Integrated dynamics modeling for supercavitating vehicle systems
NASA Astrophysics Data System (ADS)
Kim, Seonhong; Kim, Nakwan
2015-06-01
We have performed integrated dynamics modeling for a supercavitating vehicle. A 6-DOF equation of motion was constructed by defining the forces and moments acting on the supercavitating body surface that contacted water. The wetted area was obtained by calculating the cavity size and axis. Cavity dynamics were determined to obtain the cavity profile for calculating the wetted area. Subsequently, the forces and moments acting on each wetted part-the cavitator, fins, and vehicle body-were obtained by physical modeling. The planing force-the interaction force between the vehicle transom and cavity wall-was calculated using the apparent mass of the immersed vehicle transom. We integrated each model and constructed an equation of motion for the supercavitating system. We performed numerical simulations using the integrated dynamics model to analyze the characteristics of the supercavitating system and validate the modeling completeness. Our research enables the design of high-quality controllers and optimal supercavitating systems.
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.
An integrated model of Plasmodium falciparum dynamics.
McKenzie, F Ellis; Bossert, William H
2005-02-07
The within-host and between-host dynamics of malaria are linked in myriad ways, but most obviously by gametocytes, the parasite blood forms transmissible from human to mosquito. Gametocyte dynamics depend on those of non-transmissible blood forms, which stimulate immune responses, impeding transmission as well as within-host parasite densities. These dynamics can, in turn, influence antigenic diversity and recombination between genetically distinct parasites. Here, we embed a differential-equation model of parasite-immune system interactions within each of the individual humans represented in a discrete-event model of Plasmodium falciparum transmission, and examine the effects of human population turnover, parasite antigenic diversity, recombination, and gametocyte production on the dynamics of malaria. Our results indicate that the local persistence of P. falciparum increases with turnover in the human population and antigenic diversity in the parasite, particularly in combination, and that antigenic diversity arising from meiotic recombination in the parasite has complex differential effects on the persistence of founder and progeny genotypes. We also find that reductions in the duration of individual human infectivity to mosquitoes, even if universal, produce population-level effects only if near-absolute, and that, in competition, the persistence and prevalence of parasite genotypes with gametocyte production concordant with data exceed those of genotypes with higher gametocyte production. This new, integrated approach provides a framework for investigating relationships between pathogen dynamics within an individual host and pathogen dynamics within interacting host and vector populations.
Dynamic Data Integration Using Streamline Models
NASA Astrophysics Data System (ADS)
Datta-Gupta, A.
2002-12-01
Recent developments in petroleum reservoir characterization and in the management of uncertainty have lead to the ability of the industry to routinely generate large multimillion-cell detailed geologic models. Reconciling such high-resolution models to dynamic reservoir behavior (transient pressure and tracer response, multiphase production history) still remains an outstanding challenge because of the high computational costs associated with the solution of large inverse problems. Streamline-based flow simulation models can offer significant potential in this regard. In this presentation we will exploit an analogy between streamlines and seismic ray tracing to develop an efficient formalism for dynamic data integration into high-resolution subsurface models. Utilizing concepts from the asymptotic ray theory in seismic and diffusive electromagnetic imaging, we will generalize the streamline approach to incorporate transient pressure, tracer and multiphase production response during subsurface characterization. Data integration will be carried out in a manner analogous to seismic tomography and waveform imaging by first matching the `arrival time' and then the `amplitude' of the production response. Several field examples from the oil field and environmental applications will demonstrate the practical feasibility of the approach.
An integrated dynamic model of a flexible wind turbine
NASA Astrophysics Data System (ADS)
Bongers, Peter M. M.; Bierbooms, Wim A. A.; Dijkstra, Sjoerd; Vanholten, Theo
1990-06-01
A model to study the dynamic behavior of flexible wind turbines was developed. The different subsystems of the wind turbine are individually modeled with about the same degree of accuracy. The aerodynamic part describes wind shear, gravity effects, unsteady effects, and dynamic inflow. The rotor blades are provided with degrees of freedom in lag and flap directions. The tower construction is modeled including the first bending mode. The first torsional mode of the transmission is included in the model. The model of synchronous generator with dc link consists of a nonlinear fourth order model, including saturation effects. The different models of the subsystems are coupled into one integrated dynamic model which is implemented as simulation code in the DUWECS (Delf University Wind Energy Converter Simulation Package) program. The DUWECS program is developed in such a manner that it is an easy to handle tool for the study of the dynamic features of wind turbine systems.
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
Dynamical many-body localization in an integrable model
NASA Astrophysics Data System (ADS)
Keser, Ayin C.; Ganeshan, Sriram; Refael, Gil; Galitski, Victor
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 manifest both localization and delocalization in momentum space. We explicitly show that, for this model, the energy being bounded at long times is neither a necessary nor a sufficient condition for dynamical localization. We present a set of integrals of motion, which can serve as a fundamental diagnostic of dynamical localization. We also propose an experimental scheme, involving voltage-biased Josephson junctions, to realize such many-body kicked models.
The dynamics of multimodal integration: The averaging diffusion model.
Turner, Brandon M; Gao, Juan; Koenig, Scott; Palfy, Dylan; L McClelland, James
2017-03-08
We combine extant theories of evidence accumulation and multi-modal integration to develop an integrated framework for modeling multimodal integration as a process that unfolds in real time. Many studies have formulated sensory processing as a dynamic process where noisy samples of evidence are accumulated until a decision is made. However, these studies are often limited to a single sensory modality. Studies of multimodal stimulus integration have focused on how best to combine different sources of information to elicit a judgment. These studies are often limited to a single time point, typically after the integration process has occurred. We address these limitations by combining the two approaches. Experimentally, we present data that allow us to study the time course of evidence accumulation within each of the visual and auditory domains as well as in a bimodal condition. Theoretically, we develop a new Averaging Diffusion Model in which the decision variable is the mean rather than the sum of evidence samples and use it as a base for comparing three alternative models of multimodal integration, allowing us to assess the optimality of this integration. The outcome reveals rich individual differences in multimodal integration: while some subjects' data are consistent with adaptive optimal integration, reweighting sources of evidence as their relative reliability changes during evidence integration, others exhibit patterns inconsistent with optimality.
A Dynamic Theory of World Press Motivation: An Integrative Model.
ERIC Educational Resources Information Center
Schillinger, Elisabeth
Addressing the dynamic and integrative nature of the world's press systems, this paper presents a comprehensive press theory and accompanying model. Three "primary motives"--survival, ideology, and market--are posited as determinants of press systems, using the nation state as the unit of analysis. The premises of the paper are: (1)…
A System Dynamics Model for Integrated Decision Making ...
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, environmental, and ecological factors into their decisions to promote community sustainability. To help achieve this goal, EPA researchers have developed systems approaches to account for the linkages among resources, assets, and outcomes managed by a community. System dynamics (SD) is a member of the family of systems approaches and provides a framework for dynamic modeling that can assist with assessing and understanding complex issues across multiple dimensions. To test the utility of such tools when applied to a real-world situation, the EPA has developed a prototype SD model for community sustainability using the proposed Durham-Orange Light Rail Project (D-O LRP) as a case study.The EPA D-O LRP SD modeling team chose the proposed D-O LRP to demonstrate that an integrated modeling approach could represent the multitude of related cross-sectoral decisions that would be made and the cascading impacts that could result from a light rail transit system connecting Durham and Chapel Hill, NC. In keeping with the SHC vision described above, the proposal for the light rail is a starting point solution for the more intractable problems of population growth, unsustainable land use, environmenta
A System Dynamics Model for Integrated Decision Making ...
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, environmental, and ecological factors into their decisions to promote community sustainability. To help achieve this goal, EPA researchers have developed systems approaches to account for the linkages among resources, assets, and outcomes managed by a community. System dynamics (SD) is a member of the family of systems approaches and provides a framework for dynamic modeling that can assist with assessing and understanding complex issues across multiple dimensions. To test the utility of such tools when applied to a real-world situation, the EPA has developed a prototype SD model for community sustainability using the proposed Durham-Orange Light Rail Project (D-O LRP) as a case study.The EPA D-O LRP SD modeling team chose the proposed D-O LRP to demonstrate that an integrated modeling approach could represent the multitude of related cross-sectoral decisions that would be made and the cascading impacts that could result from a light rail transit system connecting Durham and Chapel Hill, NC. In keeping with the SHC vision described above, the proposal for the light rail is a starting point solution for the more intractable problems of population growth, unsustainable land use, environmenta
SMI: a structural dynamics toolbox for integrated modeling
NASA Astrophysics Data System (ADS)
Mueller, Michael; Baier, Horst
2002-07-01
In cooperation with the European Southern Observatory (ESO), the Institute of Lightweight Structures (LLB), Technische Universtitaet Muenchen, has developed the Structural Modeling Interface Toolbox (SMI), a Matlab based software package for creation of a dynamical model of a telescope structure. It is called Interface, since it uses the modal data of a finite element (FE) analysis and creates a dynamic model to be used within a time-dependent control loop simulation in the Matlab/Simulink environment. SMI is part of the Integrated Modeling Toolbox (IMT) developed in a joint effort by ESO, Astrium GmbH and LLB. Since SMI can read modal data in a general format, it is not depending on the FE-software. In addition to that, an interface to the FE-package ANSYS has been developed. It allows the variation of parameters and some settings for the FE-analysis directly within SMI. Both, force excitation like windloads and base excitation like micro seismic perturbations can be included. Several tools for model reduction are provided. Some of them are modal based, like effective modal masses, others are general model reduction procedures from control engineering like balanced truncation. For the evaluation of the reduced models, transfer functions of different models can be displayed in a Bode-plot. Time characteristics like step response or impulse response are also available. Moreover, for a typical excitation PSD the response PSD can be computed. This response can either be compared to the response of an exact model or to measured data and the rms-error can be calculated. The final result is a linear statespace model of the structure and a Simulink block, which can be included into a Simulink model.
Human growth and body weight dynamics: an integrative systems model.
Rahmandad, Hazhir
2014-01-01
Quantifying human weight and height dynamics due to growth, aging, and energy balance can inform clinical practice and policy analysis. This paper presents the first mechanism-based model spanning full individual life and capturing changes in body weight, composition and height. Integrating previous empirical and modeling findings and validated against several additional empirical studies, the model replicates key trends in human growth including A) Changes in energy requirements from birth to old ages. B) Short and long-term dynamics of body weight and composition. C) Stunted growth with chronic malnutrition and potential for catch up growth. From obesity policy analysis to treating malnutrition and tracking growth trajectories, the model can address diverse policy questions. For example I find that even without further rise in obesity, the gap between healthy and actual Body Mass Indexes (BMIs) has embedded, for different population groups, a surplus of 14%-24% in energy intake which will be a source of significant inertia in obesity trends. In another analysis, energy deficit percentage needed to reduce BMI by one unit is found to be relatively constant across ages. Accompanying documented and freely available simulation model facilitates diverse applications customized to different sub-populations.
Human Growth and Body Weight Dynamics: An Integrative Systems Model
Rahmandad, Hazhir
2014-01-01
Quantifying human weight and height dynamics due to growth, aging, and energy balance can inform clinical practice and policy analysis. This paper presents the first mechanism-based model spanning full individual life and capturing changes in body weight, composition and height. Integrating previous empirical and modeling findings and validated against several additional empirical studies, the model replicates key trends in human growth including A) Changes in energy requirements from birth to old ages. B) Short and long-term dynamics of body weight and composition. C) Stunted growth with chronic malnutrition and potential for catch up growth. From obesity policy analysis to treating malnutrition and tracking growth trajectories, the model can address diverse policy questions. For example I find that even without further rise in obesity, the gap between healthy and actual Body Mass Indexes (BMIs) has embedded, for different population groups, a surplus of 14%–24% in energy intake which will be a source of significant inertia in obesity trends. In another analysis, energy deficit percentage needed to reduce BMI by one unit is found to be relatively constant across ages. Accompanying documented and freely available simulation model facilitates diverse applications customized to different sub-populations. PMID:25479101
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) : 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.
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.
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.
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.
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.
Model-data integration to improve the LPJmL dynamic global vegetation model
NASA Astrophysics Data System (ADS)
Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno
2017-04-01
Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the
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
Toward Integrative Dynamic Models for Adaptive Perspective Taking.
Duran, Nicholas; Dale, Rick; Galati, Alexia
2016-10-01
In a matter of mere milliseconds, conversational partners can transform their expectations about the world in a way that accords with another person's perspective. At the same time, in similar situations, the exact opposite also appears to be true. Rather than being at odds, these findings suggest that there are multiple contextual and processing constraints that may guide when and how people consider perspective. These constraints are shaped by a host of factors, including the availability of social and environmental cues, and intrinsic biases and cognitive abilities. To explain how these might be integrated in a new way forward, we turn to an adaptive account of interpersonal interaction. This account draws from basic principles of dynamical systems, principles that we argue are already expressed, both implicitly and explicitly, within a broad landscape of existing research. We then showcase an initial attempt to develop a computational framework to instantiate some of these principles. This framework, consisting of what we argue to be important mechanistic insights rendered by neural network models, is based on a promising and long-standing approach that has yet to take hold in the current domain. We argue that by bridging this gap, new insights into other theoretical accounts, such as the connections between memory and common ground information, might be revealed. Copyright © 2016 Cognitive Science Society, Inc.
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
Opportunities and challenges of Integral Projection Models for modelling host-parasite dynamics.
Metcalf, C Jessica E; Graham, Andrea L; Martinez-Bakker, Micaela; Childs, Dylan Z
2016-03-01
Epidemiological dynamics are shaped by and may in turn shape host demography. These feedbacks can result in hard to predict patterns of disease incidence. Mathematical models that integrate infection and demography are consequently a key tool for informing expectations for disease burden and identifying effective measures for control. A major challenge is capturing the details of infection within individuals and quantifying their downstream impacts to understand population-scale outcomes. For example, parasite loads and antibody titres may vary over the course of an infection and contribute to differences in transmission at the scale of the population. To date, to capture these subtleties, models have mostly relied on complex mechanistic frameworks, discrete categorization and/or agent-based approaches. Integral Projection Models (IPMs) allow variance in individual trajectories of quantitative traits and their population-level outcomes to be captured in ways that directly reflect statistical models of trait-fate relationships. Given increasing data availability, and advances in modelling, there is considerable potential for extending this framework to traits of relevance for infectious disease dynamics. Here, we provide an overview of host and parasite natural history contexts where IPMs could strengthen inference of population dynamics, with examples of host species ranging from mice to sheep to humans, and parasites ranging from viruses to worms. We discuss models of both parasite and host traits, provide two case studies and conclude by reviewing potential for both ecological and evolutionary research.
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.
Brouwer, A F; Grimberg, S J; Powers, S E
2012-12-01
The Dynamic Anaerobic Reactor & Integrated Energy System (DARIES) model has been developed as a biogas and electricity production model of a dairy farm anaerobic digester system. DARIES, which incorporates the Anaerobic Digester Model No. 1 (ADM1) and simulations of both combined heat and power (CHP) and digester heating systems, may be run in either completely mixed or plug flow reactor configurations. DARIES biogas predictions were shown to be statistically coincident with measured data from eighteen full-scale dairy operations in the northeastern United States. DARIES biogas predictions were more accurate than predictions made by the U.S. AgSTAR model FarmWare 3.4. DARIES electricity production predictions were verified against data collected by the NYSERDA DG/CHP Integrated Data System. Preliminary sensitivity analysis demonstrated that DARIES output was most sensitive to influent flow rate, chemical oxygen demand (COD), and biodegradability, and somewhat sensitive to hydraulic retention time and digester temperature.
Efficient Fully Implicit Time Integration Methods for Modeling Cardiac Dynamics
Rose, Donald J.; Henriquez, Craig S.
2013-01-01
Implicit methods are well known to have greater stability than explicit methods for stiff systems, but they often are not used in practice due to perceived computational complexity. This paper applies the Backward Euler method and a second-order one-step two-stage composite backward differentiation formula (C-BDF2) for the monodomain equations arising from mathematically modeling the electrical activity of the heart. The C-BDF2 scheme is an L-stable implicit time integration method and easily implementable. It uses the simplest Forward Euler and Backward Euler methods as fundamental building blocks. The nonlinear system resulting from application of the Backward Euler method for the monodomain equations is solved for the first time by a nonlinear elimination method, which eliminates local and non-symmetric components by using a Jacobian-free Newton solver, called Newton-Krylov solver. Unlike other fully implicit methods proposed for the monodomain equations in the literature, the Jacobian of the global system after the nonlinear elimination has much smaller size, is symmetric and possibly positive definite, which can be solved efficiently by standard optimal solvers. Numerical results are presented demonstrating that the C-BDF2 scheme can yield accurate results with less CPU times than explicit methods for both a single patch and spatially extended domains. PMID:19126449
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
An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems
Yu Zhang; Changsheng Li; Carl C. Trettin; Harbin Li; Ge Sun
2002-01-01
Wetland ecosystems are an important component in global carbon (C) cycles and may exert a large influence on global clinlate change. Predictions of C dynamics require us to consider interactions among many critical factors of soil, hydrology, and vegetation. However, few such integrated C models exist for wetland ecosystems. In this paper, we report a simulation model...
Ayyadurai, V A Shiva; Dewey, C Forbes
2011-03-01
A grand challenge of computational systems biology is to create a molecular pathway model of the whole cell. Current approaches involve merging smaller molecular pathway models' source codes to create a large monolithic model (computer program) that runs on a single computer. Such a larger model is difficult, if not impossible, to maintain given ongoing updates to the source codes of the smaller models. This paper describes a new system called CytoSolve that dynamically integrates computations of smaller models that can run in parallel across different machines without the need to merge the source codes of the individual models. This approach is demonstrated on the classic Epidermal Growth Factor Receptor (EGFR) model of Kholodenko. The EGFR model is split into four smaller models and each smaller model is distributed on a different machine. Results from four smaller models are dynamically integrated to generate identical results to the monolithic EGFR model running on a single machine. The overhead for parallel and dynamic computation is approximately twice that of a monolithic model running on a single machine. The CytoSolve approach provides a scalable method since smaller models may reside on any computer worldwide, where the source code of each model can be independently maintained and updated.
Integrating Environmental Optics into Multidisciplinary, Predictive Models of Ocean Dynamics
2011-09-30
Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 2 New modeling system – The photosynthetic pigment chlorophyll a plays a pivotal role in...indicators of photosynthetic capabilities and biochemical composition, and to improve upon established procedures for retrieving estimates of...physiological properties (e.g., the irradiance to which phytoplankton are acclimated, a key measure of photosynthetic performance) depends on analysis
von Thiele Schwarz, Ulrica; Lundmark, Robert; Hasson, Henna
2016-10-01
Recently, there have been calls to develop ways of using a participatory approach when conducting interventions, including evaluating the process and context to improve and adapt the intervention as it evolves over time. The need to integrate interventions into daily organizational practices, thereby increasing the likelihood of successful implementation and sustainable changes, has also been highlighted. We propose an evaluation model-the Dynamic Integrated Evaluation Model (DIEM)-that takes this into consideration. In the model, evaluation is fitted into a co-created iterative intervention process, in which the intervention activities can be continuously adapted based on collected data. By explicitly integrating process and context factors, DIEM also considers the dynamic sustainability of the intervention over time. It emphasizes the practical value of these evaluations for organizations, as well as the importance of their rigorousness for research purposes. Copyright © 2016 John Wiley & Sons, Ltd.
Reverse engineering gene networks: Integrating genetic perturbations with dynamical modeling
Tegnér, Jesper; Yeung, M. K. Stephen; Hasty, Jeff; Collins, James J.
2003-01-01
While the fundamental building blocks of biology are being tabulated by the various genome projects, microarray technology is setting the stage for the task of deducing the connectivity of large-scale gene networks. We show how the perturbation of carefully chosen genes in a microarray experiment can be used in conjunction with a reverse engineering algorithm to reveal the architecture of an underlying gene regulatory network. Our iterative scheme identifies the network topology by analyzing the steady-state changes in gene expression resulting from the systematic perturbation of a particular node in the network. We highlight the validity of our reverse engineering approach through the successful deduction of the topology of a linear in numero gene network and a recently reported model for the segmentation polarity network in Drosophila melanogaster. Our method may prove useful in identifying and validating specific drug targets and in deconvolving the effects of chemical compounds. PMID:12730377
NASA Astrophysics Data System (ADS)
Krajewski, Florian R.; Müser, Martin H.
2005-07-01
The spectral density of quantum mechanical Frenkel Kontorova chains moving in disordered, external potentials is investigated by means of path-integral molecular dynamics. If the second moment of the embedding potential is well defined (roughness exponent H=0), there is one regime in which the chain is pinned (large masses m of chain particles) and one in which it is unpinned (small m). If the embedding potential can be classified as a random walk on large length scales ( H=1/2), then the chain is always pinned irrespective of the value of m. For H=1/2, two phonon-like branches appear in the spectra.
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.
Sydelko, P J; Hlohowskyj, I; Majerus, K; Christiansen, J; Dolph, J
2001-07-02
Ecological risk assessment requires the integration of a wide range of data on anthropogenic processes, ecological processes and on processes related to environmental fate and transport. It is a major challenge to assemble a simulation system that can successfully capture the dynamics of complex ecological systems and an even more serious challenge to be able to adapt such a simulation to shifting and expanding analytical requirements and contexts. The dynamic information architecture system (DIAS) is a flexible, extensible, object-based framework for developing and maintaining complex simulations. DIAS supports simulations in which the real-world entities that make up ecological systems are represented as software 'entity objects'. The object-oriented integrated dynamic landscape analysis and modeling system (OO-IDLAMS) provides a good example of how DIAS has been used to build a suite of models for the purpose of assessing the ecological impacts of military land use and land management practices. OO-IDLAMS is a prototype conservation modeling suite that provides military environmental managers and decision-makers with a strategic, integrated and adaptive approach to natural resources planning and ecosystem management. The OO-IDLAMS prototype used Fort Riley, Kansas as a case study to demonstrate DIAS' capabilities to offer flexibility, interprocess dynamics and cost-effective reuse of code for ecosystem modeling and simulation. DIAS can also readily lend itself to other applications in ecological risk assessment. It has great potential for the integration of ecological models (associated with biological uptake and effects) with environmental fate and transport models. A DIAS ecological risk assessment application could be used to predict the magnitude and extent of ecological risks and evaluate remedy effectiveness in a timely and cost-effective manner.
González-Suárez, Manuela; Gerber, Leah R
2008-12-01
Although there has been a call for the integration of behavioral ecology and conservation biology, there are few tools currently available to achieve this integration. Explicitly including information about behavioral strategies in population viability analyses may enhance the ability of conservation biologists to understand and estimate patterns of extinction risk. Nevertheless, most behavioral-based PVA approaches require detailed individual-based data that are rarely available for imperiled species. We present a mechanistic approach that incorporates spatial and demographic consequences of behavioral strategies into population models used for conservation. We developed a stage-structured matrix model that includes the costs and benefits of movement associated with 2 habitat-selection strategies (philopatry and direct assessment). Using a life table for California sea lions (Zalophus californianus), we explored the sensitivity of model predictions to the inclusion of these behavioral parameters. Including behavioral information dramatically changed predicted population sizes, model dynamics, and the expected distribution of individuals among sites. Estimated population sizes projected in 100 years diverged up to 1 order of magnitude among scenarios that assumed different movement behavior. Scenarios also exhibited different model dynamics that ranged from stable equilibria to cycles or extinction. These results suggest that inclusion of behavioral data in viability models may improve estimates of extinction risk for imperiled species. Our approach provides a simple method for incorporating spatial and demographic consequences of behavioral strategies into population models and may be easily extended to other species and behaviors to understand the mechanisms of population dynamics for imperiled populations.
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
HepatoDyn: A Dynamic Model of Hepatocyte Metabolism That Integrates 13C Isotopomer Data.
Foguet, Carles; Marin, Silvia; Selivanov, Vitaly A; Fanchon, Eric; Lee, Wai-Nang Paul; Guinovart, Joan J; de Atauri, Pedro; Cascante, Marta
2016-04-01
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.
NASA Astrophysics Data System (ADS)
Dai, Yu; Liu, Shao-jun
2013-04-01
An integrated dynamic model of China's deep ocean mining system is developed and the fast simulation analysis of its longitudinal reciprocating motion operation processes is achieved. The seafloor tracked miner is built as a three-dimensional single-body model with six-degree-of-freedom. The track-terrain interaction is modeled by partitioning the track-terrain interface into a certain number of mesh elements with three mutually perpendicular forces, including the normal force, the longitudinal shear force and the lateral shear force, acting on the center point of each mesh element. The hydrodynamic force of the miner is considered and applied. By considering the operational safety and collection efficiency, two new mining paths for the miner on the seafloor are proposed, which can be simulated with the established single-body dynamic model of the miner. The pipeline subsystem is built as a three-dimensional multi-body discrete element model, which is divided into rigid elements linked by flexible connectors. The flexible connector without mass is represented by six spring-damper elements. The external hydrodynamic forces of the ocean current from the longitudinal and lateral directions are both considered and modeled based on the Morison formula and applied to the mass center of each corresponding discrete rigid element. The mining ship is simplified and represented by a general kinematic point, whose heave motion induced by the ocean waves and the longitudinal and lateral towing motions are considered and applied. By integrating the single-body dynamic model of the miner and the multi-body discrete element dynamic model of the pipeline, and defining the kinematic equations of the mining ship, the integrated dynamic model of the total deep ocean mining system is formed. The longitudinal reciprocating motion operation modes of the total mining system, which combine the active straight-line and turning motions of the miner and the ship, and the passive towed motions
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
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.
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.
A new simulation model building process for use in dynamic systems integration research
NASA Technical Reports Server (NTRS)
Arbuckle, P. Douglas; Buttrill, Carey S.; Zeiler, Thomas A.
1987-01-01
A framework to build simulation models for aircraft dynamic systems integration is described. The objective of the framework is increased simulation model fidelity and reduced time required to develop and modify these models. The equations of motion for an elastic aircraft and their impact on the framework are discussed in broad terms. A software tool which automatically generates FORTRAN routines for tabular data lookups, the language used to develop a simulation model, and the structures for passing information into a simulation are discussed. A simulation variable nomenclature is presented. The framework has been applied to build an open-loop F/A-18 simulation model. This example model is used to illustrate model reduction issues. Current deficiencies in the framework are identified as areas for future research.
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.
Dynamic integrated cost and engineering (DICE) model and its applicability to ATP systems
NASA Astrophysics Data System (ADS)
LaMont, Douglas V.; Benjamin, Brian J.
1995-05-01
As the system engineering process flows down constellation coverage specifications to the Spacecraft level in terms of agility requirements it's critical that the relationships between manueverability and cost are clearly understood. The probability of optimizing the cost of typical ATP system would be greatly enhanced if a realistic integrated cost/engineering model were available during the initial phase of a program (e.g. Conceptual Design Phase). Most Cost Engineering work performed to date has been done by Cost and/or Systems Engineers which has typically lead to models with a cost emphasis. This work tends to be parametric in nature and hence the models have has little 'buy-in' from the design engineering side of the house. A better approach is to take existing credible engineering models for the key Spacecraft subsystems (Attitude Control, Thermal, Power, etc.) and to append these models to include the appropriate hardware databases. This would allow the models to output cost, power and weight, besides analytical engineering parameters like torque, momentum, etc.. For sound engineering reasons some, but not all, subsystem models should be time-domain based (dynamic) simulations--a clear diverges from the typical Systems Engineering approach. A modular spacecraft model like the one created at Lockheed for the FEWS/ALARM programs provides an ideal basis for developing a Dynamic Integrated Cost & Engineering (DICE) Model. This paper provides a 'snapshot' of the initial development of Attitude Determination and Control portion of the DICE Model. These subsystems were modeled first since maneuverability has such a large cost impact on them. A multiple body dynamics package, High TEC1, provides the core of this DICE module. This package has been integrated into several simulation packages as described in previous works. Having access to this detailed 3-axis simulation model allows one to properly size spacecraft attitude systems (especially sensors and actuators
Options of system integrated environment modelling in the predicated dynamic cyberspace
Janková, Martina; Dvořák, Jiří
2015-03-10
In this article there are briefly mentioned some selected options of contemporary conception of cybernetic system models in the corresponding and possible integratable environment with modern system dynamics thinking and all this in the cyberspace of possible projecting of predicted system characteristics. The key to new capabilities of system integration modelling in the considered cyberspace is mainly the ability to improve the environment and the system integration options, all this with the aim of modern control in the hierarchically arranged dynamic cyberspace, e.g. in the currently desired electronic business with information. The aim of this article is to assess generally the trends in the use of modern modelling methods considering the cybernetics applications verified in practice, modern concept of project management and also the potential integration of artificial intelligence in the new projecting and project management of integratable and intelligent models, e.g. with the optimal structures and adaptable behaviour.The article results from the solution of a specific research partial task at the faculty; especially the moments proving that the new economics will be based more and more on information, knowledge system defined cyberspace of modern management, are stressed in the text.
NASA Astrophysics Data System (ADS)
Xu, Xiaoming; Du, Ziqiang; Zhang, Hong
2016-10-01
Land use and land cover change (LULCC) is a widely researched topic in related studies. A number of models have been established to simulate LULCC patterns. However, the integration of the system dynamic (SD) and the cellular automata (CA) model have been rarely employed in LULCC simulations, although it allows for combining the advantages of each approach and therefore improving the simulation accuracy. In this study, we integrated an SD model and a CA model to predict LULCC under three future development scenarios in Northern Shanxi province of China, a typical agro-pastoral transitional zone. The results indicated that our integrated approach represented the impacts of natural and socioeconomic factors on LULCC well, and could accurately simulate the magnitude and spatial pattern of LULCC. The modeling scenarios illustrated that different development pathways would lead to various LULCC patterns. This study demonstrated the advantages of the integration approach for simulating LULCC and suggests that LULCC is affected to a large degree by natural and socioeconomic factors.
Arnold, Beth; Cassady, Steven J.; Van Laar, Victor S.; Berman, Sarah B.
2010-01-01
Changes in dynamic properties of mitochondria are increasingly implicated in neurodegenerative diseases, particularly Parkinson’s disease (PD). Static changes in mitochondrial morphology, often under acutely toxic conditions, are commonly utilized as indicators of changes in mitochondrial fission and fusion. However, in neurons, mitochondrial fission and fusion occur in a dynamic system of axonal/dendritic transport, biogenesis and degradation, and thus, likely interact and change over time. We sought to explore this using a chronic neuronal model (nonlethal low-concentration rotenone over several weeks), examining distal neurites, which may give insight into the earliest changes occurring in PD. Using this model, in live primary neurons, we directly quantified mitochondrial fission, fusion, and transport over time and integrated multiple aspects of mitochondrial dynamics, including morphology and growth/mitophagy. We found that rates of mitochondrial fission and fusion change as neurons age. In addition, we found that chronic rotenone exposure initially increased the ratio of fusion to fission, but later, this was reversed. Surprisingly, despite changes in rates of fission and fusion, mitochondrial morphology was minimally affected, demonstrating that morphology can be an inaccurate indicator of fission/fusion changes. In addition, we found evidence of subcellular compartmentalization of compensatory changes, as mitochondrial density increased in distal neurites first, which may be important in PD, where pathology may begin distally. We propose that rotenone-induced early changes such as in mitochondrial fusion are compensatory, accompanied later by detrimental fission. As evidence, in a dopaminergic neuronal model, in which chronic rotenone caused loss of neurites before cell death (like PD pathology), inhibiting fission protected against the neurite loss. This suggests that aberrant mitochondrial dynamics may contribute to the earliest neuropathologic
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
Nadeem, Khurram; Moore, Jeffrey E; Zhang, Ying; Chipman, Hugh
2016-07-01
Stochastic versions of Gompertz, Ricker, and various other dynamics models play a fundamental role in quantifying strength of density dependence and studying long-term dynamics of wildlife populations. These models are frequently estimated using time series of abundance estimates that are inevitably subject to observation error and missing data. This issue can be addressed with a state-space modeling framework that jointly estimates the observed data model and the underlying stochastic population dynamics (SPD) model. In cases where abundance data are from multiple locations with a smaller spatial resolution (e.g., from mark-recapture and distance sampling studies), models are conventionally fitted to spatially pooled estimates of yearly abundances. Here, we demonstrate that a spatial version of SPD models can be directly estimated from short time series of spatially referenced distance sampling data in a unified hierarchical state-space modeling framework that also allows for spatial variance (covariance) in population growth. We also show that a full range of likelihood based inference, including estimability diagnostics and model selection, is feasible in this class of models using a data cloning algorithm. We further show through simulation experiments that the hierarchical state-space framework introduced herein efficiently captures the underlying dynamical parameters and spatial abundance distribution. We apply our methodology by analyzing a time series of line-transect distance sampling data for fin whales (Balaenoptera physalus) off the U.S. west coast. Although there were only seven surveys conducted during the study time frame, 1991-2014, our analysis detected presence of strong density regulation and provided reliable estimates of fin whale densities. In summary, we show that the integrative framework developed herein allows ecologists to better infer key population characteristics such as presence of density regulation and spatial variability in a
Integrating count and detection-nondetection data to model population dynamics.
Zipkin, Elise F; Rossman, Sam; Yackulic, Charles B; Wiens, J David; Thorson, James T; Davis, Raymond J; Grant, Evan H Campbell
2017-06-01
There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture-recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection-nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection-nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection-nondetection data (1995-2014) with newly collected count data (2015-2016) from a growing population of Barred Owl (Strix varia) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance. © 2017 by the Ecological Society of
Integrating count and detection–nondetection data to model population dynamics
Zipkin, Elise F.; Rossman, Sam; Yackulic, Charles B.; Wiens, David; Thorson, James T.; Davis, Raymond J.; Grant, Evan
2017-01-01
There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture–recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection–nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection–nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection–nondetection data (1995–2014) with newly collected count data (2015–2016) from a growing population of Barred Owl (Strix varia) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance.
Simulation analysis of an integrated model for dynamic cellular manufacturing system
NASA Astrophysics Data System (ADS)
Hao, Chunfeng; Luan, Shichao; Kong, Jili
2017-05-01
Application of dynamic cellular manufacturing system (DCMS) is a well-known strategy to improve manufacturing efficiency in the production environment with high variety and low volume of production. Often, neither the trade-off of inter and intra-cell material movements nor the trade-off of hiring and firing of operators are examined in details. This paper presents simulation results of an integrated mixed-integer model including sensitivity analysis for several numerical examples. The comprehensive model includes cell formation, inter and intracellular materials handling, inventory and backorder holding, operator assignment (including resource adjustment) and flexible production routing. The model considers multi-production planning with flexible resources (machines and operators) where each period has different demands. The results verify the validity and sensitivity of the proposed model using a genetic algorithm.
Integrating modelling and experiments to assess dynamic musculoskeletal function in humans.
Fernandez, J W; Pandy, M G
2006-03-01
Magnetic resonance imaging, bi-plane X-ray fluoroscopy and biomechanical modelling are enabling technologies for the non-invasive evaluation of muscle, ligament and joint function during dynamic activity. This paper reviews these various technologies in the context of their application to the study of human movement. We describe how three-dimensional, subject-specific computer models of the muscles, ligaments, cartilage and bones can be developed from high-resolution magnetic resonance images; how X-ray fluoroscopy can be used to measure the relative movements of the bones at a joint in three dimensions with submillimetre accuracy; how complex 3-D dynamic simulations of movement can be performed using new computational methods based on non-linear control theory; and how musculoskeletal forces derived from such simulations can be used as inputs to elaborate finite-element models of a joint to calculate contact stress distributions on a subject-specific basis. A hierarchical modelling approach is highlighted that links rigid-body models of limb segments with detailed finite-element models of the joints. A framework is proposed that integrates subject-specific musculoskeletal computer models with highly accurate in vivo experimental data.
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)
Guo, B.; Bandilla, K.; Keilegavlen, E.; Doster, F.; Celia, M. A.
2014-12-01
Mathematical models with different level of complexity are needed to address a range of engineering questions on security issues of CO2 sequestration, which has been proposed as a promising strategy for carbon mitigation. Among this wide range of mathematical models, a family of vertically integrated models has been developed. These models are usually based on a vertical equilibrium (VE) assumption, which states that due to strong buoyancy, CO2 and brine segregate instantaneously and reach a hydrostatic pressure distribution in the vertical dimension. Such VE models are accurate and computationally efficient as long as the VE assumption is valid. By comparing VE models with a full three-dimensional model for a series of practical problems, Court et al. (2012) found that there are a number of cases for which the VE model is not applicable, especially when the geological formations have relatively low vertical permeability, on the order of 10 milliDarcy or lower. To overcome the VE limitation, Guo et al. (2014) have developed a vertically integrated model for homogeneous formations that relaxes the VE assumption and accounts for vertical dynamics of CO2 and brine. Though, limited to homogeneous formations, this model has a much wider applicability compared to VE models while maintains much of the VE model's computational efficiency. In this contribution, we extend the vertically integrated model of Guo et al. (2014) to deal with the horizontally layered systems to include vertical heterogeneities. Each layer of the system can have different material properties but is assumed to be homogeneous within the layer. Such horizontally layered systems are of high practical relevance because of the depositional history of the geological formations. We develop coupling conditions between the layers and use a similar algorithm of Guo et al. (2014) to solve the individual layers. The end result is a model capable of dealing with vertical geological heterogeneities while still
NASA Astrophysics Data System (ADS)
Krajewski, Florian R.; Müser, Martin H.
2005-03-01
The commensurate Frenkel Kontorova (FK) model is studied using path-integral molecular dynamics (PIMD). We focus on the highly discrete case, in which the embedding potential has a much greater maximum curvature than the harmonic potential connecting two particles in the FK chain. When efficient sampling methods are used, the dynamical interpretation of adiabatic PIMD appears to represent quite accurately the true time correlation functions of this highly correlated many-body system. We have found that the discrete, quantum FK model shows different behavior than its continuum version. The spectral density does not show the characteristic ω-2Θ(ω-ωc) cusp of the continuum solution in the pinned phase (m>mc). We also identify a dynamical quantum hysteresis in addition to the regular classical hysteresis when an external force is applied to the FK chain. In the unpinned phase (m⩽mc), we find a linear response damping coefficient which is finite and only weakly dependent on temperature T at small values of T.
Integrated opto-dynamic modeling of the 4m DAG telescope image quality performance
NASA Astrophysics Data System (ADS)
Zago, Lorenzo; Guex, Benjamin; Yesilyaprak, Cahit; Yerli, Sinan K.; Keskin, Onur
2016-08-01
The Turkish DAG 4-m telescope is currently through the final design stage. It is to be located on a 3170 m mountain top in Eastern Anatolia. The telescope will be a state-of-the art device, alt-az mount with active primary and adjustable secondary and tertiary mirrors. Its optics design is specially aimed at being compatible with advance adaptive optics instrumentation. The ultimate performance of such a telescope results of multiple concurrent effects from many different components and active functions of the complex system. The paper presents a comprehensive integrated (end-to-end) model of the telescope, comprising in one computational sequence all structural, electrodynamics and oactive optics performance that produce the image quality at the focal plane. The model is entirely programmed in Matlab/Simulink and comprises a finite element model of structure and mirrors, dynamics modal reduction, deformation analyses of structural and optical elements, active optics feedback control in the Zernike modal space.
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.
Kircher, Stefan; Kirchenbauer, Daniel; Timmer, Jens; Nagy, Ferenc; Schäfer, Eberhard; Fleck, Christian
2010-01-01
Background Plants have evolved various sophisticated mechanisms to respond and adapt to changes of abiotic factors in their natural environment. Light is one of the most important abiotic environmental factors and it regulates plant growth and development throughout their entire life cycle. To monitor the intensity and spectral composition of the ambient light environment, plants have evolved multiple photoreceptors, including the red/far-red light-sensing phytochromes. Methodology/Principal Findings We have developed an integrative mathematical model that describes how phytochrome B (phyB), an essential receptor in Arabidopsis thaliana, controls growth. Our model is based on a multiscale approach and connects the mesoscopic intracellular phyB protein dynamics to the macroscopic growth phenotype. To establish reliable and relevant parameters for the model phyB regulated growth we measured: accumulation and degradation, dark reversion kinetics and the dynamic behavior of different nuclear phyB pools using in vivo spectroscopy, western blotting and Fluorescence Recovery After Photobleaching (FRAP) technique, respectively. Conclusions/Significance The newly developed model predicts that the phyB-containing nuclear bodies (NBs) (i) serve as storage sites for phyB and (ii) control prolonged dark reversion kinetics as well as partial reversibility of phyB Pfr in extended darkness. The predictive power of this mathematical model is further validated by the fact that we are able to formalize a basic photobiological observation, namely that in light-grown seedlings hypocotyl length depends on the total amount of phyB. In addition, we demonstrate that our theoretical predictions are in excellent agreement with quantitative data concerning phyB levels and the corresponding hypocotyl lengths. Hence, we conclude that the integrative model suggested in this study captures the main features of phyB-mediated photomorphogenesis in Arabidopsis. PMID:20502669
NASA Astrophysics Data System (ADS)
Hardy, S.; Gonzalez-Huizar, H.; Smith-Konter, B. R.
2015-12-01
The frictional and stress conditions at aseismic depths in tectonic boundaries are difficult to estimate, these are important parameters in computing stress transfer from plate motion to the seismogenetic zones of the plate boundaries, and thus, in creating seismic hazard models. Ambient and triggered tectonic tremor can be useful in the estimation of friction and stress parameters at large crustal depths. Seismic waves can trigger tremor in tectonic environments, specifically in the San Andreas Fault. A large number of ambient and triggered tremors have been reported near the creeping to locking transition zone along the Parkfield-Cholame section of the San Andreas Fault as well as in the San Jacinto and Calaveras Faults, both triggered by the 2002 Denali Fault earthquake. Ambient and triggered tremor along California is well located and documents well due to the large number of seismic stations in the region. We use recorded seismic signal from magnitude > 7.5 earthquakes to calculate the dynamic stresses capable to trigger tremor in these regions; this is integrated with local tectonic stress models with the objective to estimate the spatial variability of frictional and stress parameters along the areas where tremor are triggered. Integrating static and dynamic stress for San Andreas Fault will allow us to better understand the stress and frictional conditions necessary for tremor occurrence.
Yvert, Gaëtan; Perrone-Bertolotti, Marcela; Baciu, Monica; David, Olivier
2012-01-01
Integration of phonological and lexico-semantic processes is essential for visual word recognition. Here we used dynamic causal modeling of event-related potentials, combined with group source reconstruction, to estimate how those processes translate into context-dependent modulation of effective connectivity within the temporal-frontal language network. Fifteen healthy human subjects performed a phoneme detection task in pseudo-words and a semantic categorization task in words. Cortical current densities revealed the sequential activation of temporal regions, from the occipital-temporal junction towards the anterior temporal lobe, before reaching the inferior frontal gyrus. A difference of activation between phonology and semantics was identified in the anterior temporal lobe, within the 240–300 ms peristimulus time-window. Dynamic causal modeling indicated this increase of activation of the anterior temporal lobe in the semantic condition as a consequence of an increase of forward connectivity from the posterior inferior temporal lobe to the anterior temporal lobe. In addition, fast activation of the inferior frontal region, that allowed a feedback control of frontal regions on the superior temporal and posterior inferior temporal cortices, was found to be likely. Our results precisely describe spatio-temporal network mechanisms occurring during integration of phonological and semantic processes. In particular, they support the hypothesis of multiple pathways within the temporal lobe for language processing, where frontal regions would exert a top-down control on temporal regions in the recruitment of the anterior temporal lobe for semantic processing. PMID:22442091
2017-01-01
Mass spectrometry (MS) has become an indispensable tool for investigating the architectures and dynamics of macromolecular assemblies. Here we show that covalent labeling of solvent accessible residues followed by their MS-based identification yields modeling restraints that allow mapping the location and orientation of subunits within protein assemblies. Together with complementary restraints derived from cross-linking and native MS, we built native-like models of four heterocomplexes with known subunit structures and compared them with available X-ray crystal structures. The results demonstrated that covalent labeling followed by MS markedly increased the predictive power of the integrative modeling strategy enabling more accurate protein assembly models. We applied this strategy to the F-type ATP synthase from spinach chloroplasts (cATPase) providing a structural basis for its function as a nanomotor. By subjecting the models generated by our restraint-based strategy to molecular dynamics (MD) simulations, we revealed the conformational states of the peripheral stalk and assigned flexible regions in the enzyme. Our strategy can readily incorporate complementary chemical labeling strategies and we anticipate that it will be applicable to many other systems providing new insights into the structure and function of protein complexes. PMID:28208298
Munsky, Brian; Fox, Zachary; Neuert, Gregor
2015-09-01
The production and degradation of RNA transcripts is inherently subject to biological noise that arises from small gene copy numbers in individual cells. As a result, cellular RNA levels can exhibit large fluctuations over time and from one cell to the next. This article presents a range of precise single-molecule experimental techniques, based upon RNA fluorescence in situ hybridization, which can be used to measure the fluctuations of RNA at the single-cell level. A class of models for gene activation and deactivation is postulated in order to capture complex stochastic effects of chromatin modifications or transcription factor interactions. A computational tool, known as the finite state projection approach, is introduced to accurately and efficiently analyze these models in order to predict how probability distributions of RNA change over time in response to changing environmental conditions. These single-molecule experiments, discrete stochastic models, and computational analyses are systematically integrated to identify models of gene regulation dynamics. To illustrate the power and generality of our integrated experimental and computational approach, we explore cases that include different models for three different RNA types (sRNA, mRNA and nascent RNA), three different experimental techniques and three different biological species (bacteria, yeast and human cells). Copyright © 2015. Published by Elsevier Inc.
NASA Astrophysics Data System (ADS)
Kim, J. B.; Smith, E.
2011-12-01
Many have explored the impact of climate change on insects and explored predictions under future scenarios. But the converse has been limited: no DGVM simulates insect infestation. We are assessing the potential impact of simulating insect infestation processes on DGVMs, and creating a framework for development of insect functional types (IFTs) for integration with DGVMs. Some work have been done devising IFTs for conservation and resource management, but results are limited to qualitative groupings of insect taxa based on resource usage and response to environment. The integration of IFTs into DGVMs would enable exploration of interaction between climate change and vegetation dynamics at the global scale. IFTs have the potential to significantly impact global carbon balance and vegetation distributions, and interaction with other disturbance regimes already modeled in DGVMs (e.g., fire, drought, herbivory). We identify relevant features of existing DGVMs, including spatial and temporal scales, extents, and focuses; how other disturbances are modeled; and model areas where IFTs would link to DGVMs. We identify relevant features of insect models, including hazard and risk models; spatial and temporal resolutions and extents; spatial processes; and commonly used variables. We outline the key considerations, including tradeoffs between accuracy of representation and the breadth of applicability; morphology, physiology, biochemistry, reproductive and demographic characteristics; functional effects vs. functional responses; major axes of specialization that are consistent across environments, biogeographic regions, and major insect taxa; and whether IFTs can be empirically evaluated. We propose major axes to define IFTs, and present a sample IFT, the westwide pine beetle.
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.
Hsu, Cheng-En; Huang, Kui-Chou; Lin, Tzu-Chieh; Tong, Kwok-Man; Lee, Mei-Hsuan; Chiu, Yung-Cheng
2016-11-01
Dynamic hip screw (DHS) is a common device for treating intertrochanteric fracture (ITF). Various risk factors have been reported to be associated with the operative treatment outcome. However, an integrated risk scoring prediction model is lacking. In this study, we aimed to develop a prediction model for treatment outcome of intertrochanteric fracture. We analyzed 442 AO/OTA 31-A1 and A2 fractures which were treated with DHS during the period January 2000 to June 2014 in a level I trauma center. Risk factors including age, gender, injured side, lag screw position, AO/OTA classification, tip-apex distance, postoperative lateral wall fracture, reduction patterns were analyzed to determine their influence on treatment outcome. Integrated risk scores of significant predictors were used to construct a prediction model. AO/OTA 31-A2 classification, postoperative lateral wall fracture, posteriorly inserted lag screw and varus reduction pattern were significant risk predictors for DHS failure. The failure risk for low- and high-risk groups were significantly different (P<0.001) CONCLUSION: AO/OTA 31-A2 classification, postoperative lateral wall fracture, posteriorly inserted lag screw and varus reduction pattern were significant risk predictors for DHS failure. We developed a model that integrates these factors to predict the treatment outcome, which had excellent prediction accuracy and discriminatory ability. The models may provide useful information for orthopedic doctors to identify patients who need early intervention as well as ITF patients who require more frequent follow-up in the postoperative period. Copyright © 2016. Published by Elsevier Ltd.
NASA Astrophysics Data System (ADS)
Mendoza, C. A.; Carrera-Hernández, J. J.; Devito, K. J.; Smerdon, B. D.
2008-12-01
The Boreal Plains represent an important habitat for many wildlife and vegetation species. It is currently being affected by industrial developments such as oil and gas exploration, open pit mining and forestry. To understand the impact of human activities on boreal wetlands and adjacent uplands, and to improve our understanding of the interaction between the hydrological processes that control wetland dynamics (e.g., atmospheric fluxes and intra-annual vegetation water demand), a detailed three dimensional, fully coupled model is required. To develop this type of model, the integration of both temporal and spatial data is required. A framework was developed and applied to analyze the hydrological processes of a flow-through lake (L-16) and a perched pond (P-19) located in the Utikuma Region Study Area (URSA), 370 km north of Edmonton, in Alberta, Canada. Our framework integrates field data gathered over seven years on and around both L-16 and P-19 (e.g., groundwater head measurements, lake levels, soil moisture and climatological records), aerial photographs and satellite imagery along with surface geology, lithology and LiDAR data. The integration of these data allowed the application of a Soil Vegetation Atmosphere Transfer model, and the representation of both soil and geological heterogeneity as L-16 is located on glaciofluvial deposits, while nearby P-19 is found on a transition zone between the glaciofluvial deposits (coarse) and ice contact sediments (fine-grained). The model results show that wetland persistence is the result of complex interactions between climatological and geological conditions along with vegetation water demand. This interaction causes groundwater flow reversals (i.e., water flowing uphill) when vegetation water demand is not satisfied. In addition, the modeled water bodies showed limited interaction with the regional groundwater flow system.
Integrated modelling of hydrological processes and groundwater dynamics at the river basin scale
NASA Astrophysics Data System (ADS)
Ravazzani, G.; Mancini, M.; Bergamaschi, M.; Rametta, D.
2009-09-01
In recent years, the rising demand for water has led to water scarcity condition also in those areas traditionally rich of water such as the river Po valley in Italy. On the other hand, the frequency of intense rainfall events has increased during the last years in mid and high latitudes due to the impact of climate change, causing destruction or much damage. These negative effects on human activities were also due to the lack of knowledge of the hydrological processes of the water balance at the river basin scale in an integrated perspective as requested by European Water Framework Directive. With the aim to improve the understanding of water balance related hydrological processes, sophisticated continuous hydrologic models have been developed for the simulation of soil water dynamic and river discharge also for mountain basins with complex topography. However, some uncertainties still remain. Some of the main uncertainties lie in the understanding of how the water balance of the upper river catchment can affect water resources and floods of the downstream lowland and in the importance of the interactions between the shallow groundwater and surface waters for water balance processes of alluvial plans. For this purpose a raster based distributed model was developed that allow the simulation of the processes regulating the water fluxes between soil, vegetation and atmosphere, the spatial patterns and temporal dynamics of groundwater-surface water interactions, and river discharge. The model was applied to the river Serio basin, in northern Italy.
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
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.
Dynamics of the exponential integrate-and-fire model with slow currents and adaptation.
Barranca, Victor J; Johnson, Daniel C; Moyher, Jennifer L; Sauppe, Joshua P; Shkarayev, Maxim S; Kovačič, Gregor; Cai, David
2014-08-01
In order to properly capture spike-frequency adaptation with a simplified point-neuron model, we study approximations of Hodgkin-Huxley (HH) models including slow currents by exponential integrate-and-fire (EIF) models that incorporate the same types of currents. We optimize the parameters of the EIF models under the external drive consisting of AMPA-type conductance pulses using the current-voltage curves and the van Rossum metric to best capture the subthreshold membrane potential, firing rate, and jump size of the slow current at the neuron's spike times. Our numerical simulations demonstrate that, in addition to these quantities, the approximate EIF-type models faithfully reproduce bifurcation properties of the HH neurons with slow currents, which include spike-frequency adaptation, phase-response curves, critical exponents at the transition between a finite and infinite number of spikes with increasing constant external drive, and bifurcation diagrams of interspike intervals in time-periodically forced models. Dynamics of networks of HH neurons with slow currents can also be approximated by corresponding EIF-type networks, with the approximation being at least statistically accurate over a broad range of Poisson rates of the external drive. For the form of external drive resembling realistic, AMPA-like synaptic conductance response to incoming action potentials, the EIF model affords great savings of computation time as compared with the corresponding HH-type model. Our work shows that the EIF model with additional slow currents is well suited for use in large-scale, point-neuron models in which spike-frequency adaptation is important.
Dynamic modeling of gas turbines in integrated gasification fuel cell systems
NASA Astrophysics Data System (ADS)
Maclay, James Davenport
2009-12-01
Solid oxide fuel cell-gas turbine (SOFC-GT) hybrid systems for use in integrated gasification fuel cell (IGFC) systems operating on coal will stretch existing fossil fuel reserves, generate power with less environmental impact, while having a cost of electricity advantage over most competing technologies. However, the dynamic performance of a SOFC-GT in IGFC applications has not been previously studied in detail. Of particular importance is how the turbo-machinery will be designed, controlled and operated in such applications; this is the focus of the current work. Perturbation and dynamic response analyses using numerical SimulinkRTM models indicate that compressor surge is the predominant concern for safe dynamic turbo-machinery operation while shaft over-speed and excessive turbine inlet temperatures are secondary concerns. Fuel cell temperature gradients and anode-cathode differential pressures were found to be the greatest concerns for safe dynamic fuel cell operation. Two control strategies were compared, that of constant gas turbine shaft speed and constant fuel cell temperature, utilizing a variable speed gas turbine. Neither control strategy could eliminate all vulnerabilities during dynamic operation. Constant fuel cell temperature control ensures safe fuel cell operation, while constant speed control does not. However, compressor surge is more likely with constant fuel cell temperature control than with constant speed control. Design strategies that provide greater surge margin while utilizing constant fuel cell temperature control include increasing turbine design mass flow and decreasing turbine design inlet pressure, increasing compressor design pressure ratio and decreasing compressor design mass flow, decreasing plenum volume, decreasing shaft moment of inertia, decreasing fuel cell pressure drop, maintaining constant compressor inlet air temperature. However, these strategies in some cases incur an efficiency penalty. A broad comparison of cycles
Pal, Parimal; Das, Pallabi; Chakrabortty, Sankha; Thakura, Ritwik
2016-11-01
Dynamic modelling and simulation of a nanofiltration-forward osmosis integrated complete system was done along with economic evaluation to pave the way for scale up of such a system for treating hazardous pharmaceutical wastes. The system operated in a closed loop not only protects surface water from the onslaught of hazardous industrial wastewater but also saves on cost of fresh water by turning wastewater recyclable at affordable price. The success of dynamic modelling in capturing the relevant transport phenomena is well reflected in high overall correlation coefficient value (R (2) > 0.98), low relative error (<0.1) and Willmott d-index (<0.95). The system could remove more than 97.5 % chemical oxygen demand (COD) from real pharmaceutical wastewater having initial COD value as high as 3500 mg/L while ensuring operation of the forward osmosis loop at a reasonably high flux of 56-58 l per square meter per hour.
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.
Makadia, Hirenkumar K.; Anderson, Warren D.; Fey, Dirk; Sauter, Thomas; Schwaber, James S.; Vadigepalli, Rajanikanth
2015-01-01
We developed a multiscale model to bridge neuropeptide receptor-activated signaling pathway activity with membrane electrophysiology. Typically, the neuromodulation of biochemical signaling and biophysics have been investigated separately in modeling studies. We studied the effects of Angiotensin II (AngII) on neuronal excitability changes mediated by signaling dynamics and downstream phosphorylation of ion channels. Experiments have shown that AngII binding to the AngII receptor type-1 elicits baseline-dependent regulation of cytosolic Ca2+ signaling. Our model simulations revealed a baseline Ca2+-dependent response to AngII receptor type-1 activation by AngII. Consistent with experimental observations, AngII evoked a rise in Ca2+ when starting at a low baseline Ca2+ level, and a decrease in Ca2+ when starting at a higher baseline. Our analysis predicted that the kinetics of Ca2+ transport into the endoplasmic reticulum play a critical role in shaping the Ca2+ response. The Ca2+ baseline also influenced the AngII-induced excitability changes such that lower Ca2+ levels were associated with a larger firing rate increase. We examined the relative contributions of signaling kinases protein kinase C and Ca2+/Calmodulin-dependent protein kinase II to AngII-mediated excitability changes by simulating activity blockade individually and in combination. We found that protein kinase C selectively controlled firing rate adaptation whereas Ca2+/Calmodulin-dependent protein kinase II induced a delayed effect on the firing rate increase. We tested whether signaling kinetics were necessary for the dynamic effects of AngII on excitability by simulating three scenarios of AngII-mediated KDR channel phosphorylation: (1), an increased steady state; (2), a step-change increase; and (3), dynamic modulation. Our results revealed that the kinetics emerging from neuromodulatory activation of the signaling network were required to account for the dynamical changes in excitability. In
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.
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
An integrated model for Jupiter's dynamo action and mean jet dynamics
NASA Astrophysics Data System (ADS)
Gastine, Thomas; Wicht, Johannes; Duarte, Lucia; Heimpel, Moritz
2014-05-01
Data from various space crafts revealed that Jupiter's large scale interior magnetic field is very Earth-like. This is surprising since numerical simulations have demonstrated that, for example, the radial dependence of density, electrical conductivity and other physical properties, which is only mild in the iron cores of terrestrial planets but very drastic in gas planets, can significantly affect the interior dynamics. Jupiter's dynamo action is thought to take place in the deeper envelope where hydrogen, the main constituent of Jupiter's atmosphere, assumes metallic properties. The potential interaction between the observed zonal jets and the deeper dynamo region is an unresolved problem with important consequences for the magnetic field generation. Here we present the first numerical simulation that is based on recent interior models and covers 99% of the planetary radius (below the 1 bar level). A steep decease in the electrical conductivity over the outer 10% in radius allowed us to model both the deeper metallic region and the outer molecular layer in an integrated approach. The magnetic field very closely reproduces Jupiter's known large scale field. A strong equatorial zonal jet remains constrained to the molecular layer while higher latitude jets are suppressed by Lorentz forces. This suggests that Jupiter's higher latitude jets remain shallow and are driven by an additional effect not captured in our deep convection model. The dynamo action of the equatorial jet produces a band of magnetic field located around the equator. The unprecedented magnetic field resolution expected from the Juno mission will allow to resolve this feature allowing a direct detection of the equatorial jet dynamics at depth. Typical secular variation times scales amount to around 750 yr for the dipole contribution but decrease to about 5 yr at the expected Juno resolution (spherical harmonic degree 20). At a nominal mission duration of one year Juno should therefore be able to
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
Integrated modeling of long-term vegetation and hydrologic dynamics in Rocky Mountain watersheds
Robert Steven Ahl
2007-01-01
Changes in forest structure resulting from natural disturbances, or managed treatments, can have negative and long lasting impacts on water resources. To facilitate integrated management of forest and water resources, a System for Long-Term Integrated Management Modeling (SLIMM) was developed. By combining two spatially explicit, continuous time models, vegetation...
Integrated decision-making about housing, energy and wellbeing: a qualitative system dynamics model.
Macmillan, Alexandra; Davies, Michael; Shrubsole, Clive; Luxford, Naomi; May, Neil; Chiu, Lai Fong; Trutnevyte, Evelina; Bobrova, Yekatherina; Chalabi, Zaid
2016-03-08
integrated approach to housing. The qualitative model has begun to improve the assessment of future policy options across a broad range of outcomes. Future work is needed to validate the model and increase its utility through computer simulation incorporating best quality data and evidence. Combining system dynamics modelling with other methods for weighing up policy options, as well as methods to support shifts in the conceptual frameworks underpinning policy, will be necessary to achieve shared housing goals across physical, mental, environmental, economic and social wellbeing.
Cafri, Guy; Hedeker, Donald; Aarons, Gregory A
2015-12-01
In longitudinal studies, time-varying group membership and group effects are important issues that need to be addressed. In this article we describe use of cross-classified and multiple membership random-effects models to address time-varying group membership, and dynamic group random-effects models to address time-varying group effects. We propose new models that integrate features of existing models, evaluate these models through simulation, provide guidance on how to fit these models, and apply the models in 2 real data examples. The discussion focuses on challenges in the application of these models.
Cafri, Guy; Hedeker, Donald; Aarons, Gregory A.
2016-01-01
In longitudinal studies, time-varying group membership and group effects are important issues that need to be addressed. In this article we describe use of cross-classified and multiple membership random-effect models to address time varying group membership, and dynamic group random-effect models to address time-varying group effects. We propose new models that integrate features of existing models, evaluate these models through simulation, provide guidance on how to fit these models, and apply the models in two real data examples. The discussion focuses on challenges in the application of these models. PMID:26237504
NASA Astrophysics Data System (ADS)
Chen, Yang; Wang, Huasheng; Xia, Jixia; Cai, Guobiao; Zhang, Zhenpeng
2017-04-01
For the pressure reducing regulator and check valve double-valve combined test system in an integral bipropellant propulsion system, a system model is established with modular models of various typical components. The simulation research is conducted on the whole working process of an experiment of 9 MPa working condition from startup to rated working condition and finally to shutdown. Comparison of simulation results with test data shows: five working conditions including standby, startup, rated pressurization, shutdown and halt and nine stages of the combined test system are comprehensively disclosed; valve-spool opening and closing details of the regulator and two check valves are accurately revealed; the simulation also clarifies two phenomena which test data are unable to clarify, one is the critical opening state in which the check valve spools slightly open and close alternately in their own fully closed positions, the other is the obvious effects of flow-field temperature drop and temperature rise in pipeline network with helium gas flowing. Moreover, simulation results with consideration of component wall heat transfer are closer to the test data than those under the adiabatic-wall condition, and more able to reveal the dynamic characteristics of the system in various working stages.
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2012-12-01
Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil
Integrate carbon dynamic models in analyzing carbon sequestration impact of forest biomass harvest.
Yan, Yan
2017-10-05
Biomass is an attractive natural energy resource for mitigating climate change. However, the loss of carbon sequestration as an ecosystem service due to biomass harvest has not been considered in previous studies. To assess the impact of biomass harvest on carbon sequestration, carbon dynamics in the forests and the atmosphere were integrated. The impact of forest biomass harvests on carbon sequestration was assessed based on the difference between carbon sequestration after harvest and carbon sequestration without harvest. A Chapman-Richards function and the forest vegetation simulator (FVS) were used to simulate the growth of a forest stand. The carbon dynamics in the atmosphere were simulated by the Bern2.5CC carbon cycle model. Characterization factors of the impact were calculated in three time horizons: 20-, 100- and 500-year. According to the simulations, postponement of harvest and low harvest intensity could prolong the compensation period. The annual impact on carbon sequestration was mostly negative over a short time and became positive in the end of compensation period. The highest characteristic factors of the impact on carbon sequestration were found in rotation length of 100years with the time horizon of 500-year in the Chapman-Richards simulation and in the lowest harvest intensity with the time horizon of 500-year in the FVS simulation. Based on the results, increasing growth rate, postponing harvest, reducing harvest intensity and increasing length of time horizon could reduce the impact of forest harvest on carbon sequestration. The method proposed in this study is more proper to assess the impact on carbon sequestration, and it has much wider applications in forest management practice. Copyright © 2017. Published by Elsevier B.V.
An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics.
Williams, Perry J; Hooten, Mevin B; Womble, Jamie N; Esslinger, George G; Bower, Michael R; Hefley, Trevor J
2017-02-01
Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or conservation. We describe a statistical framework for simultaneously estimating spatiotemporal occupancy and abundance dynamics of a colonizing species. Our method accounts for several issues that are common when modeling spatiotemporal ecological data including multiple levels of detection probability, multiple data sources, and computational limitations that occur when making fine-scale inference over a large spatiotemporal domain. We apply the model to estimate the colonization dynamics of sea otters (Enhydra lutris) in Glacier Bay, in southeastern Alaska. © 2016 by the Ecological Society of America.
Romano, Alessandro
This article is a first application of an integrable nonautonomous Lotka-Volterra (LV) model to the study of tourism dynamics. In particular, we analyze the interaction in terms of touristic flows among three Italian regions. Confirming an hypothesis advanced by recent theoretical works, we find that these regions not only compete against each other, but at times they also proceed in mutualism. Moreover, the kind and the intensity of the interaction changes over time, suggesting that dynamic models can play a vital role in the study of touristic flows.
Romano, Alessandro
2016-01-01
This article is a first application of an integrable nonautonomous Lotka–Volterra (LV) model to the study of tourism dynamics. In particular, we analyze the interaction in terms of touristic flows among three Italian regions. Confirming an hypothesis advanced by recent theoretical works, we find that these regions not only compete against each other, but at times they also proceed in mutualism. Moreover, the kind and the intensity of the interaction changes over time, suggesting that dynamic models can play a vital role in the study of touristic flows. PMID:27661615
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
Predicting carbon dynamics in integrated production systems in Brazil using the CQESTR model
USDA-ARS?s Scientific Manuscript database
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...
ERIC Educational Resources Information Center
Kim, Min Kyu
2010-01-01
This article discusses an effort to improve training performance in a large corporate conglomerate in South Korea. In particular, focus is placed on a new instructional design (ID) model named the Cogwheel ID model. The cogwheel metaphor is used to illustrate the integrated processes within complex training organizations, including organizational,…
Dynamic model of a micro-tubular solid oxide fuel cell stack including an integrated cooling system
NASA Astrophysics Data System (ADS)
Hering, Martin; Brouwer, Jacob; Winkler, Wolfgang
2017-02-01
A novel dynamic micro-tubular solid oxide fuel cell (MT-SOFC) and stack model including an integrated cooling system is developed using a quasi three-dimensional, spatially resolved, transient thermodynamic, physical and electrochemical model that accounts for the complex geometrical relations between the cells and cooling-tubes. The modeling approach includes a simplified tubular geometry and stack design including an integrated cooling structure, detailed pressure drop and gas property calculations, the electrical and physical constraints of the stack design that determine the current, as well as control strategies for the temperature. Moreover, an advanced heat transfer balance with detailed radiative heat transfer between the cells and the integrated cooling-tubes, convective heat transfer between the gas flows and the surrounding structures and conductive heat transfer between the solid structures inside of the stack, is included. The detailed model can be used as a design basis for the novel MT-SOFC stack assembly including an integrated cooling system, as well as for the development of a dynamic system control strategy. The evaluated best-case design achieves very high electrical efficiency between around 75 and 55% in the entire power density range between 50 and 550 mW /cm2 due to the novel stack design comprising an integrated cooling structure.
Zhao, He; Sokhansanj, Bahrad A
2007-10-01
Microtubule dynamics play a critical role in cell function and stress response, modulating mitosis, morphology, signaling, and transport. Drugs such as paclitaxel (Taxol) can impact tubulin polymerization and affect microtubule dynamics. While theoretical methods have been previously proposed to simulate microtubule dynamics, we develop a methodology here that can be used to compare model predictions with experimental data. Our model is a hybrid of (1) a simple two-state stochastic formulation of tubulin polymerization kinetics and (2) an equilibrium approximation for the chemical kinetics of Taxol drug binding to microtubule ends. Model parameters are biologically realistic, with values taken directly from experimental measurements. Model validation is conducted against published experimental data comparing optical measurements of microtubule dynamics in cultured cells under normal and Taxol-treated conditions. To compare model predictions with experimental data requires applying a "windowing" strategy on the spatiotemporal resolution of the simulation. From a biological perspective, this is consistent with interpreting the microtubule "pause" phenomenon as at least partially an artifact of spatiotemporal resolution limits on experimental measurement.
Kim, Jong Suk; Chen, Jun; Garcia, Humberto E.
2016-06-17
An RO (reverse osmosis) desalination plant is proposed as an effective, FLR (flexible load resource) to be integrated into HES (hybrid energy systems) to support various types of ancillary services to the electric grid, under variable operating conditions. To study the dynamic (transient) analysis of such system, among the various unit operations within HES, special attention is given here to the detailed dynamic modeling and control design of RO desalination process with a spiral-wound membrane module. The model incorporates key physical phenomena that have been investigated individually into a dynamic integrated model framework. In particular, the solution-diffusion model modified with the concentration polarization theory is applied to predict RO performance over a large range of operating conditions. Simulation results involving several case studies suggest that an RO desalination plant, acting as a FLR, can provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess electrical energy. Here, the incorporation of additional commodity (fresh water) produced from a FLR allows a broader range of HES operations for maximizing overall system performance and profitability. For the purpose of assessing the incorporation of health assessment into process operations, an online condition monitoring approach for RO membrane fouling supervision is addressed in the case study presented.
Kim, Jong Suk; Chen, Jun; Garcia, Humberto E.
2016-06-17
An RO (reverse osmosis) desalination plant is proposed as an effective, FLR (flexible load resource) to be integrated into HES (hybrid energy systems) to support various types of ancillary services to the electric grid, under variable operating conditions. To study the dynamic (transient) analysis of such system, among the various unit operations within HES, special attention is given here to the detailed dynamic modeling and control design of RO desalination process with a spiral-wound membrane module. The model incorporates key physical phenomena that have been investigated individually into a dynamic integrated model framework. In particular, the solution-diffusion model modified withmore » the concentration polarization theory is applied to predict RO performance over a large range of operating conditions. Simulation results involving several case studies suggest that an RO desalination plant, acting as a FLR, can provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess electrical energy. Here, the incorporation of additional commodity (fresh water) produced from a FLR allows a broader range of HES operations for maximizing overall system performance and profitability. For the purpose of assessing the incorporation of health assessment into process operations, an online condition monitoring approach for RO membrane fouling supervision is addressed in the case study presented.« less
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.
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.…
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)
Dong, ZhongZhe; Faria, Cassio; Hromčík, Martin; Pluymers, Bert; Šebek, Michael; Desmet, Wim
2017-09-01
Smart structures with integrated macro fiber composite (MFC) piezoelectric transducers have been increasingly investigated in engineering. A simple but elaborate system model of such smart structure not only can predict system dynamics, but also can reduce challenges in application. Therefore, the equivalent force (EF) modeling approach is presented to model the plate-type structures with integrated piezoelectric actuators in a semi-analytical fashion: analytical EF is applied to finite element (FE) structural models. The EF is derived from the bending effort balance between the equivalent loads, and the equivalent loads are developed by introducing the spatial distribution into a generalized Hamilton’s principle. The proposed approach is validated by cantilever aluminum beams with integrated MFC actuators and it is consistent with existing alternative approaches from literature. Then, it is validated on a non-homogeneous composite plate for dynamic applications: a laminated composite plate with integrated MFC actuators was manufactured and both an impact test and MFC drive test were elaborately carried out. The modal validation shows the high fidelity of the EF model and the predicted velocity frequency responds functions (FRFs) agree well with experimental measurement. Being applicable to both numerical and analytical modeling approaches, the EF is actually assigned to the out-plane displacement on the structure and distributed along the edges of the actuators. Therefore, it is convenient to use in EF models. The rotational degrees of freedom could also be eliminated in the EF models without losing structure complexity, since they neither link to the electromechanical coupling nor have a significant kinetic contribution to the system.
Liu, Hui; Benoit, Gaboury; Liu, Tao; Liu, Yong; Guo, Huaicheng
2015-05-15
A reliable system simulation to relate socioeconomic development with water environment and to comprehensively represent a watershed's dynamic features is important. In this study, after identifying lake watershed system processes, we developed a system dynamics modeling framework for managing lake water quality at the watershed scale. Two reinforcing loops (Development and Investment Promotion) and three balancing loops (Pollution, Resource Consumption, and Pollution Control) were constituted. Based on this work, we constructed Stock and Flow Diagrams that embedded a pollutant load model and a lake water quality model into a socioeconomic system dynamics model. The Dianchi Lake in Yunnan Province, China, which is the sixth largest and among the most severely polluted freshwater lakes in China, was employed as a case study to demonstrate the applicability of the model. Water quality parameters considered in the model included chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). The business-as-usual (BAU) scenario and three alternative management scenarios on spatial adjustment of industries and population (S1), wastewater treatment capacity construction (S2), and structural adjustment of agriculture (S3), were simulated to assess the effectiveness of certain policies in improving water quality. Results showed that S2 is most effective scenario, and the COD, TN, and TP concentrations in Caohai in 2030 are 52.5, 10.9, and 0.8 mg/L, while those in Waihai are 9.6, 1.2, and 0.08 mg/L, with sustained development in the watershed. Thus, the model can help support the decision making required in development and environmental protection strategies.
den Breems, Nicoline Y; Nguyen, Lan K; Kulasiri, Don
2014-12-01
Cells transform external stimuli, through the activation of signaling pathways, which in turn activate gene regulatory networks, in gene expression. As more omics data are generated from experiments, eliciting the integrated relationship between the external stimuli, the signaling process in the cell and the subsequent gene expression is a major challenge in systems biology. The complex system of non-linear dynamic protein interactions in signaling pathways and gene networks regulates gene expression. The complexity and non-linear aspects have resulted in the study of the signaling pathway or the gene network regulation in isolation. However, this limits the analysis of the interaction between the two components and the identification of the source of the mechanism differentiating the gene expression profiles. Here, we present a study of a model of the combined signaling pathway and gene network to highlight the importance of integrated modeling. Based on the experimental findings we developed a compartmental model and conducted several simulation experiments. The model simulates the mRNA expression of three different cytokines (RANTES, IL8 and TNFα) regulated by the transcription factor NFκB in mammary epithelial cells challenged with E. coli. The analysis of the gene network regulation identifies a lack of robustness and therefore sensitivity for the transcription factor regulation. However, analysis of the integrated signaling and gene network regulation model reveals distinctly different underlying mechanisms in the signaling pathway responsible for the variation between the three cytokine's mRNA expression levels. Our key findings reveal the importance of integrating the signaling pathway and gene expression dynamics in modeling. Modeling infers valid research questions which need to be verified experimentally and can assist in the design of future biological experiments.
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.
Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.
Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha
2017-09-01
Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.
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
Integrating Dynamic Data and Sensors with Semantic 3D City Models in the Context of Smart Cities
NASA Astrophysics Data System (ADS)
Chaturvedi, K.; Kolbe, T. H.
2016-10-01
Smart cities provide effective integration of human, physical and digital systems operating in the built environment. The advancements in city and landscape models, sensor web technologies, and simulation methods play a significant role in city analyses and improving quality of life of citizens and governance of cities. Semantic 3D city models can provide substantial benefits and can become a central information backbone for smart city infrastructures. However, current generation semantic 3D city models are static in nature and do not support dynamic properties and sensor observations. In this paper, we propose a new concept called Dynamizer allowing to represent highly dynamic data and providing a method for injecting dynamic variations of city object properties into the static representation. The approach also provides direct capability to model complex patterns based on statistics and general rules and also, real-time sensor observations. The concept is implemented as an Application Domain Extension for the CityGML standard. However, it could also be applied to other GML-based application schemas including the European INSPIRE data themes and national standards for topography and cadasters like the British Ordnance Survey Mastermap or the German cadaster standard ALKIS.
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.
Equilibrium dynamical correlations in the Toda chain and other integrable models
NASA Astrophysics Data System (ADS)
Kundu, Aritra; Dhar, Abhishek
2016-12-01
We investigate the form of equilibrium spatiotemporal correlation functions of conserved quantities in the Toda lattice and in other integrable models. From numerical simulations we find that the correlations satisfy ballistic scaling with a remarkable collapse of data from different times. We examine special limiting choices of parameter values, for which the Toda lattice tends to either the harmonic chain or the equal mass hard-particle gas. In both these limiting cases, one can obtain the correlations exactly and we find excellent agreement with the direct Toda simulation results. We also discuss a transformation to "normal mode" variables, as commonly done in hydrodynamic theory of nonintegrable systems, and find that this is useful, to some extent, even for the integrable system. The striking differences between the Toda chain and a truncated version, expected to be nonintegrable, are pointed out.
Curro, John G.; Webb III, Edmund B.; Grest, Gary S.; Weinhold, Jeffrey D.; Putz, Mathias; McCoy, John D.
1999-07-21
Molecular dynamics (MD) simulations were performed on dense liquids of polyethylene chains of 24 and 66 united atom CH{sub 2} units. A series of models was studied ranging in atomistic detail from coarse-grained, freely-jointed, tangent site chains to realistic, overlapping site models subjected to bond angle restrictions and torsional potentials. These same models were also treated with the self-consistent, polymer reference interaction site model (PRISM) theory. The intramolecular and total structure factors, as well as, the intermolecular radial distribution functions g(r) and direct correlation functions C(r) were obtained from theory and simulation. Angular correlation functions were also simulation obtained from the MD simulations. Comparisons between theory and reveal that PRISM theory works well for computing the intermolecular structure of coarse-grained chain models, but systematically underpredicts the extent of intermolecular packing as more atomistic details are introduced into the model. A consequence of g(r) having insufficient structure is that the theory yields an isothermal compressibility that progressively becomes larger, relative to the simulations, as overlapping the PRISM sites and angular restrictions are introduced into the model. We found that theory could be considerably improved by adding a tail function to C(r) beyond the effective hard core diameter. The range of this tail function was determined by requiring the theory to yield the correct compressibility.
Manesso, Erica; Teles, José; Bryder, David; Peterson, Carsten
2013-01-01
A very high number of different types of blood cells must be generated daily through a process called haematopoiesis in order to meet the physiological requirements of the organism. All blood cells originate from a population of relatively few haematopoietic stem cells residing in the bone marrow, which give rise to specific progenitors through different lineages. Steady-state dynamics are governed by cell division and commitment rates as well as by population sizes, while feedback components guarantee the restoration of steady-state conditions. In this study, all parameters governing these processes were estimated in a computational model to describe the haematopoietic hierarchy in adult mice. The model consisted of ordinary differential equations and included negative feedback regulation. A combination of literature data, a novel divide et impera approach for steady-state calculations and stochastic optimization allowed one to reduce possible configurations of the system. The model was able to recapitulate the fundamental steady-state features of haematopoiesis and simulate the re-establishment of steady-state conditions after haemorrhage and bone marrow transplantation. This computational approach to the haematopoietic system is novel and provides insight into the dynamics and the nature of possible solutions, with potential applications in both fundamental and clinical research. PMID:23256190
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). Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Starc, Blaž; Čepon, Gregor; Boltežar, Miha
2017-04-01
A new numerical procedure for efficient dynamics simulations of linear-elastic systems with unilateral contacts is proposed. The method is based on the event-driven integration of a contact problem with a combination of single- and set-valued force laws together with classical model-reduction techniques. According to the contact state, the developed event-driven integration enables the formulation of reduced system matrices. Moreover, to enable the transition among different reduced spaces the formulation of the initial conditions is also presented. The method has been developed separately for each of the four most popular model-reduction techniques (Craig-Bampton, MacNeal, Rubin and dual Craig-Bampton). The applicability of the newly presented method is demonstrated on a simple clamped-beam structure with a unilateral contact, which is excited with a harmonic force at the free end.
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.
Shilton, A; Harrison, J
2003-01-01
CFD mathematical modelling offers the potential to predict the actual flow pattern in a pond rather than generalising its mixing and mass transport as either an ideal flow reactor or, in the case of the non-ideal flow reactor, as a single dispersion number. However, perhaps the greatest benefit that CFD offers over the previous approaches is its ability to directly account for physical influences on the pond hydraulics such as the addition of baffles for example. In addition to solving the equations of fluid flow, CFD modelling also allows incorporation of other equations. The next logical development is, therefore, the integration of a reaction model within its solution domain. This potential has been recognised by several researchers, but to date no such work has been published. The primary aim of this paper was to present a CFD model of a field pond that incorporates the first order decay equation for coliforms. Experimental monitoring of the field pond gave an average effluent concentration of 3,710 f.c./100 mL, while the CFD model predicted 4,600 f.c./100 mL. Considering the pond provides an order of magnitude decrease in faecal coliform concentration, the integrated CFD model has clearly predicted the treatment efficiency very well. The secondary aim of this paper was to demonstrate the potential application of this technique. A typical pond was designed and modelled along with two variations incorporating two baffles and six baffles respectively. As is typically found in pond systems, the standard design suffered from severe short-circuiting with the model predicting a value of 6.2 x 10(6) f.c./100 mL at the outlet. The simulations of the baffled designs illustrate how treatment efficiency was improved by reducing the short-circuiting through the pond. The model predicted values of 6.0 x 10(3) f.c./100 mL for the 2-baffle design and 5.7 x 10(2) f.c./100 mL for the 6-baffle design.
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
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.
Eacker, Daniel R; Lukacs, Paul M; Proffitt, Kelly M; Hebblewhite, Mark
2017-06-01
To successfully respond to changing habitat, climate or harvest, managers need to identify the most effective strategies to reverse population trends of declining species and/or manage harvest of game species. A classic approach in conservation biology for the last two decades has been the use of matrix population models to determine the most important vital rates affecting population growth rate (λ), that is, sensitivity. Ecologists quickly realized the critical role of environmental variability in vital rates affecting λ by developing approaches such as life-stage simulation analysis (LSA) that account for both sensitivity and variability of a vital rate. These LSA methods used matrix-population modeling and Monte Carlo simulation methods, but faced challenges in integrating data from different sources, disentangling process and sampling variation, and in their flexibility. Here, we developed a Bayesian integrated population model (IPM) for two populations of a large herbivore, elk (Cervus canadensis) in Montana, USA. We then extended the IPM to evaluate sensitivity in a Bayesian framework. We integrated known-fate survival data from radio-marked adults and juveniles, fecundity data, and population counts in a hierarchical population model that explicitly accounted for process and sampling variance. Next, we tested the prevailing paradigm in large herbivore population ecology that juvenile survival of neonates <90 d old drives λ using our Bayesian LSA approach. In contrast to the prevailing paradigm in large herbivore ecology, we found that adult female survival explained more of the variation in λ than elk calf survival, and that summer and winter elk calf survival periods were nearly equivalent in importance for λ. Our Bayesian IPM improved precision of our vital rate estimates and highlighted discrepancies between count and vital rate data that could refine population monitoring, demonstrating that combining sensitivity analysis with population modeling
Integrated Dynamic Gloabal Modeling of Land Use, Energy and Economic Growth
Atul Jain, University of Illinois, Urbana-Champaign, IL Brian O'Neill, NCAR, Boulder, CO
2009-10-14
The overall objective of this collaborative project is to integrate an existing general equilibrium energy-economic growth model with a biogeochemical cycles and biophysical models in order to more fully explore the potential contribution of land use-related activities to future emissions scenarios. Land cover and land use change activities, including deforestation, afforestation, and agriculture management, are important source of not only CO2, but also non-CO2 GHGs. Therefore, contribution of land-use emissions to total emissions of GHGs is important, and consequently their future trends are relevant to the estimation of climate change and its mitigation. This final report covers the full project period of the award, beginning May 2006, which includes a sub-contract to Brown University later transferred to the National Center for Atmospheric Research (NCAR) when Co-PI Brian O'Neill changed institutional affiliations.
Sehr, Christiana; Kremling, Andreas; Marin-Sanguino, Alberto
2015-01-01
During the last 10 years, systems biology has matured from a fuzzy concept combining omics, mathematical modeling and computers into a scientific field on its own right. In spite of its incredible potential, the multilevel complexity of its objects of study makes it very difficult to establish a reliable connection between data and models. The great number of degrees of freedom often results in situations, where many different models can explain/fit all available datasets. This has resulted in a shift of paradigm from the initially dominant, maybe naive, idea of inferring the system out of a number of datasets to the application of different techniques that reduce the degrees of freedom before any data set is analyzed. There is a wide variety of techniques available, each of them can contribute a piece of the puzzle and include different kinds of experimental information. But the challenge that remains is their meaningful integration. Here we show some theoretical results that enable some of the main modeling approaches to be applied sequentially in a complementary manner, and how this workflow can benefit from evolutionary reasoning to keep the complexity of the problem in check. As a proof of concept, we show how the synergies between these modeling techniques can provide insight into some well studied problems: Ammonia assimilation in bacteria and an unbranched linear pathway with end-product inhibition. PMID:26501332
Dattner, Itai; Miller, Ezer; Petrenko, Margarita; Kadouri, Daniel E; Jurkevitch, Edouard; Huppert, Amit
2017-01-01
Most bacterial habitats are topographically complex in the micro scale. Important examples include the gastrointestinal and tracheal tracts, and the soil. Although there are myriad theoretical studies that explore the role of spatial structures on antagonistic interactions (predation, competition) among animals, there are many fewer experimental studies that have explored, validated and quantified their predictions. In this study, we experimentally monitored the temporal dynamic of the predatory bacterium Bdellovibrio bacteriovorus, and its prey, the bacterium Burkholderia stabilis in a structured habitat consisting of sand under various regimes of wetness. We constructed a dynamic model, and estimated its parameters by further developing the direct integral method, a novel estimation procedure that exploits the separability of the states and parameters in the model. We also verified that one of our parameter estimates was consistent with its known, directly measured value from the literature. The ability of the model to fit the data combined with realistic parameter estimates indicate that bacterial predation in the sand can be described by a relatively simple model, and stress the importance of prey refuge on predation dynamics in heterogeneous environments. © 2017 The Author(s).
Winger, Moritz; Trzesniak, Daniel; Baron, Riccardo; van Gunsteren, Wilfred F
2009-03-28
The use of a coarse-grained (CG) model that is widely used in molecular dynamics simulations of biomolecular systems is investigated with respect to the dependence of a variety of quantities upon the size of the used integration time step and cutoff radius. The results suggest that when using a non-bonded interaction-cutoff radius of 1.4 nm a time step of maximally 10 fs should be used, in order not to produce energy sinks or wells. Using a too-large time step, e.g. 50 fs with a cutoff of 1.2 nm, as is done in the coarse-grained model of Marrink et al. (J. Phys. Chem. B, 2004, 108, 250 and 2007, 111, 7812), induces errors due to the linear approximation of the integrators that are commonly used to integrate the equations of motion. As a spin-off of the investigation of the mentioned CG models, we found that the parameters of the CG water model place it at physiological temperatures well into the solid phase of the phase diagram.
Elucidating the Population Dynamics of Japanese Knotweed Using Integral Projection Models
Dauer, Joseph T.; Jongejans, Eelke
2013-01-01
Plant demographic studies coupled with population modeling are crucial components of invasive plant management because they inform managers when in a plant’s life cycle it is most susceptible to control efforts. Providing land managers with appropriate data can be especially challenging when there is limited data on potentially important transitions that occur belowground. For 2 years, we monitored 4 clonal Japanese knotweed (Polygonumcuspidatum) infestations for emergence, survival, shoot height until leaf senescence, dry shoot biomass after senescence, and rhizome connections for 424 shoots. We developed an integral projection model using both final autumn shoot height and shoot biomass as predictors of survival between years, growth from year to year, and number of rhizomes produced by a shoot (fecundity). Numbers of new shoots within an infestation (population growth rate λ) were projected to increase 13-233% in a year, with the greatest increase at the most frequently disturbed site. Elasticity analysis revealed population growth at 3 of the 4 sites was primarily due to ramet survival between years and to year-to-year growth in shoot height and shoot biomass. Population growth at the fourth site, the most disturbed, was due to the large production of new rhizomes and associated shoots. In contrast to previous studies, our excavation revealed that most of the shoots were not interconnected, suggesting rhizome production may be limited by the size or age of the plants, resource availability, disturbance frequency, or other factors. Future integration of plant population models with more data on belowground growth structures will clarify the critical stages in Japanese knotweed life cycle and support land managers in their management decisions. PMID:24073249
Elucidating the population dynamics of Japanese knotweed using integral projection models.
Dauer, Joseph T; Jongejans, Eelke
2013-01-01
Plant demographic studies coupled with population modeling are crucial components of invasive plant management because they inform managers when in a plant's life cycle it is most susceptible to control efforts. Providing land managers with appropriate data can be especially challenging when there is limited data on potentially important transitions that occur belowground. For 2 years, we monitored 4 clonal Japanese knotweed (Polygonumcuspidatum) infestations for emergence, survival, shoot height until leaf senescence, dry shoot biomass after senescence, and rhizome connections for 424 shoots. We developed an integral projection model using both final autumn shoot height and shoot biomass as predictors of survival between years, growth from year to year, and number of rhizomes produced by a shoot (fecundity). Numbers of new shoots within an infestation (population growth rate λ) were projected to increase 13-233% in a year, with the greatest increase at the most frequently disturbed site. Elasticity analysis revealed population growth at 3 of the 4 sites was primarily due to ramet survival between years and to year-to-year growth in shoot height and shoot biomass. Population growth at the fourth site, the most disturbed, was due to the large production of new rhizomes and associated shoots. In contrast to previous studies, our excavation revealed that most of the shoots were not interconnected, suggesting rhizome production may be limited by the size or age of the plants, resource availability, disturbance frequency, or other factors. Future integration of plant population models with more data on belowground growth structures will clarify the critical stages in Japanese knotweed life cycle and support land managers in their management decisions.
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."
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.
Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin
2014-06-01
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. 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. 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. 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.
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.
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.
Shiying Tian; Mohamed A. Youssef; R. Wayne Skaggs; Devendra M. Amatya; G.M. Chescheir
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,...
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.
Hayashi, Takehiko I; Imaizumi, Yoshitaka; Yokomizo, Hiroyuki; Tatarazako, Norihisa; Suzuki, Noriyuki
2016-01-01
Application of herbicides to paddy fields in Japan has strong seasonality, and their environmental concentrations exhibit clear spatiotemporal variation. The authors developed an approach that combines a multimedia environmental exposure model (Grid-Catchment Integrated Modeling System) and density dynamics models for algae. This approach enabled assessment of ecological risk when the exposure concentration shows spatiotemporal variation. First, risk maps of 5 herbicides (pretilachlor, butachlor, simetryn, mefenacet, and esprocarb) were created from the spatial predictions of environmental concentrations and 50% inhibitory concentrations of the herbicides. Simulations of algal density dynamics at high-risk sites were then conducted by incorporating the predicted temporal dynamics of the environmental concentration of each herbicide at the sites. The results suggested that the risk of pretilachlor was clearly the highest of the 5 herbicides, in terms of both the spatial distributions and the temporal durations. The present study highlights the importance of integrating exposure models and effect models to clarify spatial and temporal risk and to develop management plans for chemical exposure that shows high spatiotemporal variation.
A System Dynamics Model for Integrated Decision Making: The Durham-Orange Light Rail Project
EPA’s Sustainable and Healthy Communities Research Program (SHC) is conducting transdisciplinary research to inform and empower decision-makers. EPA tools and approaches are being developed to enable communities to effectively weigh and integrate human health, socioeconomic, envi...
A System Dynamics Model for Integrated Decision Making: The Durham-Orange Light Rail Project
EPA’s Sustainable and Healthy Communities Research Program (SHC) is conducting transdisciplinary research to inform and empower decision-makers. EPA tools and approaches are being developed to enable communities to effectively weigh and integrate human health, socioeconomic, envi...
Jung, Jinwoo; Lee, Jewon; Song, Hanjung
2011-03-15
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.
Jung, Jinwoo; Lee, Jewon; Song, Hanjung
2011-03-01
This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performed simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-μm single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with ± 2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.
NASA Astrophysics Data System (ADS)
Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.
2016-12-01
State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.
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 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)
Caffrey, Peter F.; Hoppel, William A.; Shi, Jainn J.
2006-12-01
The dynamics of aerosols in the marine boundary layer are simulated with a one-dimensional, multicomponent, sectional aerosol model using vertical profiles of turbulence, relative humidity, temperature, vertical velocity, cloud cover, and precipitation provided by 3-D mesoscale meteorological model output. The Naval Research Laboratory's (NRL) sectional aerosol model MARBLES (Fitzgerald et al., 1998a) was adapted to use hourly meteorological input taken from NRL's Coupled Ocean-Atmosphere Prediction System (COAMPS). COAMPS-generated turbulent mixing coefficients and large-scale vertical velocities determine vertical exchange within the marine boundary layer and exchange with the free troposphere. Air mass back trajectories were used to define the air column history along which the meteorology was retrieved for use with the aerosol model. Details on the integration of these models are described here, as well as a description of improvements made to the aerosol model, including transport by large-scale vertical motions (such as subsidence and lifting), a revised sea-salt aerosol source function, and separate tracking of sulfate mass from each of the five sources (free tropospheric, nucleated, condensed from gas phase oxidation products, cloud-processed, and produced from heterogeneous oxidation of S(IV) on sea-salt aerosol). Results from modeling air masses arriving at Oahu, Hawaii, are presented, and the relative contribution of free-tropospheric sulfate particles versus sea-salt aerosol from the surface to CCN concentrations is discussed. Limitations and benefits of the method are presented, as are sensitivity analyses of the effect of large-scale vertical motions versus turbulent mixing.
Dynamic models for control system design of integrated robot and drive systems
NASA Astrophysics Data System (ADS)
Good, M. C.; Sweet, L. M.; Strobel, K. L.
1985-03-01
The design of high performance motion controls for industrial robots is based on accurate models for the robot arm and drive systems. This paper presents analytical models and experimental data to show that interactions between electromechanical drives coupled with compliant linkages to arm link drive points are of fundamental importance to robot control system design. Flexibility in harmonic drives produces resonances in the 5 Hz to 8 Hz range. Flexibility in the robot linkages and joints connecting essentially rigid arm members produces higher frequency modes at 14 Hz and 40 Hz. The nonlinear characteristics of the drive system are modeled, and compared to experimental data. The models presented have been validated over the frequency range 0 to 50 Hz. The paper concludes with a brief discussion of the influence of model characteristics on motion control design.
Uddin, Sardar M Z; Qin, Yi-Xian
2015-06-01
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 into five groups, 1) age-matched (AM), 2) non-suspended sham (NS), 3) non-suspended-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). The 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 μm(3)/μm(2)/day) 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 femurs
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
USDA-ARS?s Scientific Manuscript database
Cellular automata (CA) is a powerful tool in modeling the evolution of macroscopic scale phenomena as it couples time, space, and variable together while remaining in a simplified form. However, such application has remained challenging in landscape-level chronic forest insect epidemics due to the h...
An integrative model of internal axoneme mechanics and external fluid dynamics in ciliary beating.
Dillon, R H; Fauci, L J
2000-12-07
We present a fluid-mechanical model of an individual cilium which incorporates discrete representations of the dynein arms, the passive elastic structure of the axoneme including the microtubules and nexin links. This model, based upon the immersed boundary method (Peskin, 1977), couples the internal force generation of the molecular motors through the passive elastic structure with the external fluid mechanics governed by the Navier-Stokes equations. Detailed geometric information is available, such as the spacing and shear between the microtubules, the local curvature of individual microtubules and the stretching of the nexin links. In addition, the explicit representation of the dynein motors allows us the flexibility to incorporate a variety of activation theories. In this article, we choose a simple activation theory so that the ciliary beat is not present, but is an emergent property of the interacting components of the coupled fluid-axoneme system. We present numerical results from computer simulations of sliding disintegration and ciliary beating with several different viscosities.
NASA Astrophysics Data System (ADS)
Gilbert, James M.; Maxwell, Reed M.
2017-02-01
Widespread irrigated agriculture and a growing population depend on the complex hydrology of the San Joaquin River basin in California. The challenge of managing this complex hydrology hinges, in part, on understanding and quantifying how processes interact to support the groundwater and surface water systems. Here, we use the integrated hydrologic platform ParFlow-CLM to simulate hourly 1 km gridded hydrology over 1 year to study un-impacted groundwater-surface water dynamics in the basin. Comparisons of simulated results to observations show the model accurately captures important regional-scale partitioning of water among streamflow, evapotranspiration (ET), snow, and subsurface storage. Analysis of this simulated Central Valley groundwater system reveals the seasonal cycle of recharge and discharge as well as the role of the small but temporally constant portion of groundwater recharge that comes from the mountain block. Considering uncertainty in mountain block hydraulic conductivity, model results suggest this component accounts for 7-23 % of total Central Valley recharge. A simulated surface water budget guides a hydrograph decomposition that quantifies the temporally variable contribution of local runoff, valley rim inflows, storage, and groundwater to streamflow across the Central Valley. Power spectra of hydrograph components suggest interactions with groundwater across the valley act to increase longer-term correlation in San Joaquin River outflows. Finally, model results reveal hysteresis in the relationship between basin streamflow and groundwater contributions to flow. Using hourly model results, we interpret the hysteretic cycle to be a result of daily-scale fluctuations from precipitation and ET superimposed on seasonal and basin-scale recharge and discharge.
Wang, Kun; D'Argenio, David Z.; Acosta, Edward P.; Sheth, Anandi N.; Delille, Cecile; Lennox, Jeffrey L.; Kerstner-Wood, Corenna; Ofotokun, Ighovwerha
2014-01-01
Background Lopinavir (LPV)/ritonavir (RTV) co-formulation (LPV/RTV) is a widely used protease inhibitor (PI) based regimen to treat HIV-infection. As with all PIs, the trough concentration (Ctrough) is a primary determinant of response, but the optimum exposure remains poorly defined. The primary objective was to develop an integrated LPV population pharmacokinetic model to investigate the influence of α-1-acid glycoprotein (AAG) and link total and free LPV exposure to pharmacodynamic changes in HIV-1 RNA and assess viral dynamic and drug efficacy parameters. Methods Data from 35 treatment-naïve HIV-infected patients initiating therapy with LPV/RTV 400/100 mg orally twice daily across two studies were used for model development and simulations using ADAPT. Total LPV (LPVt) and RTV concentrations were measured by high-performance liquid chromatography (HPLC) with ultraviolet (UV) detection. Free LPV (LPVf) concentrations were measured using equilibrium dialysis and mass spectrometry. Results LPVt typical value of clearance (CLLPVt/F) was 4.73 L/h and distribution volume (VLPVt/F) was 55.7 L. Clearance (CLLPVf/F) and distibution volume (Vf/F) for LPVf were 596 L/h and 6370 L, respectively. Virion clearance rate was 0.0350 h-1. Simulated LPVLPVt Ctrough at 90% (EC90) and 95% (EC95) maximum response were 316 and 726 ng/mL, respectively. Conclusion The pharmacokinetic/pharmacodynamic model provides a useful tool to quantitatively describe the relationship between LPV/RTV exposure and viral response. This comprehensive modeling and simulation approach could be used as a surrogate assessment of ARV where adequate early phase dose-ranging studies are lacking in order to define target trough concentrations and possibly refine dosing recommendations. PMID:24311282
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)
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.
A climate game based on a Multi-Actor Dynamic Integrated Assessment Model (MADIAM)
NASA Astrophysics Data System (ADS)
Weber, M.; Hasselmann, K.
2003-04-01
In November 2002 a special exhibition on climate issues opened in the German Museum for Science and Techniques ('Deutsches Museum') in Munich. Within this exposition we present an interactive game in which visitors control future climate policy by adopting the role of either the government, a CEO (Chief Executive Officer) of a global company or a typical private household of an industrialized country. The players endeavor to maintain a sustainable climate in the future (global goal) while pursuing their own individual welfare goals. Task of the exhibition visitor is to combine the personal interests of the actor he is adopting with the global goal. The individual goal of government is maintain economic growth while avoiding conflicts due to inter-regional or societal inequalities. The CEO seeks to maximize total profits (business earnings). The goal of households is to maximize wages and interest earnings. The evolution of the economic system and climate is governed by the decisions of the actors. Government sets economic side conditions in terms of carbon taxes, subsidies for R&D or market infusion support for climate-friendly technologies, and transfers development aid to less advanced regions. The CEOs decide how much to invest in a number of alternative investment options and in which region. Households influences the economy by their purchasing and savings decisions. The model considers four regions, three real actors (mentioned above) and two different goods (climate-adverse and a climate-friendly). We introduce four different kinds of energy (coal, oil/gas, nuclear, renewable). A World Bank handles money flows. At different points in time the actors can cooperate with other actors in order to reach the global goal Stochastic elements regarding future technology and future climate are included. A touch-screen monitor with user friendly interface is used to present animations and videos. An animated climate scientist uses a climate simulator to compute future
Davis, Amy J.; Hooten, Mevin B.; Phillips, Michael L.; Doherty, Paul F.
2014-01-01
Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short-term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage-grouse (Centrocercus minimus). The long-term population index data available for Gunnison sage-grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage-grouse to be variable and slightly declining over the past 16 years.
Davis, Amy J; Hooten, Mevin B; Phillips, Michael L; Doherty, Paul F
2014-11-01
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.
Davis, Amy J; Hooten, Mevin B; Phillips, Michael L; Doherty, Paul F
2014-01-01
Evaluation of population dynamics for rare and declining species is often limited to data that are sparse and/or of poor quality. Frequently, the best data available for rare bird species are based on large-scale, population count data. These data are commonly based on sampling methods that lack consistent sampling effort, do not account for detectability, and are complicated by observer bias. For some species, short-term studies of demographic rates have been conducted as well, but the data from such studies are typically analyzed separately. To utilize the strengths and minimize the weaknesses of these two data types, we developed a novel Bayesian integrated model that links population count data and population demographic data through population growth rate (λ) for Gunnison sage-grouse (Centrocercus minimus). The long-term population index data available for Gunnison sage-grouse are annual (years 1953–2012) male lek counts. An intensive demographic study was also conducted from years 2005 to 2010. We were able to reduce the variability in expected population growth rates across time, while correcting for potential small sample size bias in the demographic data. We found the population of Gunnison sage-grouse to be variable and slightly declining over the past 16 years. PMID:25540687
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.
Integrative structure modeling with IMP.
Webb, Benjamin; Viswanath, Shruthi; Bonomi, Massimiliano; Pellarin, Riccardo; Greenberg, Charles H; Saltzberg, Daniel; Sali, Andrej
2017-09-28
Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (IMP) (https://integrativemodeling.org), and demonstrate its use. This article is protected by copyright. All rights reserved. © 2017 The Protein Society.
NASA Astrophysics Data System (ADS)
West, Bruce J.
The proper methodology for describing the dynamics of certain complex phenomena and fractal time series is the fractional calculus through the fractional Langevin equation discussed herein and applied in a biomedical context. We show that a fractional operator (derivative or integral) acting on a fractal function, yields another fractal function, allowing us to construct a fractional Langevin equation to describe the evolution of a fractal statistical process, for example, human gait and cerebral blood flow. The goal of this talk is to make clear how certain complex phenomena, such as those that are abundantly present in human physiology, can be faithfully described using dynamical models involving fractional differential stochastic equations. These models are tested against existing data sets and shown to describe time series from complex physiologic phenomena quite well.
NASA Astrophysics Data System (ADS)
Wan, Shun Zhou; Wang, Cun Xin; Shi, Yun Yu
An efficient procedure is introduced for a generalized Langevin dynamics simulation when the exponential model is taken for the friction kernel. The leap frog algorithm is used for numerical integration of the generalized Langevin equation. Simulation with this model has been performed on a cyclic undecapeptide, cyclosporin A (CPA). By comparison with the results obtained from previous simulations, the method proves to be reliable and efficient in the simulation of CPA.
NASA Astrophysics Data System (ADS)
Murawski, Jens; Kleine, Eckhard
2017-04-01
Sea ice remains one of the frontiers of ocean modelling and is of vital importance for the correct forecasts of the northern oceans. At large scale, it is commonly considered a continuous medium whose dynamics is modelled in terms of continuum mechanics. Its specifics are a matter of constitutive behaviour which may be characterised as rigid-plastic. The new developed sea ice dynamic module bases on general principles and follows a systematic approach to the problem. Both drift field and stress field are modelled by a variational property. Rigidity is treated by Lagrangian relaxation. Thus one is led to a sensible numerical method. Modelling fast ice remains to be a challenge. It is understood that ridging and the formation of grounded ice keels plays a role in the process. The ice dynamic model includes a parameterisation of the stress associated with grounded ice keels. Shear against the grounded bottom contact might lead to plastic deformation and the loss of integrity. The numerical scheme involves a potentially large system of linear equations which is solved by pre-conditioned iteration. The entire algorithm consists of several components which result from decomposing the problem. The algorithm has been implemented and tested in practice.
Equivalence Between Approximate Dynamic Inversion and Proportional-Integral Control
2008-09-29
systems that renders the closed-loop error dynamics independent of the reference model dynamics. The equivalent PI controller will be derived and both of...integral control, PI control . I. INTRODUCTION DYNAMIC inversion (DI) or feedback linearization isa popular control design method that is well suited for...Proportional-Integral (PI) model reference controller realiza- tion. The key characteristic of the equivalent PI controller is that it is largely independent
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...
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...
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).
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.
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.
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. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
An Integrated Crustal Dynamics Simulator
NASA Astrophysics Data System (ADS)
Xing, H. L.; Mora, P.
2007-12-01
Numerical modelling offers an outstanding opportunity to gain an understanding of the crustal dynamics and complex crustal system behaviour. This presentation provides our long-term and ongoing effort on finite element based computational model and software development to simulate the interacting fault system for earthquake forecasting. A R-minimum strategy based finite-element computational model and software tool, PANDAS, for modelling 3-dimensional nonlinear frictional contact behaviour between multiple deformable bodies with the arbitrarily-shaped contact element strategy has been developed by the authors, which builds up a virtual laboratory to simulate interacting fault systems including crustal boundary conditions and various nonlinearities (e.g. from frictional contact, materials, geometry and thermal coupling). It has been successfully applied to large scale computing of the complex nonlinear phenomena in the non-continuum media involving the nonlinear frictional instability, multiple material properties and complex geometries on supercomputers, such as the South Australia (SA) interacting fault system, South California fault model and Sumatra subduction model. It has been also extended and to simulate the hot fractured rock (HFR) geothermal reservoir system in collaboration of Geodynamics Ltd which is constructing the first geothermal reservoir system in Australia and to model the tsunami generation induced by earthquakes. Both are supported by Australian Research Council.
Integrated Modeling Environment
NASA Technical Reports Server (NTRS)
Mosier, Gary; Stone, Paul; Holtery, Christopher
2006-01-01
The Integrated Modeling Environment (IME) is a software system that establishes a centralized Web-based interface for integrating people (who may be geographically dispersed), processes, and data involved in a common engineering project. The IME includes software tools for life-cycle management, configuration management, visualization, and collaboration.
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)
Morozova, Polina; Volodin, Evgeny; Rybak, Oleg; Huybrechts, Philippe; Korneva, Irina; Kaminskaia, Mariia
2017-04-01
Earth system models (ESMs) have been widely used in the recent years for complex studies of the climate system of the planet in the context of interactions between the atmosphere, oceans, ice sheets and the biosphere. Incorporation of the Earth syb-systems with very different spatial and temporal scales and response times into one model is really a challenging task. In particular, coupling of an AO GCM and ice sheet models of Greenland and Antarctic ice sheets (GrIS and AIS) requires application of special downscaling procedures. Within the frameworks of our research study, we implemented several coupling strategies. The choice of a strategy is dictated mostly by two factors - by the purpose of the research and by spatial resolution of an AO GCM. Several versions of the latter (called INMCM) were developed in the Institute of Numerical Mathematics (Moscow, Russia). For instance, the version aimed primarily for the relatively long numerical experiments (for e.g. palaeostudies) has spatial resolution of 5°×4°, 21 vertical layers in the atmospheric block, 2.5°×2°, 33 vertical layers in the oceanic block. To provide proper data exchange between the INMCM and GrIS and AIS models (spatial resolution 20×20 km), we employ rather simple buffer (sub-) models, describing regional heat and moisture diffusion. Applying buffer models enables to avoid systematic shifts in INMCM-generated precipitation fields and to much more realistically describe influence orographically driven precipitation (in Greenland) and elevation-temperature dependence. Novel versions of the INMCM with the spatial resolution of 2,5°×2° and higher generate much more realistic climatic fields, therefore the coupling procedure can be simplified to just averaging, resampling and remapping data from the AO GCM global domain to regional domains enclosing ice sheets. Increase in spatial resolution inevitably causes additional computational cost and reduces the area of the ESM application to
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
NASA Technical Reports Server (NTRS)
Wallerstein, D. V.; Lahey, R. S.; Haggenmacher, G. W.
1977-01-01
Many of the practical aspects and problems of ensuring the integrity of a structural model are discussed, as well as the steps which have been taken in the NASTRAN system to assure that these checks can be routinely performed. Model integrity as used applies not only to the structural model but also to the loads applied to the model. Emphasis is also placed on the fact that when dealing with substructure analysis, all of the checking procedures discussed should be applied at the lowest level of substructure prior to any coupling.
NASA Technical Reports Server (NTRS)
Wallerstein, D. V.; Lahey, R. S.; Haggenmacher, G. W.
1977-01-01
Many of the practical aspects and problems of ensuring the integrity of a structural model are discussed, as well as the steps which have been taken in the NASTRAN system to assure that these checks can be routinely performed. Model integrity as used applies not only to the structural model but also to the loads applied to the model. Emphasis is also placed on the fact that when dealing with substructure analysis, all of the checking procedures discussed should be applied at the lowest level of substructure prior to any coupling.
Li, Liang; Chen, Zhiqiang; Cong, Wenxiang; Wang, Ge
2015-03-01
Spectral CT with photon counting detectors can significantly improve CT performance by reducing image noise and dose, increasing contrast resolution and material specificity, as well as enabling functional and molecular imaging with existing and emerging probes. However, the current photon counting detector architecture is difficult to balance the number of energy bins and the statistical noise in each energy bin. Moreover, the hardware support for multi-energy bins demands a complex circuit which is expensive. In this paper, we promote a new scheme known as hybrid detectors that combine the dynamic-threshold-based counting and integrating modes. In this scheme, an energy threshold can be dynamically changed during a spectral CT scan, which can be considered as compressive sensing along the spectral dimension. By doing so, the number of energy bins can be retrospectively specified, even in a spatially varying fashion. To establish the feasibility and merits of such hybrid detectors, we develop a tensor-based PRISM algorithm to reconstruct a spectral CT image from dynamic dual-energy data, and perform experiments with simulated and real data, producing very promising results.
Integrated modeling 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.
Zeng, Lingxiao; Guan, Mengxin; Jin, Hongwei; Liu, Zhenming; Zhang, Liangren
2015-12-01
Homology modeling has been applied to fill in the gap in experimental G protein-coupled receptors structure determination. However, achievement of G protein-coupled receptors homology models with ligand selectivity remains challenging due to structural diversity of G protein-coupled receptors. In this work, we propose a novel strategy by integrating pharmacophore and membrane molecular dynamics (MD) simulations to improve homology modeling of G protein-coupled receptors with ligand selectivity. To validate this integrated strategy, the A2A adenosine receptor (A2A AR), whose structures in both active and inactive states have been established, has been chosen as an example. We performed blind predictions of the active-state A2A AR structure based on the inactive-state structure and compared the performance of different refinement strategies. The blind prediction model combined with the integrated strategy identified ligand-receptor interactions and conformational changes of key structural elements related to the activation of A2 A AR, including (i) the movements of intracellular ends of TM3 and TM5/TM6; (ii) the opening of ionic lock; (iii) the movements of binding site residues. The integrated strategy of pharmacophore with molecular dynamics simulations can aid in the optimization in the identification of side chain conformations in receptor models. This strategy can be further investigated in homology modeling and expand its applicability to other G protein-coupled receptor modeling, which should aid in the discovery of more effective and selective G protein-coupled receptor ligands. © 2015 John Wiley & Sons A/S.
Predictive models of forest dynamics.
Purves, Drew; Pacala, Stephen
2008-06-13
Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.
Kopecz, K
1995-10-01
The systematic variations of regular saccadic reaction times induced in gap/overlap paradigms are addressed by a quantitative model. Intentional and visual information are integrated on a retinotopic representation of visual space, on which activity dynamics is related to movement initiation. Using a specific conception of "motor preparation", known effects of general warnings and fixation point on- and offsets are reproduced. Results of new experiments are predicted and the extent to which fixation point offsets are specific to ocular responses is analyzed in the light of the exposed model architecture. Relations of the theoretical framework to neurophysiological findings are 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)
Novbari, E.; Oron, A.
2011-01-01
The nonlinear dynamics of an axisymmetric liquid film falling on the outer surface of a vertical cylinder is investigated in the framework of the set of two coupled evolution equations derived recently using the energy integral method (EIM). This set of EIM evolution equations is solved numerically and its solutions are compared with the traveling wave solutions derived from it using AUTO. We find that traveling wave solutions of EIM equations can bifurcate either supercritically or subcritically from the base state. The type of bifurcation depends on the parameter set of the problem. The set of EIM equations studied here admits both traveling wave and nonstationary wave flows. We demonstrate that in the case of subcritical primary bifurcation the film dynamics is sensitive to the choice of the initial condition and coexistence of up to five different flows is possible for the same parameter set in the domain of a given periodicity. The case of supercritical primary bifurcation exhibits much lesser dependence on the initial condition, though coexistence of two different flows for the same parameter set is possible. The synergetic approach based on both direct numerical solution of the governing evolution equations and search of traveling wave solutions using AUTO facilitate a discovery of a large variety of flows and help to conclude about stability of the traveling wave flows found using AUTO.
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)
Sharma, Rati; Cherayil, Binny J.
2013-10-01
Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p,r,t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p,r,t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t → ∞. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.
Molenaar, Peter C M
2017-02-16
Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.
NASA Astrophysics Data System (ADS)
Xu, X.; Zhang, X.; Ricciuto, D. M.; Hahn, M. S.; Hanson, P. J.; Kumar, J.; Lipson, D.; Ma, C.; Shi, X.; Song, X.; Tang, G.; Thornton, P. E.; Torn, M. S.; Wullschleger, S. D.; Yuan, F.; Oechel, W. C.; Zona, D.
2016-12-01
The methane (CH4) cycling in the mid-high latitudes is far from certain, primarily due to some well-known gaps in both experiments and models, such as the poor understanding of the seasonality of soil biogeochemical processes, the lack of mechanistic model representation of CH4 cycling and permafrost dynamics. The large uncertainty when scaling up CH4 cycling at both temporal and spatial scales has been identified, however, it is challenging to fully address these uncertainties due to low data availability. The data-model integration could be a powerful approach to improve and validate ecosystem models and to enhance our understanding of the CH4 cycling. In this study, we take advantage of a set of in-situ measurements of methane flux at plot-scale and a flux tower domain scale in Barrow, and five other long-term flux towers along a moisture gradient in Alaska, functional genomic information associated with CH4 processes, and CH4 fluxes from a large manipulative experiment in a Minnesota peatland, as well as a microbial functional group-based CH4 model-CLM-Microbe. Data-model integration is used for duel purposes: upscaling CH4 flux and parameterizing and validating an ecosystem model. A newly designed generic algorithm is used to optimize primary parameters controlling CH4 production and consumption. For the upscaling purpose, the ecosystem model is first parameterized with plot-scale measurements of CH4 flux and ecosystem properties before it is used for site-level and regional simulations across the flux tower domain. The simulated regional CH4 flux will be weighted by spatial contribution of land surface CH4 flux estimated by a footprint model, and then compared with eddy covariance measurements. The low and high boundaries of the CH4 flux in the domain will be estimated for its potential uncertainties during this upscaling process by comparing with empirical modeling method. The upscaling approach with data-model integration adopted in this study is valuable
NASA Astrophysics Data System (ADS)
Forkel, Matthias; Carvalhais, Nuno; Schaphoff, Sibyll; von Bloh, Werner; Thurner, Martin; Thonicke, Kirsten
2014-05-01
Recently produced satellite datasets of vegetation greenness demonstrate a widespread greening of the earth in the last three decades. These positive trends in vegetation greenness are related to changes in leaf area, vegetation cover and photosynthetic activity. Climatic changes, CO2 fertilization, disturbances and other land cover changes are potential drivers of these greening trends. Nevertheless, different satellite datasets show different magnitudes and trends in vegetation greenness. This fact raises the question about the reliability of these datasets. On the other hand, global vegetation models can be potentially used to assess the effects of environmental drivers on vegetation greenness and thus to explore the environmental reliability of these datasets. Unfortunately, current vegetation models have several weaknesses in reproducing observed temporal dynamics in vegetation greenness. Our aim is to integrate multiple earth observation data sets in a dynamic global vegetation model in order to 1) improve the model's capability to reproduce observed dynamics and spatial patterns of vegetation greenness and 2) to assess the spatial and temporal importance of environmental drivers for the seasonal to decadal variability of vegetation greenness. For this purpose, we developed a data integration system for the LPJmL dynamic global vegetation model (LPJmL-DIS). We implemented a new phenology scheme in LPJmL to better represent observed temporal dynamics of FAPAR (fraction of absorbed photosynthetic active radiation). Model parameters were globally optimized using a genetic optimization algorithm. The model optimization was performed globally against 30 year FAPAR time series (GIMMS3g dataset), against 10 year albedo time series (MODIS) and global patterns of gross primary production as up-scaled from FLUXNET eddy covariance measurements. Additionally, we directly prescribed satellite observations of land and tree cover in LPJmL to better represent global
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…
Di Maio, V; Lánský, P; Rodriguez, R
2004-03-01
Different variants of stochastic leaky integrate-and-fire model for the membrane depolarisation of neurons are investigated. The model is driven by a constant input and equidistant pulses of fixed amplitude. These two types of signal are considered under the influence of three types of noise: white noise, jitter on interpulse distance, and noise in the amplitude of pulses. The results of computational experiments demonstrate the enhancement of the signal by noise in subthreshold regime and deterioration of the signal if it is sufficiently strong to carry the information in absence of noise. Our study holds mainly to central neurons that process discrete pulses although an application in sensory system is also available.
Futter, M N; Löfgren, S; Köhler, S J; Lundin, L; Moldan, F; Bringmark, L
2011-12-01
Surface water concentrations of dissolved organic carbon ([DOC]) are changing throughout the northern hemisphere due to changes in climate, land use and acid deposition. However, the relative importance of these drivers is unclear. Here, we use the Integrated Catchments model for Carbon (INCA-C) to simulate long-term (1996-2008) streamwater [DOC] at the four Swedish integrated monitoring (IM) sites. These are unmanaged headwater catchments with old-growth forests and no major changes in land use. Daily, seasonal and long-term variations in streamwater [DOC] driven by runoff, seasonal temperature and atmospheric sulfate (SO₄(2-)) deposition were observed at all sites. Using INCA-C, it was possible to reproduce observed patterns of variability in streamwater [DOC] at the four IM sites. Runoff was found to be the main short-term control on [DOC]. Seasonal patterns in [DOC] were controlled primarily by soil temperature. Measured SO₄(2-) deposition explained some of the long-term [DOC] variability at all sites.
A Dynamic Integrated Fault Diagnosis Method for Power Transformers
Gao, Wensheng; Liu, Tong
2015-01-01
In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified. PMID:25685841
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.
Zhang, Yan-Chun; Prommer, Henning; Broers, Hans Peter; Slomp, Caroline P; Greskowiak, Janek; van der Grift, Bas; Van Cappellen, Philippe
2013-09-17
Leaching of nitrate from agricultural land to groundwater and the resulting nitrate pollution are a major environmental problem worldwide. Its impact is often mitigated in aquifers hosting sufficiently reactive reductants that can promote autotrophic denitrification. In the case of pyrite acting as reductant, however, denitrification is associated with the release of sulfate and often also with the mobilization of trace metals (e.g., arsenic). In this study, reactive transport modeling was used to reconstruct, quantify and analyze the dynamics of the dominant biogeochemical processes in a nitrate-polluted pyrite-containing aquifer and its evolution over the last 50 years in response to changing agricultural practices. Model simulations were constrained by measured concentration depth profiles. Measured (3)H/(3)He profiles were used to support the calibration of flow and conservative transport processes, while the comparison of simulated and measured sulfur isotope signatures acted as additional calibration constraint for the reactive processes affecting sulfur cycling. The model illustrates that denitrification largely prevented an elevated discharge of nitrate to surface waters, while sulfate discharges were significantly increased, peaking around 15 years after the maximum nitrogen inputs.
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
1989-01-01
Management , UCLA. Federgruen, A. and Zipkin , P. (1984), ’A Combined Vehicle Routing and Inventory Allocation Problem’, Operations Research 32(5), 1019-1037...Completion Based Inventory Systems: Optimal Policies for Repair Kits and Spare Machines," Management Science, 31:6 (June 1985). WMSI Working Paper 318. 210...Reprint No. 238 Computer Science in Economics and Management 2 (1989), pp. 3-15 AD-A215 219 INTEGRATED MODELING SYSTEMS by Arthur M. Geoffrion DTIC0
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.
NASA Astrophysics Data System (ADS)
Mendez-Barroso, L. A.; Vivoni, E.; Robles-Morua, A.; Yepez, E. A.; Rodriguez, J. C.; Watts, C.; Saiz-Hernandez, J.
2013-05-01
Seasonal vegetation changes highly affect the energy and hydrologic fluxes in semiarid regions around the world. Accounting for different water use strategies among drought-deciduous ecosystems is important for understanding how these exploit the temporally brief and localized rainfall pulses of the North American Monsoon (NAM). Furthermore, quantifying these plant-water relations can help elucidate the spatial patterns of ecohydrological processes at catchment scale in the NAM region. In this effort, we focus on the San Miguel river basin (~ 3500 km2) in Sonora, Mexico, which exhibits seasonal vegetation greening that varies across ecosystems organized along mountain fronts. To assess the spatial variability of ecohydrological conditions, we relied on diverse tools that included multi-temporal remote sensing observations, model-based meteorological forcing, ground-based water and energy flux measurements and hydrologic simulations carried out at multiple scales. We evaluated the impact of seasonal vegetation dynamics on evapotranspiration (ET), its partitioning into soil evaporation (E) and plant transpiration (T), as well as their spatiotemporal patterns over the course of the NAM season. We utilized ground observations of soil moisture and evapotranspiration estimated by the eddy covariance method at two sites, as well as inferences of ET partitioning from stable isotope measurements, to test the numerical simulations. We found that ecosystem phenological differences lead to variations in the time to peak in transpiration during a season and in the overall seasonal ratio of transpiration to evapotranspiration (T/ET). A sensitivity analysis of the numerical simulations revealed that vegetation cover and the soil moisure threshold at which stomata close exert strong controls on the seasonal dominance of transpiration or evaporation. The dynamics of ET and its partitioning are then mapped spatially revealing that mountain front ecosystems utilize water differently
NASA Astrophysics Data System (ADS)
Zhu, Qing; Zhou, Zhiwen; Duncan, Emily W.; Lv, Ligang; Liao, Kaihua; Feng, Huihui
2017-02-01
Spatio-temporal variability of soil moisture (θ) is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time θ monitoring methods. This restricted the comprehensive and intensive examination of θ dynamics. In this study, we integrated the manual and real-time monitored data to depict the hillslope θ dynamics with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear (support vector machines-SVM) models were used to predict θ at 39 manual sites (collected 1-2 times per month) with θ collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each depth and manual site, an optimal prediction model was then determined at this depth of this site. Results showed that θ at the 39 manual sites can be reliably predicted (root mean square errors <0.028 m3 m-3) using both SMLR and SVM. The linear or non-linear relationship between θ at each manual site and at the three real-time monitoring sites was the main reason for choosing SMLR or SVM as the optimal prediction model. The subsurface flow dynamics was an important factor that determined whether the relationship was linear or non-linear. Depth to bedrock, elevation, topographic wetness index, profile curvature, and θ temporal stability influenced the selection of prediction model since they were related to the subsurface soil water distribution and movement. Using this approach, hillslope θ spatial distributions at un-sampled times and dates can be predicted. Missing information of hillslope θ dynamics can be acquired successfully.
Thermal dynamic modeling study
NASA Technical Reports Server (NTRS)
Ojalvo, I. U.
1972-01-01
Some thermal dynamic requirements associated with the space shuttle vehicle are reviewed. Pertinent scaling laws are discussed and recommendations are offered regarding the need for conducting reduced-scale dynamic tests of major components at elevated temperatures. Items considered are the development and interpretation of thermal dynamic structural scaling laws, the identification of major related problem areas and a presentation of viable model fabrication, instrumentation, and test procedures.
Integrative modeling of the cardiac ventricular myocyte
Winslow, Raimond L.; Cortassa, Sonia; O'Rourke, Brian; Hashambhoy, Yasmin L.; Rice, John Jeremy; Greenstein, Joseph L.
2011-01-01
Cardiac electrophysiology is a discipline with a rich 50-year history of experimental research coupled with integrative modeling which has enabled us to achieve a quantitative understanding of the relationships between molecular function and the integrated behavior of the cardiac myocyte in health and disease. In this paper, we review the development of integrative computational models of the cardiac myocyte. We begin with a historical overview of key cardiac cell models that helped shape the field. We then narrow our focus to models of the cardiac ventricular myocyte and describe these models in the context of their subcellular functional systems including dynamic models of voltage-gated ion channels, mitochondrial energy production, ATP-dependent and electrogenic membrane transporters, intracellular Ca dynamics, mechanical contraction, and regulatory signal transduction pathways. We describe key advances and limitations of the models as well as point to new directions for future modeling research. PMID:20865780
NASA Astrophysics Data System (ADS)
Bocaniov, Serghei A.; Scavia, Donald
2016-06-01
Hypoxia or low bottom water dissolved oxygen (DO) is a world-wide problem of management concern requiring an understanding and ability to monitor and predict its spatial and temporal dynamics. However, this is often made difficult in large lakes and coastal oceans because of limited spatial and temporal coverage of field observations. We used a calibrated and validated three-dimensional ecological model of Lake Erie to extend a statistical relationship between hypoxic extent and bottom water DO concentrations to explore implications of the broader temporal and spatial development and dissipation of hypoxia. We provide the first numerical demonstration that hypoxia initiates in the nearshore, not the deep portion of the basin, and that the threshold used to define hypoxia matters in both spatial and temporal dynamics and in its sensitivity to climate. We show that existing monitoring programs likely underestimate both maximum hypoxic extent and the importance of low oxygen in the nearshore, discuss implications for ecosystem and drinking water protection, and recommend how these results could be used to efficiently and economically extend monitoring programs.
"Slimplectic" Integrators: Variational Integrators for General Nonconservative Dynamics
NASA Astrophysics Data System (ADS)
Tsang, David
2015-12-01
Symplectic integrators are widely used for long-term integration of conservative astrophysical problems due to their ability to preserve the constants of motion; however, they cannot in general be applied in the presence of nonconservative (e.g. dissipative) interactions. Here we present the “slimplectic” integrator, a new type of numerical integrator that shares many of the benefits of traditional symplectic integrators yet is applicable to general nonconservative systems. We utilize a fixed-time-step variational integrator formalism applied to the recently developed principle of stationary nonconservative action. As a result, the generalized momenta and energy (Noether current) evolutions are well-tracked. Slimplectic integrators are well-suited for integrations of systems where nonconservative effects play an important role in the long-term dynamical evolution. As such they are particularly appropriate for cosmological or celestial N-body dynamics problems where nonconservative interactions, e.g., PR drag, gas interactions, or dissipative tides, can play an important role
Gadhe, Changdev G; Kothandan, Gugan; Cho, Seung Joo
2013-01-01
Chemokine receptor 5 (CCR5) is an integral membrane protein that is utilized during human immunodeficiency virus type-1 entry into host cells. CCR5 is a G-protein coupled receptor that contains seven transmembrane (TM) helices. However, the crystal structure of CCR5 has not been reported. A homology model of CCR5 was developed based on the recently reported CXCR4 structure as template. Automated docking of the most potent (14), medium potent (37), and least potent (25) CCR5 antagonists was performed using the CCR5 model. To characterize the mechanism responsible for the interactions between ligands (14, 25, and 37) and CCR5, membrane molecular dynamic (MD) simulations were performed. The position and orientation of ligands (14, 25, and 37) were found to be changed after MD simulations, which demonstrated the ability of this technique to identify binding modes. Furthermore, at the end of simulation, it was found that residues identified by docking were changed and some new residues were introduced in the proximity of ligands. Our results are in line with the majority of previous mutational reports. These results show that hydrophobicity is the determining factor of CCR5 antagonism. In addition, salt bridging and hydrogen bond contacts between ligands (14, 25, and 37) and CCR5 are also crucial for inhibitory activity. The residues newly identified by MD simulation are Ser160, Phe166, Ser180, His181, and Trp190, and so far no site-directed mutagenesis studies have been reported. To determine the contributions made by these residues, additional mutational studies are suggested. We propose a general binding mode for these derivatives based on the MD simulation results of higher (14), medium (37), and lower (25) potent inhibitors. Interestingly, we found some trend for these inhibitors such as, salt bridge interaction between basic nitrogen of ligand and acidic Glu283 seemed necessary for inhibitory activity. Also, two aromatic pockets (pocket I - TM1-3 and pocket II
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…
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
Paixão, Crysttian Arantes; da Costa, Antonio Tavares
2013-06-01
This paper reports the development of a simple dynamic microscopic model to describe the main features of the phenomenon known as dynamic speckle, or biospeckle. Biospeckle is an interference pattern formed when a biological surface is illuminated with coherent light. The dynamic characteristics of biospeckle have been investigated as possible tools for assessing the quality of biological products. Our model, despite its simplicity, was able to reproduce qualitatively the main features of biospeckle. We were able to correlate variations in a microscopic parameter associated with movement of the particles comprising the organic surface with changes in a macroscopic parameter that measures the change rate of a dynamic interference pattern. We showed that this correlation occurs only within a limited range of parameter microscope values. We also showed how our model was able to describe nonuniform surfaces composed of more than one type of particles.
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
The path integral formulation of climate dynamics.
Navarra, Antonio; Tribbia, Joe; Conti, Giovanni
2013-01-01
The chaotic nature of the atmospheric dynamics has stimulated the applications of methods and ideas derived from statistical dynamics. For instance, ensemble systems are used to make weather predictions recently extensive, which are designed to sample the phase space around the initial condition. Such an approach has been shown to improve substantially the usefulness of the forecasts since it allows forecasters to issue probabilistic forecasts. These works have modified the dominant paradigm of the interpretation of the evolution of atmospheric flows (and oceanic motions to some extent) attributing more importance to the probability distribution of the variables of interest rather than to a single representation. The ensemble experiments can be considered as crude attempts to estimate the evolution of the probability distribution of the climate variables, which turn out to be the only physical quantity relevant to practice. However, little work has been done on a direct modeling of the probability evolution itself. In this paper it is shown that it is possible to write the evolution of the probability distribution as a functional integral of the same kind introduced by Feynman in quantum mechanics, using some of the methods and results developed in statistical physics. The approach allows obtaining a formal solution to the Fokker-Planck equation corresponding to the Langevin-like equation of motion with noise. The method is very general and provides a framework generalizable to red noise, as well as to delaying differential equations, and even field equations, i.e., partial differential equations with noise, for example, general circulation models with noise. These concepts will be applied to an example taken from a simple ENSO model.
The Path Integral Formulation of Climate Dynamics
Navarra, Antonio; Tribbia, Joe; Conti, Giovanni
2013-01-01
The chaotic nature of the atmospheric dynamics has stimulated the applications of methods and ideas derived from statistical dynamics. For instance, ensemble systems are used to make weather predictions recently extensive, which are designed to sample the phase space around the initial condition. Such an approach has been shown to improve substantially the usefulness of the forecasts since it allows forecasters to issue probabilistic forecasts. These works have modified the dominant paradigm of the interpretation of the evolution of atmospheric flows (and oceanic motions to some extent) attributing more importance to the probability distribution of the variables of interest rather than to a single representation. The ensemble experiments can be considered as crude attempts to estimate the evolution of the probability distribution of the climate variables, which turn out to be the only physical quantity relevant to practice. However, little work has been done on a direct modeling of the probability evolution itself. In this paper it is shown that it is possible to write the evolution of the probability distribution as a functional integral of the same kind introduced by Feynman in quantum mechanics, using some of the methods and results developed in statistical physics. The approach allows obtaining a formal solution to the Fokker-Planck equation corresponding to the Langevin-like equation of motion with noise. The method is very general and provides a framework generalizable to red noise, as well as to delaying differential equations, and even field equations, i.e., partial differential equations with noise, for example, general circulation models with noise. These concepts will be applied to an example taken from a simple ENSO model. PMID:23840577
Amézquita, A; Weller, C L; Wang, L; Thippareddi, H; Burson, D E
2005-05-25
Numerous small meat processors in the United States have difficulties complying with the stabilization performance standards for preventing growth of Clostridium perfringens by 1 log10 cycle during cooling of ready-to-eat (RTE) products. These standards were established by the Food Safety and Inspection Service (FSIS) of the US Department of Agriculture in 1999. In recent years, several attempts have been made to develop predictive models for growth of C. perfringens within the range of cooling temperatures included in the FSIS standards. Those studies mainly focused on microbiological aspects, using hypothesized cooling rates. Conversely, studies dealing with heat transfer models to predict cooling rates in meat products do not address microbial growth. Integration of heat transfer relationships with C. perfringens growth relationships during cooling of meat products has been very limited. Therefore, a computer simulation scheme was developed to analyze heat transfer phenomena and temperature-dependent C. perfringens growth during cooling of cooked boneless cured ham. The temperature history of ham was predicted using a finite element heat diffusion model. Validation of heat transfer predictions used experimental data collected in commercial meat-processing facilities. For C. perfringens growth, a dynamic model was developed using Baranyi's nonautonomous differential equation. The bacterium's growth model was integrated into the computer program using predicted temperature histories as input values. For cooling cooked hams from 66.6 degrees C to 4.4 degrees C using forced air, the maximum deviation between predicted and experimental core temperature data was 2.54 degrees C. Predicted C. perfringens growth curves obtained from dynamic modeling showed good agreement with validated results for three different cooling scenarios. Mean absolute values of relative errors were below 6%, and deviations between predicted and experimental cell counts were within 0.37 log10
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.
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.;
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.
2011-03-01
technology is the Smart Grid. Smart Grids can be defined as “the integration of communications networks with the power grid in order to create an...Figure 11 depicts the ever-increasing locations of Advanced Metering Readings (AMRs), AMIs and Smart Grids . 25 Fi gu re 1 1. N at io na l
Dynamic causal modelling revisited.
Friston, K J; Preller, Katrin H; Mathys, Chris; Cagnan, Hayriye; Heinzle, Jakob; Razi, Adeel; Zeidman, Peter
2017-02-17
This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers. Our focus here is on how to answer long-standing questions in fMRI; for example, do haemodynamic responses reflect extrinsic (afferent) input from distant cortical regions, or do they reflect intrinsic (recurrent) neuronal activity? To what extent do inhibitory interneurons contribute to neurovascular coupling? What is the relationship between haemodynamic responses and the frequency of induced neuronal activity? This paper does not pretend to answer these questions; rather it shows how they can be addressed using neural mass models of fMRI timeseries.
Dynamical Modelling of Meteoroid Streams
NASA Astrophysics Data System (ADS)
Clark, David; Wiegert, P. A.
2012-10-01
Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required questionable assumptions and significant simplifications. Extending on the approach of Vaubaillon et al. (2005)1, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of frequency based on model parameter changes. To assist in model analysis we are developing interactive software to permit the “turning of knobs” of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. With this tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform cometary surface attributes and temporal activity. The software uses a single model definition and implementation throughout model verification, sample particle bin generation and integration, and analysis. It supports the adjustment with feedback of both independent and independent model values, with the intent of providing an interface supporting multivariate analysis. Propagations of measurement uncertainties and model parameter precisions are tracked rigorously throughout. We maintain a separation of the model itself from the abstract concepts of model definition, parameter manipulation, and real-time analysis and visualization. Therefore we are able to quickly adapt to fundamental model changes. It is hoped the tool will also be of use in other solar system dynamics problems. 1 Vaubaillon, J.; Colas, F.; Jorda, L. (2005) A new method to predict meteor showers. I. Description of the model. Astronomy and
NASA Astrophysics Data System (ADS)
Jarosław, J.; Szporak, S.; Verbeiren, B.; Batelaan, O.
2012-04-01
The effective protection of wetlands demands knowledge of hydrological processes, which can be appropriately analysed using distributed models. It is eminent that the calibration and verification of distributed models of catchments with significant wetland coverage have to focus on wetland-specific issues such as the hydrological response of natural vegetation, i.e. parameterisation and dynamics of vegetation. An important and useful parameter describing vegetation canopy structure in terrestrial ecosystems is the Leaf Area Index (LAI), which is closely related to photosynthesis, net primary productivity, evapotranspiration and interception storage capacity. LAI can be estimated with remote sensing data, its suitability to derive the actual state of vegetation is high. This study focuses on improving the interception capacity calculation in the distributed hydrological model WetSpa. The main objective is to integrate seasonal LAI data. Not only field measurements, but also remote sensing derived LAI data is integrated into a WetSpa model for the Upper Biebrza catchment (northeast Poland). Biebrza National Park is characterized by a significant coverage of wetland and large variation in vegetation types. The use of remote sensing derived LAI values considerably improves the assessment of the actual status of vegetation and its seasonal dynamics. Landsat Thematic Mapper images are used to represent the different vegetation stages during the growing season (near LAI minimum and LAI maximum). They are analysed and processed to estimate the interception storage capacity of plant communities typical for Biebrza River valley. LAI of different plant communities has been measured using LAI-2000, and empirical relationships between these measurements and several spectral vegetation indices were established using linear and non-linear regression analysis. The vegetation indices with the highest correlation and the strongest linear relationship regarding LAI are NDVI (R2 = 0
NASA Astrophysics Data System (ADS)
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)
Malafeyev, O. A.; Nemnyugin, S. A.; Rylow, D.; Kolpak, E. P.; Awasthi, Achal
2017-07-01
The corruption dynamics is analyzed by means of the lattice model which is similar to the three-dimensional Ising model. Agents placed at nodes of the corrupt network periodically choose to perfom or not to perform the act of corruption at gain or loss while making decisions based on the process history. The gain value and its dynamics are defined by means of the Markov stochastic process modelling with parameters established in accordance with the influence of external and individual factors on the agent's gain. The model is formulated algorithmically and is studied by means of the computer simulation. Numerical results are obtained which demonstrate asymptotic behaviour of the corruption network under various conditions.
Dynamical modelling of meteoroid streams
NASA Astrophysics Data System (ADS)
Clark, D. L.; Wiegert, P. A.
2014-07-01
Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required significant assumptions and simplifications. Extending on the approach of Vaubaillon et al. 2005, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of weights based on model parameter changes. To assist in model analysis we are developing interactive software to permit the "turning of knobs" of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. Using the tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform and time-variant cometary surface attributes and processes.
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.
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.
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.
Hirt, Bartholomäus V; Wattis, Jonathan A D; Preston, Simon P; Laughton, Charles A
2012-02-21
The pentacyclic acridinium salt RHPS4 displays anti-tumour properties in vitro as well as in vivo and is potentially cell-cycle specific. We have collected experimental data and formulated a compartmental model using ordinary differential equations to investigate how the compound affects cells in each stage of the cell cycle. In addition to a control case in which no drug was used, we treated colorectal cancer cells with three different concentrations of the drug and fitted simulations from our models to experimental observations. We found that RHPS4 caused a concentration-dependent, marked cell death in treated cells, which is best modelled by allowing the rate parameters corresponding to cell death to be sigmoidal functions of time. We have shown that the model is "identifiable", meaning that, at least in principle, the parameter values can be determined from observable quantities. We find that at low concentrations RHPS4 primarily affects the cells in the G(2)/M phase, and that the drug has a delayed effect with the delay decreasing at larger doses. Since the drug diffuses into the nucleus, the observed delayed effect of the compound is unexpected and is a novel finding of our research into this compound. Copyright © 2011 Elsevier Ltd. All rights reserved.
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.
Bead-Fourier path integral molecular dynamics.
Ivanov, Sergei D; Lyubartsev, Alexander P; Laaksonen, Aatto
2003-06-01
Molecular dynamics formulation of Bead-Fourier path integral method for simulation of quantum systems at finite temperatures is presented. Within this scheme, both the bead coordinates and Fourier coefficients, defining the path representing the quantum particle, are treated as generalized coordinates with corresponding generalized momenta and masses. Introduction of the Fourier harmonics together with the center-of-mass thermostating scheme is shown to remove the ergodicity problem, known to pose serious difficulties in standard path integral molecular dynamics simulations. The method is tested for quantum harmonic oscillator and hydrogen atom (Coulombic potential). The simulation results are compared with the exact analytical solutions available for both these systems. Convergence of the results with respect to the number of beads and Fourier harmonics is analyzed. It was shown that addition of a few Fourier harmonics already improves the simulation results substantially, even for a relatively small number of beads. The proposed Bead-Fourier path integral molecular dynamics is a reliable and efficient alternative to simulations of quantum systems.
Bead-Fourier path integral molecular dynamics
NASA Astrophysics Data System (ADS)
Ivanov, Sergei D.; Lyubartsev, Alexander P.; Laaksonen, Aatto
2003-06-01
Molecular dynamics formulation of Bead-Fourier path integral method for simulation of quantum systems at finite temperatures is presented. Within this scheme, both the bead coordinates and Fourier coefficients, defining the path representing the quantum particle, are treated as generalized coordinates with corresponding generalized momenta and masses. Introduction of the Fourier harmonics together with the center-of-mass thermostating scheme is shown to remove the ergodicity problem, known to pose serious difficulties in standard path integral molecular dynamics simulations. The method is tested for quantum harmonic oscillator and hydrogen atom (Coulombic potential). The simulation results are compared with the exact analytical solutions available for both these systems. Convergence of the results with respect to the number of beads and Fourier harmonics is analyzed. It was shown that addition of a few Fourier harmonics already improves the simulation results substantially, even for a relatively small number of beads. The proposed Bead-Fourier path integral molecular dynamics is a reliable and efficient alternative to simulations of quantum systems.
2010-05-01
Alternative diversity, difficulties in selecting metrics and measuring performance, and other factors make the Analysis of Alternatives (AoA) difficult...particularly difficult because of the intangible nature of many important benefits. The current work addresses the need to improve the use of benefits in AoA...research focuses on the use of KVA and “Real Options” models in identifying, valuing, maintaining, and exercising options in military decision -making
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
Implicit integration methods for dislocation dynamics
Gardner, D. J.; Woodward, C. S.; Reynolds, D. R.; ...
2015-01-20
In dislocation dynamics simulations, strain hardening simulations require integrating stiff systems of ordinary differential equations in time with expensive force calculations, discontinuous topological events, and rapidly changing problem size. Current solvers in use often result in small time steps and long simulation times. Faster solvers may help dislocation dynamics simulations accumulate plastic strains at strain rates comparable to experimental observations. Here, this paper investigates the viability of high order implicit time integrators and robust nonlinear solvers to reduce simulation run times while maintaining the accuracy of the computed solution. In particular, implicit Runge-Kutta time integrators are explored as a waymore » of providing greater accuracy over a larger time step than is typically done with the standard second-order trapezoidal method. In addition, both accelerated fixed point and Newton's method are investigated to provide fast and effective solves for the nonlinear systems that must be resolved within each time step. Results show that integrators of third order are the most effective, while accelerated fixed point and Newton's method both improve solver performance over the standard fixed point method used for the solution of the nonlinear systems.« less
Implicit integration methods for dislocation dynamics
Gardner, D. J.; Woodward, C. S.; Reynolds, D. R.; Hommes, G.; Aubry, S.; Arsenlis, A.
2015-01-20
In dislocation dynamics simulations, strain hardening simulations require integrating stiff systems of ordinary differential equations in time with expensive force calculations, discontinuous topological events, and rapidly changing problem size. Current solvers in use often result in small time steps and long simulation times. Faster solvers may help dislocation dynamics simulations accumulate plastic strains at strain rates comparable to experimental observations. Here, this paper investigates the viability of high order implicit time integrators and robust nonlinear solvers to reduce simulation run times while maintaining the accuracy of the computed solution. In particular, implicit Runge-Kutta time integrators are explored as a way of providing greater accuracy over a larger time step than is typically done with the standard second-order trapezoidal method. In addition, both accelerated fixed point and Newton's method are investigated to provide fast and effective solves for the nonlinear systems that must be resolved within each time step. Results show that integrators of third order are the most effective, while accelerated fixed point and Newton's method both improve solver performance over the standard fixed point method used for the solution of the nonlinear systems.
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.
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.
Branes and integrable lattice models
NASA Astrophysics Data System (ADS)
Yagi, Junya
2017-01-01
This is a brief review of my work on the correspondence between four-dimensional 𝒩 = 1 supersymmetric field theories realized by brane tilings and two-dimensional integrable lattice models. I explain how to construct integrable lattice models from extended operators in partially topological quantum field theories, and elucidate the correspondence as an application of this construction.
Effect of dynamical interactions on integrated properties of globular clusters
NASA Astrophysics Data System (ADS)
Zhuang, Yulong; Zhang, Fenghui; Anders, Peter; Ruan, Zhifeng; Cheng, Liantao; Kang, Xiaoyu
2015-02-01
Globular clusters (GCs) are generally treated as natural validators of simple stellar population (SSP) models. However, there are still some differences between real GCs and SSPs. In this work, we use a direct N-body simulation code NBODY6 to study the influences of dynamical interactions, metallicity and primordial binaries on Milky Way GCs' integrated properties. Our models start with N = 100 000 stars, covering a metallicity range Z = 0.0001 ˜ 0.02, a subset of our models contain primordial binaries, resulting in a binary fraction as currently observed at a model age of GCs. Stellar evolution and external tidal field representative for an average Milky Way GC are taken into consideration. The integrated colours and Lick indices are calculated using BaSeL and Bluered stellar spectral libraries separately. By including dynamical interactions, our model clusters show integrated features (i.e. colours up to 0.01 mag bluer, Hβ up to 0.1 Å greater and [MgFe]' 0.05 Å smaller) making the clusters appear slightly younger than the model clusters without dynamical interactions. This effect is caused mainly by the preferential loss of low-mass stars which have a stronger contribution to redder passbands as well as different spectral features compared to higher mass stars. In addition, this effect is larger at lower metallicities. On the contrary, the incorporation of primordial binaries reduces this effect.
NASA Astrophysics Data System (ADS)
Garcon, V.; Paulmier, A.; Bretagnon, M.; Campos, F.; Dewitte, B.; Illig, S.; Maes, C.; Depretz de Gesincourt, O.; Scouarnec, L.; Grelet, J.; Coppola, L.; Oschlies, A.; Leblond, N.; Quispe, J.; Carrasco, E.
2015-12-01
In the current context of the ocean deoxygenation, OMZs are known to play a key-role on the evolution of climate (greenhouse gases) and on the ecosystems and fisheries (nitrogen loss, respiratory barrier, sulfidic events) at both local and global scales. One of the objectives of the AMOP (Activities of research dedicated to the Minimum of Oxygen in the eastern Pacific) project is to document the mechanisms associated with the OMZ variability from hourly to decadal timescales. The hypothesis is that the variability scale ranges are different at the oxycline compared to the OMZ core, and directly impact the OMZ recycling behavior acting as either a preservation or remineralization layer. Results from a mooring deployment off Callao put in evidence three main time scales of OMZ variability- intra daily, intra monthly and intra seasonally. A coupled model ROM-BioEBUS configuration of the Peruvian OMZ shows there is a marked longitudinal variability in the characteristics of the oxygen spectrum, indicative of a strong influence of mesoscale activity in shaping the OMZ structure offshore. Mooring data highlight oxygenation events occurring near the oxycline rather than within the core, and inducing a shift of the OMZ regime from organic matter preservation towards remineralisation.
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
Seeing the System: Dynamics and Complexity of Technology Integration in Secondary Schools
ERIC Educational Resources Information Center
Howard, Sarah K.; Thompson, Kate
2016-01-01
This paper introduces system dynamics modeling to understand, visualize and explore technology integration in schools, through the development of a theoretical model of technology-related change in teachers' practice. Technology integration is a dynamic social practice, within the social system of education. It is difficult, if not nearly…
Seeing the System: Dynamics and Complexity of Technology Integration in Secondary Schools
ERIC Educational Resources Information Center
Howard, Sarah K.; Thompson, Kate
2016-01-01
This paper introduces system dynamics modeling to understand, visualize and explore technology integration in schools, through the development of a theoretical model of technology-related change in teachers' practice. Technology integration is a dynamic social practice, within the social system of education. It is difficult, if not nearly…
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.
Integrable topological billiards and equivalent dynamical systems
NASA Astrophysics Data System (ADS)
Vedyushkina, V. V.; Fomenko, A. T.
2017-08-01
We consider several topological integrable billiards and prove that they are Liouville equivalent to many systems of rigid body dynamics. The proof uses the Fomenko-Zieschang theory of invariants of integrable systems. We study billiards bounded by arcs of confocal quadrics and their generalizations, generalized billiards, where the motion occurs on a locally planar surface obtained by gluing several planar domains isometrically along their boundaries, which are arcs of confocal quadrics. We describe two new classes of integrable billiards bounded by arcs of confocal quadrics, namely, non-compact billiards and generalized billiards obtained by gluing planar billiards along non-convex parts of their boundaries. We completely classify non-compact billiards bounded by arcs of confocal quadrics and study their topology using the Fomenko invariants that describe the bifurcations of singular leaves of the additional integral. We study the topology of isoenergy surfaces for some non-convex generalized billiards. It turns out that they possess exotic Liouville foliations: the integral trajectories of the billiard that lie on some singular leaves admit no continuous extension. Such billiards appear to be leafwise equivalent to billiards bounded by arcs of confocal quadrics in the Minkowski metric.
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.
Kan, Zigui; Zhu, Qiang; Yang, Lijiang; Huang, Zhixiong; Jin, Biaobing; Ma, Jing
2017-05-04
Conformation of cellulose with various degree of polymerization of n = 1-12 in ionic liquid 1,3-dimethylimidazolium chloride ([C1mim]Cl) and the intermolecular interaction between them was studied by means of molecular dynamics (MD) simulations with fixed-charge and charge variable polarizable force fields, respectively. The integrated tempering enhanced sampling method was also employed in the simulations in order to improve the sampling efficiency. Cellulose undergoes significant conformational changes from a gaseous right-hand helical twist along the long axis to a flexible conformation in ionic liquid. The intermolecular interactions between cellulose and ionic liquid were studied by both infrared spectrum measurements and theoretical simulations. Designated by their puckering parameters, the pyranose rings of cellulose oligomers are mainly arranged in a chair conformation. With the increase in the degree of polymerization of cellulose, the boat and skew-boat conformations of cellulose appear in the MD simulations, especially in the simulations with polarization model. The number and population of hydrogen bonds between the cellulose and the chloride anions show that chloride anion is prone to form HBs whenever it approaches the hydroxyl groups of cellulose and, thus, each hydroxyl group is fully hydrogen bonded to the chloride anion. MD simulations with polarization model presented more abundant conformations than that with nonpolarization model. The application of the enhanced sampling method further enlarged the conformational spaces that could be visited by facilitating the system escaping from the local minima. It was found that the electrostatics interactions between the cellulose and ionic liquid contribute more to the total interaction energies than the van der Waals interactions. Although the interaction energy between the cellulose and anion is about 2.9 times that between the cellulose and cation, the role of cation is non-negligible. In contrast
Ibáñez, J; Lavado Contador, J F; Schnabel, S; Martínez Valderrama, J
2016-02-15
An integrated dynamic model was used to evaluate the influence of climatic, soil, pastoral, economic and managerial factors on sheet erosion in rangelands of SW Spain (dehesas). This was achieved by means of a variance-based sensitivity analysis. Topsoil erodibility, climate change and a combined factor related to soil water storage capacity and the pasture production function were the factors which influenced water erosion the most. Of them, climate change is the main source of uncertainty, though in this study it caused a reduction in the mean and the variance of long-term erosion rates. The economic and managerial factors showed scant influence on soil erosion, meaning that it is unlikely to find such influence in the study area for the time being. This is because the low profitability of the livestock business maintains stocking rates at low levels. However, the potential impact of livestock, through which economic and managerial factors affect soil erosion, proved to be greater in absolute value than the impact of climate change. Therefore, if changes in some economic or managerial factors led to higher stocking rates in the future, significant increases in erosion rates would be expected.
Integrated Computational Model Development
2014-03-01
specific material properties. 15. SUBJECT TERMS alloy design, microstructure, mechanical properties, fatigue behavior, crack growth behavior...microstructure, processing, constitution, or alloy might not be correct. A critical piece of ICME is the “integration.” For years materials laboratories...experimental techniques. These four areas are explained in more detail below. Alloy Selection Processing Microstructure Lifing Properties Life Prediction Risk
Integrated Models in Education.
ERIC Educational Resources Information Center
Butler-Por, Nava
1979-01-01
Examines educational change in Israeli junior high schools which was intended to integrate ethnic, social, and ability groups into a single national entity. Topics discussed include peer tutoring, busing, tutorial work given by gifted students to slow learners, and student motivation. Journal availability: see SO 507 297. (DB)
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
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.
Sparse model selection via integral terms
NASA Astrophysics Data System (ADS)
Schaeffer, Hayden; McCalla, Scott G.
2017-08-01
Model selection and parameter estimation are important for the effective integration of experimental data, scientific theory, and precise simulations. In this work, we develop a learning approach for the selection and identification of a dynamical system directly from noisy data. The learning is performed by extracting a small subset of important features from an overdetermined set of possible features using a nonconvex sparse regression model. The sparse regression model is constructed to fit the noisy data to the trajectory of the dynamical system while using the smallest number of active terms. Computational experiments detail the model's stability, robustness to noise, and recovery accuracy. Examples include nonlinear equations, population dynamics, chaotic systems, and fast-slow systems.
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.
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.
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.
Mathematical Modeling of Wildfire Dynamics
NASA Astrophysics Data System (ADS)
Del Bene, Kevin; Drew, Donald
2012-11-01
Wildfires have been a long-standing problem in today's society. In this paper, we derive and solve a fluid dynamics model to study a specific type of wildfire, namely, a two dimensional flow around a rising plume above a concentrated heat source, modeling a fire line. This flow assumes a narrow plume of hot gas rising and entraining the surrounding air. The surrounding air is assumed to have constant density and is irrotational far from the fire line. The flow outside the plume is described by a Biot-Savart integral with jump conditions across the position of the plume. The plume model describes the unsteady evolution of the mass, momentum, energy, and vorticity inside the plume, with sources derived to model mixing in the style of Morton, et al. 1956]. The fire is then modeled using a conservation derivation, allowing the fire to propagate, coupling back to the plume model. The results show that this model is capable of capturing the complex interaction of the plume with the surrounding air and fuel layer. Funded by NSF GRFP.
Integrating systems biology models and biomedical ontologies
2011-01-01
Background Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. Results We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. Conclusions We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms. PMID:21835028
Neurobiology of dynamic psychotherapy: an integration possible?
Mundo, Emanuela
2006-01-01
In the last decades, Kandel's innovative experiments have demonstrated that brain structures and synaptic connections are dynamic. Synapses can be modified by a wide variety of environmental factors, including learning and memory processes. The hypothesis that dynamic psychotherapy process involves memory and learning processes has opened the possibility of a dialogue between neuroscience and psychoanalysis and related psychotherapy techniques. The primary aim of the present article is to critically review the more recent data on neurobiological effects of dynamic psychotherapy in psychiatric disorders. Relevant literature has been selected using the databases currently available online (i.e., PubMed). The literature search has been limited to the past 10 years and to genetic, molecular biology, and neuroimaging studies that have addressed the issue of changes induced by psychotherapy. Most of the genetic studies on mental disorders have demonstrated that psychiatric conditions result from a complex interaction of genetic susceptibility and environmental effects. For none of the many psychiatric conditions investigated has a purely genetic background been found. Molecular biology studies have indicated that gene expression is influenced by several environmental factors, including early experiences, traumas, learning, and memory processes. Neuroimaging studies (using fMRI and PET) have found that not only cognitive but also dynamic psychotherapy has measurable effects on the brain. In addition, psychotherapy may modify brain function and metabolism in specific brain areas. Most of these studies have considered patients with major depressive disorders and compared the effects of psychotherapy with the effect of standard pharmacotherapy. In conclusion, recent results from neuroscience studies have suggested that dynamic psychotherapy has a significant impact on brain function and metabolism in specific brain areas. The possible applications and developments of this
Integrable discrete PT symmetric model.
Ablowitz, Mark J; Musslimani, Ziad H
2014-09-01
An exactly solvable discrete PT invariant nonlinear Schrödinger-like model is introduced. It is an integrable Hamiltonian system that exhibits a nontrivial nonlinear PT symmetry. A discrete one-soliton solution is constructed using a left-right Riemann-Hilbert formulation. It is shown that this pure soliton exhibits unique features such as power oscillations and singularity formation. The proposed model can be viewed as a discretization of a recently obtained integrable nonlocal nonlinear Schrödinger equation.
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.
Kalantari, A S; Cabrera, V E
2012-10-01
The objective of this study was to determine the effect of reproductive performance on dairy cattle herd value. Herd value was defined as the herd's average retention payoff (RPO). Individual cow RPO is the expected profit from keeping the cow compared with immediate replacement. First, a daily dynamic programming model was developed to calculate the RPO of all cow states in a herd. Second, a daily Markov chain model was applied to estimate the herd demographics. Finally, the herd value was calculated by aggregating the RPO of all cows in the herd. Cow states were described by 5 milk yield classes (76, 88, 100, 112, and 124% with respect to the average), 9 lactations, 750 d in milk, and 282 d in pregnancy. Five different reproductive programs were studied (RP1 to RP5). Reproductive program 1 used 100% timed artificial insemination (TAI; 42% conception rate for first TAI and 30% for second and later services) and the other programs combined TAI with estrus detection. The proportion of cows receiving artificial insemination after estrus detection ranged from 30 to 80%, and conception rate ranged from 25 to 35%. These 5 reproductive programs were categorized according to their 21-d pregnancy rate (21-d PR), which is an indication of the rate that eligible cows become pregnant every 21 d. The 21-d PR was 17% for RP1, 14% for RP2, 16% for RP3, 18% for RP4, and 20% for RP5. Results showed a positive relationship between 21-d PR and herd value. The most extreme herd value difference between 2 reproductive programs was $77/cow per yr for average milk yield (RP5 - RP2), $13/cow per yr for lowest milk yield (RP5 - RP1), and $160/cow per yr for highest milk yield (RP5 - RP2). Reproductive programs were ranked based on their calculated herd value. With the exception of the best reproductive program (RP5), all other programs showed some level of ranking change according to milk yield. The most dramatic ranking change was observed in RP1, which moved from being the worst ranked
Adaptive geometric numerical integration for point vortex dynamics.
San Miguel, A
2006-10-01
In this paper we describe a variable stepsize integration method for the Hamiltonian dynamics of point vortices based on the explicit symplectic Zhang and Qin scheme. The adapted method is also explicit and preserves the reversible structure of the flow. In order to check the behavior of this adaptive method a numerical study of the exchange-scattering phenomenon in the three-vortex problem is made. The symmetry of the orbit and the energy evolution are discussed for the exchange-scattering model. A long-term integration of this and other models composed also of three vortices indicates that the adaptive Zhang-Qin method has good properties of efficiency and preservation of the first integrals associated with point vortex systems.
Impact of dynamic loads on propulsion integration
NASA Astrophysics Data System (ADS)
Seiner, J. M.
1994-09-01
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.
1986-11-01
Structured Modeling, Ph.D. Thesis, Graduate School of Management , UCLA. Federgruen, A. and P. Zipkin >. "A Combined Vehicle Routing and Inventory ...C-O 570 i1 ’. 33 %xESTEN MANAGEMENT SCIENCE INSTITUTE Lnvcrsitv of California. Los Angles WESTERN MANAGEMENT SCIENCE INSTITUTE University of...Chuan Tsai. This work was supported by the National Science Foundation , the Office of Naval Research, and the Naval Personnel R&D Center. The views
Multistage integration model for human egomotion perception.
Zacharias, G L; Miao, A X; Warren, R
1995-01-01
Human computational vision models that attempt to account for the dynamic perception of egomotion and relative depth typically assume a common three-stage process: first, compute the optical flow field based on the dynamically changing image; second, estimate the egomotion states based on the flow; and third, estimate the relative depth/shape based on the egomotion states and possibly on a model of the viewed surface. We propose a model more in line with recent work in human vision, employing multistage integration. Here the dynamic image is first processed to generate spatial and temporal image gradients that drive a mutually interconnected state estimator and depth/shape estimator. The state estimator uses the image gradient information in combination with a depth/shape estimate of the viewed surface and an assumed model of the viewer's dynamics to generate current state estimates; in tandem, the depth/shape estimator uses the image gradient information in combination with the viewer's state estimate and assumed shape model to generate current depth/shape estimates. In this paper, we describe the model and compare model predictions with empirical data.
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
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.
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 Models and Observations
NASA Technical Reports Server (NTRS)
Womebarger, Amy
2011-01-01
For the past ten years, the coronal loops community has held bi-annual workshops to discuss the analysis of coronal loop observations and the latest efforts to model the loop structures. During this time, several heating scenarios have been proposed to explain loop observations. These heating scenarios rely on different heating frequencies, locations, and durations, as well as different loop sub-structure. Often the scenarios are developed to explain an observation, hence all heating scenarios match some observational criteria. The key to discriminating between the competing heating scenarios is to first identify the distinguishing observables. For instance, both effectively steady and nanoflare-heating scenarios can produce quasi-steady intensities. Observing quasi-steady intensities, then, does not help determine which heating scenario is most likely. These heating scenarios may, however, predict different velocities or different emission measure distributions. In this talk, I will discuss a few of the expected observations for some simple heating scenarios. I will ask the modeling community to calculate similar observations for the different heating scenarios to generate a standard list of expected observations. After the community develops this list, comparisons with actual loop observations can then distinguish the most likely heating scenario.
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.
Integrating plant carbon dynamics with mutualism ecology.
Pringle, Elizabeth G
2016-04-01
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.
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.
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
Spatial gradients and multidimensional dynamics in a neural integrator circuit
Miri, Andrew; Daie, Kayvon; Arrenberg, Aristides B.; Baier, Herwig; Aksay, Emre; Tank, David W.
2011-01-01
In a neural integrator, the variability and topographical organization of neuronal firing rate persistence can provide information about the circuit’s functional architecture. Here we use optical recording to measure the time constant of decay of persistent firing (“persistence time”) across a population of neurons comprising the larval zebrafish oculomotor velocity-to-position neural integrator. We find extensive persistence time variation (10-fold; coefficients of variation 0.58–1.20) across cells within individual larvae. We also find that the similarity in firing between two neurons decreased as the distance between them increased and that a gradient in persistence time was mapped along the rostrocaudal and dorsoventral axes. This topography is consistent with the emergence of persistence time heterogeneity from a circuit architecture in which nearby neurons are more strongly interconnected than distant ones. Collectively, our results can be accounted for by integrator circuit models characterized by multiple dimensions of slow firing rate dynamics. PMID:21857656
Papaleo, Elena
2015-01-01
In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations. PMID:26075210
Papaleo, Elena
2015-01-01
In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.
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.
Dispersive models describing mosquitoes’ population dynamics
NASA Astrophysics Data System (ADS)
Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.
2016-08-01
The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.
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
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.
NASA Astrophysics Data System (ADS)
Marchenko, S. S.; Genet, H.; Euskirchen, E. S.; Breen, A. L.; McGuire, A. D.; Rupp, S. T.; Romanovsky, V. E.; Bolton, W. R.; Walsh, J. E.
2016-12-01
The impact of climate warming on permafrost and the potential of climate feedbacks resulting from permafrost thawing have recently received a great deal of attention. Permafrost temperature has increased in most locations in the Arctic and Sub-Arctic during the past 30-40 years. The typical increase in permafrost temperature is 1-3°C. The process-based permafrost dynamics model GIPL developed in the Geophysical Institute Permafrost Lab, and which is the permafrost module of the Integrated Ecosystem Model (IEM) has been using to quantify the nature and rate of permafrost degradation and its impact on ecosystems, infrastructure, CO2 and CH4fluxes and net C storage following permafrost thaw across Alaska and Northwest Canada. The IEM project is a multi-institutional and multi-disciplinary effort aimed at understanding potential landscape, habitat and ecosystem change across the IEM domain. The IEM project also aims to tie three scientific models together Terrestrial Ecosystem Model (TEM), the ALFRESCO (ALaska FRame-based EcoSystem Code) and GIPL so that they exchange data at run-time. The models produce forecasts of future fire, vegetation, organic matter, permafrost and hydrology regimes. The climate forcing data are based on the historical CRU3.1 data set for the retrospective analysis period (1901-2009) and the CMIP3 CCCMA-CGCM3.1 and MPI-ECHAM5/MPI-OM climate models for the future period (2009-2100). All data sets were downscaled to a 1 km resolution, using a differencing methodology (i.e., a delta method) and the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climatology. We estimated the dynamics of permafrost temperature, active layer thickness, area occupied by permafrost, and volume of thawed soils across the IEM domain. The modeling results indicate how different types of ecosystems affect the thermal state of permafrost and its stability. Although the rate of soil warming and permafrost degradation in peatland areas are slower than
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
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.
System Dynamics (SD) models are useful for holistic integration of data to evaluate indirect and cumulative effects and inform decisions. Complex SD models can provide key insights into how decisions affect the three interconnected pillars of sustainability. However, the complexi...
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.
Distributed Energy Resources and Dynamic Microgrid: An Integrated Assessment
NASA Astrophysics Data System (ADS)
Shang, Duo Rick
The overall goal of this thesis is to improve understanding in terms of the benefit of DERs to both utility and to electricity end-users when integrated in power distribution system. To achieve this goal, a series of two studies was conducted to assess the value of DERs when integrated with new power paradigms. First, the arbitrage value of DERs was examined in markets with time-variant electricity pricing rates (e.g., time of use, real time pricing) under a smart grid distribution paradigm. This study uses a stochastic optimization model to estimate the potential profit from electricity price arbitrage over a five-year period. The optimization process involves two types of PHEVs (PHEV-10, and PHEV-40) under three scenarios with different assumptions on technology performance, electricity market and PHEV owner types. The simulation results indicate that expected arbitrage profit is not a viable option to engage PHEVs in dispatching and in providing ancillary services without more favorable policy and PHEV battery technologies. Subsidy or change in electricity tariff or both are needed. Second, it examined the concept of dynamic microgrid as a measure to improve distribution resilience, and estimates the prices of this emerging service. An economic load dispatch (ELD) model is developed to estimate the market-clearing price in a hypothetical community with single bid auction electricity market. The results show that the electricity market clearing price on the dynamic microgrid is predominantly decided by power output and cost of electricity of each type of DGs. At circumstances where CHP is the only source, the electricity market clearing price in the island is even cheaper than the on-grid electricity price at normal times. Integration of PHEVs in the dynamic microgrid will increase electricity market clearing prices. It demonstrates that dynamic microgrid is an economically viable alternative to enhance grid resilience.
NASA Astrophysics Data System (ADS)
Hank, Tobias B.; Bach, Heike; Danner, Martin; Hodrius, Martina; Mauser, Wolfram
2016-08-01
Nitrogen, being the basic element for the construction of plant proteins and pigments, is one of the most important production factors for agricultural cultivation. High resolution and near real-time information on nitrogen status in the soil thus is of highest interest for economically and ecologically optimized fertilizer planning and application. Unfortunately, nitrogen storage in the soil column cannot be directly observed with Earth Observation (EO) instruments. Advanced EO supported process modelling approaches therefore must be applied that allow tracing the spatiotemporal dynamics of nitrogen transformation, translocation and transport in the soil and in the canopy. Before these models can be applied as decision support tools for smart farming, they must be carefully parameterized and validated. This study applies an advanced land surface process model (PROMET) to selected winter cereal fields in Southern Germany and correlates the model outputs to destructively sampled nitrogen data from the growing season of 2015 (17 sampling dates, 8 sample locations). The spatial parametrization of the process model thereby is supported by assimilating eight satellite images (5 times Landsat 8 OLI and 3 times RapidEye). It was found that the model is capable of realistically tracing the temporal and spatial dynamics of aboveground nitrogen uptake and allocation (R2 = 0.84, RMSE 31.3 kg ha-1).
Nonlinear integral equations for the sausage model
NASA Astrophysics Data System (ADS)
Ahn, Changrim; Balog, Janos; Ravanini, Francesco
2017-08-01
The sausage model, first proposed by Fateev, Onofri, and Zamolodchikov, is a deformation of the O(3) sigma model preserving integrability. The target space is deformed from the sphere to ‘sausage’ shape by a deformation parameter ν. This model is defined by a factorizable S-matrix which is obtained by deforming that of the O(3) sigma model by a parameter λ. Clues for the deformed sigma model are provided by various UV and IR information through the thermodynamic Bethe ansatz (TBA) analysis based on the S-matrix. Application of TBA to the sausage model is, however, limited to the case of 1/λ integer where the coupled integral equations can be truncated to a finite number. In this paper, we propose a finite set of nonlinear integral equations (NLIEs), which are applicable to generic value of λ. Our derivation is based on T-Q relations extracted from the truncated TBA equations. For a consistency check, we compute next-leading order corrections of the vacuum energy and extract the S-matrix information in the IR limit. We also solved the NLIE both analytically and numerically in the UV limit to get the effective central charge and compared with that of the zero-mode dynamics to obtain exact relation between ν and λ. Dedicated to the memory of Petr Petrovich Kulish.
NASA Astrophysics Data System (ADS)
Hellstrom, R. A.; Fernandez, A.; Mark, B. G.; Covert, J. M.
2016-12-01
Peru is facing imminent water resource issues as glaciers retreat and demand increases, yet limited observations and model resolution hamper understanding of hydrometerological processes on local to regional scales. Much of current global and regional climate studies neglect the meteorological forcing of lapse rates (LRs) and valley and slope wind dynamics on critical components of the Peruvian Andes' water-cycle, and herein we emphasize the wet season. In 2004 and 2005 we installed an autonomous sensor network (ASN) within the glacierized Llanganuco Valley, Cordillera Blanca (9°S), consisting of discrete, cost-effective, automatic temperature loggers located along the valley axis and anchored by two automatic weather stations. Comparisons of these embedded hydrometeorological measurements from the ASN and climate modeling by dynamical downscaling using the Weather Research and Forecasting model (WRF) elucidate distinct diurnal and seasonal characteristics of the mountain wind regime and LRs. Wind, temperature, humidity, and cloud simulations suggest that thermally driven up-valley and slope winds converging with easterly flow aloft enhance late afternoon and evening cloud development which helps explain nocturnal wet season precipitation maxima measured by the ASN. Furthermore, the extreme diurnal variability of along-valley-axis LR, and valley wind detected from ground observations and confirmed by dynamical downscaling demonstrate the importance of realistic scale parameterizations of the atmospheric boundary layer to improve regional climate model projections in mountainous regions. We are currently considering to use intermediate climate models such as ICAR to reduce computing cost and we continue to maintain the ASN in the Cordillera Blanca.
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
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.
A New Dynamical Reflection Algebra and Related Quantum Integrable Systems
NASA Astrophysics Data System (ADS)
Avan, Jean; Ragoucy, Eric
2012-07-01
We propose a new dynamical reflection algebra, distinct from the previous dynamical boundary algebra and semi-dynamical reflection algebra. The associated Yang-Baxter equations, coactions, fusions, and commuting traces are derived. Explicit examples are given and quantum integrable Hamiltonians are constructed. They exhibit features similar to the Ruijsenaars-Schneider Hamiltonians.
A LAGRANGIAN INTEGRATOR FOR PLANETARY ACCRETION AND DYNAMICS (LIPAD)
Levison, Harold F.; Duncan, Martin J.; Thommes, Edward
2012-10-01
We present the first particle-based Lagrangian code that can follow the collisional/accretional/dynamical evolution of a large number of kilometer-sized planetesimals through the entire growth process of becoming planets. We refer to it as the Lagrangian Integrator for Planetary Accretion and Dynamics or LIPAD. LIPAD is built on top of SyMBA, which is a symplectic N-body integrator. In order to handle the very large number of planetesimals required by planet formation simulations, we introduce the concept of a tracer particle. Each tracer is intended to represent a large number of disk particles on roughly the same orbit and size as one another and is characterized by three numbers: the physical radius, the bulk density, and the total mass of the disk particles represented by the tracer. We developed statistical algorithms that follow the velocity and size evolution of the tracers due to close gravitational encounters and physical collisions with one another. The tracers mainly dynamically interact with the larger objects (planetary embryos) in the normal N-body way. LIPAD's greatest strength is that it can accurately model the wholesale redistribution of planetesimals due to gravitational interaction with the embryos, which has recently been shown to significantly affect the growth rate of planetary embryos. We verify the code via a comprehensive set of tests that compare our results with those of Eulerian and/or direct N-body codes.
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.
Mattsson, Brady J.; Runge, M.C.; Devries, J.H.; Boomer, G.S.; Eadie, J.M.; Haukos, D.A.; Fleskes, J.P.; Koons, D.N.; Thogmartin, W.E.; Clark, R.G.
2012-01-01
We developed and evaluated the performance of a metapopulation model enabling managers to examine, for the first time, the consequences of alternative management strategies involving habitat conditions and hunting on both harvest opportunity and carrying capacity (i.e., equilibrium population size in the absence of harvest) for migratory waterfowl at a continental scale. Our focus is on the northern pintail (Anas acuta; hereafter, pintail), which serves as a useful model species to examine the potential for integrating waterfowl harvest and habitat management in North America. We developed submodel structure capturing important processes for pintail populations during breeding, fall migration, winter, and spring migration while encompassing spatial structure representing three core breeding areas and two core nonbreeding areas. A number of continental-scale predictions from our baseline parameterization (e.g., carrying capacity of 5.5 million, equilibrium population size of 2.9 million and harvest rate of 12% at maximum sustained yield [MSY]) were within 10% of those from the pintail harvest strategy under current use by the U.S. Fish and Wildlife Service. To begin investigating the interaction of harvest and habitat management, we examined equilibrium population conditions for pintail at the continental scale across a range of harvest rates while perturbing model parameters to represent: (1) a 10% increase in breeding habitat quality in the Prairie Pothole population (PR); and (2) a 10% increase in nonbreeding habitat quantity along in the Gulf Coast (GC). Based on our model and analysis, a greater increase in carrying capacity and sustainable harvest was seen when increasing a proxy for habitat quality in the Prairie Pothole population. This finding and underlying assumptions must be critically evaluated, however, before specific management recommendations can be made. To make such recommendations, we require (1) extended, refined submodels with additional
Neural and Cognitive Modeling with Networks of Leaky Integrator Units
NASA Astrophysics Data System (ADS)
Graben, Peter beim; Liebscher, Thomas; Kurths, Jürgen
After reviewing several physiological findings on oscillations in the electroencephalogram (EEG) and their possible explanations by dynamical modeling, we present neural networks consisting of leaky integrator units as a universal paradigm for neural and cognitive modeling. In contrast to standard recurrent neural networks, leaky integrator units are described by ordinary differential equations living in continuous time. We present an algorithm to train the temporal behavior of leaky integrator networks by generalized back-propagation and discuss their physiological relevance. Eventually, we show how leaky integrator units can be used to build oscillators that may serve as models of brain oscillations and cognitive processes.
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.
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
Launch Vehicle Dynamics Demonstrator Model
NASA Technical Reports Server (NTRS)
1963-01-01
Launch Vehicle Dynamics Demonstrator Model. The effect of vibration on launch vehicle dynamics was studied. Conditions included three modes of instability. The film includes close up views of the simulator fuel tank with and without stability control. [Entire movie available on DVD from CASI as Doc ID 20070030984. Contact help@sti.nasa.gov
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
Integrated UV fluorescence/DIAL model
Jefferson, K.J.
1994-06-01
Current SNL CALIOPE modeling efforts have produced an initial model that addresses DIAL issues of wavelength, hardware design parameters, range evaluation, etc. Although this model is producing valuable results and will be used to support the planning and evaluations necessary for the first ground field experiment, it is expected to have limitations with the complex science issues that affect the CALIOPE program. In particular, the multi-dimensional effects of atmospheric turbulence, plume dynamics, speckle, etc., may be significant issues and must be evaluated in detail as the program moves to the detection of liquids and solids, longer ranges, and elevated platform environments. The goal of the integrated UV fluorescence/DIAL modeling effort is to build upon the knowledge obtained in developing and exercising the initial model to adequately support the future activities of this program. This paper will address the development of the integrated UV model, issues and limiting assumptions that may be needed in order to address the-complex phenomena involved, limits of expected performance, and the potential use of this model.
Generative models of conformational dynamics.
Langmead, Christopher James
2014-01-01
Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term 'generative' refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GRAPHICAL MODELS OF ENERGY LANDSCAPES), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc.) from long timescale simulation data.
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. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
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.
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.
Dynamics modeling and simulation of flexible airships
NASA Astrophysics Data System (ADS)
Li, Yuwen
The resurgence of airships has created a need for dynamics models and simulation capabilities of these lighter-than-air vehicles. The focus of this thesis is a theoretical framework that integrates the flight dynamics, structural dynamics, aerostatics and aerodynamics of flexible airships. The study begins with a dynamics model based on a rigid-body assumption. A comprehensive computation of aerodynamic effects is presented, where the aerodynamic forces and moments are categorized into various terms based on different physical effects. A series of prediction approaches for different aerodynamic effects are unified and applied to airships. The numerical results of aerodynamic derivatives and the simulated responses to control surface deflection inputs are verified by comparing to existing wind-tunnel and flight test data. With the validated aerodynamics and rigid-body modeling, the equations of motion of an elastic airship are derived by the Lagrangian formulation. The airship is modeled as a free-free Euler-Bernoulli beam and the bending deformations are represented by shape functions chosen as the free-free normal modes. In order to capture the coupling between the aerodynamic forces and the structural elasticity, local velocity on the deformed vehicle is used in the computation of aerodynamic forces. Finally, with the inertial, gravity, aerostatic and control forces incorporated, the dynamics model of a flexible airship is represented by a single set of nonlinear ordinary differential equations. The proposed model is implemented as a dynamics simulation program to analyze the dynamics characteristics of the Skyship-500 airship. Simulation results are presented to demonstrate the influence of structural deformation on the aerodynamic forces and the dynamics behavior of the airship. The nonlinear equations of motion are linearized numerically for the purpose of frequency domain analysis and for aeroelastic stability analysis. The results from the latter for the
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.
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.
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.
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.
Hypnosis, suggestion, and suggestibility: an integrative model.
Lynn, Steven Jay; Laurence, Jean-Roch; Kirsch, Irving
2015-01-01
This article elucidates an integrative model of hypnosis that integrates social, cultural, cognitive, and neurophysiological variables at play both in and out of hypnosis and considers their dynamic interaction as determinants of the multifaceted experience of hypnosis. The roles of these variables are examined in the induction and suggestion stages of hypnosis, including how they are related to the experience of involuntariness, one of the hallmarks of hypnosis. It is suggested that studies of the modification of hypnotic suggestibility; cognitive flexibility; response sets and expectancies; the default-mode network; and the search for the neurophysiological correlates of hypnosis, more broadly, in conjunction with research on social psychological variables, hold much promise to further understanding of hypnosis.
Wang, Shuo; Xu, Ling; Yang, Fenglin; Wang, He
2014-02-15
Considering the limitation of the traditional method to assess the ecological carrying capacity and the complexity of the water ecological system, we used system dynamics, ANN, and CA-Markov to model a water ecological system. The social component was modeled according to Granger causality test by system dynamics. The natural component consists of the water resource and water environmental capacity, which were forecasted through the prediction of precipitation and change in land use cover. The interaction of the social component and the natural component mainly reflected environmental policies, such as the imposition of an environmental fee and environmental tax based on their values. Simulation results showed the different assessments on water ecological carrying capacity under the two policies. The population grew (2.9 million), and less pollution (86,632.37 t COD and 2854.5 t NH4N) was observed with the imposition of environmental tax compared with the imposition of an environmental fee (2.85 million population, 10,8381 t COD and 3543 t NH4N) at the same GDP level of 585 billion CNY in 2030. According to the causality loop, we discussed the different states under the policies and the reasons that caused the differences in water ecological carrying capacity state. According to game theory, we explained the limitation of the environmental fee policy on the basis of marginal benefit and cost. The externality was cleared up by the environmental tax policy.
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
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.
Cotangent Models for Integrable Systems
NASA Astrophysics Data System (ADS)
Kiesenhofer, Anna; Miranda, Eva
2017-03-01
We associate cotangent models to a neighbourhood of a Liouville torus in symplectic and Poisson manifolds focusing on b-Poisson/ b-symplectic manifolds. The semilocal equivalence with such models uses the corresponding action-angle theorems in these settings: the theorem of Liouville-Mineur-Arnold for symplectic manifolds and an action-angle theorem for regular Liouville tori in Poisson manifolds (Laurent- Gengoux et al., IntMath Res Notices IMRN 8: 1839-1869, 2011). Our models comprise regular Liouville tori of Poisson manifolds but also consider the Liouville tori on the singular locus of a b-Poisson manifold. For this latter class of Poisson structures we define a twisted cotangent model. The equivalence with this twisted cotangent model is given by an action-angle theorem recently proved by the authors and Scott (Math. Pures Appl. (9) 105(1):66-85, 2016). This viewpoint of cotangent models provides a new machinery to construct examples of integrable systems, which are especially valuable in the b-symplectic case where not many sources of examples are known. At the end of the paper we introduce non-degenerate singularities as lifted cotangent models on b-symplectic manifolds and discuss some generalizations of these models to general Poisson manifolds.
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.
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.
Path integral methods for the dynamics of stochastic and disordered systems
NASA Astrophysics Data System (ADS)
Hertz, John A.; Roudi, Yasser; Sollich, Peter
2017-01-01
We review some of the techniques used to study the dynamics of disordered systems subject to both quenched and fast (thermal) noise. Starting from the Martin-Siggia-Rose/Janssen-De Dominicis-Peliti path integral formalism for a single variable stochastic dynamics, we provide a pedagogical survey of the perturbative, i.e. diagrammatic, approach to dynamics and how this formalism can be used for studying soft spin models. We review the supersymmetric formulation of the Langevin dynamics of these models and discuss the physical implications of the supersymmetry. We also describe the key steps involved in studying the disorder-averaged dynamics. Finally, we discuss the path integral approach for the case of hard Ising spins and review some recent developments in the dynamics of such kinetic Ising models.
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.
Integrated modeling of advanced optical systems
NASA Technical Reports Server (NTRS)
Briggs, Hugh C.; Needels, Laura; Levine, B. Martin
1993-01-01
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.
ERIC Educational Resources Information Center
Journal of Science and Mathematics Education in Southeast Asia, 1981
1981-01-01
Instructions (with diagrams and parts list) are provided for constructing an eye model with a pliable lens made from a plastic bottle which can vary its convexity to accommodate changing positions of an object being viewed. Also discusses concepts which the model can assist in developing. (Author/SK)
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.
Integrity modelling of tropospheric delay models
NASA Astrophysics Data System (ADS)
Rózsa, Szabolcs; Bastiaan Ober, Pieter; Mile, Máté; Ambrus, Bence; Juni, Ildikó
2017-04-01
The effect of the neutral atmosphere on signal propagation is routinely estimated by various tropospheric delay models in satellite navigation. Although numerous studies can be found in the literature investigating the accuracy of these models, for safety-of-life applications it is crucial to study and model the worst case performance of these models using very low recurrence frequencies. The main objective of the INTegrity of TROpospheric models (INTRO) project funded by the ESA PECS programme is to establish a model (or models) of the residual error of existing tropospheric delay models for safety-of-life applications. Such models are required to overbound rare tropospheric delays and should thus include the tails of the error distributions. Their use should lead to safe error bounds on the user position and should allow computation of protection levels for the horizontal and vertical position errors. The current tropospheric model from the RTCA SBAS Minimal Operational Standards has an associated residual error that equals 0.12 meters in the vertical direction. This value is derived by simply extrapolating the observed distribution of the residuals into the tail (where no data is present) and then taking the point where the cumulative distribution has an exceedance level would be 10-7.While the resulting standard deviation is much higher than the estimated standard variance that best fits the data (0.05 meters), it surely is conservative for most applications. In the context of the INTRO project some widely used and newly developed tropospheric delay models (e.g. RTCA MOPS, ESA GALTROPO and GPT2W) were tested using 16 years of daily ERA-INTERIM Reanalysis numerical weather model data and the raytracing technique. The results showed that the performance of some of the widely applied models have a clear seasonal dependency and it is also affected by a geographical position. In order to provide a more realistic, but still conservative estimation of the residual
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.
Dynamic network management and service integration for airborne network
NASA Astrophysics Data System (ADS)
Pan, Wei; Li, Weihua
2009-12-01
The development of airborne network is conducive to resource sharing, flight management and interoperability in civilian and military aviation fields. To enhance the integrated ability of airborne network, the paper focuses on dynamic network management and service integration architecture for airborne network (DNMSIAN). Adaptive routing based on the mapping mechanism between connection identification and routing identification can provide diversified network access, and ensure the credibility and mobility of the aviation information exchange. Dynamic network management based on trustworthy cluster can ensure dynamic airborne network controllable and safe. Service integration based on semantic web and ontology can meet the customized and diversified needs for aviation information services. The DNMSIAN simulation platform demonstrates that our proposed methods can effectively perform dynamic network management and service integration.
NASA Astrophysics Data System (ADS)
Runge, Jeffrey A.; Kovach, Adrienne I.; Churchill, James H.; Kerr, Lisa A.; Morrison, John R.; Beardsley, Robert C.; Berlinsky, David L.; Chen, Changsheng; Cadrin, Steven X.; Davis, Cabell S.; Ford, Kathryn H.; Grabowski, Jonathan H.; Howell, W. Huntting; Ji, Rubao; Jones, Rebecca J.; Pershing, Andrew J.; Record, Nicholas R.; Thomas, Andrew C.; Sherwood, Graham D.; Tallack, Shelly M. L.; Townsend, David W.
2010-10-01
We put forward a combined observing and modeling strategy for evaluating effects of environmental forcing on the dynamics of spatially structured cod populations spawning in the western Gulf of Maine. Recent work indicates at least two genetically differentiated complexes in this region: a late spring spawning, coastal population centered in Ipswich Bay, and a population that spawns in winter inshore and on nearshore banks in the Gulf of Maine and off southern New England. The two populations likely differ in trophic interactions and in physiological and behavioral responses to different winter and spring environments. Coupled physical-biological modeling has advanced to the point where within-decade forecasting of environmental conditions for recruitment to each of the two populations is feasible. However, the modeling needs to be supported by hydrographic, primary production and zooplankton data collected by buoys, and by data from remote sensing and fixed station sampling. Forecasts of environmentally driven dispersal and growth of planktonic early life stages, combined with an understanding of possible population-specific predator fields, usage of coastal habitat by juveniles and adult resident and migratory patterns, can be used to develop scenarios for spatially explicit population responses to multiple forcings, including climate change, anthropogenic impacts on nearshore juvenile habitat, connectivity among populations and management interventions such as regional fisheries closures.
NASA Astrophysics Data System (ADS)
Pérez, Alejandro; Tuckerman, Mark E.
2011-08-01
Higher order factorization schemes are developed for path integral molecular dynamics in order to improve the convergence of estimators for physical observables as a function of the Trotter number. The methods are based on the Takahashi-Imada and Susuki decompositions of the Boltzmann operator. The methods introduced improve the averages of the estimators by using the classical forces needed to carry out the dynamics to construct a posteriori weighting factors for standard path integral molecular dynamics. The new approaches are straightforward to implement in existing path integral codes and carry no significant overhead. The Suzuki higher order factorization was also used to improve the end-to-end distance estimator in open path integral molecular dynamics. The new schemes are tested in various model systems, including an ab initio path integral molecular dynamics calculation on the hydrogen molecule and a quantum water model. The proposed algorithms have potential utility for reducing the cost of path integral molecular dynamics calculations of bulk systems.
Pérez, Alejandro; Tuckerman, Mark E
2011-08-14
Higher order factorization schemes are developed for path integral molecular dynamics in order to improve the convergence of estimators for physical observables as a function of the Trotter number. The methods are based on the Takahashi-Imada and Susuki decompositions of the Boltzmann operator. The methods introduced improve the averages of the estimators by using the classical forces needed to carry out the dynamics to construct a posteriori weighting factors for standard path integral molecular dynamics. The new approaches are straightforward to implement in existing path integral codes and carry no significant overhead. The Suzuki higher order factorization was also used to improve the end-to-end distance estimator in open path integral molecular dynamics. The new schemes are tested in various model systems, including an ab initio path integral molecular dynamics calculation on the hydrogen molecule and a quantum water model. The proposed algorithms have potential utility for reducing the cost of path integral molecular dynamics calculations of bulk systems.
NASA Astrophysics Data System (ADS)
Belov, A. A.; Igumnov, L. A.; Litvinchuk, S. Yu.; Metrikin, V. S.
2016-11-01
Two approaches (classical and nonclassical) of the boundary integral equation method for solving three-dimensional dynamical boundary value problems of elasticity, viscoelasticity, and poroelasticity are considered. The boundary integral equation model is used for porous materials. The Kelvin-Voigt model and the weakly singular hereditary Abel kernel are used to describe the viscoelastic properties. Both approaches permit solving the dynamic problems exactly not only in the isotropic but also in the anisotropic case. The boundary integral equation solution scheme is constructed on the basis of the boundary element technique. The numerical results obtained by the classical and nonclassical approaches are compared.
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.
Dynamic models in research and management of biological invasions.
Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R
2017-03-25
Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales.
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.
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.
Modeling Molecular Dynamics from Simulations
Hinrichs, Nina Singhal
2009-01-28
Many important processes in biology occur at the molecular scale. A detailed understanding of these processes can lead to significant advances in the medical and life sciences. For example, many diseases are caused by protein aggregation or misfolding. One approach to studying these systems is to use physically-based computational simulations to model the interactions and movement of the molecules. While molecular simulations are computationally expensive, it is now possible to simulate many independent molecular dynamics trajectories in a parallel fashion by using super- or distributed- computing methods such as Folding@Home or Blue Gene. The analysis of these large, high-dimensional data sets presents new computational challenges. In this seminar, I will discuss a novel approach to analyzing large ensembles of molecular dynamics trajectories to generate a compact model of the dynamics. This model groups conformations into discrete states and describes the dynamics as Markovian, or history-independent, transitions between the states. I will discuss why the Markovian state model (MSM) is suitable for macromolecular dynamics, and how it can be used to answer many interesting and relevant questions about the molecular system. I will also discuss many of the computational and statistical challenges in building such a model, such as how to appropriately cluster conformations, determine the statistical reliability, and efficiently design new simulations.
Flapping Wing Flight Dynamic Modeling
2011-08-22
against those of Theodorsen [16], Garrick [17], Loewy [18], Issacs [19, 20], Greenberg [21], Wagner [22], and von Karman [23] as well as experimental...kinematics and this data was used to generate the nal equations of motion (added to the nonlinear equations already derived from the Newton -Euler...wings). The ight dynamic model is a six-degree-of-freedom set of dynamic equations ( Newton -Euler scheme) with translation described in the inertial
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
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.
Dynamical properties of the Integral Sign galaxy.
NASA Astrophysics Data System (ADS)
Márquez, I.; Del Olmo, A.
The galaxy A 0705+7155, called the Integral Sign because of its singular aspect, was spectroscopically examined. Physical conditions of the ISM, rotation curve, mass, morphological type, warps, and the distance of A 0705+7155 are discussed.
Structural dynamics system model reduction
NASA Technical Reports Server (NTRS)
Chen, J. C.; Rose, T. L.; Wada, B. K.
1987-01-01
Loads analysis for structural dynamic systems is usually performed by finite element models. Because of the complexity of the structural system, the model contains large number of degree-of-freedom. The large model is necessary since details of the stress, loads and responses due to mission environments are computed. However, a simplified model is needed for other tasks such as pre-test analysis for modal testing, and control-structural interaction studies. A systematic method of model reduction for modal test analysis is presented. Perhaps it will be of some help in developing a simplified model for the control studies.
Cowan, J.H., Jr. . Chesapeake Biological Lab.); Rose, K.A. )
1991-01-01
We have used a bioenergetically-driven, individual-based model (IBM) of striped bass as a framework for synthesizing available information on population biology and quantifying, in a relative sense, factors that potentially affect year class success. The IBM has been configured to simulate environmental conditions experienced by several striped bass populations; i.e., in the Potomac River, MD; in Hudson River, NY; in the Santee-Cooper River System, SC, and; in the San Joaquin-Sacramento River System CA. These sites represent extremes in the geographic distribution and thus, environmental variability of striped bass spawning. At each location, data describing the physio-chemical and biological characteristics of the spawning population and nursery area are being collected and synthesized by means of a prioritized, directed field sampling program that is organized by the individual-based recruitment model. Here, we employ the striped bass IBM configured for the Potomac River, MD from spawning into the larval period to evaluate the potential for maternal contribution to affect larva survival and growth. Model simulations in which the size distribution and spawning day of females are altered indicate that larva survival is enhanced (3.3-fold increase) when a high fraction of females in the spawning population are large. Larva stage duration also is less ({bar X} = 18.4 d and 22.2 d) when large and small females, respectively, are mothers in simulations. Although inconclusive, these preliminary results for Potomac River striped bass suggest that the effects of female size, timing of spawning nad maternal contribution on recruitment dynamics potentially are important and illustrate our approach to the study of recruitment in striped bass. We hope to use the model, field collections and management alternatives that vary from site to site, in an iterative manner for some time to come. 54 refs., 4 figs., 1 tab.
A general dynamic model of flexible robot arms for control
NASA Technical Reports Server (NTRS)
Ding, X.; Tarn, T. J.; Bejczy, A. K.
1989-01-01
Hamilton's principle is used to derive the dynamic model for a large class of flexible robot arms. The resultant dynamic model consists of a system of partial differential-integral equations and the dynamic boundary conditions associated with it. Some properties of the model are observed, and its application to control is discussed. This model represents an infinite-dimensional nonlinear dynamic system and yet can be turned into a finite-dimensional system that could be obtained by modal expansion, if it is desired. This provides more flexibility for control purposes as well as for the analysis of the system.
Understanding Terrorist Organizations with a Dynamic Model
NASA Astrophysics Data System (ADS)
Gutfraind, Alexander
Terrorist organizations change over time because of processes such as recruitment and training as well as counter-terrorism (CT) measures, but the effects of these processes are typically studied qualitatively and in separation from each other. Seeking a more quantitative and integrated understanding, we constructed a simple dynamic model where equations describe how these processes change an organization’s membership. Analysis of the model yields a number of intuitive as well as novel findings. Most importantly it becomes possible to predict whether counter-terrorism measures would be sufficient to defeat the organization. Furthermore, we can prove in general that an organization would collapse if its strength and its pool of foot soldiers decline simultaneously. In contrast, a simultaneous decline in its strength and its pool of leaders is often insufficient and short-termed. These results and other like them demonstrate the great potential of dynamic models for informing terrorism scholarship and counter-terrorism policy making.
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
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.
Smart dynamic system design: an integrated approach
NASA Astrophysics Data System (ADS)
Carpenter, Mike J.; Skelton, Robert T.
1994-05-01
A dynamic system with satisfactory performance generally consists of a mechanical system (the plant) and a controller that drives the mechanical system to meet certain performance requirements. Traditionally the control engineer designs the controller only after the plant design is completed. This two-step approach to plant and controller design does not provide the best system design because the dynamics of the plant and the dynamics of the controller often oppose each other. This paper presents an application of the iterative system equivalent optimal mix algorithm to perform a smart design of a nine-member truss substructure and its accompanying controller. The objective of the design algorithm is to reduce the amount of energy used by the controller to maintain control performance, subject to the structure design constraints. Two unique features of the algorithm are that each iteration of the design problem is stated as a convex quadratic programming problem, and the control effort monotonically converges to its final value.
Symplectic integrator for molecular dynamics of a protein in water
NASA Astrophysics Data System (ADS)
Ishida, Hisashi; Nagai, Yoshinori; Kidera, Akinori
1998-01-01
The symplectic integrator is an algorithm for solving equations of motion, preserving the volume in phase space and ensuring a stable simulation. We carried out molecular dynamics simulations of liquid water and a protein in water using several variations of symplectic integrators. It was found that a fourth-order symplectic integrator of Calvo and Sanz-Serna generated a trajectory of much higher accuracy than the conventional Verlet and Gear methods with the same requirements for CPU time.
Herman, Dorota; Thomas, Christopher M; Stekel, Dov J
2011-07-29
IncP-1 plasmids are broad host range plasmids that have been found in clinical and environmental bacteria. They often carry genes for antibiotic resistance or catabolic pathways. The archetypal IncP-1 plasmid RK2 is a well-characterized biological system, with a fully sequenced and annotated genome and wide range of experimental measurements. Its central control operon, encoding two global regulators KorA and KorB, is a natural example of a negatively self-regulated operon. To increase our understanding of the regulation of this operon, we have constructed a dynamical mathematical model using Ordinary Differential Equations, and employed a Bayesian inference scheme, Markov Chain Monte Carlo (MCMC) using the Metropolis-Hastings algorithm, as a way of integrating experimental measurements and a priori knowledge. We also compared MCMC and Metabolic Control Analysis (MCA) as approaches for determining the sensitivity of model parameters. We identified two distinct sets of parameter values, with different biological interpretations, that fit and explain the experimental data. This allowed us to highlight the proportion of repressor protein as dimers as a key experimental measurement defining the dynamics of the system. Analysis of joint posterior distributions led to the identification of correlations between parameters for protein synthesis and partial repression by KorA or KorB dimers, indicating the necessary use of joint posteriors for correct parameter estimation. Using MCA, we demonstrated that the system is highly sensitive to the growth rate but insensitive to repressor monomerization rates in their selected value regions; the latter outcome was also confirmed by MCMC. Finally, by examining a series of different model refinements for partial repression by KorA or KorB dimers alone, we showed that a model including partial repression by KorA and KorB was most compatible with existing experimental data. We have demonstrated that the combination of dynamical
Paleocene-Eocene Data Model Integration
NASA Astrophysics Data System (ADS)
Shellito, Cindy; Lamarque, Jean-Francois; Kiehl, J.
2007-08-01
National Center for Atmospheric Research Workshop on Paleocene-Eocene Thermal Maximum Data-Model Integration, 31 May to 1 June 2007, Santa Fe, New Mexico The warming at the Paleocene-Eocene boundary about 55 million years ago is the subject of intense research, as it has the potential to inform us about the effects of warming on the global ecosystem. Despite many years of research, many questions remain regarding the specifics and dynamics of this transitionally warm period known as the Paleocene-Eocene Thermal Maximum (PETM). The proposed source of this warming is a large increase in methane, carbon dioxide, or both, possibly from volcanic activity, methane hydrates buried along the continental slopes, and methane emissions from wetlands. Global climate models adapted with Eocene geography and high greenhouse gas levels have so far been unable to reproduce the warm climate of the high latitudes depicted by proxy data from this time. The integration of proxy data derived from the geologic and fossil record with model output is also a challenge, and requires cooperation of scientists from a broad array of disciplines.
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.
Integrated Hydrosystem Modeling of the California Basin
NASA Astrophysics Data System (ADS)
Davison, J. H.; Hwang, H. T.; Sudicky, E. A.; Mallia, D.; Lin, J. C.
2015-12-01
The Western United States is facing one of the worst droughts on record. Climate change projections predict warmer temperatures, higher evapotranspiration rates, and no foreseeable increase in precipitation. California, in particular, has supplemented their decreased surface water supplies by mining deep groundwater. However, this supply of groundwater is limited, especially with reduced recharge. These combined factors place California's water-demanding society at dire risk. In an effort to quantify California's risks, we present a fully integrated water cycle model that captures the dynamics of the subsurface, land surface, and atmospheric domains over the entire California basin. Our water cycle model combines HydroGeoSphere (HGS), a 3-D control-volume finite element model that accommodates variably-saturated subsurface and surface water flow with evapotranspiration processes to the Weather Research and Forecasting (WRF) model, a 3-D finite difference nonhydrostatic mesoscale atmospheric simulator. The two-way coupling within our model, referred to as HGS-WRF, tightly integrates the water cycling processes by passing precipitation and potential evapotranspiration data from WRF to HGS, while exchanging actual evapotranspiration and soil saturation data from HGS to WRF. Furthermore, HGS-WRF implements a flexible coupling method that allows each model to use a unique mesh while maintaining mass conservation within and between domains. Our simulation replicated field measured evapotranspiration fluxes and showed a strong correlation between the soil saturation (depth to groundwater table) and latent heat fluxes. Altogether, the HGS-WRF California basin model is currently the most complete water resource simulation framework as it combines groundwater, surface water, the unsaturated zone, and the atmosphere into one coupled system.
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.
A dynamic integrated test for the Space Shuttle
NASA Technical Reports Server (NTRS)
Brody, S.; Weissberg, R. W.
1979-01-01
The dynamic integrated test (DIT) has been designed to perform a final checkout of the assembled Space Shuttle vehicle at Kennedy Space Center. The fact that the vehicle is not in a laboratory environment for the test represents a significant constraint in that the use of test equipment is extremely limited, and environment models cannot be used. In essence, the DIT causes the vehicle to believe that it is flying, so that hardware and software systems are exercised much as they would be for a real flight. This technique provides a tool for verifying such items as data bus activity patterns, critical timing sequences, software and hardware moding as a function of flight parameters, absence of EMI problems and other systems interactions which cannot be tested fully in the laboratory.
A dynamic integrated test for the Space Shuttle
NASA Technical Reports Server (NTRS)
Brody, S.; Weissberg, R. W.
1979-01-01
The dynamic integrated test (DIT) has been designed to perform a final checkout of the assembled Space Shuttle vehicle at Kennedy Space Center. The fact that the vehicle is not in a laboratory environment for the test represents a significant constraint in that the use of test equipment is extremely limited, and environment models cannot be used. In essence, the DIT causes the vehicle to believe that it is flying, so that hardware and software systems are exercised much as they would be for a real flight. This technique provides a tool for verifying such items as data bus activity patterns, critical timing sequences, software and hardware moding as a function of flight parameters, absence of EMI problems and other systems interactions which cannot be tested fully in the laboratory.
Integrated approach to monitor water dynamics with drones
NASA Astrophysics Data System (ADS)
Raymaekers, Dries; De Keukelaere, Liesbeth; Knaeps, Els; Strackx, Gert; Decrop, Boudewijn; Bollen, Mark
2017-04-01
Remote sensing has been used for more than 20 years to estimate water quality in the open ocean and study the evolution of vegetation on land. More recently big improvements have been made to extend these practices to coastal and inland waters, opening new monitoring opportunities, eg. monitoring the impact of dredging activities on the aquatic environment. While satellite sensors can provide complete coverage and historical information of the study area, they are limited in their temporal revisit time and spatial resolution. Therefore, deployment of drones can create an added value and in combination with satellite information increase insights in the dynamics and actors of coastal and aquatic systems. Drones have the advantages of monitoring at high spatial detail (cm scale), with high frequency and are flexible. One of the important water quality parameters is the suspended sediment concentration. However, retrieving sediment concentrations from unmanned systems is a challenging task. The sediment dynamics in the port of Breskens, the Netherlands, were investigated by combining information retrieved from different data sources: satellite, drone and in-situ data were collected, analysed and inserted in sediment models. As such, historical (satellite), near-real time (drone) and predictive (sediment models) information, integrated in a spatial data infrastructure, allow to perform data analysis and can support decision makers.
Nonsmooth dynamics in spiking neuron models
NASA Astrophysics Data System (ADS)
Coombes, S.; Thul, R.; Wedgwood, K. C. A.
2012-11-01
Large scale studies of spiking neural networks are a key part of modern approaches to understanding the dynamics of biological neural tissue. One approach in computational neuroscience has been to consider the detailed electrophysiological properties of neurons and build vast computational compartmental models. An alternative has been to develop minimal models of spiking neurons with a reduction in the dimensionality of both parameter and variable space that facilitates more effective simulation studies. In this latter case the single neuron model of choice is often a variant of the classic integrate-and-fire model, which is described by a nonsmooth dynamical system. In this paper we review some of the more popular spiking models of this class and describe the types of spiking pattern that they can generate (ranging from tonic to burst firing). We show that a number of techniques originally developed for the study of impact oscillators are directly relevant to their analysis, particularly those for treating grazing bifurcations. Importantly we highlight one particular single neuron model, capable of generating realistic spike trains, that is both computationally cheap and analytically tractable. This is a planar nonlinear integrate-and-fire model with a piecewise linear vector field and a state dependent reset upon spiking. We call this the PWL-IF model and analyse it at both the single neuron and network level. The techniques and terminology of nonsmooth dynamical systems are used to flesh out the bifurcation structure of the single neuron model, as well as to develop the notion of Lyapunov exponents. We also show how to construct the phase response curve for this system, emphasising that techniques in mathematical neuroscience may also translate back to the field of nonsmooth dynamical systems. The stability of periodic spiking orbits is assessed using a linear stability analysis of spiking times. At the network level we consider linear coupling between voltage
NASA Astrophysics Data System (ADS)
Johnson, Margaret E.; Hummer, Gerhard
2014-07-01
We present a new algorithm for simulating reaction-diffusion equations at single-particle resolution. Our algorithm is designed to be both accurate and simple to implement, and to be applicable to large and heterogeneous systems, including those arising in systems biology applications. We combine the use of the exact Green's function for a pair of reacting particles with the approximate free-diffusion propagator for position updates to particles. Trajectory reweighting in our free-propagator reweighting (FPR) method recovers the exact association rates for a pair of interacting particles at all times. FPR simulations of many-body systems accurately reproduce the theoretically known dynamic behavior for a variety of different reaction types. FPR does not suffer from the loss of efficiency common to other path-reweighting schemes, first, because corrections apply only in the immediate vicinity of reacting particles and, second, because by construction the average weight factor equals one upon leaving this reaction zone. FPR applications include the modeling of pathways and networks of protein-driven processes where reaction rates can vary widely and thousands of proteins may participate in the formation of large assemblies. With a limited amount of bookkeeping necessary to ensure proper association rates for each reactant pair, FPR can account for changes to reaction rates or diffusion constants as a result of reaction events. Importantly, FPR can also be extended to physical descriptions of protein interactions with long-range forces, as we demonstrate here for Coulombic interactions.
Hummer, Gerhard
2015-01-01
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. PMID:26005592
Gradient navigation model for pedestrian dynamics
NASA Astrophysics Data System (ADS)
Dietrich, Felix; Köster, Gerta
2014-06-01
We present a microscopic ordinary differential equation (ODE)-based model for pedestrian dynamics: the gradient navigation model. The model uses a superposition of gradients of distance functions to directly change the direction of the velocity vector. The velocity is then integrated to obtain the location. The approach differs fundamentally from force-based models needing only three equations to derive the ODE system, as opposed to four in, e.g., the social force model. Also, as a result, pedestrians are no longer subject to inertia. Several other advantages ensue: Model-induced oscillations are avoided completely since no actual forces are present. The derivatives in the equations of motion are smooth and therefore allow the use of fast and accurate high-order numerical integrators. At the same time, the existence and uniqueness of the solution to the ODE system follow almost directly from the smoothness properties. In addition, we introduce a method to calibrate parameters by theoretical arguments based on empirically validated assumptions rather than by numerical tests. These parameters, combined with the accurate integration, yield simulation results with no collisions of pedestrians. Several empirically observed system phenomena emerge without the need to recalibrate the parameter set for each scenario: obstacle avoidance, lane formation, stop-and-go waves, and congestion at bottlenecks. The density evolution in the latter is shown to be quantitatively close to controlled experiments. Likewise, we observe a dependence of the crowd velocity on the local density that compares well with benchmark fundamental diagrams.
Dynamical models and Galaxy surveys
NASA Astrophysics Data System (ADS)
Binney, James; Sanders, Jason L.
2014-01-01
Equilibrium dynamical models are essential tools for extracting science from surveys of our Galaxy. We show how models can be tested with data from a survey before the survey's selection function has been determined. We illustrate the application of this method by presenting some results for the RAVE survey. We extend our published analytic distribution functions to include chemistry and fit the chosen functional form to a combination of the Geneva-Copenhagen survey (GCS) and a sample of G-dwarfs observed at z ~ 1.75 kpc by the SEGUE survey. By including solid dynamics we are able to predict the contribution that the thick disc/halo stars surveyed by SEGUE should make to the GCS survey. We show that the measured [Fe/H] distribution from the GCS includes many fewer stars at [Fe/H] < -0.6 than are predicted. The problem is more likely to lie in discordant abundance scales than with incorrect dynamics.
Chen, Guangsheng; Tian, Hanqin; Huang, Chengquan; Prior, Stephen A.; Pan, Shufen
2013-07-01
Forest 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 = 10^{12} 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. Lastly, this study implies that understanding forest disturbance impacts on carbon dynamics is of critical importance for assessing regional carbon budgets.
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.
Chen, Guangsheng; Tian, Hanqin; Huang, Chengquan; ...
2013-07-01
Forest 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 formore » 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. Lastly, this study implies that understanding forest disturbance impacts on carbon dynamics is of critical importance for assessing regional carbon budgets.« less
Generative Models of Conformational Dynamics
Langmead, Christopher James
2014-01-01
Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GrAphical Models of Energy LANdscapes), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc) from long timescale simulation data. PMID:24446358
The dynamics of coastal models
Hearn, Clifford J.
2008-01-01
Coastal basins are defined as estuaries, lagoons, and embayments. This book deals with the science of coastal basins using simple models, many of which are presented in either analytical form or Microsoft Excel or MATLAB. The book introduces simple hydrodynamics and its applications, from the use of simple box and one-dimensional models to flow over coral reefs. The book also emphasizes models as a scientific tool in our understanding of coasts, and introduces the value of the most modern flexible mesh combined wave-current models. Examples from shallow basins around the world illustrate the wonders of the scientific method and the power of simple dynamics. This book is ideal for use as an advanced textbook for graduate students and as an introduction to the topic for researchers, especially those from other fields of science needing a basic understanding of the basic ideas of the dynamics of coastal basins.
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.
NASA Astrophysics Data System (ADS)
Marsh, Jeffrey; Culshaw, Nicholas
2014-05-01
granulite-amphibolite nappe structurally overlying the eclogite-bearing domains indicate that the hot nappe was emplaced over the orogenic core along kilometer-scale, pegmatite-rich, amphibolite-facies shear zones by ca. 1100 Ma. Thus, petrochronological data constrain a sequence of nappe emplacement, HP metamorphism, and migmatization evolving over ~15-20 Myrs, apparently marking a transition in the deep crustal dynamics from a predominantly thickening phase to a thermally weakened lateral flow phase. Ongoing diffusion modeling of chemical gradients in garnet crystals, reaction coronas, and symplectites should yield tighter constraints on the duration of HT residence and cooling/exhumation rates.
Predictive models of battle dynamics
NASA Astrophysics Data System (ADS)
Jelinek, Jan
2001-09-01
The application of control and game theories to improve battle planning and execution requires models, which allow military strategists and commanders to reliably predict the expected outcomes of various alternatives over a long horizon into the future. We have developed probabilistic battle dynamics models, whose building blocks in the form of Markov chains are derived from the first principles, and applied them successfully in the design of the Model Predictive Task Commander package. This paper introduces basic concepts of our modeling approach and explains the probability distributions needed to compute the transition probabilities of the Markov chains.
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
Locally Contractive Dynamics in Generalized Integrate-and-Fire Neurons.
Jimenez, Nicolas D; Mihalas, Stefan; Brown, Richard; Niebur, Ernst; Rubin, Jonathan
2013-09-10
Integrate-and-fire models of biological neurons combine differential equations with discrete spike events. In the simplest case, the reset of the neuronal voltage to its resting value is the only spike event. The response of such a model to constant input injection is limited to tonic spiking. We here study a generalized model in which two simple spike-induced currents are added. We show that this neuron exhibits not only tonic spiking at various frequencies but also the commonly observed neuronal bursting. Using analytical and numerical approaches, we show that this model can be reduced to a one-dimensional map of the adaptation variable and that this map is locally contractive over a broad set of parameter values. We derive a sufficient analytical condition on the parameters for the map to be globally contractive, in which case all orbits tend to a tonic spiking state determined by the fixed point of the return map. We then show that bursting is caused by a discontinuity in the return map, in which case the map is piecewise contractive. We perform a detailed analysis of a class of piecewise contractive maps that we call bursting maps and show that they robustly generate stable bursting behavior. To the best of our knowledge, this work is the first to point out the intimate connection between bursting dynamics and piecewise contractive maps. Finally, we discuss bifurcations in this return map, which cause transitions between spiking patterns.
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
NASA Astrophysics Data System (ADS)
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.
Model based control of dynamic atomic force microscope.
Lee, Chibum; Salapaka, Srinivasa M
2015-04-01
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
NASA Astrophysics Data System (ADS)
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.
Stochastic Model of Microtubule Dynamics
NASA Astrophysics Data System (ADS)
Hryniv, Ostap; Martínez Esteban, Antonio
2017-10-01
We introduce a continuous time stochastic process on strings made of two types of particle, whose dynamics mimics that of microtubules in a living cell. The long term behaviour of the system is described in terms of the velocity v of the string end. We show that v is an analytic function of its parameters and study its monotonicity properties. We give a complete characterisation of the phase diagram of the model and derive several criteria of the growth (v>0) and the shrinking (v<0) regimes of the dynamics.
Soil C and N models that integrate microbial diversity.
Louis, Benjamin P; Maron, Pierre-Alain; Viaud, Valérie; Leterme, Philippe; Menasseri-Aubry, Safya
Industrial agriculture is yearly responsible for the loss of 55-100 Pg of historical soil carbon and 9.9 Tg of reactive nitrogen worldwide. Therefore, management practices should be adapted to preserve ecological processes and reduce inputs and environmental impacts. In particular, the management of soil organic matter (SOM) is a key factor influencing C and N cycles. Soil microorganisms play a central role in SOM dynamics. For instance, microbial diversity may explain up to 77 % of carbon mineralisation activities. However, soil microbial diversity is actually rarely taken into account in models of C and N dynamics. Here, we review the influence of microbial diversity on C and N dynamics, and the integration of microbial diversity in soil C and N models. We found that a gain of microbial richness and evenness enhances soil C and N dynamics on the average, though the improvement of C and N dynamics depends on the composition of microbial community. We reviewed 50 models integrating soil microbial diversity. More than 90 % of models integrate microbial diversity with discrete compartments representing conceptual functional groups (64 %) or identified taxonomic groups interacting in a food web (28 %). Half of the models have not been tested against an empirical dataset while the other half mainly consider fixed parameters. This is due to the difficulty to link taxonomic and functional diversity.
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
Dynamic Model of Mesoscale Eddies
NASA Astrophysics Data System (ADS)
Dubovikov, Mikhail S.
2003-04-01
Oceanic mesoscale eddies which are analogs of well known synoptic eddies (cyclones and anticyclones), are studied on the basis of the turbulence model originated by Dubovikov (Dubovikov, M.S., "Dynamical model of turbulent eddies", Int. J. Mod. Phys.B7, 4631-4645 (1993).) and further developed by Canuto and Dubovikov (Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: I. General formalism", Phys. Fluids8, 571-586 (1996a) (CD96a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: II. Sheardriven flows", Phys. Fluids8, 587-598 (1996b) (CD96b); Canuto, V.M., Dubovikov, M.S., Cheng, Y. and Dienstfrey, A., "A dynamical model for turbulence: III. Numerical results", Phys. Fluids8, 599-613 (1996c)(CD96c); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "A dynamical model for turbulence: IV. Buoyancy-driven flows", Phys. Fluids9, 2118-2131 (1997a) (CD97a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: V. The effect of rotation", Phys. Fluids9, 2132-2140 (1997b) (CD97b); Canuto, V.M., Dubovikov, M.S. and Wielaard, D.J., "A dynamical model for turbulence: VI. Two dimensional turbulence", Phys. Fluids9, 2141-2147 (1997c) (CD97c); Canuto, V.M. and Dubovikov, M.S., "Physical regimes and dimensional structure of rotating turbulence", Phys. Rev. Lett. 78, 666-669 (1997d) (CD97d); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "Turbulent convection in a spectral model", Phys. Rev. Lett. 78, 662-665 (1997e) (CD97e); Canuto, V.M. and Dubovikov, M.S., "A new approach to turbulence", Int. J. Mod. Phys.12, 3121-3152 (1997f) (CD97f); Canuto, V.M. and Dubovikov, M.S., "Two scaling regimes for rotating Raleigh-Benard convection", Phys. Rev. Letters78, 281-284, (1998) (CD98); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: VII. The five invariants for shear driven flows", Phys. Fluids11, 659-664 (1999a) (CD99a); Canuto, V.M., Dubovikov, M.S. and Yu, G., "A dynamical model for turbulence: VIII. IR and UV
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…
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.
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.
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
2015-09-08
Optical tracking is often combined with conventional flat panel solar cells to maximize electrical power generation over the course of a day. However, conventional trackers are complex and often require costly and cumbersome structural components to support system weight. Here we use kirigami (the art of paper cutting) to realize novel solar cells where tracking is integral to the structure at the substrate level. Specifically, an elegant cut pattern is made in thin-film gallium arsenide solar cells, which are then stretched to produce an array of tilted surface elements which can be controlled to within ±1°. We analyze the combined optical and mechanical properties of the tracking system, and demonstrate a mechanically robust system with optical tracking efficiencies matching conventional trackers. This design suggests a pathway towards enabling new applications for solar tracking, as well as inspiring a broader range of optoelectronic and mechanical devices.
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.
Integrated dynamic fluidic lens system for in vivo biological imaging.
Justis, N B; Zhang, D-Y; Lo, Y H
2004-01-01
We have developed an integrated dynamic lens system for in vivo optical imaging. Bioinspired dynamic microfluidic lenses allow for real-time dynamic manipulation of the lens focal length via microfluidic injection into a PDMS membrane-capped chamber. A piezoelectrically actuated micropump is integrated with with the lens to provide highspeed, accurate lens tunability. The 5mm dynamic lens has demonstrated focal length tunability from 8.5mm to 23mm, numerical aperture values from 0.39 to 0.77, and resolution of 40 linepairs/mm. The micropump operates at 5 kHz and achieved a flow rate of approximately 2.4 mL/min. This system can be applied to optical probe techniques to improve diagnosis with real-time depth resolution and variable numerical aperture.
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.
A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony.
Zhang, J W; Rangan, A V
2015-04-01
In this paper we provide a general methodology for systematically reducing the dynamics of a class of integrate-and-fire networks down to an augmented 4-dimensional system of ordinary-differential-equations. The class of integrate-and-fire networks we focus on are homogeneously-structured, strongly coupled, and fluctuation-driven. Our reduction succeeds where most current firing-rate and population-dynamics models fail because we account for the emergence of 'multiple-firing-events' involving the semi-synchronous firing of many neurons. These multiple-firing-events are largely responsible for the fluctuations generated by the network and, as a result, our reduction faithfully describes many dynamic regimes ranging from homogeneous to synchronous. Our reduction is based on first principles, and provides an analyzable link between the integrate-and-fire network parameters and the relatively low-dimensional dynamics underlying the 4-dimensional augmented ODE.
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.
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.
Modeling integrated biomass gasification business concepts
Peter J. Ince; Ted Bilek; Mark A. Dietenberger
2011-01-01
Biomass gasification is an approach to producing energy and/or biofuels that could be integrated into existing forest product production facilities, particularly at pulp mills. Existing process heat and power loads tend to favor integration at existing pulp mills. This paper describes a generic modeling system for evaluating integrated biomass gasification business...
Variational path integral molecular dynamics study of a water molecule
NASA Astrophysics Data System (ADS)
Miura, Shinichi
2013-08-01
In the present study, a variational path integral molecular dynamics method developed by the author [Chem. Phys. Lett. 482, 165 (2009)] is applied to a water molecule on the adiabatic potential energy surface. The method numerically generates an exact wavefunction using a trial wavefunction of the target system. It has been shown that even if a poor trial wavefunction is employed, the exact quantum distribution is numerically extracted, demonstrating the robustness of the variational path integral method.
Quantum tunneling splittings from path-integral molecular dynamics
NASA Astrophysics Data System (ADS)
Mátyus, Edit; Wales, David J.; Althorpe, Stuart C.
2016-03-01
We illustrate how path-integral molecular dynamics can be used to calculate ground-state tunnelling splittings in molecules or clusters. The method obtains the splittings from ratios of density matrix elements between the degenerate wells connected by the tunnelling. We propose a simple thermodynamic integration scheme for evaluating these elements. Numerical tests on fully dimensional malonaldehyde yield tunnelling splittings in good overall agreement with the results of diffusion Monte Carlo calculations.
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.
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
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.
USDA-ARS?s Scientific Manuscript database
Spatio-temporal variability of soil moisture (') is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time ' monitoring methods. This restricted the comprehensive and intensive examination of ' dynamic...
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
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
Exploring a Dynamic Model of Trust Management Presentation
2013-08-01
Integrity (ABI) • Parsimonious foundation of trustworthiness indicators (Mayer et al., 1995) – Ability: that group of skills, competencies , and...trustworthiness indicators in the dynamic trust model [Mayer, 1995] • Three factors in the dynamic trust model: – Ability ( competence ), Benevolence...are while you are making the judgment – By culture e.g. individualistic vs. collectivistic cultural influences – competence vs. benevolence
An Instructional Model for Integrating the Calculator.
ERIC Educational Resources Information Center
Berlin, Donna F.; White, Arthur L.
1987-01-01
The design, selection, and organization of instructional materials that integrate calculators are described in relation to a model based on movement and representational level. Instructional resources and advantages of the model are described. (MNS)
Low level constraints on dynamic contour path integration.
Hall, Sophie; Bourke, Patrick; Guo, Kun
2014-01-01
Contour integration is a fundamental visual process. The constraints on integrating discrete contour elements and the associated neural mechanisms have typically been investigated using static contour paths. However, in our dynamic natural environment objects and scenes vary over space and time. With the aim of investigating the parameters affecting spatiotemporal contour path integration, we measured human contrast detection performance of a briefly presented foveal target embedded in dynamic collinear stimulus sequences (comprising five short 'predictor' bars appearing consecutively towards the fovea, followed by the 'target' bar) in four experiments. The data showed that participants' target detection performance was relatively unchanged when individual contour elements were separated by up to 2° spatial gap or 200 ms temporal gap. Randomising the luminance contrast or colour of the predictors, on the other hand, had similar detrimental effect on grouping dynamic contour path and subsequent target detection performance. Randomising the orientation of the predictors reduced target detection performance greater than introducing misalignment relative to the contour path. The results suggest that the visual system integrates dynamic path elements to bias target detection even when the continuity of path is disrupted in terms of spatial (2°), temporal (200 ms), colour (over 10 colours) and luminance (-25% to 25%) information. We discuss how the findings can be largely reconciled within the functioning of V1 horizontal connections.
USDA-ARS?s Scientific Manuscript database
AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic and water quality (H/WQ) simulation components under the Java Connection Framework (JCF) and the Object Modeling System (OMS) environmental modeling framework. AgES-W is implicitly scala...
Modeling network dynamics: the lac operon, a case study.
Vilar, José M G; Guet, Călin C; Leibler, Stanislas
2003-05-12
We use the lac operon in Escherichia coli as a prototype system to illustrate the current state, applicability, and limitations of modeling the dynamics of cellular networks. We integrate three different levels of description (molecular, cellular, and that of cell population) into a single model, which seems to capture many experimental aspects of the system.
Modeling Catastrophic Barrier Island Dynamics
NASA Astrophysics Data System (ADS)
Whitley, J. W.; McNamara, D.
2012-12-01
Barrier islands, thin strips of sand lying parallel to the mainland coastline, along the U.S. Atlantic and Gulf Coasts appear to have maintained their form for thousands of years in the face of rising sea level. The mechanisms that allow barrier islands to remain robust are transport of sediment from the ocean side of barriers to the top and backside during storms, termed island overwash, and the growth and alongshore propagation of tidal deltas near barrier island inlets. Dynamically these processes provide the necessary feedbacks to maintain a barrier island in an attractor that withstands rising sea level within a phase space of barrier island geometrical characteristics. Current barrier island configurations along the Atlantic and Gulf coasts exist among a wide range of storm climate and underlying geologic conditions and therefore the environment that forces overwash and tidal delta dynamics varies considerably. It has been suggested that barrier islands in certain locations such as those between Avon and Buxton (losing 76% of island width since 1852) and Chandeleur islands (losing 85% of its surface area since 2005) along the Atlantic and Gulf coasts, respectively, may be subject to a catastrophic shift in barrier island attractor states - more numerous inlets cutting barriers in some locations and the complete disappearance of barrier islands in other locations. In contrast to common models for barrier islands that neglect storm dynamics and often only consider cross-shore response, we use an alongshore extended model for barrier island dynamics including beach erosion, island overwash and inlet cutting during storms, and beach accretion, tidal delta growth and dune and vegetation growth between storms to explore the response of barrier islands to a wide range of environmental forcing. Results will be presented that show how barrier island attractor states are altered with variations in the rate of sea level rise, storminess, and underlying geology. We will
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
NASA Astrophysics Data System (ADS)
Minary, Peter; Martyna, Glenn J.; Tuckerman, Mark E.
2003-02-01
In this paper (Paper I) and a companion paper (Paper II), novel new algorithms and applications of the isokinetic ensemble as generated by Gauss' principle of least constraint, pioneered for use with molecular dynamics 20 years ago, are presented for biophysical, path integral, and Car-Parrinello based ab initio molecular dynamics. In Paper I, a new "extended system" version of the isokinetic equations of motion that overcomes the ergodicity problems inherent in the standard approach, is developed using a new theory of non-Hamiltonian phase space analysis [M. E. Tuckerman et al., Europhys. Lett. 45, 149 (1999); J. Chem. Phys. 115, 1678 (2001)]. Reversible multiple time step integrations schemes for the isokinetic methods, first presented by Zhang [J. Chem. Phys. 106, 6102 (1997)] are reviewed. Next, holonomic constraints are incorporated into the isokinetic methodology for use in fast efficient biomolecular simulation studies. Model and realistic examples are presented in order to evaluate, critically, the performance of the new isokinetic molecular dynamic schemes. Comparisons are made to the, now standard, canonical dynamics method, Nosé-Hoover chain dynamics [G. J. Martyna et al., J. Chem. Phys. 97, 2635 (1992)]. The new isokinetic techniques are found to yield more efficient sampling than the Nosé-Hoover chain method in both path integral molecular dynamics and biophysical molecular dynamics calculations. In Paper II, the use of isokinetic methods in Car-Parrinello based ab initio molecular dynamics calculations is presented.
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.
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.
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.
Integrative modelling for One Health: pattern, process and participation
Redding, D. W.; Wood, J. L. N.
2017-01-01
This paper argues for an integrative modelling approach for understanding zoonoses disease dynamics, combining process, pattern and participatory models. Each type of modelling provides important insights, but all are limited. Combining these in a ‘3P’ approach offers the opportunity for a productive conversation between modelling efforts, contributing to a ‘One Health’ agenda. The aim is not to come up with a composite model, but seek synergies between perspectives, encouraging cross-disciplinary interactions. We illustrate our argument with cases from Africa, and in particular from our work on Ebola virus and Lassa fever virus. Combining process-based compartmental models with macroecological data offers a spatial perspective on potential disease impacts. However, without insights from the ground, the ‘black box’ of transmission dynamics, so crucial to model assumptions, may not be fully understood. We show how participatory modelling and ethnographic research of Ebola and Lassa fever can reveal social roles, unsafe practices, mobility and movement and temporal changes in livelihoods. Together with longer-term dynamics of change in societies and ecologies, all can be important in explaining disease transmission, and provide important complementary insights to other modelling efforts. An integrative modelling approach therefore can offer help to improve disease control efforts and public health responses. This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’. PMID:28584172
Integrative modelling for One Health: pattern, process and participation.
Scoones, I; Jones, K; Lo Iacono, G; Redding, D W; Wilkinson, A; Wood, J L N
2017-07-19
This paper argues for an integrative modelling approach for understanding zoonoses disease dynamics, combining process, pattern and participatory models. Each type of modelling provides important insights, but all are limited. Combining these in a '3P' approach offers the opportunity for a productive conversation between modelling efforts, contributing to a 'One Health' agenda. The aim is not to come up with a composite model, but seek synergies between perspectives, encouraging cross-disciplinary interactions. We illustrate our argument with cases from Africa, and in particular from our work on Ebola virus and Lassa fever virus. Combining process-based compartmental models with macroecological data offers a spatial perspective on potential disease impacts. However, without insights from the ground, the 'black box' of transmission dynamics, so crucial to model assumptions, may not be fully understood. We show how participatory modelling and ethnographic research of Ebola and Lassa fever can reveal social roles, unsafe practices, mobility and movement and temporal changes in livelihoods. Together with longer-term dynamics of change in societies and ecologies, all can be important in explaining disease transmission, and provide important complementary insights to other modelling efforts. An integrative modelling approach therefore can offer help to improve disease control efforts and public health responses.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'. © 2017 The Authors.
Modeling the Dynamics of Snags.
Morrison, Michael L; Raphael, Martin G
1993-05-01
Many wildlife species required standing dead trees (i.e., snags) as part of their habitat. Therefore, the ability to predict future density, distribution, and condition of snags can assist resource managers in making land-use decisions. Here we present methods for modeling the dynamics of snags using data from a 10-yr study on the rates of decay, falling, and recruitment of snags on burned and unburned plots in the Sierra Nevada, California. Snags (all species) in advanced stages of decay usually fell within 5 yr, and snags created by fire decayed rapidly and fell quicker (within 10 yr) than those on unburned plots. Pine (Pinus spp.) snags decayed more rapidly than fir (Abies spp.). Although there was an overall net increase in snag density on unburned plots, most of this increase was in the smaller (>13-38 cm diameter at breast height [dbh]) size classes; there was a net decrease in the larger (>38 cm dbh) snags preferred by many birds for nesting and feeding. Overall, snags remained standing the longest that were larger in diameter, shorter in height, less decayed, fir rather than pine, and lacking tops. A Leslie matrix model of snag dynamics predicted changes in snag decay and density only when adjusted for the specific environmental factors(s) causing initial tree mortality. Many snags are created by episodic events, such as fire, disease, drought, and insects. Models of snag dynamics must include the species and condition of trees becoming snags, as well as the factor(s) causing the tree to die. Forest managers must consider this episodic creation of snags when developing snag-management guidelines, and when planning tree-salvage programs based on short-term inventories.
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.
Mobile Technology Integrated Pedagogical Model
ERIC Educational Resources Information Center
Khan, Arshia
2014-01-01
Integrated curricula and experiential learning are the main ingredients to the recipe to improve student learning in higher education. In the academic computer science world it is mostly assumed that this experiential learning takes place at a business as an internship experience. The intent of this paper is to schism the traditional understanding…
MOS integrated circuit fault modeling
NASA Technical Reports Server (NTRS)
Sievers, M.
1985-01-01
Three digital simulation techniques for MOS integrated circuit faults were examined. These techniques embody a hierarchy of complexity bracketing the range of simulation levels. The digital approaches are: transistor-level, connector-switch-attenuator level, and gate level. The advantages and disadvantages are discussed. Failure characteristics are also described.
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.
Mathematical Model of Porous Medium Dynamics
NASA Astrophysics Data System (ADS)
Gerschuk, Peotr; Sapozhnikov, Anatoly
1999-06-01
Semiempirical model describing porous material strains under pulse mechanical and thermal loadings is proposed. Porous medium is considered as continuous one but with special form of pressure dependence upon strain. This model takes into account principal features of porous materials behavior which can be observed when the material is strained in dynamic and static experiments ( non-reversibility of large strains, nonconvexity of loading curve). Elastoplastic properties of porous medium, its damages when it is strained and dynamic fracture are also taken into account. Dispersion of unidirectional motion caused by medium heterogeneity (porousness) is taken into acount by introducing the physical viscosity depending upon pores size. It is supposed that at every moment of time pores are in equilibrium with pressure i.e. kinetic of pores collapse is not taken into account. The model is presented by the system of differential equations connecting pressure and energy of porous medium with its strain. These equations close system of equations of motion and continuity which then is integrated numerically. The proposed model has been tested on carbon materials and porous copper . Results of calculation of these materials shock compressing are in satisfactory agreement with experimental data. Results of calculation of thin plate with porous copper layer collision are given as an illustration.
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.
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.
Eigenvalue dynamics for multimatrix models
NASA Astrophysics Data System (ADS)
de Mello Koch, Robert; Gossman, David; Nkumane, Lwazi; Tribelhorn, Laila
2017-07-01
By performing explicit computations of correlation functions, we find evidence that there is a sector of the two matrix model defined by the S U (2 ) sector of N =4 super Yang-Mills theory that can be reduced to eigenvalue dynamics. There is an interesting generalization of the usual Van der Monde determinant that plays a role. The observables we study are the Bogomol'nyi-Prasad-Sommerfield operators of the S U (2 ) sector and include traces of products of both matrices, which are genuine multimatrix observables. These operators are associated with supergravity solutions of string theory.
NASA Astrophysics Data System (ADS)
Roelvink, J. A.; Reyns, J.; McLachlan, R. L.; Eidam, E.; Liu, P.; Ogston, A. S.; Vo, T. Q.; Wackerman, C.
2016-02-01
This paper aims at connecting sparse in-situ and remote-sensed observations using 3D modeling in order to create a temporally and spatially more complete picture of the 3D hydrodynamic and sediment processes in the Hau river branch of the Mekong delta estuary, Cu Lau Dung island and the shelf. A Delft3D model was set up with a domain extending upstream to 155 km from Cu Lau Dung and approx 150 km alongshore towards the souhwest. The model was set up with a deliberately coarse grid to be able to quickly assess the dominant processes. Since the underlying bathymetry data is much finer it is relatively straightforward to refine the model according to needs. The model has 10 equidistant sigma layers and can run, including salinity and sediment processes, a spring-neap cycle in little more than an hour on a laptop, making it very suitable for a first assessment of processes and sensitivities to input parameters and forcing conditions. The model was used successfully during the final workshop of the ONR Mekong delta programme to facilitate the connection between modeling and observations. Resulting collaborative results will be presented at the conference, connecting ADCP data on fixed moorings, ADCP and CTD profiles from ships in Bassac and on the shelf, with RS images of SSC. The modeling will be used to gain understanding on the sediment exchange processes between the tidal river and estuary; between the different branches of the Song Hau; between the channels and the shelf and between the outflow plume and the shelf bottom. Detailed simulations over the periods of the fieldwork will be used for model validation, and longer-term simulations covering full years will be used to provide a spatio-temporal context and first attempts at extrapolating towards geological scales. Acknowledgements This study was funded by ONR under Grant N00014-12-1-0433 Modeling the Mekong Delta at three different scales
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
McCollum, Gin; Roberts, Patrick D
2004-12-01
Natural, everyday sensorimotor behaviors, such as rising from sitting, typically have an intrinsic organization of several levels of analysis. Taking this intrinsic organization as key to understanding neural dynamics is neither a top-down nor a bottom-up approach, but rather a meshing of multiple centers and levels of analysis. Motor control requires body dynamics that are consistent with physical dynamics, besides the more microscopic levels of neural dynamics. The dynamics of separate movements have been investigated as if the ends can be capped off, separated from the rest of the individual's life. Is this dynamically correct? Even chaotic behavior is deterministic. However, the mathematics of nonlinear oscillations is not all of dynamics. This paper relates Bloch's dynamical theorem to the modular, conditional approach to sensorimotor and other neural functioning. Bloch's dynamical theorem lays a foundation for the piecewise study of structurally accurate dynamics in theoretical neurobiology. Piecewise studies can be used as a modeling option complementary to the methods of nonlinear oscillator dynamics. By applying Bloch's theorem, dynamics of movements analyzed piecewise can be extended into a smooth flow on any manifold, either as a whole or conditionally. Conditional dynamics makes dynamical modeling options explicit, often depending on what variables the organism can control, and allows one to take different modeling options at different junctures in analyzing the same phenomenon. For example, this approach allows the study of complex motor control problems to be reduced to modular constructions using singularities and flow lines. Dynamical contingencies are expressed using the mathematics of ordered structures. This paper presents Bloch's dynamical theorem and its relevance to model construction in theoretical neurobiology. Specific examples, integrated into physiological and behavioral context, are cited from the literature.
Open source integrated modeling environment Delta Shell
NASA Astrophysics Data System (ADS)
Donchyts, G.; Baart, F.; Jagers, B.; van Putten, H.
2012-04-01
In the last decade, integrated modelling has become a very popular topic in environmental modelling since it helps solving problems, which is difficult to model using a single model. However, managing complexity of integrated models and minimizing time required for their setup remains a challenging task. The integrated modelling environment Delta Shell simplifies this task. The software components of Delta Shell are easy to reuse separately from each other as well as a part of integrated environment that can run in a command-line or a graphical user interface mode. The most components of the Delta Shell are developed using C# programming language and include libraries used to define, save and visualize various scientific data structures as well as coupled model configurations. Here we present two examples showing how Delta Shell simplifies process of setting up integrated models from the end user and developer perspectives. The first example shows coupling of a rainfall-runoff, a river flow and a run-time control models. The second example shows how coastal morphological database integrates with the coastal morphological model (XBeach) and a custom nourishment designer. Delta Shell is also available as open-source software released under LGPL license and accessible via http://oss.deltares.nl.
Bayesian Estimation of Categorical Dynamic Factor Models
ERIC Educational Resources Information Center
Zhang, Zhiyong; Nesselroade, John R.
2007-01-01
Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…
Bayesian Estimation of Categorical Dynamic Factor Models
ERIC Educational Resources Information Center
Zhang, Zhiyong; Nesselroade, John R.
2007-01-01
Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…
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 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.
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.
Delta Shell: Integrated Modeling by Example
NASA Astrophysics Data System (ADS)
Donchyts, G.; Jagers, B.; Baart, F.; Geer, P. V.
2011-12-01
We present the integrated modeling environment Delta Shell. It supports the full workflow of integrated environmental modeling: setup, configuration, simulation, analysis and reporting of results. Many components of the environment can be reused independently, allowing development of scientific, geospatial and other applications focused on data analysis, editing, visualization and storage. One of the unique features is that the Delta Shell environment integrates models from many different fields, such as hydrodynamics, hydrology, morphology, ecology, water quality, geospatial and decision support systems. This integration is possible due to flexible general data types, lightweight model coupling framework, the plugin system and the inclusion of a number of high quality open source components. Here we will use the open source morphological model XBeach as an example showing how to integrate models into the Delta Shell environment. Integration of XBeach adds a graphical interface which can be used to make testing coastal safety for complicated coastal areas easier. By using this example, we give an overview of the modeling framework and its possibilities. To increase the usability, the model is integrated with a coastal profile data set covering the whole coast of the Netherlands. This gives the end user a system to easily use the model for scanning the safety of the Dutch coast. The reuse of the components of the environment individually or combined is encouraged. They are available as separate components and have minimal or no dependencies on other components. This includes libraries to work with scientific multidimensional data, geospatial data (in particular geospatial coverages: values of some quantities defined on a spatial domain), editors, visualisation of time-dependent data and the modeling framework (projects, data linking, workflow management, model integration). Most components and the XBeach example are available as open source.
Characterizing and modeling citation dynamics.
Eom, Young-Ho; Fortunato, Santo
2011-01-01
Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well.
Characterizing and Modeling Citation Dynamics
Eom, Young-Ho; Fortunato, Santo
2011-01-01
Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well. PMID:21966387
Dynamical model for competing opinions
NASA Astrophysics Data System (ADS)
Souza, S. R.; Gonçalves, S.
2012-05-01
We propose an opinion model based on agents located at the vertices of a regular lattice. Each agent has an independent opinion (among an arbitrary, but fixed, number of choices) and its own degree of conviction. The latter changes every time two agents which have different opinions interact with each other. The dynamics leads to size distributions of clusters (made up of agents which have the same opinion and are located at contiguous spatial positions) which follow a power law, as long as the range of the interaction between the agents is not too short; i.e., the system self-organizes into a critical state. Short range interactions lead to an exponential cutoff in the size distribution and to spatial correlations which cause agents which have the same opinion to be closely grouped. When the diversity of opinions is restricted to two, a nonconsensus dynamic is observed, with unequal population fractions, whereas consensus is reached if the agents are also allowed to interact with those located far from them. The individual agents' convictions, the preestablished interaction range, and the locality of the interaction between a pair of agents (their neighborhood has no effect on the interaction) are the main characteristics which distinguish our model from previous ones.
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.
Numerical integration and optimization of motions for multibody dynamic systems
NASA Astrophysics Data System (ADS)
Aguilar Mayans, Joan
This thesis considers the optimization and simulation of motions involving rigid body systems. It does so in three distinct parts, with the following topics: optimization and analysis of human high-diving motions, efficient numerical integration of rigid body dynamics with contacts, and motion optimization of a two-link robot arm using Finite-Time Lyapunov Analysis. The first part introduces the concept of eigenpostures, which we use to simulate and analyze human high-diving motions. Eigenpostures are used in two different ways: first, to reduce the complexity of the optimal control problem that we solve to obtain such motions, and second, to generate an eigenposture space to which we map existing real world motions to better analyze them. The benefits of using eigenpostures are showcased through different examples. The second part reviews an extensive list of integration algorithms used for the integration of rigid body dynamics. We analyze the accuracy and stability of the different integrators in the three-dimensional space and the rotation space SO(3). Integrators with an accuracy higher than first order perform more efficiently than integrators with first order accuracy, even in the presence of contacts. The third part uses Finite-time Lyapunov Analysis to optimize motions for a two-link robot arm. Finite-Time Lyapunov Analysis diagnoses the presence of time-scale separation in the dynamics of the optimized motion and provides the information and methodology for obtaining an accurate approximation to the optimal solution, avoiding the complications that timescale separation causes for alternative solution methods.
Integrating expert systems with dynamic programming in generation expansion planning
David, A.K.; Rong-da, Z.
1989-08-01
Interactive software developed for integrating engineering experience and judgement from the planning dept. with a powerful mathematic optimisation method is described. The excessive size of the state space generated by conventional multidimensional dynamic programming is reduced to real world engineering proportions by rule based procedures for implementing Windows in state space and Controls in policy space. Project Frames describing generation options and State Frames describing future conditions of the system are established and manipulated by rules. Dynamic programming simultaneously tracks a feasible set of sub-optimal scenarios. The program is interactive and is written in PROLOG with numerically intensive portions in C.
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.
The predictive integration method for dynamics of infrequent events
NASA Astrophysics Data System (ADS)
Cubuk, Ekin; Waterland, Amos; Kaxiras, Efthimios
2012-02-01
With the increasing prominence and availability of multi-processor computers, recasting problems in a form amenable to parallel solution is becoming a critical step in effective scientific computation. We present a method for parallelizing molecular dynamics simulations in time scale, by using predictive integration. Our method is closely related to Voter's parallel replica method, but goes beyond that approach in that it involves speculatively initializing processors in more than one basin. Our predictive integration method requires predicting possible future configurations while it does not suffer from restrictions due to correlation time after transitions between basins.
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.
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…
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…
Dynamic Functional Segregation and Integration in Human Brain Network During Complex Tasks.
Ren, Shen; Li, Junhua; Taya, Fumihiko; deSouza, Joshua; Thakor, Nitish; Bezerianos, Anastasios
2016-09-09
The analysis of the topology and organisation of brain networks is known to greatly benefit from network measures in graph theory. However, to evaluate dynamic changes of brain functional connectivity, more sophisticated quantitative metrics characterising temporal evolution of brain topological features are required. To simplify conversion of time-varying brain connectivity to a static graph representation is straightforward but the procedure loses temporal information that could be critical in understanding the brain functions. To extend the understandings of functional segregation and integration to a dynamic fashion, we recommend dynamic graph metrics to characterise temporal changes of topological features of brain networks. This study investigated functional segregation and integration of brain networks over time by dynamic graph metrics derived from EEG signals during an experimental protocol: performance of complex flight simulation tasks with multiple levels of difficulty. We modelled time-varying brain functional connectivity as multilayer networks, in which each layer models brain connectivity at time window t + t. Dynamic graph metrics were calculated to quantify temporal and topological properties of the network. Results show that brain networks under the performance of complex tasks reveal a dynamic small-world architecture with a number of frequently connected nodes or hubs, which supports the balance of information segregation and integration in brain over time. The results also show that greater cognitive workloads caused by more difficult tasks induced a more globally efficient but less clustered dynamic small-world functional network. Our study illustrates that task-related changes of functional brain network segregation and integration can be characterised by dynamic graph metrics.
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.
Mathematical modeling of microtubule dynamics: insights into physiology and disease.
Buxton, Gavin A; Siedlak, Sandra L; Perry, George; Smith, Mark A
2010-12-01
Computer models of microtubule dynamics have provided the basis for many of the theories on the cellular mechanics of the microtubules, their polymerization kinetics, and the diffusion of tubulin and tau. In the three-dimensional model presented here, we include the effects of tau concentration and the hydrolysis of GTP-tubulin to GDP-tubulin and observe the emergence of microtubule dynamic instability. This integrated approach simulates the essential physics of microtubule dynamics in a cellular environment. The model captures the structure of the microtubules as they undergo steady state dynamic instabilities in this simplified geometry, and also yields the average number, length, and cap size of the microtubules. The model achieves realistic geometries and simulates cellular structures found in degenerating neurons in disease states such as Alzheimer disease. Further, this model can be used to simulate microtubule changes following the addition of antimitotic drugs which have recently attracted attention as chemotherapeutic agents.
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.
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.
An integrated physical and biological model for anaerobic lagoons.
Wu, Binxin; Chen, Zhenbin
2011-04-01
A computational fluid dynamics (CFD) model that integrates physical and biological processes for anaerobic lagoons is presented. In the model development, turbulence is represented using a transition k-ω model, heat conduction and solar radiation are included in the thermal model, biological oxygen demand (BOD) reduction is characterized by first-order kinetics, and methane yield rate is expressed as a linear function of temperature. A test of the model applicability is conducted in a covered lagoon digester operated under tropical climate conditions. The commercial CFD software, ANSYS-Fluent, is employed to solve the integrated model. The simulation procedures include solving fluid flow and heat transfer, predicting local resident time based on the converged flow fields, and calculating the BOD reduction and methane production. The simulated results show that monthly methane production varies insignificantly, but the time to achieve a 99% BOD reduction in January is much longer than that in July.
Chen, H; Dolly, S; Anastasio, M; Li, H; Wooten, H; Gay, H; Mutic, S; Thorstad, W; Li, H; Victoria, J; Dempsey, J; Ruan, S; Low, D
2015-06-15
Purpose: In-treatment dynamic cine images, provided by the first commercially available MRI-guided radiotherapy system, allow physicians to observe intrafractional motion of head and neck (H&N) internal structures. Nevertheless, high anatomical complexity and relatively poor cine image contrast/resolution have complicated automatic intrafractional motion evaluation. We proposed an integrated model-based approach to automatically delineate and analyze moving structures from on-board cine images. Methods: The H&N upper airway, a complex and highly deformable region wherein severe internal motion often occurs, was selected as the target-to-be-tracked. To reliably capture its motion, a hierarchical structure model containing three statistical shapes (face, face-jaw, and face-jaw-palate) was first built from a set of manually delineated shapes using principal component analysis. An integrated model-fitting algorithm was then employed to align the statistical shapes to the first to-be-detected cine frame, and multi-feature level-set contour propagation was performed to identify the airway shape change in the remaining frames. Ninety sagittal cine MR image sets, acquired from three H&N cancer patients, were utilized to demonstrate this approach. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 20 randomly selected images from each patient. The resulting dice similarity coefficient (93.28+/−1.46 %) and margin error (0.49+/−0.12 mm) showed good agreement with the manual results. Intrafractional displacements of anterior, posterior, inferior, and superior airway boundaries were observed, with values of 2.62+/−2.92, 1.78+/−1.43, 3.51+/−3.99, and 0.68+/−0.89 mm, respectively. The H&N airway motion was found to vary across directions, fractions, and patients, and highly correlated with patients’ respiratory frequency. Conclusion: We proposed the integrated computational approach, which for the first
Dynamical Modeling of Mars' Paleoclimate
NASA Technical Reports Server (NTRS)
Richardson, Mark I.
2004-01-01
This report summarizes work undertaken under a one-year grant from the NASA Mars Fundamental Research Program. The goal of the project was to initiate studies of the response of the Martian climate to changes in planetary obliquity and orbital elements. This work was undertaken with a three-dimensional numerical climate model based on the Geophysical Fluid Dynamics Laboratory (GFDL) Skyhi General Circulation Model (GCM). The Mars GCM code was adapted to simulate various obliquity and orbital parameter states. Using a version of the model with a basic water cycle (ice caps, vapor, and clouds), we examined changes in atmospheric water abundances and in the distribution of water ice sheets on the surface. This work resulted in a paper published in the Journal of Geophysical Research - Planets. In addition, the project saw the initial incorporation of a regolith water transport and storage scheme into the model. This scheme allows for interaction between water in the pores of the near subsurface (<3m) and the atmosphere. This work was not complete by the end of the one-year grant, but is now continuing within the auspices of a three-year grant of the same title awarded by the Mars Fundamental Research Program in late 2003.
Dynamical model of surrogate reactions
Aritomo, Y.; Chiba, S.; Nishio, K.
2011-08-15
A new dynamical model is developed to describe the whole process of surrogate reactions: Transfer of several nucleons at an initial stage, thermal equilibration of residues leading to washing out of shell effects, and decay of populated compound nuclei are treated in a unified framework. Multidimensional Langevin equations are employed to describe time evolution of collective coordinates with a time-dependent potential energy surface corresponding to different stages of surrogate reactions. The new model is capable of calculating spin distributions of the compound nuclei, one of the most important quantities in the surrogate technique. Furthermore, various observables of surrogate reactions can be calculated, for example, energy and angular distribution of ejectile and mass distributions of fission fragments. These features are important to assess validity of the proposed model itself, to understand mechanisms of the surrogate reactions, and to determine unknown parameters of the model. It is found that spin distributions of compound nuclei produced in {sup 18}O+{sup 238}U{yields}{sup 16}O+{sup 240}*U and {sup 18}O+{sup 236}U{yields}{sup 16}O+{sup 238}*U reactions are equivalent and much less than 10({h_bar}/2{pi}) and therefore satisfy conditions proposed by Chiba and Iwamoto [Phys. Rev. C 81, 044604 (2010)] if they are used as a pair in the surrogate ratio method.
Dynamical Modeling of Mars' Paleoclimate
NASA Technical Reports Server (NTRS)
Richardson, Mark I.
2004-01-01
This report summarizes work undertaken under a one-year grant from the NASA Mars Fundamental Research Program. The goal of the project was to initiate studies of the response of the Martian climate to changes in planetary obliquity and orbital elements. This work was undertaken with a three-dimensional numerical climate model based on the Geophysical Fluid Dynamics Laboratory (GFDL) Skyhi General Circulation Model (GCM). The Mars GCM code was adapted to simulate various obliquity and orbital parameter states. Using a version of the model with a basic water cycle (ice caps, vapor, and clouds), we examined changes in atmospheric water abundances and in the distribution of water ice sheets on the surface. This work resulted in a paper published in the Journal of Geophysical Research - Planets. In addition, the project saw the initial incorporation of a regolith water transport and storage scheme into the model. This scheme allows for interaction between water in the pores of the near subsurface (<3m) and the atmosphere. This work was not complete by the end of the one-year grant, but is now continuing within the auspices of a three-year grant of the same title awarded by the Mars Fundamental Research Program in late 2003.
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.
Firsov, Alexander A.; Lubenko, Irene Y.; Portnoy, Yury A.; Zinner, Stephen H.; Vostrov, Sergey N.
2001-01-01
Most integral endpoints of the antimicrobial effect are determined over an arbitrarily chosen time period, such as the dosing interval (τ), regardless of the actual effect duration. Unlike the τ-related endpoints, the intensity of the antimicrobial effect (IE) does consider its duration—from time zero to the time when bacterial counts on the regrowth curve achieve the same maximal numbers as in the absence of the antimicrobial. To examine the possible impact of this fundamental difference on the relationships of the antimicrobial effect to the ratio of the area under the concentration-time curve (AUC) to the MIC, a clinical isolate of Staphylococcus aureus was exposed to simulated gemifloxacin pharmacokinetics over a 40-fold range of AUC/MIC ratios, from 11 to 466 h. In each run, IE and four τ-related endpoints, including the area under the time-kill curve (AUBC), the area above the curve (AAC), the area between the control growth and time-kill curves (ABBC), and the ABBC related to the area under the control growth curve (AUGC), were calculated for τ = 24 h. Unlike the IE, which displayed pseudolinear relationships with the AUC/MIC ratio; each τ-related endpoint showed a distinct saturation at potentially therapeutic AUC/MIC ratios (116 to 466 h) when the antimicrobial effect persisted longer than τ. This saturation results from the underestimation of the true effect and may be eliminated if ABBC, AAC, and AUBC (but not AUGC) are modified and determined in the same manner as the IE to consider the actual effect duration. These data suggest a marginal value of the τ-related endpoints as indices of the total antimicrobial effect. Since all of them respond to AUC/MIC ratio changes less than the IE, the latter is preferable in comparative pharmacodynamic studies. PMID:11181382
The Integrated Model Development Environment
1994-02-01
IMDE)," was designed to support the Productivity Improvements in Simulation Modeling (PRISM) project. The objective of PRISM is to enhance the Air...Office of Primary Responsibility OT&E Operational Test and Evaluation PRISM Productivity Improvements in Simulation Modeling SAFORs Semi-Automated Forces
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.