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.
Dynamic Integrated Climate Economy model (DICE)
The DICE model is an Integrated Assessment model of climate change impacts and costs, which “integrate[s] in an end-to-end fashion the economics, carbon cycle, climate science, and impacts in a highly aggregated model that allow[s] a weighing of the costs and benefits of taking s...
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
Regional Dynamic Simulation Modeling and Analysis of Integrated Energy Futures
MALCZYNSKI, LEONARD A.; BEYELER, WALTER E.; CONRAD, STEPHEN H.; HARRIS, DAVID B; REXROTH, PAUL E.; BAKER, ARNOLD B.
2002-11-01
The Global Energy Futures Model (GEFM) is a demand-based, gross domestic product (GDP)-driven, dynamic simulation tool that provides an integrated framework to model key aspects of energy, nuclear-materials storage and disposition, environmental effluents from fossil and non fossil energy and global nuclear-materials management. Based entirely on public source data, it links oil, natural gas, coal, nuclear and renewable energy dynamically to greenhouse-gas emissions and 12 other measures of environmental impact. It includes historical data from 1990 to 2000, is benchmarked to the DOE/EIA/IEO 2001 [5] Reference Case for 2000 to 2020, and extrapolates energy demand through the year 2050. The GEFM is globally integrated, and breaks out five regions of the world: United States of America (USA), the Peoples Republic of China (China), the former Soviet Union (FSU), the Organization for Economic Cooperation and Development (OECD) nations excluding the USA (other industrialized countries), and the rest of the world (ROW) (essentially the developing world). The GEFM allows the user to examine a very wide range of ''what if'' scenarios through 2050 and to view the potential effects across widely dispersed, but interrelated areas. The authors believe that this high-level learning tool will help to stimulate public policy debate on energy, environment, economic and national security issues.
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.
An Integrated Model for Drill-String Dynamics
NASA Astrophysics Data System (ADS)
Tucker, W. R.; Wang, C.
1999-07-01
The vibrational states experienced by the active components of a drilling assembly such as that found in the oil or gas industry are discussed in the context of an integrated mathematical model. The work is motivated by the need to understand the complex vibrational states that such a system can exhibit in order to better control their constructive and destructive potential. The model is expressed in terms of six continuous independent degrees of freedom. Three locate the position of the centroid of the drill-string in space and three permit the dynamical state of the drill-string to be expressed in terms of flexural, torsional and shear strain, together with dilation and stretch. By supplementing the model with appropriate constitutive relations that relate these strains to bending and twisting couples together with shear and compression forces it can fully accommodate the modes of vibration that are traditionally associated with the motion of drill-strings in both straight and curved boreholes discussed in the engineering literature. These include axial motion along the length of the drill-string, torsional or rotational motion and transverse or lateral motion. Attention is given to the boundary conditions appropriate for an active drill-string and BHA stabiliser including an account of frictional simulations at the rock-interface, cutter simulations for different types of drill-bit and interactions between the bore cavity and the drill-string. The model is used to discuss the stability of axisymmetric drill-string configurations in vertical boreholes under both coupled torsional, axial and lateral perturbations as well as general non-perturbative coupled vibrational states under extreme conditions of lateral whirl.
State variable modeling of the integrated engine and aircraft dynamics
NASA Astrophysics Data System (ADS)
Rotaru, Constantin; SprinÅ£u, Iuliana
2014-12-01
This study explores the dynamic characteristics of the combined aircraft-engine system, based on the general theory of the state variables for linear and nonlinear systems, with details leading first to the separate formulation of the longitudinal and the lateral directional state variable models, followed by the merging of the aircraft and engine models into a single state variable model. The linearized equations were expressed in a matrix form and the engine dynamics was included in terms of variation of thrust following a deflection of the throttle. The linear model of the shaft dynamics for a two-spool jet engine was derived by extending the one-spool model. The results include the discussion of the thrust effect upon the aircraft response when the thrust force associated with the engine has a sizable moment arm with respect to the aircraft center of gravity for creating a compensating moment.
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
Integrated wetland management: an analysis with group model building based on system dynamics model.
Chen, Hsin; Chang, Yang-Chi; Chen, Kung-Chen
2014-12-15
The wetland system possesses diverse functions such as preserving water sources, mediating flooding, providing habitats for wildlife and stabilizing coastlines. Nonetheless, rapid economic growth and the increasing population have significantly deteriorated the wetland environment. To secure the sustainability of the wetland, it is essential to introduce integrated and systematic management. This paper examines the resource management of the Jiading Wetland by applying group model building (GMB) and system dynamics (SD). We systematically identify local stakeholders' mental model regarding the impact brought by the yacht industry, and further establish a SD model to simulate the dynamic wetland environment. The GMB process improves the stakeholders' understanding about the interaction between the wetland environment and management policies. Differences between the stakeholders' perceptions and the behaviors shown by the SD model also suggest that our analysis would facilitate the stakeholders to broaden their horizons and achieve consensus on the wetland resource management. PMID:25194518
NASA Astrophysics Data System (ADS)
Phinn, S. R.; Roelfsema, C.; Leon, J.; Borrego, R.; Canto, R.; Joyce, K.; McGowan, H. A.; Mackellar, M. C.
2012-12-01
Developing a complete understanding of the contemporary biogeophysical processes shaping coral reef ecosystems requires integration across multiple disciplines. This paper outlines the results obtained across multiple disciplinary projects for developing an integrated understanding of the biogeophysical processes shaping Heron Reef, on the Great Barrier Reef Australia. Heron Reef is a lagoonal platform reef on the southern Great Reef, with a small coral cay on its western edge. Over the past 10 years the nature of research undertaken On Heron reef has moved from plot-scale field surveys and lab experiments, to process-based measurements and experiments over the entire reef, its adjacent oceanic areas and atmosphere. Resultsfrom four projects are presented to act as the foundation for a conceptual model of biogeophysical processes affecting the reef. These cover: (1) benthic composition mapping; (2) biogeophysical forcing processes; (3) dynamics of benthic composition; and (4) dynamics of geomorphic zonation. (1) Benthic composition and reef structure/bathymetry/rugosity mapping to centimetre scales have been completed on an annual basis for > 10 years using standardised methods to quantify the composition of the reef substrate and benthos. Assessment of the resulting annual data sets, shows distinctive spatial variability in macro-algal and benthic micro-algal cover within and between years, while coral cover changes are longer term, unless linked to disturbance events. These data are critical for calibrating and validating satellite image mapping and models of benthic cover composition and dynamics, and determining input areas for foot-printing of eddy-correlation measurements of coral reef energy and gas fluxes. (2) Biogeophysical processes affected by surface energy and gas exchanges and hydrodynamic forcing by gravity waves and tidal currents have only been measured within past 10 years due to developments in sensor technology. For Heron Reef, several
Reactive oxygen species and energy machinery: an integrated dynamic model.
Korla, Kalyani
2016-08-01
The role of several important reactive oxygen species (ROS) on the Krebs cycle, the electron transport chain (ETC) and the two important shuttles has been modelled. Major part of the ROS is produced during oxygen reduction in the ETC, which has been kinetically simulated, and the changes in the final concentrations of several important metabolites were found. The simulation is based on chemical kinetics equation, and the associated set of differential equations was solved by the ordinary differential equation package in Octave. The validity of the model is checked by comparing the experimental results available in the literature with the simulations when a part of the ETC is blocked (80%) in the script. The present approach is versatile and flexible and has potential applications in various simulations. It is easy to study the change in concentrations of various metabolites when a particular enzyme or pathway is blocked (say by a drug). The Octave script is presented in the text. PMID:26309069
Integration of finite element modeling with solid modeling through a dynamic interface
NASA Technical Reports Server (NTRS)
Shephard, Mark S.
1987-01-01
Finite element modeling is dominated by geometric modeling type operations. Therefore, an effective interface to geometric modeling requires access to both the model and the modeling functionality used to create it. The use of a dynamic interface that addresses these needs through the use of boundary data structures and geometric operators is discussed.
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
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
Global/Regional Integrated Model System (GRIMs): Double Fourier Series (DFS) Dynamical Core
NASA Astrophysics Data System (ADS)
Koo, M.; Hong, S.
2013-12-01
A multi-scale atmospheric/oceanic model system with unified physics, the Global/Regional Integrated Model system (GRIMs) has been created for use in numerical weather prediction, seasonal simulations, and climate research projects, from global to regional scales. It includes not only the model code, but also the test cases and scripts. The model system is developed and practiced by taking advantage of both operational and research applications. We outlines the history of GRIMs, its current applications, and plans for future development, providing a summary useful to present and future users. In addition to the traditional spherical harmonics (SPH) dynamical core, a new spectral method with a double Fourier series (DFS) is available in the GRIMs (Table 1). The new DFS dynamical core with full physics is evaluated against the SPH dynamical core in terms of short-range forecast capability for a heavy rainfall event and seasonal simulation framework. Comparison of the two dynamical cores demonstrates that the new DFS dynamical core exhibits performance comparable to the SPH in terms of simulated climatology accuracy and the forecast of a heavy rainfall event. Most importantly, the DFS algorithm guarantees improved computational efficiency in the cluster computer as the model resolution increases, which is consistent with theoretical values computed from the dry primitive equation model framework of Cheong (Fig. 1). The current study shows that, at higher resolutions, the DFS approach can be a competitive dynamical core because the DFS algorithm provides the advantages of both the spectral method for high numerical accuracy and the grid-point method for high performance computing in the aspect of computational cost. GRIMs dynamical cores
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
2014-01-01
This paper 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 10 mm 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. PMID:25169658
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. PMID:25169658
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.
Integrating an open source dynamic river model in hydrology modeling frameworks
NASA Astrophysics Data System (ADS)
Liu, Frank; Hodges, Ben
2014-05-01
A challenge for hydrology modeling is linking landscape runoff models with river network models. Although some hydrological models directly implement a river routing scheme within their code, such a monolithic approach is too rigid because it does not allow the latest river routing advances to be used. Unlike the 2D interface between atmospheric and landscape models, the interface between landscape runoff models and river network models is more difficult to define. In this PICO presentation, we address problems with model interfaces, which are related to issues such as time and space-scale differences between the models. We also provide an overview of SPRINT, an open source river network model, which has adapted the model interface architecture and numerical methods widely used in semiconductor microchip design. Finally, we propose two model integration mechanisms: the file-based "net-list" and the API (application programming interface) approach.
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. PMID:25897511
Construction and evaluation of an integrated dynamical model of visual motion perception
Dosher, Barbara Anne; Lu, Zhong-Lin
2015-01-01
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. PMID:25897511
Modelling Complex Systems by Integration of Agent-Based and Dynamical Systems Models
NASA Astrophysics Data System (ADS)
Bosse, Tibor; Sharpanskykh, Alexei; Treur, Jan
Existing models for complex systems are often based on quantitative, numerical methods such as Dynamical Systems Theory (DST) [Port and Gelder 1995]. Such approaches often use numerical variables to describe global aspects and specify how they affect each other over time. An advantage of such approaches is that numerical approximation methods and software are available for simulation.
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. PMID:22366346
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
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.
NASA Astrophysics Data System (ADS)
Getirana, A.; Sulistioadi, Y. B.; Van Den Hoek, J.; Peters-Lidard, C. D.
2014-12-01
For hundreds of years, humans have altered river flow regimes all over the world with the construction of dams for hydropower generation, water supply, irrigation, navigation, and other reasons. Reservoirs resulting from dams usually have a high impact on the surrounding area by permanently flooding riparian habitat, changing river flow dynamics and soil moisture, disturbing riverine activities and fish migration, imposing the relocation of human settlements, and increasing methane emission due to submerged organic matter. The representation of these anthropogenic activities in numerical models has been the subject of several studies. However, access to reservoir operational data is often limited, preventing us from developing a consistent global scale river flow dynamic model and its physical interactions with the atmosphere and soil. Recent advances in radar altimetry (RA) data acquisition enable us to accurately monitor reservoirs in regions where distribution to information has long been restricted due to data share policies. In this study, we evaluate the potential of integrating RA data into reservoir operational modeling. Spaceborne remotely sensed data collected by the Envisat radar altimeter (2002-2010), IceSAT GLAS lidar (2003-2009), and daily inflow, outflow and water elevation data collected in situ since 2005 have been analyzed across 28 reservoirs on various Brazilian rivers. Changes in the reservoir surface water elevation from each of these data sources are compared and differences are examined with respect to seasonality and accuracy. A reservoir operation algorithm capable of integrating RA data is presented and evaluated. We discuss prospects and challenges for implementing the algorithm in a global-scale river routing scheme in order to improve our process-level understanding on river dynamics and variability.
Dynamics of global vegetation biomass simulated by the integrated Earth System Model
NASA Astrophysics Data System (ADS)
Mao, J.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.; Piao, S.; Yang, X.; Truesdale, J. E.; Bond-Lamberty, B. P.; Chini, L. P.; Thomson, A. M.; Hurtt, G. C.; Collins, W.; Edmonds, J.
2014-12-01
The global vegetation biomass stores huge amounts of carbon and is thus important to the global carbon budget (Pan et al., 2010). For the past few decades, different observation-based estimates and modeling of biomass in the above- and below-ground vegetation compartments have been comprehensively conducted (Saatchi et al., 2011; Baccini et al., 2012). However, uncertainties still exist, in particular for the simulation of biomass magnitude, tendency, and the response of biomass to climatic conditions and natural and human disturbances. The recently successful coupling of the integrated Earth System Model (iESM) (Di Vittorio et al., 2014; Bond-Lamberty et al., 2014), which links the Global Change Assessment Model (GCAM), Global Land-use Model (GLM), and Community Earth System Model (CESM), offers a great opportunity to understand the biomass-related dynamics in a fully-coupled natural and human modeling system. In this study, we focus on the systematic analysis and evaluation of the iESM simulated historical (1850-2005) and future (2006-2100) biomass changes and the response of the biomass dynamics to various impact factors, in particular the human-induced Land Use/Land Cover Change (LULCC). By analyzing the iESM simulations with and without the interactive LULCC feedbacks, we further study how and where the climate feedbacks affect socioeconomic decisions and LULCC, such as to alter vegetation carbon storage. References Pan Y et. al: A large and persistent carbon sink in the World's forests. Science 2011, 333:988-993. Saatchi SS et al: Benchmark map of forest carbon stocks in tropical regions across three continents. Proc Natl Acad Sci 2011, 108:9899-9904. Baccini A et al: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Clim Change 2012, 2:182-185. Di Vittorio AV et al: From land use to land cover: restoring the afforestation signal in a coupled integrated assessment-earth system model and the implications for
NASA Astrophysics Data System (ADS)
Calvisi, Michael; Manmi, Kawa; Wang, Qianxi
2014-11-01
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. The nonspherical dynamics of contrast agents are thought to play an important role in both diagnostic and therapeutic applications, for example, causing the emission of subharmonic frequency components and enhancing the uptake of therapeutic agents across cell membranes and tissue interfaces. A three-dimensional model for nonspherical contrast agent dynamics based on the boundary integral method is presented. The effects of the encapsulating shell are approximated by adapting Hoff's model for thin-shell, spherical contrast agents to the nonspherical case. A high-quality mesh of the bubble surface is maintained by implementing a hybrid approach of the Lagrangian method and elastic mesh technique. Numerical analyses for the dynamics of UCAs in an infinite liquid and near a rigid wall are performed in parameter regimes of clinical relevance. The results show that the presence of a coating significantly reduces the oscillation amplitude and period, increases the ultrasound pressure amplitude required to incite jetting, and reduces the jet width and velocity.
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
Jimenez Del Val, Ioscani; Fan, Yuzhou; Weilguny, Dietmar
2016-05-01
Ensuring consistent glycosylation-associated quality of therapeutic monoclonal antibodies (mAbs) has become a priority in pharmaceutical bioprocessing given that the distribution and composition of the carbohydrates (glycans) bound to these molecules determines their therapeutic efficacy and immunogenicity. However, the interaction between bioprocess conditions, cellular metabolism and the intracellular process of glycosylation remains to be fully understood. To gain further insight into these interactions, we present a novel integrated modelling platform that links dynamic variations in mAb glycosylation with cellular secretory capacity. Two alternative mechanistic representations of how mAb specific productivity (qp ) influences glycosylation are compared. In the first, mAb glycosylation is modulated by the linear velocity with which secretory cargo traverses the Golgi apparatus. In the second, glycosylation is influenced by variations in Golgi volume. Within our modelling framework, both mechanisms accurately reproduce experimentally-observed dynamic changes in mAb glycosylation. In addition, an optimisation-based strategy has been developed to estimate the concentration of glycosylation enzymes required to minimise mAb glycoform variability. Our results suggest that the availability of glycosylation machinery relative to cellular secretory capacity may play a crucial role in mAb glycosylation. In the future, the modelling framework presented here may aid in selecting and engineering cell lines that ensure consistent mAb glycosylatio. PMID:26743760
A pilot point guided pattern matching approach to integrate dynamic data into geological modeling
NASA Astrophysics Data System (ADS)
Li, Liangping; Srinivasan, Sanjay; Zhou, Haiyan; Gómez-Hernández, J. J.
2013-12-01
Methods based on multiple-point statistics (MPS) have been routinely used to characterize complex geological formations in the last decade. These methods use the available static data (for example, measured conductivities) for conditioning. Integrating dynamic data (for example, measured transient piezometric head data) into the same framework is challenging because of the complex non-linear relationship between the dynamic response and geology. The Ensemble PATtern (EnPAT) search method was recently developed as a promising technique to handle this problem. In this approach, a pattern is postulated to be composed of both parameter and state variables, and then, parameter values are sequentially (point-wise) simulated by directly sampling the matched pattern from an ensemble of training images of both geologic parameters and state variables. As a consequence, the updated ensemble of realizations of the geological parameters preserve curvilinear structures (i.e., non-multiGaussanity) as well as the complex relationship between static and dynamic data. Moreover, the uncertainty of flow and transport predictions can be assessed using the updated ensemble of geological models. In this work, we further modify the EnPAT method by introducing the pilot-point concept into the algorithm. More specifically, the parameter values at a set of randomly selected pilot point locations are simulated by the pattern searching procedure, and then a faster MPS method is used to complete the simulation by conditioning to the previously simulated pilot point values. This pilot point guided MPS implementation results in lower computational cost and more accurate inference of the parameter field. In addition, in some situations where there is sparsity of measured geologic static data, the EnPAT algorithm is extended to work only with the dynamic data. We employed a synthetic example to demonstrate the effectiveness of pilot points in the implementation of EnPAT, and also the capability of
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
Energetics and dynamics of global integrals modeling interaction between stiff filaments.
Reiter, Philipp; Felix, Dieter; von der Mosel, Heiko; Alt, Wolfgang
2009-09-01
The attractive and spacing interaction between pairs of filaments via cross-linkers, e.g. myosin oligomers connecting actin filaments, is modeled by global integral kernels for negative binding energies between two intersecting stiff and long rods in a (projected) two-dimensional situation, for simplicity. Whereas maxima of the global energy functional represent intersection angles of 'minimal contact' between the filaments, minima are approached for energy values tending to -infinity, representing the two degenerate states of parallel and anti-parallel filament alignment. Standard differential equations of negative gradient flow for such energy functionals show convergence of solutions to one of these degenerate equilibria in finite time, thus called 'super-stable' states. By considering energy variations under virtual rotation or translation of one filament with respect to the other, integral kernels for the resulting local forces parallel and orthogonal to the filament are obtained. For the special modeling situation that these variations only activate 'spring forces' in direction of the cross-links, explicit formulas for total torque and translational forces are given and calculated for typical examples. Again, the two degenerate alignment states are locally 'super-stable' equilibria of the assumed over-damped dynamics, but also other stable states of orthogonal arrangement and different asymptotic behavior can occur. These phenomena become apparent if stochastic perturbations of the local force kernels are implemented as additive Gaussian noise induced by the cross-link binding process with appropriate scaling. Then global filament dynamics is described by a certain type of degenerate stochastic differential equations yielding asymptotic stationary processes around the alignment states, which have generalized, namely bimodal Gaussian distributions. Moreover, stochastic simulations reveal characteristic sliding behavior as it is observed for myosin
Duality in Phase Space and Complex Dynamics of an Integrated Pest Management Network Model
NASA Astrophysics Data System (ADS)
Yuan, Baoyin; Tang, Sanyi; Cheke, Robert A.
Fragmented habitat patches between which plants and animals can disperse can be modeled as networks with varying degrees of connectivity. A predator-prey model with network structures is proposed for integrated pest management (IPM) with impulsive control actions. The model was analyzed using numerical methods to investigate how factors such as the impulsive period, the releasing constant of natural enemies and the mode of connections between the patches affect pest outbreak patterns and the success or failure of pest control. The concept of the cluster as defined by Holland and Hastings is used to describe variations in results ranging from global synchrony when all patches have identical fluctuations to n-cluster solutions with all patches having different dynamics. Heterogeneity in the initial densities of either pest or natural enemy generally resulted in a variety of cluster oscillations. Surprisingly, if n > 1, the clusters fall into two groups one with low amplitude fluctuations and the other with high amplitude fluctuations (i.e. duality in phase space), implying that control actions radically alter the system's characteristics by inducing duality and more complex dynamics. When the impulsive period is small enough, i.e. the control strategy is undertaken frequently, the pest can be eradicated. As the period increases, the pest's dynamics shift from a steady state to become chaotic with periodic windows and more multicluster oscillations arise for heterogenous initial density distributions. Period-doubling bifurcation and periodic halving cascades occur as the releasing constant of the natural enemy increases. For the same ecological system with five differently connected networks, as the randomness of the connectedness increases, the transient duration becomes smaller and the probability of multicluster oscillations appearing becomes higher.
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. PMID:26497003
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
Integration methods for molecular dynamics
Leimkuhler, B.J.; Reich, S.; Skeel, R.D.
1996-12-31
Classical molecular dynamics simulation of a macromolecule requires the use of an efficient time-stepping scheme that can faithfully approximate the dynamics over many thousands of timesteps. Because these problems are highly nonlinear, accurate approximation of a particular solution trajectory on meaningful time intervals is neither obtainable nor desired, but some restrictions, such as symplecticness, can be imposed on the discretization which tend to imply good long term behavior. The presence of a variety of types and strengths of interatom potentials in standard molecular models places severe restrictions on the timestep for numerical integration used in explicit integration schemes, so much recent research has concentrated on the search for alternatives that possess (1) proper dynamical properties, and (2) a relative insensitivity to the fastest components of the dynamics. We survey several recent approaches. 48 refs., 2 figs.
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)
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.
Inhibition in the Dynamics of Selective Attention: An Integrative Model for Negative Priming
Schrobsdorff, Hecke; Ihrke, Matthias; Behrendt, Jörg; Hasselhorn, Marcus; Herrmann, J. Michael
2012-01-01
We introduce a computational model of the negative priming (NP) effect that includes perception, memory, attention, decision making, and action. The model is designed to provide a coherent picture across competing theories of NP. The model is formulated in terms of abstract dynamics for the activations of features, their binding into object entities, their semantic categorization as well as related memories and appropriate reactions. The dynamic variables interact in a connectionist network which is shown to be adaptable to a variety of experimental paradigms. We find that selective attention can be modeled by means of inhibitory processes and by a threshold dynamics. From the necessity of quantifying the experimental paradigms, we conclude that the specificity of the experimental paradigm must be taken into account when predicting the nature of the NP effect. PMID:23162523
Technology Transfer Automated Retrieval System (TEKTRAN)
Challenges in agro-ecosystem conservation management have created demand for state-of-the-art, integrated, and flexible modeling tools. For example, agricultural system modeling tools are needed which are robust and fast enough to be applied on large watershed scales, but which are also able to simu...
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...
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 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
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.
NASA Astrophysics Data System (ADS)
Soulsby, C.; Birkel, C.; Tetzlaff, D.
2012-12-01
Water supplies and the ecohydrological function of terrestrial and aquatic ecosystems are dependent on the storage and release of water from the unsaturated and saturated zone of catchments. Attempts to measure and estimate storage dynamics at operational catchment scales are hampered by spatial heterogeneity which makes interpolation of point measurements (e.g. of soil moisture and groundwater dynamics) difficult. Storage-discharge relationships from rainfall-runoff models can explicitly acknowledge that water storage is neither time nor space invariant and can be useful to assess catchment storage dynamics. However, input-output relationships of natural isotopic tracers such as oxygen-18 and deuterium usually show damping and time-lags in stream flow response to precipitation fluxes. Such damping behaviour implies large mixing volumes that are usually much greater than those suggested by dynamic storage changes estimated from water balance calculations in rainfall-runoff models. This larger volume is often referred to as "passive" storage or so-called "immobile" water available for mixing that hydraulically does not contribute to streamflow at least in the short-term. Thus, combining tracer based storage (passive) estimates with those inferred from dynamic model storage (active) estimates from runoff models has the potential to provide multi-proxy tools to investigate the concept of catchment storage in an integrated way. In this paper we explore the storage-discharge relationships of two nested (3.6 and 30 km2) montane catchments in Scotland using rainfall-runoff models: (a) a non-linear discharge sensitivity function and (b) a process-based conceptual model constrained by high resolution (daily), long-term (3 year) isotope time series. Both modelling approaches consistently simulated small seasonal storage fluctuations (ca. 40-50mm) in both catchments: consistent with the wet, cool climate. In contrast, input-output relationships of oxygen-18 tracer time series
Kumar, Ramesh; Pal, Parimal
2013-08-01
Modeling and simulation was carried out for an advanced membrane-integrated hybrid treatment process that ensures reuse of water with conversion and recovery of ammoniacal nitrogen as value-added struvite fertilizer from coke wastewater. While toxic cyanide was largely removed in a pre-chemical treatment unit using Fenton's reagents under optimized conditions, more than 95% of NH4(+)-N could be recovered as a valuable by-product called struvite through addition of appropriate doses of magnesium and phosphate salts. Water could be turned reusable through a polishing treatment by nanofiltration membranes in a largely fouling free membrane module following a biodegradation step. Mathematical modeling of such an integrated process was done with Haldane-Andrew approach for the associated microbial degradation of phenol by Pseudomonas putida. Residual NH4(+) was degraded by nitrification and denitrification following the modified Monod kinetics. The model could successfully predict the plant performance as reflected in reasonably low relative error (0.03-0.18) and high Willmott d-index (>0.98). PMID:23735488
Filho, Edson; Tenenbaum, Gershon; Yang, Yanyun
2015-01-01
A nomological network on team dynamics in sports consisting of a multiframework perspective is introduced and tested. The aim was to explore the interrelationship among cohesion, team mental models (TMMs), collective efficacy (CE) and perceived performance potential (PPP). Three hundred and forty college-aged soccer players representing 17 different teams (8 female and 9 male) participated in the study. They responded to surveys on team cohesion, TMMs, CE and PPP. Results are congruent with the theoretical conceptualisation of a parsimonious view of team dynamics in sports. Specifically, cohesion was found to be an exogenous variable predicting both TMMs and CE beliefs. TMMs and CE were correlated and predicted PPP, which in turn accounted for 59% of the variance of objective performance scores as measured by teams' season record. From a theoretical standpoint, findings resulted in a parsimonious view of team dynamics, which may represent an initial step towards clarifying the epistemological roots and nomological network of various team-level properties. From an applied standpoint, results suggest that team expertise starts with the establishment of team cohesion. Following the establishment of cohesiveness, teammates are able to advance team-related schemas and a collective sense of confidence. Limitations and key directions for future research are outlined. PMID:25385557
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.
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
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
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
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
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." PMID:25462871
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)
Roach, J.; Tidwell, V.; Lansey, K.
2004-12-01
As the finite, and often over-allocated water resources of the western United States are challenged by a myriad of growing demands, computer based simulations can be a powerful tool for evaluation of potential water use scenarios for hydrologic decision making and water policy analysis. To maximize their usefulness for policy analysis, such simulations should accurately represent the physical system as well as its interconnectedness to the socio-economic systems relevant to water planning without losing user accessibility or run speed. One solution to these constraints is system dynamics (SD) modeling at a relatively coarse spatial and temporal resolution. The challenge of this approach is in maintaining sufficient physical accuracy despite coarse resolution and SD's simple modeling framework. In this paper, the development of a reach-based monthly time-step system dynamics model of the upper Rio Grande River (from the headwaters in Colorado to Elephant Butte Reservoir in New Mexico) is discussed. Within this SD model, temporally and spatially coarse physical and operational relationships are abstracted from a variety of existing models with higher resolutions, including an operations model (Upper Rio Grande Water Operations Model (URGWOM)), a land surface rainfall-runoff model, an evapotranspiration model, and two groundwater models. Abstraction and calibration methods and implications of information loss associated with this scaling are considered.
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.
Integrated modeling for the VLTI
NASA Astrophysics Data System (ADS)
Mueller, Michael; Wilhelm, Rainer; Baier, Horst; Koehler, Bertrand
2003-02-01
Within the scope of the Very Large Telescope Interferometer (VLTI) project, a set of software tools for integrated modeling of ground- and space-based stellar interferometers has been developed. Integrated modeling aims at time-dependent system analysis combining different technical disciplines (optics, mechanical structure, control system with sensors and actuators, environmental disturbances). The main components of the software are BeamWarrior, a tool for creation of dynamic optical models, and SMI (Structural Modeling Interface), which generates linear state-space models from finite element models of a mechanical structure. Based on these tools, models of the various subsystems (e.g. telescope, delay line, beam combiner) can be created in the relevant technical disciplines (e.g. optics, structure). All subsystem models are integrated into the Matlab/Simulink environment for dynamic control system simulations. The output of the dynamic model is a complete description of the time-dependent electromagnetic field in each interferometer arm. This output serves as input to an instrument model simulating the creation of interference fringes. This paper shows the application of the integrated modeling concept to the VLTI. The architecture of a Simulink-based integrated model with its main components, telescope structures, optics and control loops, is presented. Disturbance models for wind load, seismic ground excitation and atmospheric turbulence are included. Beam combination is performed using a simplified model of the VINCI instrument. Results of closed-loop dynamic simulations are presented.
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)
Tang, H. S.; Qu, K.; Wu, X. G.
2014-09-01
It is now becoming important to develop our capabilities to simulate coastal ocean flows involved with distinct physical phenomena occurring at a vast range of spatial and temporal scales. This paper presents a hybrid modeling system for such simulation. The system consists of a fully three dimensional (3D) fluid dynamics model and a geophysical fluid dynamics model, which couple with each other in two-way and march in time simultaneously. Particularly, in the hybrid system, the solver for incompressible flow on overset meshes (SIFOM) resolves fully 3D small-scale local flow phenomena, while the unstructured grid finite volume coastal ocean model (FVCOM) captures large-scale background flows. The integration of the two models are realized via domain decomposition implemented with an overset grid method. Numerical experiments on performance of the system in resolving flow patterns and solution convergence rate show that the SIFOM-FVCOM system works as intended, and its solutions compare reasonably with data obtained with measurements and other computational approaches. Its unparalleled capabilities to predict multiphysics and multiscale phenomena with high-fidelity are demonstrated by three typical applications that are beyond the reach of other currently existing models. It is anticipated that the SIFOM-FVCOM system will serve as a new platform to study many emerging coastal ocean problems.
NASA Astrophysics Data System (ADS)
Bogolubov, N. N.; Prykarpatsky, Y. A.
2013-03-01
An approach to describing nonlinear Lax type integrable dynamical systems of modern mathematical and theoretical physics, based on the Marsden-Weinstein reduction method on canonically symplectic manifolds with group symmetry, is proposed. Its natural relationship with the well-known Adler-Kostant-Souriau-Berezin-Kirillov method and the associated R-matrix approach is analyzed. A new generalized exactly solvable spatially one-dimensional quantum superradiance model, describing a charged fermionic medium interacting with external electromagnetic field, is suggested. The Lax type operator spectral problem is presented, the related R-structure is calculated. The Hamilton operator renormalization procedure subject to a physically stable vacuum is described, the quantum excitations and quantum solitons, related with the thermodynamical equilibrity of the model, are discussed.
NASA Astrophysics Data System (ADS)
Zhang, Hui; Liu, Xiangnan; Cai, Erli; Huang, Gang; Ding, Chao
2013-07-01
The objective of this study was to apply an improved Group Method of Data Handling (GMDH) network model for prediction of debris flow by integrating dynamic rainfall data and environmental factors. The rainfall data were collected from weather information, and the environmental data were extracted from RS, GIS, drilling data, and geophysical data. The input variables used in the SAGA-GMDH model were derived from six variables acquired by Kernel Linear Discriminant Analysis (KLDA). The results showed that the GMDH for prediction of debris flow performed well using the training, validation, and testing sets (R2 above 0.80 and ARE below 3.54%). The SAGA-GMDH model was subsequently compared with a back-propagation (BP) neural network model and adaptive network fuzzy interference system (ANFIS). The accuracies of the SAGA-GMDH model prediction were slightly better than those of other two models, which demonstrated that the SAGA-GMDH model was more suitable for prediction of debris flow.
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
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...
Optical systems integrated modeling
NASA Technical Reports Server (NTRS)
Shannon, Robert R.; Laskin, Robert A.; Brewer, SI; Burrows, Chris; Epps, Harlan; Illingworth, Garth; Korsch, Dietrich; Levine, B. Martin; Mahajan, Vini; Rimmer, Chuck
1992-01-01
An integrated modeling capability that provides the tools by which entire optical systems and instruments can be simulated and optimized is a key technology development, applicable to all mission classes, especially astrophysics. Many of the future missions require optical systems that are physically much larger than anything flown before and yet must retain the characteristic sub-micron diffraction limited wavefront accuracy of their smaller precursors. It is no longer feasible to follow the path of 'cut and test' development; the sheer scale of these systems precludes many of the older techniques that rely upon ground evaluation of full size engineering units. The ability to accurately model (by computer) and optimize the entire flight system's integrated structural, thermal, and dynamic characteristics is essential. Two distinct integrated modeling capabilities are required. These are an initial design capability and a detailed design and optimization system. The content of an initial design package is shown. It would be a modular, workstation based code which allows preliminary integrated system analysis and trade studies to be carried out quickly by a single engineer or a small design team. A simple concept for a detailed design and optimization system is shown. This is a linkage of interface architecture that allows efficient interchange of information between existing large specialized optical, control, thermal, and structural design codes. The computing environment would be a network of large mainframe machines and its users would be project level design teams. More advanced concepts for detailed design systems would support interaction between modules and automated optimization of the entire system. Technology assessment and development plans for integrated package for initial design, interface development for detailed optimization, validation, and modeling research are presented.
NASA Astrophysics Data System (ADS)
Bagulho Galvão, P.; Neves, R.; Silva, A.; Chambel Leitão, P.; Braunchweig, F.
2004-05-01
Integrated systems that bring together EO data, local measurements and modeling tools, are a fundamental instrument to help decision making in watershed and land use management. The BASINS system (EPA http://www.epa.gov/OST/BASINS/) follows this philosophy, merging data from local measurement with modeling tools (HSPF, SWAT, PLOAD, QUAL2E). However, remote sensed data is still used in a very static way (usually to define land cover, see corine land cover project). This approach is being replaced with operational methods that use EO data (such as land surface temperature, vegetation state, soil moisture, surface roughness) for both inputs and validation. The development of integrated watershed models that dynamically interact with remote sensed data opens interesting prospective to the validation and improvement of such models. This paper describes the possible data contribution of remote sensing to the needs associated with state of the art watershed models, including well know systems (such as SWAT or HSPF) and a system still under development (MOHID LAND). Application of such models is shown at two pilot sites, which were selected under EU projects, TempQsim and Interreg II B - ICRW.
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.
Integrated modeling and dynamics simulation for the TMT-M3 control system
NASA Astrophysics Data System (ADS)
Deng, Yong-ting; Li, Hong-wen; Yang, Fei; Wang, Jian-li; Su, Yan-qin; Zhao, Hong-chao
2014-09-01
In order to analyze the tracking performance and design the controllers for TMT-M3 control system in the design stage. This paper presents the development of the analytical model of the gear driven large telescope using the lumped mass modeling method. The analytical model includes the telescope structure, its drives, the velocity loop and position loop. First, the modal model of a flexible structure is analyzed based on the finite-element data. And the modal model is transferred into the state-space model, in continuous-time. Next, the drive model is derived, and combined into the velocity loop and position loop. Finally, the impact of the error sources on the control loop properties is simulated. According to the simulation accuracy of the analytical modeling, the analytical model can be used in implementation, such as the model-based controllers.
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.
NASA Astrophysics Data System (ADS)
Nikolov, S.; Lai, X.; Liebal, U. W.; Wolkenhauer, O.; Vera, J.
2010-01-01
In this article we present and test a strategy to integrate, in a sequential manner, sensitivity analysis, bifurcation analysis and predictive simulations. Our strategy uses some of these methods in a coordinated way such that information, generated in one step, feeds into the definition of further analyses and helps refining the structure of the mathematical model. The aim of the method is to help in the designing of more informative predictive simulations, which focus on critical model parameters and the biological effects of their modulation. We tested our methodology with a multilevel model, accounting for the effect of erythropoietin (Epo)-mediated JAK2-STAT5 signalling in erythropoiesis. Our analysis revealed that time-delays associated with the proliferation-differentiation process are critical to induce pathological sustained oscillations, whereas the modulation of time-delays related to intracellular signalling and hypoxia-controlled physiological dynamics is not enough to induce self-oscillations in the system. Furthermore, our results suggest that the system is able to compensate (through the physiological-level feedback loop on hypoxia) the partial impairment of intracellular signalling processes (downregulation or overexpression of Epo receptor complex and STAT5), but cannot control impairment in some critical physiological-level processes, which provoke the emergence of pathological oscillations.
INTEGRATED PLANNING MODEL - EPA APPLICATIONS
The Integrated Planning Model (IPM) is a multi-regional, dynamic, deterministic linear programming (LP) model of the electric power sector in the continental lower 48 states and the District of Columbia. It provides forecasts up to year 2050 of least-cost capacity expansion, elec...
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)
Yang, Xiaojuan; Wittig, Victoria; Jain, Atul K.; Post, Wilfred
2009-12-01
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 organic N storage are in tundra (1.24 Kg N m-2) and desert soil (0.06 Kg N m-2). The vegetation N storage is highest in tropical forests (0.5 Kg N m-2), and lowest in tundra and desert (<0.03 Kg N m-2). 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
NASA Astrophysics Data System (ADS)
Masek, J.; Morton, D. C.; Mcmanus, K. M.; Wang, D.; Nagol, J. R.; Poulter, B.; Boudreau, S.; Ropars, P.
2011-12-01
Dynamic Global Vegetation Models (DGVMs) generally predict poleward migration of temperate and boreal vegetation biomes in response to climate warming. Some models anticipate rapid migration of these biomes during the 21st century, suggesting that local vegetation shifts should already be observable in the satellite record. We have examined trends in high-latitude North American vegetation using long-term data records from Landsat and MODIS and model results from the Lund-Potsdam-Jena (LPJ) DGVM under a range of climate scenarios. Specifically, we have focused on NDVI trends observed from both Landsat and MODIS, as well as spectral changes in the Landsat record that could be related to compositional change. Unlike past studies that relied on integrated measures of growing season NDVI, we focused on "peak summer" trends, which are more closely related to the amount (e.g., leaf area index) and composition of vegetation, rather than variability in vegetation phenology. Analysis of a 25-year Landsat TM/ETM+ record for northern Quebec revealed widespread increases in mid-summer LAI in shrub tundra cover types since the 1980's. These increases are consistent with trends in Aqua MODIS NDVI for the most recent decade, field observations of increasing shrub cover in the region, and previous studies using AVHRR data (e.g. Pouliot et al., 2009, Int. J. Remote Sens). Continental analysis of MODIS data can place these trends in a wider context more suitable for comparisons with DGVM simulations. Across North America, we compared greening and browning trends in mid-summer Aqua MODIS NDVI to climate data records and LPJ model results. The satellite data record indicated a more complex vegetation response to climate warming across North America than model results, with both the magnitude and seasonal timing of warming playing a role. The remote sensing results will be discussed in the context of improving projections of future climate-driven biome shifts.
Integrated Assessment Model Evaluation
NASA Astrophysics Data System (ADS)
Smith, S. J.; Clarke, L.; Edmonds, J. A.; Weyant, J. P.
2012-12-01
Integrated assessment models of climate change (IAMs) are widely used to provide insights into the dynamics of the coupled human and socio-economic system, including emission mitigation analysis and the generation of future emission scenarios. Similar to the climate modeling community, the integrated assessment community has a two decade history of model inter-comparison, which has served as one of the primary venues for model evaluation and confirmation. While analysis of historical trends in the socio-economic system has long played a key role in diagnostics of future scenarios from IAMs, formal hindcast experiments are just now being contemplated as evaluation exercises. Some initial thoughts on setting up such IAM evaluation experiments are discussed. Socio-economic systems do not follow strict physical laws, which means that evaluation needs to take place in a context, unlike that of physical system models, in which there are few fixed, unchanging relationships. Of course strict validation of even earth system models is not possible (Oreskes etal 2004), a fact borne out by the inability of models to constrain the climate sensitivity. Energy-system models have also been grappling with some of the same questions over the last quarter century. For example, one of "the many questions in the energy field that are waiting for answers in the next 20 years" identified by Hans Landsberg in 1985 was "Will the price of oil resume its upward movement?" Of course we are still asking this question today. While, arguably, even fewer constraints apply to socio-economic systems, numerous historical trends and patterns have been identified, although often only in broad terms, that are used to guide the development of model components, parameter ranges, and scenario assumptions. IAM evaluation exercises are expected to provide useful information for interpreting model results and improving model behavior. A key step is the recognition of model boundaries, that is, what is inside
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
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., Jr.
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.
NASA Astrophysics Data System (ADS)
Rowan, Timothy S. C.; Maier, Holger R.; Connor, Jeff; Dandy, Graeme C.
2011-07-01
Many hydrologic systems are likely to be affected by climate change. This is of particular importance given that agricultural production systems are inextricably linked to the hydrologic systems they rely upon. Although irrigation is often employed as a method to dampen the effect of short-term variation in climatic inputs to agricultural production, sources of irrigation water are not immune to long-term climatic change. Irrigation water use decisions are most often made at the farm level. It is at this scale that the economic and social impacts of climate change will be manifest. This paper presents an integrated stochastic dynamic modeling framework that can be used to investigate the viability of irrigated farms under alternative climate change scenarios. The framework is applied to a theoretical farm in the Murray Darling Basin, Australia, under four potential future climate scenarios. It is found that neglecting interannual variability in climatic inputs to agriculture consistently underestimates the reduction in farm viability caused by climate change and that multiyear sequences of climate states strongly influence estimates of farm profitability.
Direct integration of transient rotor dynamics
NASA Technical Reports Server (NTRS)
Kascak, A. F.
1980-01-01
An implicit method was developed for integrating the equations of motion for a lumped mass model of a rotor dynamics system. As an aside, a closed form solution to the short bearing theory was also developed for a damper with arbitrary motion. The major conclusions are that the method is numerically stable and that the computation time is proportional to the number of elements in the rotor dynamics model rather than to the cube of the number. This computer code allowed the simulation of a complex rotor bearing system experiencing nonlinear transient motion and displayed the vast amount of results in an easily understood motion picture format - a 10 minute, 16 millimeter, color, sound motion picture supplement. An example problem with 19 mass elements in the rotor dynamics model took 0.7 second of central processing unit time per time step on an IBM 360-67 computer in a time sharing mode.
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
NASA Technical Reports Server (NTRS)
Merkowitz, Stephen M.
2002-01-01
The Laser Interferometer Space Antenna (LISA) space mission has unique needs that argue for an aggressive modeling effort. These models ultimately need to forecast and interrelate the behavior of the science input, structure, optics, control systems, and many other factors that affect the performance of the flight hardware. In addition, many components of these integrated models will also be used separately for the evaluation and investigation of design choices, technology development and integration and test. This article presents an overview of the LISA integrated modeling effort.
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.
Human action recognition using integrated model
NASA Astrophysics Data System (ADS)
Yi, Yang; Lin, Yikun
2013-07-01
A novel action recognition framework based on integrated model is proposed in the paper. First, the covariance descriptor is utilized to extract features from video sequences, and then each class specific codebook is constructed and appended to the global codebook. A static model applying the template matching technique and a dynamic model employing the trigram model are learned to capture complementary information in an action. And lastly, an integrated model is used to estimate the confidence of the static and dynamic models and produces a reliable result. Comparative experiments show that our presented method achieves superior results over other state-of-the-art approaches. Keywords: human action recognition, covariance descriptor, integrated model
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
NASA Astrophysics Data System (ADS)
Cosme, Jayson G.
2015-09-01
We numerically investigate the relaxation dynamics in an isolated quantum system of interacting bosons trapped in a double-well potential after an integrability breaking quench. Using the statistics of the spectrum, we identify the postquench Hamiltonian as nonchaotic and close to integrability over a wide range of interaction parameters. We demonstrate that the system exhibits thermalization in the context of the eigenstate thermalization hypothesis (ETH). We also explore the possibility of an initial state to delocalize with respect to the eigenstates of the postquench Hamiltonian even for energies away from the middle of the spectrum. We observe distinct regimes of equilibration process depending on the initial energy. For low energies, the system rapidly relaxes in a single step to a thermal state. As the energy increases towards the middle of the spectrum, the relaxation dynamics exhibits prethermalization and the lifetime of the metastable states grows. Time evolution of the occupation numbers and the von Neumann entropy in the mode-partitioned system underpins the analyses of the relaxation dynamics.
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. PMID:22565258
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.
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
Integrated modeling for the VLTI
NASA Astrophysics Data System (ADS)
Muller, Michael; Wilhelm, Rainer C.; Baier, Horst J.; Koch, Franz
2004-07-01
Within the scope of the Very Large Telescope Interferometer (VLTI) project, ESO has developed a software package for integrated modeling of single- and multi-aperture optical telescopes. Integrated modeling is aiming at time-dependent system analysis combining different technical disciplines (optics, mechanical structure, control system with sensors and actuators, environmental disturbances). This allows multi-disciplinary analysis and gives information about cross-coupling effects for system engineering of complex stellar interferometers and telescopes. At the moment the main components of the Integrated Modeling Toolbox are BeamWarrior, a numerical tool for optical analysis of single- and multi-aperture telescopes, and the Structural Modeling Interface, which allows to generate Simulink blocks with reduced size from Finite Element Models of a telescope structure. Based on these tools, models of the various subsystems (e.g. telescope, delay line, beam combiner, atmosphere) can be created in the appropriate disciplines (e.g. optics, structure, disturbance). All subsystem models are integrated into the Matlab/Simulink environment for dynamic control system simulations. The basic output of the model is a complete description of the time-dependent electromagnetic field in each interferometer arm. Alternatively, a more elaborated output can be created, such as an interference fringe pattern at the focus of a beam combining instrument. The concern of this paper is the application of the modeling concept to large complex telescope systems. The concept of the Simulink-based integrated model with the main components telescope structure, optics and control loops is presented. The models for wind loads and atmospheric turbulence are explained. Especially the extension of the modeling approach to a 50 - 100 m class telescope is discussed.
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)
Wania, R.; Ross, I.; Prentice, I. C.
2009-09-01
Northern peatlands and permafrost soils are associated with large carbon stocks. Rising temperatures are likely to affect the carbon balance in high-latitude ecosystems, but to what degree is uncertain. We have enhanced the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model by introducing processes necessary to simulate permafrost dynamics, peatland hydrology, and peatland vegetation. The new version, LPJ-WHy v1.2, was used to study soil temperature, active layer depth, permafrost distribution, and water table position. Modeled soil temperatures agreed well with observations, apart from a Siberian site where the soil is insulated by an extensive shrub layer. Water table positions were generally in the range of observations, with some exceptions. Simulated active layer depth showed a mean absolute error of 44 cm when compared to observations, but the error was reduced to 25 cm when the soil type for seven sites was manually corrected to mirror local conditions. A sensitivity test, in which temperature and precipitation were varied independently, showed that soil temperatures and active layer depths increased more under higher temperatures when precipitation was increased at the same time. The sensitivity experiment suggested persisting wet conditions in peatlands even under temperature increases of up to 9°C as long as annual precipitation is allowed to increase with temperature to the extent indicated by climate model experiments.
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.
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.
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 Astrophysics Data System (ADS)
Mohammed, I. N.; Tarboton, D. G.
2005-12-01
The Great Salt Lake (GSL), Utah, is the fourth largest, perennial, terminal lake in the world. The Great Salt Lake (GSL) level fluctuates due to the balance between inflows and outflows. These fluctuations are of interest whether they are high (flooding hazards) or low (economic impacts). Inflows are due to streamflow, primarily from the Bear River (54%), Weber River (18%) and Jordan/Provo River (28%) systems. Inflows also include precipitation directly on the lake and groundwater both from the East and West sides. The only outflow is evaporation that is controlled by the climate and area of the lake that changes with level. The GSL reached historic high levels above 1284 m in 1873 and 1986. A historic low at 1278 m occurred in 1963. These fluctuations represent the integrated effect of climate and hydrologic processes as well as the dynamic interaction between lake volume, area and salinity that impact evaporation from the lake. The topographic area-volume relationship in the GSL plays a role in the system dynamics because area is a control on the evaporation outflux. This paper examines the relationships between Basin climate (precipitation and temperature), Inflows to the lake (primarily streamflow) and outflows (evaporation). The role played by the topographic elevation-area-volume relationship on lake dynamics and the correspondence between modes in volume and area distributions and peaks in the area-volume derivative was examined. We derived, using a steady state approximation, the relationship between distributions of lake volume and lake area and the area-volume derivative from the topography/bathymetry. This analysis showed that both the topography/bathymetry and multimodality in the area distribution are required to explain the observed multimodality in the volume distribution. We also separated lake volume changes into increases in the spring (due to spring runoff) and declines in the fall (due to evaporation) and then related these volume changes to
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. PMID:25685841
NASA Astrophysics Data System (ADS)
Wattenbach, M.; Franz, D.; Liang, W.; Schmidt, M.; Seitz, F.; Güntner, A.
2012-04-01
The vegetation cover has a profound effect on the long term and seasonal dynamics of all components of the water cycle in river catchments globally. In order to understand the effect Global Change has on the Earth system, it is essential to entangle the effects of changes in land cover and land use, biogeochemical cycles, climate and weather driven shifts in phenology and human water consumption. The WaterGAP Global Hydrology Model (WGHM) is one of the few global hydrological models, which integrates total water storage simulation with an estimation of anthropogenic water consumption from streams, surface water bodies as well as groundwater. The vegetation part in the actual version of the model is, however, a rather simplified parameterization. This simplification leads to a limited temperature and climatic water balance driven representation of phenology with a static land cover mask and no land use. These model assumptions limit its ability to reflect the above mentioned dynamic in time and space. In order to understand and quantify the effect of the current implementation, we substituted it with the MODIS LAI product. Running the model with daily European Centre for Medium-Range Weather Forecasts (ECMWF) temperature and Global Precipitation Climatology Centre (GPCC) precipitation data from 1997 to 2010, we analysed the effect on all components of the water cycle. The results show a clear effect on the long term and seasonal dynamics of the water balance with a pronounced spatial and temporal pattern. The primary effect is a change in evapotranspiration driven by the change in the simulated canopy storage which propagates through the water cycle affecting all subsequent fluxes like runoff, soil water storage and groundwater dynamics. The simplified phenology in the model leads to phase mismatch in the LAI development, which results in a periodicity in the divergence between model and MODIS observations. We conclude that a more realistic implementation of
NASA Astrophysics Data System (ADS)
Wattenbach, M.; Gunter, A.; Liang, W.; Schmidt, M. G.; Seitz, F.
2012-12-01
The vegetation cover has a profound effect on the long term and seasonal dynamics of all components of the water cycle in river catchments globally. In order to understand the effect Global Change has on the Earth system, it is essential to entangle the effects of changes in land cover and land use, biogeochemical cycles, climate and weather driven shifts in phenology and human water consumption. The WaterGAP Global Hydrology Model (WGHM) is one of the few global hydrological models, which integrates total water storage simulation with an estimation of anthropogenic water consumption from streams, surface water bodies as well as groundwater. The vegetation part in the actual version of the model is, however, a rather simplified parameterization. This simplification leads to a limited temperature and climatic water balance driven representation of phenology with a static land cover mask and no land use. These model assumptions limit its ability to reflect the above mentioned dynamic in time and space. In order to understand and quantify the effect of the current implementation, we substituted it with the MODIS LAI product. Running the model with daily European Centre for Medium-Range Weather Forecasts (ECMWF) temperature and Global Precipitation Climatology Centre (GPCC) precipitation data from 1997 to 2010, we analysed the effect on all components of the water cycle. The results show a clear effect on the long term and seasonal dynamics of the water balance with a pronounced spatial and temporal pattern. The primary effect is a change in evapotranspiration driven by the change in the simulated canopy storage which propagates through the water cycle affecting all subsequent fluxes like runoff, soil water storage and groundwater dynamics. The simplified phenology in the model leads to phase mismatch in the LAI development, which results in a periodicity in the divergence between model and MODIS observations. We conclude that a more realistic implementation of
Dynamic network mechanisms of relational integration.
Parkin, Beth L; Hellyer, Peter J; Leech, Robert; Hampshire, Adam
2015-05-20
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
Integrable models and combinatorics
NASA Astrophysics Data System (ADS)
Bogolyubov, N. M.; Malyshev, C. L.
2015-10-01
Relations between quantum integrable models solvable by the quantum inverse scattering method and some aspects of enumerative combinatorics and partition theory are discussed. The main example is the Heisenberg XXZ spin chain in the limit cases of zero or infinite anisotropy. Form factors and some thermal correlation functions are calculated, and it is shown that the resulting form factors in a special q-parametrization are the generating functions for plane partitions and self-avoiding lattice paths. The asymptotic behaviour of the correlation functions is studied in the case of a large number of sites and a moderately large number of spin excitations. For sufficiently low temperature a relation is established between the correlation functions and the theory of matrix integrals. Bibliography: 125 titles.
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…
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
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
Quench dynamics and relaxation in isolated integrable quantum spin chains
NASA Astrophysics Data System (ADS)
Essler, Fabian H. L.; Fagotti, Maurizio
2016-06-01
We review the dynamics after quantum quenches in integrable quantum spin chains. We give a pedagogical introduction to relaxation in isolated quantum systems, and discuss the description of the steady state by (generalized) Gibbs ensembles. We then turn to general features in the time evolution of local observables after the quench, using a simple model of free fermions as an example. In the second part we present an overview of recent progress in describing quench dynamics in two key paradigms for quantum integrable models, the transverse field Ising chain and the anisotropic spin-1/2 Heisenberg chain.
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.
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)
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
NASA Astrophysics Data System (ADS)
Lu, X.; Zhuang, Q.
2015-12-01
Quantitative understanding of the variation in dissolved organic carbon (DOC) is important to studying the terrestrial ecosystem carbon cycle. This study presents a process-based, dissolved organic carbon dynamics model (DOCDM 1.0) that couples the soil heat conduction, water flow, DOC production, mineralization and transport in both surface and subsurface of soil profile to quantify DOC dynamics in boreal terrestrial ecosystems. The model is first evaluated and then applied for a watershed in Alaska to investigate its DOC production and transport. We find that 42 and 27 % of precipitation infiltrates to soils in 2004, a warmer year, and in 1976, a colder year, respectively. Under warming conditions, DOC transported via overland flow does not show the expected decrease trend while the overland DOC yield shows a 4 % increase. The horizontal subsurface flow only accounts for 1-2 % of total water flux, but transports 30-50 % of DOC into rivers. Water flush due to water infiltration controls DOC transport. Snowmelt plays a noticeable role in DOC flush-out and DOC transport significantly depends on flowpaths in the study region. High soil temperature stimulates DOC production. The overland DOC export does not necessarily follow the DOC downward trend in surface water transport. Overall, this study shows that DOC export behavior is complex under changing temperature and hydrological conditions in cold-region watersheds. To adequately quantify DOC dynamics in northern high latitudes, more DOC and hydrological data are needed to better parameterize and test the developed model before extrapolating it to the region.
NASA Astrophysics Data System (ADS)
Miyata, Tatsuhiko; Ikuta, Yasuhiro; Hirata, Fumio
2010-07-01
This article proposes a free energy calculation method based on the molecular dynamics simulation combined with the three dimensional reference interaction site model theory. This study employs the free energy perturbation (FEP) and the thermodynamic integration (TDI) along the coupling parameters to control the interaction potential. To illustrate the method, we applied it to a complex formation process in aqueous solutions between a crown ether molecule 18-Crown-6 (18C6) and a potassium ion as one of the simplest model systems. Two coupling parameters were introduced to switch the Lennard-Jones potential and the Coulomb potential separately. We tested two coupling procedures: one is a "sequential-coupling" to couple the Lennard-Jones interaction followed by the Coulomb coupling, and the other is a "mixed-coupling" to couple both the Lennard-Jones and the Coulomb interactions together as much as possible. The sequential-coupling both for FEP and TDI turned out to be accurate and easily handled since it was numerically well-behaved. Furthermore, it was found that the sequential-coupling had relatively small statistical errors. TDI along the mixed-coupling integral path was to be carried out carefully, paying attention to a numerical behavior of the integrand. The present model system exhibited a nonmonotonic behavior in the integrands for TDI along the mixed-coupling integral path and also showed a relatively large statistical error. A coincidence within a statistical error was obtained among the results of the free energy differences evaluated by FEP, TDI with the sequential-coupling, and TDI with the mixed-coupling. The last one is most attractive in terms of the computer power and is accurate enough if one uses a proper set of windows, taking the numerical behavior of the integrands into account. TDI along the sequential-coupling integral path would be the most convenient among the methods we tested, since it seemed to be well-balanced between the computational
Fang, Jiansong; Pang, Xiaocong; Wu, Ping; Yan, Rong; Gao, Li; Li, Chao; Lian, Wenwen; Wang, Qi; Liu, Ai-Lin; Du, Guan-Hua
2016-05-01
A dataset of 67 berberine derivatives for the inhibition of butyrylcholinesterase (BuChE) was studied based on the combination of quantitative structure-activity relationships models, molecular docking, and molecular dynamics methods. First, a series of berberine derivatives were reported, and their inhibitory activities toward butyrylcholinesterase (BuChE) were evaluated. By 2D- quantitative structure-activity relationships studies, the best model built by partial least-square had a conventional correlation coefficient of the training set (R(2) ) of 0.883, a cross-validation correlation coefficient (Qcv2) of 0.777, and a conventional correlation coefficient of the test set (Rpred2) of 0.775. The model was also confirmed by Y-randomization examination. In addition, the molecular docking and molecular dynamics simulation were performed to better elucidate the inhibitory mechanism of three typical berberine derivatives (berberine, C2, and C55) toward BuChE. The predicted binding free energy results were consistent with the experimental data and showed that the van der Waals energy term (ΔEvdw ) difference played the most important role in differentiating the activity among the three inhibitors (berberine, C2, and C55). The developed quantitative structure-activity relationships models provide details on the fine relationship linking structure and activity and offer clues for structural modifications, and the molecular simulation helps to understand the inhibitory mechanism of the three typical inhibitors. In conclusion, the results of this study provide useful clues for new drug design and discovery of BuChE inhibitors from berberine derivatives. PMID:26648584
Dai, Erfu; Wu, Shaohong; Shi, Wenzhong; Cheung, Chui-Kwan; Shaker, Ahmed
2005-10-01
The use of spatial methods to detect and characterize changes in land use has been attracting increasing attention from researchers. The objectives of this article were to formulate the dynamics of land use on the temporal and spatial dimensions from the perspectives of the Change-Pattern-Value (CPV) and driving mechanism, based on multitemporal remote sensing data and socioeconomic data. The Artificial Neural Networks were used to identify the factors driving changes in land use. The Pearl River Delta Region of southeast China, which was experiencing rapid economic growth and widespread land conversion, has been selected as the study region. The results show that from 1985 to 2000 in the study region (1) the most prominent characteristics of change in land use were the expansion of the urban land at the expense of farmland, forests, and grasslands, (2) the land-use pattern was being optimized during this period, (3) in an analysis of value, built-up land can yield a return of more than 30 times that of farmland, water area, and forests lands, and (4) rapid economic development, growth in population, and the development of an infrastructure were major driving factors behind ecological land loss and the nonecological land expansion. PMID:16222462
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 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.
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.
Dynamic Triggering Stress Modeling
NASA Astrophysics Data System (ADS)
Gonzalez-Huizar, H.; Velasco, A. A.
2008-12-01
It has been well established that static (permanent) stress changes can trigger nearby earthquakes, within a few fault lengths from the causative event, whereas triggering by dynamic (transient) stresses carried by seismic waves both nearby and at remote distances has not been as well documented nor understood. An analysis of the change in the local stress caused by the passing of surfaces waves is important for the understanding of this phenomenon. In this study, we modeled the change in the stress that the passing of Rayleigh and Loves waves causes on a fault plane of arbitrary orientation, and applied a Coulomb failure criteria to calculate the potential of these stress changes to trigger reverse, normal or strike-slip failure. We preliminarily test these model results with data from dynamically triggering earthquakes in the Australian Bowen Basin. In the Bowen region, the modeling predicts a maximum triggering potential for Rayleigh waves arriving perpendicularly to the strike of the reverse faults present in the region. The modeled potentials agree with our observations, and give us an understanding of the dynamic stress orientation needed to trigger different type of earthquakes.
Efficient time integration in dislocation dynamics
NASA Astrophysics Data System (ADS)
Sills, Ryan B.; Cai, Wei
2014-03-01
The efficiencies of one implicit and three explicit time integrators have been compared in line dislocation dynamics simulations using two test cases: a collapsing loop and a Frank-Read (FR) source with a jog. The time-step size and computational efficiency of the explicit integrators is shown to become severely limited due to the presence of so-called stiff modes, which include the oscillatory zig-zag motion of discretization nodes and orientation fluctuations of the jog. In the stability-limited regime dictated by these stiff modes, the implicit integrator shows superior efficiency when using a Jacobian that only accounts for short-range interactions due to elasticity and line tension. However, when a stable dislocation dipole forms during a jogged FR source simulation, even the implicit integrator suffers a substantial drop in the time-step size. To restore computational efficiency, a time-step subcycling algorithm is tested, in which the nodes involved in the dipole are integrated over multiple smaller, local time steps, while the remaining nodes take a single larger, global time step. The time-step subcycling method leads to substantial efficiency gain when combined with either an implicit or an explicit integrator.
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.
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
NASA Astrophysics Data System (ADS)
Gardner, D. J.; Woodward, C. S.; Reynolds, D. R.; Hommes, G.; Aubry, S.; Arsenlis, A.
2015-03-01
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. 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)
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.
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.
Integrability of the Rabi Model
Braak, D.
2011-09-02
The Rabi model is a paradigm for interacting quantum systems. It couples a bosonic mode to the smallest possible quantum model, a two-level system. I present the analytical solution which allows us to consider the question of integrability for quantum systems that do not possess a classical limit. A criterion for quantum integrability is proposed which shows that the Rabi model is integrable due to the presence of a discrete symmetry. Moreover, I introduce a generalization with no symmetries; the generalized Rabi model is the first example of a nonintegrable but exactly solvable system.
NASA Astrophysics Data System (ADS)
Ge, Jianzhong; Ding, Pingxing; Chen, Changsheng; Hu, Song; Fu, Gui; Wu, Lunyu
2013-08-01
A high-resolution numerical model system is essential to resolve multi-scale coastal ocean dynamics. So a multi-scale unstructured grid-based finite-volume coastal ocean model (FVCOM) system has been established for the East China Sea and Changjiang Estuary (ECS-CE) with the aim at resolving coastal ocean dynamics and understanding different physical processes. The modeling system consists of a three-domain-nested weather research and forecasting model, FVCOM model with the inclusion of FVCOM surface wave model in order to understand the wave-current interactions. The ECS-CE system contains three different scale models: a shelf-scale model for the East China Sea, an estuarine-scale model for the Changjiang Estuary and adjacent region, and a fine-scale model for the deep waterway regions. These three FVCOM-based models guarantee the conservation of mass and momentum transferring from outer domain to inner domain using the one-way common-grid nesting procedure. The model system has been validated using data from various observation data, including surface wind, tides, currents, salinity, and wave to accurately reveal the multi-scale dynamics of the East China Sea and Changjiang Estuary. This modeling system has been demonstrated via application to the seasonal variations of Changjiang diluted water and the bottom saltwater intrusion in the North Passage, and it shows strong potential for estuarine and coastal ocean dynamics and operational forecasting.
Model for macroevolutionary dynamics
Maruvka, Yosef E.; Shnerb, Nadav M.; Kessler, David A.; Ricklefs, Robert E.
2013-01-01
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
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
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.
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. PMID:26657389
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.
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
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.
Robust Integrated Neurocontroller for Complex Dynamic Systems
NASA Technical Reports Server (NTRS)
Zein-Sabatto, S.; Marpaka, D.; Hwang, W.
1996-01-01
The goal of this research effort is to develop an integrated control software environment for the purpose of creating an intelligent neurocontrol system. The system will be capable of estimating states, identifying parameters, diagnosing conditions, planning control strategies, and producing intelligent control actions. The distinct features of such control system are: adaptability and on-line learning capability. The proposed system will be flexible to allow structure adaptability to account for changes in the dynamic system such as: sensory failures and/or component degradations. The developed system should learn system uncertainties and changes, as they occur, while maintaining minimal control level on the dynamic system. The research activities set to achieve the research objective are summarized by the following general items: (1) Development of a system identifier or diagnostic system, (2) Development of a robust neurocontroller system, and 3. Integration of above systems to create a Robust Integrated Control system (RIC-system). Two contrary approaches are investigated in this research: classical (traditional) design approach, and the simultaneous design approach. However, in both approaches neural network is the base for the development of different functions of the system. The two resulting designs will be tested and simulation results will be compared for better possible implementation.
Robust integrated neurocontroller for complex dynamic systems
NASA Technical Reports Server (NTRS)
Zein-Sabbato, S.; Marpaka, D.; Hwang, W.
1995-01-01
The goal of this research effort is to develop an integrated control software environment for the purpose of creating an intelligent neurocontrol system. The system will be capable of estimating states, identifying parameters, diagnosing conditions, planning control strategies, and producing intelligent control actions. The distinct features of such control system are adaptability and on-line learning capability. The proposed system will be flexible to allow structure adaptability to account for changes in the dynamic system such as sensory failures and/or component degradations. The developed system should learn system uncertainties and changes, as they occur, while maintaining minimal control level on the dynamic system. The research activities set to achieve the research objective are summarized by the following general items: (1) Development of a system identifier or diagnostic system; (2) Development of a robust neurocontroller system, and; (3) Integration of above systems to create a robust Integration Control system (RIC-system). Two contrary approaches are investigated in this research: classical (traditional) design approach, and the simultaneous design approach. However, in both approaches neural network is the base for the development of different functions of the system. The two resulting designs will be tested and simulation results will be compared for better possible implementation.
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.
Subsurface integration with Shared Earth Models
Gawith, D.; Gutteridge, P.
1995-08-01
The seismic response of a reservoir is a function of rock type, geometry and pore fluids; 3D seismic data therefore contains information on the nature of reservoir rocks, the geometry of flow units, and the distribution of gas, oil and water. Proper integration of seismic interpretation and modelling with static reservoir description and flow simulation will make the most of the information available and will lead to optimal prediction of reservoir performance. One approach to this integration is through the construction of detailed numerical models of reservoir geology and properties; if the models are sufficiently accurate then both seismic response and dynamic behaviour calculated from them will match closely the behaviour of the actual reservoir. This means that the reservoir engineer`s interpretation of dynamic data can be made in a geological context and that both static and dynamic models can be kept fully consistent with the information held in seismic data. These detailed models, combining geology, geophysics and reservoir properties, are known as Shared Earth Models. We show examples of detailed geological modelling made to honour geophysical observations, and of the use of seismic modelling to support reservoir engineering.
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.
Relativistic dynamical collapse model
NASA Astrophysics Data System (ADS)
Pearle, Philip
2015-05-01
A model is discussed where all operators are constructed from a quantum scalar field whose energy spectrum takes on all real values. The Schrödinger picture wave function depends upon space and time coordinates for each particle, as well as an inexorably increasing evolution parameter s which labels a foliation of spacelike hypersurfaces. The model is constructed to be manifestly Lorentz invariant in the interaction picture. Free particle states and interactions are discussed in this framework. Then, the formalism of the continuous spontaneous localization (CSL) theory of dynamical collapse is applied. The collapse-generating operator is chosen to be the particle number space-time density. Unlike previous relativistically invariant models, the vacuum state is not excited. The collapse dynamics depends upon two parameters, a parameter Λ which represents the collapse rate/volume and a scale factor ℓ. A common example of collapse dynamics, involving a clump of matter in a superposition of two locations, is analyzed. The collapse rate is shown to be identical to that of nonrelativistic CSL when the GRW-CSL choice of ℓ=a =1 0-5 cm , is made, along with Λ =λ /a3 (GRW-CSL choice λ =1 0-16s-1). The collapse rate is also satisfactory with the choice ℓ as the size of the Universe, with Λ =λ /ℓa2. Because the collapse narrows wave functions in space and time, it increases a particle's momentum and energy, altering its mass. It is shown that, with ℓ=a , the change of mass of a nucleon is unacceptably large but, when ℓ is the size of the Universe, the change of mass over the age of the Universe is acceptably small.
Direct integration transmittance model
NASA Technical Reports Server (NTRS)
Kunde, V. G.; Maguire, W. C.
1973-01-01
A transmittance model was developed for the 200-2000/cm region for interpretation of high spectral resolution measurements of laboratory absorption and of planetary thermal emission. The high spectral resolution requires transmittances to be computed monochromatically by summing the contribution of individual molecular absorption lines. A magnetic tape atlas of H2O,O3, and CO2 molecular line parameters serves as input to the transmittance model with simple empirical representations used for continuum regions wherever suitable laboratory data exist. The theoretical formulation of the transmittance model and the computational procedures used for the evaluation of the transmittances are discussed. Application is demonstrated of the model to several homogenous path laboratory absorption examples.
Impact of dynamic loads on propulsion integration
NASA Technical Reports Server (NTRS)
Seiner, J. M.
1994-01-01
Aircraft dynamic loads produced by engine exhaust plumes are examined for a class of military fighter and bomber configurations in model and full scale. The configurations examined are associated with the USAF F-15 and B-1B aircraft, and the US F-18 HARV and ASTOVL programs. The experience gained as a result of these studies is used to formulate a level of understanding concerning this phenomena that could be useful at the preliminary stage of propulsion/airframe design.
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
A Logical Model of Conceptual Integrity in Data Integration
Flater, David
2003-01-01
Conceptual integrity is required for the result of data integration to be cohesive and sensible. Compromised conceptual integrity results in “semantic faults,” which are commonly blamed for latent integration bugs. A logical model of conceptual integrity in data integration and a simple example application are presented. Unlike constructive models that attempt to prevent semantic faults, this model allows both correct and incorrect integrations to be described. Imperfect legacy systems can therefore be modeled, allowing a more formal analysis of their flaws and the possible remedies.
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.
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.
Path integral Liouville dynamics for thermal equilibrium systems
NASA Astrophysics Data System (ADS)
Liu, Jian
2014-06-01
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.
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.
Integrating plant carbon dynamics with mutualism ecology.
Pringle, Elizabeth G
2016-04-01
71 I. 71 II. 72 III. 73 IV. 74 V. 74 74 References 74 SUMMARY: Plants reward microbial and animal mutualists with carbohydrates to obtain nutrients, defense, pollination, and dispersal. Under a fixed carbon budget, plants must allocate carbon to their mutualists at the expense of allocation to growth, reproduction, or storage. Such carbon trade-offs are indirectly expressed when a plant exhibits reduced growth or fecundity in the presence of its mutualist. Because carbon regulates the costs of all plant mutualisms, carbon dynamics are a common platform for integrating these costs in the face of ecological complexity and context dependence. The ecophysiology of whole-plant carbon allocation could thus elucidate the ecology and evolution of plant mutualisms. If mutualisms are costly to plants, then they must be important but frequently underestimated sinks in the terrestrial carbon cycle. PMID:26414800
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. PMID:26189715
Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks
Eddy, James A.; Papin, Jason A.
2008-01-01
Extracellular cues affect signaling, metabolic, and regulatory processes to elicit cellular responses. Although intracellular signaling, metabolic, and regulatory networks are highly integrated, previous analyses have largely focused on independent processes (e.g., metabolism) without considering the interplay that exists among them. However, there is evidence that many diseases arise from multifunctional components with roles throughout signaling, metabolic, and regulatory networks. Therefore, in this study, we propose a flux balance analysis (FBA)–based strategy, referred to as integrated dynamic FBA (idFBA), that dynamically simulates cellular phenotypes arising from integrated networks. The idFBA framework requires an integrated stoichiometric reconstruction of signaling, metabolic, and regulatory processes. It assumes quasi-steady-state conditions for “fast” reactions and incorporates “slow” reactions into the stoichiometric formalism in a time-delayed manner. To assess the efficacy of idFBA, we developed a prototypic integrated system comprising signaling, metabolic, and regulatory processes with network features characteristic of actual systems and incorporating kinetic parameters based on typical time scales observed in literature. idFBA was applied to the prototypic system, which was evaluated for different environments and gene regulatory rules. In addition, we applied the idFBA framework in a similar manner to a representative module of the single-cell eukaryotic organism Saccharomyces cerevisiae. Ultimately, idFBA facilitated quantitative, dynamic analysis of systemic effects of extracellular cues on cellular phenotypes and generated comparable time-course predictions when contrasted with an equivalent kinetic model. Since idFBA solves a linear programming problem and does not require an exhaustive list of detailed kinetic parameters, it may be efficiently scaled to integrated intracellular systems that incorporate signaling, metabolic, and
Dynamic coupling of three hydrodynamic models
NASA Astrophysics Data System (ADS)
Hartnack, J. N.; Philip, G. T.; Rungoe, M.; Smith, G.; Johann, G.; Larsen, O.; Gregersen, J.; Butts, M. B.
2008-12-01
The need for integrated modelling is evidently present within the field of flood management and flood forecasting. Engineers, modellers and managers are faced with flood problems which transcend the classical hydrodynamic fields of urban, river and coastal flooding. Historically the modeller has been faced with having to select one hydrodynamic model to cover all the aspects of the potentially complex dynamics occurring in a flooding situation. Such a single hydrodynamic model does not cover all dynamics of flood modelling equally well. Thus the ideal choice may in fact be a combination of models. Models combining two numerical/hydrodynamic models are becoming more standard, typically these models combine a 1D river model with a 2D overland flow model or alternatively a 1D sewer/collection system model with a 2D overland solver. In complex coastal/urban areas the flood dynamics may include rivers/streams, collection/storm water systems along with the overland flow. The dynamics within all three areas is of the same time scale and there is feedback in the system across the couplings. These two aspects dictate a fully dynamic three way coupling as opposed to running the models sequentially. It will be shown that the main challenges of the three way coupling are time step issues related to the difference in numerical schemes used in the three model components and numerical instabilities caused by the linking of the model components. MIKE FLOOD combines the models MIKE 11, MIKE 21 and MOUSE into one modelling framework which makes it possible to couple any combination of river, urban and overland flow fully dynamically. The MIKE FLOOD framework will be presented with an overview of the coupling possibilities. The flood modelling concept will be illustrated through real life cases in Australia and in Germany. The real life cases reflect dynamics and interactions across all three model components which are not possible to reproduce using a two-way coupling alone. The
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.
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
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
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
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.
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.
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.
Thermal-dynamic modeling study
NASA Technical Reports Server (NTRS)
Ojalvo, I. U.
1973-01-01
Study provides basic information for designing models and conducting thermal-dynamic structural tests. Factors considered are development and interpretation of thermal-dynamic structural scaling laws; identification of major problem areas; and presentation of model fabrication, instrumentation, and test procedures.
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.
Integrated assessment models of global climate change
Parson, E.A.; Fisher-Vanden, K.
1997-12-31
The authors review recent work in the integrated assessment modeling of global climate change. This field has grown rapidly since 1990. Integrated assessment models seek to combine knowledge from multiple disciplines in formal integrated representations; inform policy-making, structure knowledge, and prioritize key uncertainties; and advance knowledge of broad system linkages and feedbacks, particularly between socio-economic and bio-physical processes. They may combine simplified representations of the socio-economic determinants of greenhouse gas emissions, the atmosphere and oceans, impacts on human activities and ecosystems, and potential policies and responses. The authors summarize current projects, grouping them according to whether they emphasize the dynamics of emissions control and optimal policy-making, uncertainty, or spatial detail. They review the few significant insights that have been claimed from work to date and identify important challenges for integrated assessment modeling in its relationships to disciplinary knowledge and to broader assessment seeking to inform policy- and decision-making. 192 refs., 2 figs.
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, 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
A computational model for dynamic vision
NASA Technical Reports Server (NTRS)
Moezzi, Saied; Weymouth, Terry E.
1990-01-01
This paper describes a novel computational model for dynamic vision which promises to be both powerful and robust. Furthermore the paradigm is ideal for an active vision system where camera vergence changes dynamically. Its basis is the retinotopically indexed object-centered encoding of the early visual information. Specifically, the relative distances of objects to a set of referents is encoded in image registered maps. To illustrate the efficacy of the method, it is applied to the problem of dynamic stereo vision. Integration of depth information over multiple frames obtained by a moving robot generally requires precise information about the relative camera position from frame to frame. Usually, this information can only be approximated. The method facilitates the integration of depth information without direct use or knowledge of camera motion.
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.
NASA Astrophysics Data System (ADS)
Guenet, B.; Cadule, P.; Zaehle, S.; Piao, S. L.; Peylin, P.; Maignan, F.; Ciais, P.; Friedlingstein, P.
2013-05-01
The carbon cycle strongly interacts with the nitrogen cycle. Several observations show that the effects of global change on primary production and carbon storage in plant biomass and soils are partially controlled by N availability. Nevertheless, only a small number of terrestrial biosphere models represent explicitly the nitrogen cycle, despite its importance on the carbon cycle and on climate. These models are difficult to evaluate at large spatiotemporal scales because of the scarcity of data at the global scale over a long time period. In this study, we benchmark the capacity of the O-CN global terrestrial biosphere model to reproduce temporal changes in leaf area index (LAI) at the global scale observed by NOAA_AVHRR satellites over the period 1982-2002. Using a satellite LAI product based on the normalized difference vegetation index of global inventory monitoring and modelling studies dataset, we estimate the long-term trend of LAI and we compare it with the results from the terrestrial biosphere models, either with (O-CN) or without (O-C) a dynamic nitrogen cycle coupled to the carbon-water-energy cycles. In boreal and temperate regions, including a dynamic N cycle (O-CN) improved the fit between observed and modeled temporal changes in LAI. In contrast, in the tropics, simulated LAI from the model without the dynamic N cycle (O-C) better matched observed changes in LAI over time. Despite differential regional trends, the satellite estimate suggests an increase in the global average LAI during 1982-2002 by 0.0020 m2 m-2 y-1. Both versions of the model substantially overestimated the rate of change in LAI over time (0.0065 m2 m-2 y-1 for O-C and 0.0057 m2 m-2 y-1 for O-CN), suggesting that some additional limitation mechanisms are missing in the model. We also estimated the relative importance of climate, CO2 and N deposition as potential drivers of the temporal changes in LAI. We found that recent climate change better explained temporal changes in LAI when
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.
Dynamic modeling of power systems
Reed, M.; White, J.
1995-12-01
Morgantown Energy Technology Center`s (METC) Process and Project Engineering (P&PE) personnel continue to refine and modify dynamic modeling or simulations for advanced power systems. P&PE, supported by Gilbert/Commonwealth, Inc. (G/C), has adapted PC/TRAX commercial dynamic software to include equipment found in advanced power systems. PC/TRAX`s software contains the equations that describe the operation of standard power plant equipment such as gas turbines, feedwater pumps, and steam turbines. The METC team has incorporated customized dynamic models using Advanced Continuous Simulation Language (ACSL) code for pressurized circulating fluidized-bed combustors, carbonizers, and other components that are found in Advanced Pressurized Fluidized-Bed Combustion (APFBC) systems. A dynamic model of a commercial-size APFBC power plant was constructed in order to determine representative operating characteristics of the plant and to gain some insight into the best type of control system design. The dynamic model contains both process and control model components. This presentation covers development of a model used to describe the commercial APFBC power plant. Results of exercising the model to simulate plant performance are described and illustrated. Information gained during the APFBC study was applied to a dynamic model of a 1-1/2 generation PFBC system. Some initial results from this study are also presented.
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.
Research a Novel Integrated and Dynamic Multi-object Trade-Off Mechanism in Software Project
NASA Astrophysics Data System (ADS)
Jiang, Weijin; Xu, Yuhui
Aiming at practical requirements of present software project management and control, the paper presented to construct integrated multi-object trade-off model based on software project process management, so as to actualize integrated and dynamic trade-oil of the multi-object system of project. Based on analyzing basic principle of dynamic controlling and integrated multi-object trade-off system process, the paper integrated method of cybernetics and network technology, through monitoring on some critical reference points according to the control objects, emphatically discussed the integrated and dynamic multi- object trade-off model and corresponding rules and mechanism in order to realize integration of process management and trade-off of multi-object system.
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.
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
Stochastic dynamic models and Chebyshev splines
Fan, Ruzong; Zhu, Bin; Wang, Yuedong
2015-01-01
In this article, we establish a connection between a stochastic dynamic model (SDM) driven by a linear stochastic differential equation (SDE) and a Chebyshev spline, which enables researchers to borrow strength across fields both theoretically and numerically. We construct a differential operator for the penalty function and develop a reproducing kernel Hilbert space (RKHS) induced by the SDM and the Chebyshev spline. The general form of the linear SDE allows us to extend the well-known connection between an integrated Brownian motion and a polynomial spline to a connection between more complex diffusion processes and Chebyshev splines. One interesting special case is connection between an integrated Ornstein–Uhlenbeck process and an exponential spline. We use two real data sets to illustrate the integrated Ornstein–Uhlenbeck process model and exponential spline model and show their estimates are almost identical. PMID:26045632
NASA Astrophysics Data System (ADS)
Viaud, V.; Pennock, D.
2010-12-01
Plant-soil interactions and the addition of organic matter from grass have long been the only processes identified to explain soil organic carbon (SOC) distribution and the origin of the A-horizon of chernozemic soils (Dokutchaiev, 1967). But recent studies have suggested that the role of burrowing animals in soil mixing and its consequences on SOC distribution in chernozemic soils have been underestimated (Wilkinson et al., 2009). This work aims at modelling the spatio-temporal evolution of SOC stocks across a catena in a hummocky landscape of Central Saskatchewan. The catena was represented as a 2-dimensional system, divided into 1-m cells in the lateral dimension, and into 6 increments in the vertical dimension (0-to-10, 10-to-20, 20-to-30, 30-to-60, 60-to-90, and 90-to-120 cm). The carbon module of the CENTURY model was used to simulate SOC dynamics in each soil horizon, and the effect of bioturbation on soil vertical mixing in the top soil layers was explicitly modeled. The model also included a simulation of the water budget and water fluxes in soils that partly control SOC dynamics across a catena. The study was based on a detailed dataset from St Denis Wildlife Area (SK, Canada), including climate data, above- and belowground biomass measurements, soil survey, topography, and quantitative data on soil properties and C input in several landscape locations. The model was run over 10000 years. Precipitation and temperature were simulated stochastically. Simulation results, with and without bioturbation, were compared to the current values of SOC stocks.
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. PMID:25928681
An integrated approach to reservoir modeling
Donaldson, K. )
1993-08-01
The purpose of this research is to evaluate the usefulness of the following procedural and analytical methods in investigating the heterogeneity of the oil reserve for the Mississipian Big Injun Sandstone of the Granny Creek field, Clay and Roane counties, West Virginia: (1) relational database, (2) two-dimensional cross sections, (3) true three-dimensional modeling, (4) geohistory analysis, (5) a rule-based expert system, and (6) geographical information systems. The large data set could not be effectively integrated and interpreted without this approach. A relational database was designed to fully integrate three- and four-dimensional data. The database provides an effective means for maintaining and manipulating the data. A two-dimensional cross section program was designed to correlate stratigraphy, depositional environments, porosity, permeability, and petrographic data. This flexible design allows for additional four-dimensional data. Dynamic Graphics[sup [trademark
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.
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.
Integrating GIS and ABM to Explore Spatiotemporal Dynamics
NASA Astrophysics Data System (ADS)
Sun, M.; Jiang, Y.; Yang, C.
2013-12-01
Agent-based modeling as a methodology for the bottom-up exploration with the account of adaptive behavior and heterogeneity of system components can help discover the development and pattern of the complex social and environmental system. However, ABM is a computationally intensive process especially when the number of system components becomes large and the agent-agent/agent-environmental interaction is modeled very complex. Most of traditional ABM frameworks developed based on CPU do not have a satisfying computing capacity. To address the problem and as the emergence of advanced techniques, GPU computing with CUDA can provide powerful parallel structure to enable the complex simulation of spatiotemporal dynamics. In this study, we first develop a GPU-based ABM system. Secondly, in order to visualize the dynamics generated from the movement of agent and the change of agent/environmental attributes during the simulation, we integrate GIS into the ABM system. Advanced geovisualization technologies can be utilized for representing the spatiotemporal change events, such as proper 2D/3D maps with state-of-the-art symbols, space-time cube and multiple layers each of which presents pattern in one time-stamp, etc. Thirdly, visual analytics which include interactive tools (e.g. grouping, filtering, linking, etc.) is included in our ABM-GIS system to help users conduct real-time data exploration during the progress of simulation. Analysis like flow analysis and spatial cluster analysis can be integrated according to the geographical problem we want to explore.
The integrated urban land model
NASA Astrophysics Data System (ADS)
Meng, Chunlei
2015-06-01
An integrated urban land model (IUM) was developed based on the Common Land Model (CoLM). A whole layer soil evaporation parameterization scheme was developed to improve soil evaporation simulation especially in arid areas. For the urban underlying surface, the energy and water balance model were modified; urban land parameters such as the anthropogenic heat (AH), albedo, surface roughness length, imperious surface evaporation etc. were also reparameterized. IUM was validated and compared with CoLM and the urbanized high-resolution land data assimilation system (u-HRLDAS) in single and regional scale. The validation results indicate that IUM can improve the simulation of land surface parameters and land-atmosphere interaction fluxes.
Signal integration enhances the dynamic range in neuronal systems
NASA Astrophysics Data System (ADS)
Gollo, Leonardo L.; Mirasso, Claudio; Eguíluz, Víctor M.
2012-04-01
The dynamic range measures the capacity of a system to discriminate the intensity of an external stimulus. Such an ability is fundamental for living beings to survive: to leverage resources and to avoid danger. Consequently, the larger is the dynamic range, the greater is the probability of survival. We investigate how the integration of different input signals affects the dynamic range, and in general the collective behavior of a network of excitable units. By means of numerical simulations and a mean-field approach, we explore the nonequilibrium phase transition in the presence of integration. We show that the firing rate in random and scale-free networks undergoes a discontinuous phase transition depending on both the integration time and the density of integrator units. Moreover, in the presence of external stimuli, we find that a system of excitable integrator units operating in a bistable regime largely enhances its dynamic range.
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.
Dynamic properties of high structural integrity auxetic open cell foam
NASA Astrophysics Data System (ADS)
Scarpa, F.; Ciffo, L. G.; Yates, J. R.
2004-02-01
This paper illustrates various dynamic characteristics of open cell compliant polyurethane foam with auxetic (negative Poisson's ratio) behaviour. The foam is obtained from off-the-shelf open cell polyurethane grey foam with a manufacturing process based on mechanical deformation on a mould in a temperature-controlled oven. The Poisson's ratio is measured with an image processing technique based on edge detection with wavelet methods. Foam samples have been tested in a viscoelastic analyser tensile test machine to determine the Young's modulus and loss factor for small dynamic strains. The same samples have also been tested in an acoustic impedance tube to measure acoustic absorption and specific acoustic resistance and reactance with a transmissibility technique. Another set of tests has been set up on a cam plastometer machine for constant strain rate dynamic crushing analysis. All the tests have been carried out on auxetic and normal foam samples to provide a comparison between the two types of cellular solids. The results from the experimental tests are discussed and interpreted using microstructure models for cellular materials existing in the literature. The negative Poisson's ratio foam presented in this paper shows an overall superiority regarding damping and acoustic properties compared to the original conventional foam. Its dynamic crushing performance is also significantly superior to the normal foam, suggesting a possible use in structural integrity compliant elements.
NASA Astrophysics Data System (ADS)
Adams, Neil S.; Bollenbacher, Gary
1992-12-01
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.
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.
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
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.
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
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.
A Graph Based Framework to Model Virus Integration Sites.
Fronza, Raffaele; Vasciaveo, Alessandro; Benso, Alfredo; Schmidt, Manfred
2016-01-01
With next generation sequencing thousands of virus and viral vector integration genome targets are now under investigation to uncover specific integration preferences and to define clusters of integration, termed common integration sites (CIS), that may allow to assess gene therapy safety or to detect disease related genomic features such as oncogenes. Here, we addressed the challenge to: 1) define the notion of CIS on graph models, 2) demonstrate that the structure of CIS enters in the category of scale-free networks and 3) show that our network approach analyzes CIS dynamically in an integrated systems biology framework using the Retroviral Transposon Tagged Cancer Gene Database (RTCGD) as a testing dataset. PMID:27257470
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.
Dynamical models of happiness.
Sprott, J C
2005-01-01
A sequence of models for the time evolution of one's happiness in response to external events is described. These models with added nonlinearities can produce stable oscillations and chaos even without external events. Potential implications for psychotherapy and a personal approach to life are discussed. PMID:15629066
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.
Vector Product and an Integrable Dynamical System
NASA Astrophysics Data System (ADS)
Willi-Hans, Steeb; Yorick, Hardy; Igor, Tanski
2011-12-01
We study an autonomous system of first order ordinary differential equations based on the vector product. We show that the system is completely integrable by constructing the first integrals. The connection with Nambu mechanics is established. The extension to higher dimensions is also discussed.
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.
Space Station Freedom solar dynamic modules structural modelling and analysis
Lawrence, C.; Morris, R.
1991-12-01
In support of the Space Station Freedom (SSF) Solar Dynamic Power Module effort, structural design studies were performed to investigate issues related to the design of the power module, its pointing capabilities, and the integration of the module into the SSF infrastructure. Of particular concern from a structural viewpoint are the dynamics of the power module, the impact of the power module on the Space Station dynamics and controls, and the required control effort for obtaining the specified Solar Dynamic Power Module pointing accuracy. Structural analyses were performed to determine the structural dynamics attributes of both the existing and the proposed structural dynamics module designs. The objectives of these analyses were to generate validated Solar Dynamic Power Module NASTRAN finite element models, combine Space Station and power module models into integrated system models, perform finite element modal analyses to assess the effect of the relocations of the power module center of mass, and provide modal data to controls designers for control systems design.
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.
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.
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.
Nonlinear Dynamics: Maps, Integrators and Solitons
Parsa, Z.
1998-10-01
For many physical systems of interest in various disciplines, the solution to nonlinear differential equations describing the physical systems can be generated using maps, symplectic integrators and solitons. We discuss these methods and apply them for various examples.
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
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
Activated Dynamics in Dense Model Nanocomposites
NASA Astrophysics Data System (ADS)
Xie, Shijie; Schweizer, Kenneth
The nonlinear Langevin equation approach is applied to investigate the ensemble-averaged activated dynamics of small molecule liquids (or disconnected segments in a polymer melt) in dense nanocomposites under model isobaric conditions where the spherical nanoparticles are dynamically fixed. Fully thermalized and quenched-replica integral equation theory methods are employed to investigate the influence on matrix dynamics of the equilibrium and nonequilibrium nanocomposite structure, respectively. In equilibrium, the miscibility window can be narrow due to depletion and bridging attraction induced phase separation which limits the study of activated dynamics to regimes where the barriers are relatively low. In contrast, by using replica integral equation theory, macroscopic demixing is suppressed, and the addition of nanoparticles can induce much slower activated matrix dynamics which can be studied over a wide range of pure liquid alpha relaxation times, interfacial attraction strengths and ranges, particle sizes and loadings, and mixture microstructures. Numerical results for the mean activated relaxation time, transient localization length, matrix elasticity and kinetic vitrification in the nanocomposite will be presented.
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.
Integrated modeling of the Euro50
NASA Astrophysics Data System (ADS)
Andersen, Torben E.; Browne, Michael T.; Enmark, Anita; Moraru, Dan; Owner-Petersen, Mette; Riewaldt, Holger
2004-07-01
The Euro50 is a proposed 50 m optical and infrared telescope. It will have thousands of control loops to keep the optics aligned under influence of wind, gravity and thermal loads. Cross-disciplinary integrated modeling is used to study the overall performance of the Euro50. A sub-model of the mechanical structure originates from finite element modeling. The optical performance is determined using ray tracing, both non-linear and linearized. The primary mirror segment alignment control system is modeled with the 618 segments taken as rigid bodies. Adaptive optics is included using a layered model of the atmosphere and sub-models of the wavefront sensor, reconstructor and controller. The deformable mirror is, so far, described by a simple influence function and a second order dynamical transfer function but more detailed work is in progress. The model has been implemented using Matlab/Simulink on individual computers but it will shortly be implemented on a Beowulf cluster within a trusted network. Communication routines between Matlab on the cluster processors have been written and are being benchmarked. Representative results from the simulations are shown.
Stochastic models of neuronal dynamics
Harrison, L.M; David, O; Friston, K.J
2005-01-01
Cortical activity is the product of interactions among neuronal populations. Macroscopic electrophysiological phenomena are generated by these interactions. In principle, the mechanisms of these interactions afford constraints on biologically plausible models of electrophysiological responses. In other words, the macroscopic features of cortical activity can be modelled in terms of the microscopic behaviour of neurons. An evoked response potential (ERP) is the mean electrical potential measured from an electrode on the scalp, in response to some event. The purpose of this paper is to outline a population density approach to modelling ERPs. We propose a biologically plausible model of neuronal activity that enables the estimation of physiologically meaningful parameters from electrophysiological data. The model encompasses four basic characteristics of neuronal activity and organization: (i) neurons are dynamic units, (ii) driven by stochastic forces, (iii) organized into populations with similar biophysical properties and response characteristics and (iv) multiple populations interact to form functional networks. This leads to a formulation of population dynamics in terms of the Fokker–Planck equation. The solution of this equation is the temporal evolution of a probability density over state-space, representing the distribution of an ensemble of trajectories. Each trajectory corresponds to the changing state of a neuron. Measurements can be modelled by taking expectations over this density, e.g. mean membrane potential, firing rate or energy consumption per neuron. The key motivation behind our approach is that ERPs represent an average response over many neurons. This means it is sufficient to model the probability density over neurons, because this implicitly models their average state. Although the dynamics of each neuron can be highly stochastic, the dynamics of the density is not. This means we can use Bayesian inference and estimation tools that have
Dynamics of non-integrable phases and gauge symmetry breaking
Hosotani, Y.
1989-03-01
On a multiply-connected space the non-integrable phase factor/ital P/ exp(ig..integral../ital A//sub ..mu..//ital dx//sup ..mu..//r brace/), a path-ordered line integral along anon-contractable loop, becomes a dynamical degree of freedom in gauge theory.The dynamics of such non-integrable phases are examined in detail with themost general boundary condition for gauge fields and fermions. Sometimesthe dynamics of the non-integrable phases compensate the arbitrariness inthe boundary condition imposed, leading to the same physics results. Inother cases the dynamics of the non-integrable phases induce spontaneousbreaking of non-Abelian gauge symmetry. In other words the physically realizedsymmetry of the system differs from, and can be either greater or smaller than,the symmetry of the boundary condition. The effective potential for thenon-integrable phases in the /ital SU/(/ital N/) gauge theory on/ital S//sup 1//direct product//ital R//sup 1/ital d//minus/2/is computed in the one-loop approximation. It is shown that the gauge symmetryis dynamically broken in the presence of fermions in the adjoint representation,depending on the value of the boundary condition parameter./copyright/ 1989 Academic Press, Inc.
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
NASA Astrophysics Data System (ADS)
Dunn, Jennifer; Roberts, Scott C.; Kerley, Dan; Fitzsimmons, Joeleff T.; Pazder, John S.; Herriot, Glen; Smith, Malcolm J.
2004-11-01
The National Research Council's Herzberg Institute of Astrophysics (NRC-HIA) has developed an opto-mechanical integrated modeling toolset called TM-IM. This time-domain state-space toolset has been implemented using Matlab/Simulink/C. The toolset was originally developed for the Very Large Optical Telescope (VLOT) design work, and continued when Canada joined in the Thirty Meter Telescope (TMT) project. The TM-IM toolset has been developed to accommodate different structural and optical designs and has been used to evaluate telescope performance to assist in making decisions for the TMT reference design expected fall 2004. Preliminary results include delivered image quality as a function of wind loading on the structure, primary and secondary mirror, and the simulation of an Adaptive Optics system which provides control feedback to the primary mirror.
An integrated model of learning.
Trigg, A M; Cordova, F D
1987-01-01
Worldwide, most educational systems are based on three levels of education that utilize the pedagogical approaches to learning. In the 1960s, scholars formulated another approach to education that has become known as andragogy and has been applied to adult education. Several innovative scholars have seen how andragogy can be applied to teaching children. As a result, both andragogy and pedagogy are viewed as the opposite ends of the educational spectrum. Both of these approaches have a place and function within the modern educational framework. If one assumes that the goal of education is for the acquisition and application of knowledge, then both of these approaches can be used effectively for the attainment of that goal. In order to utilize these approaches effectively, an integrated model of learning has been developed that consists of initial teaching and exploratory learning phases. This model has both the directive and flexible qualities found in the theories of pedagogy and andragogy. With careful consideration and analysis this educational model can be utilized effectively within most educational systems. PMID:3588888
Painting the Phase Space Portrait of an Integrable Dynamical System
NASA Astrophysics Data System (ADS)
Coffey, Shannon; Deprit, Andre; Deprit, Etienne; Healy, Liam
1990-02-01
For an integrable dynamical system with one degree of freedom, "painting" the integral over the phase space proves to be very effective for uncovering the global flow down to minute details. Applied to the main problem in artificial satellite theory, for instance, the technique reveals an intricate configuration of equilibria and bifurcations when the polar component of the angular momentum approaches zero.
Tree Modeling and Dynamics Simulation
NASA Astrophysics Data System (ADS)
Tian-shuang, Fu; Yi-bing, Li; Dong-xu, Shen
This paper introduces the theory about tree modeling and dynamic movements simulation in computer graphics. By comparing many methods we choose Geometry-based rendering as our method. The tree is decomposed into branches and leaves, under the rotation and quaternion methods we realize the tree animation and avoid the Gimbals Lock in Euler rotation. We take Orge 3D as render engine, which has good graphics programming ability. By the end we realize the tree modeling and dynamic movements simulation, achieve realistic visual quality with little computation cost.
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.
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.
Modeling tumor evolutionary dynamics
Stransky, Beatriz; de Souza, Sandro J.
2013-01-01
Tumorigenesis can be seen as an evolutionary process, in which the transformation of a normal cell into a tumor cell involves a number of limiting genetic and epigenetic events, occurring in a series of discrete stages. However, not all mutations in a cell are directly involved in cancer development and it is likely that most of them (passenger mutations) do not contribute in any way to tumorigenesis. Moreover, the process of tumor evolution is punctuated by selection of advantageous (driver) mutations and clonal expansions. Regarding these driver mutations, it is uncertain how many limiting events are required and/or sufficient to promote a tumorigenic process or what are the values associated with the adaptive advantage of different driver mutations. In spite of the availability of high-quality cancer data, several assumptions about the mechanistic process of cancer initiation and development remain largely untested, both mathematically and statistically. Here we review the development of recent mathematical/computational models and discuss their impact in the field of tumor biology. PMID:23420281
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.
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
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
NASA Astrophysics Data System (ADS)
Chen, Guangsheng; Tian, Hanqin; Huang, Chengquan; Prior, Stephen A.; Pan, Shufen
2013-07-01
ecosystems in the southern United States are dramatically altered by three major disturbances: timber harvesting, hurricane, and permanent land conversion. Understanding and quantifying effects of disturbance on forest carbon, nitrogen, and water cycles is critical for sustainable forest management in this region. In this study, we introduced a process-based ecosystem model for simulating forest disturbance impacts on ecosystem carbon, nitrogen, and water cycles. Based on forest mortality data classified from Landsat TM/ETM + images, this model was then applied to estimate changes in carbon storage using Mississippi and Alabama as a case study. Mean annual forest mortality rate for these states was 2.37%. Due to frequent disturbance, over 50% of the forest land in the study region was less than 30 years old. Forest disturbance events caused a large carbon source (138.92 Tg C, 6.04 Tg C yr-1; 1 Tg = 1012 g) for both states during 1984-2007, accounting for 2.89% (4.81% if disregard carbon storage changes in wood products) of the total forest carbon storage in this region. Large decreases and slow recovery of forest biomass were the main causes for carbon release. Forest disturbance could result in a carbon sink in few areas if wood product carbon was considered as a local carbon pool, indicating the importance of accounting for wood product carbon when assessing forest disturbance effects. The legacy effects of forest disturbance on ecosystem carbon storage could last over 50 years. This study implies that understanding forest disturbance impacts on carbon dynamics is of critical importance for assessing regional carbon budgets.
INTEGRATED HYDROGEN STORAGE SYSTEM MODEL
Hardy, B
2007-11-16
Hydrogen storage is recognized as a key technical hurdle that must be overcome for the realization of hydrogen powered vehicles. Metal hydrides and their doped variants have shown great promise as a storage material and significant advances have been made with this technology. In any practical storage system the rate of H2 uptake will be governed by all processes that affect the rate of mass transport through the bed and into the particles. These coupled processes include heat and mass transfer as well as chemical kinetics and equilibrium. However, with few exceptions, studies of metal hydrides have focused primarily on fundamental properties associated with hydrogen storage capacity and kinetics. A full understanding of the complex interplay of physical processes that occur during the charging and discharging of a practical storage system requires models that integrate the salient phenomena. For example, in the case of sodium alanate, the size of NaAlH4 crystals is on the order of 300nm and the size of polycrystalline particles may be approximately 10 times larger ({approx}3,000nm). For the bed volume to be as small as possible, it is necessary to densely pack the hydride particles. Even so, in packed beds composed of NaAlH{sub 4} particles alone, it has been observed that the void fraction is still approximately 50-60%. Because of the large void fraction and particle to particle thermal contact resistance, the thermal conductivity of the hydride is very low, on the order of 0.2 W/m-{sup o}C, Gross, Majzoub, Thomas and Sandrock [2002]. The chemical reaction for hydrogen loading is exothermic. Based on the data in Gross [2003], on the order of 10{sup 8}J of heat of is released for the uptake of 5 kg of H{sub 2}2 and complete conversion of NaH to NaAlH{sub 4}. Since the hydride reaction transitions from hydrogen loading to discharge at elevated temperatures, it is essential to control the temperature of the bed. However, the low thermal conductivity of the hydride
Integrable open boundary conditions for XXC models
NASA Astrophysics Data System (ADS)
Arnaudon, Daniel; Maassarani, Ziad
1998-10-01
The XXC models are multistate generalizations of the well known spin-½ XXZ model. These integrable models share a common underlying su(2) structure. We derive integrable open boundary conditions for the hierarchy of conserved quantities of the XXC models . Due to lack of crossing unitarity of the R-matrix, we develop specific methods to prove integrability. The symmetry of the spectrum is determined.
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.
Integrated modeling, data transfers, and physical models
NASA Astrophysics Data System (ADS)
Brookshire, D. S.; Chermak, J. M.
2003-04-01
Difficulties in developing precise economic policy models for water reallocation and re-regulation in various regional and transboundary settings has been exacerbated not only by climate issues but also by institutional changes reflected in the promulgation of environmental laws, changing regional populations, and an increased focus on water quality standards. As complexity of the water issues have increased, model development at a micro-policy level is necessary to capture difficult institutional nuances and represent the differing national, regional and stakeholders' viewpoints. More often than not, adequate "local" or specific micro-data are not available in all settings for modeling and policy decisions. Economic policy analysis increasingly deals with this problem through data transfers (transferring results from one study area to another) and significant progress has been made in understanding the issue of the dimensionality of data transfers. This paper explores the conceptual and empirical dimensions of data transfers in the context of integrated modeling when the transfers are not only from the behavioral, but also from the hard sciences. We begin by exploring the domain of transfer issues associated with policy analyses that directly consider uncertainty in both the behavioral and physical science settings. We then, through a stylized, hybrid, economic-engineering model of water supply and demand in the Middle Rio Grand Valley of New Mexico (USA) analyze the impacts of; (1) the relative uncertainty of data transfers methods, (2) the uncertainty of climate data and, (3) the uncertainly of population growth. These efforts are motivated by the need to address the relative importance of more accurate data both from the physical sciences as well as from demography and economics for policy analyses. We evaluate the impacts by empirically addressing (within the Middle Rio Grand model): (1) How much does the surrounding uncertainty of the benefit transfer
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. PMID:15013222
Building integral projection models: a user's guide
Rees, Mark; Childs, Dylan Z; Ellner, Stephen P; Coulson, Tim
2014-01-01
In order to understand how changes in individual performance (growth, survival or reproduction) influence population dynamics and evolution, ecologists are increasingly using parameterized mathematical models. For continuously structured populations, where some continuous measure of individual state influences growth, survival or reproduction, integral projection models (IPMs) are commonly used. We provide a detailed description of the steps involved in constructing an IPM, explaining how to: (i) translate your study system into an IPM; (ii) implement your IPM; and (iii) diagnose potential problems with your IPM. We emphasize how the study organism's life cycle, and the timing of censuses, together determine the structure of the IPM kernel and important aspects of the statistical analysis used to parameterize an IPM using data on marked individuals. An IPM based on population studies of Soay sheep is used to illustrate the complete process of constructing, implementing and evaluating an IPM fitted to sample data. We then look at very general approaches to parameterizing an IPM, using a wide range of statistical techniques (e.g. maximum likelihood methods, generalized additive models, nonparametric kernel density estimators). Methods for selecting models for parameterizing IPMs are briefly discussed. We conclude with key recommendations and a brief overview of applications that extend the basic model. The online Supporting Information provides commented R code for all our analyses. PMID:24219157
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.
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. PMID:25933864
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.
Conceptual dynamical models for turbulence.
Majda, Andrew J; Lee, Yoonsang
2014-05-01
Understanding the complexity of anisotropic turbulent processes in engineering and environmental fluid flows is a formidable challenge with practical significance because energy often flows intermittently from the smaller scales to impact the largest scales in these flows. Conceptual dynamical models for anisotropic turbulence are introduced and developed here which, despite their simplicity, capture key features of vastly more complicated turbulent systems. These conceptual models involve a large-scale mean flow and turbulent fluctuations on a variety of spatial scales with energy-conserving wave-mean-flow interactions as well as stochastic forcing of the fluctuations. Numerical experiments with a six-dimensional conceptual dynamical model confirm that these models capture key statistical features of vastly more complex anisotropic turbulent systems in a qualitative fashion. These features include chaotic statistical behavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuations whereas the turbulent fluctuations have decreasing energy and correlation times at smaller scales, with nearly Gaussian pdfs for the large-scale fluctuations and fat-tailed non-Gaussian pdfs for the smaller-scale fluctuations. This last feature is a manifestation of intermittency of the small-scale fluctuations where turbulent modes with small variance have relatively frequent extreme events which directly impact the mean flow. The dynamical models introduced here potentially provide a useful test bed for algorithms for prediction, uncertainty quantification, and data assimilation for anisotropic turbulent systems. PMID:24753605
Conceptual dynamical models for turbulence
Majda, Andrew J.; Lee, Yoonsang
2014-01-01
Understanding the complexity of anisotropic turbulent processes in engineering and environmental fluid flows is a formidable challenge with practical significance because energy often flows intermittently from the smaller scales to impact the largest scales in these flows. Conceptual dynamical models for anisotropic turbulence are introduced and developed here which, despite their simplicity, capture key features of vastly more complicated turbulent systems. These conceptual models involve a large-scale mean flow and turbulent fluctuations on a variety of spatial scales with energy-conserving wave–mean-flow interactions as well as stochastic forcing of the fluctuations. Numerical experiments with a six-dimensional conceptual dynamical model confirm that these models capture key statistical features of vastly more complex anisotropic turbulent systems in a qualitative fashion. These features include chaotic statistical behavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuations whereas the turbulent fluctuations have decreasing energy and correlation times at smaller scales, with nearly Gaussian pdfs for the large-scale fluctuations and fat-tailed non-Gaussian pdfs for the smaller-scale fluctuations. This last feature is a manifestation of intermittency of the small-scale fluctuations where turbulent modes with small variance have relatively frequent extreme events which directly impact the mean flow. The dynamical models introduced here potentially provide a useful test bed for algorithms for prediction, uncertainty quantification, and data assimilation for anisotropic turbulent systems. PMID:24753605
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…
Modelling the mechanoreceptor's dynamic behaviour.
Song, Zhuoyi; Banks, Robert W; Bewick, Guy S
2015-08-01
All sensory receptors adapt, i.e. they constantly adjust their sensitivity to external stimuli to match the current demands of the natural environment. Electrophysiological responses of sensory receptors from widely different modalities seem to exhibit common features related to adaptation, and these features can be used to examine the underlying sensory transduction mechanisms. Among the principal senses, mechanosensation remains the least understood at the cellular level. To gain greater insights into mechanosensory signalling, we investigated if mechanosensation displayed adaptive dynamics that could be explained by similar biophysical mechanisms in other sensory modalities. To do this, we adapted a fly photoreceptor model to describe the primary transduction process for a stretch-sensitive mechanoreceptor, taking into account the viscoelastic properties of the accessory muscle fibres and the biophysical properties of known mechanosensitive channels (MSCs). The model's output is in remarkable agreement with the electrical properties of a primary ending in an isolated decapsulated spindle; ramp-and-hold stretch evokes a characteristic pattern of potential change, consisting of a large dynamic depolarization during the ramp phase and a smaller static depolarization during the hold phase. The initial dynamic component is likely to be caused by a combination of the mechanical properties of the muscle fibres and a refractory state in the MSCs. Consistent with the literature, the current model predicts that the dynamic component is due to a rapid stress increase during the ramp. More novel predictions from the model are the mechanisms to explain the initial peak in the dynamic component. At the onset of the ramp, all MSCs are sensitive to external stimuli, but as they become refractory (inactivated), fewer MSCs are able to respond to the continuous stretch, causing a sharp decrease after the peak response. The same mechanism could contribute a faster component in the
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.
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
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
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.
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.
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.
Generalized microcanonical and Gibbs ensembles in classical and quantum integrable dynamics
NASA Astrophysics Data System (ADS)
Yuzbashyan, Emil A.
2016-04-01
We prove two statements about the long time dynamics of integrable Hamiltonian systems. In classical mechanics, we prove the microcanonical version of the Generalized Gibbs Ensemble (GGE) by mapping it to a known theorem and then extend it to the limit of infinite number of degrees of freedom. In quantum mechanics, we prove GGE for maximal Hamiltonians-a class of models stemming from a rigorous notion of quantum integrability understood as the existence of conserved charges with prescribed dependence on a system parameter, e.g. Hubbard U, anisotropy in the XXZ model etc. In analogy with classical integrability, the defining property of these models is that they have the maximum number of independent integrals. We contrast their dynamics induced by quenching the parameter to that of random matrix Hamiltonians.
Efficient gradient computation for dynamical models
Sengupta, B.; Friston, K.J.; Penny, W.D.
2014-01-01
Data assimilation is a fundamental issue that arises across many scales in neuroscience — ranging from the study of single neurons using single electrode recordings to the interaction of thousands of neurons using fMRI. Data assimilation involves inverting a generative model that can not only explain observed data but also generate predictions. Typically, the model is inverted or fitted using conventional tools of (convex) optimization that invariably extremise some functional — norms, minimum descriptive length, variational free energy, etc. Generally, optimisation rests on evaluating the local gradients of the functional to be optimized. In this paper, we compare three different gradient estimation techniques that could be used for extremising any functional in time — (i) finite differences, (ii) forward sensitivities and a method based on (iii) the adjoint of the dynamical system. We demonstrate that the first-order gradients of a dynamical system, linear or non-linear, can be computed most efficiently using the adjoint method. This is particularly true for systems where the number of parameters is greater than the number of states. For such systems, integrating several sensitivity equations – as required with forward sensitivities – proves to be most expensive, while finite-difference approximations have an intermediate efficiency. In the context of neuroimaging, adjoint based inversion of dynamical causal models (DCMs) can, in principle, enable the study of models with large numbers of nodes and parameters. PMID:24769182
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.
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.
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.
Integrated Control Modeling for Propulsion Systems Using NPSS
NASA Technical Reports Server (NTRS)
Parker, Khary I.; Felder, James L.; Lavelle, Thomas M.; Withrow, Colleen A.; Yu, Albert Y.; Lehmann, William V. A.
2004-01-01
The Numerical Propulsion System Simulation (NPSS), an advanced engineering simulation environment used to design and analyze aircraft engines, has been enhanced by integrating control development tools into it. One of these tools is a generic controller interface that allows NPSS to communicate with control development software environments such as MATLAB and EASY5. The other tool is a linear model generator (LMG) that gives NPSS the ability to generate linear, time-invariant state-space models. Integrating these tools into NPSS enables it to be used for control system development. This paper will discuss the development and integration of these tools into NPSS. In addition, it will show a comparison of transient model results of a generic, dual-spool, military-type engine model that has been implemented in NPSS and Simulink. It will also show the linear model generator s ability to approximate the dynamics of a nonlinear NPSS engine model.
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
Quantum tunneling splittings from path-integral molecular dynamics.
Mátyus, Edit; Wales, David J; Althorpe, Stuart C
2016-03-21
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. PMID:27004863
Beam dynamics aspects for the APT integrated linac
Nath, S.; Gray, E.R.; Wangler, T.P.
1997-08-01
The accelerator-based production of tritium calls for a high-power cw proton linac. The current Los Alamos design uses an integrated approach in terms of accelerating structure. The front part of the accelerator uses normal-conducting (NC) structures while most (>80%) of the linac structure is superconducting (SC). Here, the authors report the beam-dynamics rationale used in the integrated design and present particle simulation results.
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
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
Fully integrated aerodynamic/dynamic optimization of helicopter rotor blades
NASA Technical Reports Server (NTRS)
Walsh, Joanne L.; Lamarsh, William J., II; Adelman, Howard M.
1992-01-01
A fully integrated aerodynamic/dynamic optimization procedure is described for helicopter rotor blades. The procedure combines performance and dynamic analyses with a general purpose optimizer. The procedure minimizes a linear combination of power required (in hover, forward flight, and maneuver) and vibratory hub shear. The design variables include pretwist, taper initiation, taper ratio, root chord, blade stiffnesses, tuning masses, and tuning mass locations. Aerodynamic constraints consist of limits on power required in hover, forward flight and maneuvers; airfoil section stall; drag divergence Mach number; minimum tip chord; and trim. Dynamic constraints are on frequencies, minimum autorotational inertia, and maximum blade weight. The procedure is demonstrated for two cases. In the first case, the objective function involves power required (in hover, forward flight and maneuver) and dynamics. The second case involves only hover power and dynamics. The designs from the integrated procedure are compared with designs from a sequential optimization approach in which the blade is first optimized for performance and then for dynamics. In both cases, the integrated approach is superior.
Concordance: A Framework for Managing Model Integrity
NASA Astrophysics Data System (ADS)
Rose, Louis M.; Kolovos, Dimitrios S.; Drivalos, Nicholas; Williams, James R.; Paige, Richard F.; Polack, Fiona A. C.; Fernandes, Kiran J.
A change to a software development artefact, such as source code or documentation, can affect the integrity of others. Many contemporary software development environments provide tools that automatically manage (detect, report and reconcile) integrity. For instance, incremental background compilation can reconcile object code with changing source code and report calls to a method that are inconsistent with its definition. Although models are increasingly first-class citizens in software development, contemporary development environments are less able to automatically detect, manage and reconcile the integrity of models than the integrity of other types of artefact. In this paper, we discuss the scalability and efficiency problems faced when managing model integrity for two categories of change that occur in MDE. We present a framework to support the incremental management of model integrity, evaluating the efficiency of the proposed approach atop Eclipse and EMF.
Integrable dynamical systems with hierarchy. I. Formulation
Okubo, S.
1989-04-01
It is shown that any model with the zero (generalized) Nijenhuis tensor, under some additional assumptions, will automatically satisfy the hierarchy equation with an infinite number of conserved quantities in involution. Especially, if there is a dual symplectic structure with zero Nijenhuis tensor, then there exist infinite numbers of Poisson brackets and of Lagrangians giving the same equation of motion. Toda lattice is one such example
Dynamical model of brushite precipitation
NASA Astrophysics Data System (ADS)
Oliveira, Cristina; Georgieva, Petia; Rocha, Fernando; Ferreira, António; Feyo de Azevedo, Sebastião
2007-07-01
The objectives of this work are twofold. From academic point of view the aim is to build a dynamical macro model to fit the material balance and explain the main kinetic mechanisms that govern the transformation of the hydroxyapatite (HAP) into brushite and the growth of brushite, based on laboratory experiments and collected database. From practical point of view, the aim is to design a reliable process simulator that can be easily imbedded in industrial software for model driven monitoring, optimization and control purposes. Based upon a databank of laboratory measurements of the calcium concentration in solution (on-line) and the particle size distribution (off-line) a reliable dynamical model of the dual nature of brushite particle formation for a range of initial concentrations of the reagents was derived as a system of ordinary differential equations of time. The performance of the model is tested with respect to the predicted evolution of mass of calcium in solution and the average (in mass) particle size along time. Results obtained demonstrate a good agreement between the model time trajectories and the available experimental data for a number of different initial concentrations of reagents.
NASA Astrophysics Data System (ADS)
Subbareddy, Pramod; Candler, Graham
2009-11-01
Hybrid RANS/LES methods are being increasingly used for turbulent flow simulations in complex geometries. Spalart's detached eddy simulation (DES) model is one of the more popular ones. We are interested in examining the behavior of the Spalart-Allmaras (S-A) Detached Eddy Simulation (DES) model in its ``LES mode.'' The role of the near-wall functions present in the equations is analyzed and an explicit analogy between the S-A and a one-equation LES model based on the sub-grid kinetic energy is presented. A dynamic version of the S-A DES model is proposed based on this connection. Validation studies and results from DES and LES applications will be presented and the effect of the proposed modification will be discussed.
Multifunctional optomechanical dynamics in integrated silicon photonics
NASA Astrophysics Data System (ADS)
Li, Huan
Light can generate forces on matter. The nature of these forces is electromagnetic force, or Lorentz force. The emergence and rapid progress of nanotechnology provided an unprecedented platform where the very feeble optical forces began to play significant roles. The interactions between light and matter in nanoscale has been the focus of almost a decade of active theoretical and experimental investigations, which are still ongoing and constitute a whole new burgeoning branch of nanotechnology, nano-optomechanical systems (NOMS). In such context, the general goal of my research is to generate, enhance and control optical forces on silicon photonics platforms, with a focus on developing new functionalities and demonstrating novel effects, which will potentially lead to a new class of silicon photonic devices for a broad spectrum of applications. In this dissertation, the concept of optical force and the general background of the NOMS research area are first introduced. The general goal of the silicon photonics research area and the research presented in this dissertation is then described. Subsequently, the fundamental theory for optical force is summarized. The different methods to calculate optical forces are enumerated and briefly reviewed. Integrated hybrid plasmonic waveguide (HPWG) devices have been successfully fabricated and the enhanced optical forces experimentally measured for the first time. All-optical amplification of RF signals has been successfully demonstrated. The optical force generated by one laser is used to mechanically change the optical path and hence the output power of another laser. In addition, completely optically tunable mechanical nonlinear behavior has been demonstrated for the first time and systematically studied. Optomechanical photon shuttling between photonic cavities has been demonstrated with a "photon see-saw" device. This photon see-saw is a novel multicavity optomechanical device which consists of two photonic crystal
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...
Dynamical models of a sample of Population II stars
NASA Astrophysics Data System (ADS)
Levison, H. F.; Richstone, D. O.
1986-09-01
Dynamical models are constructed in order to investigate the implications of recent kinematic data of distant Population II stars on the emissivity distribution of those stars. Models are constructed using a modified Schwarzschild method in two extreme scale-free potentials, spherical and E6 elliptical. Both potentials produce flat rotation curves and velocity dispersion profiles. In all models, the distribution of stars in this sample is flat. Moreover, it is not possible to construct a model with a strictly spheroidal emissivity distribution. Most models have dimples at the poles. The dynamics of the models indicate that the system is supported by both the third integral and z angular momentum.
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 human spine using dynamic spline approach for vibrational simulation
NASA Astrophysics Data System (ADS)
Valentini, Pier Paolo
2012-12-01
This paper deals with the description of an innovative numerical dynamic model of the human spine for vibrational behavior assessment. The modeling approach is based on the use of the dynamic spline formalism in order to achieve a condensed description requiring a smaller set of variables but maintaining the nonlinear characteristic and the accuracy of a fully multibody dynamic model. The methodology has been validated by comparing the modal behavior of the spine sub-assembly to other models available in literature. Moreover, the proposed dynamic sub-system has been integrated into a two dimensional multibody model of a seated vehicle occupant in order to compute the seat-to-head transmissibility. This characteristic has been compared to those obtained using other spine sub-models. Both modal behavior and acceleration transmissibility computed with the proposed approach show a very good accordance with others coming from more complex models.
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
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.
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.
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…
The Spatial Representation of Dynamic Scenes - An Integrative Approach
NASA Astrophysics Data System (ADS)
Huff, Markus; Schwan, Stephan; Garsoffky, Bärbel
This paper addresses the spatial representation of dynamic scenes, particularly the question whether recognition performance is viewpoint dependent or viewpoint invariant. Beginning with the delimitation of static and dynamic scene recognition, the viewpoint dependency of visual recognition performance and the structure of the underlying mental representation are discussed. In the following, two parameters (an easy to identify event model and salient static features) are identified which appeared to be accountable for viewpoint dependency or viewpoint invariance of visual recognition performance for dynamic scenes.
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.
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
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.
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.
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.
Opinion dynamics model with weighted influence: Exit probability and dynamics
NASA Astrophysics Data System (ADS)
Biswas, Soham; Sinha, Suman; Sen, Parongama
2013-08-01
We introduce a stochastic model of binary opinion dynamics in which the opinions are determined by the size of the neighboring domains. The exit probability here shows a step function behavior, indicating the existence of a separatrix distinguishing two different regions of basin of attraction. This behavior, in one dimension, is in contrast to other well known opinion dynamics models where no such behavior has been observed so far. The coarsening study of the model also yields novel exponent values. A lower value of persistence exponent is obtained in the present model, which involves stochastic dynamics, when compared to that in a similar type of model with deterministic dynamics. This apparently counterintuitive result is justified using further analysis. Based on these results, it is concluded that the proposed model belongs to a unique dynamical class.
NASA Astrophysics Data System (ADS)
Anderson, Eric Ross
Landslides pose a persistent threat to El Salvador's population, economy and environment. Government officials share responsibility in managing this hazard by alerting populations when and where landslides may occur as well as developing and enforcing proper land use and zoning practices. This thesis addresses gaps in current knowledge between identifying precisely when and where slope failures may initiate and outlining the extent of the potential debris inundation areas. Improvements on hazard maps are achieved by considering a series of environmental variables to determine causal factors through spatial and temporal analysis techniques in Geographic Information Systems and remote sensing. The output is a more dynamic tool that links high resolution geomorphic and hydrological factors to daily precipitation. Directly incorporable into existing decision support systems, this allows for better disaster management and is transferable to other developing countries.
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.
Integrating molecular dynamics simulations with chemical probing experiments using SHAPE-FIT.
Kirmizialtin, Serdal; Hennelly, Scott P; Schug, Alexander; Onuchic, Jose N; Sanbonmatsu, Karissa Y
2015-01-01
Integration and calibration of molecular dynamics simulations with experimental data remain 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 force field 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
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
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.
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.
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.
NASA Technical Reports Server (NTRS)
Wong, R. C.; Owen, H. A., Jr.; Wilson, T. G.; Rodriguez, G. E.
1980-01-01
Small-signal modeling techniques are used in a system stability analysis of a breadboard version of a complete functional electrical power system. The system consists of a regulated switching dc-to-dc converter, a solar-cell-array simulator, a solar-array EMI filter, battery chargers and linear shunt regulators. Loss mechanisms in the converter power stage, including switching-time effects in the semiconductor elements, are incorporated into the modeling procedure to provide an accurate representation of the system without requiring frequency-domain measurements to determine the damping factor. The small-signal system model is validated by the use of special measurement techniques which are adapted to the poor signal-to-noise ratio encountered in switching-mode systems. The complete electrical power system with the solar-array EMI filter is shown to be stable over the intended range of operation.
A Jini-based dynamic service WebGIS model
NASA Astrophysics Data System (ADS)
Xuan, Wenling; Chen, Xiuwan; Huang, Zhaoqiang; Zhao, Gang
2007-06-01
The development of current GIS technology has evolved from single platform GIS system into WebGIS. However, The Geographic Information Services (GIServices) provision and application manner cannot meet the requirement of pervasive computing environment. Jini/JAVA technique, a dynamic distributed architecture for providing spontaneous network of services, might be a tool/solution to improve the GIService performance of current WebGIS. This paper studies and analyses Jini infrastructure and its dynamic service mechanism, designs a new WebGIS architecture with Jini-based dynamic service model. The experiment shows that Jini technique can be integrated into WebGIS and to realize the dynamic services organization and management.
NASA Astrophysics Data System (ADS)
Piacentino, Michael R.; Berends, David C.; Zhang, David C.; Gudis, Eduardo
2013-05-01
Two of the biggest challenges in designing U×V vision systems are properly representing high dynamic range scene content using low dynamic range components and reducing camera motion blur. SRI's MASI-HDR (Motion Adaptive Signal Integration-High Dynamic Range) is a novel technique for generating blur-reduced video using multiple captures for each displayed frame while increasing the effective camera dynamic range by four bits or more. MASI-HDR processing thus provides high performance video from rapidly moving platforms in real-world conditions in low latency real time, enabling even the most demanding applications on air, ground and water.
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.
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…
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…
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. PMID:26657065
Jamaica Integrated National Energy Planning Model
Macal, C.M.
1987-01-01
The Jamaica Integrated National Energy Planning (JINEP) Model was developed by Argonne National Laboratory under contract to the Jamaica Ministry of Mining, Energy, and Tourism. JINEP is a comprehensive model of the energy-producing sector and the major energy consuming sectors of Jamaica. The JINEP Model is an application of a modelling system, the Integrated Demand and Energy Supply (IDES) Model, that was previously developed at Argonne for the purpose of analyzing energy systems of developing countries. IDES is based on several years of experience in analyzing energy planning issues characteristic of developing countries.
Development of the Ball integrated telescope model (ITM)
NASA Astrophysics Data System (ADS)
Lieber, Michael D.
2002-07-01
As the complexity of telescope systems have increased, system engineering trades related to cost and performance issues have become correspondingly complex. The traditional methodology for end-to-end system modeling depends upon focused analysis and data handoff between disciplines - aptly termed the "bucket brigade" approach. For the last 7 years, Ball Aerospace has supported development of an integrated modeling environment for telescope performance modeling and analysis. The Integrated Telescope Model (ITM), a realization of this effort, has been used on several current large telescope programs such as the VLT, NGST, TPF and MAXIM. It permits the user to do both time simulations and analytical work in the spatial/temporal frequency domains. The individual discipline models in structural dynamics, optics, controls, signal processing, detector physics and disturbance modeling are seamlessly integrated into one cohesive model to efficiently support system level trades and analysis. The core of the model is formed by the optical toolbox implemented in MATLAB and realized in object-oriented Simulink environment. Both geometric and physical optical models can be constructed and interfaced to disturbances and detection models. The geometric approach includes ray tracing for exact modeling or sensitivity matrices for rapid execution. Spectral, transmission and polarization information is carried with each ray. The physical optics modules do wavefront propagation for analyzing diffraction effects under either with coherent or incoherent conditions. Coupling of the static offset models, quasi-static thermal deformations and structural dynamics with an optical model allows one to view the full range of disturbance effects on the resulting PSF. This paper addresses the overall model architecture, considerations and issues related to model execution speed, complexity and model resolution/validity. Example of a recent use of the model is reviewed.
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.
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...
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.
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.
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.
Mechanical Model of Traditional Thai Massage for Integrated Healthcare.
Rattanaphan, Salinee; Srichandr, Panya
2015-01-01
In this study, a mechanical model was developed, aiming to provide standardized and programmable traditional Thai massage (TTM) therapy to patients. The TTM was modeled and integrated into a mechanical hand (MH) system, and a prototype massage chair was built and tested for user satisfaction. Three fundamental principles of Thai massage were integrated: pull, press, and pin. Based on these principles, the mechanics of Thai massage was studied and a mathematical model was developed to describe the dynamics and conditions for the design and prototyping of an MH. On average, it was found that users were satisfied with the treatment and felt that the treatment was similar to that performed by human hands. According to the interview results, users indicated that they were likely to utilize the MH as an alternative to traditional massage. Therefore, integrated TTM with an MH may help healthcare providers deliver standardized, programmable massage therapy to patients as opposed to variable, inconsistent human massage. PMID:26288887
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.
A Normalization Model of Multisensory Integration
Ohshiro, Tomokazu; Angelaki, Dora E.; DeAngelis, Gregory C.
2011-01-01
Responses of neurons that integrate multiple sensory inputs are traditionally characterized in terms of a set of empirical principles. However, a simple computational framework that accounts for these empirical features of multisensory integration has not been established. We propose that divisive normalization, acting at the stage of multisensory integration, can account for many of the empirical principles of multisensory integration exhibited by single neurons, such as the principle of inverse effectiveness and the spatial principle. This model, which employs a simple functional operation (normalization) for which there is considerable experimental support, also accounts for the recent observation that the mathematical rule by which multisensory neurons combine their inputs changes with cue reliability. The normalization model, which makes a strong testable prediction regarding cross-modal suppression, may therefore provide a simple unifying computational account of the key features of multisensory integration by neurons. PMID:21552274
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.
Integrated Model Reduction and Control of Aircraft with Flexible Wings
NASA Technical Reports Server (NTRS)
Swei, Sean Shan-Min; Zhu, Guoming G.; Nguyen, Nhan T.
2013-01-01
This paper presents an integrated approach to the modeling and control of aircraft with exible wings. The coupled aircraft rigid body dynamics with a high-order elastic wing model can be represented in a nite dimensional state-space form. Given a set of desired output covariance, a model reduction process is performed by using the weighted Modal Cost Analysis (MCA). A dynamic output feedback controller, which is designed based on the reduced-order model, is developed by utilizing output covariance constraint (OCC) algorithm, and the resulting OCC design weighting matrix is used for the next iteration of the weighted cost analysis. This controller is then validated for full-order evaluation model to ensure that the aircraft's handling qualities are met and the uttering motion of the wings suppressed. An iterative algorithm is developed in CONDUIT environment to realize the integration of model reduction and controller design. The proposed integrated approach is applied to NASA Generic Transport Model (GTM) for demonstration.
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
Construction of a GP integration model.
Batterham, R; Southern, D; Appleby, N; Elsworth, G; Fabris, S; Dunt, D; Young, D
2002-04-01
There are frequent calls to improve integration of health services, within and between primary and secondary care sectors. In Australia, general medical practitioners (GPs) are central to these endeavours. This paper aims to better conceptualise GP integration and to develop a model and index based on this. A conceptualisation of integration is proposed based on integration fundamentally as an activity or process not structure. Integration process is the frequency and quality of episodes of information exchange involving the GP and another practitioner or patient and aimed at fulfilling the objectives of the health care system with regard to patient care. These are both direct responses to structural forces and emergent GP capacities and dispositions. The content of this typology was studied using Concept Mapping in 11 groups of GPs, consumers and other practitioners. Clusters of related statements within thematic domains were used as the basis for a provisional model. This was tested using confirmatory factor analysis in a data set derived from a national probability sample of 501 GPs. Some re-specification of the model was necessary, with three integration process factors needing to be subdivided. One factor congeneric model assumptions were used to identify the constituent items for these factors. The result was a model in which 50 items measured nine integration process factors and 20 items measured five enabling factors. Two distinct but correlated higher order factors, relating to individual patient care and public (or community) health--in contrast to a single higher order factor for integration--were identified. The re-specified model was tested with a new sample of 151 GPs and exhibited strong psychometric properties. Reliability and validity were acceptable to this stage of the indices' development. Further testing of the index is necessary to demonstrate factor invariance of the indices in other contexts as well as their utility in cross
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.
Quantifying chaotic dynamics from integrate-and-fire processes
NASA Astrophysics Data System (ADS)
Pavlov, A. N.; Pavlova, O. N.; Mohammad, Y. K.; Kurths, J.
2015-01-01
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.
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
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.
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.
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.
Dynamical and Physical Models of Ecliptic Comets
NASA Astrophysics Data System (ADS)
Dones, L.; Boyce, D. C.; Levison, H. F.; Duncan, M. J.
2005-08-01
In most simulations of the dynamical evolution of the cometary reservoirs, a comet is removed from the computer only if it is thrown from the Solar System or strikes the Sun or a planet. However, ejection or collision is probably not the fate of most active comets. Some, like 3D/Biela, disintegrate for no apparent reason, and others, such as the Sun-grazers, 16P/Brooks 2, and D/1993 F2 Shoemaker-Levy 9, are pulled apart by the Sun or a planet. Still others, like 107P/Wilson Harrington and D/1819 W1 Blanpain, are lost and then rediscovered as asteroids. Historically, amateurs discovered most comets. However, robotic surveys now dominate the discovery of comets (http://www.comethunter.de/). These surveys include large numbers of comets observed in a standard way, so the process of discovery is amenable to modeling. Understanding the selection effects for discovery of comets is a key problem in constructing models of cometary origin. To address this issue, we are starting new orbital integrations that will provide the best model to date of the population of ecliptic comets as a function of location in the Solar System and the size of the cometary nucleus, which we expect will vary with location. The integrations include the gravitational effects of the terrestrial and giant planets and, in some cases, nongravitational jetting forces. We will incorporate simple parameterizations for mantling and mass loss based upon detailed physical models. This approach will enable us to estimate the fraction of comets in different states (active, extinct, dormant, or disintegrated) and to track how the cometary size distribution changes as a function of distance from the Sun. We will compare the results of these simulations with bias-corrected models of the orbital and absolute magnitude distributions of Jupiter-family comets and Centaurs.
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...
Modeling "Soft" Errors in Bipolar Integrated Circuits
NASA Technical Reports Server (NTRS)
Zoutendyk, J.; Benumof, R.; Vonroos, O.
1985-01-01
Mathematical models represent single-event upset in bipolar memory chips. Physics of single-event upset in integrated circuits discussed in theoretical paper. Pair of companion reports present mathematical models to predict critical charges for producing single-event upset in bipolar randomaccess memory (RAM) chips.
Dynamic Models of Robots with Elastic Hinges
NASA Astrophysics Data System (ADS)
Krakhmalev, O. N.
2016-04-01
Two dynamic models of robots with elastic hinges are considered. Dynamic models are the implementation of the method based on the Lagrange equation using the transformation matrices of elastic coordinates. Dynamic models make it possible to determine the elastic deviations from programmed motion trajectories caused by elastic deformations in hinges, which are taken into account in directions of change of the corresponding generalized coordinates. One model is the exact implementation of the Lagrange method and makes it possible to determine the total elastic deviation of the robot from the programmed motion trajectory. Another dynamic model is approximated and makes it possible to determine small elastic quasi-static deviations and elastic vibrations. The results of modeling the dynamics by two models are compared to the example of a two-link manipulator system. The considered models can be used when performing investigations of the mathematical accuracy of the robots.
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. PMID:26754972
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.
NASA Astrophysics Data System (ADS)
Hafkenscheid, Edith; Warners-Ruckstuhl, Karin; van Oosterhout, Cees; Bergman, Steve; Davies, J. Huw; Govers, Rob; Hochard, Cyril; Kennan, Lorcan; Ross, Malcolm; Stampfli, Gérard M.; Vérard, Christan; Webb, Peter; Wortel, Rinus
2013-04-01
Effective hydrocarbon exploration in frontier regions requires an understanding of the tectonic and thermal evolution of basins, among other parameters or conditions. This is especially challenging when high-resolution local data are lacking, requiring reasonable interpolation and extrapolation of more regional knowledge. Some of the key first-order parameters influencing the presence and preservation of an economic petroleum system are the basin's vertical motion history and its thermal and stress evolution. To quantify these parameters in a physically consistent manner over several hundred million years, an integrated lithosphere-mantle dynamics modeling approach is needed. To this purpose, we embarked on developing a 3D dynamic model for the whole earth that links surface phenomena to mantle convection and lithosphere dynamics. The project involved a close collaboration between Shell and three universities, and integration of many disciplines and techniques. University of Lausanne developed 600-0 Ma global plate reconstructions with consistently evolving plate boundaries. The 300-0 Ma period was then adapted to be used as surface boundary condition for forward mantle convection modeling by Cardiff University, producing global predictions of base lithosphere temperatures, heat flow and mantle induced vertical surface motion through time. As a last step, Utrecht University developed a method to predict the lithospheric stress field through time based on integration of these mantle modeling results with the plate reconstruction model. This approach offers predictive scenarios and grids relevant to petroleum exploration that can be validated with local geological and geophysical data.
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.
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.
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
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)
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
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
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.
Dynamic time warp pattern matching using an integrated multiprocessing array
Weste, N.; Burr, D.J.; Ackland, B.D.
1983-08-01
Dynamic time warping is a well-established technique for time alignment and comparison of speech and image patterns. This paper describes the architecture, algorithms and design of a CMOS integrated processing array used for computing the dynamic time warp algorithm. Emphasis is placed on speech recognition applications because of the real-time constraints imposed by isolated and continuous speech recognition. High throughput is obtained through the use of extensive pipelining, parallel computation and simultaneous matching of multiple patterns. A realistic speech recognition application based on 40 nine-component linear predictor coefficient (LPC) vectors per word permits 20000 isolated word comparisons per second or, equivalently, real time recognition of a 20000 word vocabulary. The paper also illustrates a trend in IC design in which the architecture of the system leads to an embodiment which far outperforms solutions based on current design methodologies. 27 references.
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.
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. PMID:26871079
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.
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.
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).
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.
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.
System performance evaluation of the MAXIM concept with integrated modeling
NASA Astrophysics Data System (ADS)
Lieber, Michael D.; Gallagher, Dennis J.; Cash, Webster C.; Shipley, Ann F.
2003-03-01
The MAXIM (Mico-Arcsecond X-Ray Imaging Mission) and MAXIM Pathfinder, a technology precursor mission, is considered by NASA as 'visionary missions' in space astronomy. Currently the MAXIM mission design would fly multiple spacecraft in formation, each carrying precision optics, to direct x-rays from an astronomical source to collector and imaging spacecrafts. The mission architecture is complex and provides technical challenges in formaiton flying and external metrology, and target acquisition. To further develop the concept, an integrated model (IM) of the MAXIM and MAXIM Pathfinder was developed. Individual subsystem models from disciplines in structural dynamics, optics, controls, signal processing, detector physics and disturbance modelign are seamlessly integrated into one cohesive model to efficiently support system level trades and analysis. The optical system design is a unique combination of optical concepts and therefore results from the IM were extensively compared with ASAP optical software.
Hu, Yan; Wen, Jing-Ya; Li, Xiao-Li; Wang, Da-Zhou; Li, Yu
2013-10-15
A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach was developed for contaminated sites management. The contaminant concentrations were simulated by a validated interval dynamic multimedia fugacity model, and different guideline values for the same contaminant were represented as a fuzzy environmental guideline. Then, the probability of violating environmental guideline (Pv) can be determined by comparison between the modeled concentrations and the fuzzy environmental guideline, and the constructed relationship between the Pvs and environmental risk levels was used to assess the environmental risk level. The developed approach was applied to assess the integrated environmental risk at a case study site in China, simulated from 1985 to 2020. Four scenarios were analyzed, including "residential land" and "industrial land" environmental guidelines under "strict" and "loose" strictness. It was found that PAH concentrations will increase steadily over time, with soil found to be the dominant sink. Source emission in soil was the leading input and atmospheric sedimentation was the dominant transfer process. The integrated environmental risks primarily resulted from petroleum spills and coke ovens, while the soil environmental risks came from coal combustion. The developed approach offers an effective tool for quantifying variability and uncertainty in the dynamic multimedia integrated environmental risk assessment and the contaminated site management. PMID:23995555
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
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.
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.
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.
Quiver gauge theories and integrable lattice models
NASA Astrophysics Data System (ADS)
Yagi, Junya
2015-10-01
We discuss connections between certain classes of supersymmetric quiver gauge theories and integrable lattice models from the point of view of topological quantum field theories (TQFTs). The relevant classes include 4d N=1 theories known as brane box and brane tilling models, 3d N=2 and 2d N=(2,2) theories obtained from them by compactification, and 2d N=(0,2) theories closely related to these theories. We argue that their supersymmetric indices carry structures of TQFTs equipped with line operators, and as a consequence, are equal to the partition functions of lattice models. The integrability of these models follows from the existence of extra dimension in the TQFTs, which emerges after the theories are embedded in M-theory. The Yang-Baxter equation expresses the invariance of supersymmetric indices under Seiberg duality and its lower-dimensional analogs.
Which coordinate system for modelling path integration?
Vickerstaff, Robert J; Cheung, Allen
2010-03-21
Path integration is a navigation strategy widely observed in nature where an animal maintains a running estimate, called the home vector, of its location during an excursion. Evidence suggests it is both ancient and ubiquitous in nature, and has been studied for over a century. In that time, canonical and neural network models have flourished, based on a wide range of assumptions, justifications and supporting data. Despite the importance of the phenomenon, consensus and unifying principles appear lacking. A fundamental issue is the neural representation of space needed for biological path integration. This paper presents a scheme to classify path integration systems on the basis of the way the home vector records and updates the spatial relationship between the animal and its home location. Four extended classes of coordinate systems are used to unify and review both canonical and neural network models of path integration, from the arthropod and mammalian literature. This scheme demonstrates analytical equivalence between models which may otherwise appear unrelated, and distinguishes between models which may superficially appear similar. A thorough analysis is carried out of the equational forms of important facets of path integration including updating, steering, searching and systematic errors, using each of the four coordinate systems. The type of available directional cue, namely allothetic or idiothetic, is also considered. It is shown that on balance, the class of home vectors which includes the geocentric Cartesian coordinate system, appears to be the most robust for biological systems. A key conclusion is that deducing computational structure from behavioural data alone will be difficult or impossible, at least in the absence of an analysis of random errors. Consequently it is likely that further theoretical insights into path integration will require an in-depth study of the effect of noise on the four classes of home vectors. PMID:19962387
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…
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...
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.
EPA EXPOSURE MODELS LIBRARY AND INTEGRATED MODEL EVALUATION SYSTEM
The third edition of the U.S. Environmental Protection Agencys (EPA) EML/IMES (Exposure Models Library and Integrated Model Evaluation System) on CD-ROM is now available. The purpose of the disc is to provide a compact and efficient means to distribute exposure models, documentat...
Flexing computational muscle: modeling and simulation of musculotendon dynamics.
Millard, Matthew; Uchida, Thomas; Seth, Ajay; Delp, Scott L
2013-02-01
Muscle-driven simulations of human and animal motion are widely used to complement physical experiments for studying movement dynamics. Musculotendon models are an essential component of muscle-driven simulations, yet neither the computational speed nor the biological accuracy of the simulated forces has been adequately evaluated. Here we compare the speed and accuracy of three musculotendon models: two with an elastic tendon (an equilibrium model and a damped equilibrium model) and one with a rigid tendon. Our simulation benchmarks demonstrate that the equilibrium and damped equilibrium models produce similar force profiles but have different computational speeds. At low activation, the damped equilibrium model is 29 times faster than the equilibrium model when using an explicit integrator and 3 times faster when using an implicit integrator; at high activation, the two models have similar simulation speeds. In the special case of simulating a muscle with a short tendon, the rigid-tendon model produces forces that match those generated by the elastic-tendon models, but simulates 2-54 times faster when an explicit integrator is used and 6-31 times faster when an implicit integrator is used. The equilibrium, damped equilibrium, and rigid-tendon models reproduce forces generated by maximally-activated biological muscle with mean absolute errors less than 8.9%, 8.9%, and 20.9% of the maximum isometric muscle force, respectively. When compared to forces generated by submaximally-activated biological muscle, the forces produced by the equilibrium, damped equilibrium, and rigid-tendon models have mean absolute errors less than 16.2%, 16.4%, and 18.5%, respectively. To encourage further development of musculotendon models, we provide implementations of each of these models in OpenSim version 3.1 and benchmark data online, enabling others to reproduce our results and test their models of musculotendon dynamics. PMID:23445050
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.
Stochastic-dynamic Modelling of Morphodynamics
NASA Astrophysics Data System (ADS)
Eppel, D. P.; Kapitza, H.
The numerical prediction of coastal sediment motion over time spans of years and decades is hampered by the sediment's ability, when stirred by waves and currents, to often react not uniquely to the external forcing but rather to show some kind of internal dynamics whose characteristics are not directly linked to the external forcing. Analytical stability analyses of the sediment-water system indicate that instabilities of tidally forced sediment layers in shallow seas can occur on spatial scales smaller than and not related to the scales of the tidal components. The finite growth of these un- stable amplitides can be described in terms of Ginzburg-Landau equations. Examples are the formation of ripples, sand waves and sand dunes or the formation of shore- face connected ridges. Among others, analyses of time series of coastal profiles from Duck, South Carolina extending over several decades gave evidence for self-organized behaviour suggesting that some important sediment-water systems can be perceived as dissipative dynamical structures. The consequences of such behaviour for predicting morphodynamics has been pointed out: one would expect that there exist time horizons beyond which predictions in the traditional deterministic sense are not possible. One would have to look for statistical quantities containing information of some relevance such as phase-space densities of solutions, attractor sets and the like. This contribution is part of an effort to address the prediction problem of morphody- namics through process-oriented models containing stochastic parameterizations for bottom shear stresses, critical shear stresses, etc.; process-based models because they are directly related to the physical processes but in a stochastic form because it is known that the physical processes contain strong stochastic components. The final outcome of such a program would be the generation of an ensemble of solutions by Monte Carlo integrations of the stochastic model
Symbolic dynamics and computation in model gene networks.
Edwards, R.; Siegelmann, H. T.; Aziza, K.; Glass, L.
2001-03-01
We analyze a class of ordinary differential equations representing a simplified model of a genetic network. In this network, the model genes control the production rates of other genes by a logical function. The dynamics in these equations are represented by a directed graph on an n-dimensional hypercube (n-cube) in which each edge is directed in a unique orientation. The vertices of the n-cube correspond to orthants of state space, and the edges correspond to boundaries between adjacent orthants. The dynamics in these equations can be represented symbolically. Starting from a point on the boundary between neighboring orthants, the equation is integrated until the boundary is crossed for a second time. Each different cycle, corresponding to a different sequence of orthants that are traversed during the integration of the equation always starting on a boundary and ending the first time that same boundary is reached, generates a different letter of the alphabet. A word consists of a sequence of letters corresponding to a possible sequence of orthants that arise from integration of the equation starting and ending on the same boundary. The union of the words defines the language. Letters and words correspond to analytically computable Poincare maps of the equation. This formalism allows us to define bifurcations of chaotic dynamics of the differential equation that correspond to changes in the associated language. Qualitative knowledge about the dynamics found by integrating the equation can be used to help solve the inverse problem of determining the underlying network generating the dynamics. This work places the study of dynamics in genetic networks in a context comprising both nonlinear dynamics and the theory of computation. (c) 2001 American Institute of Physics. PMID:12779450
Modeling and simulation of consumer response to dynamic pricing.
Valenzuela, J.; Thimmapuram, P.; Kim, J
2012-08-01
Assessing the impacts of dynamic-pricing under the smart grid concept is becoming extremely important for deciding its full deployment. In this paper, we develop a model that represents the response of consumers to dynamic pricing. In the model, consumers use forecasted day-ahead prices to shift daily energy consumption from hours when the price is expected to be high to hours when the price is expected to be low while maintaining the total energy consumption as unchanged. We integrate the consumer response model into the Electricity Market Complex Adaptive System (EMCAS). EMCAS is an agent-based model that simulates restructured electricity markets. We explore the impacts of dynamic-pricing on price spikes, peak demand, consumer energy bills, power supplier profits, and congestion costs. A simulation of an 11-node test network that includes eight generation companies and five aggregated consumers is performed for a period of 1 month. In addition, we simulate the Korean power system.
Toward "optimal" integration of terrestrial biosphere models
NASA Astrophysics Data System (ADS)
Schwalm, Christopher R.; Huntzinger, Deborah N.; Fisher, Joshua B.; Michalak, Anna M.; Bowman, Kevin; Ciais, Philippe; Cook, Robert; El-Masri, Bassil; Hayes, Daniel; Huang, Maoyi; Ito, Akihiko; Jain, Atul; King, Anthony W.; Lei, Huimin; Liu, Junjie; Lu, Chaoqun; Mao, Jiafu; Peng, Shushi; Poulter, Benjamin; Ricciuto, Daniel; Schaefer, Kevin; Shi, Xiaoying; Tao, Bo; Tian, Hanqin; Wang, Weile; Wei, Yaxing; Yang, Jia; Zeng, Ning
2015-06-01
Multimodel ensembles (MME) are commonplace in Earth system modeling. Here we perform MME integration using a 10-member ensemble of terrestrial biosphere models (TBMs) from the Multiscale synthesis and Terrestrial Model Intercomparison Project (MsTMIP). We contrast optimal (skill based for present-day carbon cycling) versus naïve ("one model-one vote") integration. MsTMIP optimal and naïve mean land sink strength estimates (-1.16 versus -1.15 Pg C per annum respectively) are statistically indistinguishable. This holds also for grid cell values and extends to gross uptake, biomass, and net ecosystem productivity. TBM skill is similarly indistinguishable. The added complexity of skill-based integration does not materially change MME values. This suggests that carbon metabolism has predictability limits and/or that all models and references are misspecified. Resolving this issue requires addressing specific uncertainty types (initial conditions, structure, and references) and a change in model development paradigms currently dominant in the TBM community.
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.
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.
[Integrated model system for environmental policy analysis].
Jiang, Lin
2006-05-01
An integrated model system for environmental policy analysis is built up with a Computable General Equilibrium (CGE) model as a core model, which is linked with an environmental model, air dispersion model, and health effect model (exposure-response functions) in an explicit way, therefore the model system is capable of evaluating the effects of policies on environment, health and economy and their interactions comprehensively. This method is used to analyze the effects of Beijing presumptive (energy) taxes on air quality, health, welfare and economic growth, and the conclusion is that sole presumptive taxes may slow down the economic growth, but the presumptive taxes with green tax reform can promote Beijing sustainable development. PMID:16850855
Animal Models and Integrated Nested Laplace Approximations
Holand, Anna Marie; Steinsland, Ingelin; Martino, Sara; Jensen, Henrik
2013-01-01
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. PMID:23708299
[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
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
Local dynamic subgrid-scale models in channel flow
NASA Technical Reports Server (NTRS)
Cabot, William H.
1994-01-01
The dynamic subgrid-scale (SGS) model has given good results in the large-eddy simulation (LES) of homogeneous isotropic or shear flow, and in the LES of channel flow, using averaging in two or three homogeneous directions (the DA model). In order to simulate flows in general, complex geometries (with few or no homogeneous directions), the dynamic SGS model needs to be applied at a local level in a numerically stable way. Channel flow, which is inhomogeneous and wall-bounded flow in only one direction, provides a good initial test for local SGS models. Tests of the dynamic localization model were performed previously in channel flow using a pseudospectral code and good results were obtained. Numerical instability due to persistently negative eddy viscosity was avoided by either constraining the eddy viscosity to be positive or by limiting the time that eddy viscosities could remain negative by co-evolving the SGS kinetic energy (the DLk model). The DLk model, however, was too expensive to run in the pseudospectral code due to a large near-wall term in the auxiliary SGS kinetic energy (k) equation. One objective was then to implement the DLk model in a second-order central finite difference channel code, in which the auxiliary k equation could be integrated implicitly in time at great reduction in cost, and to assess its performance in comparison with the plane-averaged dynamic model or with no model at all, and with direct numerical simulation (DNS) and/or experimental data. Other local dynamic SGS models have been proposed recently, e.g., constrained dynamic models with random backscatter, and with eddy viscosity terms that are averaged in time over material path lines rather than in space. Another objective was to incorporate and test these models in channel flow.
Local dynamic subgrid-scale models in channel flow
NASA Astrophysics Data System (ADS)
Cabot, William H.
1994-12-01
The dynamic subgrid-scale (SGS) model has given good results in the large-eddy simulation (LES) of homogeneous isotropic or shear flow, and in the LES of channel flow, using averaging in two or three homogeneous directions (the DA model). In order to simulate flows in general, complex geometries (with few or no homogeneous directions), the dynamic SGS model needs to be applied at a local level in a numerically stable way. Channel flow, which is inhomogeneous and wall-bounded flow in only one direction, provides a good initial test for local SGS models. Tests of the dynamic localization model were performed previously in channel flow using a pseudospectral code and good results were obtained. Numerical instability due to persistently negative eddy viscosity was avoided by either constraining the eddy viscosity to be positive or by limiting the time that eddy viscosities could remain negative by co-evolving the SGS kinetic energy (the DLk model). The DLk model, however, was too expensive to run in the pseudospectral code due to a large near-wall term in the auxiliary SGS kinetic energy (k) equation. One objective was then to implement the DLk model in a second-order central finite difference channel code, in which the auxiliary k equation could be integrated implicitly in time at great reduction in cost, and to assess its performance in comparison with the plane-averaged dynamic model or with no model at all, and with direct numerical simulation (DNS) and/or experimental data. Other local dynamic SGS models have been proposed recently, e.g., constrained dynamic models with random backscatter, and with eddy viscosity terms that are averaged in time over material path lines rather than in space. Another objective was to incorporate and test these models in channel flow.
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.
System dynamics modeling of transboundary systems: the bear river basin model.
Sehlke, Gerald; Jacobson, Jake
2005-01-01
System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multipurpose national laboratory managed by the Department of Energy, has developed a system dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River basin, a transboundary basin that includes portions of Idaho, Utah, and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and ground water data and for simulating the interactions between these sources within a given basin. In addition, we also found that system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory, and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple "what-if" scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or ground water modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause-effect relationships in large-scale hydrological systems, for integrating disparate data, for incorporating output from traditional hydraulic/hydrologic models, and for integration of interdisciplinary data, information, and criteria to support better management decisions. PMID:16149968
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.
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
DynaMIT: the dynamic motif integration toolkit
Dassi, Erik; Quattrone, Alessandro
2016-01-01
De-novo motif search is a frequently applied bioinformatics procedure to identify and prioritize recurrent elements in sequences sets for biological investigation, such as the ones derived from high-throughput differential expression experiments. Several algorithms have been developed to perform motif search, employing widely different approaches and often giving divergent results. In order to maximize the power of these investigations and ultimately be able to draft solid biological hypotheses, there is the need for applying multiple tools on the same sequences and merge the obtained results. However, motif reporting formats and statistical evaluation methods currently make such an integration task difficult to perform and mostly restricted to specific scenarios. We thus introduce here the Dynamic Motif Integration Toolkit (DynaMIT), an extremely flexible platform allowing to identify motifs employing multiple algorithms, integrate them by means of a user-selected strategy and visualize results in several ways; furthermore, the platform is user-extendible in all its aspects. DynaMIT is freely available at http://cibioltg.bitbucket.org. PMID:26253738
Explicit stress integration of complex soil models
NASA Astrophysics Data System (ADS)
Zhao, Jidong; Sheng, Daichao; Rouainia, M.; Sloan, Scott W.
2005-10-01
In this paper, two complex critical-state models are implemented in a displacement finite element code. The two models are used for structured clays and sands, and are characterized by multiple yield surfaces, plastic yielding within the yield surface, and complex kinematic and isotropic hardening laws. The consistent tangent operators - which lead to a quadratic convergence when used in a fully implicit algorithm - are difficult to derive or may even not exist. The stress integration scheme used in this paper is based on the explicit Euler method with automatic substepping and error control. This scheme employs the classical elastoplastic stiffness matrix and requires only the first derivatives of the yield function and plastic potential. This explicit scheme is used to integrate the two complex critical-state models - the sub/super-loading surfaces model (SSLSM) and the kinematic hardening structure model (KHSM). Various boundary-value problems are then analysed. The results for the two models are compared with each other, as well with those from standard Cam-clay models. Accuracy and efficiency of the scheme used for the complex models are also investigated. Copyright
Chaotic dynamics in a simple dynamical green ocean plankton model
NASA Astrophysics Data System (ADS)
Cropp, Roger; Moroz, Irene M.; Norbury, John
2014-11-01
The exchange of important greenhouse gases between the ocean and atmosphere is influenced by the dynamics of near-surface plankton ecosystems. Marine plankton ecosystems are modified by climate change creating a feedback mechanism that could have significant implications for predicting future climates. The collapse or extinction of a plankton population may push the climate system across a tipping point. Dynamic green ocean models (DGOMs) are currently being developed for inclusion into climate models to predict the future state of the climate. The appropriate complexity of the DGOMs used to represent plankton processes is an ongoing issue, with models tending to become more complex, with more complicated dynamics, and an increasing propensity for chaos. We consider a relatively simple (four-population) DGOM of phytoplankton, zooplankton, bacteria and zooflagellates where the interacting plankton populations are connected by a single limiting nutrient. Chaotic solutions are possible in this 4-dimensional model for plankton population dynamics, as well as in a reduced 3-dimensional model, as we vary two of the key mortality parameters. Our results show that chaos is robust to the variation of parameters as well as to the presence of environmental noise, where the attractor of the more complex system is more robust than the attractor of its simplified equivalent. We find robust chaotic dynamics in low trophic order ecological models, suggesting that chaotic dynamics might be ubiquitous in the more complex models, but this is rarely observed in DGOM simulations. The physical equations of DGOMs are well understood and are constrained by conservation principles, but the ecological equations are not well understood, and generally have no explicitly conserved quantities. This work, in the context of the paucity of the empirical and theoretical bases upon which DGOMs are constructed, raises the interesting question of whether DGOMs better represent reality if they include
Becker, William J; Cropanzano, Russell
2011-03-01
Previous research pertaining to job performance and voluntary turnover has been guided by 2 distinct theoretical perspectives. First, the push-pull model proposes that there is a quadratic or curvilinear relationship existing between these 2 variables. Second, the unfolding model of turnover posits that turnover is a dynamic process and that a downward performance change may increase the likelihood of organizational separation. Drawing on decision theory, we propose and test an integrative framework. This approach incorporates both of these earlier models. Specifically, we argue that individuals are most likely to voluntarily exit when they are below-average performers who are also experiencing a downward performance change. Furthermore, the interaction between this downward change and performance partially accounts for the curvilinear relationship proposed by the push-pull model. Findings from a longitudinal field study supported this integrative theory. PMID:20853945
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.
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. PMID:25314550
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.
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.
FRF based joint dynamics modeling and identification
NASA Astrophysics Data System (ADS)
Mehrpouya, Majid; Graham, Eldon; Park, Simon S.
2013-08-01
Complex structures, such as machine tools, are comprised of several substructures connected to each other through joints to form the assembled structures. Joints can have significant contributions on the behavior of the overall assembly and ignoring joint effects in the design stage may result in considerable deviations from the actual dynamic behavior. The identification of joint dynamics enables us to accurately predict overall assembled dynamics by mathematically combining substructure dynamics through the equilibrium and compatibility conditions at the joint. The essence of joint identification is the determination of the difference between the measured overall dynamics and the rigidly coupled substructure dynamics. In this study, we investigate the inverse receptance coupling (IRC) method and the point-mass joint model, which considers the joint as lumped mass, damping and stiffness elements. The dynamic properties of the joint are investigated using both methods through a finite element (FE) simulation and experimental tests. `100
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
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.
Modeling dynamical geometry with lattice gas automata
Hasslacher, B.; Meyer, D.A.
1998-06-27
Conventional lattice gas automata consist of particles moving discretely on a fixed lattice. While such models have been quite successful for a variety of fluid flow problems, there are other systems, e.g., flow in a flexible membrane or chemical self-assembly, in which the geometry is dynamical and coupled to the particle flow. Systems of this type seem to call for lattice gas models with dynamical geometry. The authors construct such a model on one dimensional (periodic) lattices and describe some simulations illustrating its nonequilibrium dynamics.
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.
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, Jr.; 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.
Towards Measurable Types for Dynamical Process Modeling Languages
Mjolsness, Eric
2011-01-01
Process modeling languages such as “Dynamical Grammars” are highly expressive in the processes they model using stochastic and deterministic dynamical systems, and can be given formal semantics in terms of an operator algebra. However such process languages may be more limited in the types of objects whose dynamics is easily expressible. For many applications in biology, the dynamics of spatial objects in particular (including combinations of discrete and continuous spatial structures) should be formalizable at a high level of abstraction. We suggest that this may be achieved by formalizing such objects within a type system endowed with type constructors suitable for complex dynamical objects. To this end we review and illustrate the operator algebraic formulation of heterogeneous process modeling and semantics, extending it to encompass partial differential equations and intrinsic graph grammar dynamics. We show that in the operator approach to heterogeneous dynamics, types require integration measures. From this starting point, “measurable” object types can be enriched with generalized metrics under which approximation can be defined. The resulting measurable and “metricated” types can be built up systematically by type constructors such as vectors, products, and labelled graphs. We find conditions under which functions and quotients can be added as constructors of measurable and metricated types. PMID:21572536
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
Pathological gambling and couple: towards an integrative systemic model.
Cunha, Diana; Relvas, Ana Paula
2014-06-01
This article is a critical literature review of pathological gambling focused in the family factors, particularly in the couple dynamics. Its main goal is to develop an explicative integrative systemic model of pathological gambling, based in these couple dynamics. To achieve that aim, a bibliography search was made, using on-line data bases (e.g., EBSCO Host) and recognized books in pathological gambling subject, as well as in the systemic approach in general. This process privileged the recent works (about 70 % of the reviewed literature was published in the last decade), however, also considered some classic works (the oldest one dates back to 1970). The guiding focus of this literature search evolves according to the following steps: (1) search of general comprehension of pathological gambling (19 references), (2) search specification to the subject "pathological gambling and family" (24 references), (3) search specification to the subject "pathological gambling and couple"(11 references), (4) search of systemic information which integrates the evidence resulted in the previous steps (4 references). The developed model is constituted by different levels of systemic complexity (social context, family of origin, couple and individual) and explains the problem as a signal of perturbation in the marital subsystem vital functions (e.g., power and control) though the regularities of marital dynamics of pathological gamblers. Furthermore, it gives theoretical evidence of the systemic familiar intervention in the pathological gambling. PMID:23423730
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 research on healthcare integrating model of medical information system].
Lü, Xudong; Duan, Huilong
2005-02-01
System integration is inevitable since there are lots of heterogeneous medical information systems in the complicated medical environment. The current medical communication standards often focus on one aspect of the integration and do not provide a general scheme. Based on the analysis of the application of medical integration, the medical integration model HIM (Healthcare integrating model) is put forward, and the dataflow integration framework, function integration framework and interface integration framework in the HIM are designed subsequently. HIM provides a 3-D scheme for the integration of medical information systems, which not only contains the three aspects of integration application vertically, but covers the whole medical area horizontally. PMID:15762128
A Microcomputer Dynamical Modelling System.
ERIC Educational Resources Information Center
Ogborn, Jon; Wong, Denis
1984-01-01
Presents a system that permits students to engage directly in the process of modelling and to learn some important lessons about models and classes of models. The system described currently runs on RML 380Z and 480Z, Apple II and IIe, and BBC model B microcomputers. (JN)
Dynamic modeling of emulsion polymerization reactors
Penlidis, A.; Hamielec, A.E.; MacGregor, J.F.
1985-06-01
This paper is a survey of recent published works on the dynamic and steady state modeling of emulsion homo- and copolymerization in batch, semicontinuous , and continuous latex reactors. Contributions to our understanding of diffusion-controlled termination and propagation reactions, molecular weight, long chain branching and crosslinking development, polymer particle nucleation, and of the dynamics of continuous emulsion polymerization are critically reviewed.
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
Pinto, Rogério M; Spector, Anya Y; Valera, Pamela A
2011-08-01
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: (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
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.
Flexible aircraft dynamic modeling for dynamic analysis and control synthesis
NASA Technical Reports Server (NTRS)
Schmidt, David K.
1989-01-01
The linearization and simplification of a nonlinear, literal model for flexible aircraft is highlighted. Areas of model fidelity that are critical if the model is to be used for control system synthesis are developed and several simplification techniques that can deliver the necessary model fidelity are discussed. These techniques include both numerical and analytical approaches. An analytical approach, based on first-order sensitivity theory is shown to lead not only to excellent numerical results, but also to closed-form analytical expressions for key system dynamic properties such as the pole/zero factors of the vehicle transfer-function matrix. The analytical results are expressed in terms of vehicle mass properties, vibrational characteristics, and rigid-body and aeroelastic stability derivatives, thus leading to the underlying causes for critical dynamic characteristics.
Complexity and network dynamics in physiological adaptation: an integrated view.
Baffy, György; Loscalzo, Joseph
2014-05-28
Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. PMID:24751342
Dynamic properties of integrated nanostructure on metallic surface
NASA Astrophysics Data System (ADS)
Zerirgui, D.; Tigrine, R.; Bourahla, B.
2012-02-01
We investigated the vibration properties of integrated nanostructure on crystalline surface. The embedded chain of molecules is parallel to y-axis and takes three different positions: top, hollow, and bridge. The vibrational dynamics of the structure is considered within the harmonic approximation framework. The evanescent and propagating vibrational field of the perfect lattice is determined and interpreted. The presence of the diatomic molecule chain breakdown the translation symmetry in one direction, and gives rise to localized states on its neighborhood. Our study is based on the matching method and the Green functions, the spectral and state densities associated to localized modes are determined and calculated numerically. Our results show that the presence of the inhomogeneity contribute to the creation of new branches of localized vibrational modes, and their number and feature depend strongly on structural parameters of the system and the position of the diatomic chain.
Integrative variable selection via Bayesian model uncertainty.
Quintana, M A; Conti, D V
2013-12-10
We are interested in developing integrative approaches for variable selection problems that incorporate external knowledge on a set of predictors of interest. In particular, we have developed an integrative Bayesian model uncertainty (iBMU) method, which formally incorporates multiple sources of data via a second-stage probit model on the probability that any predictor is associated with the outcome of interest. Using simulations, we demonstrate that iBMU leads to an increase in power to detect true marginal associations over more commonly used variable selection techniques, such as least absolute shrinkage and selection operator and elastic net. In addition, iBMU leads to a more efficient model search algorithm over the basic BMU method even when the predictor-level covariates are only modestly informative. The increase in power and efficiency of our method becomes more substantial as the predictor-level covariates become more informative. Finally, we demonstrate the power and flexibility of iBMU for integrating both gene structure and functional biomarker information into a candidate gene study investigating over 50 genes in the brain reward system and their role with smoking cessation from the Pharmacogenetics of Nicotine Addiction and Treatment Consortium. PMID:23824835
Integrated engineering modeling for air breathing rockets
NASA Astrophysics Data System (ADS)
Chitilappilly, Lazar T.; Subramanyam, J. D. A.
An innovative aerodynamic-propulsion-flight integrated modeling is carried out for airbreathing rockets, the propulsion of which has primary dependence on flight conditions. The integrated modeling is highly beneficial for design and analysis of accelerating air breathing rockets characterized by continuously varying flight conditions. The details of the modeling is described; the force accounting, trajectory analysis, solving the flow in the sub-systems (air intake, primary rocket, secondary combustion chamber and secondary nozzle), matching the subsystem flow fields and determining the mode of operation. Operational features are listed of the computer software developed, air breathing integrated design and analysis engineering software. It gives all the propulsion and flight parameters from take-off of the rocket to end of flight and has been instrumental in the design of the research air breathing rocket ABR-200(I). The hundreds of flight performance analyses required for design is possible by the engineering approach adopted for solving the propulsor flow field. The software results are compared with ejector mode and connected pipe mode static tests. The overall validation of the software is achieved by flight tests; the performance predictions have matched exactly with that measured during thee first and second flights of the ABR-200(I).
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
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
NASA Astrophysics Data System (ADS)
Daniels, Bryan C.; Nemenman, Ilya
2015-08-01
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.
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.
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.
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. PMID:27090842
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.
Integrating stochasticity and network structure into an epidemic model
Dangerfield, C. E.; Ross, J. V.; Keeling, M. J.
2009-01-01
While the foundations of modern epidemiology are based upon deterministic models with homogeneous mixing, it is being increasingly realized that both spatial structure and stochasticity play major roles in shaping epidemic dynamics. The integration of these two confounding elements is generally ascertained through numerical simulation. Here, for the first time, we develop a more rigorous analytical understanding based on pairwise approximations to incorporate localized spatial structure and diffusion approximations to capture the impact of stochasticity. Our results allow us to quantify, analytically, the impact of network structure on the variability of an epidemic. Using the susceptible–infectious–susceptible framework for the infection dynamics, the pairwise stochastic model is compared with the stochastic homogeneous-mixing (mean-field) model—although to enable a fair comparison the homogeneous-mixing parameters are scaled to give agreement with the pairwise dynamics. At equilibrium, we show that the pairwise model always displays greater variation about the mean, although the differences are generally small unless the prevalence of infection is low. By contrast, during the early epidemic growth phase when the level of infection is increasing exponentially, the pairwise model generally shows less variation. PMID:18974032
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
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. PMID:26799437
Integrating Cellular Metabolism into a Multiscale Whole-Body Model
Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars
2012-01-01
Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351
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
Single timepoint models of dynamic systems
Sachs, K.; Itani, S.; Fitzgerald, J.; Schoeberl, B.; Nolan, G. P.; Tomlin, C. J.
2013-01-01
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
Computational modeling of dynamic behaviors of human teeth.
Liao, Zhipeng; Chen, Junning; Zhang, Zhongpu; Li, Wei; Swain, Michael; Li, Qing
2015-12-16
Despite the importance of dynamic behaviors of dental and periodontal structures to clinics, the biomechanical roles of anatomic sophistication and material properties in quantification of vibratory characteristics remain under-studied. This paper aimed to generate an anatomically accurate and structurally detailed 3D finite element (FE) maxilla model and explore the dynamic behaviors of human teeth through characterizing the natural frequencies (NFs) and mode shapes. The FE models with different levels of structural integrities and material properties were established to quantify the effects of modeling techniques on the computation of vibratory characteristics. The results showed that the integrity of computational model considerably influences the characterization of vibratory behaviors, as evidenced by declined NFs and perceptibly altered mode shapes resulting from the models with higher degrees of completeness and accuracy. A primary NF of 889Hz and the corresponding mode shape featuring linguo-buccal vibration of maxillary right 2nd molar were obtained based on the complete maxilla model. It was found that the periodontal ligament (PDL), a connective soft tissue, plays an important role in quantifying NFs. It was also revealed that damping and heterogeneity of materials contribute to the quantification of vibratory characteristics. The study provided important biomechanical insights and clinical references for future studies on dynamic behaviors of dental and periodontal structures. PMID:26584964
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.
Dynamics of two nonlinear oligopoly models
NASA Astrophysics Data System (ADS)
Ibrahim, Adyda
2014-06-01
This paper considers an n firms oligopoly model with isoelastic demand function and linear cost function. This model is introduced in two different dynamical systems. In the first system, firms are assumed have naive expectation, while in the second system, firms are assumed to have bounded rationality. We study the dynamics of both dynamical systems in the special case of firms behaving identically. The main result shows that as the number of firm increases, the equilibrium in the first system becomes unstable when the number of firms is greater than four, while in the second system, there is a change in the region of stability for the equilibrium.
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.
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)…
Dynamics of the Standard Model
NASA Astrophysics Data System (ADS)
Donoghue, John F.; Golowich, Eugene; Holstein, Barry R.
2014-04-01
Preface; 1. Inputs to the Standard Model; 2. Interactions of the Standard Model; 3. Symmetries and anomalies; 4. Introduction to effective field theory; 5. Charged leptons; 6. Neutrinos; 7. Effective field theory for low energy QCD; 8. Weak interactions of Kaons; 9. Mass mixing and CP violation; 10. The Nc-1 expansion; 11. Phenomenological models; 12. Baryon properties; 13. Hadron spectroscopy; 14. Weak interactions of heavy quarks; 15. The Higgs boson; 16. The electroweak sector; Appendixes; References; Index.
Dynamical model for DNA sequences
NASA Astrophysics Data System (ADS)
Allegrini, P.; Barbi, M.; Grigolini, P.; West, B. J.
1995-11-01
We address the problem of DNA sequences, developing a ``dynamical'' method based on the assumption that the statistical properties of DNA paths are determined by the joint action of two processes, one deterministic with long-range correlations, and the other random and δ-function correlated. The generator of the deterministic evolution is a nonlinear map, belonging to a class of maps recently tailored to mimic the processes of weak chaos that are responsible for the birth of anomalous diffusion. It is assumed that the deterministic process corresponds to unknown biological rules that determine the DNA path, whereas the noise mimics the influence of an infinite-dimensional environment on the biological process under study. We prove that the resulting diffusion process, if the effect of the random process is neglected, is an α-stable Lévy process with 1<α<2. We also show that, if the diffusion process is determined by the joint action of the deterministic and the random process, the correlation effects of the ``deterministic dynamics'' are cancelled on the short-range scale, but show up in the long-range one. We denote our prescription to generate statistical sequences as the copying mistake map (CMM). We carry out our analysis of several DNA sequences and their CMM realizations with a variety of techniques, and we especially focus on a method of regression to equilibrium, which we call the Onsager analysis. With these techniques we establish the statistical equivalence of the real DNA sequences with their CMM realizations. We show that long-range correlations are present in exons as well as in introns, but are difficult to detect, since the exon ``dynamics'' is shown to be determined by the entanglement of three distinct and independent CMM's.
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].
Dynamic Complexity Study of Nuclear Reactor and Process Heat Application Integration
J'Tia Patrice Taylor; David E. Shropshire
2009-09-01
Abstract This paper describes the key obstacles and challenges facing the integration of nuclear reactors with process heat applications as they relate to dynamic issues. The paper also presents capabilities of current modeling and analysis tools available to investigate these issues. A pragmatic approach to an analysis is developed with the ultimate objective of improving the viability of nuclear energy as a heat source for process industries. The extension of nuclear energy to process heat industries would improve energy security and aid in reduction of carbon emissions by reducing demands for foreign derived fossil fuels. The paper begins with an overview of nuclear reactors and process application for potential use in an integrated system. Reactors are evaluated against specific characteristics that determine their compatibility with process applications such as heat outlet temperature. The reactor system categories include light water, heavy water, small to medium, near term high-temperature, and far term high temperature reactors. Low temperature process systems include desalination, district heating, and tar sands and shale oil recovery. High temperature processes that support hydrogen production include steam reforming, steam cracking, hydrogen production by electrolysis, and far-term applications such as the sulfur iodine chemical process and high-temperature electrolysis. A simple static matching between complementary systems is performed; however, to gain a true appreciation for system integration complexity, time dependent dynamic analysis is required. The paper identifies critical issues arising from dynamic complexity associated with integration of systems. Operational issues include scheduling conflicts and resource allocation for heat and electricity. Additionally, economic and safety considerations that could impact the successful integration of these systems are considered. Economic issues include the cost differential arising due to an integrated
Combining multimedia models with integrated urban water system models for micropollutants.
De Keyser, W; Gevaert, V; Verdonck, F; Nopens, I; De Baets, B; Vanrolleghem, P A; Mikkelsen, P S; Benedetti, L
2010-01-01
Integrated urban water system (IUWS) modeling aims at assessing the quality of the surface water receiving the urban emissions through sewage treatment plants, combined sewer overflows (CSOs) and stormwater drainage systems. However, some micropollutants tend to appear in more than one environmental medium (air, water, sediment, soil, groundwater, etc.). In this work, a multimedia fate and transport model (MFTM) is "wrapped around" a dynamic IUWS model for organic micropollutants to enable integrated environmental assessment. The combined model was tested on a hypothetical catchment using two scenarios: on the one hand a reference scenario with a combined sewerage system and on the other hand a stormwater infiltration pond scenario, as an example of a sustainable urban drainage system (SUDS). A case for Bis(2-ethylhexyl) phthalate (DEHP) was simulated and resulted in reduced surface water concentrations for the latter scenario. However, the model also showed that this was at the expense of increased fluxes to air, groundwater and infiltration pond soil. The latter effects are generally not included in IUWS models, whereas MTFMs usually do not consider dynamic surface water concentrations,; hence the combined model approach provides a better basis for integrated environmental assessment of micropollutants' fate in urban environments. PMID:20935380
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.
Dynamic and Structural Gas Turbine Engine Modeling
NASA Technical Reports Server (NTRS)
Turso, James A.
2003-01-01
Model the interactions between the structural dynamics and the performance dynamics of a gas turbine engine. Generally these two aspects are considered separate, unrelated phenomena and are studied independently. For diagnostic purposes, it is desirable to bring together as much information as possible, and that involves understanding how performance is affected by structural dynamics (if it is) and vice versa. This can involve the relationship between thrust response and the excitation of structural modes, for instance. The job will involve investigating and characterizing these dynamical relationships, generating a model that incorporates them, and suggesting and/or developing diagnostic and prognostic techniques that can be incorporated in a data fusion system. If no coupling is found, at the least a vibration model should be generated that can be used for diagnostics and prognostics related to blade loss, for instance.
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 d