura-Oosawa model for colloid-polymer mixtures for which the phase diagram is known. In the current model version, the colloid particles are made active using the Vicsek model for self-propelling particles. The resultant active system is studied by molecular dynamics methods and integral equation theory. Both methods produce results consistent with each other and demonstrate that the Vicsek model-based activity facilitates phase separation, thus, broadening the coexistence region.
Phase behavior of active swimmers in depletants: molecular dynamics and integral equation theory.
Das, Subir K; Egorov, Sergei A; Trefz, Benjamin; Virnau, Peter; Binder, Kurt
2014-05-16
We study the structure and phase behavior of a binary mixture where one of the components is self-propelling in nature. The interparticle interactions in the system are taken from the Asakura-Oosawa model for colloid-polymer mixtures for which the phase diagram is known. In the current model version, the colloid particles are made active using the Vicsek model for self-propelling particles. The resultant active system is studied by molecular dynamics methods and integral equation theory. Both methods produce results consistent with each other and demonstrate that the Vicsek model-based activity facilitates phase separation, thus, broadening the coexistence region. PMID:24877969
Nonlinear Behaviour in Long Range Integrable Models with Spin
NASA Astrophysics Data System (ADS)
Kulkarni, Manas; Franchini, Fabio; Abanov, Alexander
2010-03-01
We study nonlinear aspects of long range integrable models with spin by going beyond the Luttinger Liquid theory. We present here [1], the fully nonlinear dynamics of spin and charge in spin-Calogero model (sCM), an integrable 1D model of quantum spin-1/2 particles interacting through inverse square interaction and exchange. Hydrodynamic equations of motion are written for this model in the regime where gradient corrections to the exact theory may be neglected. In this approximation, variables separate in terms of dressed Fermi momenta of the model. Hydrodynamic equations reduce to a set of decoupled Riemann-Hopf equations for the dressed Fermi momenta. We study the dynamics of some non-equilibrium spin-charge configurations for times smaller than the time-scale of gradient catastrophe. We then show [2] how this field theory allows to calculate correlation functions that cannot be considered with conventional bosonization. We also highlight the connections between sCM, Haldane-Shastry model and λ=2 spin-less Calogero model. [1] M. Kulkarni, F. Franchini, A. G. Abanov, Phys. Rev. B 80, 165105 (2009) [2] F. Franchini, M. Kulkarni, Nucl. Phys. B, 825, 320 (2010)
System Dynamics Models and Institutional Pricing Decisions.
ERIC Educational Resources Information Center
Chen, Fiona
1986-01-01
A system dynamics model for the pricing of tuition is presented, illustrating how such models enable decision-makers to anticipate cause-and-effect relationships and test alternative courses of action. (Author)
Preliminary shuttle structural dynamics modeling design study
NASA Technical Reports Server (NTRS)
1972-01-01
The design and development of a structural dynamics model of the space shuttle are discussed. The model provides for early study of structural dynamics problems, permits evaluation of the accuracy of the structural and hydroelastic analysis methods used on test vehicles, and provides for efficiently evaluating potential cost savings in structural dynamic testing techniques. The discussion is developed around the modes in which major input forces and responses occur and the significant structural details in these modes.
Cong, Zhang; Yun-Jie, Wu
2016-07-01
In this paper, a novel cascade type design model is transformed from the simulation model, which has a broader scope of application, for integrated guidance and control (IGC). A novel non-singular terminal dynamic surface control based IGC method is proposed. It can guarantee the missile with multiple disturbances fast hits the target with high accuracy, while considering the terminal impact angular constraint commendably. And the stability of the closed-loop system is strictly proved. The essence of integrated guidance and control design philosophy is reached that establishing a direct relation between guidance and attitude equations by "intermediate states" and then designing an IGC law for the obtained integrated cascade design model. Finally, a series of simulations and comparisons with a 6-DOF nonlinear missile that includes all aerodynamic effects are demonstrated to illustrate the effectiveness and advantage of the proposed IGC method.
Cong, Zhang; Yun-Jie, Wu
2016-07-01
In this paper, a novel cascade type design model is transformed from the simulation model, which has a broader scope of application, for integrated guidance and control (IGC). A novel non-singular terminal dynamic surface control based IGC method is proposed. It can guarantee the missile with multiple disturbances fast hits the target with high accuracy, while considering the terminal impact angular constraint commendably. And the stability of the closed-loop system is strictly proved. The essence of integrated guidance and control design philosophy is reached that establishing a direct relation between guidance and attitude equations by "intermediate states" and then designing an IGC law for the obtained integrated cascade design model. Finally, a series of simulations and comparisons with a 6-DOF nonlinear missile that includes all aerodynamic effects are demonstrated to illustrate the effectiveness and advantage of the proposed IGC method. PMID:27049772
Neuronal integration of dynamic sources: Bayesian learning and Bayesian inference
NASA Astrophysics Data System (ADS)
Siegelmann, Hava T.; Holzman, Lars E.
2010-09-01
One of the brain's most basic functions is integrating sensory data from diverse sources. This ability causes us to question whether the neural system is computationally capable of intelligently integrating data, not only when sources have known, fixed relative dependencies but also when it must determine such relative weightings based on dynamic conditions, and then use these learned weightings to accurately infer information about the world. We suggest that the brain is, in fact, fully capable of computing this parallel task in a single network and describe a neural inspired circuit with this property. Our implementation suggests the possibility that evidence learning requires a more complex organization of the network than was previously assumed, where neurons have different specialties, whose emergence brings the desired adaptivity seen in human online inference.
The Challenges to Coupling Dynamic Geospatial Models
Goldstein, N
2006-06-23
Many applications of modeling spatial dynamic systems focus on a single system and a single process, ignoring the geographic and systemic context of the processes being modeled. A solution to this problem is the coupled modeling of spatial dynamic systems. Coupled modeling is challenging for both technical reasons, as well as conceptual reasons. This paper explores the benefits and challenges to coupling or linking spatial dynamic models, from loose coupling, where information transfer between models is done by hand, to tight coupling, where two (or more) models are merged as one. To illustrate the challenges, a coupled model of Urbanization and Wildfire Risk is presented. This model, called Vesta, was applied to the Santa Barbara, California region (using real geospatial data), where Urbanization and Wildfires occur and recur, respectively. The preliminary results of the model coupling illustrate that coupled modeling can lead to insight into the consequences of processes acting on their own.
Comparative dynamics in a health investment model.
Eisenring, C
1999-10-01
The method of comparative dynamics fully exploits the inter-temporal structure of optimal control models. I derive comparative dynamic results in a simplified demand for health model. The effect of a change in the depreciation rate on the optimal paths for health capital and investment in health is studied by use of a phase diagram.
Generalized Gaussian wave packet dynamics: Integrable and chaotic systems
NASA Astrophysics Data System (ADS)
Pal, Harinder; Vyas, Manan; Tomsovic, Steven
2016-01-01
The ultimate semiclassical wave packet propagation technique is a complex, time-dependent Wentzel-Kramers-Brillouin method known as generalized Gaussian wave packet dynamics (GGWPD). It requires overcoming many technical difficulties in order to be carried out fully in practice. In its place roughly twenty years ago, linearized wave packet dynamics was generalized to methods that include sets of off-center, real trajectories for both classically integrable and chaotic dynamical systems that completely capture the dynamical transport. The connections between those methods and GGWPD are developed in a way that enables a far more practical implementation of GGWPD. The generally complex saddle-point trajectories at its foundation are found using a multidimensional Newton-Raphson root search method that begins with the set of off-center, real trajectories. This is possible because there is a one-to-one correspondence. The neighboring trajectories associated with each off-center, real trajectory form a path that crosses a unique saddle; there are exceptions that are straightforward to identify. The method is applied to the kicked rotor to demonstrate the accuracy improvement as a function of ℏ that comes with using the saddle-point trajectories.
Generalized Gaussian wave packet dynamics: Integrable and chaotic systems.
Pal, Harinder; Vyas, Manan; Tomsovic, Steven
2016-01-01
The ultimate semiclassical wave packet propagation technique is a complex, time-dependent Wentzel-Kramers-Brillouin method known as generalized Gaussian wave packet dynamics (GGWPD). It requires overcoming many technical difficulties in order to be carried out fully in practice. In its place roughly twenty years ago, linearized wave packet dynamics was generalized to methods that include sets of off-center, real trajectories for both classically integrable and chaotic dynamical systems that completely capture the dynamical transport. The connections between those methods and GGWPD are developed in a way that enables a far more practical implementation of GGWPD. The generally complex saddle-point trajectories at its foundation are found using a multidimensional Newton-Raphson root search method that begins with the set of off-center, real trajectories. This is possible because there is a one-to-one correspondence. The neighboring trajectories associated with each off-center, real trajectory form a path that crosses a unique saddle; there are exceptions that are straightforward to identify. The method is applied to the kicked rotor to demonstrate the accuracy improvement as a function of ℏ that comes with using the saddle-point trajectories.
CTBT integrated verification system evaluation model supplement
EDENBURN,MICHAEL W.; BUNTING,MARCUS; PAYNE JR.,ARTHUR C.; TROST,LAWRENCE C.
2000-03-02
Sandia National Laboratories has developed a computer based model called IVSEM (Integrated Verification System Evaluation Model) to estimate the performance of a nuclear detonation monitoring system. The IVSEM project was initiated in June 1994, by Sandia's Monitoring Systems and Technology Center and has been funded by the U.S. Department of Energy's Office of Nonproliferation and National Security (DOE/NN). IVSEM is a simple, ''top-level,'' modeling tool which estimates the performance of a Comprehensive Nuclear Test Ban Treaty (CTBT) monitoring system and can help explore the impact of various sensor system concepts and technology advancements on CTBT monitoring. One of IVSEM's unique features is that it integrates results from the various CTBT sensor technologies (seismic, in sound, radionuclide, and hydroacoustic) and allows the user to investigate synergy among the technologies. Specifically, IVSEM estimates the detection effectiveness (probability of detection), location accuracy, and identification capability of the integrated system and of each technology subsystem individually. The model attempts to accurately estimate the monitoring system's performance at medium interfaces (air-land, air-water) and for some evasive testing methods such as seismic decoupling. The original IVSEM report, CTBT Integrated Verification System Evaluation Model, SAND97-25 18, described version 1.2 of IVSEM. This report describes the changes made to IVSEM version 1.2 and the addition of identification capability estimates that have been incorporated into IVSEM version 2.0.
Prethermalization and universal dynamics in near-integrable quantum systems
NASA Astrophysics Data System (ADS)
Langen, Tim; Gasenzer, Thomas; Schmiedmayer, Jörg
2016-06-01
We review the recent progress in the understanding of the relaxation of isolated near-integrable quantum many-body systems. Focusing on prethermalization and universal dynamics following a quench, we describe the experiments with ultracold atomic gases that illustrate these phenomena and summarize the essential theoretical concepts employed to interpret them. Our discussion highlights the key topics that link the different approaches to this interdisciplinary field, including the generalized Gibbs ensemble, non-thermal fixed points, critical slowing and universal scaling. Finally, we point to new experimental challenges demonstrating these fundamental features of many-body quantum systems out of equilibrium.
New generalizations of the integrable problems in rigid body dynamics
NASA Astrophysics Data System (ADS)
Yehia, H. M.
1997-10-01
We consider the general problem of motion of a rigid body about a fixed point under the action of an axisymmetric combination of potential and gyroscopic forces. We introduce six cases of this problem which are completely integrable for arbitrary initial conditions. The new cases generalize by several parameters all, but one, of the known results in the subject of rigid body dynamics. Namely, we generalize all the results due to Euler, Lagrange, Clebsch, Kovalevskaya, Brun and Lyapunov and also their subsequent generalizations by Rubanovsky and the present author.
Data and Model Integration Promoting Interdisciplinarity
NASA Astrophysics Data System (ADS)
Koike, T.
2014-12-01
It is very difficult to reflect accumulated subsystem knowledge into holistic knowledge. Knowledge about a whole system can rarely be introduced into a targeted subsystem. In many cases, knowledge in one discipline is inapplicable to other disciplines. We are far from resolving cross-disciplinary issues. It is critically important to establish interdisciplinarity so that scientific knowledge can transcend disciplines. We need to share information and develop knowledge interlinkages by building models and exchanging tools. We need to tackle a large increase in the volume and diversity of data from observing the Earth. The volume of data stored has exponentially increased. Previously, almost all of the large-volume data came from satellites, but model outputs occupy the largest volume in general. To address the large diversity of data, we should develop an ontology system for technical and geographical terms in coupling with a metadata design according to international standards. In collaboration between Earth environment scientists and IT group, we should accelerate data archiving by including data loading, quality checking and metadata registration, and enrich data-searching capability. DIAS also enables us to perform integrated research and realize interdisciplinarity. For example, climate change should be addressed in collaboration between the climate models, integrated assessment models including energy, economy, agriculture, health, and the models of adaptation, vulnerability, and human settlement and infrastructure. These models identify water as central to these systems. If a water expert can develop an interrelated system including each component, the integrated crisis can be addressed by collaboration with various disciplines. To realize this purpose, we are developing a water-related data- and model-integration system called a water cycle integrator (WCI).
Parametric solution, traveling wave solution for integrable dynamical system
NASA Astrophysics Data System (ADS)
Qiao, Zhijun; Holm, Darryl
2002-11-01
In this talk, I introduce a new integrable hierarchy of nonlinear dynamical equations. In this hierarchy there are the following representative equations: u_t=partial^5x u^-2/3, u_t=partial^5_xfrac(u^-1/3)_xx -2(u^-1/6)_x^2u,u_xxt+3u_xxu_x+u_xxxu=0. The first two are in the positive order hierarchy while the 3rd one is in the negative order hierarchy. The whole hierarchy is shown integrable through solving a key 3× 3 matrix equation. The 3×3 Lax pairs and their adjoint representations are nonlinearized to be two Liouville-integrable canonical Hamiltonian systems. Based on the integrability of 6N-dimensional systems we give the parametric solution of the positive hierarchy.In particular, we obtain the parametric solution of the equation u_t=partial^5x u^-2/3. Finally, we give the travelling wave solution (TWS) of the above three equations. The TWSs of the first two equations have singularity, but the TWS of the 3rd one is continuous. For the 5th-order equation, its smooth parametric solution can not include its singular TWS. We also analyse the initial Gaussian solutions for the equations u_t=partial^5x u^-2/3, and u_xxt+3u_xxu_x+u_xxxu=0. The former is stable, but the latter is not.
Integrating language models into classifiers for BCI communication: a review
NASA Astrophysics Data System (ADS)
Speier, W.; Arnold, C.; Pouratian, N.
2016-06-01
Objective. The present review systematically examines the integration of language models to improve classifier performance in brain–computer interface (BCI) communication systems. Approach. The domain of natural language has been studied extensively in linguistics and has been used in the natural language processing field in applications including information extraction, machine translation, and speech recognition. While these methods have been used for years in traditional augmentative and assistive communication devices, information about the output domain has largely been ignored in BCI communication systems. Over the last few years, BCI communication systems have started to leverage this information through the inclusion of language models. Main results. Although this movement began only recently, studies have already shown the potential of language integration in BCI communication and it has become a growing field in BCI research. BCI communication systems using language models in their classifiers have progressed down several parallel paths, including: word completion; signal classification; integration of process models; dynamic stopping; unsupervised learning; error correction; and evaluation. Significance. Each of these methods have shown significant progress, but have largely been addressed separately. Combining these methods could use the full potential of language model, yielding further performance improvements. This integration should be a priority as the field works to create a BCI system that meets the needs of the amyotrophic lateral sclerosis population.
Integrating language models into classifiers for BCI communication: a review
NASA Astrophysics Data System (ADS)
Speier, W.; Arnold, C.; Pouratian, N.
2016-06-01
Objective. The present review systematically examines the integration of language models to improve classifier performance in brain-computer interface (BCI) communication systems. Approach. The domain of natural language has been studied extensively in linguistics and has been used in the natural language processing field in applications including information extraction, machine translation, and speech recognition. While these methods have been used for years in traditional augmentative and assistive communication devices, information about the output domain has largely been ignored in BCI communication systems. Over the last few years, BCI communication systems have started to leverage this information through the inclusion of language models. Main results. Although this movement began only recently, studies have already shown the potential of language integration in BCI communication and it has become a growing field in BCI research. BCI communication systems using language models in their classifiers have progressed down several parallel paths, including: word completion; signal classification; integration of process models; dynamic stopping; unsupervised learning; error correction; and evaluation. Significance. Each of these methods have shown significant progress, but have largely been addressed separately. Combining these methods could use the full potential of language model, yielding further performance improvements. This integration should be a priority as the field works to create a BCI system that meets the needs of the amyotrophic lateral sclerosis population.
Integrated odour modelling for sewage treatment works.
Gostelow, P; Parsons, S A; Lovell, M
2004-01-01
Odours from sewage treatment works are a significant source of environmental annoyance. There is a need for tools to assess the degree of annoyance caused, and to assess strategies for mitigation of the problem. This is the role of odour modelling. Four main stages are important in the development of an odour problem. Firstly, the odorous molecules must be formed in the liquid phase. They must then transfer from the liquid to the gaseous phase. They are then transported through the atmosphere to the population surrounding the odour source, and are then perceived and assessed by that population. Odour modelling as currently practised tends to concentrate on the transportation of odorants through the atmosphere, with the other areas receiving less attention. Instead, odour modelling should consider each stage in an integrated manner. This paper describes the development of integrated odour models for annoyance prediction. The models describe the liquid-phase transformations and emission of hydrogen sulphide from sewage treatment processes. Model output is in a form suitable for integration with dispersion models, the predictions of which can in turn be used to indicate the probability of annoyance. The models have been applied to both hypothetical and real sewage treatment works cases. Simulation results have highlighted the potential variability of emission rates from sewage treatment works, resulting from flow, quality and meteorological variations. Emission rate variations can have significant effects on annoyance predictions, which is an important finding, as they are usually considered to be fixed and only meteorological variations are considered in predicting the odour footprint. Areas for further development of integrated odour modelling are discussed, in particular the search for improved links between analytical and sensory measurements, and a better understanding of dose/response relationships for odour annoyance.
Hydration dynamics near a model protein surface
Russo, Daniela; Hura, Greg; Head-Gordon, Teresa
2003-09-01
The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces.
Benchmarking of Planning Models Using Recorded Dynamics
Huang, Zhenyu; Yang, Bo; Kosterev, Dmitry
2009-03-15
Power system planning extensively uses model simulation to understand the dynamic behaviors and determine the operating limits of a power system. Model quality is key to the safety and reliability of electricity delivery. Planning model benchmarking, or model validation, has been one of the central topics in power engineering studies for years. As model validation aims at obtaining reasonable models to represent dynamic behavior of power system components, it has been essential to validate models against actual measurements. The development of phasor technology provides such measurements and represents a new opportunity for model validation as phasor measurements can capture power system dynamics with high-speed, time-synchronized data. Previously, methods for rigorous comparison of model simulation and recorded dynamics have been developed and applied to quantify model quality of power plants in the Western Electricity Coordinating Council (WECC). These methods can locate model components which need improvement. Recent work continues this effort and focuses on how model parameters may be calibrated to match recorded dynamics after the problematic model components are identified. A calibration method using Extended Kalman Filter technique is being developed. This paper provides an overview of prior work on model validation and presents new development on the calibration method and initial results of model parameter calibration.
Ryll, A; Bucher, J; Bonin, A; Bongard, S; Gonçalves, E; Saez-Rodriguez, J; Niklas, J; Klamt, S
2014-10-01
Systems biology has to increasingly cope with large- and multi-scale biological systems. Many successful in silico representations and simulations of various cellular modules proved mathematical modelling to be an important tool in gaining a solid understanding of biological phenomena. However, models spanning different functional layers (e.g. metabolism, signalling and gene regulation) are still scarce. Consequently, model integration methods capable of fusing different types of biological networks and various model formalisms become a key methodology to increase the scope of cellular processes covered by mathematical models. Here we propose a new integration approach to couple logical models of signalling or/and gene-regulatory networks with kinetic models of metabolic processes. The procedure ends up with an integrated dynamic model of both layers relying on differential equations. The feasibility of the approach is shown in an illustrative case study integrating a kinetic model of central metabolic pathways in hepatocytes with a Boolean logical network depicting the hormonally induced signal transduction and gene regulation events involved. In silico simulations demonstrate the integrated model to qualitatively describe the physiological switch-like behaviour of hepatocytes in response to nutritionally regulated changes in extracellular glucagon and insulin levels. A simulated failure mode scenario addressing insulin resistance furthermore illustrates the pharmacological potential of a model covering interactions between signalling, gene regulation and metabolism. PMID:25063553
Integrated Human Futures Modeling in Egypt
Passell, Howard D.; Aamir, Munaf Syed; Bernard, Michael Lewis; Beyeler, Walter E.; Fellner, Karen Marie; Hayden, Nancy Kay; Jeffers, Robert Fredric; Keller, Elizabeth James Kistin; Malczynski, Leonard A.; Mitchell, Michael David; Silver, Emily; Tidwell, Vincent C.; Villa, Daniel; Vugrin, Eric D.; Engelke, Peter; Burrow, Mat; Keith, Bruce
2016-01-01
The Integrated Human Futures Project provides a set of analytical and quantitative modeling and simulation tools that help explore the links among human social, economic, and ecological conditions, human resilience, conflict, and peace, and allows users to simulate tradeoffs and consequences associated with different future development and mitigation scenarios. In the current study, we integrate five distinct modeling platforms to simulate the potential risk of social unrest in Egypt resulting from the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile in Ethiopia. The five platforms simulate hydrology, agriculture, economy, human ecology, and human psychology/behavior, and show how impacts derived from development initiatives in one sector (e.g., hydrology) might ripple through to affect other sectors and how development and security concerns may be triggered across the region. This approach evaluates potential consequences, intended and unintended, associated with strategic policy actions that span the development-security nexus at the national, regional, and international levels. Model results are not intended to provide explicit predictions, but rather to provide system-level insight for policy makers into the dynamics among these interacting sectors, and to demonstrate an approach to evaluating short- and long-term policy trade-offs across different policy domains and stakeholders. The GERD project is critical to government-planned development efforts in Ethiopia but is expected to reduce downstream freshwater availability in the Nile Basin, fueling fears of negative social and economic impacts that could threaten stability and security in Egypt. We tested these hypotheses and came to the following preliminary conclusions. First, the GERD will have an important short-term impact on water availability, food production, and hydropower production in Egypt, depending on the short- term reservoir fill rate. Second, the GERD will have a very small impact on
Correlation of ground tests and analyses of a dynamically scaled space station model configuration
NASA Technical Reports Server (NTRS)
Javeed, Mehzad; Edighoffer, Harold H.; Mcgowan, Paul E.
1993-01-01
Verification of analytical models through correlation with ground test results of a complex space truss structure is demonstrated. A multi-component, dynamically scaled space station model configuration is the focus structure for this work. Previously established test/analysis correlation procedures are used to develop improved component analytical models. Integrated system analytical models, consisting of updated component analytical models, are compared with modal test results to establish the accuracy of system-level dynamic predictions. Design sensitivity model updating methods are shown to be effective for providing improved component analytical models. Also, the effects of component model accuracy and interface modeling fidelity on the accuracy of integrated model predictions is examined.
Correlation of ground tests and analyses of a dynamically scaled Space Station model configuration
NASA Technical Reports Server (NTRS)
Javeed, Mehzad; Edighoffer, Harold H.; Mcgowan, Paul E.
1993-01-01
Verification of analytical models through correlation with ground test results of a complex space truss structure is demonstrated. A multi-component, dynamically scaled space station model configuration is the focus structure for this work. Previously established test/analysis correlation procedures are used to develop improved component analytical models. Integrated system analytical models, consisting of updated component analytical models, are compared with modal test results to establish the accuracy of system-level dynamic predictions. Design sensitivity model updating methods are shown to be effective for providing improved component analytical models. Also, the effects of component model accuracy and interface modeling fidelity on the accuracy of integrated model predictions is examined.
Ensemble-type numerical uncertainty information from single model integrations
Rauser, Florian Marotzke, Jochem; Korn, Peter
2015-07-01
We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of the influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.
PET2OGS: Algorithms to link the static model of Petrel with the dynamic model of OpenGeoSys
NASA Astrophysics Data System (ADS)
Park, C.-H.; Shinn, Y. J.; Park, Y.-C.; Huh, D.-G.; Lee, S. K.
2014-01-01
A set of three algorithms named PET2OGS is developed to integrate the static model (Petrel) with the dynamic model (OpenGeoSys). PET2OGS consists of three sub-algorithms that convert finite difference methods (FDMs) grids to finite element methods (FEMs) grids. The algorithms and the workflow of the integration procedures are described in detail. After the proposed algorithms are tested on a variety of grids both in homogeneous and heterogeneous media, the integrated platform of the static and dynamic models is applied to model CO2 storage in a saline aquifer. A successful demonstration of the proposed algorithms proved a robust integration of the platform. With some minor modifications of the algorithms in the part of input and output, the proposed algorithms can be extended to integrate different combinations of FDM-based static models and FEM-based dynamic models beyond the example combination in the paper.
Analytical properties of a three-compartmental dynamical demographic model
NASA Astrophysics Data System (ADS)
Postnikov, E. B.
2015-07-01
The three-compartmental demographic model by Korotaeyv-Malkov-Khaltourina, connecting population size, economic surplus, and education level, is considered from the point of view of dynamical systems theory. It is shown that there exist two integrals of motion, which enables the system to be reduced to one nonlinear ordinary differential equation. The study of its structure provides analytical criteria for the dominance ranges of the dynamics of Malthus and Kremer. Additionally, the particular ranges of parameters enable the derived general ordinary differential equations to be reduced to the models of Gompertz and Thoularis-Wallace.
A modeling technique for STOVL ejector and volume dynamics
NASA Technical Reports Server (NTRS)
Drummond, C. K.; Barankiewicz, W. S.
1990-01-01
New models for thrust augmenting ejector performance prediction and feeder duct dynamic analysis are presented and applied to a proposed Short Take Off and Vertical Landing (STOVL) aircraft configuration. Central to the analysis is the nontraditional treatment of the time-dependent volume integrals in the otherwise conventional control-volume approach. In the case of the thrust augmenting ejector, the analysis required a new relationship for transfer of kinetic energy from the primary flow to the secondary flow. Extraction of the required empirical corrections from current steady-state experimental data is discussed; a possible approach for modeling insight through Computational Fluid Dynamics (CFD) is presented.
Design for and efficient dynamic climate model with realistic geography
NASA Technical Reports Server (NTRS)
Suarez, M. J.; Abeles, J.
1984-01-01
The long term climate sensitivity which include realistic atmospheric dynamics are severely restricted by the expense of integrating atmospheric general circulation models are discussed. Taking as an example models used at GSFC for this dynamic model is an alternative which is of much lower horizontal or vertical resolution. The model of Heid and Suarez uses only two levels in the vertical and, although it has conventional grid resolution in the meridional direction, horizontal resolution is reduced by keeping only a few degrees of freedom in the zonal wavenumber spectrum. Without zonally asymmetric forcing this model simulates a day in roughly 1/2 second on a CRAY. The model under discussion is a fully finite differenced, zonally asymmetric version of the Heid-Suarez model. It is anticipated that speeds can be obtained a few seconds a day roughly 50 times faster than moderate resolution, multilayer GCM's.
a 2d Integrable Axion Model and Target Space Duality
NASA Astrophysics Data System (ADS)
Forgács, Péter
2001-04-01
A review is given on the recently proposed two dimensional axion model (O(3) σ-model with a dynamical θ-term) and the T-duality relating it to the SU(2)×U(1) symmetric anisotropic σ-model. The T-duality transformation leads to a new Lax-pair. Strong evidence is presented for the correctness of the proposed S-matrix for both models comparing perturbative and Thermodynamical Bethe Ansatz calculations for different types of free energies. The quantum non-integrability of the O(3) σ-model with a constant θ-term, in contradistinction to the axion model, is illustrated by calculating the 2 → 3 particle production amplitude to lowest order in θ
IPEM: An Integrated Planning, Effectiveness Model.
ERIC Educational Resources Information Center
Donsky, Aaron P.
1995-01-01
Proposes a Florida community college's integrated planning approach comprised of three key elements: strategic planning, operational planning, and effectiveness measures. This model, which uses the institutional mission statement as the initiating point, is an efficient and meaningful way to relate an institution's purpose, goals, and outcome…
International Summit on Integrated Environmental Modeling
This report describes the International Summit on Integrated Environmental Modeling (IEM), held in Washington, DC 7th-9th December 2010. The meeting brought together 57 scientists and managers from leading US and European government and non-governmental organizations, universitie...
DC modeling of PN integrated cross varactors
NASA Astrophysics Data System (ADS)
Gonzalez, Benito; Perez, Jose A.; Kemchandani, Sunil L.; Goni-Iturri, Amaya; del Pino, Javier; Garcia, Javier
2005-06-01
In this paper models for the capacitance of cross integrated varactors based in the PN junction are presented. Three different approximations are assumed, in order to reproduce the measured results of the capacitance. The relative error with the measured capacitance is under 10% in all cases.
Fingernail Injuries and NASA's Integrated Medical Model
NASA Technical Reports Server (NTRS)
Kerstman, Eric; Butler, Doug
2008-01-01
The goal of space medicine is to optimize both crew health and performance. Currently, expert opinion is primarily relied upon for decision-making regarding medical equipment and supplies flown in space. Evidence-based decisions are preferred due to mass and volume limitations and the expense of space flight. The Integrated Medical Model (IMM) is an attempt to move us in that direction!
Rethinking School Bullying: Towards an Integrated Model
ERIC Educational Resources Information Center
Dixon, Roz; Smith, Peter K.
2011-01-01
What would make anti-bullying initiatives more successful? This book offers a new approach to the problem of school bullying. The question of what constitutes a useful theory of bullying is considered and suggestions are made as to how priorities for future research might be identified. The integrated, systemic model of school bullying introduced…
A Separable Model for Dynamic Networks
Krivitsky, Pavel N.; Handcock, Mark S.
2013-01-01
Summary Models of dynamic networks — networks that evolve over time — have manifold applications. We develop a discrete-time generative model for social network evolution that inherits the richness and flexibility of the class of exponential-family random graph models. The model — a Separable Temporal ERGM (STERGM) — facilitates separable modeling of the tie duration distributions and the structural dynamics of tie formation. We develop likelihood-based inference for the model, and provide computational algorithms for maximum likelihood estimation. We illustrate the interpretability of the model in analyzing a longitudinal network of friendship ties within a school. PMID:24443639
Psychotherapy and pharmacotherapy: toward an integrative model.
Karasu, T B
1982-09-01
The author reviews historical trends, hypotheses, and problems in the application of pharmacotherapy and psychotherapy and uses research findings to develop an integrative model. He portrays a chronology of models over three decades; an "additive" relationship represents the decade of 1970 to 1980. He presents factors that must be considered in determining the effects of pharmacotherapy plus psychotherapy and recommends refinement of these variables in future research.
Launch Vehicle Dynamics Demonstrator Model
NASA Technical Reports Server (NTRS)
1963-01-01
The effect of vibration on launch vehicle dynamics was studied. Conditions included three modes of instability. The film includes close up views of the simulator fuel tank with and without stability control.
Map-based models in neuronal dynamics
NASA Astrophysics Data System (ADS)
Ibarz, B.; Casado, J. M.; Sanjuán, M. A. F.
2011-04-01
Ever since the pioneering work of Hodgkin and Huxley, biological neuron models have consisted of ODEs representing the evolution of the transmembrane voltage and the dynamics of ionic conductances. It is only recently that discrete dynamical systems-also known as maps-have begun to receive attention as valid phenomenological neuron models. The present review tries to provide a coherent perspective of map-based biological neuron models, describing their dynamical properties; stressing the similarities and differences, both among them and in relation to continuous-time models; exploring their behavior in networks; and examining their wide-ranging possibilities of application in computational neuroscience.
A Lagrangian dynamic subgrid-scale model turbulence
NASA Technical Reports Server (NTRS)
Meneveau, C.; Lund, T. S.; Cabot, W.
1994-01-01
A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.
Integrable extended van der Waals model
NASA Astrophysics Data System (ADS)
Giglio, Francesco; Landolfi, Giulio; Moro, Antonio
2016-10-01
Inspired by the recent developments in the study of the thermodynamics of van der Waals fluids via the theory of nonlinear conservation laws and the description of phase transitions in terms of classical (dissipative) shock waves, we propose a novel approach to the construction of multi-parameter generalisations of the van der Waals model. The theory of integrable nonlinear conservation laws still represents the inspiring framework. Starting from a macroscopic approach, a four parameter family of integrable extended van der Waals models is indeed constructed in such a way that the equation of state is a solution to an integrable nonlinear conservation law linearisable by a Cole-Hopf transformation. This family is further specified by the request that, in regime of high temperature, far from the critical region, the extended model reproduces asymptotically the standard van der Waals equation of state. We provide a detailed comparison of our extended model with two notable empirical models such as Peng-Robinson and Soave's modification of the Redlich-Kwong equations of state. We show that our extended van der Waals equation of state is compatible with both empirical models for a suitable choice of the free parameters and can be viewed as a master interpolating equation. The present approach also suggests that further generalisations can be obtained by including the class of dispersive and viscous-dispersive nonlinear conservation laws and could lead to a new type of thermodynamic phase transitions associated to nonclassical and dispersive shock waves.
Prototype of integrated pseudo-dynamic crosstalk network for cancer molecular mechanism.
Wu, Shinq-Jen; Chen, Wei-Yong; Chou, Chia-Hsien; Wu, Cheng-Tao
2013-05-01
In this study, we attempted to solve two important challenges in systems biology. First, although the Michaelis-Menten (MM) model provides local kinetic information, it is hard to generalize MM models to model a large system because increasingly large amounts of experimental data are necessary for the parameter identification. In addition, it is not possible to develop an MM model that provides information about the strength of the interactions in the system. Second, although the dynamic simulation of various signal transduction pathways is important in cancer research, it is impossible to theoretically derive a mathematical model to describe the cancer molecular mechanism. Predictive computational approaches can be used to analyze the dynamics of a system and to determine the dysfunction of a regulatory process. In this report, we first propose a pseudo-dynamic pathway to describe protein interactions in an MM system. We then discuss the dynamic behavior of two large-scale systems (antigrowth-signal-induced cell cycle and apoptotic-signal-transduction mechanism). These two systems were constructed through the in-series and organic integration, respectively, of MM modules with Petri net modules; moreover, more than 30% additional reactions were added during this integration step. We then described an extremely large multi-stream system (growth signal transduction); however, the analysis of this system to obtain dynamic predictions is critical but appears impossible. Thus, we introduced a fuzzy concept that can be used to develop a physically realizable model prototype. In the future, through step-by-step in vivo modifications, researchers will be able to develop a complete model of cancer metabolism to achieve accurate predictions. PMID:23454229
[Review of dynamic global vegetation models (DGVMs)].
Che, Ming-Liang; Chen, Bao-Zhang; Wang, Ying; Guo, Xiang-Yun
2014-01-01
Dynamic global vegetation model (DGVM) is an important and efficient tool for study on the terrestrial carbon circle processes and vegetation dynamics. This paper reviewed the development history of DGVMs, introduced the basic structure of DGVMs, and the outlines of several world-widely used DGVMs, including CLM-DGVM, LPJ, IBIS and SEIB. The shortages of the description of dynamic vegetation mechanisms in the current DGVMs were proposed, including plant functional types (PFT) scheme, vegetation competition, disturbance, and phenology. Then the future research directions of DGVMs were pointed out, i. e. improving the PFT scheme, refining the vegetation dynamic mechanism, and implementing a model inter-comparison project. PMID:24765870
Misaligned Image Integration With Local Linear Model.
Baba, Tatsuya; Matsuoka, Ryo; Shirai, Keiichiro; Okuda, Masahiro
2016-05-01
We present a new image integration technique for a flash and long-exposure image pair to capture a dark scene without incurring blurring or noisy artifacts. Most existing methods require well-aligned images for the integration, which is often a burdensome restriction in practical use. We address this issue by locally transferring the colors of the flash images using a small fraction of the corresponding pixels in the long-exposure images. We formulate the image integration as a convex optimization problem with the local linear model. The proposed method makes it possible to integrate the color of the long-exposure image with the detail of the flash image without causing any harmful effects to its contrast, where we do not need perfect alignment between the images by virtue of our new integration principle. We show that our method successfully outperforms the state of the art in the image integration and reference-based color transfer for challenging misaligned data sets.
Animal models and integrated nested Laplace approximations.
Holand, Anna Marie; Steinsland, Ingelin; Martino, Sara; Jensen, Henrik
2013-08-07
Animal models are generalized linear mixed models used in evolutionary biology and animal breeding to identify the genetic part of traits. Integrated Nested Laplace Approximation (INLA) is a methodology for making fast, nonsampling-based Bayesian inference for hierarchical Gaussian Markov models. In this article, we demonstrate that the INLA methodology can be used for many versions of Bayesian animal models. We analyze animal models for both synthetic case studies and house sparrow (Passer domesticus) population case studies with Gaussian, binomial, and Poisson likelihoods using INLA. Inference results are compared with results using Markov Chain Monte Carlo methods. For model choice we use difference in deviance information criteria (DIC). We suggest and show how to evaluate differences in DIC by comparing them with sampling results from simulation studies. We also introduce an R package, AnimalINLA, for easy and fast inference for Bayesian Animal models using INLA.
Stirling Convertor System Dynamic Model Developed
NASA Technical Reports Server (NTRS)
Lewandowski, Edward J.; Regan, Timothy F.
2005-01-01
Free-piston Stirling convertors are being developed for potential use on NASA exploration missions. In support of this effort, the NASA Glenn Research Center has developed the Stirling convertor System Dynamic Model (SDM). The SDM models the Stirling cycle thermodynamics; heat flow; gas, mechanical, and mounting dynamics; the linear alternator; and the controller. The SDM s scope extends from the thermal energy input to thermal, mechanical, and electrical energy output, allowing one to study complex system interactions among subsystems. Thermal, mechanical, fluid, magnetic, and electrical subsystems can be studied in one model. The SDM is a nonlinear time-domain model containing sub-cycle dynamics, which simulates transient and dynamic phenomena that other models cannot. The entire range of convertor operation is modeled, from startup to full-power conditions.
Dash, Ranjan K.; Li, Yanjun; Kim, Jaeyeon; Beard, Daniel A.; Saidel, Gerald M.; Cabrera, Marco E.
2008-01-01
Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD+. The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and
Study on UKF based federal integrated navigation for high dynamic aviation
NASA Astrophysics Data System (ADS)
Zhao, Gang; Shao, Wei; Chen, Kai; Yan, Jie
2011-08-01
High dynamic aircraft is a very attractive new generation vehicles, in which provides near space aviation with large flight envelope both speed and altitude, for example the hypersonic vehicles. The complex flight environments for high dynamic vehicles require high accuracy and stability navigation scheme. Since the conventional Strapdown Inertial Navigation System (SINS) and Global Position System (GPS) federal integrated scheme based on EKF (Extended Kalman Filter) is invalidation in GPS single blackout situation because of high speed flight, a new high precision and stability integrated navigation approach is presented in this paper, in which the SINS, GPS and Celestial Navigation System (CNS) is combined as a federal information fusion configuration based on nonlinear Unscented Kalman Filter (UKF) algorithm. Firstly, the new integrated system state error is modeled. According to this error model, the SINS system is used as the navigation solution mathematic platform. The SINS combine with GPS constitute one error estimation filter subsystem based on UKF to obtain local optimal estimation, and the SINS combine with CNS constitute another error estimation subsystem. A non-reset federated configuration filter based on partial information is proposed to fuse two local optimal estimations to get global optimal error estimation, and the global optimal estimation is used to correct the SINS navigation solution. The χ 2 fault detection method is used to detect the subsystem fault, and the fault subsystem is isolation through fault interval to protect system away from the divergence. The integrated system takes advantages of SINS, GPS and CNS to an immense improvement for high accuracy and reliably high dynamic navigation application. Simulation result shows that federated fusion of using GPS and CNS to revise SINS solution is reasonable and availably with good estimation performance, which are satisfied with the demands of high dynamic flight navigation. The UKF is
Modelling Information System Dynamics: A Perspective.
ERIC Educational Resources Information Center
Oswitch, Pauline
1983-01-01
Describes British Library's work on Systems Dynamics, a set of techniques for building simulation models based on analysis of information feedback loops. Highlights include macro-simulation modelling activities of social science disciplines, systems analyses and models of information retrieval processes and library services, policy models, and…
Building an Open Source Framework for Integrated Catchment Modeling
NASA Astrophysics Data System (ADS)
Jagers, B.; Meijers, E.; Villars, M.
2015-12-01
In order to develop effective strategies and associated policies for environmental management, we need to understand the dynamics of the natural system as a whole and the human role therein. This understanding is gained by comparing our mental model of the world with observations from the field. However, to properly understand the system we should look at dynamics of water, sediments, water quality, and ecology throughout the whole system from catchment to coast both at the surface and in the subsurface. Numerical models are indispensable in helping us understand the interactions of the overall system, but we need to be able to update and adjust them to improve our understanding and test our hypotheses. To support researchers around the world with this challenging task we started a few years ago with the development of a new open source modeling environment DeltaShell that integrates distributed hydrological models with 1D, 2D, and 3D hydraulic models including generic components for the tracking of sediment, water quality, and ecological quantities throughout the hydrological cycle composed of the aforementioned components. The open source approach combined with a modular approach based on open standards, which allow for easy adjustment and expansion as demands and knowledge grow, provides an ideal starting point for addressing challenging integrated environmental questions.
Very Large System Dynamics Models - Lessons Learned
Jacob J. Jacobson; Leonard Malczynski
2008-10-01
This paper provides lessons learned from developing several large system dynamics (SD) models. System dynamics modeling practice emphasize the need to keep models small so that they are manageable and understandable. This practice is generally reasonable and prudent; however, there are times that large SD models are necessary. This paper outlines two large SD projects that were done at two Department of Energy National Laboratories, the Idaho National Laboratory and Sandia National Laboratories. This paper summarizes the models and then discusses some of the valuable lessons learned during these two modeling efforts.
Neural dynamics for landmark orientation and angular path integration.
Seelig, Johannes D; Jayaraman, Vivek
2015-05-14
Many animals navigate using a combination of visual landmarks and path integration. In mammalian brains, head direction cells integrate these two streams of information by representing an animal's heading relative to landmarks, yet maintaining their directional tuning in darkness based on self-motion cues. Here we use two-photon calcium imaging in head-fixed Drosophila melanogaster walking on a ball in a virtual reality arena to demonstrate that landmark-based orientation and angular path integration are combined in the population responses of neurons whose dendrites tile the ellipsoid body, a toroidal structure in the centre of the fly brain. The neural population encodes the fly's azimuth relative to its environment, tracking visual landmarks when available and relying on self-motion cues in darkness. When both visual and self-motion cues are absent, a representation of the animal's orientation is maintained in this network through persistent activity, a potential substrate for short-term memory. Several features of the population dynamics of these neurons and their circular anatomical arrangement are suggestive of ring attractors, network structures that have been proposed to support the function of navigational brain circuits. PMID:25971509
Neural dynamics for landmark orientation and angular path integration
Seelig, Johannes D.; Jayaraman, Vivek
2015-01-01
Summary Many animals navigate using a combination of visual landmarks and path integration. In mammalian brains, head direction cells integrate these two streams of information by representing an animal's heading relative to landmarks, yet maintaining their directional tuning in darkness based on self-motion cues. Here we use two-photon calcium imaging in head-fixed flies walking on a ball in a virtual reality arena to demonstrate that landmark-based orientation and angular path integration are combined in the population responses of neurons whose dendrites tile the ellipsoid body — a toroidal structure in the center of the fly brain. The population encodes the fly's azimuth relative to its environment, tracking visual landmarks when available and relying on self-motion cues in darkness. When both visual and self-motion cues are absent, a representation of the animal's orientation is maintained in this network through persistent activity — a potential substrate for short-term memory. Several features of the population dynamics of these neurons and their circular anatomical arrangement are suggestive of ring attractors — network structures proposed to support the function of navigational brain circuits. PMID:25971509
Development of the Integrated Environmental Control Model
Rubin, E.S.; Berkenpas, M.B.; Kalagnanam, J.
1993-04-01
The purpose of this contract is to develop and refine the Integrated Environmental Control Model (IECM) created and enhanced by Carnegie Mellon University (CMU) for the US Department of Energy's Pittsburgh Energy Technology Center (DOE/PETC) under contract Numbers FG22-83PC60271 and AC22-87PC79864. In its current configuration, the IECM provides a capability to model various conventional and advanced processes for controlling air pollutant emissions from coal-fired power plants before, during, or after combustion. The principal purpose of the model is to calculate the performance, emissions, and cost of power plant configurations employing alternative environmental control methods. The model consists of various control technology modules, which may be integrated into a complete utility plant in any desired combination. In contrast to conventional deterministic models, the IECM offers the unique capability to assign probabilistic values to all model input parameters, and to obtain probabilistic outputs in the form of cumulative distribution functions indicating the likelihood of different costs and performance results. The work in this contract is divided into two phases. Phase I deals with further developing the existing version of the IECM and training PETC personnel on the effective use of the model. Phase II deals with creating new technology modules, linking the IECM with PETC databases, and training PETC personnel on the effective use of the updated model.
Comparing models of Red Knot population dynamics
McGowan, Conor
2015-01-01
Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.
Clark, M. A.; Joo, Balint; Kennedy, A. D.; Silva, P. J.
2011-10-01
We show how the integrators used for the molecular dynamics step of the Hybrid Monte Carlo algorithm can be further improved. These integrators not only approximately conserve some Hamiltonian H but conserve exactly a nearby shadow Hamiltonian H-tilde. This property allows for a new tuning method of the molecular dynamics integrator and also allows for a new class of integrators (force-gradient integrators) which is expected to reduce significantly the computational cost of future large-scale gauge field ensemble generation.
Human systems dynamics: Toward a computational model
NASA Astrophysics Data System (ADS)
Eoyang, Glenda H.
2012-09-01
A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.
Modeling microbial growth and dynamics.
Esser, Daniel S; Leveau, Johan H J; Meyer, Katrin M
2015-11-01
Modeling has become an important tool for widening our understanding of microbial growth in the context of applied microbiology and related to such processes as safe food production, wastewater treatment, bioremediation, or microbe-mediated mining. Various modeling techniques, such as primary, secondary and tertiary mathematical models, phenomenological models, mechanistic or kinetic models, reactive transport models, Bayesian network models, artificial neural networks, as well as agent-, individual-, and particle-based models have been applied to model microbial growth and activity in many applied fields. In this mini-review, we summarize the basic concepts of these models using examples and applications from food safety and wastewater treatment systems. We further review recent developments in other applied fields focusing on models that explicitly include spatial relationships. Using these examples, we point out the conceptual similarities across fields of application and encourage the combined use of different modeling techniques in hybrid models as well as their cross-disciplinary exchange. For instance, pattern-oriented modeling has its origin in ecology but may be employed to parameterize microbial growth models when experimental data are scarce. Models could also be used as virtual laboratories to optimize experimental design analogous to the virtual ecologist approach. Future microbial growth models will likely become more complex to benefit from the rich toolbox that is now available to microbial growth modelers.
Modeling microbial growth and dynamics.
Esser, Daniel S; Leveau, Johan H J; Meyer, Katrin M
2015-11-01
Modeling has become an important tool for widening our understanding of microbial growth in the context of applied microbiology and related to such processes as safe food production, wastewater treatment, bioremediation, or microbe-mediated mining. Various modeling techniques, such as primary, secondary and tertiary mathematical models, phenomenological models, mechanistic or kinetic models, reactive transport models, Bayesian network models, artificial neural networks, as well as agent-, individual-, and particle-based models have been applied to model microbial growth and activity in many applied fields. In this mini-review, we summarize the basic concepts of these models using examples and applications from food safety and wastewater treatment systems. We further review recent developments in other applied fields focusing on models that explicitly include spatial relationships. Using these examples, we point out the conceptual similarities across fields of application and encourage the combined use of different modeling techniques in hybrid models as well as their cross-disciplinary exchange. For instance, pattern-oriented modeling has its origin in ecology but may be employed to parameterize microbial growth models when experimental data are scarce. Models could also be used as virtual laboratories to optimize experimental design analogous to the virtual ecologist approach. Future microbial growth models will likely become more complex to benefit from the rich toolbox that is now available to microbial growth modelers. PMID:26298697
NASA Astrophysics Data System (ADS)
Clemente, Patrice; Rouzaud-Cornabas, Jonathan; Toinard, Christian
Protection deals with the enforcement of integrity and confidentiality. Integrity violations often lead to confidentiality vulnerabilities. This paper proposes a novel approach of Mandatory Access Control enforcement for guaranteeing a large range of integrity properties. In the literature, many integrity models are proposed such as the Biba model, data integrity, subject integrity, domain integrity and Trusted Path Execution. There can be numerous integrity models. In practice, an administrator needs to combine various integrity models. The major limitations of existing solutions deal first with the support of indirect activities aiming at violating integrity and second with the impossibility to extend existing models or even define new ones.
Integral equation model for warm and hot dense mixtures.
Starrett, C E; Saumon, D; Daligault, J; Hamel, S
2014-09-01
In a previous work [C. E. Starrett and D. Saumon, Phys. Rev. E 87, 013104 (2013)] a model for the calculation of electronic and ionic structures of warm and hot dense matter was described and validated. In that model the electronic structure of one atom in a plasma is determined using a density-functional-theory-based average-atom (AA) model and the ionic structure is determined by coupling the AA model to integral equations governing the fluid structure. That model was for plasmas with one nuclear species only. Here we extend it to treat plasmas with many nuclear species, i.e., mixtures, and apply it to a carbon-hydrogen mixture relevant to inertial confinement fusion experiments. Comparison of the predicted electronic and ionic structures with orbital-free and Kohn-Sham molecular dynamics simulations reveals excellent agreement wherever chemical bonding is not significant.
Dynamic phase transition in diluted Ising model
NASA Astrophysics Data System (ADS)
Chattopadhyay, Sourav; Gorai, Gopal; Santra, S. B.
2015-06-01
Dynamic phase transition in disordered Ising model in two dimensions has been studied in presence of external time dependent oscillating magnetic field applying Glauber Monte Carlo techniques. Dynamic phase transitions are identified estimating dynamic order parameter against temperature for different concentrations of disorder. For a given field strength and frequency for which there was no hysteresis, it is observed that disorder is able induce hysteresis in the system. Effect of increasing concentration of disorder on hysteresis loop area has also been studied.
Computational modeling of red blood cells: A symplectic integration algorithm
NASA Astrophysics Data System (ADS)
Schiller, Ulf D.; Ladd, Anthony J. C.
2010-03-01
Red blood cells can undergo shape transformations that impact the rheological properties of blood. Computational models have to account for the deformability and red blood cells are often modeled as elastically deformable objects. We present a symplectic integration algorithm for deformable objects. The surface is represented by a set of marker points obtained by surface triangulation, along with a set of fiber vectors that describe the orientation of the material plane. The various elastic energies are formulated in terms of these variables and the equations of motion are obtained by exact differentiation of a discretized Hamiltonian. The integration algorithm preserves the Hamiltonian structure and leads to highly accurate energy conservation, hence he method is expected to be more stable than conventional finite element methods. We apply the algorithm to simulate the shape dynamics of red blood cells.
Differential equation models for sharp threshold dynamics.
Schramm, Harrison C; Dimitrov, Nedialko B
2014-01-01
We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations. PMID:24184349
Equivalent dynamic model of DEMES rotary joint
NASA Astrophysics Data System (ADS)
Zhao, Jianwen; Wang, Shu; Xing, Zhiguang; McCoul, David; Niu, Junyang; Huang, Bo; Liu, Liwu; Leng, Jinsong
2016-07-01
The dielectric elastomer minimum energy structure (DEMES) can realize large angular deformations by a small voltage-induced strain of the dielectric elastomer (DE), so it is a suitable candidate to make a rotary joint for a soft robot. Dynamic analysis is necessary for some applications, but the dynamic response of DEMESs is difficult to model because of the complicated morphology and viscoelasticity of the DE film. In this paper, a method composed of theoretical analysis and experimental measurement is presented to model the dynamic response of a DEMES rotary joint under an alternating voltage. Based on measurements of equivalent driving force and damping of the DEMES, the model can be derived. Some experiments were carried out to validate the equivalent dynamic model. The maximum angle error between model and experiment is greater than ten degrees, but it is acceptable to predict angular velocity of the DEMES, therefore, it can be applied in feedforward–feedback compound control.
Differential equation models for sharp threshold dynamics.
Schramm, Harrison C; Dimitrov, Nedialko B
2014-01-01
We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations.
Dynamics Modelling of Biolistic Gene Guns
Zhang, M.; Tao, W.; Pianetta, P.A.
2009-06-04
The gene transfer process using biolistic gene guns is a highly dynamic process. To achieve good performance, the process needs to be well understood and controlled. Unfortunately, no dynamic model is available in the open literature for analysing and controlling the process. This paper proposes such a model. Relationships of the penetration depth with the helium pressure, the penetration depth with the acceleration distance, and the penetration depth with the micro-carrier radius are presented. Simulations have also been conducted. The results agree well with experimental results in the open literature. The contribution of this paper includes a dynamic model for improving and manipulating performance of the biolistic gene gun.
Simple Dynamic Gasifier Model That Runs in Aspen Dynamics
Robinson, P.J.; Luyben, W.L.
2008-10-15
Gasification (or partial oxidation) is a vital component of 'clean coal' technology. Sulfur and nitrogen emissions can be reduced, overall energy efficiency is increased, and carbon dioxide recovery and sequestration are facilitated. Gasification units in an electric power generation plant produce a fuel for driving combustion turbines. Gasification units in a chemical plant generate gas, which can be used to produce a wide spectrum of chemical products. Future plants are predicted to be hybrid power/chemical plants with gasification as the key unit operation. The widely used process simulator Aspen Plus provides a library of models that can be used to develop an overall gasifier model that handles solids. So steady-state design and optimization studies of processes with gasifiers can be undertaken. This paper presents a simple approximate method for achieving the objective of having a gasifier model that can be exported into Aspen Dynamics. The basic idea is to use a high molecular weight hydrocarbon that is present in the Aspen library as a pseudofuel. This component should have the same 1:1 hydrogen-to-carbon ratio that is found in coal and biomass. For many plantwide dynamic studies, a rigorous high-fidelity dynamic model of the gasifier is not needed because its dynamics are very fast and the gasifier gas volume is a relatively small fraction of the total volume of the entire plant. The proposed approximate model captures the essential macroscale thermal, flow, composition, and pressure dynamics. This paper does not attempt to optimize the design or control of gasifiers but merely presents an idea of how to dynamically simulate coal gasification in an approximate way.
Markov state models of biomolecular conformational dynamics
Chodera, John D.; Noé, Frank
2014-01-01
It has recently become practical to construct Markov state models (MSMs) that reproduce the long-time statistical conformational dynamics of biomolecules using data from molecular dynamics simulations. MSMs can predict both stationary and kinetic quantities on long timescales (e.g. milliseconds) using a set of atomistic molecular dynamics simulations that are individually much shorter, thus addressing the well-known sampling problem in molecular dynamics simulation. In addition to providing predictive quantitative models, MSMs greatly facilitate both the extraction of insight into biomolecular mechanism (such as folding and functional dynamics) and quantitative comparison with single-molecule and ensemble kinetics experiments. A variety of methodological advances and software packages now bring the construction of these models closer to routine practice. Here, we review recent progress in this field, considering theoretical and methodological advances, new software tools, and recent applications of these approaches in several domains of biochemistry and biophysics, commenting on remaining challenges. PMID:24836551
Challenges and opportunities for integrating lake ecosystem modelling approaches
Mooij, Wolf M.; Trolle, Dennis; Jeppesen, Erik; Arhonditsis, George; Belolipetsky, Pavel V.; Chitamwebwa, Deonatus B.R.; Degermendzhy, Andrey G.; DeAngelis, Donald L.; Domis, Lisette N. De Senerpont; Downing, Andrea S.; Elliott, J. Alex; Ruberto, Carlos Ruberto; Gaedke, Ursula; Genova, Svetlana N.; Gulati, Ramesh D.; Hakanson, Lars; Hamilton, David P.; Hipsey, Matthew R.; Hoen, Jochem 't; Hulsmann, Stephan; Los, F. Hans; Makler-Pick, Vardit; Petzoldt, Thomas; Prokopkin, Igor G.; Rinke, Karsten; Schep, Sebastiaan A.; Tominaga, Koji; Van Dam, Anne A.; Van Nes, Egbert H.; Wells, Scott A.; Janse, Jan H.
2010-01-01
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative
CTBT Integrated Verification System Evaluation Model
Edenburn, M.W.; Bunting, M.L.; Payne, A.C. Jr.
1997-10-01
Sandia National Laboratories has developed a computer based model called IVSEM (Integrated Verification System Evaluation Model) to estimate the performance of a nuclear detonation monitoring system. The IVSEM project was initiated in June 1994, by Sandia`s Monitoring Systems and Technology Center and has been funded by the US Department of Energy`s Office of Nonproliferation and National Security (DOE/NN). IVSEM is a simple, top-level, modeling tool which estimates the performance of a Comprehensive Nuclear Test Ban Treaty (CTBT) monitoring system and can help explore the impact of various sensor system concepts and technology advancements on CTBT monitoring. One of IVSEM`s unique features is that it integrates results from the various CTBT sensor technologies (seismic, infrasound, radionuclide, and hydroacoustic) and allows the user to investigate synergy among the technologies. Specifically, IVSEM estimates the detection effectiveness (probability of detection) and location accuracy of the integrated system and of each technology subsystem individually. The model attempts to accurately estimate the monitoring system`s performance at medium interfaces (air-land, air-water) and for some evasive testing methods such as seismic decoupling. This report describes version 1.2 of IVSEM.
Coarse-grained dynamics of alignment in animal group models
NASA Astrophysics Data System (ADS)
Moon, Sung Joon; Levin, Simon; Kevrekidis, Yannis
2006-03-01
Coordinated motion in animal groups, such as bird flocks and fish schools, and their models gives rise to remarkable coherent structures. Using equation-free computational tools we explore the coarse-grained dynamics of a model for the orientational movement decision in animal groups, consisting of a small number of informed "leaders" and a large number of uninformed, nonidentical ``followers.'' The direction in which each group member is headed is characterized by a phase angle of a limit-cycle oscillator, whose dynamics are nonlinearly coupled with those of all the other group members. We identify a small number of proper coarse-grained variables (using uncertainty quantification methods) that describe the collective dynamics, and perform coarse projective integration and equation-free bifurcation analysis of the coarse-grained model behavior in these variables.
A mathematical model for the dynamics and synchronization of cows
NASA Astrophysics Data System (ADS)
Sun, Jie; Bollt, Erik M.; Porter, Mason A.; Dawkins, Marian S.
2011-09-01
We formulate a mathematical model for the daily activities of a cow (eating, lying down, and standing) in terms of a piecewise linear dynamical system. We analyze the properties of this bovine dynamical system representing the single animal and develop an exact integrative form as a discrete-time mapping. We then couple multiple cow “oscillators” together to study synchrony and cooperation in cattle herds. We comment on the relevant biology and discuss extensions of our model. With this abstract approach, we not only investigate equations with interesting dynamics but also develop biological predictions. In particular, our model illustrates that it is possible for cows to synchronize less when the coupling is increased.
Multilayer Control Hierarchy in an Integrated Hydrological Model
NASA Astrophysics Data System (ADS)
Park, J.; Obeysekera, J.; Vanzee, R.
2005-05-01
Considerable progress has been made in the functionality of integrated hydrological models which can provide evaluation of anthropogenic control and management policies of water resources. Nonetheless, there is still room for improvement in the coupling and expression of water control policies into hydrological models [1]. The Management Simulation Engine (MSE) component of the Regional Simulation Model (RSM) incorporates a multi-level hierarchical control architecture which emphasizes the decoupling of hydrological state information from the management information processing applied to the states. The MSE is intended to allow a flexible, extensible expression of a wide variety anthropogenic water resource control schemes integrated with the hydrological state evaluations of the RSM. Synergy between the multilayer control hierarchy and decoupled hydrologic state and management information facilitates a water resource management feature set not typical of integrated hydrological models. Some of these features include: interoperation and compatibility of diverse management algorithms such as PID, Fuzzy control, LP; and dynamic switching of control processors. This paper describes the MSE control hierarchy with a focus on the aforementioned features and their implementation. [1] Belaineh, G., Peralta, R. C., Hughes, T. C., Simulation/ Optimization Modeling for Water Resources Management, ASCE Journal Water Resources Planning Management, 125(3), p 154-61, 1999
Development of the integrated environmental control model
Rubin, E.S.
1993-01-01
In its current configuration, the IECM provides a capability to model various conventional and advanced processes for controlling air pollutant emissions from coalfired power plants before, during, or after combustion. The principal purpose of the model is to calculate the performance, emissions, and cost of power Plant configurations employing alternative environmental control methods. The model consists of various control technology modules, which may be integrated into a complete utility plant in any desired combination. in conuwt to conventional deterministic models, the IECM offers the unique capability to assign probabilistic values to all model input parameters, and to obtain probabilistic outputs in the form of cumulative distribution functions indicating the likelihood of different costs and performance results. The most recent version of the IECM, implemented on a Macintosh II computer and containing a number of software and model enhancements, was delivered to DOE/PETC at the end of the last contract in May 1991. The current contract will continue the model development effort to provide DOE/PETC with improved model capabilities, including new software developments tO facilitate model use and new technical capabilities for analysis of environmental control technologies and integrated environmental control systr,ms involving precombustion, combustion, and Post-combustion control methods. The work in this contract is divided into two phases. Phase I deals with further developing the existing version of the IECM and training PETC personnel on the effective use of the model. Phase H deals with creating new technology modules, linking the IECM with PETC databases, and training PETC personnel on the effective use of the updated model.
Integrating Biosystem Models Using Waveform Relaxation
2008-01-01
Modelling in systems biology often involves the integration of component models into larger composite models. How to do this systematically and efficiently is a significant challenge: coupling of components can be unidirectional or bidirectional, and of variable strengths. We adapt the waveform relaxation (WR) method for parallel computation of ODEs as a general methodology for computing systems of linked submodels. Four test cases are presented: (i) a cascade of unidirectionally and bidirectionally coupled harmonic oscillators, (ii) deterministic and stochastic simulations of calcium oscillations, (iii) single cell calcium oscillations showing complex behaviour such as periodic and chaotic bursting, and (iv) a multicellular calcium model for a cell plate of hepatocytes. We conclude that WR provides a flexible means to deal with multitime-scale computation and model heterogeneity. Global solutions over time can be captured independently of the solution techniques for the individual components, which may be distributed in different computing environments. PMID:19125183
Heavy gas dispersion: integral models and shallow layer models.
Hankin, Robin K S
2003-10-01
Integral models for heavy gas dispersion approximate a dispersing cloud in terms of a small number of variables; each of these is ultimately a function of an independent variable which is usually time (instantaneous releases) or downwind distance (continuous releases). This type of model is used almost exclusively in risk assessment [HSE's risk assessment tool, RISKAT, in: Major Hazards: Onshore and Offshore, October 1992, pp. 607-638; Ann. Rev. Fluid Mech. 21 (1989) 317], but many distinct integral models exist. The code comparison exercise of Mercer et al. [CEA/AEA exchange agreement on external event. Comparison of heavy gas dispersion models for instantaneous releases: final report, Technical Report IR/L/HA/91/6, Health and Safety Laboratory, Sheffield, June 1991; J. Hazard. Mater. 36 (1994) 193] presented the results from a number of integral models in a common format; Mercer found that the range of predictions for some scenarios exceeded three orders of magnitude. Here, the TWODEE shallow layer model [J. Hazard. Mater. 66 (3) (1999) 211; J. Hazard. Mater. 66 (3) (1999) 227; J. Hazard. Mater. 66 (3) (1999) 239] is added to Mercer's code comparison exercise. The physical assumptions used in shallow layer models differ profoundly from those used in integral models and the implications of these differences for risk assessment are discussed. TWODEE was used to simulate four representative cases considered by Mercer. In terms of cloud averaged concentration (CAC) vs. centroid position, the present model gave predictions that were consistent with the integral models used by Mercer. As the model neglects horizontal diffusion for passive clouds, overprediction at large downwind distances was expected, but not generally observed.
Search of novel model for integrative medicine.
Patwardhan, Bhushan; Mutalik, Gururaj
2014-03-01
This article provides global and Indian scenario with strengths and limitations of present health care system. Affordability, accessibility and availability of health care coupled with disproportionate growth and double burden of diseases have become major concerns in India. This article emphasizes need for mindset change from illness-disease-drug centric curative to person-health-wellness centric preventive and promotive approaches. It highlights innovation deficit faced pharmaceutical industry and drugs being withdrawn from market for safety reasons. Medical pluralism is a growing trend and people are exploring various options including modern, traditional, complementary and alternative medicine. In such a situation, knowledge from Ayurveda, yoga, Chinese medicine and acupuncture may play an important role. We can evolve a suitable model by integrating modern and traditional systems of medicine for affordable health care. In the larger interest of global community, Indian and Chinese systems should share knowledge and experiences for mutual intellectual enrichments and work together to evolve a novel model of integrative medicine.
The Integrated Airport Competition Model, 1998
NASA Technical Reports Server (NTRS)
Veldhuis, J.; Essers, I.; Bakker, D.; Cohn, N.; Kroes, E.
1999-01-01
This paper addresses recent model development by the Directorate General of Civil Aviation (DGCA) and Hague Consulting Group (HCG) concerning long-distance travel, Long-distance travel demand is growing very quickly and raising a great deal of economic and policy issues. There is increasing competition among the main Western European airports, and smaller, regional airports are fighting for market share. New modes of transport, such as high speed rail, arc also coming into the picture and affect the mode split for medium distance transport within Europe. Developments such as these are demanding the attention of policy makers and a tool is required for their analysis. For DGCA, Hague Consulting Group has developed a model system to provide answers to the policy questions posed by these expected trends, and to identify areas where policy makers can influence the traveller choices. The development of this model system, the Integrated Airport Competition Model/Integral Luchthaven Competitive Model (ILCM), began in 1992. Since that time the sub-models, input data and user interface have been expanded, updated and improved. HCG and DGCA have transformed the ILCM from a prototype into an operational forecasting tool.
Ontological Modeling for Integrated Spacecraft Analysis
NASA Technical Reports Server (NTRS)
Wicks, Erica
2011-01-01
Current spacecraft work as a cooperative group of a number of subsystems. Each of these requiresmodeling software for development, testing, and prediction. It is the goal of my team to create anoverarching software architecture called the Integrated Spacecraft Analysis (ISCA) to aid in deploying the discrete subsystems' models. Such a plan has been attempted in the past, and has failed due to the excessive scope of the project. Our goal in this version of ISCA is to use new resources to reduce the scope of the project, including using ontological models to help link the internal interfaces of subsystems' models with the ISCA architecture.I have created an ontology of functions specific to the modeling system of the navigation system of a spacecraft. The resulting ontology not only links, at an architectural level, language specificinstantiations of the modeling system's code, but also is web-viewable and can act as a documentation standard. This ontology is proof of the concept that ontological modeling can aid in the integration necessary for ISCA to work, and can act as the prototype for future ISCA ontologies.
Pinto, Rogério M.; Spector, Anya Y.; Valera, Pamela A.
2011-01-01
To demonstrate how Community Advisory Boards (CABs) can best integrate community perspectives with scientific knowledge and involve community in disseminating HIV knowledge, this paper provides a case study exploring the structure and dynamic process of a “Community Collaborative Board” (CCB). We use the term CCB to emphasize collaboration over advisement. The CCB membership, structure and dynamics are informed by theory and research. The CCB is affiliated with Columbia University School of Social Work and its original membership included 30 members. CCB was built using six systematized steps meant to engage members in procedural and substantive research roles. Steps: (1) Engaging membership, (2) Developing relationships, (3) Exchanging information, (4) Negotiation and decision-making, (5) Retaining membership, and (6) Studying dynamic process. This model requires that all meetings be audio-taped to capture CCB dynamics. Using transcribed meeting data, we have identified group dynamics that help the CCB accomplish its objectives: 1) dialectic process helps exchange of information; 2) mutual support helps members work together despite social and professional differences; and 3) problem solving helps members achieve consensus. These dynamics also help members attain knowledge about HIV treatment and prevention and disseminate HIV-related knowledge. CABs can be purposeful in their use of group dynamics, narrow the knowledge gap between researchers and community partners, prepare members for procedural and substantive research roles, and retain community partners. PMID:21390878
Airship dynamics modeling: A literature review
NASA Astrophysics Data System (ADS)
Li, Yuwen; Nahon, Meyer; Sharf, Inna
2011-04-01
The resurgence of airships has created a need for dynamics models and simulation capabilities adapted to these lighter-than-air vehicles. However, the modeling techniques for airship dynamics have lagged behind and are less systematic than those for fixed-wing aircraft. A state-of-the-art literature review is presented on airship dynamics modeling, aiming to provide a comprehensive description of the main problems in this area and a useful source of references for researchers and engineers interested in modern airship applications. The references are categorized according to the major topics in this area: aerodynamics, flight dynamics, incorporation of structural flexibility, incorporation of atmospheric turbulence, and effects of ballonets. Relevant analytical, numerical, and semi-empirical techniques are discussed, with a particular focus on how the main differences between lighter-than-air and heavier-than-air aircraft have been addressed in the modeling. Directions are suggested for future research on each of these topics.
Constructing minimal models for complex system dynamics
NASA Astrophysics Data System (ADS)
Barzel, Baruch; Liu, Yang-Yu; Barabási, Albert-László
2015-05-01
One of the strengths of statistical physics is the ability to reduce macroscopic observations into microscopic models, offering a mechanistic description of a system's dynamics. This paradigm, rooted in Boltzmann's gas theory, has found applications from magnetic phenomena to subcellular processes and epidemic spreading. Yet, each of these advances were the result of decades of meticulous model building and validation, which are impossible to replicate in most complex biological, social or technological systems that lack accurate microscopic models. Here we develop a method to infer the microscopic dynamics of a complex system from observations of its response to external perturbations, allowing us to construct the most general class of nonlinear pairwise dynamics that are guaranteed to recover the observed behaviour. The result, which we test against both numerical and empirical data, is an effective dynamic model that can predict the system's behaviour and provide crucial insights into its inner workings.
Automated adaptive inference of phenomenological dynamical models
Daniels, Bryan C.; Nemenman, Ilya
2015-01-01
Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508
The Higher Moments Dynamic on SIS Model
NASA Astrophysics Data System (ADS)
Pinto, Alberto; Martins, José; Stollenwerk, Nico
2009-09-01
The basic contact process or the SIS model is a well known epidemic process and have been studied for a wide class of people. In an epidemiological context, many authors worked on the SIS model considering only the dynamic of the first moments of infecteds, i.e., the mean value and the variance of the infected individuals. In this work, we study not only the dynamic of the first moments of infecteds but also on the dynamic of the higher moments. Recursively, we consider the dynamic equations for all the moments of infecteds and, applying the moment closure approximation, we obtain the stationary states of the state variables. We observe that the stationary states of the SIS model, in the moment closure approximation, can be used to obtain good approximations of the quasi-stationary states of the SIS model.
MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS*
CHAHINE, Georges L.; HSIAO, Chao-Tsung
2012-01-01
Controlling microbubble dynamics to produce desirable biomedical outcomes when and where necessary and avoid deleterious effects requires advanced knowledge, which can be achieved only through a combination of experimental and numerical/analytical techniques. The present communication presents a multi-physics approach to study the dynamics combining viscous- in-viscid effects, liquid and structure dynamics, and multi bubble interaction. While complex numerical tools are developed and used, the study aims at identifying the key parameters influencing the dynamics, which need to be included in simpler models. PMID:22833696
Integrable model with parafermion zero energy modes.
Tsvelik, A M
2014-08-01
Parafermion zero energy modes are a vital element of fault-tolerant topological quantum computation. Although it is believed that such modes form on the border between topological and normal phases, this has been demonstrated only for Z(2) (Majorana) and Z(3) parafermions. I consider an integrable model of one-dimensional fermions where such a demonstration is possible for Z(N) parafermions with any N. The procedure is easily generalizable for more complicated symmetry groups. PMID:25148341
Integrable Model with Parafermion Zero Energy Modes
NASA Astrophysics Data System (ADS)
Tsvelik, A. M.
2014-08-01
Parafermion zero energy modes are a vital element of fault-tolerant topological quantum computation. Although it is believed that such modes form on the border between topological and normal phases, this has been demonstrated only for Z2 (Majorana) and Z3 parafermions. I consider an integrable model of one-dimensional fermions where such a demonstration is possible for ZN parafermions with any N. The procedure is easily generalizable for more complicated symmetry groups.
Integrating local static and dynamic information for routing traffic
NASA Astrophysics Data System (ADS)
Wang, Wen-Xu; Yin, Chuan-Yang; Yan, Gang; Wang, Bing-Hong
2006-07-01
The efficiency of traffic routing on complex networks can be reflected by two key measurements, i.e., the network capacity and the average travel time of data packets. In this paper we propose a mixing routing strategy by integrating local static and dynamic information for enhancing the efficiency of traffic on scale-free networks. The strategy is governed by a single parameter. Simulation results show that maximizing the network capacity and reducing the packet travel time can generate an optimal parameter value. Compared with the strategy of adopting exclusive local static information, the new strategy shows its advantages in improving the efficiency of the system. The detailed analysis of the mixing strategy is provided for explaining its effects on traffic routing. The work indicates that effectively utilizing the larger degree nodes plays a key role in scale-free traffic systems.
COMPUTATIONAL FLUID DYNAMICS MODELING ANALYSIS OF COMBUSTORS
Mathur, M.P.; Freeman, Mark; Gera, Dinesh
2001-11-06
In the current fiscal year FY01, several CFD simulations were conducted to investigate the effects of moisture in biomass/coal, particle injection locations, and flow parameters on carbon burnout and NO{sub x} inside a 150 MW GEEZER industrial boiler. Various simulations were designed to predict the suitability of biomass cofiring in coal combustors, and to explore the possibility of using biomass as a reburning fuel to reduce NO{sub x}. Some additional CFD simulations were also conducted on CERF combustor to examine the combustion characteristics of pulverized coal in enriched O{sub 2}/CO{sub 2} environments. Most of the CFD models available in the literature treat particles to be point masses with uniform temperature inside the particles. This isothermal condition may not be suitable for larger biomass particles. To this end, a stand alone program was developed from the first principles to account for heat conduction from the surface of the particle to its center. It is envisaged that the recently developed non-isothermal stand alone module will be integrated with the Fluent solver during next fiscal year to accurately predict the carbon burnout from larger biomass particles. Anisotropy in heat transfer in radial and axial will be explored using different conductivities in radial and axial directions. The above models will be validated/tested on various fullscale industrial boilers. The current NO{sub x} modules will be modified to account for local CH, CH{sub 2}, and CH{sub 3} radicals chemistry, currently it is based on global chemistry. It may also be worth exploring the effect of enriched O{sub 2}/CO{sub 2} environment on carbon burnout and NO{sub x} concentration. The research objective of this study is to develop a 3-Dimensional Combustor Model for Biomass Co-firing and reburning applications using the Fluent Computational Fluid Dynamics Code.
NASA Astrophysics Data System (ADS)
Syvitski, J. P.; Csdms Scientific; Software Team
2010-12-01
CSDMS is the virtual home for a diverse community who foster and promote the modeling of earth surface processes, with emphasis on the movement of fluids, sediment and solutes through landscapes, seascapes and through their sedimentary basins. CSDMS develops, integrates, disseminates & archives software (> 150 models and 3million+ lines of code) that reflects and predicts earth surface processes over a broad range of time and space scales. CSDMS deals with the Earth's surface—the ever-changing, dynamic interface between lithosphere, hydrosphere, cryosphere, and atmosphere. CSDMS employs state-of-the-art architectures, interface standards and frameworks that make it possible to convert stand-alone models into flexible, "plug-and-play" components that can be assembled into larger applications. The CSDMS model-coupling environment offers language interoperability, structured and unstructured grids, and serves as a migration pathway for surface dynamics modelers towards High-Performance Computing (HPC). The CSDMS Modeling Tool is a key product of the overall project, as it allows earth scientists with relatively modest computer coding experience to use the CSDMS modules for earth surface dynamics research and education. The CMT Tool is platform independent. CMT can easily couple models that have followed the CSDMS protocols for model contribution: 1) Open-source license; 2) Available; 3) Vetted; 4) Open-source language; 5) Refactored for componentization; 6) Metadata & test files; 7) Clean and documented using keywords.
ORPHEE 3D: Static and dynamic tridimensional BHA computer models
Birades, M.
1986-01-01
Elf Aquitaine, within an ARTEP research project granted by EEC, has developed two three-dimensional mathematical models to predict the directional behavior of bottom hole assemblies (BHAs). Both models simulate BHAs by finite element methods. The first model describes dynamically their transient behavior step by step during short time intervals which are continuously adjusted to attain the required precision. Displacements and lateral forces, computed for each step, integrate friction against the borehole wall through a sophisticated shock algorithm. The second model computes a static equilibrium of the BHA while assuming simplified friction forces at the contact points between the wellbore and the BHA. The lateral forces and displacements are found to be an average of the highly varying ones computed by the dynamic model and the static computer run is much faster.
Lee, Mi Kyung; Huo, Pengfei; Coker, David F
2016-05-27
This article reviews recent progress in the theoretical modeling of excitation energy transfer (EET) processes in natural light harvesting complexes. The iterative partial linearized density matrix path-integral propagation approach, which involves both forward and backward propagation of electronic degrees of freedom together with a linearized, short-time approximation for the nuclear degrees of freedom, provides an accurate and efficient way to model the nonadiabatic quantum dynamics at the heart of these EET processes. Combined with a recently developed chromophore-protein interaction model that incorporates both accurate ab initio descriptions of intracomplex vibrations and chromophore-protein interactions treated with atomistic detail, these simulation tools are beginning to unravel the detailed EET pathways and relaxation dynamics in light harvesting complexes.
NASA Astrophysics Data System (ADS)
Lee, Mi Kyung; Huo, Pengfei; Coker, David F.
2016-05-01
This article reviews recent progress in the theoretical modeling of excitation energy transfer (EET) processes in natural light harvesting complexes. The iterative partial linearized density matrix path-integral propagation approach, which involves both forward and backward propagation of electronic degrees of freedom together with a linearized, short-time approximation for the nuclear degrees of freedom, provides an accurate and efficient way to model the nonadiabatic quantum dynamics at the heart of these EET processes. Combined with a recently developed chromophore-protein interaction model that incorporates both accurate ab initio descriptions of intracomplex vibrations and chromophore-protein interactions treated with atomistic detail, these simulation tools are beginning to unravel the detailed EET pathways and relaxation dynamics in light harvesting complexes.
Integrated Experiment and Modeling of Insensitive High Explosives
NASA Astrophysics Data System (ADS)
Stewart, D. Scott; Lambert, David E.; Yoo, Sunhee; Lieber, M.; Holman, Steven
2009-06-01
New design paradigms for insensitive high explosives are being sought for use in munitions applications that require enhanced, safety, reliability and performance. We describe recent work of our group that uses an integrated approach to develop predictive models, guided by experiments. Insensitive explosive can have relatively longer detonation reaction zones and slower reaction rates than their sensitive counterparts. We employ reactive flow models that are constrained by detonation shock dynamics to pose candidate predictive models. We discuss variation of the pressure dependent reaction rate exponent and reaction order, on the length of the supporting reaction zone, the detonation velocity curvature relation, computed critical energy required for initiation, the relation between the diameter effect curve and the corresponding normal detonation velocity curvature relation. We discuss representative characterization experiments carried out at Eglin, AFB and the constraints imposed on models by a standardized experimental characterization sequence.
Single timepoint models of dynamic systems.
Sachs, K; Itani, S; Fitzgerald, J; Schoeberl, B; Nolan, G P; Tomlin, C J
2013-08-01
Many interesting studies aimed at elucidating the connectivity structure of biomolecular pathways make use of abundance measurements, and employ statistical and information theoretic approaches to assess connectivities. These studies often do not address the effects of the dynamics of the underlying biological system, yet dynamics give rise to impactful issues such as timepoint selection and its effect on structure recovery. In this work, we study conditions for reliable retrieval of the connectivity structure of a dynamic system, and the impact of dynamics on structure-learning efforts. We encounter an unexpected problem not previously described in elucidating connectivity structure from dynamic systems, show how this confounds structure learning of the system and discuss possible approaches to overcome the confounding effect. Finally, we test our hypotheses on an accurate dynamic model of the IGF signalling pathway. We use two structure-learning methods at four time points to contrast the performance and robustness of those methods in terms of recovering correct connectivity. PMID:24511382
Integrating Cloud-Computing-Specific Model into Aircraft Design
NASA Astrophysics Data System (ADS)
Zhimin, Tian; Qi, Lin; Guangwen, Yang
Cloud Computing is becoming increasingly relevant, as it will enable companies involved in spreading this technology to open the door to Web 3.0. In the paper, the new categories of services introduced will slowly replace many types of computational resources currently used. In this perspective, grid computing, the basic element for the large scale supply of cloud services, will play a fundamental role in defining how those services will be provided. The paper tries to integrate cloud computing specific model into aircraft design. This work has acquired good results in sharing licenses of large scale and expensive software, such as CFD (Computational Fluid Dynamics), UG, CATIA, and so on.
A quantitative model for integrating landscape evolution and soil formation
NASA Astrophysics Data System (ADS)
Vanwalleghem, T.; Stockmann, U.; Minasny, B.; McBratney, Alex B.
2013-06-01
evolution is closely related to soil formation. Quantitative modeling of the dynamics of soils and landscapes should therefore be integrated. This paper presents a model, named Model for Integrated Landscape Evolution and Soil Development (MILESD), which describes the interaction between pedogenetic and geomorphic processes. This mechanistic model includes the most significant soil formation processes, ranging from weathering to clay translocation, and combines these with the lateral redistribution of soil particles through erosion and deposition. The model is spatially explicit and simulates the vertical variation in soil horizon depth as well as basic soil properties such as texture and organic matter content. In addition, sediment export and its properties are recorded. This model is applied to a 6.25 km2 area in the Werrikimbe National Park, Australia, simulating soil development over a period of 60,000 years. Comparison with field observations shows how the model accurately predicts trends in total soil thickness along a catena. Soil texture and bulk density are predicted reasonably well, with errors of the order of 10%, however, field observations show a much higher organic carbon content than predicted. At the landscape scale, different scenarios with varying erosion intensity result only in small changes of landscape-averaged soil thickness, while the response of the total organic carbon stored in the system is higher. Rates of sediment export show a highly nonlinear response to soil development stage and the presence of a threshold, corresponding to the depletion of the soil reservoir, beyond which sediment export drops significantly.
The integrated Regional Earth System Model
NASA Astrophysics Data System (ADS)
Kraucunas, I.; Clarke, L.; Dirks, J.; Hejazi, M. I.; Hibbard, K. A.; Huang, M.; Janetos, A. C.; Kintner-Meyer, M.; Kleese van Dam, K.; Leung, L.; Moss, R. H.; Rice, J.; Scott, M. J.; Thomson, A. M.; West, T. O.; Whitney, P.; Yang, Z.
2012-12-01
The integrated Regional Earth System Model (iRESM) is a unique modeling framework being developed at Pacific Northwest National Laboratory (PNNL) to simulate the interactions among natural and human systems at scales relevant to regional decision making. The framework unites high-resolution models of regional climate, hydrology, agriculture, socioeconomics, and energy systems using a flexible software architecture. The framework is portable and can be customized to inform a variety of complex questions and decisions, including (but not limited to) planning, implementation, and evaluation of mitigation and adaptation options across a range of sectors. iRESM also incorporates extensive stakeholder interactions and analysis to inform model development, coupling strategies, and characterization of uncertainties. Ongoing numerical experiments are yielding new insights into the interactions among human and natural systems on regional scales, with an initial focus on the energy-land-water nexus and the penetration of renewable energy technologies in the upper U.S. Midwest. The iRESM framework also is being extended and applied to the U.S. Gulf Coast, with a particular emphasis on how changes in extreme events will affect both coastal in inland energy infrastructure in the region. This talk will focus on iRESM's development and capabilities, initial results from numerical experiments, and the challenges and opportunities associated with integrated regional modeling.
Dynamic functional integration of distinct neural empathy systems
2014-01-01
Recent evidence points to two separate systems for empathy: a vicarious sharing emotional system that supports our ability to share emotions and mental states and a cognitive system that involves cognitive understanding of the perspective of others. Several recent models offer new evidence regarding the brain regions involved in these systems, but no study till date has examined how regions within each system dynamically interact. The study by Raz et al. in this issue of Social, Cognitive, & Affective Neuroscience is among the first to use a novel approach of functional magnetic resonance imaging analysis of fluctuations in network cohesion while an individual is experiencing empathy. Their results substantiate the approach positing two empathy mechanisms and, more broadly, demonstrate how dynamic analysis of emotions can further our understanding of social behavior. PMID:23956080
Dynamic functional integration of distinct neural empathy systems.
Shamay-Tsoory, Simone G
2014-01-01
Recent evidence points to two separate systems for empathy: a vicarious sharing emotional system that supports our ability to share emotions and mental states and a cognitive system that involves cognitive understanding of the perspective of others. Several recent models offer new evidence regarding the brain regions involved in these systems, but no study till date has examined how regions within each system dynamically interact. The study by Raz et al. in this issue of Social, Cognitive, & Affective Neuroscience is among the first to use a novel approach of functional magnetic resonance imaging analysis of fluctuations in network cohesion while an individual is experiencing empathy. Their results substantiate the approach positing two empathy mechanisms and, more broadly, demonstrate how dynamic analysis of emotions can further our understanding of social behavior. PMID:23956080
Swarm Intelligence for Urban Dynamics Modelling
NASA Astrophysics Data System (ADS)
Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.
2009-04-01
In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.
Swarm Intelligence for Urban Dynamics Modelling
Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.
2009-04-16
In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.
Quantum Thermal Bath for Path Integral Molecular Dynamics Simulation.
Brieuc, Fabien; Dammak, Hichem; Hayoun, Marc
2016-03-01
The quantum thermal bath (QTB) method has been recently developed to account for the quantum nature of the nuclei by using standard molecular dynamics (MD) simulation. QTB-MD is an efficient but approximate method when dealing with strongly anharmonic systems, while path integral molecular dynamics (PIMD) gives exact results but in a huge amount of computation time. The QTB and PIMD methods have been combined in order to improve the PIMD convergence or correct the failures of the QTB-MD technique. Therefore, a new power spectral density of the random force within the QTB has been developed. A modified centroid-virial estimator of the kinetic energy, especially adapted to QTB-PIMD, has also been proposed. The method is applied to selected systems: a one-dimensional double-well system, a ferroelectric phase transition, and the position distribution of an hydrogen atom in a fuel cell material. The advantage of the QTB-PIMD method is its ability to give exact results with a more reasonable computation time for strongly anharmonic systems.
A High Precision Prediction Model Using Hybrid Grey Dynamic Model
ERIC Educational Resources Information Center
Li, Guo-Dong; Yamaguchi, Daisuke; Nagai, Masatake; Masuda, Shiro
2008-01-01
In this paper, we propose a new prediction analysis model which combines the first order one variable Grey differential equation Model (abbreviated as GM(1,1) model) from grey system theory and time series Autoregressive Integrated Moving Average (ARIMA) model from statistics theory. We abbreviate the combined GM(1,1) ARIMA model as ARGM(1,1)…
Dynamic process modeling with recurrent neural networks
You, Yong; Nikolaou, M. . Dept. of Chemical Engineering)
1993-10-01
Mathematical models play an important role in control system synthesis. However, due to the inherent nonlinearity, complexity and uncertainty of chemical processes, it is usually difficult to obtain an accurate model for a chemical engineering system. A method of nonlinear static and dynamic process modeling via recurrent neural networks (RNNs) is studied. An RNN model is a set of coupled nonlinear ordinary differential equations in continuous time domain with nonlinear dynamic node characteristics as well as both feed forward and feedback connections. For such networks, each physical input to a system corresponds to exactly one input to the network. The system's dynamics are captured by the internal structure of the network. The structure of RNN models may be more natural and attractive than that of feed forward neural network models, but computation time for training is longer. Simulation results show that RNNs can learn both steady-state relationships and process dynamics of continuous and batch, single-input/single-output and multi-input/multi-output systems in a simple and direct manner. Training of RNNs shows only small degradation in the presence of noise in the training data. Thus, RNNs constitute a feasible alternative to layered feed forward back propagation neural networks in steady-state and dynamic process modeling and model-based control.
Model systems for single molecule polymer dynamics
Latinwo, Folarin
2012-01-01
Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of “ideal” and “real” chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force–extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer–monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of “real” polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena. PMID:22956980
Integrated modeling of submillimeter radio telescopes
NASA Astrophysics Data System (ADS)
Moraru, Dan; Andersen, Torben
2002-07-01
Integrated models are inherently complex and often obscure to any but those who write them. Their usefulness can be greatly enhanced through well-structured, object-oriented design. A robust and computationally efficient Simulink/C++ library of optics, control, finite-element, and visualization routines for modeling radio telescope performance under various operating conditions is being developed and is described. The library is being developed in conjunction with an end-to-end model of the Atacama Large Millimeter Array (ALMA) antennas. The model includes the mechanical structure, optics, servos, and potential laser gyros, and can be used to investigate such issues as tracking performance, compliance with error budgets, wind sensitivity, and effectiveness of an internal metrology system. It will also be a good tool for comparison of different antenna designs.
Aggregated models for integrated distillation systems
Caballero, J.A.; Grossmann, I.E.
1999-06-01
In this work the authors present an aggregated representation for distillation columns that can be used in the synthesis of separation sequences with heat integration. A new aggregated model is first presented for the stripping and rectifying sections of individual distillation columns. This model is based on mass balances and equilibrium feasibility, expressed in terms of flows, inlet concentrations, and recoveries. The energy balance can then be decoupled from the mass balance, and the utilities can be calculated for each separation task. The proposed model is applied to three different superstructures: state task network, state equipment network, and an intermediate representation. The proposed model yields a lower bound to the vapor flow or to the total cost of the utilities. Performance of the different superstructure representations in terms of robustness and computational time is illustrated with several examples.
Integrated Model for E-Learning Acceptance
NASA Astrophysics Data System (ADS)
Ramadiani; Rodziah, A.; Hasan, S. M.; Rusli, A.; Noraini, C.
2016-01-01
E-learning is not going to work if the system is not used in accordance with user needs. User Interface is very important to encourage using the application. Many theories had discuss about user interface usability evaluation and technology acceptance separately, actually why we do not make it correlation between interface usability evaluation and user acceptance to enhance e-learning process. Therefore, the evaluation model for e-learning interface acceptance is considered important to investigate. The aim of this study is to propose the integrated e-learning user interface acceptance evaluation model. This model was combined some theories of e-learning interface measurement such as, user learning style, usability evaluation, and the user benefit. We formulated in constructive questionnaires which were shared at 125 English Language School (ELS) students. This research statistics used Structural Equation Model using LISREL v8.80 and MANOVA analysis.
Integrated statistical modelling of spatial landslide probability
NASA Astrophysics Data System (ADS)
Mergili, M.; Chu, H.-J.
2015-09-01
Statistical methods are commonly employed to estimate spatial probabilities of landslide release at the catchment or regional scale. Travel distances and impact areas are often computed by means of conceptual mass point models. The present work introduces a fully automated procedure extending and combining both concepts to compute an integrated spatial landslide probability: (i) the landslide inventory is subset into release and deposition zones. (ii) We employ a simple statistical approach to estimate the pixel-based landslide release probability. (iii) We use the cumulative probability density function of the angle of reach of the observed landslide pixels to assign an impact probability to each pixel. (iv) We introduce the zonal probability i.e. the spatial probability that at least one landslide pixel occurs within a zone of defined size. We quantify this relationship by a set of empirical curves. (v) The integrated spatial landslide probability is defined as the maximum of the release probability and the product of the impact probability and the zonal release probability relevant for each pixel. We demonstrate the approach with a 637 km2 study area in southern Taiwan, using an inventory of 1399 landslides triggered by the typhoon Morakot in 2009. We observe that (i) the average integrated spatial landslide probability over the entire study area corresponds reasonably well to the fraction of the observed landside area; (ii) the model performs moderately well in predicting the observed spatial landslide distribution; (iii) the size of the release zone (or any other zone of spatial aggregation) influences the integrated spatial landslide probability to a much higher degree than the pixel-based release probability; (iv) removing the largest landslides from the analysis leads to an enhanced model performance.
A stochastic model of human gait dynamics
NASA Astrophysics Data System (ADS)
Ashkenazy, Yosef; M. Hausdorff, Jeffrey; Ch. Ivanov, Plamen; Eugene Stanley, H.
2002-12-01
We present a stochastic model of gait rhythm dynamics, based on transitions between different “neural centers”, that reproduces distinctive statistical properties of normal human walking. By tuning one model parameter, the transition (hopping) range, the model can describe alterations in gait dynamics from childhood to adulthood-including a decrease in the correlation and volatility exponents with maturation. The model also generates time series with multifractal spectra whose broadness depends only on this parameter. Moreover, we find that the volatility exponent increases monotonically as a function of the width of the multifractal spectrum, suggesting the possibility of a change in multifractality with maturation.
The future dynamic world model
NASA Astrophysics Data System (ADS)
Karr, Thomas J.
2014-10-01
Defense and security forces exploit sensor data by means of a model of the world. They use a world model to geolocate sensor data, fuse it with other data, navigate platforms, recognize features and feature changes, etc. However, their need for situational awareness today exceeds the capabilities of their current world model for defense operations, despite the great advances of sensing technology in recent decades. I review emerging technologies that may enable a great improvement in the spatial and spectral coverage, the timeliness, and the functional insight of their world model.
Complexity vs. Simplicity: Tradeoffs in Integrated Water Resources Models
NASA Astrophysics Data System (ADS)
Gonda, J.; Elshorbagy, A. A.; Wheater, H. S.; Razavi, S.
2014-12-01
Integrated Water Resources Management is an interdisciplinary approach to managing water. Integration often involves linking hydrologic processes with socio-economic development. When implemented through a simulation or optimization model, complexities arise. This complexity is due to the large data requirements, making it difficult to implement by the end users. Not only is computational efficiency at stake, but it becomes cumbersome to future model users. To overcome this issue the model may be simplified through emulation, at the expense of information loss. Herein lies a tradeoff: Complexity involved in an accurate, detailed model versus the transparency and saliency of a simplified model. This presentation examines the role of model emulation towards simplifying a water allocation model. The case study is located in Southern Alberta, Canada. Water here is allocated between agricultural, municipal, environmental and energy sectors. Currently, water allocation is modeled through a detailed optimization model, WRMM. Although WRMM can allocate water on a priority basis, it lacks the simplicity needed by the end user. The proposed System Dynamics-based model, SWAMP 2.0, emulates this optimization model, utilizing two scales of complexity. A regional scale spatially aggregates individual components, reducing the complexity of the original model. A local scale retains the original detail, and is contained within the regional scale. This two tiered emulation presents relevant spatial scales to water managers, who may not be interested in all the details of WRMM. By evaluating the accuracy of SWAMP 2.0 against the original allocation model, the tradeoff of accuracy for simplicity can be further realized.
Multi-scale modelling and dynamics
NASA Astrophysics Data System (ADS)
Müller-Plathe, Florian
Moving from a fine-grained particle model to one of lower resolution leads, with few exceptions, to an acceleration of molecular mobility, higher diffusion coefficient, lower viscosities and more. On top of that, the level of acceleration is often different for different dynamical processes as well as for different state points. While the reasons are often understood, the fact that coarse-graining almost necessarily introduces unpredictable acceleration of the molecular dynamics severely limits its usefulness as a predictive tool. There are several attempts under way to remedy these shortcoming of coarse-grained models. On the one hand, we follow bottom-up approaches. They attempt already when the coarse-graining scheme is conceived to estimate their impact on the dynamics. This is done by excess-entropy scaling. On the other hand, we also pursue a top-down development. Here we start with a very coarse-grained model (dissipative particle dynamics) which in its native form produces qualitatively wrong polymer dynamics, as its molecules cannot entangle. This model is modified by additional temporary bonds, so-called slip springs, to repair this defect. As a result, polymer melts and solutions described by the slip-spring DPD model show correct dynamical behaviour. Read more: ``Excess entropy scaling for the segmental and global dynamics of polyethylene melts'', E. Voyiatzis, F. Müller-Plathe, and M.C. Böhm, Phys. Chem. Chem. Phys. 16, 24301-24311 (2014). [DOI: 10.1039/C4CP03559C] ``Recovering the Reptation Dynamics of Polymer Melts in Dissipative Particle Dynamics Simulations via Slip-Springs'', M. Langeloth, Y. Masubuchi, M. C. Böhm, and F. Müller-Plathe, J. Chem. Phys. 138, 104907 (2013). [DOI: 10.1063/1.4794156].
Dynamical phase transitions, time-integrated observables, and geometry of states
NASA Astrophysics Data System (ADS)
Hickey, James M.; Genway, Sam; Garrahan, Juan P.
2014-02-01
We show that there exist dynamical phase transitions (DPTs), as defined by Heyl et al. [Phys. Rev. Lett. 110, 135704 (2013), 10.1103/PhysRevLett.110.135704], in the transverse-field Ising model (TFIM) away from the static quantum critical points. We study a class of special states associated with singularities in the generating functions of time-integrated observables as found by Hickey et al. [Phys. Rev. B 87, 184303 (2013)], 10.1103/PhysRevB.87.184303. Studying the dynamics of these special states under the evolution of the TFIM Hamiltonian, we find temporal nonanalyticities in the initial-state return probability associated with dynamical phase transitions. By calculating the Berry phase and Chern number we show the set of special states have interesting geometric features similar to those associated with static quantum critical points.
Stirling Engine Dynamic System Modeling
NASA Technical Reports Server (NTRS)
Nakis, Christopher G.
2004-01-01
The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.
Energy Balance Models and Planetary Dynamics
NASA Technical Reports Server (NTRS)
Domagal-Goldman, Shawn
2012-01-01
We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.
Modeling cell shape and dynamics on micropatterns
Albert, Philipp J.; Schwarz, Ulrich S.
2016-01-01
ABSTRACT Adhesive micropatterns have become a standard tool to study cells under defined conditions. Applications range from controlling the differentiation and fate of single cells to guiding the collective migration of cell sheets. In long-term experiments, single cell normalization is challenged by cell division. For all of these setups, mathematical models predicting cell shape and dynamics can guide pattern design. Here we review recent advances in predicting and explaining cell shape, traction forces and dynamics on micropatterns. Starting with contour models as the simplest approach to explain concave cell shapes, we move on to network and continuum descriptions as examples for static models. To describe dynamic processes, cellular Potts, vertex and phase field models can be used. Different types of model are appropriate to address different biological questions and together, they provide a versatile tool box to predict cell behavior on micropatterns. PMID:26838278
Haptics-based dynamic implicit solid modeling.
Hua, Jing; Qin, Hong
2004-01-01
This paper systematically presents a novel, interactive solid modeling framework, Haptics-based Dynamic Implicit Solid Modeling, which is founded upon volumetric implicit functions and powerful physics-based modeling. In particular, we augment our modeling framework with a haptic mechanism in order to take advantage of additional realism associated with a 3D haptic interface. Our dynamic implicit solids are semi-algebraic sets of volumetric implicit functions and are governed by the principles of dynamics, hence responding to sculpting forces in a natural and predictable manner. In order to directly manipulate existing volumetric data sets as well as point clouds, we develop a hierarchical fitting algorithm to reconstruct and represent discrete data sets using our continuous implicit functions, which permit users to further design and edit those existing 3D models in real-time using a large variety of haptic and geometric toolkits, and visualize their interactive deformation at arbitrary resolution. The additional geometric and physical constraints afford more sophisticated control of the dynamic implicit solids. The versatility of our dynamic implicit modeling enables the user to easily modify both the geometry and the topology of modeled objects, while the inherent physical properties can offer an intuitive haptic interface for direct manipulation with force feedback.
Wimmer, Klaus; Compte, Albert; Roxin, Alex; Peixoto, Diogo; Renart, Alfonso; de la Rocha, Jaime
2015-01-01
Neuronal variability in sensory cortex predicts perceptual decisions. This relationship, termed choice probability (CP), can arise from sensory variability biasing behaviour and from top-down signals reflecting behaviour. To investigate the interaction of these mechanisms during the decision-making process, we use a hierarchical network model composed of reciprocally connected sensory and integration circuits. Consistent with monkey behaviour in a fixed-duration motion discrimination task, the model integrates sensory evidence transiently, giving rise to a decaying bottom-up CP component. However, the dynamics of the hierarchical loop recruits a concurrently rising top-down component, resulting in sustained CP. We compute the CP time-course of neurons in the medial temporal area (MT) and find an early transient component and a separate late contribution reflecting decision build-up. The stability of individual CPs and the dynamics of noise correlations further support this decomposition. Our model provides a unified understanding of the circuit dynamics linking neural and behavioural variability. PMID:25649611
Synaptic dynamics: linear model and adaptation algorithm.
Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W
2014-08-01
In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neur