Rainfall runoff modelling of the Upper Ganga and Brahmaputra basins using PERSiST.
Futter, M N; Whitehead, P G; Sarkar, S; Rodda, H; Crossman, J
2015-06-01
There are ongoing discussions about the appropriate level of complexity and sources of uncertainty in rainfall runoff models. Simulations for operational hydrology, flood forecasting or nutrient transport all warrant different levels of complexity in the modelling approach. More complex model structures are appropriate for simulations of land-cover dependent nutrient transport while more parsimonious model structures may be adequate for runoff simulation. The appropriate level of complexity is also dependent on data availability. Here, we use PERSiST; a simple, semi-distributed dynamic rainfall-runoff modelling toolkit to simulate flows in the Upper Ganges and Brahmaputra rivers. We present two sets of simulations driven by single time series of daily precipitation and temperature using simple (A) and complex (B) model structures based on uniform and hydrochemically relevant land covers respectively. Models were compared based on ensembles of Bayesian Information Criterion (BIC) statistics. Equifinality was observed for parameters but not for model structures. Model performance was better for the more complex (B) structural representations than for parsimonious model structures. The results show that structural uncertainty is more important than parameter uncertainty. The ensembles of BIC statistics suggested that neither structural representation was preferable in a statistical sense. Simulations presented here confirm that relatively simple models with limited data requirements can be used to credibly simulate flows and water balance components needed for nutrient flux modelling in large, data-poor basins.
NASA Technical Reports Server (NTRS)
Jones, Lisa E. (Technical Monitor); Stockwell, Alan E.
2005-01-01
LS-DYNA simulations were conducted to study the influence of model complexity on the response of a typical Reinforced Carbon-Carbon (RCC) panel to a foam impact at a location approximately midway between the ribs. A structural model comprised of Panels 10, 11, and TSeal 11 was chosen as the baseline model for the study. A simulation was conducted with foam striking Panel 10 at Location 4 at an alpha angle of 10 degrees, with an impact velocity of 1000 ft/sec. A second simulation was conducted after removing Panel 11 from the model, and a third simulation was conducted after removing both Panel 11 and T-Seal 11. All three simulations showed approximately the same response for Panel 10, and the simplified simulation model containing only Panel 10 was shown to be significantly less expensive to execute than the other two more complex models.
A program code generator for multiphysics biological simulation using markup languages.
Amano, Akira; Kawabata, Masanari; Yamashita, Yoshiharu; Rusty Punzalan, Florencio; Shimayoshi, Takao; Kuwabara, Hiroaki; Kunieda, Yoshitoshi
2012-01-01
To cope with the complexity of the biological function simulation models, model representation with description language is becoming popular. However, simulation software itself becomes complex in these environment, thus, it is difficult to modify the simulation conditions, target computation resources or calculation methods. In the complex biological function simulation software, there are 1) model equations, 2) boundary conditions and 3) calculation schemes. Use of description model file is useful for first point and partly second point, however, third point is difficult to handle for various calculation schemes which is required for simulation models constructed from two or more elementary models. We introduce a simulation software generation system which use description language based description of coupling calculation scheme together with cell model description file. By using this software, we can easily generate biological simulation code with variety of coupling calculation schemes. To show the efficiency of our system, example of coupling calculation scheme with three elementary models are shown.
STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python
Wils, Stefan; Schutter, Erik De
2008-01-01
We describe how the use of the Python language improved the user interface of the program STEPS. STEPS is a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process that consists of many phases. Initial versions of STEPS relied on a static input format that did not cleanly separate these phases, limiting modelers in how they could control the simulation and becoming increasingly complex as new features and new simulation algorithms were added. We solved all of these problems by tightly integrating STEPS with Python, using SWIG to expose our existing simulation code. PMID:19623245
Drewes, Rich; Zou, Quan; Goodman, Philip H
2009-01-01
Neuroscience modeling experiments often involve multiple complex neural network and cell model variants, complex input stimuli and input protocols, followed by complex data analysis. Coordinating all this complexity becomes a central difficulty for the experimenter. The Python programming language, along with its extensive library packages, has emerged as a leading "glue" tool for managing all sorts of complex programmatic tasks. This paper describes a toolkit called Brainlab, written in Python, that leverages Python's strengths for the task of managing the general complexity of neuroscience modeling experiments. Brainlab was also designed to overcome the major difficulties of working with the NCS (NeoCortical Simulator) environment in particular. Brainlab is an integrated model-building, experimentation, and data analysis environment for the powerful parallel spiking neural network simulator system NCS.
Drewes, Rich; Zou, Quan; Goodman, Philip H.
2008-01-01
Neuroscience modeling experiments often involve multiple complex neural network and cell model variants, complex input stimuli and input protocols, followed by complex data analysis. Coordinating all this complexity becomes a central difficulty for the experimenter. The Python programming language, along with its extensive library packages, has emerged as a leading “glue” tool for managing all sorts of complex programmatic tasks. This paper describes a toolkit called Brainlab, written in Python, that leverages Python's strengths for the task of managing the general complexity of neuroscience modeling experiments. Brainlab was also designed to overcome the major difficulties of working with the NCS (NeoCortical Simulator) environment in particular. Brainlab is an integrated model-building, experimentation, and data analysis environment for the powerful parallel spiking neural network simulator system NCS. PMID:19506707
Juckem, Paul F.; Clark, Brian R.; Feinstein, Daniel T.
2017-05-04
The U.S. Geological Survey, National Water-Quality Assessment seeks to map estimated intrinsic susceptibility of the glacial aquifer system of the conterminous United States. Improved understanding of the hydrogeologic characteristics that explain spatial patterns of intrinsic susceptibility, commonly inferred from estimates of groundwater age distributions, is sought so that methods used for the estimation process are properly equipped. An important step beyond identifying relevant hydrogeologic datasets, such as glacial geology maps, is to evaluate how incorporation of these resources into process-based models using differing levels of detail could affect resulting simulations of groundwater age distributions and, thus, estimates of intrinsic susceptibility.This report describes the construction and calibration of three groundwater-flow models of northeastern Wisconsin that were developed with differing levels of complexity to provide a framework for subsequent evaluations of the effects of process-based model complexity on estimations of groundwater age distributions for withdrawal wells and streams. Preliminary assessments, which focused on the effects of model complexity on simulated water levels and base flows in the glacial aquifer system, illustrate that simulation of vertical gradients using multiple model layers improves simulated heads more in low-permeability units than in high-permeability units. Moreover, simulation of heterogeneous hydraulic conductivity fields in coarse-grained and some fine-grained glacial materials produced a larger improvement in simulated water levels in the glacial aquifer system compared with simulation of uniform hydraulic conductivity within zones. The relation between base flows and model complexity was less clear; however, the relation generally seemed to follow a similar pattern as water levels. Although increased model complexity resulted in improved calibrations, future application of the models using simulated particle tracking is anticipated to evaluate if these model design considerations are similarly important for understanding the primary modeling objective - to simulate reasonable groundwater age distributions.
Simulating complex intracellular processes using object-oriented computational modelling.
Johnson, Colin G; Goldman, Jacki P; Gullick, William J
2004-11-01
The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.
NASA Astrophysics Data System (ADS)
Ma, Yulong; Liu, Heping
2017-12-01
Atmospheric flow over complex terrain, particularly recirculation flows, greatly influences wind-turbine siting, forest-fire behaviour, and trace-gas and pollutant dispersion. However, there is a large uncertainty in the simulation of flow over complex topography, which is attributable to the type of turbulence model, the subgrid-scale (SGS) turbulence parametrization, terrain-following coordinates, and numerical errors in finite-difference methods. Here, we upgrade the large-eddy simulation module within the Weather Research and Forecasting model by incorporating the immersed-boundary method into the module to improve simulations of the flow and recirculation over complex terrain. Simulations over the Bolund Hill indicate improved mean absolute speed-up errors with respect to previous studies, as well an improved simulation of the recirculation zone behind the escarpment of the hill. With regard to the SGS parametrization, the Lagrangian-averaged scale-dependent Smagorinsky model performs better than the classic Smagorinsky model in reproducing both velocity and turbulent kinetic energy. A finer grid resolution also improves the strength of the recirculation in flow simulations, with a higher horizontal grid resolution improving simulations just behind the escarpment, and a higher vertical grid resolution improving results on the lee side of the hill. Our modelling approach has broad applications for the simulation of atmospheric flows over complex topography.
Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C
2015-01-01
Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175
DOT National Transportation Integrated Search
2008-01-01
Computer simulations are often used in aviation studies. These simulation tools may require complex, high-fidelity aircraft models. Since many of the flight models used are third-party developed products, independent validation is desired prior to im...
NASA Astrophysics Data System (ADS)
Takemura, Kazuhiro; Guo, Hao; Sakuraba, Shun; Matubayasi, Nobuyuki; Kitao, Akio
2012-12-01
We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.
Takemura, Kazuhiro; Guo, Hao; Sakuraba, Shun; Matubayasi, Nobuyuki; Kitao, Akio
2012-12-07
We propose a method to evaluate binding free energy differences among distinct protein-protein complex model structures through all-atom molecular dynamics simulations in explicit water using the solution theory in the energy representation. Complex model structures are generated from a pair of monomeric structures using the rigid-body docking program ZDOCK. After structure refinement by side chain optimization and all-atom molecular dynamics simulations in explicit water, complex models are evaluated based on the sum of their conformational and solvation free energies, the latter calculated from the energy distribution functions obtained from relatively short molecular dynamics simulations of the complex in water and of pure water based on the solution theory in the energy representation. We examined protein-protein complex model structures of two protein-protein complex systems, bovine trypsin/CMTI-1 squash inhibitor (PDB ID: 1PPE) and RNase SA/barstar (PDB ID: 1AY7), for which both complex and monomer structures were determined experimentally. For each system, we calculated the energies for the crystal complex structure and twelve generated model structures including the model most similar to the crystal structure and very different from it. In both systems, the sum of the conformational and solvation free energies tended to be lower for the structure similar to the crystal. We concluded that our energy calculation method is useful for selecting low energy complex models similar to the crystal structure from among a set of generated models.
Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.
Perez-Acle, Tomas; Fuenzalida, Ignacio; Martin, Alberto J M; Santibañez, Rodrigo; Avaria, Rodrigo; Bernardin, Alejandro; Bustos, Alvaro M; Garrido, Daniel; Dushoff, Jonathan; Liu, James H
2018-03-29
Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.
Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner
2016-01-01
Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.
Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong; Baudry, Michel; Berger, Theodore W
2015-01-01
Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.
Hu, Eric Y.; Bouteiller, Jean-Marie C.; Song, Dong; Baudry, Michel; Berger, Theodore W.
2015-01-01
Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations. PMID:26441622
NASA Technical Reports Server (NTRS)
Kavi, K. M.
1984-01-01
There have been a number of simulation packages developed for the purpose of designing, testing and validating computer systems, digital systems and software systems. Complex analytical tools based on Markov and semi-Markov processes have been designed to estimate the reliability and performance of simulated systems. Petri nets have received wide acceptance for modeling complex and highly parallel computers. In this research data flow models for computer systems are investigated. Data flow models can be used to simulate both software and hardware in a uniform manner. Data flow simulation techniques provide the computer systems designer with a CAD environment which enables highly parallel complex systems to be defined, evaluated at all levels and finally implemented in either hardware or software. Inherent in data flow concept is the hierarchical handling of complex systems. In this paper we will describe how data flow can be used to model computer system.
Lim, Hooi Been; Baumann, Dirk; Li, Er-Ping
2011-03-01
Wireless body area network (WBAN) is a new enabling system with promising applications in areas such as remote health monitoring and interpersonal communication. Reliable and optimum design of a WBAN system relies on a good understanding and in-depth studies of the wave propagation around a human body. However, the human body is a very complex structure and is computationally demanding to model. This paper aims to investigate the effects of the numerical model's structure complexity and feature details on the simulation results. Depending on the application, a simplified numerical model that meets desired simulation accuracy can be employed for efficient simulations. Measurements of ultra wideband (UWB) signal propagation along a human arm are performed and compared to the simulation results obtained with numerical arm models of different complexity levels. The influence of the arm shape and size, as well as tissue composition and complexity is investigated.
The effects of numerical-model complexity and observation type on estimated porosity values
Starn, Jeffrey; Bagtzoglou, Amvrossios C.; Green, Christopher T.
2015-01-01
The relative merits of model complexity and types of observations employed in model calibration are compared. An existing groundwater flow model coupled with an advective transport simulation of the Salt Lake Valley, Utah (USA), is adapted for advective transport, and effective porosity is adjusted until simulated tritium concentrations match concentrations in samples from wells. Two calibration approaches are used: a “complex” highly parameterized porosity field and a “simple” parsimonious model of porosity distribution. The use of an atmospheric tracer (tritium in this case) and apparent ages (from tritium/helium) in model calibration also are discussed. Of the models tested, the complex model (with tritium concentrations and tritium/helium apparent ages) performs best. Although tritium breakthrough curves simulated by complex and simple models are very generally similar, and there is value in the simple model, the complex model is supported by a more realistic porosity distribution and a greater number of estimable parameters. Culling the best quality data did not lead to better calibration, possibly because of processes and aquifer characteristics that are not simulated. Despite many factors that contribute to shortcomings of both the models and the data, useful information is obtained from all the models evaluated. Although any particular prediction of tritium breakthrough may have large errors, overall, the models mimic observed trends.
Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases
Amos, Christopher I.; Bafna, Vineet; Hauser, Elizabeth R.; Hernandez, Ryan D.; Li, Chun; Liberles, David A.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Papanicolaou, George J.; Peng, Bo; Ritchie, Marylyn D.; Rosenfeld, Gabriel; Witte, John S.
2014-01-01
Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled “Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases” at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to: (i) identify opportunities, challenges and resource needs for the development and application of genetic simulation models; (ii) improve the integration of tools for modeling and analysis of simulated data; and (iii) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation. PMID:25371374
Building complex simulations rapidly using MATRIX(x): The Space Station redesign
NASA Technical Reports Server (NTRS)
Carrington, C. K.
1994-01-01
MSFC's quick response to the Space Station redesign effort last year required the development of a computer simulation to model the attitude and station-keeping dynamics of a complex body with rotating solar arrays in orbit around the Earth. The simulation was written using a rapid-prototyping graphical simulation and design tool called MATRIX(x) and provided the capability to quickly remodel complex configuration changes by icon manipulation using a mouse. The simulation determines time-dependent inertia properties, and models forces and torques from gravity-gradient, solar radiation, and aerodynamic disturbances. Surface models are easily built from a selection of beams, plates, tetrahedrons, and cylinders. An optimization scheme was written to determine the torque equilibrium attitudes that balance gravity-gradient and aerodynamic torques over an orbit, and propellant-usage estimates were determined. The simulation has been adapted to model the attitude dynamics for small spacecraft.
Urbanowicz, Ryan J; Kiralis, Jeff; Sinnott-Armstrong, Nicholas A; Heberling, Tamra; Fisher, Jonathan M; Moore, Jason H
2012-10-01
Geneticists who look beyond single locus disease associations require additional strategies for the detection of complex multi-locus effects. Epistasis, a multi-locus masking effect, presents a particular challenge, and has been the target of bioinformatic development. Thorough evaluation of new algorithms calls for simulation studies in which known disease models are sought. To date, the best methods for generating simulated multi-locus epistatic models rely on genetic algorithms. However, such methods are computationally expensive, difficult to adapt to multiple objectives, and unlikely to yield models with a precise form of epistasis which we refer to as pure and strict. Purely and strictly epistatic models constitute the worst-case in terms of detecting disease associations, since such associations may only be observed if all n-loci are included in the disease model. This makes them an attractive gold standard for simulation studies considering complex multi-locus effects. We introduce GAMETES, a user-friendly software package and algorithm which generates complex biallelic single nucleotide polymorphism (SNP) disease models for simulation studies. GAMETES rapidly and precisely generates random, pure, strict n-locus models with specified genetic constraints. These constraints include heritability, minor allele frequencies of the SNPs, and population prevalence. GAMETES also includes a simple dataset simulation strategy which may be utilized to rapidly generate an archive of simulated datasets for given genetic models. We highlight the utility and limitations of GAMETES with an example simulation study using MDR, an algorithm designed to detect epistasis. GAMETES is a fast, flexible, and precise tool for generating complex n-locus models with random architectures. While GAMETES has a limited ability to generate models with higher heritabilities, it is proficient at generating the lower heritability models typically used in simulation studies evaluating new algorithms. In addition, the GAMETES modeling strategy may be flexibly combined with any dataset simulation strategy. Beyond dataset simulation, GAMETES could be employed to pursue theoretical characterization of genetic models and epistasis.
Computer modeling and simulation of human movement. Applications in sport and rehabilitation.
Neptune, R R
2000-05-01
Computer modeling and simulation of human movement plays an increasingly important role in sport and rehabilitation, with applications ranging from sport equipment design to understanding pathologic gait. The complex dynamic interactions within the musculoskeletal and neuromuscular systems make analyzing human movement with existing experimental techniques difficult but computer modeling and simulation allows for the identification of these complex interactions and causal relationships between input and output variables. This article provides an overview of computer modeling and simulation and presents an example application in the field of rehabilitation.
Using multi-criteria analysis of simulation models to understand complex biological systems
Maureen C. Kennedy; E. David Ford
2011-01-01
Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...
Protein-Protein Interactions of Azurin Complex by Coarse-Grained Simulations with a Gō-Like Model
NASA Astrophysics Data System (ADS)
Rusmerryani, Micke; Takasu, Masako; Kawaguchi, Kazutomo; Saito, Hiroaki; Nagao, Hidemi
Proteins usually perform their biological functions by forming a complex with other proteins. It is very important to study the protein-protein interactions since these interactions are crucial in many processes of a living organism. In this study, we develop a coarse grained model to simulate protein complex in liquid system. We carry out molecular dynamics simulations with topology-based potential interactions to simulate dynamical properties of Pseudomonas Aeruginosa azurin complex systems. Azurin is known to play an essential role as an anticancer agent and bind many important intracellular molecules. Some physical properties are monitored during simulation time to get a better understanding of the influence of protein-protein interactions to the azurin complex dynamics. These studies will provide valuable insights for further investigation on protein-protein interactions in more realistic system.
Spectrum simulation in DTSA-II.
Ritchie, Nicholas W M
2009-10-01
Spectrum simulation is a useful practical and pedagogical tool. Particularly with complex samples or trace constituents, a simulation can help to understand the limits of the technique and the instrument parameters for the optimal measurement. DTSA-II, software for electron probe microanalysis, provides both easy to use and flexible tools for simulating common and less common sample geometries and materials. Analytical models based on (rhoz) curves provide quick simulations of simple samples. Monte Carlo models based on electron and X-ray transport provide more sophisticated models of arbitrarily complex samples. DTSA-II provides a broad range of simulation tools in a framework with many different interchangeable physical models. In addition, DTSA-II provides tools for visualizing, comparing, manipulating, and quantifying simulated and measured spectra.
Marshall, Deborah A; Burgos-Liz, Lina; IJzerman, Maarten J; Osgood, Nathaniel D; Padula, William V; Higashi, Mitchell K; Wong, Peter K; Pasupathy, Kalyan S; Crown, William
2015-01-01
Health care delivery systems are inherently complex, consisting of multiple tiers of interdependent subsystems and processes that are adaptive to changes in the environment and behave in a nonlinear fashion. Traditional health technology assessment and modeling methods often neglect the wider health system impacts that can be critical for achieving desired health system goals and are often of limited usefulness when applied to complex health systems. Researchers and health care decision makers can either underestimate or fail to consider the interactions among the people, processes, technology, and facility designs. Health care delivery system interventions need to incorporate the dynamics and complexities of the health care system context in which the intervention is delivered. This report provides an overview of common dynamic simulation modeling methods and examples of health care system interventions in which such methods could be useful. Three dynamic simulation modeling methods are presented to evaluate system interventions for health care delivery: system dynamics, discrete event simulation, and agent-based modeling. In contrast to conventional evaluations, a dynamic systems approach incorporates the complexity of the system and anticipates the upstream and downstream consequences of changes in complex health care delivery systems. This report assists researchers and decision makers in deciding whether these simulation methods are appropriate to address specific health system problems through an eight-point checklist referred to as the SIMULATE (System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence) tool. It is a primer for researchers and decision makers working in health care delivery and implementation sciences who face complex challenges in delivering effective and efficient care that can be addressed with system interventions. On reviewing this report, the readers should be able to identify whether these simulation modeling methods are appropriate to answer the problem they are addressing and to recognize the differences of these methods from other modeling approaches used typically in health technology assessment applications. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Computational methods to predict railcar response to track cross-level variations
DOT National Transportation Integrated Search
1976-09-01
The rocking response of railroad freight cars to track cross-level variations is studied using: (1) a reduced complexity digital simulation model, and (2) a quasi-linear describing function analysis. The reduced complexity digital simulation model em...
Acceleration techniques for dependability simulation. M.S. Thesis
NASA Technical Reports Server (NTRS)
Barnette, James David
1995-01-01
As computer systems increase in complexity, the need to project system performance from the earliest design and development stages increases. We have to employ simulation for detailed dependability studies of large systems. However, as the complexity of the simulation model increases, the time required to obtain statistically significant results also increases. This paper discusses an approach that is application independent and can be readily applied to any process-based simulation model. Topics include background on classical discrete event simulation and techniques for random variate generation and statistics gathering to support simulation.
Coarse-grained molecular dynamics simulations for giant protein-DNA complexes
NASA Astrophysics Data System (ADS)
Takada, Shoji
Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.
FLAME: A platform for high performance computing of complex systems, applied for three case studies
Kiran, Mariam; Bicak, Mesude; Maleki-Dizaji, Saeedeh; ...
2011-01-01
FLAME allows complex models to be automatically parallelised on High Performance Computing (HPC) grids enabling large number of agents to be simulated over short periods of time. Modellers are hindered by complexities of porting models on parallel platforms and time taken to run large simulations on a single machine, which FLAME overcomes. Three case studies from different disciplines were modelled using FLAME, and are presented along with their performance results on a grid.
A GENERAL PHYSIOLOGICAL AND TOXICOKINETIC (GPAT) MODEL FOR SIMULATION OF COMPLEX TOLUENE EXPOSURE SCENARIOS IN HUMANS. E M Kenyon1, T Colemen2, C R Eklund1 and V A Benignus3. 1U.S. EPA, ORD, NHEERL, ETD, PKB, RTP, NC, USA; 2Biological Simulators, Inc., Jackson MS, USA, 3U.S. EP...
Piloted Evaluation of a UH-60 Mixer Equivalent Turbulence Simulation Model
NASA Technical Reports Server (NTRS)
Lusardi, Jeff A.; Blanken, Chris L.; Tischeler, Mark B.
2002-01-01
A simulation study of a recently developed hover/low speed Mixer Equivalent Turbulence Simulation (METS) model for the UH-60 Black Hawk helicopter was conducted in the NASA Ames Research Center Vertical Motion Simulator (VMS). The experiment was a continuation of previous work to develop a simple, but validated, turbulence model for hovering rotorcraft. To validate the METS model, two experienced test pilots replicated precision hover tasks that had been conducted in an instrumented UH-60 helicopter in turbulence. Objective simulation data were collected for comparison with flight test data, and subjective data were collected that included handling qualities ratings and pilot comments for increasing levels of turbulence. Analyses of the simulation results show good analytic agreement between the METS model and flight test data, with favorable pilot perception of the simulated turbulence. Precision hover tasks were also repeated using the more complex rotating-frame SORBET (Simulation Of Rotor Blade Element Turbulence) model to generate turbulence. Comparisons of the empirically derived METS model with the theoretical SORBET model show good agreement providing validation of the more complex blade element method of simulating turbulence.
Numerical investigation of coupled density-driven flow and hydrogeochemical processes below playas
NASA Astrophysics Data System (ADS)
Hamann, Enrico; Post, Vincent; Kohfahl, Claus; Prommer, Henning; Simmons, Craig T.
2015-11-01
Numerical modeling approaches with varying complexity were explored to investigate coupled groundwater flow and geochemical processes in saline basins. Long-term model simulations of a playa system gain insights into the complex feedback mechanisms between density-driven flow and the spatiotemporal patterns of precipitating evaporites and evolving brines. Using a reactive multicomponent transport model approach, the simulations reproduced, for the first time in a numerical study, the evaporite precipitation sequences frequently observed in saline basins ("bull's eyes"). Playa-specific flow, evapoconcentration, and chemical divides were found to be the primary controls for the location of evaporites formed, and the resulting brine chemistry. Comparative simulations with the computationally far less demanding surrogate single-species transport models showed that these were still able to replicate the major flow patterns obtained by the more complex reactive transport simulations. However, the simulated degree of salinization was clearly lower than in reactive multicomponent transport simulations. For example, in the late stages of the simulations, when the brine becomes halite-saturated, the nonreactive simulation overestimated the solute mass by almost 20%. The simulations highlight the importance of the consideration of reactive transport processes for understanding and quantifying geochemical patterns, concentrations of individual dissolved solutes, and evaporite evolution.
Phase-field simulations of GaN growth by selective area epitaxy on complex mask geometries
Aagesen, Larry K.; Coltrin, Michael Elliott; Han, Jung; ...
2015-05-15
Three-dimensional phase-field simulations of GaN growth by selective area epitaxy were performed. Furthermore, this model includes a crystallographic-orientation-dependent deposition rate and arbitrarily complex mask geometries. The orientation-dependent deposition rate can be determined from experimental measurements of the relative growth rates of low-index crystallographic facets. Growth on various complex mask geometries was simulated on both c-plane and a-plane template layers. Agreement was observed between simulations and experiment, including complex phenomena occurring at the intersections between facets. The sources of the discrepancies between simulated and experimental morphologies were also investigated. We found that the model provides a route to optimize masks andmore » processing conditions during materials synthesis for solar cells, light-emitting diodes, and other electronic and opto-electronic applications.« less
Improving the Aircraft Design Process Using Web-Based Modeling and Simulation
NASA Technical Reports Server (NTRS)
Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.; Follen, Gregory J. (Technical Monitor)
2000-01-01
Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and multifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.
Improving the Aircraft Design Process Using Web-based Modeling and Simulation
NASA Technical Reports Server (NTRS)
Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.
2003-01-01
Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and muitifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.
The use of discrete-event simulation modelling to improve radiation therapy planning processes.
Werker, Greg; Sauré, Antoine; French, John; Shechter, Steven
2009-07-01
The planning portion of the radiation therapy treatment process at the British Columbia Cancer Agency is efficient but nevertheless contains room for improvement. The purpose of this study is to show how a discrete-event simulation (DES) model can be used to represent this complex process and to suggest improvements that may reduce the planning time and ultimately reduce overall waiting times. A simulation model of the radiation therapy (RT) planning process was constructed using the Arena simulation software, representing the complexities of the system. Several types of inputs feed into the model; these inputs come from historical data, a staff survey, and interviews with planners. The simulation model was validated against historical data and then used to test various scenarios to identify and quantify potential improvements to the RT planning process. Simulation modelling is an attractive tool for describing complex systems, and can be used to identify improvements to the processes involved. It is possible to use this technique in the area of radiation therapy planning with the intent of reducing process times and subsequent delays for patient treatment. In this particular system, reducing the variability and length of oncologist-related delays contributes most to improving the planning time.
NASA Astrophysics Data System (ADS)
Mei, Yuan; Sherman, David M.; Liu, Weihua; Etschmann, Barbara; Testemale, Denis; Brugger, Joël
2015-02-01
The solubility of zinc minerals in hydrothermal fluids is enhanced by chloride complexation of Zn2+. Thermodynamic models of these complexation reactions are central to models of Zn transport and ore formation. However, existing thermodynamic models, derived from solubility measurements, are inconsistent with spectroscopic measurements of Zn speciation. Here, we used ab initio molecular dynamics simulations (with the PBE exchange-correlation functional) to predict the speciation of Zn-Cl complexes from 25 to 600 °C. We also obtained in situ XAS measurements of Zn-Cl solutions at 30-600 °C. Qualitatively, the simulations reproduced the main features derived from in situ XANES and EXAFS measurements: octahedral to tetrahedral transition with increasing temperature and salinity, stability of ZnCl42- at high chloride concentration up to ⩾500 °C, and increasing stability of the trigonal planar [ZnCl3]- complex at high temperature. Having confirmed the dominant species, we directly determined the stability constants for the Zn-Cl complexes using thermodynamic integration along constrained Zn-Cl distances in a series of MD simulations. We corrected our stability constants to infinite dilution using the b-dot model for the activity coefficients of the solute species. In order to compare the ab initio results with experiments, we need to re-model the existing solubility data using the species we identified in our MD simulations. The stability constants derived from refitting published experimental data are in reasonable agreement with those we obtained using ab initio MD simulations. Our new thermodynamic model accurately predicts the experimentally observed changes in ZnO(s) and ZnCO3(s) solubility as a function of chloride concentration from 200 (Psat) to 600 °C (2000 bar). This study demonstrates that metal speciation and geologically useful stability constants can be derived for species in hydrothermal fluids from ab initio MD simulations even at the generalized gradient approximation for exchange-correlation. We caution, however, that simulations are mostly reliable at high T where ligand exchange is fast enough to yield thermodynamic averages over the timescales of the simulations.
NASA Astrophysics Data System (ADS)
Antsiferov, S. I.; Eltsov, M. Iu; Khakhalev, P. A.
2018-03-01
This paper considers a newly designed electronic digital model of a robotic complex for implementing full-scale additive technologies, funded under a Federal Target Program. The electronic and digital model was used to solve the problem of simulating the movement of a robotic complex using the NX CAD/CAM/CAE system. The virtual mechanism was built and the main assemblies, joints, and drives were identified as part of solving the problem. In addition, the maximum allowed printable area size was identified for the robotic complex, and a simulation of printing a rectangular-shaped article was carried out.
LISP based simulation generators for modeling complex space processes
NASA Technical Reports Server (NTRS)
Tseng, Fan T.; Schroer, Bernard J.; Dwan, Wen-Shing
1987-01-01
The development of a simulation assistant for modeling discrete event processes is presented. Included are an overview of the system, a description of the simulation generators, and a sample process generated using the simulation assistant.
Hybrid modeling and empirical analysis of automobile supply chain network
NASA Astrophysics Data System (ADS)
Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying
2017-05-01
Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.
Frequency analysis of stress relaxation dynamics in model asphalts
NASA Astrophysics Data System (ADS)
Masoori, Mohammad; Greenfield, Michael L.
2014-09-01
Asphalt is an amorphous or semi-crystalline material whose mechanical performance relies on viscoelastic responses to applied strain or stress. Chemical composition and its effect on the viscoelastic properties of model asphalts have been investigated here by computing complex modulus from molecular dynamics simulation results for two different model asphalts whose compositions each resemble the Strategic Highway Research Program AAA-1 asphalt in different ways. For a model system that contains smaller molecules, simulation results for storage and loss modulus at 443 K reach both the low and high frequency scaling limits of the Maxwell model. Results for a model system composed of larger molecules (molecular weights 300-900 g/mol) with longer branches show a quantitatively higher complex modulus that decreases significantly as temperature increases over 400-533 K. Simulation results for its loss modulus approach the low frequency scaling limit of the Maxwell model at only the highest temperature simulated. A Black plot or van Gurp-Palman plot of complex modulus vs. phase angle for the system of larger molecules suggests some overlap among results at different temperatures for less high frequencies, with an interdependence consistent with the empirical Christensen-Anderson-Marasteanu model. Both model asphalts are thermorheologically complex at very high frequencies, where they show a loss peak that appears to be independent of temperature and density.
A hierarchical approach for simulating northern forest dynamics
Don C. Bragg; David W. Roberts; Thomas R. Crow
2004-01-01
Complexity in ecological systems has challenged forest simulation modelers for years, resulting in a number of approaches with varying degrees of success. Arguments in favor of hierarchical modeling are made, especially for considering a complex environmental issue like widespread eastern hemlock regeneration failure. We present the philosophy and basic framework for...
Abaqus Simulations of Rock Response to Dynamic Loading
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steedman, David W.; Coblentz, David
The LANL Geodynamics Team has been applying Abaqus modeling to achieve increasingly complex simulations. Advancements in Abaqus model building and simulation tools allows this progress. We use Lab-developed constitutive models, the fully coupled CEL Abaqus and general contact to simulate response of realistic sites to explosively driven shock.
NASA Astrophysics Data System (ADS)
Hoepfer, Matthias
Over the last two decades, computer modeling and simulation have evolved as the tools of choice for the design and engineering of dynamic systems. With increased system complexities, modeling and simulation become essential enablers for the design of new systems. Some of the advantages that modeling and simulation-based system design allows for are the replacement of physical tests to ensure product performance, reliability and quality, the shortening of design cycles due to the reduced need for physical prototyping, the design for mission scenarios, the invoking of currently nonexisting technologies, and the reduction of technological and financial risks. Traditionally, dynamic systems are modeled in a monolithic way. Such monolithic models include all the data, relations and equations necessary to represent the underlying system. With increased complexity of these models, the monolithic model approach reaches certain limits regarding for example, model handling and maintenance. Furthermore, while the available computer power has been steadily increasing according to Moore's Law (a doubling in computational power every 10 years), the ever-increasing complexities of new models have negated the increased resources available. Lastly, modern systems and design processes are interdisciplinary, enforcing the necessity to make models more flexible to be able to incorporate different modeling and design approaches. The solution to bypassing the shortcomings of monolithic models is cosimulation. In a very general sense, co-simulation addresses the issue of linking together different dynamic sub-models to a model which represents the overall, integrated dynamic system. It is therefore an important enabler for the design of interdisciplinary, interconnected, highly complex dynamic systems. While a basic co-simulation setup can be very easy, complications can arise when sub-models display behaviors such as algebraic loops, singularities, or constraints. This work frames the co-simulation approach to modeling and simulation. It lays out the general approach to dynamic system co-simulation, and gives a comprehensive overview of what co-simulation is and what it is not. It creates a taxonomy of the requirements and limits of co-simulation, and the issues arising with co-simulating sub-models. Possible solutions towards resolving the stated problems are investigated to a certain depth. A particular focus is given to the issue of time stepping. It will be shown that for dynamic models, the selection of the simulation time step is a crucial issue with respect to computational expense, simulation accuracy, and error control. The reasons for this are discussed in depth, and a time stepping algorithm for co-simulation with unknown dynamic sub-models is proposed. Motivations and suggestions for the further treatment of selected issues are presented.
Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist
Banerjee, Debjani; Bellesia, Giovanni; Daigle, Bernie J.; Douglas, Geoffrey; Gu, Mengyuan; Gupta, Anand; Hellander, Stefan; Horuk, Chris; Nath, Dibyendu; Takkar, Aviral; Lötstedt, Per; Petzold, Linda R.
2016-01-01
We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources and exchange models via a public model repository. We demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity. PMID:27930676
Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist
Drawert, Brian; Hellander, Andreas; Bales, Ben; ...
2016-12-08
We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources andmore » exchange models via a public model repository. We also demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity.« less
A multi-species exchange model for fully fluctuating polymer field theory simulations.
Düchs, Dominik; Delaney, Kris T; Fredrickson, Glenn H
2014-11-07
Field-theoretic models have been used extensively to study the phase behavior of inhomogeneous polymer melts and solutions, both in self-consistent mean-field calculations and in numerical simulations of the full theory capturing composition fluctuations. The models commonly used can be grouped into two categories, namely, species models and exchange models. Species models involve integrations of functionals that explicitly depend on fields originating both from species density operators and their conjugate chemical potential fields. In contrast, exchange models retain only linear combinations of the chemical potential fields. In the two-component case, development of exchange models has been instrumental in enabling stable complex Langevin (CL) simulations of the full complex-valued theory. No comparable stable CL approach has yet been established for field theories of the species type. Here, we introduce an extension of the exchange model to an arbitrary number of components, namely, the multi-species exchange (MSE) model, which greatly expands the classes of soft material systems that can be accessed by the complex Langevin simulation technique. We demonstrate the stability and accuracy of the MSE-CL sampling approach using numerical simulations of triblock and tetrablock terpolymer melts, and tetrablock quaterpolymer melts. This method should enable studies of a wide range of fluctuation phenomena in multiblock/multi-species polymer blends and composites.
GPU-accelerated depth map generation for X-ray simulations of complex CAD geometries
NASA Astrophysics Data System (ADS)
Grandin, Robert J.; Young, Gavin; Holland, Stephen D.; Krishnamurthy, Adarsh
2018-04-01
Interactive x-ray simulations of complex computer-aided design (CAD) models can provide valuable insights for better interpretation of the defect signatures such as porosity from x-ray CT images. Generating the depth map along a particular direction for the given CAD geometry is the most compute-intensive step in x-ray simulations. We have developed a GPU-accelerated method for real-time generation of depth maps of complex CAD geometries. We preprocess complex components designed using commercial CAD systems using a custom CAD module and convert them into a fine user-defined surface tessellation. Our CAD module can be used by different simulators as well as handle complex geometries, including those that arise from complex castings and composite structures. We then make use of a parallel algorithm that runs on a graphics processing unit (GPU) to convert the finely-tessellated CAD model to a voxelized representation. The voxelized representation can enable heterogeneous modeling of the volume enclosed by the CAD model by assigning heterogeneous material properties in specific regions. The depth maps are generated from this voxelized representation with the help of a GPU-accelerated ray-casting algorithm. The GPU-accelerated ray-casting method enables interactive (> 60 frames-per-second) generation of the depth maps of complex CAD geometries. This enables arbitrarily rotation and slicing of the CAD model, leading to better interpretation of the x-ray images by the user. In addition, the depth maps can be used to aid directly in CT reconstruction algorithms.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Udhay Ravishankar; Milos manic
2013-08-01
This paper presents a micro-grid simulator tool useful for implementing and testing multi-agent controllers (SGridSim). As a common engineering practice it is important to have a tool that simplifies the modeling of the salient features of a desired system. In electric micro-grids, these salient features are the voltage and power distributions within the micro-grid. Current simplified electric power grid simulator tools such as PowerWorld, PowerSim, Gridlab, etc, model only the power distribution features of a desired micro-grid. Other power grid simulators such as Simulink, Modelica, etc, use detailed modeling to accommodate the voltage distribution features. This paper presents a SGridSimmore » micro-grid simulator tool that simplifies the modeling of both the voltage and power distribution features in a desired micro-grid. The SGridSim tool accomplishes this simplified modeling by using Effective Node-to-Node Complex Impedance (EN2NCI) models of components that typically make-up a micro-grid. The term EN2NCI models means that the impedance based components of a micro-grid are modeled as single impedances tied between their respective voltage nodes on the micro-grid. Hence the benefit of the presented SGridSim tool are 1) simulation of a micro-grid is performed strictly in the complex-domain; 2) faster simulation of a micro-grid by avoiding the simulation of detailed transients. An example micro-grid model was built using the SGridSim tool and tested to simulate both the voltage and power distribution features with a total absolute relative error of less than 6%.« less
Simulating Mass Removal of Groundwater Contaminant Plumes with Complex and Simple Models
NASA Astrophysics Data System (ADS)
Lopez, J.; Guo, Z.; Fogg, G. E.
2016-12-01
Chlorinated solvents used in industrial, commercial, and other applications continue to pose significant threats to human health through contamination of groundwater resources. A recent National Research Council report concludes that it is unlikely that remediation of these complex sites will be achieved in a time frame of 50-100 years under current methods and standards (NRC, 2013). Pump and treat has been a common strategy at many sites to contain and treat groundwater contamination. In these sites, extensive retention of contaminant mass in low-permeability materials (tailing) has been observed after years or decades of pumping. Although transport models can be built that contain enough of the complex, 3D heterogeneity to simulate the tailing and long cleanup times, this is seldom done because of the large data and computational burdens. Hence, useful, reliable models to simulate various cleanup strategies are rare. The purpose of this study is to explore other potential ways to simulate the mass-removal processes with shorter time and less cost but still produce robust results by capturing effects of the heterogeneity and long-term retention of mass. A site containing a trichloroethylene groundwater plume was selected as the study area. The plume is located within alluvial sediments in the Tucson Basin. A fully heterogeneous domain is generated first and MODFLOW is used to simulate the flow field. Contaminant transport is simulated using both MT3D and RWHet for the fully heterogeneous model. Other approaches, including dual-domain mass transfer and heterogeneous chemical reactions, are manipulated to simulate the mass removal in a less heterogeneous, or homogeneous, domain and results are compared to the results obtained from complex models. The capability of these simpler models to simulate remediation processes, especially capture the late-time tailing, are examined.
Routine Discovery of Complex Genetic Models using Genetic Algorithms
Moore, Jason H.; Hahn, Lance W.; Ritchie, Marylyn D.; Thornton, Tricia A.; White, Bill C.
2010-01-01
Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes. PMID:20948983
NASA Astrophysics Data System (ADS)
Chou, S. C.; Zolino, M. M.; Gomes, J. L.; Bustamante, J. F.; Lima-e-Silva, P. P.
2012-04-01
The Eta Model is used operationally by CPTEC to produce weather forecasts over South America since 1997. The model has gone through upgrades. In order to prepare the model for operational higher resolution forecasts, the model is configured and tested over a region of complex topography located near the coast of Southeast Brazil. The Eta Model was configured, with 2-km horizontal resolution and 50 layers. The Eta-2km is a second nesting, it is driven by Eta-15km, which in its turn is driven by Era-Interim reanalyses. The model domain includes the two Brazilians cities, Rio de Janeiro and Sao Paulo, urban areas, preserved tropical forest, pasture fields, and complex terrain and coastline. Mountains can rise up to about 700m. The region suffers frequent events of floods and landslides. The objective of this work is to evaluate high resolution simulations of wind and temperature in this complex area. Verification of model runs uses observations taken from the nuclear power plant. Accurate near-surface wind direction and magnitude are needed for the plant emergency plan and winds are highly sensitive to model spatial resolution and atmospheric stability. Verification of two cases during summer shows that model has clear diurnal cycle signal for wind in that region. The area is characterized by weak winds which makes the simulation more difficult. The simulated wind magnitude is about 1.5m/s, which is close to observations of about 2m/s; however, the observed change of wind direction of the sea breeze is fast whereas it is slow in the simulations. Nighttime katabatic flow is captured by the simulations. Comparison against Eta-5km runs show that the valley circulation is better described in the 2-km resolution run. Simulated temperatures follow closely the observed diurnal cycle. Experiments improving some surface conditions such as the surface temperature and land cover show simulation error reduction and improved diurnal cycle.
A Review of Numerical Simulation and Analytical Modeling for Medical Devices Safety in MRI
Kabil, J.; Belguerras, L.; Trattnig, S.; Pasquier, C.; Missoffe, A.
2016-01-01
Summary Objectives To review past and present challenges and ongoing trends in numerical simulation for MRI (Magnetic Resonance Imaging) safety evaluation of medical devices. Methods A wide literature review on numerical and analytical simulation on simple or complex medical devices in MRI electromagnetic fields shows the evolutions through time and a growing concern for MRI safety over the years. Major issues and achievements are described, as well as current trends and perspectives in this research field. Results Numerical simulation of medical devices is constantly evolving, supported by calculation methods now well-established. Implants with simple geometry can often be simulated in a computational human model, but one issue remaining today is the experimental validation of these human models. A great concern is to assess RF heating on implants too complex to be traditionally simulated, like pacemaker leads. Thus, ongoing researches focus on alternative hybrids methods, both numerical and experimental, with for example a transfer function method. For the static field and gradient fields, analytical models can be used for dimensioning simple implants shapes, but limited for complex geometries that cannot be studied with simplifying assumptions. Conclusions Numerical simulation is an essential tool for MRI safety testing of medical devices. The main issues remain the accuracy of simulations compared to real life and the studies of complex devices; but as the research field is constantly evolving, some promising ideas are now under investigation to take up the challenges. PMID:27830244
A CellML simulation compiler and code generator using ODE solving schemes
2012-01-01
Models written in description languages such as CellML are becoming a popular solution to the handling of complex cellular physiological models in biological function simulations. However, in order to fully simulate a model, boundary conditions and ordinary differential equation (ODE) solving schemes have to be combined with it. Though boundary conditions can be described in CellML, it is difficult to explicitly specify ODE solving schemes using existing tools. In this study, we define an ODE solving scheme description language-based on XML and propose a code generation system for biological function simulations. In the proposed system, biological simulation programs using various ODE solving schemes can be easily generated. We designed a two-stage approach where the system generates the equation set associating the physiological model variable values at a certain time t with values at t + Δt in the first stage. The second stage generates the simulation code for the model. This approach enables the flexible construction of code generation modules that can support complex sets of formulas. We evaluate the relationship between models and their calculation accuracies by simulating complex biological models using various ODE solving schemes. Using the FHN model simulation, results showed good qualitative and quantitative correspondence with the theoretical predictions. Results for the Luo-Rudy 1991 model showed that only first order precision was achieved. In addition, running the generated code in parallel on a GPU made it possible to speed up the calculation time by a factor of 50. The CellML Compiler source code is available for download at http://sourceforge.net/projects/cellmlcompiler. PMID:23083065
Moving alcohol prevention research forward-Part I: introducing a complex systems paradigm.
Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller
2018-02-01
The drinking environment is a complex system consisting of a number of heterogeneous, evolving and interacting components, which exhibit circular causality and emergent properties. These characteristics reduce the efficacy of commonly used research approaches, which typically do not account for the underlying dynamic complexity of alcohol consumption and the interdependent nature of diverse factors influencing misuse over time. We use alcohol misuse among college students in the United States as an example for framing our argument for a complex systems paradigm. A complex systems paradigm, grounded in socio-ecological and complex systems theories and computational modeling and simulation, is introduced. Theoretical, conceptual, methodological and analytical underpinnings of this paradigm are described in the context of college drinking prevention research. The proposed complex systems paradigm can transcend limitations of traditional approaches, thereby fostering new directions in alcohol prevention research. By conceptualizing student alcohol misuse as a complex adaptive system, computational modeling and simulation methodologies and analytical techniques can be used. Moreover, use of participatory model-building approaches to generate simulation models can further increase stakeholder buy-in, understanding and policymaking. A complex systems paradigm for research into alcohol misuse can provide a holistic understanding of the underlying drinking environment and its long-term trajectory, which can elucidate high-leverage preventive interventions. © 2017 Society for the Study of Addiction.
Elements of complexity in subsurface modeling, exemplified with three case studies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Freedman, Vicky L.; Truex, Michael J.; Rockhold, Mark
2017-04-03
There are complexity elements to consider when applying subsurface flow and transport models to support environmental analyses. Modelers balance the benefits and costs of modeling along the spectrum of complexity, taking into account the attributes of more simple models (e.g., lower cost, faster execution, easier to explain, less mechanistic) and the attributes of more complex models (higher cost, slower execution, harder to explain, more mechanistic and technically defensible). In this paper, modeling complexity is examined with respect to considering this balance. The discussion of modeling complexity is organized into three primary elements: 1) modeling approach, 2) description of process, andmore » 3) description of heterogeneity. Three examples are used to examine these complexity elements. Two of the examples use simulations generated from a complex model to develop simpler models for efficient use in model applications. The first example is designed to support performance evaluation of soil vapor extraction remediation in terms of groundwater protection. The second example investigates the importance of simulating different categories of geochemical reactions for carbon sequestration and selecting appropriate simplifications for use in evaluating sequestration scenarios. In the third example, the modeling history for a uranium-contaminated site demonstrates that conservative parameter estimates were inadequate surrogates for complex, critical processes and there is discussion on the selection of more appropriate model complexity for this application. All three examples highlight how complexity considerations are essential to create scientifically defensible models that achieve a balance between model simplification and complexity.« less
Elements of complexity in subsurface modeling, exemplified with three case studies
NASA Astrophysics Data System (ADS)
Freedman, Vicky L.; Truex, Michael J.; Rockhold, Mark L.; Bacon, Diana H.; Freshley, Mark D.; Wellman, Dawn M.
2017-09-01
There are complexity elements to consider when applying subsurface flow and transport models to support environmental analyses. Modelers balance the benefits and costs of modeling along the spectrum of complexity, taking into account the attributes of more simple models (e.g., lower cost, faster execution, easier to explain, less mechanistic) and the attributes of more complex models (higher cost, slower execution, harder to explain, more mechanistic and technically defensible). In this report, modeling complexity is examined with respect to considering this balance. The discussion of modeling complexity is organized into three primary elements: (1) modeling approach, (2) description of process, and (3) description of heterogeneity. Three examples are used to examine these complexity elements. Two of the examples use simulations generated from a complex model to develop simpler models for efficient use in model applications. The first example is designed to support performance evaluation of soil-vapor-extraction remediation in terms of groundwater protection. The second example investigates the importance of simulating different categories of geochemical reactions for carbon sequestration and selecting appropriate simplifications for use in evaluating sequestration scenarios. In the third example, the modeling history for a uranium-contaminated site demonstrates that conservative parameter estimates were inadequate surrogates for complex, critical processes and there is discussion on the selection of more appropriate model complexity for this application. All three examples highlight how complexity considerations are essential to create scientifically defensible models that achieve a balance between model simplification and complexity.
The Idaho National Engineering & Environmental Lab (INEEL) was charged by DOE EM to develop a complex-wide science and technology roadmap for the characterization, modeling and simulation of the fate and transport of contamination in the vadose zone. Various types of hazardous, r...
ERIC Educational Resources Information Center
Guevara, Porfirio
2014-01-01
This article identifies elements and connections that seem to be relevant to explain persistent aggregate behavioral patterns in educational systems when using complex dynamical systems modeling and simulation approaches. Several studies have shown what factors are at play in educational fields, but confusion still remains about the underlying…
Design of a framework for modeling, integration and simulation of physiological models.
Erson, E Zeynep; Cavuşoğlu, M Cenk
2012-09-01
Multiscale modeling and integration of physiological models carry challenges due to the complex nature of physiological processes. High coupling within and among scales present a significant challenge in constructing and integrating multiscale physiological models. In order to deal with such challenges in a systematic way, there is a significant need for an information technology framework together with related analytical and computational tools that will facilitate integration of models and simulations of complex biological systems. Physiological Model Simulation, Integration and Modeling Framework (Phy-SIM) is an information technology framework providing the tools to facilitate development, integration and simulation of integrated models of human physiology. Phy-SIM brings software level solutions to the challenges raised by the complex nature of physiological systems. The aim of Phy-SIM, and this paper is to lay some foundation with the new approaches such as information flow and modular representation of the physiological models. The ultimate goal is to enhance the development of both the models and the integration approaches of multiscale physiological processes and thus this paper focuses on the design approaches that would achieve such a goal. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Uranium adsorption on weathered schist - Intercomparison of modeling approaches
Payne, T.E.; Davis, J.A.; Ochs, M.; Olin, M.; Tweed, C.J.
2004-01-01
Experimental data for uranium adsorption on a complex weathered rock were simulated by twelve modelling teams from eight countries using surface complexation (SC) models. This intercomparison was part of an international project to evaluate the present capabilities and limitations of SC models in representing sorption by geologic materials. The models were assessed in terms of their predictive ability, data requirements, number of optimised parameters, ability to simulate diverse chemical conditions and transferability to other substrates. A particular aim was to compare the generalised composite (GC) and component additivity (CA) approaches for modelling sorption by complex substrates. Both types of SC models showed a promising capability to simulate sorption data obtained across a range of chemical conditions. However, the models incorporated a wide variety of assumptions, particularly in terms of input parameters such as site densities and surface site types. Furthermore, the methods used to extrapolate the model simulations to different weathered rock samples collected at the same field site tended to be unsatisfactory. The outcome of this modelling exercise provides an overview of the present status of adsorption modelling in the context of radionuclide migration as practised in a number of countries worldwide.
NASA Astrophysics Data System (ADS)
Chang, Yong; Wu, Jichun; Jiang, Guanghui; Kang, Zhiqiang
2017-05-01
Conceptual models often suffer from the over-parameterization problem due to limited available data for the calibration. This leads to the problem of parameter nonuniqueness and equifinality, which may bring much uncertainty of the simulation result. How to find out the appropriate model structure supported by the available data to simulate the catchment is still a big challenge in the hydrological research. In this paper, we adopt a multi-model framework to identify the dominant hydrological process and appropriate model structure of a karst spring, located in Guilin city, China. For this catchment, the spring discharge is the only available data for the model calibration. This framework starts with a relative complex conceptual model according to the perception of the catchment and then this complex is simplified into several different models by gradually removing the model component. The multi-objective approach is used to compare the performance of these different models and the regional sensitivity analysis (RSA) is used to investigate the parameter identifiability. The results show this karst spring is mainly controlled by two different hydrological processes and one of the processes is threshold-driven which is consistent with the fieldwork investigation. However, the appropriate model structure to simulate the discharge of this spring is much simpler than the actual aquifer structure and hydrological processes understanding from the fieldwork investigation. A simple linear reservoir with two different outlets is enough to simulate this spring discharge. The detail runoff process in the catchment is not needed in the conceptual model to simulate the spring discharge. More complex model should need more other additional data to avoid serious deterioration of model predictions.
Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.
Kalton, Alan; Falconer, Erin; Docherty, John; Alevras, Dimitris; Brann, David; Johnson, Kyle
2016-02-01
This paper discusses the creation of an Agent-Based Simulation that modeled the introduction of care coordination capabilities into a complex system of care for patients with Serious and Persistent Mental Illness. The model describes the engagement between patients and the medical, social and criminal justice services they interact with in a complex ecosystem of care. We outline the challenges involved in developing the model, including process mapping and the collection and synthesis of data to support parametric estimates, and describe the controls built into the model to support analysis of potential changes to the system. We also describe the approach taken to calibrate the model to an observable level of system performance. Preliminary results from application of the simulation are provided to demonstrate how it can provide insights into potential improvements deriving from introduction of care coordination technology.
Nguyen, Hai; Pérez, Alberto; Bermeo, Sherry; Simmerling, Carlos
2016-01-01
The Generalized Born (GB) implicit solvent model has undergone significant improvements in accuracy for modeling of proteins and small molecules. However, GB still remains a less widely explored option for nucleic acid simulations, in part because fast GB models are often unable to maintain stable nucleic acid structures, or they introduce structural bias in proteins, leading to difficulty in application of GB models in simulations of protein-nucleic acid complexes. Recently, GB-neck2 was developed to improve the behavior of protein simulations. In an effort to create a more accurate model for nucleic acids, a similar procedure to the development of GB-neck2 is described here for nucleic acids. The resulting parameter set significantly reduces absolute and relative energy error relative to Poisson Boltzmann for both nucleic acids and nucleic acid-protein complexes, when compared to its predecessor GB-neck model. This improvement in solvation energy calculation translates to increased structural stability for simulations of DNA and RNA duplexes, quadruplexes, and protein-nucleic acid complexes. The GB-neck2 model also enables successful folding of small DNA and RNA hairpins to near native structures as determined from comparison with experiment. The functional form and all required parameters are provided here and also implemented in the AMBER software. PMID:26574454
Three-dimensional curved grid finite-difference modelling for non-planar rupture dynamics
NASA Astrophysics Data System (ADS)
Zhang, Zhenguo; Zhang, Wei; Chen, Xiaofei
2014-11-01
In this study, we present a new method for simulating the 3-D dynamic rupture process occurring on a non-planar fault. The method is based on the curved-grid finite-difference method (CG-FDM) proposed by Zhang & Chen and Zhang et al. to simulate the propagation of seismic waves in media with arbitrary irregular surface topography. While keeping the advantages of conventional FDM, that is computational efficiency and easy implementation, the CG-FDM also is flexible in modelling the complex fault model by using general curvilinear grids, and thus is able to model the rupture dynamics of a fault with complex geometry, such as oblique dipping fault, non-planar fault, fault with step-over, fault branching, even if irregular topography exists. The accuracy and robustness of this new method have been validated by comparing with the previous results of Day et al., and benchmarks for rupture dynamics simulations. Finally, two simulations of rupture dynamics with complex fault geometry, that is a non-planar fault and a fault rupturing a free surface with topography, are presented. A very interesting phenomenon was observed that topography can weaken the tendency for supershear transition to occur when rupture breaks out at a free surface. Undoubtedly, this new method provides an effective, at least an alternative, tool to simulate the rupture dynamics of a complex non-planar fault, and can be applied to model the rupture dynamics of a real earthquake with complex geometry.
The Role of Simulation in Microsurgical Training.
Evgeniou, Evgenios; Walker, Harriet; Gujral, Sameer
Simulation has been established as an integral part of microsurgical training. The aim of this study was to assess and categorize the various simulation models in relation to the complexity of the microsurgical skill being taught and analyze the assessment methods commonly employed in microsurgical simulation training. Numerous courses have been established using simulation models. These models can be categorized, according to the level of complexity of the skill being taught, into basic, intermediate, and advanced. Microsurgical simulation training should be assessed using validated assessment methods. Assessment methods vary significantly from subjective expert opinions to self-assessment questionnaires and validated global rating scales. The appropriate assessment method should carefully be chosen based on the simulation modality. Simulation models should be validated, and a model with appropriate fidelity should be chosen according to the microsurgical skill being taught. Assessment should move from traditional simple subjective evaluations of trainee performance to validated tools. Future studies should assess the transferability of skills gained during simulation training to the real-life setting. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.
Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen
DOE Office of Scientific and Technical Information (OSTI.GOV)
Plechac, Petr; Vlachos, Dionisios; Katsoulakis, Markos
2013-09-05
The overall objective of this project is to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals. Specific goals include: (i) Development of rigorous spatio-temporal coarse-grained kinetic Monte Carlo (KMC) mathematics and simulation for microscopic processes encountered in biomassmore » transformation. (ii) Development of hybrid multiscale simulation that links stochastic simulation to a deterministic partial differential equation (PDE) model for an entire reactor. (iii) Development of hybrid multiscale simulation that links KMC simulation with quantum density functional theory (DFT) calculations. (iv) Development of parallelization of models of (i)-(iii) to take advantage of Petaflop computing and enable real world applications of complex, multiscale models. In this NCE period, we continued addressing these objectives and completed the proposed work. Main initiatives, key results, and activities are outlined.« less
Physics-based statistical model and simulation method of RF propagation in urban environments
Pao, Hsueh-Yuan; Dvorak, Steven L.
2010-09-14
A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.
NASA Astrophysics Data System (ADS)
Ravazzani, G.; Montaldo, N.; Mancini, M.; Rosso, R.
2003-04-01
Event-based hydrologic models need the antecedent soil moisture condition, as critical boundary initial condition for flood simulation. Land-surface models (LSMs) have been developed to simulate mass and energy transfers, and to update the soil moisture condition through time from the solution of water and energy balance equations. They are recently used in distributed hydrologic modeling for flood prediction systems. Recent developments have made LSMs more complex by inclusion of more processes and controlling variables, increasing parameter number and uncertainty of their estimates. This also led to increasing of computational burden and parameterization of the distributed hydrologic models. In this study we investigate: 1) the role of soil moisture initial conditions in the modeling of Alpine basin floods; 2) the adequate complexity level of LSMs for the distributed hydrologic modeling of Alpine basin floods. The Toce basin is the case study; it is located in the North Piedmont (Italian Alps), and it has a total drainage area of 1534 km2 at Candoglia section. Three distributed hydrologic models of different level of complexity are developed and compared: two (TDLSM and SDLSM) are continuous models, one (FEST02) is an event model based on the simplified SCS-CN method for rainfall abstractions. In the TDLSM model a two-layer LSM computes both saturation and infiltration excess runoff, and simulates the evolution of the water table spatial distribution using the topographic index; in the SDLSM model a simplified one-layer distributed LSM only computes hortonian runoff, and doesn’t simulate the water table dynamic. All the three hydrologic models simulate the surface runoff propagation through the Muskingum-Cunge method. TDLSM and SDLSM models have been applied for the two-year (1996 and 1997) simulation period, during which two major floods occurred in the November 1996 and in the June 1997. The models have been calibrated and tested comparing simulated and observed hydrographs at Candoglia. Sensitivity analysis of the models to significant LSM parameters were also performed. The performances of the three models in the simulation of the two major floods are compared. Interestingly, the results indicate that the SDLSM model is able to sufficiently well predict the major floods of this Alpine basin; indeed, this model is a good compromise between the over-parameterized and too complex TDLSM model and the over-simplified FEST02 model.
NASA Technical Reports Server (NTRS)
Spinks, Debra (Compiler)
1997-01-01
This report contains the 1997 annual progress reports of the research fellows and students supported by the Center for Turbulence Research (CTR). Titles include: Invariant modeling in large-eddy simulation of turbulence; Validation of large-eddy simulation in a plain asymmetric diffuser; Progress in large-eddy simulation of trailing-edge turbulence and aeronautics; Resolution requirements in large-eddy simulations of shear flows; A general theory of discrete filtering for LES in complex geometry; On the use of discrete filters for large eddy simulation; Wall models in large eddy simulation of separated flow; Perspectives for ensemble average LES; Anisotropic grid-based formulas for subgrid-scale models; Some modeling requirements for wall models in large eddy simulation; Numerical simulation of 3D turbulent boundary layers using the V2F model; Accurate modeling of impinging jet heat transfer; Application of turbulence models to high-lift airfoils; Advances in structure-based turbulence modeling; Incorporating realistic chemistry into direct numerical simulations of turbulent non-premixed combustion; Effects of small-scale structure on turbulent mixing; Turbulent premixed combustion in the laminar flamelet and the thin reaction zone regime; Large eddy simulation of combustion instabilities in turbulent premixed burners; On the generation of vorticity at a free-surface; Active control of turbulent channel flow; A generalized framework for robust control in fluid mechanics; Combined immersed-boundary/B-spline methods for simulations of flow in complex geometries; and DNS of shock boundary-layer interaction - preliminary results for compression ramp flow.
Drawert, Brian; Engblom, Stefan; Hellander, Andreas
2012-06-22
Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. We have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at an early stage of development. In this paper we demonstrate, in a series of examples with high relevance to the molecular systems biology community, that the proposed software framework is a useful tool for both practitioners and developers of spatial stochastic simulation algorithms. Through the combined efforts of algorithm development and improved modeling accuracy, increasingly complex biological models become feasible to study through computational methods. URDME is freely available at http://www.urdme.org.
Koldsø, Heidi; Shorthouse, David; Hélie, Jean; Sansom, Mark S. P.
2014-01-01
Cell membranes are complex multicomponent systems, which are highly heterogeneous in the lipid distribution and composition. To date, most molecular simulations have focussed on relatively simple lipid compositions, helping to inform our understanding of in vitro experimental studies. Here we describe on simulations of complex asymmetric plasma membrane model, which contains seven different lipids species including the glycolipid GM3 in the outer leaflet and the anionic lipid, phosphatidylinositol 4,5-bisphophate (PIP2), in the inner leaflet. Plasma membrane models consisting of 1500 lipids and resembling the in vivo composition were constructed and simulations were run for 5 µs. In these simulations the most striking feature was the formation of nano-clusters of GM3 within the outer leaflet. In simulations of protein interactions within a plasma membrane model, GM3, PIP2, and cholesterol all formed favorable interactions with the model α-helical protein. A larger scale simulation of a model plasma membrane containing 6000 lipid molecules revealed correlations between curvature of the bilayer surface and clustering of lipid molecules. In particular, the concave (when viewed from the extracellular side) regions of the bilayer surface were locally enriched in GM3. In summary, these simulations explore the nanoscale dynamics of model bilayers which mimic the in vivo lipid composition of mammalian plasma membranes, revealing emergent nanoscale membrane organization which may be coupled both to fluctuations in local membrane geometry and to interactions with proteins. PMID:25340788
Koldsø, Heidi; Shorthouse, David; Hélie, Jean; Sansom, Mark S P
2014-10-01
Cell membranes are complex multicomponent systems, which are highly heterogeneous in the lipid distribution and composition. To date, most molecular simulations have focussed on relatively simple lipid compositions, helping to inform our understanding of in vitro experimental studies. Here we describe on simulations of complex asymmetric plasma membrane model, which contains seven different lipids species including the glycolipid GM3 in the outer leaflet and the anionic lipid, phosphatidylinositol 4,5-bisphophate (PIP2), in the inner leaflet. Plasma membrane models consisting of 1500 lipids and resembling the in vivo composition were constructed and simulations were run for 5 µs. In these simulations the most striking feature was the formation of nano-clusters of GM3 within the outer leaflet. In simulations of protein interactions within a plasma membrane model, GM3, PIP2, and cholesterol all formed favorable interactions with the model α-helical protein. A larger scale simulation of a model plasma membrane containing 6000 lipid molecules revealed correlations between curvature of the bilayer surface and clustering of lipid molecules. In particular, the concave (when viewed from the extracellular side) regions of the bilayer surface were locally enriched in GM3. In summary, these simulations explore the nanoscale dynamics of model bilayers which mimic the in vivo lipid composition of mammalian plasma membranes, revealing emergent nanoscale membrane organization which may be coupled both to fluctuations in local membrane geometry and to interactions with proteins.
ERIC Educational Resources Information Center
Markowitz, Dina; Holt, Susan
2011-01-01
Students use manipulative models and small-scale simulations that promote learning of complex biological concepts. The authors have developed inexpensive wet-lab simulations and manipulative models for "Diagnosing Diabetes," "A Kidney Problem?" and "A Medical Mystery." (Contains 5 figures and 3 online resources.)
NASA Astrophysics Data System (ADS)
Ye, L.; Wu, J.; Wang, L.; Song, T.; Ji, R.
2017-12-01
Flooding in small-scale watershed in hilly area is characterized by short time periods and rapid rise and recession due to the complex underlying surfaces, various climate type and strong effect of human activities. It is almost impossible for a single hydrological model to describe the variation of flooding in both time and space accurately for all the catchments in hilly area because the hydrological characteristics can vary significantly among different catchments. In this study, we compare the performance of 5 hydrological models with varying degrees of complexity for simulation of flash flood for 14 small-scale watershed in China in order to find the relationship between the applicability of the hydrological models and the catchments characteristics. Meanwhile, given the fact that the hydrological data is sparse in hilly area, the effect of precipitation data, DEM resolution and their interference on the uncertainty of flood simulation is also illustrated. In general, the results showed that the distributed hydrological model (HEC-HMS in this study) performed better than the lumped hydrological models. Xinajiang and API models had good simulation for the humid catchments when long-term and continuous rainfall data is provided. Dahuofang model can simulate the flood peak well while the runoff generation module is relatively poor. In addition, the effect of diverse modelling data on the simulations is not simply superposed, and there is a complex interaction effect among different modelling data. Overall, both the catchment hydrological characteristics and modelling data situation should be taken into consideration in order to choose the suitable hydrological model for flood simulation for small-scale catchment in hilly area.
NASA Astrophysics Data System (ADS)
Zhang, Yali; Wang, Jun
2017-09-01
In an attempt to investigate the nonlinear complex evolution of financial dynamics, a new financial price model - the multitype range-intensity contact (MRIC) financial model, is developed based on the multitype range-intensity interacting contact system, in which the interaction and transmission of different types of investment attitudes in a stock market are simulated by viruses spreading. Two new random visibility graph (VG) based analyses and Lempel-Ziv complexity (LZC) are applied to study the complex behaviors of return time series and the corresponding random sorted series. The VG method is the complex network theory, and the LZC is a non-parametric measure of complexity reflecting the rate of new pattern generation of a series. In this work, the real stock market indices are considered to be comparatively studied with the simulation data of the proposed model. Further, the numerical empirical study shows the similar complexity behaviors between the model and the real markets, the research confirms that the financial model is reasonable to some extent.
NASA Astrophysics Data System (ADS)
Hu, X.; Li, X.; Lu, L.
2017-12-01
Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.
Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks
Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.
2017-01-01
Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under increasing levels of neural complexity. PMID:28223930
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arion is a library and tool set that enables researchers to holistically define test system models. To define a complex system for testing an algorithm or control requires expertise across multiple domains. Simulating a complex system requires the integration of multiple simulators and test hardware, each with their own specification languages and concepts. This requires extensive set of knowledge and capabilities. Arion was developed to alleviate this challenge. Arion is a library of Java libraries that abstracts the concepts from supported simulators into a cohesive model language that allows someone to build models to their needed level of fidelity andmore » expertise. Arion is also a software tool that translates the users model back into the specification languages of the simulators and test hardware needed for execution.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aagesen, Larry K.; Coltrin, Michael Elliott; Han, Jung
Three-dimensional phase-field simulations of GaN growth by selective area epitaxy were performed. Furthermore, this model includes a crystallographic-orientation-dependent deposition rate and arbitrarily complex mask geometries. The orientation-dependent deposition rate can be determined from experimental measurements of the relative growth rates of low-index crystallographic facets. Growth on various complex mask geometries was simulated on both c-plane and a-plane template layers. Agreement was observed between simulations and experiment, including complex phenomena occurring at the intersections between facets. The sources of the discrepancies between simulated and experimental morphologies were also investigated. We found that the model provides a route to optimize masks andmore » processing conditions during materials synthesis for solar cells, light-emitting diodes, and other electronic and opto-electronic applications.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aagesen, Larry K.; Thornton, Katsuyo, E-mail: kthorn@umich.edu; Coltrin, Michael E.
Three-dimensional phase-field simulations of GaN growth by selective area epitaxy were performed. The model includes a crystallographic-orientation-dependent deposition rate and arbitrarily complex mask geometries. The orientation-dependent deposition rate can be determined from experimental measurements of the relative growth rates of low-index crystallographic facets. Growth on various complex mask geometries was simulated on both c-plane and a-plane template layers. Agreement was observed between simulations and experiment, including complex phenomena occurring at the intersections between facets. The sources of the discrepancies between simulated and experimental morphologies were also investigated. The model provides a route to optimize masks and processing conditions during materialsmore » synthesis for solar cells, light-emitting diodes, and other electronic and opto-electronic applications.« less
Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu
2005-01-01
Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...
Building an Open-source Simulation Platform of Acoustic Radiation Force-based Breast Elastography
Wang, Yu; Peng, Bo; Jiang, Jingfeng
2017-01-01
Ultrasound-based elastography including strain elastography (SE), acoustic radiation force Impulse (ARFI) imaging, point shear wave elastography (pSWE) and supersonic shear imaging (SSI) have been used to differentiate breast tumors among other clinical applications. The objective of this study is to extend a previously published virtual simulation platform built for ultrasound quasi-static breast elastography toward acoustic radiation force-based breast elastography. Consequently, the extended virtual breast elastography simulation platform can be used to validate image pixels with known underlying soft tissue properties (i.e. “ground truth”) in complex, heterogeneous media, enhancing confidence in elastographic image interpretations. The proposed virtual breast elastography system inherited four key components from the previously published virtual simulation platform: an ultrasound simulator (Field II), a mesh generator (Tetgen), a finite element solver (FEBio) and a visualization and data processing package (VTK). Using a simple message passing mechanism, functionalities have now been extended to acoustic radiation force-based elastography simulations. Examples involving three different numerical breast models with increasing complexity – one uniform model, one simple inclusion model and one virtual complex breast model derived from magnetic resonance imaging data, were used to demonstrate capabilities of this extended virtual platform. Overall, simulation results were compared with the published results. In the uniform model, the estimated shear wave speed (SWS) values were within 4% compared to the predetermined SWS values. In the simple inclusion and the complex breast models, SWS values of all hard inclusions in soft backgrounds were slightly underestimated, similar to what has been reported. The elastic contrast values and visual observation show that ARFI images have higher spatial resolution, while SSI images can provide higher inclusion-to-background contrast. In summary, our initial results were consistent with our expectations and what have been reported in the literature. The proposed (open-source) simulation platform can serve as a single gateway to perform many elastographic simulations in a transparent manner, thereby promoting collaborative developments. PMID:28075330
Kiraly, Laszlo; Tofeig, Magdi; Jha, Neerod Kumar; Talo, Haitham
2016-02-01
Three-dimensional (3D) printed prototypes of malformed hearts have been used for education, communication, presurgical planning and simulation. We present a case of a 5-month old infant with complex obstruction at the neoaortic to transverse arch and descending aortic junction following the neonatal modified Norwood-1 procedure for hypoplastic left heart syndrome. Digital 3D models were created from a routine 64-slice CT dataset; then life-size solid and magnified hollow models were printed with a 3D printer. The solid model provided further insights into details of the anatomy, whereas the surgical approach and steps of the operation were simulated on the hollow model. Intraoperative assessment confirmed the anatomical accuracy of the 3D models. The operation was performed in accordance with preoperative simulation: sliding autologous flaps achieved relief of the obstruction without additional patching. Knowledge gained from the models fundamentally contributed to successful outcome and improved patient safety. This case study presents an effective use of 3D models in exploring complex spatial relationship at the aortic arch and in simulation-based planning of the operative procedure. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.
Minimum-complexity helicopter simulation math model
NASA Technical Reports Server (NTRS)
Heffley, Robert K.; Mnich, Marc A.
1988-01-01
An example of a minimal complexity simulation helicopter math model is presented. Motivating factors are the computational delays, cost, and inflexibility of the very sophisticated math models now in common use. A helicopter model form is given which addresses each of these factors and provides better engineering understanding of the specific handling qualities features which are apparent to the simulator pilot. The technical approach begins with specification of features which are to be modeled, followed by a build up of individual vehicle components and definition of equations. Model matching and estimation procedures are given which enable the modeling of specific helicopters from basic data sources such as flight manuals. Checkout procedures are given which provide for total model validation. A number of possible model extensions and refinement are discussed. Math model computer programs are defined and listed.
Systematic coarse-grained modeling of complexation between small interfering RNA and polycations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wei, Zonghui; Luijten, Erik, E-mail: luijten@northwestern.edu; Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208
All-atom molecular dynamics simulations can provide insight into the properties of polymeric gene-delivery carriers by elucidating their interactions and detailed binding patterns with nucleic acids. However, to explore nanoparticle formation through complexation of these polymers and nucleic acids and study their behavior at experimentally relevant time and length scales, a reliable coarse-grained model is needed. Here, we systematically develop such a model for the complexation of small interfering RNA (siRNA) and grafted polyethyleneimine copolymers, a promising candidate for siRNA delivery. We compare the predictions of this model with all-atom simulations and demonstrate that it is capable of reproducing detailed bindingmore » patterns, charge characteristics, and water release kinetics. Since the coarse-grained model accelerates the simulations by one to two orders of magnitude, it will make it possible to quantitatively investigate nanoparticle formation involving multiple siRNA molecules and cationic copolymers.« less
Managing complexity in simulations of land surface and near-surface processes
Coon, Ethan T.; Moulton, J. David; Painter, Scott L.
2016-01-12
Increasing computing power and the growing role of simulation in Earth systems science have led to an increase in the number and complexity of processes in modern simulators. We present a multiphysics framework that specifies interfaces for coupled processes and automates weak and strong coupling strategies to manage this complexity. Process management is enabled by viewing the system of equations as a tree, where individual equations are associated with leaf nodes and coupling strategies with internal nodes. A dynamically generated dependency graph connects a variable to its dependencies, streamlining and automating model evaluation, easing model development, and ensuring models aremore » modular and flexible. Additionally, the dependency graph is used to ensure that data requirements are consistent between all processes in a given simulation. Here we discuss the design and implementation of these concepts within the Arcos framework, and demonstrate their use for verification testing and hypothesis evaluation in numerical experiments.« less
Modelling and Simulation as a Recognizing Method in Education
ERIC Educational Resources Information Center
Stoffa, Veronika
2004-01-01
Computer animation-simulation models of complex processes and events, which are the method of instruction, can be an effective didactic device. Gaining deeper knowledge about objects modelled helps to plan simulation experiments oriented on processes and events researched. Animation experiments realized on multimedia computers can aid easier…
Hulme, Adam; Thompson, Jason; Nielsen, Rasmus Oestergaard; Read, Gemma J M; Salmon, Paul M
2018-06-18
There have been recent calls for the application of the complex systems approach in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. Therefore, our objective was to use a computational modelling method and develop a dynamic simulation in sports injury research. Agent-based modelling (ABM) was used to model the occurrence of sports injury in a synthetic athlete population. The ABM was developed based on sports injury causal frameworks and was applied in the context of distance running-related injury (RRI). Using the acute:chronic workload ratio (ACWR), we simulated the dynamic relationship between changes in weekly running distance and RRI through the manipulation of various 'athlete management tools'. The findings confirmed that building weekly running distances over time, even within the reported ACWR 'sweet spot', will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a 'hard ceiling' dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads. The presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM and other simulation-based techniques could be considered as a complementary and alternative methodological approach in sports injury research. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Simulations of Sea Level Rise Effects on Complex Coastal Systems
NASA Astrophysics Data System (ADS)
Niedoroda, A. W.; Ye, M.; Saha, B.; Donoghue, J. F.; Reed, C. W.
2009-12-01
It is now established that complex coastal systems with elements such as beaches, inlets, bays, and rivers adjust their morphologies according to time-varying balances in between the processes that control the exchange of sediment. Accelerated sea level rise introduces a major perturbation into the sediment-sharing systems. A modeling framework based on a new SL-PR model which is an advanced version of the aggregate-scale CST Model and the event-scale CMS-2D and CMS-Wave combination have been used to simulate the recent evolution of a portion of the Florida panhandle coast. This combination of models provides a method to evaluate coefficients in the aggregate-scale model that were previously treated as fitted parameters. That is, by carrying out simulations of a complex coastal system with runs of the event-scale model representing more than a year it is now possible to directly relate the coefficients in the large-scale SL-PR model to measureable physical parameters in the current and wave fields. This cross-scale modeling procedure has been used to simulate the shoreline evolution at the Santa Rosa Island, a long barrier which houses significant military infrastructure at the north Gulf Coast. The model has been used to simulate 137 years of measured shoreline change and to extend these to predictions of future rates of shoreline migration.
An evaluation of 3-D traffic simulation modeling capabilities
DOT National Transportation Integrated Search
2007-06-01
The use of 3D modeling in simulation has become the standard for both the military and private sector. Compared to physical models, 3D models are more affordable, more flexible, and can incorporate complex operations. Unlike a physical model, a dynam...
Chimaera simulation of complex states of flowing matter
2016-01-01
We discuss a unified mesoscale framework (chimaera) for the simulation of complex states of flowing matter across scales of motion. The chimaera framework can deal with each of the three macro–meso–micro levels through suitable ‘mutations’ of the basic mesoscale formulation. The idea is illustrated through selected simulations of complex micro- and nanoscale flows. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698031
NASA Astrophysics Data System (ADS)
Cronkite-Ratcliff, C.; Phelps, G. A.; Boucher, A.
2011-12-01
In many geologic settings, the pathways of groundwater flow are controlled by geologic heterogeneities which have complex geometries. Models of these geologic heterogeneities, and consequently, their effects on the simulated pathways of groundwater flow, are characterized by uncertainty. Multiple-point geostatistics, which uses a training image to represent complex geometric descriptions of geologic heterogeneity, provides a stochastic approach to the analysis of geologic uncertainty. Incorporating multiple-point geostatistics into numerical models provides a way to extend this analysis to the effects of geologic uncertainty on the results of flow simulations. We present two case studies to demonstrate the application of multiple-point geostatistics to numerical flow simulation in complex geologic settings with both static and dynamic conditioning data. Both cases involve the development of a training image from a complex geometric description of the geologic environment. Geologic heterogeneity is modeled stochastically by generating multiple equally-probable realizations, all consistent with the training image. Numerical flow simulation for each stochastic realization provides the basis for analyzing the effects of geologic uncertainty on simulated hydraulic response. The first case study is a hypothetical geologic scenario developed using data from the alluvial deposits in Yucca Flat, Nevada. The SNESIM algorithm is used to stochastically model geologic heterogeneity conditioned to the mapped surface geology as well as vertical drill-hole data. Numerical simulation of groundwater flow and contaminant transport through geologic models produces a distribution of hydraulic responses and contaminant concentration results. From this distribution of results, the probability of exceeding a given contaminant concentration threshold can be used as an indicator of uncertainty about the location of the contaminant plume boundary. The second case study considers a characteristic lava-flow aquifer system in Pahute Mesa, Nevada. A 3D training image is developed by using object-based simulation of parametric shapes to represent the key morphologic features of rhyolite lava flows embedded within ash-flow tuffs. In addition to vertical drill-hole data, transient pressure head data from aquifer tests can be used to constrain the stochastic model outcomes. The use of both static and dynamic conditioning data allows the identification of potential geologic structures that control hydraulic response. These case studies demonstrate the flexibility of the multiple-point geostatistics approach for considering multiple types of data and for developing sophisticated models of geologic heterogeneities that can be incorporated into numerical flow simulations.
ERIC Educational Resources Information Center
Swaak, Janine; And Others
In this study, learners worked with a simulation of harmonic oscillation. Two supportive measures were introduced: model progression and assignments. In model progression, the model underlying the simulation is not offered in its full complexity from the start, but variables are gradually introduced. Assignments are small exercises that help the…
[Design of Complex Cavity Structure in Air Route System of Automated Peritoneal Dialysis Machine].
Quan, Xiaoliang
2017-07-30
This paper introduced problems about Automated Peritoneal Dialysis machine(APD) that the lack of technical issues such as the structural design of the complex cavities. To study the flow characteristics of this special structure, the application of ANSYS CFX software is used with k-ε turbulence model as the theoretical basis of fluid mechanics. The numerical simulation of flow field simulation result in the internal model can be gotten after the complex structure model is imported into ANSYS CFX module. Then, it will present the distribution of complex cavities inside the flow field and the flow characteristics parameter, which will provide an important reference design for APD design.
A finite element model of rigid body structures actuated by dielectric elastomer actuators
NASA Astrophysics Data System (ADS)
Simone, F.; Linnebach, P.; Rizzello, G.; Seelecke, S.
2018-06-01
This paper presents on finite element (FE) modeling and simulation of dielectric elastomer actuators (DEAs) coupled with articulated structures. DEAs have proven to represent an effective transduction technology for the realization of large deformation, low-power consuming, and fast mechatronic actuators. However, the complex dynamic behavior of the material, characterized by nonlinearities and rate-dependent phenomena, makes it difficult to accurately model and design DEA systems. The problem is further complicated in case the DEA is used to activate articulated structures, which increase both system complexity and implementation effort of numerical simulation models. In this paper, we present a model based tool which allows to effectively implement and simulate complex articulated systems actuated by DEAs. A first prototype of a compact switch actuated by DEA membranes is chosen as reference study to introduce the methodology. The commercially available FE software COMSOL is used for implementing and coupling a physics-based dynamic model of the DEA with the external structure, i.e., the switch. The model is then experimentally calibrated and validated in both quasi-static and dynamic loading conditions. Finally, preliminary results on how to use the simulation tool to optimize the design are presented.
A novel medical image data-based multi-physics simulation platform for computational life sciences.
Neufeld, Esra; Szczerba, Dominik; Chavannes, Nicolas; Kuster, Niels
2013-04-06
Simulating and modelling complex biological systems in computational life sciences requires specialized software tools that can perform medical image data-based modelling, jointly visualize the data and computational results, and handle large, complex, realistic and often noisy anatomical models. The required novel solvers must provide the power to model the physics, biology and physiology of living tissue within the full complexity of the human anatomy (e.g. neuronal activity, perfusion and ultrasound propagation). A multi-physics simulation platform satisfying these requirements has been developed for applications including device development and optimization, safety assessment, basic research, and treatment planning. This simulation platform consists of detailed, parametrized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a visualization toolkit-based visualization engine, a Python scripting interface for customized applications, a coupling framework, and more. Core components are cross-platform compatible and use open formats. Several examples of applications are presented: hyperthermia cancer treatment planning, tumour growth modelling, evaluating the magneto-haemodynamic effect as a biomarker and physics-based morphing of anatomical models.
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.
Hettinger, Lawrence J.; Kirlik, Alex; Goh, Yang Miang; Buckle, Peter
2015-01-01
Accurate comprehension and analysis of complex sociotechnical systems is a daunting task. Empirically examining, or simply envisioning the structure and behaviour of such systems challenges traditional analytic and experimental approaches as well as our everyday cognitive capabilities. Computer-based models and simulations afford potentially useful means of accomplishing sociotechnical system design and analysis objectives. From a design perspective, they can provide a basis for a common mental model among stakeholders, thereby facilitating accurate comprehension of factors impacting system performance and potential effects of system modifications. From a research perspective, models and simulations afford the means to study aspects of sociotechnical system design and operation, including the potential impact of modifications to structural and dynamic system properties, in ways not feasible with traditional experimental approaches. This paper describes issues involved in the design and use of such models and simulations and describes a proposed path forward to their development and implementation. Practitioner Summary: The size and complexity of real-world sociotechnical systems can present significant barriers to their design, comprehension and empirical analysis. This article describes the potential advantages of computer-based models and simulations for understanding factors that impact sociotechnical system design and operation, particularly with respect to process and occupational safety. PMID:25761227
Structure and dynamics of complex liquid water: Molecular dynamics simulation
NASA Astrophysics Data System (ADS)
S, Indrajith V.; Natesan, Baskaran
2015-06-01
We have carried out detailed structure and dynamical studies of complex liquid water using molecular dynamics simulations. Three different model potentials, namely, TIP3P, TIP4P and SPC-E have been used in the simulations, in order to arrive at the best possible potential function that could reproduce the structure of experimental bulk water. All the simulations were performed in the NVE micro canonical ensemble using LAMMPS. The radial distribution functions, gOO, gOH and gHH and the self diffusion coefficient, Ds, were calculated for all three models. We conclude from our results that the structure and dynamical parameters obtained for SPC-E model matched well with the experimental values, suggesting that among the models studied here, the SPC-E model gives the best structure and dynamics of bulk water.
Schryver, Jack; Nutaro, James; Shankar, Mallikarjun
2015-10-30
An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schryver, Jack; Nutaro, James; Shankar, Mallikarjun
An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less
Nesting large-eddy simulations within mesoscale simulations for wind energy applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lundquist, J K; Mirocha, J D; Chow, F K
2008-09-08
With increasing demand for more accurate atmospheric simulations for wind turbine micrositing, for operational wind power forecasting, and for more reliable turbine design, simulations of atmospheric flow with resolution of tens of meters or higher are required. These time-dependent large-eddy simulations (LES), which resolve individual atmospheric eddies on length scales smaller than turbine blades and account for complex terrain, are possible with a range of commercial and open-source software, including the Weather Research and Forecasting (WRF) model. In addition to 'local' sources of turbulence within an LES domain, changing weather conditions outside the domain can also affect flow, suggesting thatmore » a mesoscale model provide boundary conditions to the large-eddy simulations. Nesting a large-eddy simulation within a mesoscale model requires nuanced representations of turbulence. Our group has improved the Weather and Research Forecasting model's (WRF) LES capability by implementing the Nonlinear Backscatter and Anisotropy (NBA) subfilter stress model following Kosovic (1997) and an explicit filtering and reconstruction technique to compute the Resolvable Subfilter-Scale (RSFS) stresses (following Chow et al, 2005). We have also implemented an immersed boundary method (IBM) in WRF to accommodate complex terrain. These new models improve WRF's LES capabilities over complex terrain and in stable atmospheric conditions. We demonstrate approaches to nesting LES within a mesoscale simulation for farms of wind turbines in hilly regions. Results are sensitive to the nesting method, indicating that care must be taken to provide appropriate boundary conditions, and to allow adequate spin-up of turbulence in the LES domain.« less
Retkute, Renata; Townsend, Alexandra J; Murchie, Erik H; Jensen, Oliver E; Preston, Simon P
2018-05-25
Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the complex ways that photosynthesis responds to changes in light intensity. Current methods to characterize light dynamics, such as ray-tracing, are able to produce data with excellent spatio-temporal resolution but are computationally intensive and the resulting data are complex and high-dimensional. This necessitates development of more economical models for summarizing the data and for simulating realistic light patterns over the course of a day. High-resolution reconstructions of field-grown plants are assembled in various configurations to form canopies, and a forward ray-tracing algorithm is applied to the canopies to compute light dynamics at high (1 min) temporal resolution. From the ray-tracer output, the sunlit or shaded state for each patch on the plants is determined, and these data are used to develop a novel stochastic model for the sunlit-shaded patterns. The model is designed to be straightforward to fit to data using maximum likelihood estimation, and fast to simulate from. For a wide range of contrasting 3-D canopies, the stochastic model is able to summarize, and replicate in simulations, key features of the light dynamics. When light patterns simulated from the stochastic model are used as input to a model of photoinhibition, the predicted reduction in carbon gain is similar to that from calculations based on the (extremely costly) ray-tracer data. The model provides a way to summarize highly complex data in a small number of parameters, and a cost-effective way to simulate realistic light patterns. Simulations from the model will be particularly useful for feeding into larger-scale photosynthesis models for calculating how light dynamics affects the photosynthetic productivity of canopies.
Simulation-based modeling of building complexes construction management
NASA Astrophysics Data System (ADS)
Shepelev, Aleksandr; Severova, Galina; Potashova, Irina
2018-03-01
The study reported here examines the experience in the development and implementation of business simulation games based on network planning and management of high-rise construction. Appropriate network models of different types and levels of detail have been developed; a simulation model including 51 blocks (11 stages combined in 4 units) is proposed.
Tutorial: Parallel Computing of Simulation Models for Risk Analysis.
Reilly, Allison C; Staid, Andrea; Gao, Michael; Guikema, Seth D
2016-10-01
Simulation models are widely used in risk analysis to study the effects of uncertainties on outcomes of interest in complex problems. Often, these models are computationally complex and time consuming to run. This latter point may be at odds with time-sensitive evaluations or may limit the number of parameters that are considered. In this article, we give an introductory tutorial focused on parallelizing simulation code to better leverage modern computing hardware, enabling risk analysts to better utilize simulation-based methods for quantifying uncertainty in practice. This article is aimed primarily at risk analysts who use simulation methods but do not yet utilize parallelization to decrease the computational burden of these models. The discussion is focused on conceptual aspects of embarrassingly parallel computer code and software considerations. Two complementary examples are shown using the languages MATLAB and R. A brief discussion of hardware considerations is located in the Appendix. © 2016 Society for Risk Analysis.
Efficient field-theoretic simulation of polymer solutions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Villet, Michael C.; Fredrickson, Glenn H., E-mail: ghf@mrl.ucsb.edu; Department of Materials, University of California, Santa Barbara, California 93106
2014-12-14
We present several developments that facilitate the efficient field-theoretic simulation of polymers by complex Langevin sampling. A regularization scheme using finite Gaussian excluded volume interactions is used to derive a polymer solution model that appears free of ultraviolet divergences and hence is well-suited for lattice-discretized field theoretic simulation. We show that such models can exhibit ultraviolet sensitivity, a numerical pathology that dramatically increases sampling error in the continuum lattice limit, and further show that this pathology can be eliminated by appropriate model reformulation by variable transformation. We present an exponential time differencing algorithm for integrating complex Langevin equations for fieldmore » theoretic simulation, and show that the algorithm exhibits excellent accuracy and stability properties for our regularized polymer model. These developments collectively enable substantially more efficient field-theoretic simulation of polymers, and illustrate the importance of simultaneously addressing analytical and numerical pathologies when implementing such computations.« less
Complex molecular assemblies at hand via interactive simulations.
Delalande, Olivier; Férey, Nicolas; Grasseau, Gilles; Baaden, Marc
2009-11-30
Studying complex molecular assemblies interactively is becoming an increasingly appealing approach to molecular modeling. Here we focus on interactive molecular dynamics (IMD) as a textbook example for interactive simulation methods. Such simulations can be useful in exploring and generating hypotheses about the structural and mechanical aspects of biomolecular interactions. For the first time, we carry out low-resolution coarse-grain IMD simulations. Such simplified modeling methods currently appear to be more suitable for interactive experiments and represent a well-balanced compromise between an important gain in computational speed versus a moderate loss in modeling accuracy compared to higher resolution all-atom simulations. This is particularly useful for initial exploration and hypothesis development for rare molecular interaction events. We evaluate which applications are currently feasible using molecular assemblies from 1900 to over 300,000 particles. Three biochemical systems are discussed: the guanylate kinase (GK) enzyme, the outer membrane protease T and the soluble N-ethylmaleimide-sensitive factor attachment protein receptors complex involved in membrane fusion. We induce large conformational changes, carry out interactive docking experiments, probe lipid-protein interactions and are able to sense the mechanical properties of a molecular model. Furthermore, such interactive simulations facilitate exploration of modeling parameters for method improvement. For the purpose of these simulations, we have developed a freely available software library called MDDriver. It uses the IMD protocol from NAMD and facilitates the implementation and application of interactive simulations. With MDDriver it becomes very easy to render any particle-based molecular simulation engine interactive. Here we use its implementation in the Gromacs software as an example. Copyright 2009 Wiley Periodicals, Inc.
Sachetto Oliveira, Rafael; Martins Rocha, Bernardo; Burgarelli, Denise; Meira, Wagner; Constantinides, Christakis; Weber Dos Santos, Rodrigo
2018-02-01
The use of computer models as a tool for the study and understanding of the complex phenomena of cardiac electrophysiology has attained increased importance nowadays. At the same time, the increased complexity of the biophysical processes translates into complex computational and mathematical models. To speed up cardiac simulations and to allow more precise and realistic uses, 2 different techniques have been traditionally exploited: parallel computing and sophisticated numerical methods. In this work, we combine a modern parallel computing technique based on multicore and graphics processing units (GPUs) and a sophisticated numerical method based on a new space-time adaptive algorithm. We evaluate each technique alone and in different combinations: multicore and GPU, multicore and GPU and space adaptivity, multicore and GPU and space adaptivity and time adaptivity. All the techniques and combinations were evaluated under different scenarios: 3D simulations on slabs, 3D simulations on a ventricular mouse mesh, ie, complex geometry, sinus-rhythm, and arrhythmic conditions. Our results suggest that multicore and GPU accelerate the simulations by an approximate factor of 33×, whereas the speedups attained by the space-time adaptive algorithms were approximately 48. Nevertheless, by combining all the techniques, we obtained speedups that ranged between 165 and 498. The tested methods were able to reduce the execution time of a simulation by more than 498× for a complex cellular model in a slab geometry and by 165× in a realistic heart geometry simulating spiral waves. The proposed methods will allow faster and more realistic simulations in a feasible time with no significant loss of accuracy. Copyright © 2017 John Wiley & Sons, Ltd.
Lionberger, Megan A.; Schoellhamer, David H.; Shellenbarger, Gregory; Orlando, James L.; Ganju, Neil K.
2007-01-01
This report documents the development and application of a box model to simulate water level, salinity, and temperature of the Alviso Salt Pond Complex in South San Francisco Bay. These ponds were purchased for restoration in 2003 and currently are managed by the U.S. Fish and Wildlife Service to maintain existing wildlife habitat and prevent a build up of salt during the development of a long-term restoration plan. The model was developed for the purpose of aiding pond managers during the current interim management period to achieve these goals. A previously developed box model of a salt pond, SPOOM, which calculates daily pond volume and salinity, was reconfigured to simulate multiple connected ponds and a temperature subroutine was added. The updated model simulates rainfall, evaporation, water flowing between the ponds and the adjacent tidal slough network, and water flowing from one pond to the next by gravity and pumps. Theoretical and measured relations between discharge and corresponding differences in water level are used to simulate most flows between ponds and between ponds and sloughs. The principle of conservation of mass is used to calculate daily pond volume and salinity. The model configuration includes management actions specified in the Interim Stewardship Plan for the ponds. The temperature subroutine calculates hourly net heat transfer to or from a pond resulting in a rise or drop in pond temperature and daily average, minimum, and maximum pond temperatures are recorded. Simulated temperature was compared with hourly measured data from pond 3 of the Napa?Sonoma Salt Pond Complex and monthly measured data from pond A14 of the Alviso Salt-Pond Complex. Comparison showed good agreement of measured and simulated pond temperature on the daily and monthly time scales.
Development and Application of a Simple Hydrogeomorphic Model for Headwater Catchments
We developed a catchment model based on a hydrogeomorphic concept that simulates discharge from channel-riparian complexes, zero-order basins (ZOB, basins ZB and FA), and hillslopes. Multitank models simulate ZOB and hillslope hydrological response, while kinematic wave models pr...
NASA Astrophysics Data System (ADS)
Zhang, Ning; Du, Yunsong; Miao, Shiguang; Fang, Xiaoyi
2016-08-01
The simulation performance over complex building clusters of a wind simulation model (Wind Information Field Fast Analysis model, WIFFA) in a micro-scale air pollutant dispersion model system (Urban Microscale Air Pollution dispersion Simulation model, UMAPS) is evaluated using various wind tunnel experimental data including the CEDVAL (Compilation of Experimental Data for Validation of Micro-Scale Dispersion Models) wind tunnel experiment data and the NJU-FZ experiment data (Nanjing University-Fang Zhuang neighborhood wind tunnel experiment data). The results show that the wind model can reproduce the vortexes triggered by urban buildings well, and the flow patterns in urban street canyons and building clusters can also be represented. Due to the complex shapes of buildings and their distributions, the simulation deviations/discrepancies from the measurements are usually caused by the simplification of the building shapes and the determination of the key zone sizes. The computational efficiencies of different cases are also discussed in this paper. The model has a high computational efficiency compared to traditional numerical models that solve the Navier-Stokes equations, and can produce very high-resolution (1-5 m) wind fields of a complex neighborhood scale urban building canopy (~ 1 km ×1 km) in less than 3 min when run on a personal computer.
Chimaera simulation of complex states of flowing matter.
Succi, S
2016-11-13
We discuss a unified mesoscale framework (chimaera) for the simulation of complex states of flowing matter across scales of motion. The chimaera framework can deal with each of the three macro-meso-micro levels through suitable 'mutations' of the basic mesoscale formulation. The idea is illustrated through selected simulations of complex micro- and nanoscale flows.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).
2009-11-01
dynamics of the complex predicted by multiple molecular dynamics simulations , and discuss further structural optimization to achieve better in vivo efficacy...complex with BoNTAe and the dynamics of the complex predicted by multiple molecular dynamics simulations (MMDSs). On the basis of the 3D model, we discuss...is unlimited whereas AHP exhibited 54% inhibition under the same conditions (Table 1). Computer Simulation Twenty different molecular dynamics
Effects of in-sewer processes: a stochastic model approach.
Vollertsen, J; Nielsen, A H; Yang, W; Hvitved-Jacobsen, T
2005-01-01
Transformations of organic matter, nitrogen and sulfur in sewers can be simulated taking into account the relevant transformation and transport processes. One objective of such simulation is the assessment and management of hydrogen sulfide formation and corrosion. Sulfide is formed in the biofilms and sediments of the water phase, but corrosion occurs on the moist surfaces of the sewer gas phase. Consequently, both phases and the transport of volatile substances between these phases must be included. Furthermore, wastewater composition and transformations in sewers are complex and subject to high, natural variability. This paper presents the latest developments of the WATS model concept, allowing integrated aerobic, anoxic and anaerobic simulation of the water phase and of gas phase processes. The resulting model is complex and with high parameter variability. An example applying stochastic modeling shows how this complexity and variability can be taken into account.
USER MANUAL FOR EXPRESS, THE EXAMS-PRZM EXPOSURE SIMULATION SHELL
The Environmental Fate and Effects Division (EFED) of EPA's Office of Pesticide Programs(OPP) uses a suite of ORD simulation models for the exposure analysis portion of regulatory risk assessments. These models (PRZM, EXAMS, AgDisp) are complex, process-based simulation codes tha...
Calibration of an Unsteady Groundwater Flow Model for a Complex, Strongly Heterogeneous Aquifer
NASA Astrophysics Data System (ADS)
Curtis, Z. K.; Liao, H.; Li, S. G.; Phanikumar, M. S.; Lusch, D.
2016-12-01
Modeling of groundwater systems characterized by complex three-dimensional structure and heterogeneity remains a significant challenge. Most of today's groundwater models are developed based on relatively simple conceptual representations in favor of model calibratibility. As more complexities are modeled, e.g., by adding more layers and/or zones, or introducing transient processes, more parameters have to be estimated and issues related to ill-posed groundwater problems and non-unique calibration arise. Here, we explore the use of an alternative conceptual representation for groundwater modeling that is fully three-dimensional and can capture complex 3D heterogeneity (both systematic and "random") without over-parameterizing the aquifer system. In particular, we apply Transition Probability (TP) geostatistics on high resolution borehole data from a water well database to characterize the complex 3D geology. Different aquifer material classes, e.g., `AQ' (aquifer material), `MAQ' (marginal aquifer material'), `PCM' (partially confining material), and `CM' (confining material), are simulated, with the hydraulic properties of each material type as tuning parameters during calibration. The TP-based approach is applied to simulate unsteady groundwater flow in a large, complex, and strongly heterogeneous glacial aquifer system in Michigan across multiple spatial and temporal scales. The resulting model is calibrated to observed static water level data over a time span of 50 years. The results show that the TP-based conceptualization enables much more accurate and robust calibration/simulation than that based on conventional deterministic layer/zone based conceptual representations.
High-fidelity meshes from tissue samples for diffusion MRI simulations.
Panagiotaki, Eleftheria; Hall, Matt G; Zhang, Hui; Siow, Bernard; Lythgoe, Mark F; Alexander, Daniel C
2010-01-01
This paper presents a method for constructing detailed geometric models of tissue microstructure for synthesizing realistic diffusion MRI data. We construct three-dimensional mesh models from confocal microscopy image stacks using the marching cubes algorithm. Random-walk simulations within the resulting meshes provide synthetic diffusion MRI measurements. Experiments optimise simulation parameters and complexity of the meshes to achieve accuracy and reproducibility while minimizing computation time. Finally we assess the quality of the synthesized data from the mesh models by comparison with scanner data as well as synthetic data from simple geometric models and simplified meshes that vary only in two dimensions. The results support the extra complexity of the three-dimensional mesh compared to simpler models although sensitivity to the mesh resolution is quite robust.
Scanlan, Adam B; Nguyen, Alex V; Ilina, Anna; Lasso, Andras; Cripe, Linnea; Jegatheeswaran, Anusha; Silvestro, Elizabeth; McGowan, Francis X; Mascio, Christopher E; Fuller, Stephanie; Spray, Thomas L; Cohen, Meryl S; Fichtinger, Gabor; Jolley, Matthew A
2018-03-01
Mastering the technical skills required to perform pediatric cardiac valve surgery is challenging in part due to limited opportunity for practice. Transformation of 3D echocardiographic (echo) images of congenitally abnormal heart valves to realistic physical models could allow patient-specific simulation of surgical valve repair. We compared materials, processes, and costs for 3D printing and molding of patient-specific models for visualization and surgical simulation of congenitally abnormal heart valves. Pediatric atrioventricular valves (mitral, tricuspid, and common atrioventricular valve) were modeled from transthoracic 3D echo images using semi-automated methods implemented as custom modules in 3D Slicer. Valve models were then both 3D printed in soft materials and molded in silicone using 3D printed "negative" molds. Using pre-defined assessment criteria, valve models were evaluated by congenital cardiac surgeons to determine suitability for simulation. Surgeon assessment indicated that the molded valves had superior material properties for the purposes of simulation compared to directly printed valves (p < 0.01). Patient-specific, 3D echo-derived molded valves are a step toward realistic simulation of complex valve repairs but require more time and labor to create than directly printed models. Patient-specific simulation of valve repair in children using such models may be useful for surgical training and simulation of complex congenital cases.
Ellis, Alicia M.; Garcia, Andres J.; Focks, Dana A.; Morrison, Amy C.; Scott, Thomas W.
2011-01-01
Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority. PMID:21813844
Fractional modeling of viscoelasticity in 3D cerebral arteries and aneurysms
NASA Astrophysics Data System (ADS)
Yu, Yue; Perdikaris, Paris; Karniadakis, George Em
2016-10-01
We develop efficient numerical methods for fractional order PDEs, and employ them to investigate viscoelastic constitutive laws for arterial wall mechanics. Recent simulations using one-dimensional models [1] have indicated that fractional order models may offer a more powerful alternative for modeling the arterial wall response, exhibiting reduced sensitivity to parametric uncertainties compared with the integer-calculus-based models. Here, we study three-dimensional (3D) fractional PDEs that naturally model the continuous relaxation properties of soft tissue, and for the first time employ them to simulate flow structure interactions for patient-specific brain aneurysms. To deal with the high memory requirements and in order to accelerate the numerical evaluation of hereditary integrals, we employ a fast convolution method [2] that reduces the memory cost to O (log (N)) and the computational complexity to O (Nlog (N)). Furthermore, we combine the fast convolution with high-order backward differentiation to achieve third-order time integration accuracy. We confirm that in 3D viscoelastic simulations, the integer order models strongly depends on the relaxation parameters, while the fractional order models are less sensitive. As an application to long-time simulations in complex geometries, we also apply the method to modeling fluid-structure interaction of a 3D patient-specific compliant cerebral artery with an aneurysm. Taken together, our findings demonstrate that fractional calculus can be employed effectively in modeling complex behavior of materials in realistic 3D time-dependent problems if properly designed efficient algorithms are employed to overcome the extra memory requirements and computational complexity associated with the non-local character of fractional derivatives.
Fractional modeling of viscoelasticity in 3D cerebral arteries and aneurysms
Perdikaris, Paris; Karniadakis, George Em
2017-01-01
We develop efficient numerical methods for fractional order PDEs, and employ them to investigate viscoelastic constitutive laws for arterial wall mechanics. Recent simulations using one-dimensional models [1] have indicated that fractional order models may offer a more powerful alternative for modeling the arterial wall response, exhibiting reduced sensitivity to parametric uncertainties compared with the integer-calculus-based models. Here, we study three-dimensional (3D) fractional PDEs that naturally model the continuous relaxation properties of soft tissue, and for the first time employ them to simulate flow structure interactions for patient-specific brain aneurysms. To deal with the high memory requirements and in order to accelerate the numerical evaluation of hereditary integrals, we employ a fast convolution method [2] that reduces the memory cost to O(log(N)) and the computational complexity to O(N log(N)). Furthermore, we combine the fast convolution with high-order backward differentiation to achieve third-order time integration accuracy. We confirm that in 3D viscoelastic simulations, the integer order models strongly depends on the relaxation parameters, while the fractional order models are less sensitive. As an application to long-time simulations in complex geometries, we also apply the method to modeling fluid–structure interaction of a 3D patient-specific compliant cerebral artery with an aneurysm. Taken together, our findings demonstrate that fractional calculus can be employed effectively in modeling complex behavior of materials in realistic 3D time-dependent problems if properly designed efficient algorithms are employed to overcome the extra memory requirements and computational complexity associated with the non-local character of fractional derivatives. PMID:29104310
NASA Astrophysics Data System (ADS)
de Vries, R.
2004-02-01
Electrostatic complexation of flexible polyanions with the whey proteins α-lactalbumin and β-lactoglobulin is studied using Monte Carlo simulations. The proteins are considered at their respective isoelectric points. Discrete charges on the model polyelectrolytes and proteins interact through Debye-Hückel potentials. Protein excluded volume is taken into account through a coarse-grained model of the protein shape. Consistent with experimental results, it is found that α-lactalbumin complexes much more strongly than β-lactoglobulin. For α-lactalbumin, strong complexation is due to localized binding to a single large positive "charge patch," whereas for β-lactoglobulin, weak complexation is due to diffuse binding to multiple smaller charge patches.
Evaluation of the new EMAC-SWIFT chemistry climate model
NASA Astrophysics Data System (ADS)
Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Rex, Markus
2016-04-01
It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Including atmospheric ozone chemistry into climate simulations is usually done by prescribing a climatological ozone field, by including a fast linear ozone scheme into the model or by using a climate model with complex interactive chemistry. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. Although interactive chemistry provides a realistic representation of atmospheric chemistry such model simulations are computationally very expensive and hence not suitable for ensemble simulations or simulations with multiple climate change scenarios. A new approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has recently been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. Here, we show first results of EMAC-SWIFT simulations and validate these against EMAC simulations using the complex interactive chemistry scheme MECCA, and against observations.
Hu, Jin; Wang, Jun
2015-06-01
In recent years, complex-valued recurrent neural networks have been developed and analysed in-depth in view of that they have good modelling performance for some applications involving complex-valued elements. In implementing continuous-time dynamical systems for simulation or computational purposes, it is quite necessary to utilize a discrete-time model which is an analogue of the continuous-time system. In this paper, we analyse a discrete-time complex-valued recurrent neural network model and obtain the sufficient conditions on its global exponential periodicity and exponential stability. Simulation results of several numerical examples are delineated to illustrate the theoretical results and an application on associative memory is also given. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ghosh, Soumik; Bhatla, R.; Mall, R. K.; Srivastava, Prashant K.; Sahai, A. K.
2018-03-01
Climate model faces considerable difficulties in simulating the rainfall characteristics of southwest summer monsoon. In this study, the dynamical downscaling of European Centre for Medium-Range Weather Forecast's (ECMWF's) ERA-Interim (EIN15) has been utilized for the simulation of Indian summer monsoon (ISM) through the Regional Climate Model version 4.3 (RegCM-4.3) over the South Asia Co-Ordinated Regional Climate Downscaling EXperiment (CORDEX) domain. The complexities of model simulation over a particular terrain are generally influenced by factors such as complex topography, coastal boundary, and lack of unbiased initial and lateral boundary conditions. In order to overcome some of these limitations, the RegCM-4.3 is employed for simulating the rainfall characteristics over the complex topographical conditions. For reliable rainfall simulation, implementations of numerous lower boundary conditions are forced in the RegCM-4.3 with specific horizontal grid resolution of 50 km over South Asia CORDEX domain. The analysis is considered for 30 years of climatological simulation of rainfall, outgoing longwave radiation (OLR), mean sea level pressure (MSLP), and wind with different vertical levels over the specified region. The dependency of model simulation with the forcing of EIN15 initial and lateral boundary conditions is used to understand the impact of simulated rainfall characteristics during different phases of summer monsoon. The results obtained from this study are used to evaluate the activity of initial conditions of zonal wind circulation speed, which causes an increase in the uncertainty of regional model output over the region under investigation. Further, the results showed that the EIN15 zonal wind circulation lacks sufficient speed over the specified region in a particular time, which was carried forward by the RegCM output and leads to a disrupted regional simulation in the climate model.
Stimulation from Simulation? A Teaching Model of Hillslope Hydrology for Use on Microcomputers.
ERIC Educational Resources Information Center
Burt, Tim; Butcher, Dave
1986-01-01
The design and use of a simple computer model which simulates a hillslope hydrology is described in a teaching context. The model shows a relatively complex environmental system can be constructed on the basis of a simple but realistic theory, thus allowing students to simulate the hydrological response of real hillslopes. (Author/TRS)
Becky K. Kerns; Miles A. Hemstrom; David Conklin; Gabriel I. Yospin; Bart Johnson; Dominique Bachelet; Scott Bridgham
2012-01-01
Understanding landscape vegetation dynamics often involves the use of scientifically-based modeling tools that are capable of testing alternative management scenarios given complex ecological, management, and social conditions. State-and-transition simulation model (STSM) frameworks and software such as PATH and VDDT are commonly used tools that simulate how landscapes...
The Diffusion Simulator - Teaching Geomorphic and Geologic Problems Visually.
ERIC Educational Resources Information Center
Gilbert, R.
1979-01-01
Describes a simple hydraulic simulator based on more complex models long used by engineers to develop approximate solutions. It allows students to visualize non-steady transfer, to apply a model to solve a problem, and to compare experimentally simulated information with calculated values. (Author/MA)
SIGMA--A Graphical Approach to Teaching Simulation.
ERIC Educational Resources Information Center
Schruben, Lee W.
1992-01-01
SIGMA (Simulation Graphical Modeling and Analysis) is a computer graphics environment for building, testing, and experimenting with discrete event simulation models on personal computers. It uses symbolic representations (computer animation) to depict the logic of large, complex discrete event systems for easier understanding and has proven itself…
New approaches in agent-based modeling of complex financial systems
NASA Astrophysics Data System (ADS)
Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei
2017-12-01
Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.
An ODE-Based Wall Model for Turbulent Flow Simulations
NASA Technical Reports Server (NTRS)
Berger, Marsha J.; Aftosmis, Michael J.
2017-01-01
Fully automated meshing for Reynolds-Averaged Navier-Stokes Simulations, Mesh generation for complex geometry continues to be the biggest bottleneck in the RANS simulation process; Fully automated Cartesian methods routinely used for inviscid simulations about arbitrarily complex geometry; These methods lack of an obvious & robust way to achieve near wall anisotropy; Goal: Extend these methods for RANS simulation without sacrificing automation, at an affordable cost; Note: Nothing here is limited to Cartesian methods, and much becomes simpler in a body-fitted setting.
Lattice Boltzmann simulations of immiscible displacement process with large viscosity ratios
NASA Astrophysics Data System (ADS)
Rao, Parthib; Schaefer, Laura
2017-11-01
Immiscible displacement is a key physical mechanism involved in enhanced oil recovery and carbon sequestration processes. This multiphase flow phenomenon involves a complex interplay of viscous, capillary, inertial and wettability effects. The lattice Boltzmann (LB) method is an accurate and efficient technique for modeling and simulating multiphase/multicomponent flows especially in complex flow configurations and media. In this presentation we present numerical simulation results of displacement process in thin long channels. The results are based on a new psuedo-potential multicomponent LB model with multiple relaxation time collision (MRT) model and explicit forcing scheme. We demonstrate that the proposed model is capable of accurately simulating the displacement process involving fluids with a wider range of viscosity ratios (>100) and which also leads to viscosity-independent interfacial tension and reduction of some important numerical artifacts.
High-resolution dust modelling over complex terrains in West Asia
NASA Astrophysics Data System (ADS)
Basart, S.; Vendrell, L.; Baldasano, J. M.
2016-12-01
The present work demonstrates the impact of model resolution in dust propagation in a complex terrain region such as West Asia. For this purpose, two simulations using the NMMB/BSC-Dust model are performed and analysed, one with a high horizontal resolution (at 0.03° × 0.03°) and one with a lower horizontal resolution (at 0.33° × 0.33°). Both model experiments cover two intense dust storms that occurred on 17-20 March 2012 as a consequence of strong northwesterly Shamal winds that spanned over thousands of kilometres in West Asia. The comparison with ground-based (surface weather stations and sunphotometers) and satellite aerosol observations (Aqua/MODIS and MSG/SEVIRI) shows that despite differences in the magnitude of the simulated dust concentrations, the model is able to reproduce these two dust outbreaks. Differences between both simulations on the dust spread rise on regional dust transport areas in south-western Saudi Arabia, Yemen and Oman. The complex orography in south-western Saudi Arabia, Yemen and Oman (with peaks higher than 3000 m) has an impact on the transported dust concentration fields over mountain regions. Differences between both model configurations are mainly associated to the channelization of the dust flow through valleys and the differences in the modelled altitude of the mountains that alters the meteorology and blocks the dust fronts limiting the dust transport. These results demonstrate how the dust prediction in the vicinity of complex terrains improves using high-horizontal resolution simulations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vögele, Martin; Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Frankfurt a. M.; Holm, Christian
2015-12-28
We present simulations of aqueous polyelectrolyte complexes with new MARTINI models for the charged polymers poly(styrene sulfonate) and poly(diallyldimethylammonium). Our coarse-grained polyelectrolyte models allow us to study large length and long time scales with regard to chemical details and thermodynamic properties. The results are compared to the outcomes of previous atomistic molecular dynamics simulations and verify that electrostatic properties are reproduced by our MARTINI coarse-grained approach with reasonable accuracy. Structural similarity between the atomistic and the coarse-grained results is indicated by a comparison between the pair radial distribution functions and the cumulative number of surrounding particles. Our coarse-grained models aremore » able to quantitatively reproduce previous findings like the correct charge compensation mechanism and a reduced dielectric constant of water. These results can be interpreted as the underlying reason for the stability of polyelectrolyte multilayers and complexes and validate the robustness of the proposed models.« less
Computer modeling describes gravity-related adaptation in cell cultures.
Alexandrov, Ludmil B; Alexandrova, Stoyana; Usheva, Anny
2009-12-16
Questions about the changes of biological systems in response to hostile environmental factors are important but not easy to answer. Often, the traditional description with differential equations is difficult due to the overwhelming complexity of the living systems. Another way to describe complex systems is by simulating them with phenomenological models such as the well-known evolutionary agent-based model (EABM). Here we developed an EABM to simulate cell colonies as a multi-agent system that adapts to hyper-gravity in starvation conditions. In the model, the cell's heritable characteristics are generated and transferred randomly to offspring cells. After a qualitative validation of the model at normal gravity, we simulate cellular growth in hyper-gravity conditions. The obtained data are consistent with previously confirmed theoretical and experimental findings for bacterial behavior in environmental changes, including the experimental data from the microgravity Atlantis and the Hypergravity 3000 experiments. Our results demonstrate that it is possible to utilize an EABM with realistic qualitative description to examine the effects of hypergravity and starvation on complex cellular entities.
Some Approaches to Modeling Complex Information Systems.
ERIC Educational Resources Information Center
Rao, V. Venkata; Zunde, Pranas
1982-01-01
Brief discussion of state-of-the-art of modeling complex information systems distinguishes between macrolevel and microlevel modeling of such systems. Network layout and hierarchical system models, simulation, information acquisition and dissemination, databases and information storage, and operating systems are described and assessed. Thirty-four…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Blaszczyk, Jaroslaw; Lu, Zhenwei; Li, Yue
2014-09-01
To understand the structural basis for the biochemical differences and further investigate the catalytic mechanism of DHNA, we have determined the structure of EcDHNA complexed with NP at 1.07-Å resolution [PDB:2O90], built an atomic model of EcDHNA complexed with the substrate DHNP, and performed molecular dynamics (MD) simulation analysis of the substrate complex. EcDHNA has the same fold as SaDHNA and also forms an octamer that consists of two tetramers, but the packing of one tetramer with the other is significantly different between the two enzymes. Furthermore, the structures reveal significant differences in the vicinity of the active site, particularlymore » in the loop that connects strands β3 and β4, mainly due to the substitution of nearby residues. The building of an atomic model of the complex of EcDHNA and the substrate DHNP and the MD simulation of the complex show that some of the hydrogen bonds between the substrate and the enzyme are persistent, whereas others are transient. The substrate binding model and MD simulation provide the molecular basis for the biochemical behaviors of the enzyme, including noncooperative substrate binding, indiscrimination of a pair of epimers as the substrates, proton wire switching during catalysis, and formation of epimerization product.« less
Modeling complexity in engineered infrastructure system: Water distribution network as an example
NASA Astrophysics Data System (ADS)
Zeng, Fang; Li, Xiang; Li, Ke
2017-02-01
The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.
Ranking streamflow model performance based on Information theory metrics
NASA Astrophysics Data System (ADS)
Martinez, Gonzalo; Pachepsky, Yakov; Pan, Feng; Wagener, Thorsten; Nicholson, Thomas
2016-04-01
The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic model evaluation and selection. We simulated 10-year streamflow time series in five watersheds located in Texas, North Carolina, Mississippi, and West Virginia. Eight model of different complexity were applied. The information-theory based metrics were obtained after representing the time series as strings of symbols where different symbols corresponded to different quantiles of the probability distribution of streamflow. The symbol alphabet was used. Three metrics were computed for those strings - mean information gain that measures the randomness of the signal, effective measure complexity that characterizes predictability and fluctuation complexity that characterizes the presence of a pattern in the signal. The observed streamflow time series has smaller information content and larger complexity metrics than the precipitation time series. Watersheds served as information filters and and streamflow time series were less random and more complex than the ones of precipitation. This is reflected the fact that the watershed acts as the information filter in the hydrologic conversion process from precipitation to streamflow. The Nash Sutcliffe efficiency metric increased as the complexity of models increased, but in many cases several model had this efficiency values not statistically significant from each other. In such cases, ranking models by the closeness of the information-theory based parameters in simulated and measured streamflow time series can provide an additional criterion for the evaluation of hydrologic model performance.
Dshell++: A Component Based, Reusable Space System Simulation Framework
NASA Technical Reports Server (NTRS)
Lim, Christopher S.; Jain, Abhinandan
2009-01-01
This paper describes the multi-mission Dshell++ simulation framework for high fidelity, physics-based simulation of spacecraft, robotic manipulation and mobility systems. Dshell++ is a C++/Python library which uses modern script driven object-oriented techniques to allow component reuse and a dynamic run-time interface for complex, high-fidelity simulation of spacecraft and robotic systems. The goal of the Dshell++ architecture is to manage the inherent complexity of physicsbased simulations while supporting component model reuse across missions. The framework provides several features that support a large degree of simulation configurability and usability.
Bai, Shuming; Song, Kai; Shi, Qiang
2015-05-21
Observations of oscillatory features in the 2D spectra of several photosynthetic complexes have led to diverged opinions on their origins, including electronic coherence, vibrational coherence, and vibronic coherence. In this work, effects of these different types of quantum coherence on ultrafast pump-probe polarization anisotropy are investigated and distinguished. We first simulate the isotropic pump-probe signal and anisotropy decay of the Fenna-Matthews-Olson (FMO) complex using a model with only electronic coherence at low temperature and obtain the same coherence time as in the previous experiment. Then, three model dimer systems with different prespecified quantum coherence are simulated, and the results show that their different spectral characteristics can be used to determine the type of coherence during the spectral process. Finally, we simulate model systems with different electronic-vibrational couplings and reveal the condition in which long time vibronic coherence can be observed in systems like the FMO complex.
A Novel DEM Approach to Simulate Block Propagation on Forested Slopes
NASA Astrophysics Data System (ADS)
Toe, David; Bourrier, Franck; Dorren, Luuk; Berger, Frédéric
2018-03-01
In order to model rockfall on forested slopes, we developed a trajectory rockfall model based on the discrete element method (DEM). This model is able to take the complex mechanical processes at work during an impact into account (large deformations, complex contact conditions) and can explicitly simulate block/soil, block/tree contacts as well as contacts between neighbouring trees. In this paper, we describe the DEM model developed and we use it to assess the protective effect of different types of forest. In addition, we compared it with a more classical rockfall simulation model. The results highlight that forests can significantly reduce rockfall hazard and that the spatial structure of coppice forests has to be taken into account in rockfall simulations in order to avoid overestimating the protective role of these forest structures against rockfall hazard. In addition, the protective role of the forests is mainly influenced by the basal area. Finally, the advantages and limitations of the DEM model were compared with classical rockfall modelling approaches.
Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model
NASA Astrophysics Data System (ADS)
Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran
2014-09-01
Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.
NASA Astrophysics Data System (ADS)
He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun
2015-06-01
Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.
Module-based multiscale simulation of angiogenesis in skeletal muscle
2011-01-01
Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529
NASA Astrophysics Data System (ADS)
Swallow, B.; Rigby, M. L.; Rougier, J.; Manning, A.; Thomson, D.; Webster, H. N.; Lunt, M. F.; O'Doherty, S.
2016-12-01
In order to understand underlying processes governing environmental and physical phenomena, a complex mathematical model is usually required. However, there is an inherent uncertainty related to the parameterisation of unresolved processes in these simulators. Here, we focus on the specific problem of accounting for uncertainty in parameter values in an atmospheric chemical transport model. Systematic errors introduced by failing to account for these uncertainties have the potential to have a large effect on resulting estimates in unknown quantities of interest. One approach that is being increasingly used to address this issue is known as emulation, in which a large number of forward runs of the simulator are carried out, in order to approximate the response of the output to changes in parameters. However, due to the complexity of some models, it is often unfeasible to run large numbers of training runs that is usually required for full statistical emulators of the environmental processes. We therefore present a simplified model reduction method for approximating uncertainties in complex environmental simulators without the need for very large numbers of training runs. We illustrate the method through an application to the Met Office's atmospheric transport model NAME. We show how our parameter estimation framework can be incorporated into a hierarchical Bayesian inversion, and demonstrate the impact on estimates of UK methane emissions, using atmospheric mole fraction data. We conclude that accounting for uncertainties in the parameterisation of complex atmospheric models is vital if systematic errors are to be minimized and all relevant uncertainties accounted for. We also note that investigations of this nature can prove extremely useful in highlighting deficiencies in the simulator that might otherwise be missed.
Rule-based spatial modeling with diffusing, geometrically constrained molecules.
Gruenert, Gerd; Ibrahim, Bashar; Lenser, Thorsten; Lohel, Maiko; Hinze, Thomas; Dittrich, Peter
2010-06-07
We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly.
Rule-based spatial modeling with diffusing, geometrically constrained molecules
2010-01-01
Background We suggest a new type of modeling approach for the coarse grained, particle-based spatial simulation of combinatorially complex chemical reaction systems. In our approach molecules possess a location in the reactor as well as an orientation and geometry, while the reactions are carried out according to a list of implicitly specified reaction rules. Because the reaction rules can contain patterns for molecules, a combinatorially complex or even infinitely sized reaction network can be defined. For our implementation (based on LAMMPS), we have chosen an already existing formalism (BioNetGen) for the implicit specification of the reaction network. This compatibility allows to import existing models easily, i.e., only additional geometry data files have to be provided. Results Our simulations show that the obtained dynamics can be fundamentally different from those simulations that use classical reaction-diffusion approaches like Partial Differential Equations or Gillespie-type spatial stochastic simulation. We show, for example, that the combination of combinatorial complexity and geometric effects leads to the emergence of complex self-assemblies and transportation phenomena happening faster than diffusion (using a model of molecular walkers on microtubules). When the mentioned classical simulation approaches are applied, these aspects of modeled systems cannot be observed without very special treatment. Further more, we show that the geometric information can even change the organizational structure of the reaction system. That is, a set of chemical species that can in principle form a stationary state in a Differential Equation formalism, is potentially unstable when geometry is considered, and vice versa. Conclusions We conclude that our approach provides a new general framework filling a gap in between approaches with no or rigid spatial representation like Partial Differential Equations and specialized coarse-grained spatial simulation systems like those for DNA or virus capsid self-assembly. PMID:20529264
Modeling and simulating networks of interdependent protein interactions.
Stöcker, Bianca K; Köster, Johannes; Zamir, Eli; Rahmann, Sven
2018-05-21
Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of these systems emerge not only from the protein interactions themselves but also from the dependencies between these interactions, as generated by allosteric effects or mutual exclusion due to steric hindrance. Therefore, formal models for integrating and utilizing information about interaction dependencies are of high interest. Here, we describe an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining constrained protein interaction networks ("constrained networks"). The construction of these networks is based on public interaction databases as well as text-mined information about interaction dependencies. We present an efficient data structure and algorithm to simulate protein complex formation in constrained networks. The efficiency of the model allows fast simulation and facilitates the analysis of many proteins in large networks. In addition, this approach enables the simulation of perturbation effects, such as knockout of single or multiple proteins and changes of protein concentrations. We illustrate how our model can be used to analyze a constrained human adhesome protein network, which is responsible for the formation of diverse and dynamic cell-matrix adhesion sites. By comparing protein complex formation under known interaction dependencies versus without dependencies, we investigate how these dependencies shape the resulting repertoire of protein complexes. Furthermore, our model enables investigating how the interplay of network topology with interaction dependencies influences the propagation of perturbation effects across a large biochemical system. Our simulation software CPINSim (for Constrained Protein Interaction Network Simulator) is available under the MIT license at http://github.com/BiancaStoecker/cpinsim and as a Bioconda package (https://bioconda.github.io).
NASA Astrophysics Data System (ADS)
Del Carpio R., Maikol; Hashemi, M. Javad; Mosqueda, Gilberto
2017-10-01
This study examines the performance of integration methods for hybrid simulation of large and complex structural systems in the context of structural collapse due to seismic excitations. The target application is not necessarily for real-time testing, but rather for models that involve large-scale physical sub-structures and highly nonlinear numerical models. Four case studies are presented and discussed. In the first case study, the accuracy of integration schemes including two widely used methods, namely, modified version of the implicit Newmark with fixed-number of iteration (iterative) and the operator-splitting (non-iterative) is examined through pure numerical simulations. The second case study presents the results of 10 hybrid simulations repeated with the two aforementioned integration methods considering various time steps and fixed-number of iterations for the iterative integration method. The physical sub-structure in these tests consists of a single-degree-of-freedom (SDOF) cantilever column with replaceable steel coupons that provides repeatable highlynonlinear behavior including fracture-type strength and stiffness degradations. In case study three, the implicit Newmark with fixed-number of iterations is applied for hybrid simulations of a 1:2 scale steel moment frame that includes a relatively complex nonlinear numerical substructure. Lastly, a more complex numerical substructure is considered by constructing a nonlinear computational model of a moment frame coupled to a hybrid model of a 1:2 scale steel gravity frame. The last two case studies are conducted on the same porotype structure and the selection of time steps and fixed number of iterations are closely examined in pre-test simulations. The generated unbalance forces is used as an index to track the equilibrium error and predict the accuracy and stability of the simulations.
Triple Value Simulation Model Fact Sheet
The Triple Value Simulation (3VS) is a high-level model that accounts for the complex relationships among economic, social and environmental systems in order to explore scenarios and solutions to improve the health of the Bay.
Comparison of AERMOD and CALPUFF models for simulating SO2 concentrations in a gas refinery.
Atabi, Farideh; Jafarigol, Farzaneh; Moattar, Faramarz; Nouri, Jafar
2016-09-01
In this study, concentration of SO2 from a gas refinery located in complex terrain was calculated by the steady-state, AERMOD model, and nonsteady-state CALPUFF model. First, in four seasons, SO2 concentrations emitted from 16 refinery stacks, in nine receptors, were obtained by field measurements, and then the performance of both models was evaluated. Then, the simulated results for SO2 ambient concentrations made by each model were compared with the results of the observed concentrations, and model results were compared among themselves. The evaluation of the two models to simulate SO2 concentrations was based on the statistical analysis and Q-Q plots. Review of statistical parameters and Q-Q plots has shown that, according to the evaluation of estimations made, performance of both models to simulate the concentration of SO2 in the region can be considered acceptable. The results showed the AERMOD composite ratio between simulated values made by models and the observed values in various receptors for all four average times is 0.72, whereas CALPUFF's ratio is 0.89. However, in the complex conditions of topography, CALPUFF offers better agreement with the observed concentrations.
Advanced EUV mask and imaging modeling
NASA Astrophysics Data System (ADS)
Evanschitzky, Peter; Erdmann, Andreas
2017-10-01
The exploration and optimization of image formation in partially coherent EUV projection systems with complex source shapes requires flexible, accurate, and efficient simulation models. This paper reviews advanced mask diffraction and imaging models for the highly accurate and fast simulation of EUV lithography systems, addressing important aspects of the current technical developments. The simulation of light diffraction from the mask employs an extended rigorous coupled wave analysis (RCWA) approach, which is optimized for EUV applications. In order to be able to deal with current EUV simulation requirements, several additional models are included in the extended RCWA approach: a field decomposition and a field stitching technique enable the simulation of larger complex structured mask areas. An EUV multilayer defect model including a database approach makes the fast and fully rigorous defect simulation and defect repair simulation possible. A hybrid mask simulation approach combining real and ideal mask parts allows the detailed investigation of the origin of different mask 3-D effects. The image computation is done with a fully vectorial Abbe-based approach. Arbitrary illumination and polarization schemes and adapted rigorous mask simulations guarantee a high accuracy. A fully vectorial sampling-free description of the pupil with Zernikes and Jones pupils and an optimized representation of the diffraction spectrum enable the computation of high-resolution images with high accuracy and short simulation times. A new pellicle model supports the simulation of arbitrary membrane stacks, pellicle distortions, and particles/defects on top of the pellicle. Finally, an extension for highly accurate anamorphic imaging simulations is included. The application of the models is demonstrated by typical use cases.
Roelker, Sarah A; Caruthers, Elena J; Baker, Rachel K; Pelz, Nicholas C; Chaudhari, Ajit M W; Siston, Robert A
2017-11-01
With more than 29,000 OpenSim users, several musculoskeletal models with varying levels of complexity are available to study human gait. However, how different model parameters affect estimated joint and muscle function between models is not fully understood. The purpose of this study is to determine the effects of four OpenSim models (Gait2392, Lower Limb Model 2010, Full-Body OpenSim Model, and Full Body Model 2016) on gait mechanics and estimates of muscle forces and activations. Using OpenSim 3.1 and the same experimental data for all models, six young adults were scaled in each model, gait kinematics were reproduced, and static optimization estimated muscle function. Simulated measures differed between models by up to 6.5° knee range of motion, 0.012 Nm/Nm peak knee flexion moment, 0.49 peak rectus femoris activation, and 462 N peak rectus femoris force. Differences in coordinate system definitions between models altered joint kinematics, influencing joint moments. Muscle parameter and joint moment discrepancies altered muscle activations and forces. Additional model complexity yielded greater error between experimental and simulated measures; therefore, this study suggests Gait2392 is a sufficient model for studying walking in healthy young adults. Future research is needed to determine which model(s) is best for tasks with more complex motion.
Simulation modeling for the health care manager.
Kennedy, Michael H
2009-01-01
This article addresses the use of simulation software to solve administrative problems faced by health care managers. Spreadsheet add-ins, process simulation software, and discrete event simulation software are available at a range of costs and complexity. All use the Monte Carlo method to realistically integrate probability distributions into models of the health care environment. Problems typically addressed by health care simulation modeling are facility planning, resource allocation, staffing, patient flow and wait time, routing and transportation, supply chain management, and process improvement.
The role of deleterious mutations in the stability of hybridogenetic water frog complexes
2014-01-01
Background Some species of water frogs originated from hybridization between different species. Such hybrid populations have a particular reproduction system called hybridogenesis. In this paper we consider the two species Pelophylax ridibundus and Pelophylax lessonae, and their hybrids Pelophylax esculentus. P. lessonae and P. esculentus form stable complexes (L-E complexes) in which P. esculentus are hemiclonal. In L-E complexes all the transmitted genomes by P. esculentus carry deleterious mutations which are lethal in homozygosity. Results We analyze, by means of an individual based computational model, L-E complexes. The results of simulations based on the model show that, by eliminating deleterious mutations, L-E complexes collapse. In addition, simulations show that particular female preferences can contribute to the diffusion of deleterious mutations among all P. esculentus frogs. Finally, simulations show how L-E complexes react to the introduction of translocated P. ridibundus. Conclusions The conclusions are the following: (i) deleterious mutations (combined with sexual preferences) strongly contribute to the stability of L-E complexes; (ii) female sexual choice can contribute to the diffusion of deleterious mutations; and (iii) the introduction of P. ridibundus can destabilize L-E complexes. PMID:24885008
Andrianakis, Ioannis; Vernon, Ian R.; McCreesh, Nicky; McKinley, Trevelyan J.; Oakley, Jeremy E.; Nsubuga, Rebecca N.; Goldstein, Michael; White, Richard G.
2015-01-01
Advances in scientific computing have allowed the development of complex models that are being routinely applied to problems in disease epidemiology, public health and decision making. The utility of these models depends in part on how well they can reproduce empirical data. However, fitting such models to real world data is greatly hindered both by large numbers of input and output parameters, and by long run times, such that many modelling studies lack a formal calibration methodology. We present a novel method that has the potential to improve the calibration of complex infectious disease models (hereafter called simulators). We present this in the form of a tutorial and a case study where we history match a dynamic, event-driven, individual-based stochastic HIV simulator, using extensive demographic, behavioural and epidemiological data available from Uganda. The tutorial describes history matching and emulation. History matching is an iterative procedure that reduces the simulator's input space by identifying and discarding areas that are unlikely to provide a good match to the empirical data. History matching relies on the computational efficiency of a Bayesian representation of the simulator, known as an emulator. Emulators mimic the simulator's behaviour, but are often several orders of magnitude faster to evaluate. In the case study, we use a 22 input simulator, fitting its 18 outputs simultaneously. After 9 iterations of history matching, a non-implausible region of the simulator input space was identified that was times smaller than the original input space. Simulator evaluations made within this region were found to have a 65% probability of fitting all 18 outputs. History matching and emulation are useful additions to the toolbox of infectious disease modellers. Further research is required to explicitly address the stochastic nature of the simulator as well as to account for correlations between outputs. PMID:25569850
Deep Drawing Simulations With Different Polycrystalline Models
NASA Astrophysics Data System (ADS)
Duchêne, Laurent; de Montleau, Pierre; Bouvier, Salima; Habraken, Anne Marie
2004-06-01
The goal of this research is to study the anisotropic material behavior during forming processes, represented by both complex yield loci and kinematic-isotropic hardening models. A first part of this paper describes the main concepts of the `Stress-strain interpolation' model that has been implemented in the non-linear finite element code Lagamine. This model consists of a local description of the yield locus based on the texture of the material through the full constraints Taylor's model. The texture evolution due to plastic deformations is computed throughout the FEM simulations. This `local yield locus' approach was initially linked to the classical isotropic Swift hardening law. Recently, a more complex hardening model was implemented: the physically-based microstructural model of Teodosiu. It takes into account intergranular heterogeneity due to the evolution of dislocation structures, that affects isotropic and kinematic hardening. The influence of the hardening model is compared to the influence of the texture evolution thanks to deep drawing simulations.
A Generic Multibody Parachute Simulation Model
NASA Technical Reports Server (NTRS)
Neuhaus, Jason Richard; Kenney, Patrick Sean
2006-01-01
Flight simulation of dynamic atmospheric vehicles with parachute systems is a complex task that is not easily modeled in many simulation frameworks. In the past, the performance of vehicles with parachutes was analyzed by simulations dedicated to parachute operations and were generally not used for any other portion of the vehicle flight trajectory. This approach required multiple simulation resources to completely analyze the performance of the vehicle. Recently, improved software engineering practices and increased computational power have allowed a single simulation to model the entire flight profile of a vehicle employing a parachute.
NASA Astrophysics Data System (ADS)
Choi, Eunsong
Computer simulations are an integral part of research in modern condensed matter physics; they serve as a direct bridge between theory and experiment by systemactically applying a microscopic model to a collection of particles that effectively imitate a macroscopic system. In this thesis, we study two very differnt condensed systems, namely complex fluids and frustrated magnets, primarily by simulating classical dynamics of each system. In the first part of the thesis, we focus on ionic liquids (ILs) and polymers--the two complementary classes of materials that can be combined to provide various unique properties. The properties of polymers/ILs systems, such as conductivity, viscosity, and miscibility, can be fine tuned by choosing an appropriate combination of cations, anions, and polymers. However, designing a system that meets a specific need requires a concrete understanding of physics and chemistry that dictates a complex interplay between polymers and ionic liquids. In this regard, molecular dynamics (MD) simulation is an efficient tool that provides a molecular level picture of such complex systems. We study the behavior of Poly (ethylene oxide) (PEO) and the imidazolium based ionic liquids, using MD simulations and statistical mechanics. We also discuss our efforts to develop reliable and efficient classical force-fields for PEO and the ionic liquids. The second part is devoted to studies on geometrically frustrated magnets. In particular, a microscopic model, which gives rise to an incommensurate spiral magnetic ordering observed in a pyrochlore antiferromagnet is investigated. The validation of the model is made via a comparison of the spin-wave spectra with the neutron scattering data. Since the standard Holstein-Primakoff method is difficult to employ in such a complex ground state structure with a large unit cell, we carry out classical spin dynamics simulations to compute spin-wave spectra directly from the Fourier transform of spin trajectories. We conclude the study by showing an excellent agreement between the simulation and the experiment.
Ludwig, T; Kern, P; Bongards, M; Wolf, C
2011-01-01
The optimization of relaxation and filtration times of submerged microfiltration flat modules in membrane bioreactors used for municipal wastewater treatment is essential for efficient plant operation. However, the optimization and control of such plants and their filtration processes is a challenging problem due to the underlying highly nonlinear and complex processes. This paper presents the use of genetic algorithms for this optimization problem in conjunction with a fully calibrated simulation model, as computational intelligence methods are perfectly suited to the nonconvex multi-objective nature of the optimization problems posed by these complex systems. The simulation model is developed and calibrated using membrane modules from the wastewater simulation software GPS-X based on the Activated Sludge Model No.1 (ASM1). Simulation results have been validated at a technical reference plant. They clearly show that filtration process costs for cleaning and energy can be reduced significantly by intelligent process optimization.
Thibault, J. C.; Roe, D. R.; Eilbeck, K.; Cheatham, T. E.; Facelli, J. C.
2015-01-01
Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data – both within the same organization and among different ones – remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations. PMID:26387907
Thibault, J C; Roe, D R; Eilbeck, K; Cheatham, T E; Facelli, J C
2015-01-01
Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data - both within the same organization and among different ones - remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations.
Application of Complex Adaptive Systems in Portfolio Management
ERIC Educational Resources Information Center
Su, Zheyuan
2017-01-01
Simulation-based methods are becoming a promising research tool in financial markets. A general Complex Adaptive System can be tailored to different application scenarios. Based on the current research, we built two models that would benefit portfolio management by utilizing Complex Adaptive Systems (CAS) in Agent-based Modeling (ABM) approach.…
de Vries, R
2004-02-15
Electrostatic complexation of flexible polyanions with the whey proteins alpha-lactalbumin and beta-lactoglobulin is studied using Monte Carlo simulations. The proteins are considered at their respective isoelectric points. Discrete charges on the model polyelectrolytes and proteins interact through Debye-Huckel potentials. Protein excluded volume is taken into account through a coarse-grained model of the protein shape. Consistent with experimental results, it is found that alpha-lactalbumin complexes much more strongly than beta-lactoglobulin. For alpha-lactalbumin, strong complexation is due to localized binding to a single large positive "charge patch," whereas for beta-lactoglobulin, weak complexation is due to diffuse binding to multiple smaller charge patches. Copyright 2004 American Institute of Physics
NASA Astrophysics Data System (ADS)
Azougagh, Yassine; Benhida, Khalid; Elfezazi, Said
2016-02-01
In this paper, the focus is on studying the performance of complex systems in a supply chain context by developing a structured modelling approach based on the methodology ASDI (Analysis, Specification, Design and Implementation) by combining the modelling by Petri nets and simulation using ARENA. The linear approach typically followed in conducting of this kind of problems has to cope with a difficulty of modelling due to the complexity and the number of parameters of concern. Therefore, the approach used in this work is able to structure modelling a way to cover all aspects of the performance study. The modelling structured approach is first introduced before being applied to the case of an industrial system in the field of phosphate. Results of the performance indicators obtained from the models developed, permitted to test the behaviour and fluctuations of this system and to develop improved models of the current situation. In addition, in this paper, it was shown how Arena software can be adopted to simulate complex systems effectively. The method in this research can be applied to investigate various improvements scenarios and their consequences before implementing them in reality.
Network model of bilateral power markets based on complex networks
NASA Astrophysics Data System (ADS)
Wu, Yang; Liu, Junyong; Li, Furong; Yan, Zhanxin; Zhang, Li
2014-06-01
The bilateral power transaction (BPT) mode becomes a typical market organization with the restructuring of electric power industry, the proper model which could capture its characteristics is in urgent need. However, the model is lacking because of this market organization's complexity. As a promising approach to modeling complex systems, complex networks could provide a sound theoretical framework for developing proper simulation model. In this paper, a complex network model of the BPT market is proposed. In this model, price advantage mechanism is a precondition. Unlike other general commodity transactions, both of the financial layer and the physical layer are considered in the model. Through simulation analysis, the feasibility and validity of the model are verified. At same time, some typical statistical features of BPT network are identified. Namely, the degree distribution follows the power law, the clustering coefficient is low and the average path length is a bit long. Moreover, the topological stability of the BPT network is tested. The results show that the network displays a topological robustness to random market member's failures while it is fragile against deliberate attacks, and the network could resist cascading failure to some extent. These features are helpful for making decisions and risk management in BPT markets.
Project 0-1800 : NAFTA impacts on operations : executive summary
DOT National Transportation Integrated Search
2001-07-01
Project 0-1800 pioneered the use of modern micro-simulation models to analyze the complex procedures involved in international border crossing in Texas. Animated models simulate the entire southbound commercial traffic flow in two important internati...
A General Linear Model (GLM) was used to evaluate the deviation of predicted values from expected values for a complex environmental model. For this demonstration, we used the default level interface of the Regional Mercury Cycling Model (R-MCM) to simulate epilimnetic total mer...
Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas
2016-01-01
Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.
Research on complex 3D tree modeling based on L-system
NASA Astrophysics Data System (ADS)
Gang, Chen; Bin, Chen; Yuming, Liu; Hui, Li
2018-03-01
L-system as a fractal iterative system could simulate complex geometric patterns. Based on the field observation data of trees and knowledge of forestry experts, this paper extracted modeling constraint rules and obtained an L-system rules set. Using the self-developed L-system modeling software the L-system rule set was parsed to generate complex tree 3d models.The results showed that the geometrical modeling method based on l-system could be used to describe the morphological structure of complex trees and generate 3D tree models.
Second Generation Crop Yield Models Review
NASA Technical Reports Server (NTRS)
Hodges, T. (Principal Investigator)
1982-01-01
Second generation yield models, including crop growth simulation models and plant process models, may be suitable for large area crop yield forecasting in the yield model development project. Subjective and objective criteria for model selection are defined and models which might be selected are reviewed. Models may be selected to provide submodels as input to other models; for further development and testing; or for immediate testing as forecasting tools. A plant process model may range in complexity from several dozen submodels simulating (1) energy, carbohydrates, and minerals; (2) change in biomass of various organs; and (3) initiation and development of plant organs, to a few submodels simulating key physiological processes. The most complex models cannot be used directly in large area forecasting but may provide submodels which can be simplified for inclusion into simpler plant process models. Both published and unpublished models which may be used for development or testing are reviewed. Several other models, currently under development, may become available at a later date.
O'Donnell, Michael
2015-01-01
State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf
The QuakeSim Project: Numerical Simulations for Active Tectonic Processes
NASA Technical Reports Server (NTRS)
Donnellan, Andrea; Parker, Jay; Lyzenga, Greg; Granat, Robert; Fox, Geoffrey; Pierce, Marlon; Rundle, John; McLeod, Dennis; Grant, Lisa; Tullis, Terry
2004-01-01
In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.
On validating remote sensing simulations using coincident real data
NASA Astrophysics Data System (ADS)
Wang, Mingming; Yao, Wei; Brown, Scott; Goodenough, Adam; van Aardt, Jan
2016-05-01
The remote sensing community often requires data simulation, either via spectral/spatial downsampling or through virtual, physics-based models, to assess systems and algorithms. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is one such first-principles, physics-based model for simulating imagery for a range of modalities. Complex simulation of vegetation environments subsequently has become possible, as scene rendering technology and software advanced. This in turn has created questions related to the validity of such complex models, with potential multiple scattering, bidirectional distribution function (BRDF), etc. phenomena that could impact results in the case of complex vegetation scenes. We selected three sites, located in the Pacific Southwest domain (Fresno, CA) of the National Ecological Observatory Network (NEON). These sites represent oak savanna, hardwood forests, and conifer-manzanita-mixed forests. We constructed corresponding virtual scenes, using airborne LiDAR and imaging spectroscopy data from NEON, ground-based LiDAR data, and field-collected spectra to characterize the scenes. Imaging spectroscopy data for these virtual sites then were generated using the DIRSIG simulation environment. This simulated imagery was compared to real AVIRIS imagery (15m spatial resolution; 12 pixels/scene) and NEON Airborne Observation Platform (AOP) data (1m spatial resolution; 180 pixels/scene). These tests were performed using a distribution-comparison approach for select spectral statistics, e.g., established the spectra's shape, for each simulated versus real distribution pair. The initial comparison results of the spectral distributions indicated that the shapes of spectra between the virtual and real sites were closely matched.
A View on Future Building System Modeling and Simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wetter, Michael
This chapter presents what a future environment for building system modeling and simulation may look like. As buildings continue to require increased performance and better comfort, their energy and control systems are becoming more integrated and complex. We therefore focus in this chapter on the modeling, simulation and analysis of building energy and control systems. Such systems can be classified as heterogeneous systems because they involve multiple domains, such as thermodynamics, fluid dynamics, heat and mass transfer, electrical systems, control systems and communication systems. Also, they typically involve multiple temporal and spatial scales, and their evolution can be described bymore » coupled differential equations, discrete equations and events. Modeling and simulating such systems requires a higher level of abstraction and modularisation to manage the increased complexity compared to what is used in today's building simulation programs. Therefore, the trend towards more integrated building systems is likely to be a driving force for changing the status quo of today's building simulation programs. Thischapter discusses evolving modeling requirements and outlines a path toward a future environment for modeling and simulation of heterogeneous building systems.A range of topics that would require many additional pages of discussion has been omitted. Examples include computational fluid dynamics for air and particle flow in and around buildings, people movement, daylight simulation, uncertainty propagation and optimisation methods for building design and controls. For different discussions and perspectives on the future of building modeling and simulation, we refer to Sahlin (2000), Augenbroe (2001) and Malkawi and Augenbroe (2004).« less
Large eddy simulation of a boundary layer with concave streamwise curvature
NASA Technical Reports Server (NTRS)
Lund, Thomas S.
1993-01-01
One of the most exciting recent developments in the field of large eddy simulation (LES) is the dynamic subgrid-scale model. The dynamic model concept is a general procedure for evaluating model constants by sampling a band of the smallest scales actually resolved in the simulation. To date, the procedure has been used primarily in conjunction with the Smagorinsky model. The dynamic procedure has the advantage that the value of the model constant need not be specified a priori, but rather is calculated as a function of space and time as the simulation progresses. This feature makes the dynamic model especially attractive for flows in complex geometries where it is difficult or impossible to calibrate model constants. The dynamic model was highly successful in benchmark tests involving homogeneous and channel flows. Having demonstrated the potential of the dynamic model in these simple flows, the overall direction of the LES effort at CTR shifted toward an evaluation of the model in more complex situations. The current test cases are basic engineering-type flows for which Reynolds averaged approaches were unable to model the turbulence to within engineering accuracy. Flows currently under investigation include a backward-facing step, wake behind a circular cylinder, airfoil at high angles of attack, separated flow in a diffuser, and boundary layer over a concave surface. Preliminary results from the backward-facing step and cylinder wake simulations are encouraging. Progress on the LES of a boundary layer on a concave surface is discussed. Although the geometry of a concave wall is not very complex, the boundary layer that develops on its surface is difficult to model due to the presence of streamwise Taylor-Gortler vortices. These vortices arise as a result of a centrifugal instability associated with the convex curvature.
Teaching Supply Chain Management Complexities: A SCOR Model Based Classroom Simulation
ERIC Educational Resources Information Center
Webb, G. Scott; Thomas, Stephanie P.; Liao-Troth, Sara
2014-01-01
The SCOR (Supply Chain Operations Reference) Model Supply Chain Classroom Simulation is an in-class experiential learning activity that helps students develop a holistic understanding of the processes and challenges of supply chain management. The simulation has broader learning objectives than other supply chain related activities such as the…
Large eddy simulation modeling of particle-laden flows in complex terrain
NASA Astrophysics Data System (ADS)
Salesky, S.; Giometto, M. G.; Chamecki, M.; Lehning, M.; Parlange, M. B.
2017-12-01
The transport, deposition, and erosion of heavy particles over complex terrain in the atmospheric boundary layer is an important process for hydrology, air quality forecasting, biology, and geomorphology. However, in situ observations can be challenging in complex terrain due to spatial heterogeneity. Furthermore, there is a need to develop numerical tools that can accurately represent the physics of these multiphase flows over complex surfaces. We present a new numerical approach to accurately model the transport and deposition of heavy particles in complex terrain using large eddy simulation (LES). Particle transport is represented through solution of the advection-diffusion equation including terms that represent gravitational settling and inertia. The particle conservation equation is discretized in a cut-cell finite volume framework in order to accurately enforce mass conservation. Simulation results will be validated with experimental data, and numerical considerations required to enforce boundary conditions at the surface will be discussed. Applications will be presented in the context of snow deposition and transport, as well as urban dispersion.
Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K
2016-05-01
We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was implemented under a client-server paradigm that enables remote users to visualize and analyze simulation data as it is being generated at each time step of the model. Performance of a simulation case study of vocal fold inflammation and wound healing with 3.8 million agents shows 35× and 7× speedup in execution time over single-core and multi-core CPU respectively. Each iteration of the model took less than 200 ms to simulate, visualize and send the results to the client. This enables users to monitor the simulation in real-time and modify its course as needed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Potter, Kristin C; Brunhart-Lupo, Nicholas J; Bush, Brian W
We have developed a framework for the exploration, design, and planning of energy systems that combines interactive visualization with machine-learning based approximations of simulations through a general purpose dataflow API. Our system provides a visual inter- face allowing users to explore an ensemble of energy simulations representing a subset of the complex input parameter space, and spawn new simulations to 'fill in' input regions corresponding to new enegery system scenarios. Unfortunately, many energy simula- tions are far too slow to provide interactive responses. To support interactive feedback, we are developing reduced-form models via machine learning techniques, which provide statistically soundmore » esti- mates of the full simulations at a fraction of the computational cost and which are used as proxies for the full-form models. Fast com- putation and an agile dataflow enhance the engagement with energy simulations, and allow researchers to better allocate computational resources to capture informative relationships within the system and provide a low-cost method for validating and quality-checking large-scale modeling efforts.« less
ALC: automated reduction of rule-based models
Koschorreck, Markus; Gilles, Ernst Dieter
2008-01-01
Background Combinatorial complexity is a challenging problem for the modeling of cellular signal transduction since the association of a few proteins can give rise to an enormous amount of feasible protein complexes. The layer-based approach is an approximative, but accurate method for the mathematical modeling of signaling systems with inherent combinatorial complexity. The number of variables in the simulation equations is highly reduced and the resulting dynamic models show a pronounced modularity. Layer-based modeling allows for the modeling of systems not accessible previously. Results ALC (Automated Layer Construction) is a computer program that highly simplifies the building of reduced modular models, according to the layer-based approach. The model is defined using a simple but powerful rule-based syntax that supports the concepts of modularity and macrostates. ALC performs consistency checks on the model definition and provides the model output in different formats (C MEX, MATLAB, Mathematica and SBML) as ready-to-run simulation files. ALC also provides additional documentation files that simplify the publication or presentation of the models. The tool can be used offline or via a form on the ALC website. Conclusion ALC allows for a simple rule-based generation of layer-based reduced models. The model files are given in different formats as ready-to-run simulation files. PMID:18973705
Liotta, Flavia; d'Antonio, Giuseppe; Esposito, Giovanni; Fabbricino, Massimiliano; Frunzo, Luigi; van Hullebusch, Eric D; Lens, Piet N L; Pirozzi, Francesco
2014-01-01
The role of the moisture content and particle size (PS) on the disintegration of complex organic matter during the wet anaerobic digestion (AD) process was investigated. A range of total solids (TS) from 5% to 11.3% and PS from 0.25 to 15 mm was evaluated using carrot waste as model complex organic matter. The experimental results showed that the methane production rate decreased with higher TS and PS. A modified version of the AD model no.1 for complex organic substrates was used to model the experimental data. The simulations showed a decrease of the disintegration rate constants with increasing TS and PS. The results of the biomethanation tests were used to calibrate and validate the applied model. In particular, the values of the disintegration constant for various TS and PS were determined. The simulations showed good agreement between the numerical and observed data.
JAMS - a software platform for modular hydrological modelling
NASA Astrophysics Data System (ADS)
Kralisch, Sven; Fischer, Christian
2015-04-01
Current challenges of understanding and assessing the impacts of climate and land use changes on environmental systems demand for an ever-increasing integration of data and process knowledge in corresponding simulation models. Software frameworks that allow for a seamless creation of integrated models based on less complex components (domain models, process simulation routines) have therefore gained increasing attention during the last decade. JAMS is an Open-Source software framework that has been especially designed to cope with the challenges of eco-hydrological modelling. This is reflected by (i) its flexible approach for representing time and space, (ii) a strong separation of process simulation components from the declarative description of more complex models using domain specific XML, (iii) powerful analysis and visualization functions for spatial and temporal input and output data, and (iv) parameter optimization and uncertainty analysis functions commonly used in environmental modelling. Based on JAMS, different hydrological and nutrient-transport simulation models were implemented and successfully applied during the last years. We will present the JAMS core concepts and give an overview of models, simulation components and support tools available for that framework. Sample applications will be used to underline the advantages of component-based model designs and to show how JAMS can be used to address the challenges of integrated hydrological modelling.
Susan Hummel; Maureen Kennedy; E. Ashley Steel
2012-01-01
Given that resource managers rely on computer simulation models when it is difficult or expensive to obtain vital information directly, it is important to evaluate how well a particular model satisfies applications for which it is designed. The Forest Vegetation Simulator (FVS) is used widely for forest management in the US, and its scope and complexity continue to...
Calibrating and testing a gap model for simulating forest management in the Oregon Coast Range
Robert J. Pabst; Matthew N. Goslin; Steven L. Garman; Thomas A. Spies
2008-01-01
The complex mix of economic and ecological objectives facing today's forest managers necessitates the development of growth models with a capacity for simulating a wide range of forest conditions while producing outputs useful for economic analyses. We calibrated the gap model ZELIG to simulate stand level forest development in the Oregon Coast Range as part of a...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Keller, J.; Lacava, W.; Austin, J.
2015-02-01
This work investigates the minimum level of fidelity required to accurately simulate wind turbine gearboxes using state-of-the-art design tools. Excessive model fidelity including drivetrain complexity, gearbox complexity, excitation sources, and imperfections, significantly increases computational time, but may not provide a commensurate increase in the value of the results. Essential designparameters are evaluated, including the planetary load-sharing factor, gear tooth load distribution, and sun orbit motion. Based on the sensitivity study results, recommendations for the minimum model fidelities are provided.
Simplified and advanced modelling of traction control systems of heavy-haul locomotives
NASA Astrophysics Data System (ADS)
Spiryagin, Maksym; Wolfs, Peter; Szanto, Frank; Cole, Colin
2015-05-01
Improving tractive effort is a very complex task in locomotive design. It requires the development of not only mechanical systems but also power systems, traction machines and traction algorithms. At the initial design stage, traction algorithms can be verified by means of a simulation approach. A simple single wheelset simulation approach is not sufficient because all locomotive dynamics are not fully taken into consideration. Given that many traction control strategies exist, the best solution is to use more advanced approaches for such studies. This paper describes the modelling of a locomotive with a bogie traction control strategy based on a co-simulation approach in order to deliver more accurate results. The simplified and advanced modelling approaches of a locomotive electric power system are compared in this paper in order to answer a fundamental question. What level of modelling complexity is necessary for the investigation of the dynamic behaviours of a heavy-haul locomotive running under traction? The simulation results obtained provide some recommendations on simulation processes and the further implementation of advanced and simplified modelling approaches.
NASA Astrophysics Data System (ADS)
Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.
2015-12-01
Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.
The Prodiguer Messaging Platform
NASA Astrophysics Data System (ADS)
Greenslade, Mark; Denvil, Sebastien; Raciazek, Jerome; Carenton, Nicolas; Levavasseur, Guillame
2014-05-01
CONVERGENCE is a French multi-partner national project designed to gather HPC and informatics expertise to innovate in the context of running French climate models with differing grids and at differing resolutions. Efficient and reliable execution of these models and the management and dissemination of model output (data and meta-data) are just some of the complexities that CONVERGENCE aims to resolve. The Institut Pierre Simon Laplace (IPSL) is responsible for running climate simulations upon a set of heterogenous HPC environments within France. With heterogeneity comes added complexity in terms of simulation instrumentation and control. Obtaining a global perspective upon the state of all simulations running upon all HPC environments has hitherto been problematic. In this presentation we detail how, within the context of CONVERGENCE, the implementation of the Prodiguer messaging platform resolves complexity and permits the development of real-time applications such as: 1. a simulation monitoring dashboard; 2. a simulation metrics visualizer; 3. an automated simulation runtime notifier; 4. an automated output data & meta-data publishing pipeline; The Prodiguer messaging platform leverages a widely used open source message broker software called RabbitMQ. RabbitMQ itself implements the Advanced Message Queue Protocol (AMPQ). Hence it will be demonstrated that the Prodiguer messaging platform is built upon both open source and open standards.
NASA Astrophysics Data System (ADS)
Rajabzadeh Oghaz, Hamidreza; Damiano, Robert; Meng, Hui
2015-11-01
Intracranial aneurysms (IAs) are pathological outpouchings of cerebral vessels, the progression of which are mediated by complex interactions between the blood flow and vasculature. Image-based computational fluid dynamics (CFD) has been used for decades to investigate IA hemodynamics. However, the commonly adopted simplifying assumptions in CFD (e.g. rigid wall) compromise the simulation accuracy and mask the complex physics involved in IA progression and eventual rupture. Several groups have considered the wall compliance by using fluid-structure interaction (FSI) modeling. However, FSI simulation is highly sensitive to numerical assumptions (e.g. linear-elastic wall material, Newtonian fluid, initial vessel configuration, and constant pressure outlet), the effects of which are poorly understood. In this study, a comprehensive investigation of the sensitivity of FSI simulations in patient-specific IAs is investigated using a multi-stage approach with a varying level of complexity. We start with simulations incorporating several common simplifications: rigid wall, Newtonian fluid, and constant pressure at the outlets, and then we stepwise remove these simplifications until the most comprehensive FSI simulations. Hemodynamic parameters such as wall shear stress and oscillatory shear index are assessed and compared at each stage to better understand the sensitivity of in FSI simulations for IA to model assumptions. Supported by the National Institutes of Health (1R01 NS 091075-01).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Romander, C. M.; Cagliostro, D. J.
Five experiments were performed to help evaluate the structural integrity of the reactor vessel and head design and to verify code predictions. In the first experiment (SM 1), a detailed model of the head was loaded statically to determine its stiffness. In the remaining four experiments (SM 2 to SM 5), models of the vessel and head were loaded dynamically under a simulated 661 MW-sec hypothetical core disruptive accident (HCDA). Models SM 2 to SM 4, each of increasing complexity, systematically showed the effects of upper internals structures, a thermal liner, core support platform, and torospherical bottom on vessel response.more » Model SM 5, identical to SM 4 but more heavily instrumented, demonstrated experimental reproducibility and provided more comprehensive data. The models consisted of a Ni 200 vessel and core barrel, a head with shielding and simulated component masses, an upper internals structure (UIS), and, in the more complex models SM 4 and SM 5, a Ni 200 thermal liner and core support structure. Water simulated the liquid sodium coolant and a low-density explosive simulated the HCDA loads.« less
Building an open-source simulation platform of acoustic radiation force-based breast elastography
NASA Astrophysics Data System (ADS)
Wang, Yu; Peng, Bo; Jiang, Jingfeng
2017-03-01
Ultrasound-based elastography including strain elastography, acoustic radiation force impulse (ARFI) imaging, point shear wave elastography and supersonic shear imaging (SSI) have been used to differentiate breast tumors among other clinical applications. The objective of this study is to extend a previously published virtual simulation platform built for ultrasound quasi-static breast elastography toward acoustic radiation force-based breast elastography. Consequently, the extended virtual breast elastography simulation platform can be used to validate image pixels with known underlying soft tissue properties (i.e. ‘ground truth’) in complex, heterogeneous media, enhancing confidence in elastographic image interpretations. The proposed virtual breast elastography system inherited four key components from the previously published virtual simulation platform: an ultrasound simulator (Field II), a mesh generator (Tetgen), a finite element solver (FEBio) and a visualization and data processing package (VTK). Using a simple message passing mechanism, functionalities have now been extended to acoustic radiation force-based elastography simulations. Examples involving three different numerical breast models with increasing complexity—one uniform model, one simple inclusion model and one virtual complex breast model derived from magnetic resonance imaging data, were used to demonstrate capabilities of this extended virtual platform. Overall, simulation results were compared with the published results. In the uniform model, the estimated shear wave speed (SWS) values were within 4% compared to the predetermined SWS values. In the simple inclusion and the complex breast models, SWS values of all hard inclusions in soft backgrounds were slightly underestimated, similar to what has been reported. The elastic contrast values and visual observation show that ARFI images have higher spatial resolution, while SSI images can provide higher inclusion-to-background contrast. In summary, our initial results were consistent with our expectations and what have been reported in the literature. The proposed (open-source) simulation platform can serve as a single gateway to perform many elastographic simulations in a transparent manner, thereby promoting collaborative developments.
NASA Astrophysics Data System (ADS)
Kouznetsova, I.; Gerhard, J. I.; Mao, X.; Barry, D. A.; Robinson, C.; Brovelli, A.; Harkness, M.; Fisher, A.; Mack, E. E.; Payne, J. A.; Dworatzek, S.; Roberts, J.
2008-12-01
A detailed model to simulate trichloroethene (TCE) dechlorination in anaerobic groundwater systems has been developed and implemented through PHAST, a robust and flexible geochemical modeling platform. The approach is comprehensive but retains flexibility such that models of varying complexity can be used to simulate TCE biodegradation in the vicinity of nonaqueous phase liquid (NAPL) source zones. The complete model considers a full suite of biological (e.g., dechlorination, fermentation, sulfate and iron reduction, electron donor competition, toxic inhibition, pH inhibition), physical (e.g., flow and mass transfer) and geochemical processes (e.g., pH modulation, gas formation, mineral interactions). Example simulations with the model demonstrated that the feedback between biological, physical, and geochemical processes is critical. Successful simulation of a thirty-two-month column experiment with site soil, complex groundwater chemistry, and exhibiting both anaerobic dechlorination and endogenous respiration, provided confidence in the modeling approach. A comprehensive suite of batch simulations was then conducted to estimate the sensitivity of predicted TCE degradation to the 36 model input parameters. A local sensitivity analysis was first employed to rank the importance of parameters, revealing that 5 parameters consistently dominated model predictions across a range of performance metrics. A global sensitivity analysis was then performed to evaluate the influence of a variety of full parameter data sets available in the literature. The modeling study was performed as part of the SABRE (Source Area BioREmediation) project, a public/private consortium whose charter is to determine if enhanced anaerobic bioremediation can result in effective and quantifiable treatment of chlorinated solvent DNAPL source areas. The modelling conducted has provided valuable insight into the complex interactions between processes in the evolving biogeochemical systems, particularly at the laboratory scale.
Fluid Structural Analysis of Human Cerebral Aneurysm Using Their Own Wall Mechanical Properties
Valencia, Alvaro; Burdiles, Patricio; Ignat, Miguel; Mura, Jorge; Rivera, Rodrigo; Sordo, Juan
2013-01-01
Computational Structural Dynamics (CSD) simulations, Computational Fluid Dynamics (CFD) simulation, and Fluid Structure Interaction (FSI) simulations were carried out in an anatomically realistic model of a saccular cerebral aneurysm with the objective of quantifying the effects of type of simulation on principal fluid and solid mechanics results. Eight CSD simulations, one CFD simulation, and four FSI simulations were made. The results allowed the study of the influence of the type of material elements in the solid, the aneurism's wall thickness, and the type of simulation on the modeling of a human cerebral aneurysm. The simulations use their own wall mechanical properties of the aneurysm. The more complex simulation was the FSI simulation completely coupled with hyperelastic Mooney-Rivlin material, normal internal pressure, and normal variable thickness. The FSI simulation coupled in one direction using hyperelastic Mooney-Rivlin material, normal internal pressure, and normal variable thickness is the one that presents the most similar results with respect to the more complex FSI simulation, requiring one-fourth of the calculation time. PMID:24151523
Stollenwerk, Kenneth G.
1998-01-01
A natural-gradient tracer test was conducted in an unconfined sand and gravel aquifer on Cape Cod, Massachusetts. Molybdate was included in the injectate to study the effects of variable groundwater chemistry on its aqueous distribution and to evaluate the reliability of laboratory experiments for identifying and quantifying reactions that control the transport of reactive solutes in groundwater. Transport of molybdate in this aquifer was controlled by adsorption. The amount adsorbed varied with aqueous chemistry that changed with depth as freshwater recharge mixed with a plume of sewage-contaminated groundwater. Molybdate adsorption was strongest near the water table where pH (5.7) and the concentration of the competing solutes phosphate (2.3 micromolar) and sulfate (86 micromolar) were low. Adsorption of molybdate decreased with depth as pH increased to 6.5, phosphate increased to 40 micromolar, and sulfate increased to 340 micromolar. A one-site diffuse-layer surface-complexation model and a two-site diffuse-layer surface-complexation model were used to simulate adsorption. Reactions and equilibrium constants for both models were determined in laboratory experiments and used in the reactive-transport model PHAST to simulate the two-dimensional transport of molybdate during the tracer test. No geochemical parameters were adjusted in the simulation to improve the fit between model and field data. Both models simulated the travel distance of the molybdate cloud to within 10% during the 2-year tracer test; however, the two-site diffuse-layer model more accurately simulated the molybdate concentration distribution within the cloud.
Discrete event simulation modelling of patient service management with Arena
NASA Astrophysics Data System (ADS)
Guseva, Elena; Varfolomeyeva, Tatyana; Efimova, Irina; Movchan, Irina
2018-05-01
This paper describes the simulation modeling methodology aimed to aid in solving the practical problems of the research and analysing the complex systems. The paper gives the review of a simulation platform sand example of simulation model development with Arena 15.0 (Rockwell Automation).The provided example of the simulation model for the patient service management helps to evaluate the workload of the clinic doctors, determine the number of the general practitioners, surgeons, traumatologists and other specialized doctors required for the patient service and develop recommendations to ensure timely delivery of medical care and improve the efficiency of the clinic operation.
Reverse logistics system planning for recycling computers hardware: A case study
NASA Astrophysics Data System (ADS)
Januri, Siti Sarah; Zulkipli, Faridah; Zahari, Siti Meriam; Shamsuri, Siti Hajar
2014-09-01
This paper describes modeling and simulation of reverse logistics networks for collection of used computers in one of the company in Selangor. The study focuses on design of reverse logistics network for used computers recycling operation. Simulation modeling, presented in this work allows the user to analyze the future performance of the network and to understand the complex relationship between the parties involved. The findings from the simulation suggest that the model calculates processing time and resource utilization in a predictable manner. In this study, the simulation model was developed by using Arena simulation package.
Modelling radiation fluxes in simple and complex environments: basics of the RayMan model.
Matzarakis, Andreas; Rutz, Frank; Mayer, Helmut
2010-03-01
Short- and long-wave radiation flux densities absorbed by people have a significant influence on their energy balance. The heat effect of the absorbed radiation flux densities is parameterised by the mean radiant temperature. This paper presents the physical basis of the RayMan model, which simulates the short- and long-wave radiation flux densities from the three-dimensional surroundings in simple and complex environments. RayMan has the character of a freely available radiation and human-bioclimate model. The aim of the RayMan model is to calculate radiation flux densities, sunshine duration, shadow spaces and thermo-physiologically relevant assessment indices using only a limited number of meteorological and other input data. A comparison between measured and simulated values for global radiation and mean radiant temperature shows that the simulated data closely resemble measured data.
Modeling and Simulation for Mission Operations Work System Design
NASA Technical Reports Server (NTRS)
Sierhuis, Maarten; Clancey, William J.; Seah, Chin; Trimble, Jay P.; Sims, Michael H.
2003-01-01
Work System analysis and design is complex and non-deterministic. In this paper we describe Brahms, a multiagent modeling and simulation environment for designing complex interactions in human-machine systems. Brahms was originally conceived as a business process design tool that simulates work practices, including social systems of work. We describe our modeling and simulation method for mission operations work systems design, based on a research case study in which we used Brahms to design mission operations for a proposed discovery mission to the Moon. We then describe the results of an actual method application project-the Brahms Mars Exploration Rover. Space mission operations are similar to operations of traditional organizations; we show that the application of Brahms for space mission operations design is relevant and transferable to other types of business processes in organizations.
Simulations of surface winds at the Viking Lander sites using a one-level model
NASA Technical Reports Server (NTRS)
Bridger, Alison F. C.; Haberle, Robert M.
1992-01-01
The one-level model developed by Mass and Dempsey for use in predicting surface flows in regions of complex terrain was adapted to simulate surface flows at the Viking lander sites on Mars. In the one-level model, prediction equations for surface winds and temperatures are formulated and solved. Surface temperatures change with time in response to diabatic heating, horizontal advection, adiabatic heating and cooling effects, and horizontal diffusion. Surface winds can change in response to horizontal advection, pressure gradient forces, Coriolis forces, surface drag, and horizontal diffusion. Surface pressures are determined by integration of the hydrostatic equation from the surface to some reference level. The model has successfully simulated surface flows under a variety of conditions in complex-terrain regions on Earth.
NASA Astrophysics Data System (ADS)
Vivoni, Enrique R.; Mascaro, Giuseppe; Mniszewski, Susan; Fasel, Patricia; Springer, Everett P.; Ivanov, Valeriy Y.; Bras, Rafael L.
2011-10-01
SummaryA major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.
An approach for modelling snowcover ablation and snowmelt runoff in cold region environments
NASA Astrophysics Data System (ADS)
Dornes, Pablo Fernando
Reliable hydrological model simulations are the result of numerous complex interactions among hydrological inputs, landscape properties, and initial conditions. Determination of the effects of these factors is one of the main challenges in hydrological modelling. This situation becomes even more difficult in cold regions due to the ungauged nature of subarctic and arctic environments. This research work is an attempt to apply a new approach for modelling snowcover ablation and snowmelt runoff in complex subarctic environments with limited data while retaining integrity in the process representations. The modelling strategy is based on the incorporation of both detailed process understanding and inputs along with information gained from observations of basin-wide streamflow phenomenon; essentially a combination of deductive and inductive approaches. The study was conducted in the Wolf Creek Research Basin, Yukon Territory, using three models, a small-scale physically based hydrological model, a land surface scheme, and a land surface hydrological model. The spatial representation was based on previous research studies and observations, and was accomplished by incorporating landscape units, defined according to topography and vegetation, as the spatial model elements. Comparisons between distributed and aggregated modelling approaches showed that simulations incorporating distributed initial snowcover and corrected solar radiation were able to properly simulate snowcover ablation and snowmelt runoff whereas the aggregated modelling approaches were unable to represent the differential snowmelt rates and complex snowmelt runoff dynamics. Similarly, the inclusion of spatially distributed information in a land surface scheme clearly improved simulations of snowcover ablation. Application of the same modelling approach at a larger scale using the same landscape based parameterisation showed satisfactory results in simulating snowcover ablation and snowmelt runoff with minimal calibration. Verification of this approach in an arctic basin illustrated that landscape based parameters are a feasible regionalisation framework for distributed and physically based models. In summary, the proposed modelling philosophy, based on the combination of an inductive and deductive reasoning, is a suitable strategy for reliable predictions of snowcover ablation and snowmelt runoff in cold regions and complex environments.
The unsaturated or vadose zone provides a complex system for the simulation of water movement and contaminant transport and fate. Numerous models are available for performing simulations related to the movement of water. There exists extensive documentation of these models. Ho...
USDA-ARS?s Scientific Manuscript database
DayCent is a biogeochemical model of intermediate complexity used to simulate carbon, nutrient, and greenhouse gas fluxes for crop, grassland, forest, and savanna ecosystems. Model inputs include: soil texture and hydraulic properties, current and historical land use, vegetation cover, daily maximum...
A protocol for parameterization and calibration of RZWQM2 in field research
USDA-ARS?s Scientific Manuscript database
Use of agricultural system models in field research requires a full understanding of both the model and the system it simulates. Since the 1960s, agricultural system models have increased tremendously in their complexity due to greater understanding of the processes simulated, their application to r...
USDA-ARS?s Scientific Manuscript database
In recent years, large-scale watershed modeling has been implemented broadly in the field of water resources planning and management. Complex hydrological, sediment, and nutrient processes can be simulated by sophisticated watershed simulation models for important issues such as water resources all...
In this study, the calibration of subsurface batch and reactive-transport models involving complex biogeochemical processes was systematically evaluated. Two hypothetical nitrate biodegradation scenarios were developed and simulated in numerical experiments to evaluate the perfor...
Kim, Yong Sun; Choi, Hyeong Ho; Cho, Young Nam; Park, Yong Jae; Lee, Jong B; Yang, King H; King, Albert I
2005-11-01
Although biomechanical studies on the knee-thigh-hip (KTH) complex have been extensive, interactions between the KTH and various vehicular interior design parameters in frontal automotive crashes for newer models have not been reported in the open literature to the best of our knowledge. A 3D finite element (FE) model of a 50(th) percentile male KTH complex, which includes explicit representations of the iliac wing, acetabulum, pubic rami, sacrum, articular cartilage, femoral head, femoral neck, femoral condyles, patella, and patella tendon, has been developed to simulate injuries such as fracture of the patella, femoral neck, acetabulum, and pubic rami of the KTH complex. Model results compared favorably against regional component test data including a three-point bending test of the femur, axial loading of the isolated knee-patella, axial loading of the KTH complex, axial loading of the femoral head, and lateral loading of the isolated pelvis. The model was further integrated into a Wayne State University upper torso model and validated against data obtained from whole body sled tests. The model was validated against these experimental data over a range of impact speeds, impactor masses and boundary conditions. Using Design Of Experiment (DOE) methods based on Taguchi's approach and the developed FE model of the whole body, including the KTH complex, eight vehicular interior design parameters, namely the load limiter force, seat belt elongation, pretensioner inlet amount, knee-knee bolster distance, knee bolster angle, knee bolster stiffness, toe board angle and impact speed, each with either two or three design levels, were simulated to predict their respective effects on the potential of KTH injury in frontal impacts. Simulation results proposed best design levels for vehicular interior design parameters to reduce the injury potential of the KTH complex due to frontal automotive crashes. This study is limited by the fact that prediction of bony fracture was based on an element elimination method available in the LS-DYNA code. No validation study was conducted to determine if this method is suitable when simulating fractures of biological tissues. More work is still needed to further validate the FE model of the KTH complex to increase its reliability in the assessment of various impact loading conditions associated with vehicular crash scenarios.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mian, Muhammad Umer, E-mail: umermian@gmail.com; Khir, M. H. Md.; Tang, T. B.
Pre-fabrication, behavioural and performance analysis with computer aided design (CAD) tools is a common and fabrication cost effective practice. In light of this we present a simulation methodology for a dual-mass oscillator based 3 Degree of Freedom (3-DoF) MEMS gyroscope. 3-DoF Gyroscope is modeled through lumped parameter models using equivalent circuit elements. These equivalent circuits consist of elementary components which are counterpart of their respective mechanical components, used to design and fabricate 3-DoF MEMS gyroscope. Complete designing of equivalent circuit model, mathematical modeling and simulation are being presented in this paper. Behaviors of the equivalent lumped models derived for themore » proposed device design are simulated in MEMSPRO T-SPICE software. Simulations are carried out with the design specifications following design rules of the MetalMUMPS fabrication process. Drive mass resonant frequencies simulated by this technique are 1.59 kHz and 2.05 kHz respectively, which are close to the resonant frequencies found by the analytical formulation of the gyroscope. The lumped equivalent circuit modeling technique proved to be a time efficient modeling technique for the analysis of complex MEMS devices like 3-DoF gyroscopes. The technique proves to be an alternative approach to the complex and time consuming couple field analysis Finite Element Analysis (FEA) previously used.« less
Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Dali; Yuan, Fengming; Hernandez, Benjamin
Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less
Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations
Wang, Dali; Yuan, Fengming; Hernandez, Benjamin; ...
2017-01-01
Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less
Leveraging Modeling Approaches: Reaction Networks and Rules
Blinov, Michael L.; Moraru, Ion I.
2012-01-01
We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high resolution and/or high throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatio-temporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks – the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks. PMID:22161349
Leveraging modeling approaches: reaction networks and rules.
Blinov, Michael L; Moraru, Ion I
2012-01-01
We have witnessed an explosive growth in research involving mathematical models and computer simulations of intracellular molecular interactions, ranging from metabolic pathways to signaling and gene regulatory networks. Many software tools have been developed to aid in the study of such biological systems, some of which have a wealth of features for model building and visualization, and powerful capabilities for simulation and data analysis. Novel high-resolution and/or high-throughput experimental techniques have led to an abundance of qualitative and quantitative data related to the spatiotemporal distribution of molecules and complexes, their interactions kinetics, and functional modifications. Based on this information, computational biology researchers are attempting to build larger and more detailed models. However, this has proved to be a major challenge. Traditionally, modeling tools require the explicit specification of all molecular species and interactions in a model, which can quickly become a major limitation in the case of complex networks - the number of ways biomolecules can combine to form multimolecular complexes can be combinatorially large. Recently, a new breed of software tools has been created to address the problems faced when building models marked by combinatorial complexity. These have a different approach for model specification, using reaction rules and species patterns. Here we compare the traditional modeling approach with the new rule-based methods. We make a case for combining the capabilities of conventional simulation software with the unique features and flexibility of a rule-based approach in a single software platform for building models of molecular interaction networks.
NASA Technical Reports Server (NTRS)
Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan
2014-01-01
Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.
Evolving Scale-Free Networks by Poisson Process: Modeling and Degree Distribution.
Feng, Minyu; Qu, Hong; Yi, Zhang; Xie, Xiurui; Kurths, Jurgen
2016-05-01
Since the great mathematician Leonhard Euler initiated the study of graph theory, the network has been one of the most significant research subject in multidisciplinary. In recent years, the proposition of the small-world and scale-free properties of complex networks in statistical physics made the network science intriguing again for many researchers. One of the challenges of the network science is to propose rational models for complex networks. In this paper, in order to reveal the influence of the vertex generating mechanism of complex networks, we propose three novel models based on the homogeneous Poisson, nonhomogeneous Poisson and birth death process, respectively, which can be regarded as typical scale-free networks and utilized to simulate practical networks. The degree distribution and exponent are analyzed and explained in mathematics by different approaches. In the simulation, we display the modeling process, the degree distribution of empirical data by statistical methods, and reliability of proposed networks, results show our models follow the features of typical complex networks. Finally, some future challenges for complex systems are discussed.
Alimohammadi, Mona; Sherwood, Joseph M; Karimpour, Morad; Agu, Obiekezie; Balabani, Stavroula; Díaz-Zuccarini, Vanessa
2015-04-15
The management and prognosis of aortic dissection (AD) is often challenging and the use of personalised computational models is being explored as a tool to improve clinical outcome. Including vessel wall motion in such simulations can provide more realistic and potentially accurate results, but requires significant additional computational resources, as well as expertise. With clinical translation as the final aim, trade-offs between complexity, speed and accuracy are inevitable. The present study explores whether modelling wall motion is worth the additional expense in the case of AD, by carrying out fluid-structure interaction (FSI) simulations based on a sample patient case. Patient-specific anatomical details were extracted from computed tomography images to provide the fluid domain, from which the vessel wall was extrapolated. Two-way fluid-structure interaction simulations were performed, with coupled Windkessel boundary conditions and hyperelastic wall properties. The blood was modelled using the Carreau-Yasuda viscosity model and turbulence was accounted for via a shear stress transport model. A simulation without wall motion (rigid wall) was carried out for comparison purposes. The displacement of the vessel wall was comparable to reports from imaging studies in terms of intimal flap motion and contraction of the true lumen. Analysis of the haemodynamics around the proximal and distal false lumen in the FSI model showed complex flow structures caused by the expansion and contraction of the vessel wall. These flow patterns led to significantly different predictions of wall shear stress, particularly its oscillatory component, which were not captured by the rigid wall model. Through comparison with imaging data, the results of the present study indicate that the fluid-structure interaction methodology employed herein is appropriate for simulations of aortic dissection. Regions of high wall shear stress were not significantly altered by the wall motion, however, certain collocated regions of low and oscillatory wall shear stress which may be critical for disease progression were only identified in the FSI simulation. We conclude that, if patient-tailored simulations of aortic dissection are to be used as an interventional planning tool, then the additional complexity, expertise and computational expense required to model wall motion is indeed justified.
Computational Modeling and Simulation of Genital Tubercle Development
Hypospadias is a developmental defect of urethral tube closure that has a complex etiology. Here, we describe a multicellular agent-based model of genital tubercle development that simulates urethrogenesis from the urethral plate stage to urethral tube closure in differentiating ...
Using HexSim to simulate complex species, landscape, and stressor interactions
Background / Question / Methods The use of simulation models in conservation biology, landscape ecology, and other disciplines is increasing. Models are essential tools for researchers who, for example, need to forecast future conditions, weigh competing recovery and mitigation...
Problem-Solving in the Pre-Clinical Curriculum: The Uses of Computer Simulations.
ERIC Educational Resources Information Center
Michael, Joel A.; Rovick, Allen A.
1986-01-01
Promotes the use of computer-based simulations in the pre-clinical medical curriculum as a means of providing students with opportunities for problem solving. Describes simple simulations of skeletal muscle loads, complex simulations of major organ systems and comprehensive simulation models of the entire human body. (TW)
NASA Astrophysics Data System (ADS)
Prasad, K.
2017-12-01
Atmospheric transport is usually performed with weather models, e.g., the Weather Research and Forecasting (WRF) model that employs a parameterized turbulence model and does not resolve the fine scale dynamics generated by the flow around buildings and features comprising a large city. The NIST Fire Dynamics Simulator (FDS) is a computational fluid dynamics model that utilizes large eddy simulation methods to model flow around buildings at length scales much smaller than is practical with models like WRF. FDS has the potential to evaluate the impact of complex topography on near-field dispersion and mixing that is difficult to simulate with a mesoscale atmospheric model. A methodology has been developed to couple the FDS model with WRF mesoscale transport models. The coupling is based on nudging the FDS flow field towards that computed by WRF, and is currently limited to one way coupling performed in an off-line mode. This approach allows the FDS model to operate as a sub-grid scale model with in a WRF simulation. To test and validate the coupled FDS - WRF model, the methane leak from the Aliso Canyon underground storage facility was simulated. Large eddy simulations were performed over the complex topography of various natural gas storage facilities including Aliso Canyon, Honor Rancho and MacDonald Island at 10 m horizontal and vertical resolution. The goal of these simulations included improving and validating transport models as well as testing leak hypotheses. Forward simulation results were compared with aircraft and tower based in-situ measurements as well as methane plumes observed using the NASA Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) and the next generation instrument AVIRIS-NG. Comparison of simulation results with measurement data demonstrate the capability of the coupled FDS-WRF models to accurately simulate the transport and dispersion of methane plumes over urban domains. Simulated integrated methane enhancements will be presented and compared with results obtained from spectrometer data to estimate the temporally evolving methane flux during the Aliso Canyon blowout.
Modeling and simulation for fewer-axis grinding of complex surface
NASA Astrophysics Data System (ADS)
Li, Zhengjian; Peng, Xiaoqiang; Song, Ci
2017-10-01
As the basis of fewer-axis grinding of complex surface, the grinding mathematical model is of great importance. A mathematical model of the grinding wheel was established, and then coordinate and normal vector of the wheel profile could be calculated. Through normal vector matching at the cutter contact point and the coordinate system transformation, the grinding mathematical model was established to work out the coordinate of the cutter location point. Based on the model, interference analysis was simulated to find out the right position and posture of workpiece for grinding. Then positioning errors of the workpiece including the translation positioning error and the rotation positioning error were analyzed respectively, and the main locating datum was obtained. According to the analysis results, the grinding tool path was planned and generated to grind the complex surface, and good form accuracy was obtained. The grinding mathematical model is simple, feasible and can be widely applied.
Large eddy simulation of forest canopy flow for wildland fire modeling
Eric Mueller; William Mell; Albert Simeoni
2014-01-01
Large eddy simulation (LES) based computational fluid dynamics (CFD) simulators have obtained increasing attention in the wildland fire research community, as these tools allow the inclusion of important driving physics. However, due to the complexity of the models, individual aspects must be isolated and tested rigorously to ensure meaningful results. As wind is a...
A novel approach to simulate gene-environment interactions in complex diseases.
Amato, Roberto; Pinelli, Michele; D'Andrea, Daniel; Miele, Gennaro; Nicodemi, Mario; Raiconi, Giancarlo; Cocozza, Sergio
2010-01-05
Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study.
Experimentally modeling stochastic processes with less memory by the use of a quantum processor
Palsson, Matthew S.; Gu, Mile; Ho, Joseph; Wiseman, Howard M.; Pryde, Geoff J.
2017-01-01
Computer simulation of observable phenomena is an indispensable tool for engineering new technology, understanding the natural world, and studying human society. However, the most interesting systems are often so complex that simulating their future behavior demands storing immense amounts of information regarding how they have behaved in the past. For increasingly complex systems, simulation becomes increasingly difficult and is ultimately constrained by resources such as computer memory. Recent theoretical work shows that quantum theory can reduce this memory requirement beyond ultimate classical limits, as measured by a process’ statistical complexity, C. We experimentally demonstrate this quantum advantage in simulating stochastic processes. Our quantum implementation observes a memory requirement of Cq = 0.05 ± 0.01, far below the ultimate classical limit of C = 1. Scaling up this technique would substantially reduce the memory required in simulations of more complex systems. PMID:28168218
Aromatic sulfonation with sulfur trioxide: mechanism and kinetic model.
Moors, Samuel L C; Deraet, Xavier; Van Assche, Guy; Geerlings, Paul; De Proft, Frank
2017-01-01
Electrophilic aromatic sulfonation of benzene with sulfur trioxide is studied with ab initio molecular dynamics simulations in gas phase, and in explicit noncomplexing (CCl 3 F) and complexing (CH 3 NO 2 ) solvent models. We investigate different possible reaction pathways, the number of SO 3 molecules participating in the reaction, and the influence of the solvent. Our simulations confirm the existence of a low-energy concerted pathway with formation of a cyclic transition state with two SO 3 molecules. Based on the simulation results, we propose a sequence of elementary reaction steps and a kinetic model compatible with experimental data. Furthermore, a new alternative reaction pathway is proposed in complexing solvent, involving two SO 3 and one CH 3 NO 2 .
Cluster-Expansion Model for Complex Quinary Alloys: Application to Alnico Permanent Magnets
NASA Astrophysics Data System (ADS)
Nguyen, Manh Cuong; Zhou, Lin; Tang, Wei; Kramer, Matthew J.; Anderson, Iver E.; Wang, Cai-Zhuang; Ho, Kai-Ming
2017-11-01
An accurate and transferable cluster-expansion model for complex quinary alloys is developed. Lattice Monte Carlo simulation enabled by this cluster-expansion model is used to investigate temperature-dependent atomic structure of alnico alloys, which are considered as promising high-performance non-rare-earth permanent-magnet materials for high-temperature applications. The results of the Monte Carlo simulations are consistent with available experimental data and provide useful insights into phase decomposition, selection, and chemical ordering in alnico. The simulations also reveal a previously unrecognized D 03 alloy phase. This phase is very rich in Ni and exhibits very weak magnetization. Manipulating the size and location of this phase provides a possible route to improve the magnetic properties of alnico, especially coercivity.
NASA Technical Reports Server (NTRS)
Kleb, William L.; Wood, William A.
2004-01-01
The computational simulation community is not routinely publishing independently verifiable tests to accompany new models or algorithms. A survey reveals that only 22% of new models published are accompanied by tests suitable for independently verifying the new model. As the community develops larger codes with increased functionality, and hence increased complexity in terms of the number of building block components and their interactions, it becomes prohibitively expensive for each development group to derive the appropriate tests for each component. Therefore, the computational simulation community is building its collective castle on a very shaky foundation of components with unpublished and unrepeatable verification tests. The computational simulation community needs to begin publishing component level verification tests before the tide of complexity undermines its foundation.
New simulation model of multicomponent crystal growth and inhibition.
Wathen, Brent; Kuiper, Michael; Walker, Virginia; Jia, Zongchao
2004-04-02
We review a novel computational model for the study of crystal structures both on their own and in conjunction with inhibitor molecules. The model advances existing Monte Carlo (MC) simulation techniques by extending them from modeling 3D crystal surface patches to modeling entire 3D crystals, and by including the use of "complex" multicomponent molecules within the simulations. These advances makes it possible to incorporate the 3D shape and non-uniform surface properties of inhibitors into simulations, and to study what effect these inhibitor properties have on the growth of whole crystals containing up to tens of millions of molecules. The application of this extended MC model to the study of antifreeze proteins (AFPs) and their effects on ice formation is reported, including the success of the technique in achieving AFP-induced ice-growth inhibition with concurrent changes to ice morphology that mimic experimental results. Simulations of ice-growth inhibition suggest that the degree of inhibition afforded by an AFP is a function of its ice-binding position relative to the underlying anisotropic growth pattern of ice. This extended MC technique is applicable to other crystal and crystal-inhibitor systems, including more complex crystal systems such as clathrates.
A computational study of the chemokine receptor CXCR1 bound with interleukin-8
NASA Astrophysics Data System (ADS)
Wang, Yang; Severin Lupala, Cecylia; Wang, Ting; Li, Xuanxuan; Yun, Ji-Hye; Park, Jae-hyun; Jin, Zeyu; Lee, Weontae; Tan, Leihan; Liu, Haiguang
2018-03-01
CXCR1 is a G-protein coupled receptor, transducing signals from chemokines, in particular the interleukin-8 (IL8) molecules. This study combines homology modeling and molecular dynamics simulation methods to study the structure of CXCR1-IL8 complex. By using CXCR4-vMIP-II crystallography structure as the homologous template, CXCR1-IL8 complex structure was constructed, and then refined using all-atom molecular dynamics simulations. Through extensive simulations, CXCR1-IL8 binding poses were investigated in detail. Furthermore, the role of the N-terminal of CXCR1 receptor was studied by comparing four complex models differing in the N-terminal sequences. The results indicate that the receptor N-terminal affects the binding of IL8 significantly. With a shorter N-terminal domain, the binding of IL8 to CXCR1 becomes unstable. The homology modeling and simulations also reveal the key receptor-ligand residues involved in the electrostatic interactions known to be vital for complex formation. Project supported by the National Natural Science Foundation of China (Grant Nos. 11575021, U1530401, and U1430237) and the National Research Foundation of Korea (Grant Nos. NRF-2017R1A2B2008483 and NRF-2016R1A6A3A04010213).
Stochastic model simulation using Kronecker product analysis and Zassenhaus formula approximation.
Caglar, Mehmet Umut; Pal, Ranadip
2013-01-01
Probabilistic Models are regularly applied in Genetic Regulatory Network modeling to capture the stochastic behavior observed in the generation of biological entities such as mRNA or proteins. Several approaches including Stochastic Master Equations and Probabilistic Boolean Networks have been proposed to model the stochastic behavior in genetic regulatory networks. It is generally accepted that Stochastic Master Equation is a fundamental model that can describe the system being investigated in fine detail, but the application of this model is computationally enormously expensive. On the other hand, Probabilistic Boolean Network captures only the coarse-scale stochastic properties of the system without modeling the detailed interactions. We propose a new approximation of the stochastic master equation model that is able to capture the finer details of the modeled system including bistabilities and oscillatory behavior, and yet has a significantly lower computational complexity. In this new method, we represent the system using tensors and derive an identity to exploit the sparse connectivity of regulatory targets for complexity reduction. The algorithm involves an approximation based on Zassenhaus formula to represent the exponential of a sum of matrices as product of matrices. We derive upper bounds on the expected error of the proposed model distribution as compared to the stochastic master equation model distribution. Simulation results of the application of the model to four different biological benchmark systems illustrate performance comparable to detailed stochastic master equation models but with considerably lower computational complexity. The results also demonstrate the reduced complexity of the new approach as compared to commonly used Stochastic Simulation Algorithm for equivalent accuracy.
Evaluation of Intersection Traffic Control Measures through Simulation
NASA Astrophysics Data System (ADS)
Asaithambi, Gowri; Sivanandan, R.
2015-12-01
Modeling traffic flow is stochastic in nature due to randomness in variables such as vehicle arrivals and speeds. Due to this and due to complex vehicular interactions and their manoeuvres, it is extremely difficult to model the traffic flow through analytical methods. To study this type of complex traffic system and vehicle interactions, simulation is considered as an effective tool. Application of homogeneous traffic models to heterogeneous traffic may not be able to capture the complex manoeuvres and interactions in such flows. Hence, a microscopic simulation model for heterogeneous traffic is developed using object oriented concepts. This simulation model acts as a tool for evaluating various control measures at signalized intersections. The present study focuses on the evaluation of Right Turn Lane (RTL) and Channelised Left Turn Lane (CLTL). A sensitivity analysis was performed to evaluate RTL and CLTL by varying the approach volumes, turn proportions and turn lane lengths. RTL is found to be advantageous only up to certain approach volumes and right-turn proportions, beyond which it is counter-productive. CLTL is found to be advantageous for lower approach volumes for all turn proportions, signifying the benefits of CLTL. It is counter-productive for higher approach volume and lower turn proportions. This study pinpoints the break-even points for various scenarios. The developed simulation model can be used as an appropriate intersection lane control tool for enhancing the efficiency of flow at intersections. This model can also be employed for scenario analysis and can be valuable to field traffic engineers in implementing vehicle-type based and lane-based traffic control measures.
Modeling and Simulation of Lab-on-a-Chip Systems
2005-08-12
complex chip geometries (including multiple turns). Variations of sample concentration profiles in laminar diffusion-based micromixers are also derived...CHAPTER 6 MODELING OF LAMINAR DIFFUSION-BASED COMPLEX ELECTROKINETIC PASSIVE MICROMIXERS ...140 6.4.4 Multi-Stream (Inter-Digital) Micromixers
Understanding Emergency Care Delivery Through Computer Simulation Modeling.
Laker, Lauren F; Torabi, Elham; France, Daniel J; Froehle, Craig M; Goldlust, Eric J; Hoot, Nathan R; Kasaie, Parastu; Lyons, Michael S; Barg-Walkow, Laura H; Ward, Michael J; Wears, Robert L
2018-02-01
In 2017, Academic Emergency Medicine convened a consensus conference entitled, "Catalyzing System Change through Health Care Simulation: Systems, Competency, and Outcomes." This article, a product of the breakout session on "understanding complex interactions through systems modeling," explores the role that computer simulation modeling can and should play in research and development of emergency care delivery systems. This article discusses areas central to the use of computer simulation modeling in emergency care research. The four central approaches to computer simulation modeling are described (Monte Carlo simulation, system dynamics modeling, discrete-event simulation, and agent-based simulation), along with problems amenable to their use and relevant examples to emergency care. Also discussed is an introduction to available software modeling platforms and how to explore their use for research, along with a research agenda for computer simulation modeling. Through this article, our goal is to enhance adoption of computer simulation, a set of methods that hold great promise in addressing emergency care organization and design challenges. © 2017 by the Society for Academic Emergency Medicine.
van Gestel, Aukje; Severens, Johan L; Webers, Carroll A B; Beckers, Henny J M; Jansonius, Nomdo M; Schouten, Jan S A G
2010-01-01
Discrete event simulation (DES) modeling has several advantages over simpler modeling techniques in health economics, such as increased flexibility and the ability to model complex systems. Nevertheless, these benefits may come at the cost of reduced transparency, which may compromise the model's face validity and credibility. We aimed to produce a transparent report on the construction and validation of a DES model using a recently developed model of ocular hypertension and glaucoma. Current evidence of associations between prognostic factors and disease progression in ocular hypertension and glaucoma was translated into DES model elements. The model was extended to simulate treatment decisions and effects. Utility and costs were linked to disease status and treatment, and clinical and health economic outcomes were defined. The model was validated at several levels. The soundness of design and the plausibility of input estimates were evaluated in interdisciplinary meetings (face validity). Individual patients were traced throughout the simulation under a multitude of model settings to debug the model, and the model was run with a variety of extreme scenarios to compare the outcomes with prior expectations (internal validity). Finally, several intermediate (clinical) outcomes of the model were compared with those observed in experimental or observational studies (external validity) and the feasibility of evaluating hypothetical treatment strategies was tested. The model performed well in all validity tests. Analyses of hypothetical treatment strategies took about 30 minutes per cohort and lead to plausible health-economic outcomes. There is added value of DES models in complex treatment strategies such as glaucoma. Achieving transparency in model structure and outcomes may require some effort in reporting and validating the model, but it is feasible.
Qualitative models and experimental investigation of chaotic NOR gates and set/reset flip-flops
NASA Astrophysics Data System (ADS)
Rahman, Aminur; Jordan, Ian; Blackmore, Denis
2018-01-01
It has been observed through experiments and SPICE simulations that logical circuits based upon Chua's circuit exhibit complex dynamical behaviour. This behaviour can be used to design analogues of more complex logic families and some properties can be exploited for electronics applications. Some of these circuits have been modelled as systems of ordinary differential equations. However, as the number of components in newer circuits increases so does the complexity. This renders continuous dynamical systems models impractical and necessitates new modelling techniques. In recent years, some discrete dynamical models have been developed using various simplifying assumptions. To create a robust modelling framework for chaotic logical circuits, we developed both deterministic and stochastic discrete dynamical models, which exploit the natural recurrence behaviour, for two chaotic NOR gates and a chaotic set/reset flip-flop. This work presents a complete applied mathematical investigation of logical circuits. Experiments on our own designs of the above circuits are modelled and the models are rigorously analysed and simulated showing surprisingly close qualitative agreement with the experiments. Furthermore, the models are designed to accommodate dynamics of similarly designed circuits. This will allow researchers to develop ever more complex chaotic logical circuits with a simple modelling framework.
Qualitative models and experimental investigation of chaotic NOR gates and set/reset flip-flops.
Rahman, Aminur; Jordan, Ian; Blackmore, Denis
2018-01-01
It has been observed through experiments and SPICE simulations that logical circuits based upon Chua's circuit exhibit complex dynamical behaviour. This behaviour can be used to design analogues of more complex logic families and some properties can be exploited for electronics applications. Some of these circuits have been modelled as systems of ordinary differential equations. However, as the number of components in newer circuits increases so does the complexity. This renders continuous dynamical systems models impractical and necessitates new modelling techniques. In recent years, some discrete dynamical models have been developed using various simplifying assumptions. To create a robust modelling framework for chaotic logical circuits, we developed both deterministic and stochastic discrete dynamical models, which exploit the natural recurrence behaviour, for two chaotic NOR gates and a chaotic set/reset flip-flop. This work presents a complete applied mathematical investigation of logical circuits. Experiments on our own designs of the above circuits are modelled and the models are rigorously analysed and simulated showing surprisingly close qualitative agreement with the experiments. Furthermore, the models are designed to accommodate dynamics of similarly designed circuits. This will allow researchers to develop ever more complex chaotic logical circuits with a simple modelling framework.
Zhao, Lei; Gossmann, Toni I; Waxman, David
2016-03-21
The Wright-Fisher model is an important model in evolutionary biology and population genetics. It has been applied in numerous analyses of finite populations with discrete generations. It is recognised that real populations can behave, in some key aspects, as though their size that is not the census size, N, but rather a smaller size, namely the effective population size, Ne. However, in the Wright-Fisher model, there is no distinction between the effective and census population sizes. Equivalently, we can say that in this model, Ne coincides with N. The Wright-Fisher model therefore lacks an important aspect of biological realism. Here, we present a method that allows Ne to be directly incorporated into the Wright-Fisher model. The modified model involves matrices whose size is determined by Ne. Thus apart from increased biological realism, the modified model also has reduced computational complexity, particularly so when Ne⪡N. For complex problems, it may be hard or impossible to numerically analyse the most commonly-used approximation of the Wright-Fisher model that incorporates Ne, namely the diffusion approximation. An alternative approach is simulation. However, the simulations need to be sufficiently detailed that they yield an effective size that is different to the census size. Simulations may also be time consuming and have attendant statistical errors. The method presented in this work may then be the only alternative to simulations, when Ne differs from N. We illustrate the straightforward application of the method to some problems involving allele fixation and the determination of the equilibrium site frequency spectrum. We then apply the method to the problem of fixation when three alleles are segregating in a population. This latter problem is significantly more complex than a two allele problem and since the diffusion equation cannot be numerically solved, the only other way Ne can be incorporated into the analysis is by simulation. We have achieved good accuracy in all cases considered. In summary, the present work extends the realism and tractability of an important model of evolutionary biology and population genetics. Copyright © 2016 Elsevier Ltd. All rights reserved.
Complexity, accuracy and practical applicability of different biogeochemical model versions
NASA Astrophysics Data System (ADS)
Los, F. J.; Blaas, M.
2010-04-01
The construction of validated biogeochemical model applications as prognostic tools for the marine environment involves a large number of choices particularly with respect to the level of details of the .physical, chemical and biological aspects. Generally speaking, enhanced complexity might enhance veracity, accuracy and credibility. However, very complex models are not necessarily effective or efficient forecast tools. In this paper, models of varying degrees of complexity are evaluated with respect to their forecast skills. In total 11 biogeochemical model variants have been considered based on four different horizontal grids. The applications vary in spatial resolution, in vertical resolution (2DH versus 3D), in nature of transport, in turbidity and in the number of phytoplankton species. Included models range from 15 year old applications with relatively simple physics up to present state of the art 3D models. With all applications the same year, 2003, has been simulated. During the model intercomparison it has been noticed that the 'OSPAR' Goodness of Fit cost function (Villars and de Vries, 1998) leads to insufficient discrimination of different models. This results in models obtaining similar scores although closer inspection of the results reveals large differences. In this paper therefore, we have adopted the target diagram by Jolliff et al. (2008) which provides a concise and more contrasting picture of model skill on the entire model domain and for the entire period of the simulations. Correctness in prediction of the mean and the variability are separated and thus enhance insight in model functioning. Using the target diagrams it is demonstrated that recent models are more consistent and have smaller biases. Graphical inspection of time series confirms this, as the level of variability appears more realistic, also given the multi-annual background statistics of the observations. Nevertheless, whether the improvements are all genuine for the particular year cannot be judged due to the low sampling frequency of the traditional monitoring data at hand. Specifically, the overall results for chlorophyll- a are rather consistent throughout all models, but regionally recent models are better; resolution is crucial for the accuracy of transport and more important than the nature of the forcing of the transport; SPM strongly affects the biomass simulation and species composition, but even the most recent SPM results do not yet obtain a good overall score; coloured dissolved organic matter (CDOM) should be included in the calculation of the light regime; more complexity in the phytoplankton model improves the chlorophyll- a simulation, but the simulated species composition needs further improvement for some of the functional groups.
Platform-Independence and Scheduling In a Multi-Threaded Real-Time Simulation
NASA Technical Reports Server (NTRS)
Sugden, Paul P.; Rau, Melissa A.; Kenney, P. Sean
2001-01-01
Aviation research often relies on real-time, pilot-in-the-loop flight simulation as a means to develop new flight software, flight hardware, or pilot procedures. Often these simulations become so complex that a single processor is incapable of performing the necessary computations within a fixed time-step. Threads are an elegant means to distribute the computational work-load when running on a symmetric multi-processor machine. However, programming with threads often requires operating system specific calls that reduce code portability and maintainability. While a multi-threaded simulation allows a significant increase in the simulation complexity, it also increases the workload of a simulation operator by requiring that the operator determine which models run on which thread. To address these concerns an object-oriented design was implemented in the NASA Langley Standard Real-Time Simulation in C++ (LaSRS++) application framework. The design provides a portable and maintainable means to use threads and also provides a mechanism to automatically load balance the simulation models.
NASA Astrophysics Data System (ADS)
Ammouri, Aymen; Ben Salah, Walid; Khachroumi, Sofiane; Ben Salah, Tarek; Kourda, Ferid; Morel, Hervé
2014-05-01
Design of integrated power converters needs prototype-less approaches. Specific simulations are required for investigation and validation process. Simulation relies on active and passive device models. Models of planar devices, for instance, are still not available in power simulator tools. There is, thus, a specific limitation during the simulation process of integrated power systems. The paper focuses on the development of a physically-based planar inductor model and its validation inside a power converter during transient switching. The planar inductor model remains a complex device to model, particularly when the skin, the proximity and the parasitic capacitances effects are taken into account. Heterogeneous simulation scheme, including circuit and device models, is successfully implemented in VHDL-AMS language and simulated in Simplorer platform. The mixed simulation results has been favorably tested and compared with practical measurements. It is found that the multi-domain simulation results and measurements data are in close agreement.
NASA Astrophysics Data System (ADS)
Mottes, Charles; Lesueur-Jannoyer, Magalie; Charlier, Jean-Baptiste; Carles, Céline; Guéné, Mathilde; Le Bail, Marianne; Malézieux, Eric
2015-10-01
Simulation of flows and pollutant transfers in heterogeneous media is widely recognized to be a remaining frontier in hydrology research. We present a new modeling approach to simulate agricultural pollutions in watersheds: WATPPASS, a model for Watershed Agricultural Techniques and Pesticide Practices ASSessment. It is designed to assess mean pesticide concentrations and loads that result from the use of pesticides in horticultural watersheds located on heterogeneous subsoil. WATPPASS is suited for small watershed with significant groundwater flows and complex aquifer systems. The model segments the watershed into fields with independent hydrological and pesticide transfers at the ground surface. Infiltrated water and pesticides are routed toward outlet using a conceptual reservoir model. We applied WATPPASS on a heterogeneous tropical volcanic watershed of Martinique in the French West Indies. We carried out and hydrological analysis that defined modeling constraints: (i) a spatial variability of runoff/infiltration partitioning according to land use, and (ii) a predominance of groundwater flow paths in two overlapping aquifers under permeable soils (50-60% of annual flows). We carried out simulations on a 550 days period at a daily time step for hydrology (Nashsqrt > 0.75). Weekly concentrations and loads of a persistent organic pesticide (chlordecone) were simulated for 67 weeks to evaluate the modeling approach. Pesticide simulations without specific calibration detected the mean long-term measured concentration, leading to a good quantification of the cumulative loads (5% error), but failed to represent the concentration peaks at the correct timing. Nevertheless, we succeed in adjusting the model structure to better represent the temporal dynamic of pesticide concentrations. This modification requires a proper evaluation on an independent dataset. Finally, WATPPASS is a compromise between complexity and easiness of use that makes it suited for cropping system assessment in complex pedological and geological environment.
Proposed best practice for projects that involve modelling and simulation.
O'Kelly, Michael; Anisimov, Vladimir; Campbell, Chris; Hamilton, Sinéad
2017-03-01
Modelling and simulation has been used in many ways when developing new treatments. To be useful and credible, it is generally agreed that modelling and simulation should be undertaken according to some kind of best practice. A number of authors have suggested elements required for best practice in modelling and simulation. Elements that have been suggested include the pre-specification of goals, assumptions, methods, and outputs. However, a project that involves modelling and simulation could be simple or complex and could be of relatively low or high importance to the project. It has been argued that the level of detail and the strictness of pre-specification should be allowed to vary, depending on the complexity and importance of the project. This best practice document does not prescribe how to develop a statistical model. Rather, it describes the elements required for the specification of a project and requires that the practitioner justify in the specification the omission of any of the elements and, in addition, justify the level of detail provided about each element. This document is an initiative of the Special Interest Group for modelling and simulation. The Special Interest Group for modelling and simulation is a body open to members of Statisticians in the Pharmaceutical Industry and the European Federation of Statisticians in the Pharmaceutical Industry. Examples of a very detailed specification and a less detailed specification are included as appendices. Copyright © 2016 John Wiley & Sons, Ltd.
Metabolic flexibility of mitochondrial respiratory chain disorders predicted by computer modelling.
Zieliński, Łukasz P; Smith, Anthony C; Smith, Alexander G; Robinson, Alan J
2016-11-01
Mitochondrial respiratory chain dysfunction causes a variety of life-threatening diseases affecting about 1 in 4300 adults. These diseases are genetically heterogeneous, but have the same outcome; reduced activity of mitochondrial respiratory chain complexes causing decreased ATP production and potentially toxic accumulation of metabolites. Severity and tissue specificity of these effects varies between patients by unknown mechanisms and treatment options are limited. So far most research has focused on the complexes themselves, and the impact on overall cellular metabolism is largely unclear. To illustrate how computer modelling can be used to better understand the potential impact of these disorders and inspire new research directions and treatments, we simulated them using a computer model of human cardiomyocyte mitochondrial metabolism containing over 300 characterised reactions and transport steps with experimental parameters taken from the literature. Overall, simulations were consistent with patient symptoms, supporting their biological and medical significance. These simulations predicted: complex I deficiencies could be compensated using multiple pathways; complex II deficiencies had less metabolic flexibility due to impacting both the TCA cycle and the respiratory chain; and complex III and IV deficiencies caused greatest decreases in ATP production with metabolic consequences that parallel hypoxia. Our study demonstrates how results from computer models can be compared to a clinical phenotype and used as a tool for hypothesis generation for subsequent experimental testing. These simulations can enhance understanding of dysfunctional mitochondrial metabolism and suggest new avenues for research into treatment of mitochondrial disease and other areas of mitochondrial dysfunction. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
In-vehicle group activity modeling and simulation in sensor-based virtual environment
NASA Astrophysics Data System (ADS)
Shirkhodaie, Amir; Telagamsetti, Durga; Poshtyar, Azin; Chan, Alex; Hu, Shuowen
2016-05-01
Human group activity recognition is a very complex and challenging task, especially for Partially Observable Group Activities (POGA) that occur in confined spaces with limited visual observability and often under severe occultation. In this paper, we present IRIS Virtual Environment Simulation Model (VESM) for the modeling and simulation of dynamic POGA. More specifically, we address sensor-based modeling and simulation of a specific category of POGA, called In-Vehicle Group Activities (IVGA). In VESM, human-alike animated characters, called humanoids, are employed to simulate complex in-vehicle group activities within the confined space of a modeled vehicle. Each articulated humanoid is kinematically modeled with comparable physical attributes and appearances that are linkable to its human counterpart. Each humanoid exhibits harmonious full-body motion - simulating human-like gestures and postures, facial impressions, and hands motions for coordinated dexterity. VESM facilitates the creation of interactive scenarios consisting of multiple humanoids with different personalities and intentions, which are capable of performing complicated human activities within the confined space inside a typical vehicle. In this paper, we demonstrate the efficiency and effectiveness of VESM in terms of its capabilities to seamlessly generate time-synchronized, multi-source, and correlated imagery datasets of IVGA, which are useful for the training and testing of multi-source full-motion video processing and annotation. Furthermore, we demonstrate full-motion video processing of such simulated scenarios under different operational contextual constraints.
Macroscopic modeling and simulations of supercoiled DNA with bound proteins
NASA Astrophysics Data System (ADS)
Huang, Jing; Schlick, Tamar
2002-11-01
General methods are presented for modeling and simulating DNA molecules with bound proteins on the macromolecular level. These new approaches are motivated by the need for accurate and affordable methods to simulate slow processes (on the millisecond time scale) in DNA/protein systems, such as the large-scale motions involved in the Hin-mediated inversion process. Our approaches, based on the wormlike chain model of long DNA molecules, introduce inhomogeneous potentials for DNA/protein complexes based on available atomic-level structures. Electrostatically, treat those DNA/protein complexes as sets of effective charges, optimized by our discrete surface charge optimization package, in which the charges are distributed on an excluded-volume surface that represents the macromolecular complex. We also introduce directional bending potentials as well as non-identical bead hydrodynamics algorithm to further mimic the inhomogeneous effects caused by protein binding. These models thus account for basic elements of protein binding effects on DNA local structure but remain computational tractable. To validate these models and methods, we reproduce various properties measured by both Monte Carlo methods and experiments. We then apply the developed models to study the Hin-mediated inversion system in long DNA. By simulating supercoiled, circular DNA with or without bound proteins, we observe significant effects of protein binding on global conformations and long-time dynamics of the DNA on the kilo basepair length.
NASA Astrophysics Data System (ADS)
Bharatham, Kavitha; Bharatham, Nagakumar; Kwon, Yong Jung; Lee, Keun Woo
2008-12-01
Allosteric inhibition of protein tyrosine phosphatase 1B (PTP1B), has paved a new path to design specific inhibitors for PTP1B, which is an important drug target for the treatment of type II diabetes and obesity. The PTP1B1-282-allosteric inhibitor complex crystal structure lacks α7 (287-298) and moreover there is no available 3D structure of PTP1B1-298 in open form. As the interaction between α7 and α6-α3 helices plays a crucial role in allosteric inhibition, α7 was modeled to the PTP1B1-282 in open form complexed with an allosteric inhibitor (compound-2) and a 5 ns MD simulation was performed to investigate the relative orientation of the α7-α6-α3 helices. The simulation conformational space was statistically sampled by clustering analyses. This approach was helpful to reveal certain clues on PTP1B allosteric inhibition. The simulation was also utilized in the generation of receptor based pharmacophore models to include the conformational flexibility of the protein-inhibitor complex. Three cluster representative structures of the highly populated clusters were selected for pharmacophore model generation. The three pharmacophore models were subsequently utilized for screening databases to retrieve molecules containing the features that complement the allosteric site. The retrieved hits were filtered based on certain drug-like properties and molecular docking simulations were performed in two different conformations of protein. Thus, performing MD simulation with α7 to investigate the changes at the allosteric site, then developing receptor based pharmacophore models and finally docking the retrieved hits into two distinct conformations will be a reliable methodology in identifying PTP1B allosteric inhibitors.
High-fidelity simulation capability for virtual testing of seismic and acoustic sensors
NASA Astrophysics Data System (ADS)
Wilson, D. Keith; Moran, Mark L.; Ketcham, Stephen A.; Lacombe, James; Anderson, Thomas S.; Symons, Neill P.; Aldridge, David F.; Marlin, David H.; Collier, Sandra L.; Ostashev, Vladimir E.
2005-05-01
This paper describes development and application of a high-fidelity, seismic/acoustic simulation capability for battlefield sensors. The purpose is to provide simulated sensor data so realistic that they cannot be distinguished by experts from actual field data. This emerging capability provides rapid, low-cost trade studies of unattended ground sensor network configurations, data processing and fusion strategies, and signatures emitted by prototype vehicles. There are three essential components to the modeling: (1) detailed mechanical signature models for vehicles and walkers, (2) high-resolution characterization of the subsurface and atmospheric environments, and (3) state-of-the-art seismic/acoustic models for propagating moving-vehicle signatures through realistic, complex environments. With regard to the first of these components, dynamic models of wheeled and tracked vehicles have been developed to generate ground force inputs to seismic propagation models. Vehicle models range from simple, 2D representations to highly detailed, 3D representations of entire linked-track suspension systems. Similarly detailed models of acoustic emissions from vehicle engines are under development. The propagation calculations for both the seismics and acoustics are based on finite-difference, time-domain (FDTD) methodologies capable of handling complex environmental features such as heterogeneous geologies, urban structures, surface vegetation, and dynamic atmospheric turbulence. Any number of dynamic sources and virtual sensors may be incorporated into the FDTD model. The computational demands of 3D FDTD simulation over tactical distances require massively parallel computers. Several example calculations of seismic/acoustic wave propagation through complex atmospheric and terrain environments are shown.
ERIC Educational Resources Information Center
Reid, Maurice; Brown, Steve; Tabibzadeh, Kambiz
2012-01-01
For the past decade teaching models have been changing, reflecting the dynamics, complexities, and uncertainties of today's organizations. The traditional and the more current active models of learning have disadvantages. Simulation provides a platform to combine the best aspects of both types of teaching practices. This research explores the…
USDA-ARS?s Scientific Manuscript database
The NTT (Nutrient Tracking Tool) was designed to provide an opportunity for all users, including producers, to simulate the complex models, such as APEX (Agricultural Policy Environmental eXtender) and associated required databases. The APEX model currently nested within NTT provides estimates of th...
Simulation of human behavior in exposure modeling is a complex task. Traditionally, inter-individual variation in human activity has been modeled by drawing from a pool of single day time-activity diaries such as the US EPA Consolidated Human Activity Database (CHAD). Here, an ag...
Specifying and Refining a Measurement Model for a Simulation-Based Assessment. CSE Report 619.
ERIC Educational Resources Information Center
Levy, Roy; Mislevy, Robert J.
2004-01-01
The challenges of modeling students' performance in simulation-based assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance in a complex assessment. This paper describes a Bayesian approach to modeling and estimating…
Simulation of tracer dispersion from elevated and surface releases in complex terrain
NASA Astrophysics Data System (ADS)
Hernández, J. F.; Cremades, L.; Baldasano, J. M.
A new version of an advanced mesoscale dispersion modeling system for simulating passive air pollutant dispersion in the real atmospheric planetary boundary layer (PBL), is presented. The system comprises a diagnostic mass-consistent meteorological model and a Lagrangian particle dispersion model (LADISMO). The former version of LADISMO, developed according to Zannetti (Air pollution modelling, 1990), was based on the Monte Carlo technique and included calculation of higher-order moments of vertical random forcing for convective conditions. Its ability to simulate complex flow dispersion has been stated in a previous paper (Hernández et al. 1995, Atmospheric Environment, 29A, 1331-1341). The new version follows Thomson's scheme (1984, Q. Jl Roy. Met. Soc.110, 1107-1120). It is also based on Langevin equation and follows the ideas given by Brusasca et al. (1992, Atmospheric Environment26A, 707-723) and Anfossi et al. (1992, Nuovo Cemento 15c, 139-158). The model is used to simulate the dispersion and predict the ground level concentration (g.l.c.) of a tracer (SF 6) released from both an elevated source ( case a) and a ground level source ( case b) in a highly complex mountainous terrain during neutral and synoptically dominated conditions ( case a) and light and apparently stable conditions ( case b). The last case is considered as being a specially difficult task to simulate. In fact, few works have reported situations with valley drainage flows in complex terrains and real stable atmospheric conditions with weak winds. The model assumes that nearly calm situations associated to strong stability and air stagnation, make the lowest layers of PBL poorly diffusive (Brusasca et al., 1992, Atmospheric Environment26A, 707-723). Model results are verified against experimental data from Guardo-90 tracer experiments, an intensive field campaign conducted in the Carrion river valley (Northern Spain) to study atmospheric diffusion within a steep walled valley in mountainous terrain (Ibarra, 1992, Energia, No. 1, 74-85).
Mathematical and Numerical Techniques in Energy and Environmental Modeling
NASA Astrophysics Data System (ADS)
Chen, Z.; Ewing, R. E.
Mathematical models have been widely used to predict, understand, and optimize many complex physical processes, from semiconductor or pharmaceutical design to large-scale applications such as global weather models to astrophysics. In particular, simulation of environmental effects of air pollution is extensive. Here we address the need for using similar models to understand the fate and transport of groundwater contaminants and to design in situ remediation strategies. Three basic problem areas need to be addressed in the modeling and simulation of the flow of groundwater contamination. First, one obtains an effective model to describe the complex fluid/fluid and fluid/rock interactions that control the transport of contaminants in groundwater. This includes the problem of obtaining accurate reservoir descriptions at various length scales and modeling the effects of this heterogeneity in the reservoir simulators. Next, one develops accurate discretization techniques that retain the important physical properties of the continuous models. Finally, one develops efficient numerical solution algorithms that utilize the potential of the emerging computing architectures. We will discuss recent advances and describe the contribution of each of the papers in this book in these three areas. Keywords: reservoir simulation, mathematical models, partial differential equations, numerical algorithms
Simulating physiological interactions in a hybrid system of mathematical models.
Kretschmer, Jörn; Haunsberger, Thomas; Drost, Erick; Koch, Edmund; Möller, Knut
2014-12-01
Mathematical models can be deployed to simulate physiological processes of the human organism. Exploiting these simulations, reactions of a patient to changes in the therapy regime can be predicted. Based on these predictions, medical decision support systems (MDSS) can help in optimizing medical therapy. An MDSS designed to support mechanical ventilation in critically ill patients should not only consider respiratory mechanics but should also consider other systems of the human organism such as gas exchange or blood circulation. A specially designed framework allows combining three model families (respiratory mechanics, cardiovascular dynamics and gas exchange) to predict the outcome of a therapy setting. Elements of the three model families are dynamically combined to form a complex model system with interacting submodels. Tests revealed that complex model combinations are not computationally feasible. In most patients, cardiovascular physiology could be simulated by simplified models decreasing computational costs. Thus, a simplified cardiovascular model that is able to reproduce basic physiological behavior is introduced. This model purely consists of difference equations and does not require special algorithms to be solved numerically. The model is based on a beat-to-beat model which has been extended to react to intrathoracic pressure levels that are present during mechanical ventilation. The introduced reaction to intrathoracic pressure levels as found during mechanical ventilation has been tuned to mimic the behavior of a complex 19-compartment model. Tests revealed that the model is able to represent general system behavior comparable to the 19-compartment model closely. Blood pressures were calculated with a maximum deviation of 1.8 % in systolic pressure and 3.5 % in diastolic pressure, leading to a simulation error of 0.3 % in cardiac output. The gas exchange submodel being reactive to changes in cardiac output showed a resulting deviation of less than 0.1 %. Therefore, the proposed model is usable in combinations where cardiovascular simulation does not have to be detailed. Computing costs have been decreased dramatically by a factor 186 compared to a model combination employing the 19-compartment model.
Amanzi: An Open-Source Multi-process Simulator for Environmental Applications
NASA Astrophysics Data System (ADS)
Moulton, J. D.; Molins, S.; Johnson, J. N.; Coon, E.; Lipnikov, K.; Day, M.; Barker, E.
2014-12-01
The Advanced Simulation Capabililty for Environmental Management (ASCEM) program is developing an approach and open-source tool suite for standardized risk and performance assessments at legacy nuclear waste sites. These assessments begin with simplified models, and add geometric and geologic complexity as understanding is gained. The Platform toolsets (Akuna) generates these conceptual models and Amanzi provides the computational engine to perform the simulations, returning the results for analysis and visualization. In this presentation we highlight key elements of the design, algorithms and implementations used in Amanzi. In particular, the hierarchical and modular design is aligned with the coupled processes being sumulated, and naturally supports a wide range of model complexity. This design leverages a dynamic data manager and the synergy of two graphs (one from the high-level perspective of the models the other from the dependencies of the variables in the model) to enable this flexible model configuration at run time. Moreover, to model sites with complex hydrostratigraphy, as well as engineered systems, we are developing a dual unstructured/structured capability. Recently, these capabilities have been collected in a framework named Arcos, and efforts have begun to improve interoperability between the unstructured and structured AMR approaches in Amanzi. To leverage a range of biogeochemistry capability from the community (e.g., CrunchFlow, PFLOTRAN, etc.), a biogeochemistry interface library was developed called Alquimia. To ensure that Amanzi is truly an open-source community code we require a completely open-source tool chain for our development. We will comment on elements of this tool chain, including the testing and documentation development tools such as docutils, and Sphinx. Finally, we will show simulation results from our phased demonstrations, including the geochemically complex Savannah River F-Area seepage basins.
NETIMIS: Dynamic Simulation of Health Economics Outcomes Using Big Data.
Johnson, Owen A; Hall, Peter S; Hulme, Claire
2016-02-01
Many healthcare organizations are now making good use of electronic health record (EHR) systems to record clinical information about their patients and the details of their healthcare. Electronic data in EHRs is generated by people engaged in complex processes within complex environments, and their human input, albeit shaped by computer systems, is compromised by many human factors. These data are potentially valuable to health economists and outcomes researchers but are sufficiently large and complex enough to be considered part of the new frontier of 'big data'. This paper describes emerging methods that draw together data mining, process modelling, activity-based costing and dynamic simulation models. Our research infrastructure includes safe links to Leeds hospital's EHRs with 3 million secondary and tertiary care patients. We created a multidisciplinary team of health economists, clinical specialists, and data and computer scientists, and developed a dynamic simulation tool called NETIMIS (Network Tools for Intervention Modelling with Intelligent Simulation; http://www.netimis.com ) suitable for visualization of both human-designed and data-mined processes which can then be used for 'what-if' analysis by stakeholders interested in costing, designing and evaluating healthcare interventions. We present two examples of model development to illustrate how dynamic simulation can be informed by big data from an EHR. We found the tool provided a focal point for multidisciplinary team work to help them iteratively and collaboratively 'deep dive' into big data.
A hybrid parallel framework for the cellular Potts model simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jiang, Yi; He, Kejing; Dong, Shoubin
2009-01-01
The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approachmore » achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).« less
A 3D virtual reality simulator for training of minimally invasive surgery.
Mi, Shao-Hua; Hou, Zeng-Gunag; Yang, Fan; Xie, Xiao-Liang; Bian, Gui-Bin
2014-01-01
For the last decade, remarkable progress has been made in the field of cardiovascular disease treatment. However, these complex medical procedures require a combination of rich experience and technical skills. In this paper, a 3D virtual reality simulator for core skills training in minimally invasive surgery is presented. The system can generate realistic 3D vascular models segmented from patient datasets, including a beating heart, and provide a real-time computation of force and force feedback module for surgical simulation. Instruments, such as a catheter or guide wire, are represented by a multi-body mass-spring model. In addition, a realistic user interface with multiple windows and real-time 3D views are developed. Moreover, the simulator is also provided with a human-machine interaction module that gives doctors the sense of touch during the surgery training, enables them to control the motion of a virtual catheter/guide wire inside a complex vascular model. Experimental results show that the simulator is suitable for minimally invasive surgery training.
The cost of conservative synchronization in parallel discrete event simulations
NASA Technical Reports Server (NTRS)
Nicol, David M.
1990-01-01
The performance of a synchronous conservative parallel discrete-event simulation protocol is analyzed. The class of simulation models considered is oriented around a physical domain and possesses a limited ability to predict future behavior. A stochastic model is used to show that as the volume of simulation activity in the model increases relative to a fixed architecture, the complexity of the average per-event overhead due to synchronization, event list manipulation, lookahead calculations, and processor idle time approach the complexity of the average per-event overhead of a serial simulation. The method is therefore within a constant factor of optimal. The analysis demonstrates that on large problems--those for which parallel processing is ideally suited--there is often enough parallel workload so that processors are not usually idle. The viability of the method is also demonstrated empirically, showing how good performance is achieved on large problems using a thirty-two node Intel iPSC/2 distributed memory multiprocessor.
NASA Technical Reports Server (NTRS)
Rothhaar, Paul M.; Murphy, Patrick C.; Bacon, Barton J.; Gregory, Irene M.; Grauer, Jared A.; Busan, Ronald C.; Croom, Mark A.
2014-01-01
Control of complex Vertical Take-Off and Landing (VTOL) aircraft traversing from hovering to wing born flight mode and back poses notoriously difficult modeling, simulation, control, and flight-testing challenges. This paper provides an overview of the techniques and advances required to develop the GL-10 tilt-wing, tilt-tail, long endurance, VTOL aircraft control system. The GL-10 prototype's unusual and complex configuration requires application of state-of-the-art techniques and some significant advances in wind tunnel infrastructure automation, efficient Design Of Experiments (DOE) tunnel test techniques, modeling, multi-body equations of motion, multi-body actuator models, simulation, control algorithm design, and flight test avionics, testing, and analysis. The following compendium surveys key disciplines required to develop an effective control system for this challenging vehicle in this on-going effort.
NASA Astrophysics Data System (ADS)
Li, Zhanjie; Yu, Jingshan; Xu, Xinyi; Sun, Wenchao; Pang, Bo; Yue, Jiajia
2018-06-01
Hydrological models are important and effective tools for detecting complex hydrological processes. Different models have different strengths when capturing the various aspects of hydrological processes. Relying on a single model usually leads to simulation uncertainties. Ensemble approaches, based on multi-model hydrological simulations, can improve application performance over single models. In this study, the upper Yalongjiang River Basin was selected for a case study. Three commonly used hydrological models (SWAT, VIC, and BTOPMC) were selected and used for independent simulations with the same input and initial values. Then, the BP neural network method was employed to combine the results from the three models. The results show that the accuracy of BP ensemble simulation is better than that of the single models.
Matlab Geochemistry: An open source geochemistry solver based on MRST
NASA Astrophysics Data System (ADS)
McNeece, C. J.; Raynaud, X.; Nilsen, H.; Hesse, M. A.
2017-12-01
The study of geological systems often requires the solution of complex geochemical relations. To address this need we present an open source geochemical solver based on the Matlab Reservoir Simulation Toolbox (MRST) developed by SINTEF. The implementation supports non-isothermal multicomponent aqueous complexation, surface complexation, ion exchange, and dissolution/precipitation reactions. The suite of tools available in MRST allows for rapid model development, in particular the incorporation of geochemical calculations into transport simulations of multiple phases, complex domain geometry and geomechanics. Different numerical schemes and additional physics can be easily incorporated into the existing tools through the object-oriented framework employed by MRST. The solver leverages the automatic differentiation tools available in MRST to solve arbitrarily complex geochemical systems with any choice of species or element concentration as input. Four mathematical approaches enable the solver to be quite robust: 1) the choice of chemical elements as the basis components makes all entries in the composition matrix positive thus preserving convexity, 2) a log variable transformation is used which transfers the nonlinearity to the convex composition matrix, 3) a priori bounds on variables are calculated from the structure of the problem, constraining Netwon's path and 4) an initial guess is calculated implicitly by sequentially adding model complexity. As a benchmark we compare the model to experimental and semi-analytic solutions of the coupled salinity-acidity transport system. Together with the reservoir simulation capabilities of MRST the solver offers a promising tool for geochemical simulations in reservoir domains for applications in a diversity of fields from enhanced oil recovery to radionuclide storage.
Behavior of the gypsy moth life system model and development of synoptic model formulations
J. J. Colbert; Xu Rumei
1991-01-01
Aims of the research: The gypsy moth life system model (GMLSM) is a complex model which incorporates numerous components (both biotic and abiotic) and ecological processes. It is a detailed simulation model which has much biological reality. However, it has not yet been tested with life system data. For such complex models, evaluation and testing cannot be adequately...
Analysing initial attack on wildland fires using stochastic simulation.
Jeremy S. Fried; J. Keith Gilless; James Spero
2006-01-01
Stochastic simulation models of initial attack on wildland fire can be designed to reflect the complexity of the environmental, administrative, and institutional context in which wildland fire protection agencies operate, but such complexity may come at the cost of a considerable investment in data acquisition and management. This cost may be well justified when it...
Virtual planning for craniomaxillofacial surgery--7 years of experience.
Adolphs, Nicolai; Haberl, Ernst-Johannes; Liu, Weichen; Keeve, Erwin; Menneking, Horst; Hoffmeister, Bodo
2014-07-01
Contemporary computer-assisted surgery systems more and more allow for virtual simulation of even complex surgical procedures with increasingly realistic predictions. Preoperative workflows are established and different commercially software solutions are available. Potential and feasibility of virtual craniomaxillofacial surgery as an additional planning tool was assessed retrospectively by comparing predictions and surgical results. Since 2006 virtual simulation has been performed in selected patient cases affected by complex craniomaxillofacial disorders (n = 8) in addition to standard surgical planning based on patient specific 3d-models. Virtual planning could be performed for all levels of the craniomaxillofacial framework within a reasonable preoperative workflow. Simulation of even complex skeletal displacements corresponded well with the real surgical result and soft tissue simulation proved to be helpful. In combination with classic 3d-models showing the underlying skeletal pathology virtual simulation improved planning and transfer of craniomaxillofacial corrections. Additional work and expenses may be justified by increased possibilities of visualisation, information, instruction and documentation in selected craniomaxillofacial procedures. Copyright © 2013 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
USDA-ARS?s Scientific Manuscript database
Simulation of vertical soil hydrology is a critical component of simulating even more complex soil water dynamics in space and time, including land-atmosphere and subsurface interactions. The AgroEcoSystem (AgES) model is defined here as a single land unit implementation of the full AgES-W (Watershe...
Constitutive Model Calibration via Autonomous Multiaxial Experimentation (Postprint)
2016-09-17
test machine. Experimental data is reduced and finite element simulations are conducted in parallel with the test based on experimental strain...data is reduced and finite element simulations are conducted in parallel with the test based on experimental strain conditions. Optimization methods...be used directly in finite element simulations of more complex geometries. Keywords Axial/torsional experimentation • Plasticity • Constitutive model
Stochastic Simulation Using @ Risk for Dairy Business Investment Decisions
USDA-ARS?s Scientific Manuscript database
A dynamic, stochastic, mechanistic simulation model of a dairy business was developed to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting fram...
Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas
2017-01-01
Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948
USDA-ARS?s Scientific Manuscript database
Complex watershed simulation models are powerful tools that can help scientists and policy-makers address challenging topics, such as land use management and water security. In the Western Lake Erie Basin (WLEB), complex hydrological models have been applied at various scales to help describe relat...
An ecohydrologic model for a shallow groundwater urban environment.
Arden, Sam; Ma, Xin Cissy; Brown, Mark
2014-01-01
The urban environment is a patchwork of natural and artificial surfaces that results in complex interactions with and impacts to natural hydrologic cycles. Evapotranspiration is a major hydrologic flow that is often altered through urbanization, although the mechanisms of change are sometimes difficult to tease out due to difficulty in effectively simulating soil-plant-atmosphere interactions. This paper introduces a simplified yet realistic model that is a combination of existing surface runoff and ecohydrology models designed to increase the quantitative understanding of complex urban hydrologic processes. Results demonstrate that the model is capable of simulating the long-term variability of major hydrologic fluxes as a function of impervious surface, temperature, water table elevation, canopy interception, soil characteristics, precipitation and complex mechanisms of plant water uptake. These understandings have potential implications for holistic urban water system management.
Building Blocks for Reliable Complex Nonlinear Numerical Simulations
NASA Technical Reports Server (NTRS)
Yee, H. C.; Mansour, Nagi N. (Technical Monitor)
2002-01-01
This talk describes some of the building blocks to ensure a higher level of confidence in the predictability and reliability (PAR) of numerical simulation of multiscale complex nonlinear problems. The focus is on relating PAR of numerical simulations with complex nonlinear phenomena of numerics. To isolate sources of numerical uncertainties, the possible discrepancy between the chosen partial differential equation (PDE) model and the real physics and/or experimental data is set aside. The discussion is restricted to how well numerical schemes can mimic the solution behavior of the underlying PDE model for finite time steps and grid spacings. The situation is complicated by the fact that the available theory for the understanding of nonlinear behavior of numerics is not at a stage to fully analyze the nonlinear Euler and Navier-Stokes equations. The discussion is based on the knowledge gained for nonlinear model problems with known analytical solutions to identify and explain the possible sources and remedies of numerical uncertainties in practical computations. Examples relevant to turbulent flow computations are included.
Building Blocks for Reliable Complex Nonlinear Numerical Simulations
NASA Technical Reports Server (NTRS)
Yee, H. C.
2005-01-01
This chapter describes some of the building blocks to ensure a higher level of confidence in the predictability and reliability (PAR) of numerical simulation of multiscale complex nonlinear problems. The focus is on relating PAR of numerical simulations with complex nonlinear phenomena of numerics. To isolate sources of numerical uncertainties, the possible discrepancy between the chosen partial differential equation (PDE) model and the real physics and/or experimental data is set aside. The discussion is restricted to how well numerical schemes can mimic the solution behavior of the underlying PDE model for finite time steps and grid spacings. The situation is complicated by the fact that the available theory for the understanding of nonlinear behavior of numerics is not at a stage to fully analyze the nonlinear Euler and Navier-Stokes equations. The discussion is based on the knowledge gained for nonlinear model problems with known analytical solutions to identify and explain the possible sources and remedies of numerical uncertainties in practical computations.
Building Blocks for Reliable Complex Nonlinear Numerical Simulations. Chapter 2
NASA Technical Reports Server (NTRS)
Yee, H. C.; Mansour, Nagi N. (Technical Monitor)
2001-01-01
This chapter describes some of the building blocks to ensure a higher level of confidence in the predictability and reliability (PAR) of numerical simulation of multiscale complex nonlinear problems. The focus is on relating PAR of numerical simulations with complex nonlinear phenomena of numerics. To isolate sources of numerical uncertainties, the possible discrepancy between the chosen partial differential equation (PDE) model and the real physics and/or experimental data is set aside. The discussion is restricted to how well numerical schemes can mimic the solution behavior of the underlying PDE model for finite time steps and grid spacings. The situation is complicated by the fact that the available theory for the understanding of nonlinear behavior of numerics is not at a stage to fully analyze the nonlinear Euler and Navier-Stokes equations. The discussion is based on the knowledge gained for nonlinear model problems with known analytical solutions to identify and explain the possible sources and remedies of numerical uncertainties in practical computations. Examples relevant to turbulent flow computations are included.
NASA Astrophysics Data System (ADS)
Xu, Haixuan; Osetsky, Yury N.; Stoller, Roger E.
2011-10-01
An accelerated atomistic kinetic Monte Carlo (KMC) approach for evolving complex atomistic structures has been developed. The method incorporates on-the-fly calculations of transition states (TSs) with a scheme for defining active volumes (AVs) in an off-lattice (relaxed) system. In contrast to conventional KMC models that require all reactions to be predetermined, this approach is self-evolving and any physically relevant motion or reaction may occur. Application of this self-evolving atomistic kinetic Monte Carlo (SEAK-MC) approach is illustrated by predicting the evolution of a complex defect configuration obtained in a molecular dynamics (MD) simulation of a displacement cascade in Fe. Over much longer times, it was shown that interstitial clusters interacting with other defects may change their structure, e.g., from glissile to sessile configuration. The direct comparison with MD modeling confirms the atomistic fidelity of the approach, while the longer time simulation demonstrates the unique capability of the model.
Block Oriented Simulation System (BOSS)
NASA Technical Reports Server (NTRS)
Ratcliffe, Jaimie
1988-01-01
Computer simulation is assuming greater importance as a flexible and expedient approach to modeling system and subsystem behavior. Simulation has played a key role in the growth of complex, multiple access space communications such as those used by the space shuttle and the TRW-built Tracking and Data Relay Satellites (TDRS). A powerful new simulator for use in designing and modeling the communication system of NASA's planned Space Station is being developed. Progress to date on the Block (Diagram) Oriented Simulation System (BOSS) is described.
System-of-Systems Approach for Integrated Energy Systems Modeling and Simulation: Preprint
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mittal, Saurabh; Ruth, Mark; Pratt, Annabelle
Today’s electricity grid is the most complex system ever built—and the future grid is likely to be even more complex because it will incorporate distributed energy resources (DERs) such as wind, solar, and various other sources of generation and energy storage. The complexity is further augmented by the possible evolution to new retail market structures that provide incentives to owners of DERs to support the grid. To understand and test new retail market structures and technologies such as DERs, demand-response equipment, and energy management systems while providing reliable electricity to all customers, an Integrated Energy System Model (IESM) is beingmore » developed at NREL. The IESM is composed of a power flow simulator (GridLAB-D), home energy management systems implemented using GAMS/Pyomo, a market layer, and hardware-in-the-loop simulation (testing appliances such as HVAC, dishwasher, etc.). The IESM is a system-of-systems (SoS) simulator wherein the constituent systems are brought together in a virtual testbed. We will describe an SoS approach for developing a distributed simulation environment. We will elaborate on the methodology and the control mechanisms used in the co-simulation illustrated by a case study.« less
Data-driven non-linear elasticity: constitutive manifold construction and problem discretization
NASA Astrophysics Data System (ADS)
Ibañez, Ruben; Borzacchiello, Domenico; Aguado, Jose Vicente; Abisset-Chavanne, Emmanuelle; Cueto, Elias; Ladeveze, Pierre; Chinesta, Francisco
2017-11-01
The use of constitutive equations calibrated from data has been implemented into standard numerical solvers for successfully addressing a variety problems encountered in simulation-based engineering sciences (SBES). However, the complexity remains constantly increasing due to the need of increasingly detailed models as well as the use of engineered materials. Data-Driven simulation constitutes a potential change of paradigm in SBES. Standard simulation in computational mechanics is based on the use of two very different types of equations. The first one, of axiomatic character, is related to balance laws (momentum, mass, energy,\\ldots ), whereas the second one consists of models that scientists have extracted from collected, either natural or synthetic, data. Data-driven (or data-intensive) simulation consists of directly linking experimental data to computers in order to perform numerical simulations. These simulations will employ laws, universally recognized as epistemic, while minimizing the need of explicit, often phenomenological, models. The main drawback of such an approach is the large amount of required data, some of them inaccessible from the nowadays testing facilities. Such difficulty can be circumvented in many cases, and in any case alleviated, by considering complex tests, collecting as many data as possible and then using a data-driven inverse approach in order to generate the whole constitutive manifold from few complex experimental tests, as discussed in the present work.
Pflock, Tobias J; Oellerich, Silke; Krapf, Lisa; Southall, June; Cogdell, Richard J; Ullmann, G Matthias; Köhler, Jürgen
2011-07-21
We performed time-resolved spectroscopy on homoarrays of LH2 complexes from the photosynthetic purple bacterium Rhodopseudomonas acidophila. Variations of the fluorescence transients were monitored as a function of the excitation fluence and the repetition rate of the excitation. These parameters are directly related to the excitation density within the array and to the number of LH2 complexes that still carry a triplet state prior to the next excitation. Comparison of the experimental observations with results from dynamic Monte Carlo simulations for a model cluster of LH2 complexes yields qualitative agreement without the need for any free parameter and reveals the mutual relationship between energy transfer and annihilation processes.
The analysis of a generic air-to-air missile simulation model
NASA Technical Reports Server (NTRS)
Kaplan, Joseph A.; Chappell, Alan R.; Mcmanus, John W.
1994-01-01
A generic missile model was developed to evaluate the benefits of using a dynamic missile fly-out simulation system versus a static missile launch envelope system for air-to-air combat simulation. This paper examines the performance of a launch envelope model and a missile fly-out model. The launch envelope model bases its probability of killing the target aircraft on the target aircraft's position at the launch time of the weapon. The benefits gained from a launch envelope model are the simplicity of implementation and the minimal computational overhead required. A missile fly-out model takes into account the physical characteristics of the missile as it simulates the guidance, propulsion, and movement of the missile. The missile's probability of kill is based on the missile miss distance (or the minimum distance between the missile and the target aircraft). The problems associated with this method of modeling are a larger computational overhead, the additional complexity required to determine the missile miss distance, and the additional complexity of determining the reason(s) the missile missed the target. This paper evaluates the two methods and compares the results of running each method on a comprehensive set of test conditions.
Simulating Vibrations in a Complex Loaded Structure
NASA Technical Reports Server (NTRS)
Cao, Tim T.
2005-01-01
The Dynamic Response Computation (DIRECT) computer program simulates vibrations induced in a complex structure by applied dynamic loads. Developed to enable rapid analysis of launch- and landing- induced vibrations and stresses in a space shuttle, DIRECT also can be used to analyze dynamic responses of other structures - for example, the response of a building to an earthquake, or the response of an oil-drilling platform and attached tanks to large ocean waves. For a space-shuttle simulation, the required input to DIRECT includes mathematical models of the space shuttle and its payloads, and a set of forcing functions that simulates launch and landing loads. DIRECT can accommodate multiple levels of payload attachment and substructure as well as nonlinear dynamic responses of structural interfaces. DIRECT combines the shuttle and payload models into a single structural model, to which the forcing functions are then applied. The resulting equations of motion are reduced to an optimum set and decoupled into a unique format for simulating dynamics. During the simulation, maximum vibrations, loads, and stresses are monitored and recorded for subsequent analysis to identify structural deficiencies in the shuttle and/or payloads.
CHARMM-GUI 10 Years for Biomolecular Modeling and Simulation
Jo, Sunhwan; Cheng, Xi; Lee, Jumin; Kim, Seonghoon; Park, Sang-Jun; Patel, Dhilon S.; Beaven, Andrew H.; Lee, Kyu Il; Rui, Huan; Roux, Benoît; MacKerell, Alexander D.; Klauda, Jeffrey B.; Qi, Yifei
2017-01-01
CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the molecular details of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. PMID:27862047
CHARMM-GUI 10 years for biomolecular modeling and simulation.
Jo, Sunhwan; Cheng, Xi; Lee, Jumin; Kim, Seonghoon; Park, Sang-Jun; Patel, Dhilon S; Beaven, Andrew H; Lee, Kyu Il; Rui, Huan; Park, Soohyung; Lee, Hui Sun; Roux, Benoît; MacKerell, Alexander D; Klauda, Jeffrey B; Qi, Yifei; Im, Wonpil
2017-06-05
CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
FEA Simulation of Free-Bending - a Preforming Step in the Hydroforming Process Chain
NASA Astrophysics Data System (ADS)
Beulich, N.; Craighero, P.; Volk, W.
2017-09-01
High-strength steel and aluminum alloys are essential for developing innovative, lightly-weighted space frame concepts. The intended design is built from car body parts with high geometrical complexity and reduced material-thickness. Over the past few years, many complex car body parts have been produced using hydroforming. To increase the accuracy of hydroforming in relation to prospective car concepts, the virtual manufacturing of forming becomes more important. As a part of process digitalization, it is necessary to develop a simulation model for the hydroforming process chain. The preforming of longitudinal welded tubes is therefore implemented by the use of three-dimensional free-bending. This technique is able to reproduce complex deflection curves in combination with innovative low-thickness material design for hydroforming processes. As a first step to the complete process simulation, the content of this paper deals with the development of a finite element simulation model for the free-bending process with 6 degrees of freedom. A mandrel built from spherical segments connected by a steel rope is located inside of the tube to prevent geometrical instability. Critical parameters for the result of the bending process are therefore evaluated and optimized. The simulation model is verified by surface measurements of a two-dimensional bending test.
Modeling hydraulic regenerative hybrid vehicles using AMESim and Matlab/Simulink
NASA Astrophysics Data System (ADS)
Lynn, Alfred; Smid, Edzko; Eshraghi, Moji; Caldwell, Niall; Woody, Dan
2005-05-01
This paper presents the overview of the simulation modeling of a hydraulic system with regenerative braking used to improve vehicle emissions and fuel economy. Two simulation software packages were used together to enhance the simulation capability for fuel economy results and development of vehicle and hybrid control strategy. AMESim, a hydraulic simulation software package modeled the complex hydraulic circuit and component hardware and was interlinked with a Matlab/Simulink model of the vehicle, engine and the control strategy required to operate the vehicle and the hydraulic hybrid system through various North American and European drive cycles.
Simulating wall and corner fire tests on wood products with the OSU room fire model
H. C. Tran
1994-01-01
This work demonstrates the complexity of modeling wall and corner fires in a compartment. The model chosen for this purpose is the Ohio State University (OSU) room fire model. This model was designed to simulate fire growth on walls in a compartment and therefore lends itself to direct comparison with standard room test results. The model input were bench-scale data...
Mesh-based Monte Carlo code for fluorescence modeling in complex tissues with irregular boundaries
NASA Astrophysics Data System (ADS)
Wilson, Robert H.; Chen, Leng-Chun; Lloyd, William; Kuo, Shiuhyang; Marcelo, Cynthia; Feinberg, Stephen E.; Mycek, Mary-Ann
2011-07-01
There is a growing need for the development of computational models that can account for complex tissue morphology in simulations of photon propagation. We describe the development and validation of a user-friendly, MATLAB-based Monte Carlo code that uses analytically-defined surface meshes to model heterogeneous tissue geometry. The code can use information from non-linear optical microscopy images to discriminate the fluorescence photons (from endogenous or exogenous fluorophores) detected from different layers of complex turbid media. We present a specific application of modeling a layered human tissue-engineered construct (Ex Vivo Produced Oral Mucosa Equivalent, EVPOME) designed for use in repair of oral tissue following surgery. Second-harmonic generation microscopic imaging of an EVPOME construct (oral keratinocytes atop a scaffold coated with human type IV collagen) was employed to determine an approximate analytical expression for the complex shape of the interface between the two layers. This expression can then be inserted into the code to correct the simulated fluorescence for the effect of the irregular tissue geometry.
Turbulence modeling for Francis turbine water passages simulation
NASA Astrophysics Data System (ADS)
Maruzewski, P.; Hayashi, H.; Munch, C.; Yamaishi, K.; Hashii, T.; Mombelli, H. P.; Sugow, Y.; Avellan, F.
2010-08-01
The applications of Computational Fluid Dynamics, CFD, to hydraulic machines life require the ability to handle turbulent flows and to take into account the effects of turbulence on the mean flow. Nowadays, Direct Numerical Simulation, DNS, is still not a good candidate for hydraulic machines simulations due to an expensive computational time consuming. Large Eddy Simulation, LES, even, is of the same category of DNS, could be an alternative whereby only the small scale turbulent fluctuations are modeled and the larger scale fluctuations are computed directly. Nevertheless, the Reynolds-Averaged Navier-Stokes, RANS, model have become the widespread standard base for numerous hydraulic machine design procedures. However, for many applications involving wall-bounded flows and attached boundary layers, various hybrid combinations of LES and RANS are being considered, such as Detached Eddy Simulation, DES, whereby the RANS approximation is kept in the regions where the boundary layers are attached to the solid walls. Furthermore, the accuracy of CFD simulations is highly dependent on the grid quality, in terms of grid uniformity in complex configurations. Moreover any successful structured and unstructured CFD codes have to offer a wide range to the variety of classic RANS model to hybrid complex model. The aim of this study is to compare the behavior of turbulent simulations for both structured and unstructured grids topology with two different CFD codes which used the same Francis turbine. Hence, the study is intended to outline the encountered discrepancy for predicting the wake of turbine blades by using either the standard k-epsilon model, or the standard k-epsilon model or the SST shear stress model in a steady CFD simulation. Finally, comparisons are made with experimental data from the EPFL Laboratory for Hydraulic Machines reduced scale model measurements.
A Practical Philosophy of Complex Climate Modelling
NASA Technical Reports Server (NTRS)
Schmidt, Gavin A.; Sherwood, Steven
2014-01-01
We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.
Managing resource capacity using hybrid simulation
NASA Astrophysics Data System (ADS)
Ahmad, Norazura; Ghani, Noraida Abdul; Kamil, Anton Abdulbasah; Tahar, Razman Mat
2014-12-01
Due to the diversity of patient flows and interdependency of the emergency department (ED) with other units in hospital, the use of analytical models seems not practical for ED modeling. One effective approach to study the dynamic complexity of ED problems is by developing a computer simulation model that could be used to understand the structure and behavior of the system. Attempts to build a holistic model using DES only will be too complex while if only using SD will lack the detailed characteristics of the system. This paper discusses the combination of DES and SD in order to get a better representation of the actual system than using either modeling paradigm solely. The model is developed using AnyLogic software that will enable us to study patient flows and the complex interactions among hospital resources for ED operations. Results from the model show that patients' length of stay is influenced by laboratories turnaround time, bed occupancy rate and ward admission rate.
SIM_EXPLORE: Software for Directed Exploration of Complex Systems
NASA Technical Reports Server (NTRS)
Burl, Michael; Wang, Esther; Enke, Brian; Merline, William J.
2013-01-01
Physics-based numerical simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. While such codes may provide the highest- fidelity representation of system behavior, they are often so slow to run that insight into the system is limited. Trying to understand the effects of inputs on outputs by conducting an exhaustive grid-based sweep over the input parameter space is simply too time-consuming. An alternative approach called "directed exploration" has been developed to harvest information from numerical simulators more efficiently. The basic idea is to employ active learning and supervised machine learning to choose cleverly at each step which simulation trials to run next based on the results of previous trials. SIM_EXPLORE is a new computer program that uses directed exploration to explore efficiently complex systems represented by numerical simulations. The software sequentially identifies and runs simulation trials that it believes will be most informative given the results of previous trials. The results of new trials are incorporated into the software's model of the system behavior. The updated model is then used to pick the next round of new trials. This process, implemented as a closed-loop system wrapped around existing simulation code, provides a means to improve the speed and efficiency with which a set of simulations can yield scientifically useful results. The software focuses on the case in which the feedback from the simulation trials is binary-valued, i.e., the learner is only informed of the success or failure of the simulation trial to produce a desired output. The software offers a number of choices for the supervised learning algorithm (the method used to model the system behavior given the results so far) and a number of choices for the active learning strategy (the method used to choose which new simulation trials to run given the current behavior model). The software also makes use of the LEGION distributed computing framework to leverage the power of a set of compute nodes. The approach has been demonstrated on a planetary science application in which numerical simulations are used to study the formation of asteroid families.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Celia, Michael A.
This report documents the accomplishments achieved during the project titled “Model complexity and choice of model approaches for practical simulations of CO 2 injection,migration, leakage and long-term fate” funded by the US Department of Energy, Office of Fossil Energy. The objective of the project was to investigate modeling approaches of various levels of complexity relevant to geologic carbon storage (GCS) modeling with the goal to establish guidelines on choice of modeling approach.
Simulation model of a gear synchronisation unit for application in a real-time HiL environment
NASA Astrophysics Data System (ADS)
Kirchner, Markus; Eberhard, Peter
2017-05-01
Gear shifting simulations using the multibody system approach and the finite-element method are standard in the development of transmissions. However, the corresponding models are typically large due to the complex geometries and numerous contacts, which causes long calculation times. The present work sets itself apart from these detailed shifting simulations by proposing a much simpler but powerful synchronisation model which can be computed in real-time while it is still more realistic than a pure rigid multibody model. Therefore, the model is even used as part of a Hardware-in-the-Loop (HiL) test rig. The proposed real-time capable synchronization model combines the rigid multibody system approach with a multiscale simulation approach. The multibody system approach is suitable for the description of the large motions. The multiscale simulation approach is using also the finite-element method suitable for the analysis of the contact processes. An efficient contact search for the claws of a car transmission synchronisation unit is described in detail which shortens the required calculation time of the model considerably. To further shorten the calculation time, the use of a complex pre-synchronisation model with a nonlinear contour is presented. The model has to provide realistic results with the time-step size of the HiL test rig. To reach this specification, a particularly adapted multirate method for the synchronisation model is shown. Measured results of test rigs of the real-time capable synchronisation model are verified on plausibility. The simulation model is then also used in the HiL test rig for a transmission control unit.
A computational microscopy study of nanostructural evolution in irradiated pressure vessel steels
NASA Astrophysics Data System (ADS)
Odette, G. R.; Wirth, B. D.
1997-11-01
Nanostructural features that form in reactor pressure vessel steels under neutron irradiation at around 300°C lead to significant hardening and embrittlement. Continuum thermodynamic-kinetic based rate theories have been very successful in modeling the general characteristics of the copper and manganese nickel rich precipitate evolution, often the dominant source of embrittlement. However, a more detailed atomic scale understanding of these features is needed to interpret experimental measurements and better underpin predictive embrittlement models. Further, other embrittling features, believed to be subnanometer defect (vacancy)-solute complexes and small regions of modest enrichment of solutes are not well understood. A general approach to modeling embrittlement nanostructures, based on the concept of a computational microscope, is described. The objective of the computational microscope is to self-consistently integrate atomic scale simulations with other sources of information, including a wide range of experiments. In this work, lattice Monte Carlo (LMC) simulations are used to resolve the chemically and structurally complex nature of CuMnNiSi precipitates. The LMC simulations unify various nanoscale analytical characterization methods and basic thermodynamics. The LMC simulations also reveal that significant coupled vacancy and solute clustering takes place during cascade aging. The cascade clustering produces the metastable vacancy-cluster solute complexes that mediate flux effects. Cascade solute clustering may also play a role in the formation of dilute atmospheres of solute enrichment and enhance the nucleation of manganese-nickel rich precipitates at low Cu levels. Further, the simulations suggest that complex, highly correlated processes (e.g. cluster diffusion, formation of favored vacancy diffusion paths and solute scavenging vacancy cluster complexes) may lead to anomalous fast thermal aging kinetics at temperatures below about 450°C. The potential technical significance of these phenomena is described.
NASA Astrophysics Data System (ADS)
Yadav, Basant; Ch, Sudheer; Mathur, Shashi; Adamowski, Jan
2016-12-01
In-situ bioremediation is the most common groundwater remediation procedure used for treating organically contaminated sites. A simulation-optimization approach, which incorporates a simulation model for groundwaterflow and transport processes within an optimization program, could help engineers in designing a remediation system that best satisfies management objectives as well as regulatory constraints. In-situ bioremediation is a highly complex, non-linear process and the modelling of such a complex system requires significant computational exertion. Soft computing techniques have a flexible mathematical structure which can generalize complex nonlinear processes. In in-situ bioremediation management, a physically-based model is used for the simulation and the simulated data is utilized by the optimization model to optimize the remediation cost. The recalling of simulator to satisfy the constraints is an extremely tedious and time consuming process and thus there is need for a simulator which can reduce the computational burden. This study presents a simulation-optimization approach to achieve an accurate and cost effective in-situ bioremediation system design for groundwater contaminated with BTEX (Benzene, Toluene, Ethylbenzene, and Xylenes) compounds. In this study, the Extreme Learning Machine (ELM) is used as a proxy simulator to replace BIOPLUME III for the simulation. The selection of ELM is done by a comparative analysis with Artificial Neural Network (ANN) and Support Vector Machine (SVM) as they were successfully used in previous studies of in-situ bioremediation system design. Further, a single-objective optimization problem is solved by a coupled Extreme Learning Machine (ELM)-Particle Swarm Optimization (PSO) technique to achieve the minimum cost for the in-situ bioremediation system design. The results indicate that ELM is a faster and more accurate proxy simulator than ANN and SVM. The total cost obtained by the ELM-PSO approach is held to a minimum while successfully satisfying all the regulatory constraints of the contaminated site.
Christ, Andreas; Thews, Oliver
2016-04-01
Mathematical models are suitable to simulate complex biological processes by a set of non-linear differential equations. These simulation models can be used as an e-learning tool in medical education. However, in many cases these mathematical systems have to be treated numerically which is computationally intensive. The aim of the study was to develop a system for numerical simulation to be used in an online e-learning environment. In the software system the simulation is located on the server as a CGI application. The user (student) selects the boundary conditions for the simulation (e.g., properties of a simulated patient) on the browser. With these parameters the simulation on the server is started and the simulation result is re-transferred to the browser. With this system two examples of e-learning units were realized. The first one uses a multi-compartment model of the glucose-insulin control loop for the simulation of the plasma glucose level after a simulated meal or during diabetes (including treatment by subcutaneous insulin application). The second one simulates the ion transport leading to the resting and action potential in nerves. The student can vary parameters systematically to explore the biological behavior of the system. The described system is able to simulate complex biological processes and offers the possibility to use these models in an online e-learning environment. As far as the underlying principles can be described mathematically, this type of system can be applied to a broad spectrum of biomedical or natural scientific topics. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Evaluating crown fire rate of spread predictions from physics-based models
C. M. Hoffman; J. Ziegler; J. Canfield; R. R. Linn; W. Mell; C. H. Sieg; F. Pimont
2015-01-01
Modeling the behavior of crown fires is challenging due to the complex set of coupled processes that drive the characteristics of a spreading wildfire and the large range of spatial and temporal scales over which these processes occur. Detailed physics-based modeling approaches such as FIRETEC and the Wildland Urban Interface Fire Dynamics Simulator (WFDS) simulate...
NASA Astrophysics Data System (ADS)
Faucci, Maria Teresa; Melani, Fabrizio; Mura, Paola
2002-06-01
Molecular modeling was used to investigate factors influencing complex formation between cyclodextrins and guest molecules and predict their stability through a theoretical model based on the search for a correlation between experimental stability constants ( Ks) and some theoretical parameters describing complexation (docking energy, host-guest contact surfaces, intermolecular interaction fields) calculated from complex structures at a minimum conformational energy, obtained through stochastic methods based on molecular dynamic simulations. Naproxen, ibuprofen, ketoprofen and ibuproxam were used as model drug molecules. Multiple Regression Analysis allowed identification of the significant factors for the complex stability. A mathematical model ( r=0.897) related log Ks with complex docking energy and lipophilic molecular fields of cyclodextrin and drug.
3D printing to simulate laparoscopic choledochal surgery.
Burdall, Oliver C; Makin, Erica; Davenport, Mark; Ade-Ajayi, Niyi
2016-05-01
Laparoscopic simulation has transformed skills acquisition for many procedures. However, realistic nonbiological simulators for complex reconstructive surgery are rare. Life-like tactile feedback is particularly difficult to reproduce. Technological innovations may contribute novel solutions to these shortages. We describe a hybrid model, harnessing 3D technology to simulate laparoscopic choledochal surgery for the first time. Digital hepatic anatomy images and standard laparoscopic trainer dimensions were employed to create an entry level laparoscopic choledochal surgery model. The information was fed into a 3D systems project 660pro with visijet pxl core powder to create a free standing liver mold. This included a cuboid portal in which to slot disposable hybrid components representing hepatic and pancreatic ducts and choledochal cyst. The mold was used to create soft silicone replicas with T28 resin and T5 fast catalyst. The model was assessed at a national pediatric surgery training day. The 10 delegates that trialed the simulation felt that the tactile likeness was good (5.6/10±1.71, 10=like the real thing), was not too complex (6.2/10±1.35; where 1=too simple, 10=too complicated), and generally very useful (7.36/10±1.57, 10=invaluable). 100% stated that they felt they could reproduce this in their own centers, and 100% would recommend this simulation to colleagues. Though this first phase choledochal cyst excision simulation requires further development, 3D printing provides a useful means of creating specific and detailed simulations for rare and complex operations with huge potential for development. Copyright © 2016. Published by Elsevier Inc.
Simulating the dynamics of complex plasmas.
Schwabe, M; Graves, D B
2013-08-01
Complex plasmas are low-temperature plasmas that contain micrometer-size particles in addition to the neutral gas particles and the ions and electrons that make up the plasma. The microparticles interact strongly and display a wealth of collective effects. Here we report on linked numerical simulations that reproduce many of the experimental results of complex plasmas. We model a capacitively coupled plasma with a fluid code written for the commercial package comsol. The output of this model is used to calculate forces on microparticles. The microparticles are modeled using the molecular dynamics package lammps, which we extended to include the forces from the plasma. Using this method, we are able to reproduce void formation, the separation of particles of different sizes into layers, lane formation, vortex formation, and other effects.
Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting
Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart
2015-02-14
Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equationsmore » at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.« less
PAM: Particle automata model in simulation of Fusarium graminearum pathogen expansion.
Wcisło, Rafał; Miller, S Shea; Dzwinel, Witold
2016-01-21
The multi-scale nature and inherent complexity of biological systems are a great challenge for computer modeling and classical modeling paradigms. We present a novel particle automata modeling metaphor in the context of developing a 3D model of Fusarium graminearum infection in wheat. The system consisting of the host plant and Fusarium pathogen cells can be represented by an ensemble of discrete particles defined by a set of attributes. The cells-particles can interact with each other mimicking mechanical resistance of the cell walls and cell coalescence. The particles can move, while some of their attributes can be changed according to prescribed rules. The rules can represent cellular scales of a complex system, while the integrated particle automata model (PAM) simulates its overall multi-scale behavior. We show that due to the ability of mimicking mechanical interactions of Fusarium tip cells with the host tissue, the model is able to simulate realistic penetration properties of the colonization process reproducing both vertical and lateral Fusarium invasion scenarios. The comparison of simulation results with micrographs from laboratory experiments shows encouraging qualitative agreement between the two. Copyright © 2015 Elsevier Ltd. All rights reserved.
Modelling and simulating a crisis management system: an organisational perspective
NASA Astrophysics Data System (ADS)
Chaawa, Mohamed; Thabet, Inès; Hanachi, Chihab; Ben Said, Lamjed
2017-04-01
Crises are complex situations due to the dynamism of the environment, its unpredictability and the complexity of the interactions among several different and autonomous involved organisations. In such a context, establishing an organisational view as well as structuring organisations' communications and their functioning is a crucial requirement. In this article, we propose a multi-agent organisational model (OM) to abstract, simulate and analyse a crisis management system (CMS). The objective is to evaluate the CMS from an organisational view, to assess its strength as well as its weakness and to provide deciders with some recommendations for a more flexible and reactive CMS. The proposed OM is illustrated through a real case study: a snowstorm in a Tunisian region. More precisely, we made the following contribution: firstly, we provide an environmental model that identifies the concepts involved in the crisis. Then, we define a role model that copes with the involved actors. In addition, we specify the organisational structure and the interaction model that rule communications and structure actors' functioning. Those models, built following the GAIA methodology, abstract the CMS from an organisational perspective. Finally, we implemented a customisable multi-agent simulator based on the Janus platform to analyse, through several performed simulations, the organisational model.
Diamond-like nanoparticles influence on flavonoids transport: molecular modelling
NASA Astrophysics Data System (ADS)
Plastun, Inna L.; Agandeeva, Ksenia E.; Bokarev, Andrey N.; Zenkin, Nikita S.
2017-03-01
Intermolecular interaction of diamond-like nanoparticles and flavonoids is investigated by numerical simulation. Using molecular modelling by the density functional theory method, we analyze hydrogen bonds formation and their influence on IR - spectra and structure of molecular complex which is formed due to interaction between flavonoids and nanodiamonds surrounded with carboxylic groups. Enriched adamantane (1,3,5,7 - adamantanetetracarboxylic acid) is used as an example of diamond-like nanoparticles. Intermolecular forces and structure of hydrogen bonds are investigated. IR - spectra and structure parameters of quercetin - adamantanetetracarboxylic acid molecular complex are obtained by numerical simulation using the Gaussian software complex. Received data coincide well with experimental results. Intermolecular interactions and hydrogen bonding structure in the obtained molecular complex are examined. Possibilities of flavonoids interaction with DNA at the molecular level are also considered.
Quality assurance paradigms for artificial intelligence in modelling and simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Oren, T.I.
1987-04-01
New classes of quality assurance concepts and techniques are required for the advanced knowledge-processing paradigms (such as artificial intelligence, expert systems, or knowledge-based systems) and the complex problems that only simulative systems can cope with. A systematization of quality assurance problems as well as examples are given to traditional and cognizant quality assurance techniques in traditional and cognizant modelling and simulation.
Hezaveh, Samira; Zeng, An-Ping; Jandt, Uwe
2016-05-19
Targeted manipulation and exploitation of beneficial properties of multienzyme complexes, especially for the design of novel and efficiently structured enzymatic reaction cascades, require a solid model understanding of mechanistic principles governing the structure and functionality of the complexes. This type of system-level and quantitative knowledge has been very scarce thus far. We utilize the human pyruvate dehydrogenase complex (hPDC) as a versatile template to conduct corresponding studies. Here we present new homology models of the core subunits of the hPDC, namely E2 and E3BP, as the first time effort to elucidate the assembly of hPDC core based on molecular dynamic simulation. New models of E2 and E3BP were generated and validated at atomistic level for different properties of the proteins. The results of the wild type dimer simulations showed a strong hydrophobic interaction between the C-terminal and the hydrophobic pocket which is the main driving force in the intertrimer binding and the core self-assembly. On the contrary, the C-terminal truncated versions exhibited a drastic loss of hydrophobic interaction leading to a dimeric separation. This study represents a significant step toward a model-based understanding of structure and function of large multienzyme systems like PDC for developing highly efficient biocatalyst or bioreaction cascades.
Use of Mechanistic Models to?Improve Understanding: Differential, mass balance, process-based Spatial and temporal resolution Necessary simplifications of system complexity Combing field monitoring and modeling efforts Balance between capturing complexity and maintaining...
Virtual reality simulator: demonstrated use in neurosurgical oncology.
Clarke, David B; D'Arcy, Ryan C N; Delorme, Sebastien; Laroche, Denis; Godin, Guy; Hajra, Sujoy Ghosh; Brooks, Rupert; DiRaddo, Robert
2013-04-01
The overriding importance of patient safety, the complexity of surgical techniques, and the challenges associated with teaching surgical trainees in the operating room are all factors driving the need for innovative surgical simulation technologies. Despite these issues, widespread use of virtual reality simulation technology in surgery has not been fully implemented, largely because of the technical complexities in developing clinically relevant and useful models. This article describes the successful use of the NeuroTouch neurosurgical simulator in the resection of a left frontal meningioma. The widespread application of surgical simulation technology has the potential to decrease surgical risk, improve operating room efficiency, and fundamentally change surgical training.
Jasper, Micah N; Martin, Sheppard A; Oshiro, Wendy M; Ford, Jermaine; Bushnell, Philip J; El-Masri, Hisham
2016-03-15
People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.
Erin L. Landguth,; Muhlfeld, Clint C.; Luikart, Gordon
2012-01-01
We introduce Cost Distance FISHeries (CDFISH), a simulator of population genetics and connectivity in complex riverscapes for a wide range of environmental scenarios of aquatic organisms. The spatially-explicit program implements individual-based genetic modeling with Mendelian inheritance and k-allele mutation on a riverscape with resistance to movement. The program simulates individuals in subpopulations through time employing user-defined functions of individual migration, reproduction, mortality, and dispersal through straying on a continuous resistance surface.
Road simulation for four-wheel vehicle whole input power spectral density
NASA Astrophysics Data System (ADS)
Wang, Jiangbo; Qiang, Baomin
2017-05-01
As the vibration of running vehicle mainly comes from road and influence vehicle ride performance. So the road roughness power spectral density simulation has great significance to analyze automobile suspension vibration system parameters and evaluate ride comfort. Firstly, this paper based on the mathematical model of road roughness power spectral density, established the integral white noise road random method. Then in the MATLAB/Simulink environment, according to the research method of automobile suspension frame from simple two degree of freedom single-wheel vehicle model to complex multiple degrees of freedom vehicle model, this paper built the simple single incentive input simulation model. Finally the spectrum matrix was used to build whole vehicle incentive input simulation model. This simulation method based on reliable and accurate mathematical theory and can be applied to the random road simulation of any specified spectral which provides pavement incentive model and foundation to vehicle ride performance research and vibration simulation.
Visual Complexity in Orthographic Learning: Modeling Learning across Writing System Variations
ERIC Educational Resources Information Center
Chang, Li-Yun; Plaut, David C.; Perfetti, Charles A.
2016-01-01
The visual complexity of orthographies varies across writing systems. Prior research has shown that complexity strongly influences the initial stage of reading development: the perceptual learning of grapheme forms. This study presents a computational simulation that examines the degree to which visual complexity leads to grapheme learning…
NASA Astrophysics Data System (ADS)
Ren, Lei; Zhang, Lin; Tao, Fei; (Luke) Zhang, Xiaolong; Luo, Yongliang; Zhang, Yabin
2012-08-01
Multidisciplinary design of complex products leads to an increasing demand for high performance simulation (HPS) platforms. One great challenge is how to achieve high efficient utilisation of large-scale simulation resources in distributed and heterogeneous environments. This article reports a virtualisation-based methodology to realise a HPS platform. This research is driven by the issues concerning large-scale simulation resources deployment and complex simulation environment construction, efficient and transparent utilisation of fine-grained simulation resources and high reliable simulation with fault tolerance. A framework of virtualisation-based simulation platform (VSIM) is first proposed. Then the article investigates and discusses key approaches in VSIM, including simulation resources modelling, a method to automatically deploying simulation resources for dynamic construction of system environment, and a live migration mechanism in case of faults in run-time simulation. Furthermore, the proposed methodology is applied to a multidisciplinary design system for aircraft virtual prototyping and some experiments are conducted. The experimental results show that the proposed methodology can (1) significantly improve the utilisation of fine-grained simulation resources, (2) result in a great reduction in deployment time and an increased flexibility for simulation environment construction and (3)achieve fault tolerant simulation.
NASA Astrophysics Data System (ADS)
Hill, James C.; Liu, Zhenping; Fox, Rodney O.; Passalacqua, Alberto; Olsen, Michael G.
2015-11-01
The multi-inlet vortex reactor (MIVR) has been developed to provide a platform for rapid mixing in the application of flash nanoprecipitation (FNP) for manufacturing functional nanoparticles. Unfortunately, commonly used RANS methods are unable to accurately model this complex swirling flow. Large eddy simulations have also been problematic, as expensive fine grids to accurately model the flow are required. These dilemmas led to the strategy of applying a Delayed Detached Eddy Simulation (DDES) method to the vortex reactor. In the current work, the turbulent swirling flow inside a scaled-up MIVR has been investigated by using a dynamic DDES model. In the DDES model, the eddy viscosity has a form similar to the Smagorinsky sub-grid viscosity in LES and allows the implementation of a dynamic procedure to determine its coefficient. The complex recirculating back flow near the reactor center has been successfully captured by using this dynamic DDES model. Moreover, the simulation results are found to agree with experimental data for mean velocity and Reynolds stresses.
Information driving force and its application in agent-based modeling
NASA Astrophysics Data System (ADS)
Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei
2018-04-01
Exploring the scientific impact of online big-data has attracted much attention of researchers from different fields in recent years. Complex financial systems are typical open systems profoundly influenced by the external information. Based on the large-scale data in the public media and stock markets, we first define an information driving force, and analyze how it affects the complex financial system. The information driving force is observed to be asymmetric in the bull and bear market states. As an application, we then propose an agent-based model driven by the information driving force. Especially, all the key parameters are determined from the empirical analysis rather than from statistical fitting of the simulation results. With our model, both the stationary properties and non-stationary dynamic behaviors are simulated. Considering the mean-field effect of the external information, we also propose a few-body model to simulate the financial market in the laboratory.
Computer modeling and simulation in inertial confinement fusion
DOE Office of Scientific and Technical Information (OSTI.GOV)
McCrory, R.L.; Verdon, C.P.
1989-03-01
The complex hydrodynamic and transport processes associated with the implosion of an inertial confinement fusion (ICF) pellet place considerable demands on numerical simulation programs. Processes associated with implosion can usually be described using relatively simple models, but their complex interplay requires that programs model most of the relevant physical phenomena accurately. Most hydrodynamic codes used in ICF incorporate a one-fluid, two-temperature model. Electrons and ions are assumed to flow as one fluid (no charge separation). Due to the relatively weak coupling between the ions and electrons, each species is treated separately in terms of its temperature. In this paper wemore » describe some of the major components associated with an ICF hydrodynamics simulation code. To serve as an example we draw heavily on a two-dimensional Lagrangian hydrodynamic code (ORCHID) written at the University of Rochester's Laboratory for Laser Energetics. 46 refs., 19 figs., 1 tab.« less
Mathematical model of organic substrate degradation in solid waste windrow composting.
Seng, Bunrith; Kristanti, Risky Ayu; Hadibarata, Tony; Hirayama, Kimiaki; Katayama-Hirayama, Keiko; Kaneko, Hidehiro
2016-01-01
Organic solid waste composting is a complex process that involves many coupled physical, chemical and biological mechanisms. To understand this complexity and to ease in planning, design and management of the composting plant, mathematical model for simulation is usually applied. The aim of this paper is to develop a mathematical model of organic substrate degradation and its performance evaluation in solid waste windrow composting system. The present model is a biomass-dependent model, considering biological growth processes under the limitation of moisture, oxygen and substrate contents, and temperature. The main output of this model is substrate content which was divided into two categories: slowly and rapidly degradable substrates. To validate the model, it was applied to a laboratory scale windrow composting of a mixture of wood chips and dog food. The wastes were filled into a cylindrical reactor of 6 cm diameter and 1 m height. The simulation program was run for 3 weeks with 1 s stepwise. The simulated results were in reasonably good agreement with the experimental results. The MC and temperature of model simulation were found to be matched with those of experiment, but limited for rapidly degradable substrates. Under anaerobic zone, the degradation of rapidly degradable substrate needs to be incorporated into the model to achieve full simulation of a long period static pile composting. This model is a useful tool to estimate the changes of substrate content during composting period, and acts as a basic model for further development of a sophisticated model.
A systems-based approach for integrated design of materials, products and design process chains
NASA Astrophysics Data System (ADS)
Panchal, Jitesh H.; Choi, Hae-Jin; Allen, Janet K.; McDowell, David L.; Mistree, Farrokh
2007-12-01
The concurrent design of materials and products provides designers with flexibility to achieve design objectives that were not previously accessible. However, the improved flexibility comes at a cost of increased complexity of the design process chains and the materials simulation models used for executing the design chains. Efforts to reduce the complexity generally result in increased uncertainty. We contend that a systems based approach is essential for managing both the complexity and the uncertainty in design process chains and simulation models in concurrent material and product design. Our approach is based on simplifying the design process chains systematically such that the resulting uncertainty does not significantly affect the overall system performance. Similarly, instead of striving for accurate models for multiscale systems (that are inherently complex), we rely on making design decisions that are robust to uncertainties in the models. Accordingly, we pursue hierarchical modeling in the context of design of multiscale systems. In this paper our focus is on design process chains. We present a systems based approach, premised on the assumption that complex systems can be designed efficiently by managing the complexity of design process chains. The approach relies on (a) the use of reusable interaction patterns to model design process chains, and (b) consideration of design process decisions using value-of-information based metrics. The approach is illustrated using a Multifunctional Energetic Structural Material (MESM) design example. Energetic materials store considerable energy which can be released through shock-induced detonation; conventionally, they are not engineered for strength properties. The design objectives for the MESM in this paper include both sufficient strength and energy release characteristics. The design is carried out by using models at different length and time scales that simulate different aspects of the system. Finally, by applying the method to the MESM design problem, we show that the integrated design of materials and products can be carried out more efficiently by explicitly accounting for design process decisions with the hierarchy of models.
The Use of Computer Simulation Techniques in Educational Planning.
ERIC Educational Resources Information Center
Wilson, Charles Z.
Computer simulations provide powerful models for establishing goals, guidelines, and constraints in educational planning. They are dynamic models that allow planners to examine logical descriptions of organizational behavior over time as well as permitting consideration of the large and complex systems required to provide realistic descriptions of…
NASA Technical Reports Server (NTRS)
Seltzer, S. M.; Patel, J. S.; Justice, D. W.; Schweitzer, G. E.
1972-01-01
The results are presented of a study of the dynamics of a spinning Skylab space station. The stability of motion of several simplified models with flexible appendages was investigated. A digital simulation model that more accurately portrays the complex Skylab vehicle is described, and simulation results are compared with analytically derived results.
NASA Astrophysics Data System (ADS)
Nakagawa, Satoshi; Kurniawan, Isman; Kodama, Koichi; Arwansyah, Muhammad Saleh; Kawaguchi, Kazutomo; Nagao, Hidemi
2018-03-01
We present a simple coarse-grained model with the molecular crowding effect in solvent to investigate the structure and dynamics of protein complexes including association and/or dissociation processes and investigate some physical properties such as the structure and the reaction rate from the viewpoint of the hydrophobic intermolecular interactions of protein complex. In the present coarse-grained model, a function depending upon the density of hydrophobic amino acid residues in a binding area of the complex is introduced, and the function involves the molecular crowding effect for the intermolecular interactions of hydrophobic amino acid residues between proteins. We propose a hydrophobic intermolecular potential energy between proteins by using the density-dependent function. The present coarse-grained model is applied to the complex of cytochrome f and plastocyanin by using the Langevin dynamics simulation to investigate some physical properties such as the complex structure, the electron transfer reaction rate constant from plastocyanin to cytochrome f and so on. We find that for proceeding the electron transfer reaction, the distance between metals in their active sites is necessary within about 18 Å. We discuss some typical complex structures formed in the present simulation in relation to the molecular crowding effect on hydrophobic interactions.
Simulation and analysis of a model dinoflagellate predator-prey system
NASA Astrophysics Data System (ADS)
Mazzoleni, M. J.; Antonelli, T.; Coyne, K. J.; Rossi, L. F.
2015-12-01
This paper analyzes the dynamics of a model dinoflagellate predator-prey system and uses simulations to validate theoretical and experimental studies. A simple model for predator-prey interactions is derived by drawing upon analogies from chemical kinetics. This model is then modified to account for inefficiencies in predation. Simulation results are shown to closely match the model predictions. Additional simulations are then run which are based on experimental observations of predatory dinoflagellate behavior, and this study specifically investigates how the predatory dinoflagellate Karlodinium veneficum uses toxins to immobilize its prey and increase its feeding rate. These simulations account for complex dynamics that were not included in the basic models, and the results from these computational simulations closely match the experimentally observed predatory behavior of K. veneficum and reinforce the notion that predatory dinoflagellates utilize toxins to increase their feeding rate.
A.J. Tepley; E.A. Thomann
2012-01-01
Recent increases in computation power have prompted enormous growth in the use of simulation models in ecological research. These models are valued for their ability to account for much of the ecological complexity found in field studies, but this ability usually comes at the cost of losing transparency into how the models work. In order to foster greater understanding...
Computational modeling of carbohydrate recognition in protein complex
NASA Astrophysics Data System (ADS)
Ishida, Toyokazu
2017-11-01
To understand the mechanistic principle of carbohydrate recognition in proteins, we propose a systematic computational modeling strategy to identify complex carbohydrate chain onto the reduced 2D free energy surface (2D-FES), determined by MD sampling combined with QM/MM energy corrections. In this article, we first report a detailed atomistic simulation study of the norovirus capsid proteins with carbohydrate antigens based on ab initio QM/MM combined with MD-FEP simulations. The present result clearly shows that the binding geometries of complex carbohydrate antigen are determined not by one single, rigid carbohydrate structure, but rather by the sum of averaged conformations mapped onto the minimum free energy region of QM/MM 2D-FES.
Greiner, Maximilian; Sonnleitner, Bettina; Mailänder, Markus; Briesen, Heiko
2014-02-01
Additional benefits of foods are an increasing factor in the consumer's purchase. To produce foods with the properties the consumer demands, understanding the micro- and nanostructure is becoming more important in food research today. We present molecular dynamics (MD) simulations as a tool to study complex and multi-component food systems on the example of chocolate conching. The process of conching is chosen because of the interesting challenges it provides: the components (fats, emulsifiers and carbohydrates) contain diverse functional groups, are naturally fluctuating in their chemical composition, and have a high number of internal degrees of freedom. Further, slow diffusion in the non-aqueous medium is expected. All of these challenges are typical to food systems in general. Simulation results show the suitability of present force fields to correctly model the liquid and crystal density of cocoa butter and sucrose, respectively. Amphiphilic properties of emulsifiers are observed by micelle formation in water. For non-aqueous media, pulling simulations reveal high energy barriers for motion in the viscous cocoa butter. The work for detachment of an emulsifier from the sucrose crystal is calculated and matched with detachment of the head and tail groups separately. Hydrogen bonding is shown to be the dominant interaction between the emulsifier and the crystal surface. Thus, MD simulations are suited to model the interaction between the emulsifier and sugar crystal interface in non-aqueous media, revealing detailed information about the structuring and interactions on a molecular level. With interaction parameters being available for a wide variety of chemical groups, MD simulations are a valuable tool to understand complex and multi-component food systems in general. MD simulations provide a substantial benefit to researchers to verify their hypothesis in dynamic simulations with an atomistic resolution. Rapid rise of computational resources successively increases the complexity and the size of the systems that can be studied.
Model Checking Satellite Operational Procedures
NASA Astrophysics Data System (ADS)
Cavaliere, Federico; Mari, Federico; Melatti, Igor; Minei, Giovanni; Salvo, Ivano; Tronci, Enrico; Verzino, Giovanni; Yushtein, Yuri
2011-08-01
We present a model checking approach for the automatic verification of satellite operational procedures (OPs). Building a model for a complex system as a satellite is a hard task. We overcome this obstruction by using a suitable simulator (SIMSAT) for the satellite. Our approach aims at improving OP quality assurance by automatic exhaustive exploration of all possible simulation scenarios. Moreover, our solution decreases OP verification costs by using a model checker (CMurphi) to automatically drive the simulator. We model OPs as user-executed programs observing the simulator telemetries and sending telecommands to the simulator. In order to assess feasibility of our approach we present experimental results on a simple meaningful scenario. Our results show that we can save up to 90% of verification time.
NASA Astrophysics Data System (ADS)
Kraus, E. I.; Shabalin, I. I.; Shabalin, T. I.
2018-04-01
The main points of development of numerical tools for simulation of deformation and failure of complex technical objects under nonstationary conditions of extreme loading are presented. The possibility of extending the dynamic method for construction of difference grids to the 3D case is shown. A 3D realization of discrete-continuum approach to the deformation and failure of complex technical objects is carried out. The efficiency of the existing software package for 3D modelling is shown.
NASA Astrophysics Data System (ADS)
Paiewonsky, Pablo; Elison Timm, Oliver
2018-03-01
In this paper, we present a simple dynamic global vegetation model whose primary intended use is auxiliary to the land-atmosphere coupling scheme of a climate model, particularly one of intermediate complexity. The model simulates and provides important ecological-only variables but also some hydrological and surface energy variables that are typically either simulated by land surface schemes or else used as boundary data input for these schemes. The model formulations and their derivations are presented here, in detail. The model includes some realistic and useful features for its level of complexity, including a photosynthetic dependency on light, full coupling of photosynthesis and transpiration through an interactive canopy resistance, and a soil organic carbon dependence for bare-soil albedo. We evaluate the model's performance by running it as part of a simple land surface scheme that is driven by reanalysis data. The evaluation against observational data includes net primary productivity, leaf area index, surface albedo, and diagnosed variables relevant for the closure of the hydrological cycle. In this setup, we find that the model gives an adequate to good simulation of basic large-scale ecological and hydrological variables. Of the variables analyzed in this paper, gross primary productivity is particularly well simulated. The results also reveal the current limitations of the model. The most significant deficiency is the excessive simulation of evapotranspiration in mid- to high northern latitudes during their winter to spring transition. The model has a relative advantage in situations that require some combination of computational efficiency, model transparency and tractability, and the simulation of the large-scale vegetation and land surface characteristics under non-present-day conditions.
Route complexity and simulated physical ageing negatively influence wayfinding.
Zijlstra, Emma; Hagedoorn, Mariët; Krijnen, Wim P; van der Schans, Cees P; Mobach, Mark P
2016-09-01
The aim of this age-simulation field experiment was to assess the influence of route complexity and physical ageing on wayfinding. Seventy-five people (aged 18-28) performed a total of 108 wayfinding tasks (i.e., 42 participants performed two wayfinding tasks and 33 performed one wayfinding task), of which 59 tasks were performed wearing gerontologic ageing suits. Outcome variables were wayfinding performance (i.e., efficiency and walking speed) and physiological outcomes (i.e., heart and respiratory rates). Analysis of covariance showed that persons on more complex routes (i.e., more floor and building changes) walked less efficiently than persons on less complex routes. In addition, simulated elderly participants perform worse in wayfinding than young participants in terms of speed (p < 0.001). Moreover, a linear mixed model showed that simulated elderly persons had higher heart rates and respiratory rates compared to young people during a wayfinding task, suggesting that simulated elderly consumed more energy during this task. Copyright © 2016 Elsevier Ltd. All rights reserved.
Predictive Validation of an Influenza Spread Model
Hyder, Ayaz; Buckeridge, David L.; Leung, Brian
2013-01-01
Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive ability. PMID:23755236
Townsend, Molly T; Sarigul-Klijn, Nesrin
2016-01-01
Simplified material models are commonly used in computational simulation of biological soft tissue as an approximation of the complicated material response and to minimize computational resources. However, the simulation of complex loadings, such as long-duration tissue swelling, necessitates complex models that are not easy to formulate. This paper strives to offer the updated Lagrangian formulation comprehensive procedure of various non-linear material models for the application of finite element analysis of biological soft tissues including a definition of the Cauchy stress and the spatial tangential stiffness. The relationships between water content, osmotic pressure, ionic concentration and the pore pressure stress of the tissue are discussed with the merits of these models and their applications.
Activity Diagrams for DEVS Models: A Case Study Modeling Health Care Behavior
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ozmen, Ozgur; Nutaro, James J
Discrete Event Systems Specification (DEVS) is a widely used formalism for modeling and simulation of discrete and continuous systems. While DEVS provides a sound mathematical representation of discrete systems, its practical use can suffer when models become complex. Five main functions, which construct the core of atomic modules in DEVS, can realize the behaviors that modelers want to represent. The integration of these functions is handled by the simulation routine, however modelers can implement each function in various ways. Therefore, there is a need for graphical representations of complex models to simplify their implementation and facilitate their reproduction. In thismore » work, we illustrate the use of activity diagrams for this purpose in the context of a health care behavior model, which is developed with an agent-based modeling paradigm.« less
Simplified contaminant source depletion models as analogs of multiphase simulators
NASA Astrophysics Data System (ADS)
Basu, Nandita B.; Fure, Adrian D.; Jawitz, James W.
2008-04-01
Four simplified dense non-aqueous phase liquid (DNAPL) source depletion models recently introduced in the literature are evaluated for the prediction of long-term effects of source depletion under natural gradient flow. These models are simple in form (a power function equation is an example) but are shown here to serve as mathematical analogs to complex multiphase flow and transport simulators. The spill and subsequent dissolution of DNAPLs was simulated in domains having different hydrologic characteristics (variance of the log conductivity field = 0.2, 1 and 3) using the multiphase flow and transport simulator UTCHEM. The dissolution profiles were fitted using four analytical models: the equilibrium streamtube model (ESM), the advection dispersion model (ADM), the power law model (PLM) and the Damkohler number model (DaM). All four models, though very different in their conceptualization, include two basic parameters that describe the mean DNAPL mass and the joint variability in the velocity and DNAPL distributions. The variability parameter was observed to be strongly correlated with the variance of the log conductivity field in the ESM and ADM but weakly correlated in the PLM and DaM. The DaM also includes a third parameter that describes the effect of rate-limited dissolution, but here this parameter was held constant as the numerical simulations were found to be insensitive to local-scale mass transfer. All four models were able to emulate the characteristics of the dissolution profiles generated from the complex numerical simulator, but the one-parameter PLM fits were the poorest, especially for the low heterogeneity case.
Simplified contaminant source depletion models as analogs of multiphase simulators.
Basu, Nandita B; Fure, Adrian D; Jawitz, James W
2008-04-28
Four simplified dense non-aqueous phase liquid (DNAPL) source depletion models recently introduced in the literature are evaluated for the prediction of long-term effects of source depletion under natural gradient flow. These models are simple in form (a power function equation is an example) but are shown here to serve as mathematical analogs to complex multiphase flow and transport simulators. The spill and subsequent dissolution of DNAPLs was simulated in domains having different hydrologic characteristics (variance of the log conductivity field=0.2, 1 and 3) using the multiphase flow and transport simulator UTCHEM. The dissolution profiles were fitted using four analytical models: the equilibrium streamtube model (ESM), the advection dispersion model (ADM), the power law model (PLM) and the Damkohler number model (DaM). All four models, though very different in their conceptualization, include two basic parameters that describe the mean DNAPL mass and the joint variability in the velocity and DNAPL distributions. The variability parameter was observed to be strongly correlated with the variance of the log conductivity field in the ESM and ADM but weakly correlated in the PLM and DaM. The DaM also includes a third parameter that describes the effect of rate-limited dissolution, but here this parameter was held constant as the numerical simulations were found to be insensitive to local-scale mass transfer. All four models were able to emulate the characteristics of the dissolution profiles generated from the complex numerical simulator, but the one-parameter PLM fits were the poorest, especially for the low heterogeneity case.
Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics
NASA Astrophysics Data System (ADS)
Chen, Yu-Zhong; Lai, Ying-Cheng
2018-03-01
Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.
Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics.
Chen, Yu-Zhong; Lai, Ying-Cheng
2018-03-01
Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.
Efficient evaluation of wireless real-time control networks.
Horvath, Peter; Yampolskiy, Mark; Koutsoukos, Xenofon
2015-02-11
In this paper, we present a system simulation framework for the design and performance evaluation of complex wireless cyber-physical systems. We describe the simulator architecture and the specific developments that are required to simulate cyber-physical systems relying on multi-channel, multihop mesh networks. We introduce realistic and efficient physical layer models and a system simulation methodology, which provides statistically significant performance evaluation results with low computational complexity. The capabilities of the proposed framework are illustrated in the example of WirelessHART, a centralized, real-time, multi-hop mesh network designed for industrial control and monitor applications.
Advanced laser modeling with BLAZE multiphysics
NASA Astrophysics Data System (ADS)
Palla, Andrew D.; Carroll, David L.; Gray, Michael I.; Suzuki, Lui
2017-01-01
The BLAZE Multiphysics™ software simulation suite was specifically developed to model highly complex multiphysical systems in a computationally efficient and highly scalable manner. These capabilities are of particular use when applied to the complexities associated with high energy laser systems that combine subsonic/transonic/supersonic fluid dynamics, chemically reacting flows, laser electronics, heat transfer, optical physics, and in some cases plasma discharges. In this paper we present detailed cw and pulsed gas laser calculations using the BLAZE model with comparisons to data. Simulations of DPAL, XPAL, ElectricOIL (EOIL), and the optically pumped rare gas laser were found to be in good agreement with experimental data.
Towards Automatic Processing of Virtual City Models for Simulations
NASA Astrophysics Data System (ADS)
Piepereit, R.; Schilling, A.; Alam, N.; Wewetzer, M.; Pries, M.; Coors, V.
2016-10-01
Especially in the field of numerical simulations, such as flow and acoustic simulations, the interest in using virtual 3D models to optimize urban systems is increasing. The few instances in which simulations were already carried out in practice have been associated with an extremely high manual and therefore uneconomical effort for the processing of models. Using different ways of capturing models in Geographic Information System (GIS) and Computer Aided Engineering (CAE), increases the already very high complexity of the processing. To obtain virtual 3D models suitable for simulation, we developed a tool for automatic processing with the goal to establish ties between the world of GIS and CAE. In this paper we introduce a way to use Coons surfaces for the automatic processing of building models in LoD2, and investigate ways to simplify LoD3 models in order to reduce unnecessary information for a numerical simulation.
Tutoring and Multi-Agent Systems: Modeling from Experiences
ERIC Educational Resources Information Center
Bennane, Abdellah
2010-01-01
Tutoring systems become complex and are offering varieties of pedagogical software as course modules, exercises, simulators, systems online or offline, for single user or multi-user. This complexity motivates new forms and approaches to the design and the modelling. Studies and research in this field introduce emergent concepts that allow the…
Investigating Complexity Using Excel and Visual Basic.
ERIC Educational Resources Information Center
Zetie, K. P.
2001-01-01
Shows how some of the simple ideas in complexity can be investigated using a spreadsheet and a macro written in Visual Basic. Shows how the sandpile model of Bak, Chao, and Wiesenfeld can be simulated and animated. The model produces results that cannot easily be predicted from its properties. (Author/MM)
NASA Astrophysics Data System (ADS)
Wray, Timothy J.
Computational fluid dynamics (CFD) is routinely used in performance prediction and design of aircraft, turbomachinery, automobiles, and in many other industrial applications. Despite its wide range of use, deficiencies in its prediction accuracy still exist. One critical weakness is the accurate simulation of complex turbulent flows using the Reynolds-Averaged Navier-Stokes equations in conjunction with a turbulence model. The goal of this research has been to develop an eddy viscosity type turbulence model to increase the accuracy of flow simulations for mildly separated flows, flows with rotation and curvature effects, and flows with surface roughness. It is accomplished by developing a new zonal one-equation turbulence model which relies heavily on the flow physics; it is now known in the literature as the Wray-Agarwal one-equation turbulence model. The effectiveness of the new model is demonstrated by comparing its results with those obtained by the industry standard one-equation Spalart-Allmaras model and two-equation Shear-Stress-Transport k - o model and experimental data. Results for subsonic, transonic, and supersonic flows in and about complex geometries are presented. It is demonstrated that the Wray-Agarwal model can provide the industry and CFD researchers an accurate, efficient, and reliable turbulence model for the computation of a large class of complex turbulent flows.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Düchs, Dominik; Delaney, Kris T., E-mail: kdelaney@mrl.ucsb.edu; Fredrickson, Glenn H., E-mail: ghf@mrl.ucsb.edu
Field-theoretic models have been used extensively to study the phase behavior of inhomogeneous polymer melts and solutions, both in self-consistent mean-field calculations and in numerical simulations of the full theory capturing composition fluctuations. The models commonly used can be grouped into two categories, namely, species models and exchange models. Species models involve integrations of functionals that explicitly depend on fields originating both from species density operators and their conjugate chemical potential fields. In contrast, exchange models retain only linear combinations of the chemical potential fields. In the two-component case, development of exchange models has been instrumental in enabling stable complexmore » Langevin (CL) simulations of the full complex-valued theory. No comparable stable CL approach has yet been established for field theories of the species type. Here, we introduce an extension of the exchange model to an arbitrary number of components, namely, the multi-species exchange (MSE) model, which greatly expands the classes of soft material systems that can be accessed by the complex Langevin simulation technique. We demonstrate the stability and accuracy of the MSE-CL sampling approach using numerical simulations of triblock and tetrablock terpolymer melts, and tetrablock quaterpolymer melts. This method should enable studies of a wide range of fluctuation phenomena in multiblock/multi-species polymer blends and composites.« less
Exact simulation of max-stable processes.
Dombry, Clément; Engelke, Sebastian; Oesting, Marco
2016-06-01
Max-stable processes play an important role as models for spatial extreme events. Their complex structure as the pointwise maximum over an infinite number of random functions makes their simulation difficult. Algorithms based on finite approximations are often inexact and computationally inefficient. We present a new algorithm for exact simulation of a max-stable process at a finite number of locations. It relies on the idea of simulating only the extremal functions, that is, those functions in the construction of a max-stable process that effectively contribute to the pointwise maximum. We further generalize the algorithm by Dieker & Mikosch (2015) for Brown-Resnick processes and use it for exact simulation via the spectral measure. We study the complexity of both algorithms, prove that our new approach via extremal functions is always more efficient, and provide closed-form expressions for their implementation that cover most popular models for max-stable processes and multivariate extreme value distributions. For simulation on dense grids, an adaptive design of the extremal function algorithm is proposed.
An Object-Oriented Serial DSMC Simulation Package
NASA Astrophysics Data System (ADS)
Liu, Hongli; Cai, Chunpei
2011-05-01
A newly developed three-dimensional direct simulation Monte Carlo (DSMC) simulation package, named GRASP ("Generalized Rarefied gAs Simulation Package"), is reported in this paper. This package utilizes the concept of simulation engine, many C++ features and software design patterns. The package has an open architecture which can benefit further development and maintenance of the code. In order to reduce the engineering time for three-dimensional models, a hybrid grid scheme, combined with a flexible data structure compiled by C++ language, are implemented in this package. This scheme utilizes a local data structure based on the computational cell to achieve high performance on workstation processors. This data structure allows the DSMC algorithm to be very efficiently parallelized with domain decomposition and it provides much flexibility in terms of grid types. This package can utilize traditional structured, unstructured or hybrid grids within the framework of a single code to model arbitrarily complex geometries and to simulate rarefied gas flows. Benchmark test cases indicate that this package has satisfactory accuracy for complex rarefied gas flows.
Modeling and experimental characterization of electromigration in interconnect trees
NASA Astrophysics Data System (ADS)
Thompson, C. V.; Hau-Riege, S. P.; Andleigh, V. K.
1999-11-01
Most modeling and experimental characterization of interconnect reliability is focussed on simple straight lines terminating at pads or vias. However, laid-out integrated circuits often have interconnects with junctions and wide-to-narrow transitions. In carrying out circuit-level reliability assessments it is important to be able to assess the reliability of these more complex shapes, generally referred to as `trees.' An interconnect tree consists of continuously connected high-conductivity metal within one layer of metallization. Trees terminate at diffusion barriers at vias and contacts, and, in the general case, can have more than one terminating branch when they include junctions. We have extended the understanding of `immortality' demonstrated and analyzed for straight stud-to-stud lines, to trees of arbitrary complexity. This leads to a hierarchical approach for identifying immortal trees for specific circuit layouts and models for operation. To complete a circuit-level-reliability analysis, it is also necessary to estimate the lifetimes of the mortal trees. We have developed simulation tools that allow modeling of stress evolution and failure in arbitrarily complex trees. We are testing our models and simulations through comparisons with experiments on simple trees, such as lines broken into two segments with different currents in each segment. Models, simulations and early experimental results on the reliability of interconnect trees are shown to be consistent.
Rabattu, Pierre-Yves; Massé, Benoit; Ulliana, Federico; Rousset, Marie-Christine; Rohmer, Damien; Léon, Jean-Claude; Palombi, Olivier
2015-01-01
Embryology is a complex morphologic discipline involving a set of entangled mechanisms, sometime difficult to understand and to visualize. Recent computer based techniques ranging from geometrical to physically based modeling are used to assist the visualization and the simulation of virtual humans for numerous domains such as surgical simulation and learning. On the other side, the ontology-based approach applied to knowledge representation is more and more successfully adopted in the life-science domains to formalize biological entities and phenomena, thanks to a declarative approach for expressing and reasoning over symbolic information. 3D models and ontologies are two complementary ways to describe biological entities that remain largely separated. Indeed, while many ontologies providing a unified formalization of anatomy and embryology exist, they remain only descriptive and make the access to anatomical content of complex 3D embryology models and simulations difficult. In this work, we present a novel ontology describing the development of the human embryology deforming 3D models. Beyond describing how organs and structures are composed, our ontology integrates a procedural description of their 3D representations, temporal deformation and relations with respect to their developments. We also created inferences rules to express complex connections between entities. It results in a unified description of both the knowledge of the organs deformation and their 3D representations enabling to visualize dynamically the embryo deformation during the Carnegie stages. Through a simplified ontology, containing representative entities which are linked to spatial position and temporal process information, we illustrate the added-value of such a declarative approach for interactive simulation and visualization of 3D embryos. Combining ontologies and 3D models enables a declarative description of different embryological models that capture the complexity of human developmental anatomy. Visualizing embryos with 3D geometric models and their animated deformations perhaps paves the way towards some kind of hypothesis-driven application. These can also be used to assist the learning process of this complex knowledge. http://www.mycorporisfabrica.org/.
Compilation of Abstracts for SC12 Conference Proceedings
NASA Technical Reports Server (NTRS)
Morello, Gina Francine (Compiler)
2012-01-01
1 A Breakthrough in Rotorcraft Prediction Accuracy Using Detached Eddy Simulation; 2 Adjoint-Based Design for Complex Aerospace Configurations; 3 Simulating Hypersonic Turbulent Combustion for Future Aircraft; 4 From a Roar to a Whisper: Making Modern Aircraft Quieter; 5 Modeling of Extended Formation Flight on High-Performance Computers; 6 Supersonic Retropropulsion for Mars Entry; 7 Validating Water Spray Simulation Models for the SLS Launch Environment; 8 Simulating Moving Valves for Space Launch System Liquid Engines; 9 Innovative Simulations for Modeling the SLS Solid Rocket Booster Ignition; 10 Solid Rocket Booster Ignition Overpressure Simulations for the Space Launch System; 11 CFD Simulations to Support the Next Generation of Launch Pads; 12 Modeling and Simulation Support for NASA's Next-Generation Space Launch System; 13 Simulating Planetary Entry Environments for Space Exploration Vehicles; 14 NASA Center for Climate Simulation Highlights; 15 Ultrascale Climate Data Visualization and Analysis; 16 NASA Climate Simulations and Observations for the IPCC and Beyond; 17 Next-Generation Climate Data Services: MERRA Analytics; 18 Recent Advances in High-Resolution Global Atmospheric Modeling; 19 Causes and Consequences of Turbulence in the Earths Protective Shield; 20 NASA Earth Exchange (NEX): A Collaborative Supercomputing Platform; 21 Powering Deep Space Missions: Thermoelectric Properties of Complex Materials; 22 Meeting NASA's High-End Computing Goals Through Innovation; 23 Continuous Enhancements to the Pleiades Supercomputer for Maximum Uptime; 24 Live Demonstrations of 100-Gbps File Transfers Across LANs and WANs; 25 Untangling the Computing Landscape for Climate Simulations; 26 Simulating Galaxies and the Universe; 27 The Mysterious Origin of Stellar Masses; 28 Hot-Plasma Geysers on the Sun; 29 Turbulent Life of Kepler Stars; 30 Modeling Weather on the Sun; 31 Weather on Mars: The Meteorology of Gale Crater; 32 Enhancing Performance of NASAs High-End Computing Applications; 33 Designing Curiosity's Perfect Landing on Mars; 34 The Search Continues: Kepler's Quest for Habitable Earth-Sized Planets.
Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks
Walpole, J.; Chappell, J.C.; Cluceru, J.G.; Mac Gabhann, F.; Bautch, V.L.; Peirce, S. M.
2015-01-01
Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods. PMID:26158406
Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.
Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M
2015-09-01
Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.
Application of the GERTS II simulator in the industrial environment.
NASA Technical Reports Server (NTRS)
Whitehouse, G. E.; Klein, K. I.
1971-01-01
GERT was originally developed to aid in the analysis of stochastic networks. GERT can be used to graphically model and analyze complex systems. Recently a simulator model, GERTS II, has been developed to solve GERT Networks. The simulator language used in the development of this model was GASP II A. This paper discusses the possible application of GERTS II to model and analyze (1) assembly line operations, (2) project management networks, (3) conveyor systems and (4) inventory systems. Finally, an actual application dealing with a job shop loading problem is presented.
Lázár, Attila N; Clarke, Derek; Adams, Helen; Akanda, Abdur Razzaque; Szabo, Sylvia; Nicholls, Robert J; Matthews, Zoe; Begum, Dilruba; Saleh, Abul Fazal M; Abedin, Md Anwarul; Payo, Andres; Streatfield, Peter Kim; Hutton, Craig; Mondal, M Shahjahan; Moslehuddin, Abu Zofar Md
2015-06-01
Coastal Bangladesh experiences significant poverty and hazards today and is highly vulnerable to climate and environmental change over the coming decades. Coastal stakeholders are demanding information to assist in the decision making processes, including simulation models to explore how different interventions, under different plausible future socio-economic and environmental scenarios, could alleviate environmental risks and promote development. Many existing simulation models neglect the complex interdependencies between the socio-economic and environmental system of coastal Bangladesh. Here an integrated approach has been proposed to develop a simulation model to support agriculture and poverty-based analysis and decision-making in coastal Bangladesh. In particular, we show how a simulation model of farmer's livelihoods at the household level can be achieved. An extended version of the FAO's CROPWAT agriculture model has been integrated with a downscaled regional demography model to simulate net agriculture profit. This is used together with a household income-expenses balance and a loans logical tree to simulate the evolution of food security indicators and poverty levels. Modelling identifies salinity and temperature stress as limiting factors to crop productivity and fertilisation due to atmospheric carbon dioxide concentrations as a reinforcing factor. The crop simulation results compare well with expected outcomes but also reveal some unexpected behaviours. For example, under current model assumptions, temperature is more important than salinity for crop production. The agriculture-based livelihood and poverty simulations highlight the critical significance of debt through informal and formal loans set at such levels as to persistently undermine the well-being of agriculture-dependent households. Simulations also indicate that progressive approaches to agriculture (i.e. diversification) might not provide the clear economic benefit from the perspective of pricing due to greater susceptibility to climate vagaries. The livelihood and poverty results highlight the importance of the holistic consideration of the human-nature system and the careful selection of poverty indicators. Although the simulation model at this stage contains the minimum elements required to simulate the complexity of farmer livelihood interactions in coastal Bangladesh, the crop and socio-economic findings compare well with expected behaviours. The presented integrated model is the first step to develop a holistic, transferable analytic method and tool for coastal Bangladesh.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Trent, D.S.; Eyler, L.L.
In this study several aspects of simulating hydrogen distribution in geometric configurations relevant to reactor containment structures were investigated using the TEMPEST computer code. Of particular interest was the performance of the TEMPEST turbulence model in a density-stratified environment. Computed results illustrated that the TEMPEST numerical procedures predicted the measured phenomena with good accuracy under a variety of conditions and that the turbulence model used is a viable approach in complex turbulent flow simulation.
A Formal Modelling Language Extending SysML for Simulation of Continuous and Discrete System
2012-11-01
UNCLASSIFIED DSTO-GD-0734 16. A Formal Modelling Language Extending SysML for Simulation of Continuous and Discrete System – Mark Hodson1 and...be conceptual at some level because a one to one mapping with the real system will never exist. SysML is an extension and modification of UML that...simulation, which can provide great insights into the behaviour of complex systems. Although UML and SysML primarily support conceptual modelling they
Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models
NASA Astrophysics Data System (ADS)
Pallant, Amy; Lee, Hee-Sun
2015-04-01
Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students ( N = 512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation tasks with three increasingly complex dynamic climate models. Each scientific argumentation task consisted of four parts: multiple-choice claim, openended explanation, five-point Likert scale uncertainty rating, and open-ended uncertainty rationale. We coded 1,294 scientific arguments in terms of a claim's consistency with current scientific consensus, whether explanations were model based or knowledge based and categorized the sources of uncertainty (personal vs. scientific). We used chi-square and ANOVA tests to identify significant patterns. Results indicate that (1) a majority of students incorporated models as evidence to support their claims, (2) most students used model output results shown on graphs to confirm their claim rather than to explain simulated molecular processes, (3) students' dependence on model results and their uncertainty rating diminished as the dynamic climate models became more and more complex, (4) some students' misconceptions interfered with observing and interpreting model results or simulated processes, and (5) students' uncertainty sources reflected more frequently on their assessment of personal knowledge or abilities related to the tasks than on their critical examination of scientific evidence resulting from models. These findings have implications for teaching and research related to the integration of scientific argumentation and modeling practices to address complex Earth systems.
An Open Simulation System Model for Scientific Applications
NASA Technical Reports Server (NTRS)
Williams, Anthony D.
1995-01-01
A model for a generic and open environment for running multi-code or multi-application simulations - called the open Simulation System Model (OSSM) - is proposed and defined. This model attempts to meet the requirements of complex systems like the Numerical Propulsion Simulator System (NPSS). OSSM places no restrictions on the types of applications that can be integrated at any state of its evolution. This includes applications of different disciplines, fidelities, etc. An implementation strategy is proposed that starts with a basic prototype, and evolves over time to accommodate an increasing number of applications. Potential (standard) software is also identified which may aid in the design and implementation of the system.
Real-time simulation of large-scale floods
NASA Astrophysics Data System (ADS)
Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.
2016-08-01
According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.
NASA Technical Reports Server (NTRS)
Taylor, B. K.; Casasent, D. P.
1989-01-01
The use of simplified error models to accurately simulate and evaluate the performance of an optical linear-algebra processor is described. The optical architecture used to perform banded matrix-vector products is reviewed, along with a linear dynamic finite-element case study. The laboratory hardware and ac-modulation technique used are presented. The individual processor error-source models and their simulator implementation are detailed. Several significant simplifications are introduced to ease the computational requirements and complexity of the simulations. The error models are verified with a laboratory implementation of the processor, and are used to evaluate its potential performance.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Christensen, J.B.; Christensen, T.H.
1999-11-01
Complexation of cadmium (Cd), nickel (Ni), and zinc (Zn) by dissolved organic carbon (DOC) in leachate-polluted groundwater was measured using a resin equilibrium method and an aquifer material sorption technique. The first method is commonly used in complexation studies, while the second method better represents aquifer conditions. The two approaches gave similar results. Metal-DOC complexation was measured over a range of DOC concentrations using the resin equilibrium method, and the results were compared to simulations made by two speciation models containing default databases on metal-DOC complexes (WHAM and MINTEQA2). The WHAM model gave reasonable estimates of Cd and Ni complexationmore » by DOC for both leachate-polluted groundwater samples. The estimated effect of complexation differed less than 50% from the experimental values corresponding to a deviation on the activity of the free metal ion of a factor of 2.5. The effect of DOC complexation for Zn was largely overestimated by the WHAM model, and it was found that using a binding constant of 1.7 instead of the default value of 1.3 would improve the fit between the simulations and experimental data. The MINTEQA2 model gave reasonable predictions of the complexation of Cd and Zn by DOC, whereas deviations in the estimated activity of the free Ni{sup 2+} ion as compared to experimental results are up to a factor of 5.« less
ERIC Educational Resources Information Center
Holzinger, Andreas; Kickmeier-Rust, Michael D.; Wassertheurer, Sigi; Hessinger, Michael
2009-01-01
Objective: Since simulations are often accepted uncritically, with excessive emphasis being placed on technological sophistication at the expense of underlying psychological and educational theories, we evaluated the learning performance of simulation software, in order to gain insight into the proper use of simulations for application in medical…
NASA Astrophysics Data System (ADS)
De Lucia, Marco; Kempka, Thomas; Jatnieks, Janis; Kühn, Michael
2017-04-01
Reactive transport simulations - where geochemical reactions are coupled with hydrodynamic transport of reactants - are extremely time consuming and suffer from significant numerical issues. Given the high uncertainties inherently associated with the geochemical models, which also constitute the major computational bottleneck, such requirements may seem inappropriate and probably constitute the main limitation for their wide application. A promising way to ease and speed-up such coupled simulations is achievable employing statistical surrogates instead of "full-physics" geochemical models [1]. Data-driven surrogates are reduced models obtained on a set of pre-calculated "full physics" simulations, capturing their principal features while being extremely fast to compute. Model reduction of course comes at price of a precision loss; however, this appears justified in presence of large uncertainties regarding the parametrization of geochemical processes. This contribution illustrates the integration of surrogates into the flexible simulation framework currently being developed by the authors' research group [2]. The high level language of choice for obtaining and dealing with surrogate models is R, which profits from state-of-the-art methods for statistical analysis of large simulations ensembles. A stand-alone advective mass transport module was furthermore developed in order to add such capability to any multiphase finite volume hydrodynamic simulator within the simulation framework. We present 2D and 3D case studies benchmarking the performance of surrogates and "full physics" chemistry in scenarios pertaining the assessment of geological subsurface utilization. [1] Jatnieks, J., De Lucia, M., Dransch, D., Sips, M.: "Data-driven surrogate model approach for improving the performance of reactive transport simulations.", Energy Procedia 97, 2016, p. 447-453. [2] Kempka, T., Nakaten, B., De Lucia, M., Nakaten, N., Otto, C., Pohl, M., Chabab [Tillner], E., Kühn, M.: "Flexible Simulation Framework to Couple Processes in Complex 3D Models for Subsurface Utilization Assessment.", Energy Procedia, 97, 2016 p. 494-501.
Zacarías-Lara, Oscar J; Correa-Basurto, José; Bello, Martiniano
2016-07-01
B-cell lymphoma (Bcl-2) is commonly associated with the progression and preservation of cancer and certain lymphomas; therefore, it is considered as a biological target against cancer. Nevertheless, evidence of all its structural binding sites has been hidden because of the lack of a complete Bcl-2 model, given the presence of a flexible loop domain (FLD), which is responsible for its complex behavior. FLD region has been implicated in phosphorylation, homotrimerization, and heterodimerization associated with Bcl-2 antiapoptotic function. In this contribution, homology modeling, molecular dynamics (MD) simulations in the microsecond (µs) time-scale and docking calculations were combined to explore the conformational complexity of unphosphorylated/phosphorylated monomeric and trimeric Bcl-2 systems. Conformational ensembles generated through MD simulations allowed for identifying the most populated unphosphorylated/phosphorylated monomeric conformations, which were used as starting models to obtain trimeric complexes through protein-protein docking calculations, also submitted to µs MD simulations. Principal component analysis showed that FLD represents the main contributor to total Bcl-2 mobility, and is affected by phosphorylation and oligomerization. Subsequently, based on the most representative unphosphorylated/phosphorylated monomeric and trimeric Bcl-2 conformations, docking studies were initiated to identify the ligand binding site of several known Bcl-2 inhibitors to explain their influence in homo-complex formation and phosphorylation. Docking studies showed that the different conformational states experienced by FLD, such as phosphorylation and oligomerization, play an essential role in the ability to make homo and hetero-complexes. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 393-413, 2016. © 2016 Wiley Periodicals, Inc.
Nikkhoo, Mohammad; Hsu, Yu-Chun; Haghpanahi, Mohammad; Parnianpour, Mohamad; Wang, Jaw-Lin
2013-06-01
Finite element analysis is an effective tool to evaluate the material properties of living tissue. For an interactive optimization procedure, the finite element analysis usually needs many simulations to reach a reasonable solution. The meta-model analysis of finite element simulation can be used to reduce the computation of a structure with complex geometry or a material with composite constitutive equations. The intervertebral disc is a complex, heterogeneous, and hydrated porous structure. A poroelastic finite element model can be used to observe the fluid transferring, pressure deviation, and other properties within the disc. Defining reasonable poroelastic material properties of the anulus fibrosus and nucleus pulposus is critical for the quality of the simulation. We developed a material property updating protocol, which is basically a fitting algorithm consisted of finite element simulations and a quadratic response surface regression. This protocol was used to find the material properties, such as the hydraulic permeability, elastic modulus, and Poisson's ratio, of intact and degenerated porcine discs. The results showed that the in vitro disc experimental deformations were well fitted with limited finite element simulations and a quadratic response surface regression. The comparison of material properties of intact and degenerated discs showed that the hydraulic permeability significantly decreased but Poisson's ratio significantly increased for the degenerated discs. This study shows that the developed protocol is efficient and effective in defining material properties of a complex structure such as the intervertebral disc.
2010-01-01
Background The longitudinal epidemiology of major depressive episodes (MDE) is poorly characterized in most countries. Some potentially relevant data sources may be underutilized because they are not conducive to estimating the most salient epidemiologic parameters. An available data source in Canada provides estimates that are potentially valuable, but that are difficult to apply in clinical or public health practice. For example, weeks depressed in the past year is assessed in this data source whereas episode duration would be of more interest. The goal of this project was to derive, using simulation, more readily interpretable parameter values from the available data. Findings The data source was a Canadian longitudinal study called the National Population Health Survey (NPHS). A simulation model representing the course of depressive episodes was used to reshape estimates deriving from binary and ordinal logistic models (fit to the NPHS data) into equations more capable of informing clinical and public health decisions. Discrete event simulation was used for this purpose. Whereas the intention was to clarify a complex epidemiology, the models themselves needed to become excessively complex in order to provide an accurate description of the data. Conclusions Simulation methods are useful in circumstances where a representation of a real-world system has practical value. In this particular scenario, the usefulness of simulation was limited both by problems with the data source and by inherent complexity of the underlying epidemiology. PMID:20796271
Considerations for Reporting Finite Element Analysis Studies in Biomechanics
Erdemir, Ahmet; Guess, Trent M.; Halloran, Jason; Tadepalli, Srinivas C.; Morrison, Tina M.
2012-01-01
Simulation-based medicine and the development of complex computer models of biological structures is becoming ubiquitous for advancing biomedical engineering and clinical research. Finite element analysis (FEA) has been widely used in the last few decades to understand and predict biomechanical phenomena. Modeling and simulation approaches in biomechanics are highly interdisciplinary, involving novice and skilled developers in all areas of biomedical engineering and biology. While recent advances in model development and simulation platforms offer a wide range of tools to investigators, the decision making process during modeling and simulation has become more opaque. Hence, reliability of such models used for medical decision making and for driving multiscale analysis comes into question. Establishing guidelines for model development and dissemination is a daunting task, particularly with the complex and convoluted models used in FEA. Nonetheless, if better reporting can be established, researchers will have a better understanding of a model’s value and the potential for reusability through sharing will be bolstered. Thus, the goal of this document is to identify resources and considerate reporting parameters for FEA studies in biomechanics. These entail various levels of reporting parameters for model identification, model structure, simulation structure, verification, validation, and availability. While we recognize that it may not be possible to provide and detail all of the reporting considerations presented, it is possible to establish a level of confidence with selective use of these parameters. More detailed reporting, however, can establish an explicit outline of the decision-making process in simulation-based analysis for enhanced reproducibility, reusability, and sharing. PMID:22236526
Pattern-oriented modeling of agent-based complex systems: Lessons from ecology
Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.
2005-01-01
Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.
Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology
NASA Astrophysics Data System (ADS)
Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.
2005-11-01
Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.
[Animal experimentation, computer simulation and surgical research].
Carpentier, Alain
2009-11-01
We live in a digital world In medicine, computers are providing new tools for data collection, imaging, and treatment. During research and development of complex technologies and devices such as artificial hearts, computer simulation can provide more reliable information than experimentation on large animals. In these specific settings, animal experimentation should serve more to validate computer models of complex devices than to demonstrate their reliability.
NASA Astrophysics Data System (ADS)
Deng, Shaohui; Wang, Xiaoling; Yu, Jia; Zhang, Yichi; Liu, Zhen; Zhu, Yushan
2018-06-01
Grouting plays a crucial role in dam safety. Due to the concealment of grouting activities, complexity of fracture distribution in rock masses and rheological properties of cement grout, it is difficult to analyze the effects of grouting. In this paper, a computational fluid dynamics (CFD) simulation approach of dam foundation grouting based on a 3D fracture network model is proposed. In this approach, the 3D fracture network model, which is based on an improved bootstrap sampling method and established by VisualGeo software, can provide a reliable and accurate geometric model for CFD simulation of dam foundation grouting. Based on the model, a CFD simulation is performed, in which the Papanastasiou regularized model is used to express the grout rheological properties, and the volume of fluid technique is utilized to capture the grout fronts. Two sets of tests are performed to verify the effectiveness of the Papanastasiou regularized model. When applying the CFD simulation approach for dam foundation grouting, three technical issues can be solved: (1) collapsing potential of the fracture samples, (2) inconsistencies in the geometric model in actual fractures under complex geological conditions, and (3) inappropriate method of characterizing the rheological properties of cement grout. The applicability of the proposed approach is demonstrated by an illustrative case study—a hydropower station dam foundation in southwestern China.
Active Learning for Directed Exploration of Complex Systems
NASA Technical Reports Server (NTRS)
Burl, Michael C.; Wang, Esther
2009-01-01
Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fidelity representation of system behavior, but are often so slow to run that insight into the system is limited. For example, conducting an exhaustive sweep over a d-dimensional input parameter space with k-steps along each dimension requires k(sup d) simulation trials (translating into k(sup d) CPU-days for one of our current simulations). An alternative is directed exploration in which the next simulation trials are cleverly chosen at each step. Given the results of previous trials, supervised learning techniques (SVM, KDE, GP) are applied to build up simplified predictive models of system behavior. These models are then used within an active learning framework to identify the most valuable trials to run next. Several active learning strategies are examined including a recently-proposed information-theoretic approach. Performance is evaluated on a set of thirteen synthetic oracles, which serve as surrogates for the more expensive simulations and enable the experiments to be replicated by other researchers.
NASA Astrophysics Data System (ADS)
Marconi, S.; Collalti, A.; Santini, M.; Valentini, R.
2013-12-01
3D-CMCC-Forest Ecosystem Model is a process based model formerly developed for complex forest ecosystems to estimate growth, water and carbon cycles, phenology and competition processes on a daily/monthly time scale. The Model integrates some characteristics of the functional-structural tree models with the robustness of the light use efficiency approach. It treats different heights, ages and species as discrete classes, in competition for light (vertical structure) and space (horizontal structure). The present work evaluates the results of the recently developed daily version of 3D-CMCC-FEM for two neighboring different even aged and mono specific study cases. The former is a heterogeneous Pedunculate oak forest (Quercus robur L. ), the latter a more homogeneous Scot pine forest (Pinus sylvestris L.). The multi-layer approach has been evaluated against a series of simplified versions to determine whether the improved model complexity in canopy structure definition increases its predictive ability. Results show that a more complex structure (three height layers) should be preferable to simulate heterogeneous scenarios (Pedunculate oak stand), where heights distribution within the canopy justify the distinction in dominant, dominated and sub-dominated layers. On the contrary, it seems that using a multi-layer approach for more homogeneous stands (Scot pine stand) may be disadvantageous. Forcing the structure of an homogeneous stand to a multi-layer approach may in fact increase sources of uncertainty. On the other hand forcing complex forests to a mono layer simplified model, may cause an increase in mortality and a reduction in average DBH and Height. Compared with measured CO2 flux data, model results show good ability in estimating carbon sequestration trends, on both a monthly/seasonal and daily time scales. Moreover the model simulates quite well leaf phenology and the combined effects of the two different forest stands on CO2 fluxes.
NASA Astrophysics Data System (ADS)
Heidarinejad, Mohammad
This dissertation develops rapid and accurate building energy simulations based on a building classification that identifies and focuses modeling efforts on most significant heat transfer processes. The building classification identifies energy use patterns and their contributing parameters for a portfolio of buildings. The dissertation hypothesis is "Building classification can provide minimal required inputs for rapid and accurate energy simulations for a large number of buildings". The critical literature review indicated there is lack of studies to (1) Consider synoptic point of view rather than the case study approach, (2) Analyze influence of different granularities of energy use, (3) Identify key variables based on the heat transfer processes, and (4) Automate the procedure to quantify model complexity with accuracy. Therefore, three dissertation objectives are designed to test out the dissertation hypothesis: (1) Develop different classes of buildings based on their energy use patterns, (2) Develop different building energy simulation approaches for the identified classes of buildings to quantify tradeoffs between model accuracy and complexity, (3) Demonstrate building simulation approaches for case studies. Penn State's and Harvard's campus buildings as well as high performance LEED NC office buildings are test beds for this study to develop different classes of buildings. The campus buildings include detailed chilled water, electricity, and steam data, enabling to classify buildings into externally-load, internally-load, or mixed-load dominated. The energy use of the internally-load buildings is primarily a function of the internal loads and their schedules. Externally-load dominated buildings tend to have an energy use pattern that is a function of building construction materials and outdoor weather conditions. However, most of the commercial medium-sized office buildings have a mixed-load pattern, meaning the HVAC system and operation schedule dictate the indoor condition regardless of the contribution of internal and external loads. To deploy the methodology to another portfolio of buildings, simulated LEED NC office buildings are selected. The advantage of this approach is to isolate energy performance due to inherent building characteristics and location, rather than operational and maintenance factors that can contribute to significant variation in building energy use. A framework for detailed building energy databases with annual energy end-uses is developed to select variables and omit outliers. The results show that the high performance office buildings are internally-load dominated with existence of three different clusters of low-intensity, medium-intensity, and high-intensity energy use pattern for the reviewed office buildings. Low-intensity cluster buildings benefit from small building area, while the medium- and high-intensity clusters have a similar range of floor areas and different energy use intensities. Half of the energy use in the low-intensity buildings is associated with the internal loads, such as lighting and plug loads, indicating that there are opportunities to save energy by using lighting or plug load management systems. A comparison between the frameworks developed for the campus buildings and LEED NC office buildings indicates these two frameworks are complementary to each other. Availability of the information has yielded to two different procedures, suggesting future studies for a portfolio of buildings such as city benchmarking and disclosure ordinance should collect and disclose minimal required inputs suggested by this study with the minimum level of monthly energy consumption granularity. This dissertation developed automated methods using the OpenStudio API (Application Programing Interface) to create energy models based on the building class. ASHRAE Guideline 14 defines well-accepted criteria to measure accuracy of energy simulations; however, there is no well-accepted methodology to quantify the model complexity without the influence of the energy modeler judgment about the model complexity. This study developed a novel method using two weighting factors, including weighting factors based on (1) computational time and (2) easiness of on-site data collection, to measure complexity of the energy models. Therefore, this dissertation enables measurement of both model complexity and accuracy as well as assessment of the inherent tradeoffs between energy simulation model complexity and accuracy. The results of this methodology suggest for most of the internal load contributors such as operation schedules the on-site data collection adds more complexity to the model compared to the computational time. Overall, this study provided specific data on tradeoffs between accuracy and model complexity that points to critical inputs for different building classes, rather than an increase in the volume and detail of model inputs as the current research and consulting practice indicates. (Abstract shortened by UMI.).
A Dynamic Finite Element Analysis of Human Foot Complex in the Sagittal Plane during Level Walking
Qian, Zhihui; Ren, Lei; Ding, Yun; Hutchinson, John R.; Ren, Luquan
2013-01-01
The objective of this study is to develop a computational framework for investigating the dynamic behavior and the internal loading conditions of the human foot complex during locomotion. A subject-specific dynamic finite element model in the sagittal plane was constructed based on anatomical structures segmented from medical CT scan images. Three-dimensional gait measurements were conducted to support and validate the model. Ankle joint forces and moment derived from gait measurements were used to drive the model. Explicit finite element simulations were conducted, covering the entire stance phase from heel-strike impact to toe-off. The predicted ground reaction forces, center of pressure, foot bone motions and plantar surface pressure showed reasonably good agreement with the gait measurement data over most of the stance phase. The prediction discrepancies can be explained by the assumptions and limitations of the model. Our analysis showed that a dynamic FE simulation can improve the prediction accuracy in the peak plantar pressures at some parts of the foot complex by 10%–33% compared to a quasi-static FE simulation. However, to simplify the costly explicit FE simulation, the proposed model is confined only to the sagittal plane and has a simplified representation of foot structure. The dynamic finite element foot model proposed in this study would provide a useful tool for future extension to a fully muscle-driven dynamic three-dimensional model with detailed representation of all major anatomical structures, in order to investigate the structural dynamics of the human foot musculoskeletal system during normal or even pathological functioning. PMID:24244500
A dynamic finite element analysis of human foot complex in the sagittal plane during level walking.
Qian, Zhihui; Ren, Lei; Ding, Yun; Hutchinson, John R; Ren, Luquan
2013-01-01
The objective of this study is to develop a computational framework for investigating the dynamic behavior and the internal loading conditions of the human foot complex during locomotion. A subject-specific dynamic finite element model in the sagittal plane was constructed based on anatomical structures segmented from medical CT scan images. Three-dimensional gait measurements were conducted to support and validate the model. Ankle joint forces and moment derived from gait measurements were used to drive the model. Explicit finite element simulations were conducted, covering the entire stance phase from heel-strike impact to toe-off. The predicted ground reaction forces, center of pressure, foot bone motions and plantar surface pressure showed reasonably good agreement with the gait measurement data over most of the stance phase. The prediction discrepancies can be explained by the assumptions and limitations of the model. Our analysis showed that a dynamic FE simulation can improve the prediction accuracy in the peak plantar pressures at some parts of the foot complex by 10%-33% compared to a quasi-static FE simulation. However, to simplify the costly explicit FE simulation, the proposed model is confined only to the sagittal plane and has a simplified representation of foot structure. The dynamic finite element foot model proposed in this study would provide a useful tool for future extension to a fully muscle-driven dynamic three-dimensional model with detailed representation of all major anatomical structures, in order to investigate the structural dynamics of the human foot musculoskeletal system during normal or even pathological functioning.
Experimental validation of numerical simulations on a cerebral aneurysm phantom model
Seshadhri, Santhosh; Janiga, Gábor; Skalej, Martin; Thévenin, Dominique
2012-01-01
The treatment of cerebral aneurysms, found in roughly 5% of the population and associated in case of rupture to a high mortality rate, is a major challenge for neurosurgery and neuroradiology due to the complexity of the intervention and to the resulting, high hazard ratio. Improvements are possible but require a better understanding of the associated, unsteady blood flow patterns in complex 3D geometries. It would be very useful to carry out such studies using suitable numerical models, if it is proven that they reproduce accurately enough the real conditions. This validation step is classically based on comparisons with measured data. Since in vivo measurements are extremely difficult and therefore of limited accuracy, complementary model-based investigations considering realistic configurations are essential. In the present study, simulations based on computational fluid dynamics (CFD) have been compared with in situ, laser-Doppler velocimetry (LDV) measurements in the phantom model of a cerebral aneurysm. The employed 1:1 model is made from transparent silicone. A liquid mixture composed of water, glycerin, xanthan gum and sodium chloride has been specifically adapted for the present investigation. It shows physical flow properties similar to real blood and leads to a refraction index perfectly matched to that of the silicone model, allowing accurate optical measurements of the flow velocity. For both experiments and simulations, complex pulsatile flow waveforms and flow rates were accounted for. This finally allows a direct, quantitative comparison between measurements and simulations. In this manner, the accuracy of the employed computational model can be checked. PMID:24265876
InterSpread Plus: a spatial and stochastic simulation model of disease in animal populations.
Stevenson, M A; Sanson, R L; Stern, M W; O'Leary, B D; Sujau, M; Moles-Benfell, N; Morris, R S
2013-04-01
We describe the spatially explicit, stochastic simulation model of disease spread, InterSpread Plus, in terms of its epidemiological framework, operation, and mode of use. The input data required by the model, the method for simulating contact and infection spread, and methods for simulating disease control measures are described. Data and parameters that are essential for disease simulation modelling using InterSpread Plus are distinguished from those that are non-essential, and it is suggested that a rational approach to simulating disease epidemics using this tool is to start with core data and parameters, adding additional layers of complexity if and when the specific requirements of the simulation exercise require it. We recommend that simulation models of disease are best developed as part of epidemic contingency planning so decision makers are familiar with model outputs and assumptions and are well-positioned to evaluate their strengths and weaknesses to make informed decisions in times of crisis. Copyright © 2012 Elsevier B.V. All rights reserved.
Numerical Simulation of Regional Circulation in the Monterey Bay Region
NASA Technical Reports Server (NTRS)
Tseng, Y. H.; Dietrich, D. E.; Ferziger, J. H.
2003-01-01
The objective of this study is to produce a high-resolution numerical model of Mon- terey Bay area in which the dynamics are determined by the complex geometry of the coastline, steep bathymetry, and the in uence of the water masses that constitute the CCS. Our goal is to simulate the regional-scale ocean response with realistic dynamics (annual cycle), forcing, and domain. In particular, we focus on non-hydrostatic e ects (by comparing the results of hydrostatic and non-hydrostatic models) and the role of complex geometry, i.e. the bay and submarine canyon, on the nearshore circulation. To the best of our knowledge, the current study is the rst to simulate the regional circulation in the vicinity of Monterey Bay using a non-hydrostatic model. Section 2 introduces the high resolution Monterey Bay area regional model (MBARM). Section 3 provides the results and veri cation with mooring and satellite data. Section 4 compares the results of hydrostatic and non-hydrostatic models.
A method to identify and analyze biological programs through automated reasoning
Yordanov, Boyan; Dunn, Sara-Jane; Kugler, Hillel; Smith, Austin; Martello, Graziano; Emmott, Stephen
2016-01-01
Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich, but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function. PMID:27668090
Johnson, M.S.; Coon, W.F.; Mehta, V.K.; Steenhuis, T.S.; Brooks, E.S.; Boll, J.
2003-01-01
Differences in the simulation of hydrologic processes by watershed models directly affect the accuracy of results. Surface runoff generation can be simulated as either: (1) infiltration-excess (or Hortonian) overland flow, or (2) saturation-excess overland flow. This study compared the Hydrological Simulation Program - FORTRAN (HSPF) and the Soil Moisture Routing (SMR) models, each representing one of these mechanisms. These two models were applied to a 102 km2 watershed in the upper part of the Irondequoit Creek basin in central New York State over a seven-year simulation period. The models differed in both the complexity of simulating snowmelt and baseflow processes as well as the detail in which the geographic information was preserved by each model. Despite their differences in structure and representation of hydrologic processes, the two models simulated streamflow with almost equal accuracy. Since streamflow is an integral response and depends mainly on the watershed water balance, this was not unexpected. Model efficiency values for the seven-year simulation period were 0.67 and 0.65 for SMR and HSPF, respectively. HSPF simulated winter streamflow slightly better than SMR as a result of its complex snowmelt routine, whereas SMR simulated summer flows better than HSPF as a result of its runoff and baseflow processes. An important difference between model results was the ability to predict the spatial distribution of soil moisture content. HSPF aggregates soil moisture content, which is generally related to a specific pervious land unit across the entire watershed, whereas SMR predictions of moisture content distribution are geographically specific and matched field observations reasonably well. Important is that the saturated area was predicted well by SMR and confirmed the validity of using saturation-excess mechanisms for this hillslope dominated watershed. ?? 2003 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Fu, Qiang; Liu, Jianhua; Wang, Xiaoman; Jiang, Huilin; Liu, Zhi
2014-12-01
The laser transmission characteristics affected in the complex channel environment, which limits the performance of laser equipment and engineering application severely. The article aim at the influence of laser transmission in atmospheric and seawater channels, summarizes the foreign researching work of the simulation and comprehensive test regarding to the laser transmission characteristics in complex environment. And researched the theory of atmospheric turbulence effect, water attenuation features, and put forward the corresponding theoretical model. And researched the simulate technology of atmospheric channel and sea water channel, put forward the analog device plan, adopt the similar theory of flowing to simulate the atmosphere turbulence .When the flowing has the same condition of geometric limits including the same Reynolds, they must be similar to each other in the motivation despite of the difference in the size, speed, and intrinsic quality. On this basis, set up a device for complex channel simulation and comprehensive testing, the overall design of the structure of the device, Hot and Cold Air Convection Simulation of Atmospheric Turbulence, mainly consists of cell body, heating systems, cooling systems, automatic control system. he simulator provides platform and method for the basic research of laser transmission characteristics in the domestic.
NASA Astrophysics Data System (ADS)
Calderer, Antoni; Guo, Xin; Shen, Lian; Sotiropoulos, Fotis
2018-02-01
We develop a numerical method for simulating coupled interactions of complex floating structures with large-scale ocean waves and atmospheric turbulence. We employ an efficient large-scale model to develop offshore wind and wave environmental conditions, which are then incorporated into a high resolution two-phase flow solver with fluid-structure interaction (FSI). The large-scale wind-wave interaction model is based on a two-fluid dynamically-coupled approach that employs a high-order spectral method for simulating the water motion and a viscous solver with undulatory boundaries for the air motion. The two-phase flow FSI solver is based on the level set method and is capable of simulating the coupled dynamic interaction of arbitrarily complex bodies with airflow and waves. The large-scale wave field solver is coupled with the near-field FSI solver with a one-way coupling approach by feeding into the latter waves via a pressure-forcing method combined with the level set method. We validate the model for both simple wave trains and three-dimensional directional waves and compare the results with experimental and theoretical solutions. Finally, we demonstrate the capabilities of the new computational framework by carrying out large-eddy simulation of a floating offshore wind turbine interacting with realistic ocean wind and waves.
Development and application of computational fluid dynamics (CFD) simulations are being advanced through case studies for simulating air pollutant concentrations from sources within open fields and within complex urban building environments. CFD applications have been under deve...
Efficacy of Simulation-Based Learning of Electronics Using Visualization and Manipulation
ERIC Educational Resources Information Center
Chen, Yu-Lung; Hong, Yu-Ru; Sung, Yao-Ting; Chang, Kuo-En
2011-01-01
Software for simulation-based learning of electronics was implemented to help learners understand complex and abstract concepts through observing external representations and exploring concept models. The software comprises modules for visualization and simulative manipulation. Differences in learning performance of using the learning software…
A framework for WRF to WRF-IBM grid nesting to enable multiscale simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wiersema, David John; Lundquist, Katherine A.; Chow, Fotini Katapodes
With advances in computational power, mesoscale models, such as the Weather Research and Forecasting (WRF) model, are often pushed to higher resolutions. As the model’s horizontal resolution is refined, the maximum resolved terrain slope will increase. Because WRF uses a terrain-following coordinate, this increase in resolved terrain slopes introduces additional grid skewness. At high resolutions and over complex terrain, this grid skewness can introduce large numerical errors that require methods, such as the immersed boundary method, to keep the model accurate and stable. Our implementation of the immersed boundary method in the WRF model, WRF-IBM, has proven effective at microscalemore » simulations over complex terrain. WRF-IBM uses a non-conforming grid that extends beneath the model’s terrain. Boundary conditions at the immersed boundary, the terrain, are enforced by introducing a body force term to the governing equations at points directly beneath the immersed boundary. Nesting between a WRF parent grid and a WRF-IBM child grid requires a new framework for initialization and forcing of the child WRF-IBM grid. This framework will enable concurrent multi-scale simulations within the WRF model, improving the accuracy of high-resolution simulations and enabling simulations across a wide range of scales.« less
2016-03-14
flows , or continuous state changes, with feedback loops and lags modeled in the flow system. Agent based simulations operate using a discrete event...DeLand, S. M., Rutherford, B . M., Diegert, K. V., & Alvin, K. F. (2002). Error and uncertainty in modeling and simulation . Reliability Engineering...intrinsic complexity of the underlying social systems fundamentally limits the ability to make
The United States Environmental Protection Agency’s Environmental Sciences and Atmospheric Modeling Analysis Divisions are investigating the viability of simulated (i.e., ‘modeled’) leaf area index (LAI) inputs into various regional and local scale air quality models. Satellite L...
NASA Astrophysics Data System (ADS)
Kosovic, B.; Jimenez, P. A.; Haupt, S. E.; Martilli, A.; Olson, J.; Bao, J. W.
2017-12-01
At present, the planetary boundary layer (PBL) parameterizations available in most numerical weather prediction (NWP) models are one-dimensional. One-dimensional parameterizations are based on the assumption of horizontal homogeneity. This homogeneity assumption is appropriate for grid cell sizes greater than 10 km. However, for mesoscale simulations of flows in complex terrain with grid cell sizes below 1 km, the assumption of horizontal homogeneity is violated. Applying a one-dimensional PBL parameterization to high-resolution mesoscale simulations in complex terrain could result in significant error. For high-resolution mesoscale simulations of flows in complex terrain, we have therefore developed and implemented a three-dimensional (3D) PBL parameterization in the Weather Research and Forecasting (WRF) model. The implementation of the 3D PBL scheme is based on the developments outlined by Mellor and Yamada (1974, 1982). Our implementation in the Weather Research and Forecasting (WRF) model uses a pure algebraic model (level 2) to diagnose the turbulent fluxes. To evaluate the performance of the 3D PBL model, we use observations from the Wind Forecast Improvement Project 2 (WFIP2). The WFIP2 field study took place in the Columbia River Gorge area from 2015-2017. We focus on selected cases when physical phenomena of significance for wind energy applications such as mountain waves, topographic wakes, and gap flows were observed. Our assessment of the 3D PBL parameterization also considers a large-eddy simulation (LES). We carried out a nested LES with grid cell sizes of 30 m and 10 m covering a large fraction of the WFIP2 study area. Both LES domains were discretized using 6000 x 3000 x 200 grid cells in zonal, meridional, and vertical direction, respectively. The LES results are used to assess the relative magnitude of horizontal gradients of turbulent stresses and fluxes in comparison to vertical gradients. The presentation will highlight the advantages of the 3D PBL scheme in regions of complex terrain.
Model improvements to simulate charging in SEM
NASA Astrophysics Data System (ADS)
Arat, K. T.; Klimpel, T.; Hagen, C. W.
2018-03-01
Charging of insulators is a complex phenomenon to simulate since the accuracy of the simulations is very sensitive to the interaction of electrons with matter and electric fields. In this study, we report model improvements for a previously developed Monte-Carlo simulator to more accurately simulate samples that charge. The improvements include both modelling of low energy electron scattering and charging of insulators. The new first-principle scattering models provide a more realistic charge distribution cloud in the material, and a better match between non-charging simulations and experimental results. Improvements on charging models mainly focus on redistribution of the charge carriers in the material with an induced conductivity (EBIC) and a breakdown model, leading to a smoother distribution of the charges. Combined with a more accurate tracing of low energy electrons in the electric field, we managed to reproduce the dynamically changing charging contrast due to an induced positive surface potential.
Scale-Dependent Rates of Uranyl Surface Complexation Reaction in Sediments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Chongxuan; Shang, Jianying; Kerisit, Sebastien N.
Scale-dependency of uranyl[U(VI)] surface complexation rates was investigated in stirred flow-cell and column systems using a U(VI)-contaminated sediment from the US Department of Energy, Hanford site, WA. The experimental results were used to estimate the apparent rate of U(VI) surface complexation at the grain-scale and in porous media. Numerical simulations using molecular, pore-scale, and continuum models were performed to provide insights into and to estimate the rate constants of U(VI) surface complexation at the different scales. The results showed that the grain-scale rate constant of U(VI) surface complexation was over 3 to 10 orders of magnitude smaller, dependent on themore » temporal scale, than the rate constant calculated using the molecular simulations. The grain-scale rate was faster initially and slower with time, showing the temporal scale-dependency. The largest rate constant at the grain-scale decreased additional 2 orders of magnitude when the rate was scaled to the porous media in the column. The scaling effect from the grain-scale to the porous media became less important for the slower sorption sites. Pore-scale simulations revealed the importance of coupled mass transport and reactions in both intragranular and inter-granular domains, which caused both spatial and temporal dependence of U(VI) surface complexation rates in the sediment. Pore-scale simulations also revealed a new rate-limiting mechanism in the intragranular porous domains that the rate of coupled diffusion and surface complexation reaction was slower than either process alone. The results provided important implications for developing models to scale geochemical/biogeochemical reactions.« less
A parallel reaction-transport model applied to cement hydration and microstructure development
NASA Astrophysics Data System (ADS)
Bullard, Jeffrey W.; Enjolras, Edith; George, William L.; Satterfield, Steven G.; Terrill, Judith E.
2010-03-01
A recently described stochastic reaction-transport model on three-dimensional lattices is parallelized and is used to simulate the time-dependent structural and chemical evolution in multicomponent reactive systems. The model, called HydratiCA, uses probabilistic rules to simulate the kinetics of diffusion, homogeneous reactions and heterogeneous phenomena such as solid nucleation, growth and dissolution in complex three-dimensional systems. The algorithms require information only from each lattice site and its immediate neighbors, and this localization enables the parallelized model to exhibit near-linear scaling up to several hundred processors. Although applicable to a wide range of material systems, including sedimentary rock beds, reacting colloids and biochemical systems, validation is performed here on two minerals that are commonly found in Portland cement paste, calcium hydroxide and ettringite, by comparing their simulated dissolution or precipitation rates far from equilibrium to standard rate equations, and also by comparing simulated equilibrium states to thermodynamic calculations, as a function of temperature and pH. Finally, we demonstrate how HydratiCA can be used to investigate microstructure characteristics, such as spatial correlations between different condensed phases, in more complex microstructures.
Braathen, Sverre; Sendstad, Ole Jakob
2004-08-01
Possible techniques for representing automatic decision-making behavior approximating human experts in complex simulation model experiments are of interest. Here, fuzzy logic (FL) and constraint satisfaction problem (CSP) methods are applied in a hybrid design of automatic decision making in simulation game models. The decision processes of a military headquarters are used as a model for the FL/CSP decision agents choice of variables and rulebases. The hybrid decision agent design is applied in two different types of simulation games to test the general applicability of the design. The first application is a two-sided zero-sum sequential resource allocation game with imperfect information interpreted as an air campaign game. The second example is a network flow stochastic board game designed to capture important aspects of land manoeuvre operations. The proposed design is shown to perform well also in this complex game with a very large (billionsize) action set. Training of the automatic FL/CSP decision agents against selected performance measures is also shown and results are presented together with directions for future research.
Comparisons of CTH simulations with measured wave profiles for simple flyer plate experiments
Thomas, S. A.; Veeser, L. R.; Turley, W. D.; ...
2016-06-13
We conducted detailed 2-dimensional hydrodynamics calculations to assess the quality of simulations commonly used to design and analyze simple shock compression experiments. Such simple shock experiments also contain data where dynamic properties of materials are integrated together. We wished to assess how well the chosen computer hydrodynamic code could do at capturing both the simple parts of the experiments and the integral parts. We began with very simple shock experiments, in which we examined the effects of the equation of state and the compressional and tensile strength models. We increased complexity to include spallation in copper and iron and amore » solid-solid phase transformation in iron to assess the quality of the damage and phase transformation simulations. For experiments with a window, the response of both the sample and the window are integrated together, providing a good test of the material models. While CTH physics models are not perfect and do not reproduce all experimental details well, we find the models are useful; the simulations are adequate for understanding much of the dynamic process and for planning experiments. However, higher complexity in the simulations, such as adding in spall, led to greater differences between simulation and experiment. Lastly, this comparison of simulation to experiment may help guide future development of hydrodynamics codes so that they better capture the underlying physics.« less
Smoldyn on graphics processing units: massively parallel Brownian dynamics simulations.
Dematté, Lorenzo
2012-01-01
Space is a very important aspect in the simulation of biochemical systems; recently, the need for simulation algorithms able to cope with space is becoming more and more compelling. Complex and detailed models of biochemical systems need to deal with the movement of single molecules and particles, taking into consideration localized fluctuations, transportation phenomena, and diffusion. A common drawback of spatial models lies in their complexity: models can become very large, and their simulation could be time consuming, especially if we want to capture the systems behavior in a reliable way using stochastic methods in conjunction with a high spatial resolution. In order to deliver the promise done by systems biology to be able to understand a system as whole, we need to scale up the size of models we are able to simulate, moving from sequential to parallel simulation algorithms. In this paper, we analyze Smoldyn, a widely diffused algorithm for stochastic simulation of chemical reactions with spatial resolution and single molecule detail, and we propose an alternative, innovative implementation that exploits the parallelism of Graphics Processing Units (GPUs). The implementation executes the most computational demanding steps (computation of diffusion, unimolecular, and bimolecular reaction, as well as the most common cases of molecule-surface interaction) on the GPU, computing them in parallel on each molecule of the system. The implementation offers good speed-ups and real time, high quality graphics output
Lattice Boltzmann Modeling of Complex Flows for Engineering Applications
NASA Astrophysics Data System (ADS)
Montessori, Andrea; Falcucci, Giacomo
2018-01-01
Nature continuously presents a huge number of complex and multiscale phenomena, which in many cases, involve the presence of one or more fluids flowing, merging and evolving around us. Since the very first years of the third millennium, the Lattice Boltzmann method (LB) has seen an exponential growth of applications, especially in the fields connected with the simulation of complex and soft matter flows. LB, in fact, has shown a remarkable versatility in different fields of applications from nanoactive materials, free surface flows, and multiphase and reactive flows to the simulation of the processes inside engines and fluid machinery. In this book, the authors present the most recent advances of the application of the LB to complex flow phenomena of scientific and technical interest with focus on the multiscale modeling of heterogeneous catalysis within nano-porous media and multiphase, multicomponent flows.
An Example-Based Brain MRI Simulation Framework.
He, Qing; Roy, Snehashis; Jog, Amod; Pham, Dzung L
2015-02-21
The simulation of magnetic resonance (MR) images plays an important role in the validation of image analysis algorithms such as image segmentation, due to lack of sufficient ground truth in real MR images. Previous work on MRI simulation has focused on explicitly modeling the MR image formation process. However, because of the overwhelming complexity of MR acquisition these simulations must involve simplifications and approximations that can result in visually unrealistic simulated images. In this work, we describe an example-based simulation framework, which uses an "atlas" consisting of an MR image and its anatomical models derived from the hard segmentation. The relationships between the MR image intensities and its anatomical models are learned using a patch-based regression that implicitly models the physics of the MR image formation. Given the anatomical models of a new brain, a new MR image can be simulated using the learned regression. This approach has been extended to also simulate intensity inhomogeneity artifacts based on the statistical model of training data. Results show that the example based MRI simulation method is capable of simulating different image contrasts and is robust to different choices of atlas. The simulated images resemble real MR images more than simulations produced by a physics-based model.
EMU Suit Performance Simulation
NASA Technical Reports Server (NTRS)
Cowley, Matthew S.; Benson, Elizabeth; Harvill, Lauren; Rajulu, Sudhakar
2014-01-01
Introduction: Designing a planetary suit is very complex and often requires difficult trade-offs between performance, cost, mass, and system complexity. To verify that new suit designs meet requirements, full prototypes must be built and tested with human subjects. However, numerous design iterations will occur before the hardware meets those requirements. Traditional draw-prototype-test paradigms for research and development are prohibitively expensive with today's shrinking Government budgets. Personnel at NASA are developing modern simulation techniques that focus on a human-centric design paradigm. These new techniques make use of virtual prototype simulations and fully adjustable physical prototypes of suit hardware. This is extremely advantageous and enables comprehensive design down-selections to be made early in the design process. Objectives: The primary objective was to test modern simulation techniques for evaluating the human performance component of two EMU suit concepts, pivoted and planar style hard upper torso (HUT). Methods: This project simulated variations in EVA suit shoulder joint design and subject anthropometry and then measured the differences in shoulder mobility caused by the modifications. These estimations were compared to human-in-the-loop test data gathered during past suited testing using four subjects (two large males, two small females). Results: Results demonstrated that EVA suit modeling and simulation are feasible design tools for evaluating and optimizing suit design based on simulated performance. The suit simulation model was found to be advantageous in its ability to visually represent complex motions and volumetric reach zones in three dimensions, giving designers a faster and deeper comprehension of suit component performance vs. human performance. Suit models were able to discern differing movement capabilities between EMU HUT configurations, generic suit fit concerns, and specific suit fit concerns for crewmembers based on individual anthropometry
A flexible object-oriented software framework for developing complex multimedia simulations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sydelko, P. J.; Dolph, J. E.; Christiansen, J. H.
Decision makers involved in brownfields redevelopment and long-term stewardship must consider environmental conditions, future-use potential, site ownership, area infrastructure, funding resources, cost recovery, regulations, risk and liability management, community relations, and expected return on investment in a comprehensive and integrated fashion to achieve desired results. Successful brownfields redevelopment requires the ability to assess the impacts of redevelopment options on multiple interrelated aspects of the ecosystem, both natural and societal. Computer-based tools, such as simulation models, databases, and geographical information systems (GISs) can be used to address brownfields planning and project execution. The transparent integration of these tools into a comprehensivemore » and dynamic decision support system would greatly enhance the brownfields assessment process. Such a system needs to be able to adapt to shifting and expanding analytical requirements and contexts. The Dynamic Information Architecture System (DIAS) is a flexible, extensible, object-oriented framework for developing and maintaining complex multidisciplinary simulations of a wide variety of application domains. The modeling domain of a specific DIAS-based simulation is determined by (1) software objects that represent the real-world entities that comprise the problem space (atmosphere, watershed, human), and (2) simulation models and other data processing applications that express the dynamic behaviors of the domain entities. Models and applications used to express dynamic behaviors can be either internal or external to DIAS, including existing legacy models written in various languages (FORTRAN, C, etc.). The flexible design framework of DIAS makes the objects adjustable to the context of the problem without a great deal of recoding. The DIAS Spatial Data Set facility allows parameters to vary spatially depending on the simulation context according to any of a number of 1-D, 2-D, or 3-D topologies. DIAS is also capable of interacting with other GIS packages and can import many standard spatial data formats. DIAS simulation capabilities can also be extended by including societal process models. Models that implement societal behaviors of individuals and organizations within larger DIAS-based natural systems simulations allow for interaction and feedback among natural and societal processes. The ability to simulate the complex interplay of multimedia processes makes DIAS a promising tool for constructing applications for comprehensive community planning, including the assessment of multiple development and redevelopment scenarios.« less
NASA Astrophysics Data System (ADS)
Heister, Timo; Dannberg, Juliane; Gassmöller, Rene; Bangerth, Wolfgang
2017-08-01
Computations have helped elucidate the dynamics of Earth's mantle for several decades already. The numerical methods that underlie these simulations have greatly evolved within this time span, and today include dynamically changing and adaptively refined meshes, sophisticated and efficient solvers, and parallelization to large clusters of computers. At the same time, many of the methods - discussed in detail in a previous paper in this series - were developed and tested primarily using model problems that lack many of the complexities that are common to the realistic models our community wants to solve today. With several years of experience solving complex and realistic models, we here revisit some of the algorithm designs of the earlier paper and discuss the incorporation of more complex physics. In particular, we re-consider time stepping and mesh refinement algorithms, evaluate approaches to incorporate compressibility, and discuss dealing with strongly varying material coefficients, latent heat, and how to track chemical compositions and heterogeneities. Taken together and implemented in a high-performance, massively parallel code, the techniques discussed in this paper then allow for high resolution, 3-D, compressible, global mantle convection simulations with phase transitions, strongly temperature dependent viscosity and realistic material properties based on mineral physics data.
Simulating the Composite Propellant Manufacturing Process
NASA Technical Reports Server (NTRS)
Williamson, Suzanne; Love, Gregory
2000-01-01
There is a strategic interest in understanding how the propellant manufacturing process contributes to military capabilities outside the United States. The paper will discuss how system dynamics (SD) has been applied to rapidly assess the capabilities and vulnerabilities of a specific composite propellant production complex. These facilities produce a commonly used solid propellant with military applications. The authors will explain how an SD model can be configured to match a specific production facility followed by a series of scenarios designed to analyze operational vulnerabilities. By using the simulation model to rapidly analyze operational risks, the analyst gains a better understanding of production complexities. There are several benefits of developing SD models to simulate chemical production. SD is an effective tool for characterizing complex problems, especially the production process where the cascading effect of outages quickly taxes common understanding. By programming expert knowledge into an SD application, these tools are transformed into a knowledge management resource that facilitates rapid learning without requiring years of experience in production operations. It also permits the analyst to rapidly respond to crisis situations and other time-sensitive missions. Most importantly, the quantitative understanding gained from applying the SD model lends itself to strategic analysis and planning.
Venkateshwari, Sureshkumar; Veluraja, Kasinadar
2012-01-01
The conformational property of oligosaccharide GT1B in aqueous environment was studied by molecular dynamics (MD) simulation using all-atom model. Based on the trajectory analysis, three prominent conformational models were proposed for GT1B. Direct and water-mediated hydrogen bonding interactions stabilize these structures. The molecular modeling and 15 ns MD simulation of the Botulinum Neuro Toxin/B (BoNT/B) - GT1B complex revealed that BoNT/B can accommodate the GT1B in the single binding mode. Least mobility was seen for oligo-GT1B in the binding pocket. The bound conformation of GT1B obtained from the MD simulation of the BoNT/B-GT1B complex bear a close conformational similarity with the crystal structure of BoNT/A-GT1B complex. The mobility noticed for Arg 1268 in the dynamics was accounted for its favorable interaction with terminal NeuNAc. The internal NeuNAc1 tends to form 10 hydrogen bonds with BoNT/B, hence specifying this particular site as a crucial space for the therapeutic design that can restrict the pathogenic activity of BoNT/B.
Simulation Models for Socioeconomic Inequalities in Health: A Systematic Review
Speybroeck, Niko; Van Malderen, Carine; Harper, Sam; Müller, Birgit; Devleesschauwer, Brecht
2013-01-01
Background: The emergence and evolution of socioeconomic inequalities in health involves multiple factors interacting with each other at different levels. Simulation models are suitable for studying such complex and dynamic systems and have the ability to test the impact of policy interventions in silico. Objective: To explore how simulation models were used in the field of socioeconomic inequalities in health. Methods: An electronic search of studies assessing socioeconomic inequalities in health using a simulation model was conducted. Characteristics of the simulation models were extracted and distinct simulation approaches were identified. As an illustration, a simple agent-based model of the emergence of socioeconomic differences in alcohol abuse was developed. Results: We found 61 studies published between 1989 and 2013. Ten different simulation approaches were identified. The agent-based model illustration showed that multilevel, reciprocal and indirect effects of social determinants on health can be modeled flexibly. Discussion and Conclusions: Based on the review, we discuss the utility of using simulation models for studying health inequalities, and refer to good modeling practices for developing such models. The review and the simulation model example suggest that the use of simulation models may enhance the understanding and debate about existing and new socioeconomic inequalities of health frameworks. PMID:24192788
NASA Astrophysics Data System (ADS)
Wrożyna, Andrzej; Pernach, Monika; Kuziak, Roman; Pietrzyk, Maciej
2016-04-01
Due to their exceptional strength properties combined with good workability the Advanced High-Strength Steels (AHSS) are commonly used in automotive industry. Manufacturing of these steels is a complex process which requires precise control of technological parameters during thermo-mechanical treatment. Design of these processes can be significantly improved by the numerical models of phase transformations. Evaluation of predictive capabilities of models, as far as their applicability in simulation of thermal cycles thermal cycles for AHSS is considered, was the objective of the paper. Two models were considered. The former was upgrade of the JMAK equation while the latter was an upgrade of the Leblond model. The models can be applied to any AHSS though the examples quoted in the paper refer to the Dual Phase (DP) steel. Three series of experimental simulations were performed. The first included various thermal cycles going beyond limitations of the continuous annealing lines. The objective was to validate models behavior in more complex cooling conditions. The second set of tests included experimental simulations of the thermal cycle characteristic for the continuous annealing lines. Capability of the models to describe properly phase transformations in this process was evaluated. The third set included data from the industrial continuous annealing line. Validation and verification of models confirmed their good predictive capabilities. Since it does not require application of the additivity rule, the upgrade of the Leblond model was selected as the better one for simulation of industrial processes in AHSS production.
Gravitational orientation of the orbital complex, Salyut-6--Soyuz
NASA Technical Reports Server (NTRS)
Grecho, G. M.; Sarychev, V. A.; Legostayev, V. P.; Sazonov, V. V.; Gansvind, I. N.
1983-01-01
A simple mathematical model is proposed for the Salyut-6-Soyuz orbital complex motion with respect to the center of mass under the one-axis gravity-gradient orientation regime. This model was used for processing the measurements of the orbital complex motion parameters when the above orientation region was implemented. Some actual satellite motions are simulated and the satellite's aerodynamic parameters are determined. Estimates are obtained for the accuracy of measurements as well as that of the mathematical model.
On the robustness of complex heterogeneous gene expression networks.
Gómez-Gardeñes, Jesús; Moreno, Yamir; Floría, Luis M
2005-04-01
We analyze a continuous gene expression model on the underlying topology of a complex heterogeneous network. Numerical simulations aimed at studying the chaotic and periodic dynamics of the model are performed. The results clearly indicate that there is a region in which the dynamical and structural complexity of the system avoid chaotic attractors. However, contrary to what has been reported for Random Boolean Networks, the chaotic phase cannot be completely suppressed, which has important bearings on network robustness and gene expression modeling.
Rudling, Axel; Orro, Adolfo; Carlsson, Jens
2018-02-26
Water plays a major role in ligand binding and is attracting increasing attention in structure-based drug design. Water molecules can make large contributions to binding affinity by bridging protein-ligand interactions or by being displaced upon complex formation, but these phenomena are challenging to model at the molecular level. Herein, networks of ordered water molecules in protein binding sites were analyzed by clustering of molecular dynamics (MD) simulation trajectories. Locations of ordered waters (hydration sites) were first identified from simulations of high resolution crystal structures of 13 protein-ligand complexes. The MD-derived hydration sites reproduced 73% of the binding site water molecules observed in the crystal structures. If the simulations were repeated without the cocrystallized ligands, a majority (58%) of the crystal waters in the binding sites were still predicted. In addition, comparison of the hydration sites obtained from simulations carried out in the absence of ligands to those identified for the complexes revealed that the networks of ordered water molecules were preserved to a large extent, suggesting that the locations of waters in a protein-ligand interface are mainly dictated by the protein. Analysis of >1000 crystal structures showed that hydration sites bridged protein-ligand interactions in complexes with different ligands, and those with high MD-derived occupancies were more likely to correspond to experimentally observed ordered water molecules. The results demonstrate that ordered water molecules relevant for modeling of protein-ligand complexes can be identified from MD simulations. Our findings could contribute to development of improved methods for structure-based virtual screening and lead optimization.
Modeling software systems by domains
NASA Technical Reports Server (NTRS)
Dippolito, Richard; Lee, Kenneth
1992-01-01
The Software Architectures Engineering (SAE) Project at the Software Engineering Institute (SEI) has developed engineering modeling techniques that both reduce the complexity of software for domain-specific computer systems and result in systems that are easier to build and maintain. These techniques allow maximum freedom for system developers to apply their domain expertise to software. We have applied these techniques to several types of applications, including training simulators operating in real time, engineering simulators operating in non-real time, and real-time embedded computer systems. Our modeling techniques result in software that mirrors both the complexity of the application and the domain knowledge requirements. We submit that the proper measure of software complexity reflects neither the number of software component units nor the code count, but the locus of and amount of domain knowledge. As a result of using these techniques, domain knowledge is isolated by fields of engineering expertise and removed from the concern of the software engineer. In this paper, we will describe kinds of domain expertise, describe engineering by domains, and provide relevant examples of software developed for simulator applications using the techniques.
Hierarchical Model for the Analysis of Scattering Data of Complex Materials
Oyedele, Akinola; Mcnutt, Nicholas W.; Rios, Orlando; ...
2016-05-16
Interpreting the results of scattering data for complex materials with a hierarchical structure in which at least one phase is amorphous presents a significant challenge. Often the interpretation relies on the use of large-scale molecular dynamics (MD) simulations, in which a structure is hypothesized and from which a radial distribution function (RDF) can be extracted and directly compared against an experimental RDF. This computationally intensive approach presents a bottleneck in the efficient characterization of the atomic structure of new materials. Here, we propose and demonstrate an approach for a hierarchical decomposition of the RDF in which MD simulations are replacedmore » by a combination of tractable models and theory at the atomic scale and the mesoscale, which when combined yield the RDF. We apply the procedure to a carbon composite, in which graphitic nanocrystallites are distributed in an amorphous domain. We compare the model with the RDF from both MD simulation and neutron scattering data. Ultimately, this procedure is applicable for understanding the fundamental processing-structure-property relationships in complex magnetic materials.« less
A Framework for Simulating Turbine-Based Combined-Cycle Inlet Mode-Transition
NASA Technical Reports Server (NTRS)
Le, Dzu K.; Vrnak, Daniel R.; Slater, John W.; Hessel, Emil O.
2012-01-01
A simulation framework based on the Memory-Mapped-Files technique was created to operate multiple numerical processes in locked time-steps and send I/O data synchronously across to one-another to simulate system-dynamics. This simulation scheme is currently used to study the complex interactions between inlet flow-dynamics, variable-geometry actuation mechanisms, and flow-controls in the transition from the supersonic to hypersonic conditions and vice-versa. A study of Mode-Transition Control for a high-speed inlet wind-tunnel model with this MMF-based framework is presented to illustrate this scheme and demonstrate its usefulness in simulating supersonic and hypersonic inlet dynamics and controls or other types of complex systems.
Unified Approach to Modeling and Simulation of Space Communication Networks and Systems
NASA Technical Reports Server (NTRS)
Barritt, Brian; Bhasin, Kul; Eddy, Wesley; Matthews, Seth
2010-01-01
Network simulator software tools are often used to model the behaviors and interactions of applications, protocols, packets, and data links in terrestrial communication networks. Other software tools that model the physics, orbital dynamics, and RF characteristics of space systems have matured to allow for rapid, detailed analysis of space communication links. However, the absence of a unified toolset that integrates the two modeling approaches has encumbered the systems engineers tasked with the design, architecture, and analysis of complex space communication networks and systems. This paper presents the unified approach and describes the motivation, challenges, and our solution - the customization of the network simulator to integrate with astronautical analysis software tools for high-fidelity end-to-end simulation. Keywords space; communication; systems; networking; simulation; modeling; QualNet; STK; integration; space networks
Technical Note: Approximate Bayesian parameterization of a complex tropical forest model
NASA Astrophysics Data System (ADS)
Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.
2013-08-01
Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.
Pope, Bernard J; Fitch, Blake G; Pitman, Michael C; Rice, John J; Reumann, Matthias
2011-01-01
Future multiscale and multiphysics models must use the power of high performance computing (HPC) systems to enable research into human disease, translational medical science, and treatment. Previously we showed that computationally efficient multiscale models will require the use of sophisticated hybrid programming models, mixing distributed message passing processes (e.g. the message passing interface (MPI)) with multithreading (e.g. OpenMP, POSIX pthreads). The objective of this work is to compare the performance of such hybrid programming models when applied to the simulation of a lightweight multiscale cardiac model. Our results show that the hybrid models do not perform favourably when compared to an implementation using only MPI which is in contrast to our results using complex physiological models. Thus, with regards to lightweight multiscale cardiac models, the user may not need to increase programming complexity by using a hybrid programming approach. However, considering that model complexity will increase as well as the HPC system size in both node count and number of cores per node, it is still foreseeable that we will achieve faster than real time multiscale cardiac simulations on these systems using hybrid programming models.
STEPS: efficient simulation of stochastic reaction-diffusion models in realistic morphologies.
Hepburn, Iain; Chen, Weiliang; Wils, Stefan; De Schutter, Erik
2012-05-10
Models of cellular molecular systems are built from components such as biochemical reactions (including interactions between ligands and membrane-bound proteins), conformational changes and active and passive transport. A discrete, stochastic description of the kinetics is often essential to capture the behavior of the system accurately. Where spatial effects play a prominent role the complex morphology of cells may have to be represented, along with aspects such as chemical localization and diffusion. This high level of detail makes efficiency a particularly important consideration for software that is designed to simulate such systems. We describe STEPS, a stochastic reaction-diffusion simulator developed with an emphasis on simulating biochemical signaling pathways accurately and efficiently. STEPS supports all the above-mentioned features, and well-validated support for SBML allows many existing biochemical models to be imported reliably. Complex boundaries can be represented accurately in externally generated 3D tetrahedral meshes imported by STEPS. The powerful Python interface facilitates model construction and simulation control. STEPS implements the composition and rejection method, a variation of the Gillespie SSA, supporting diffusion between tetrahedral elements within an efficient search and update engine. Additional support for well-mixed conditions and for deterministic model solution is implemented. Solver accuracy is confirmed with an original and extensive validation set consisting of isolated reaction, diffusion and reaction-diffusion systems. Accuracy imposes upper and lower limits on tetrahedron sizes, which are described in detail. By comparing to Smoldyn, we show how the voxel-based approach in STEPS is often faster than particle-based methods, with increasing advantage in larger systems, and by comparing to MesoRD we show the efficiency of the STEPS implementation. STEPS simulates models of cellular reaction-diffusion systems with complex boundaries with high accuracy and high performance in C/C++, controlled by a powerful and user-friendly Python interface. STEPS is free for use and is available at http://steps.sourceforge.net/
STEPS: efficient simulation of stochastic reaction–diffusion models in realistic morphologies
2012-01-01
Background Models of cellular molecular systems are built from components such as biochemical reactions (including interactions between ligands and membrane-bound proteins), conformational changes and active and passive transport. A discrete, stochastic description of the kinetics is often essential to capture the behavior of the system accurately. Where spatial effects play a prominent role the complex morphology of cells may have to be represented, along with aspects such as chemical localization and diffusion. This high level of detail makes efficiency a particularly important consideration for software that is designed to simulate such systems. Results We describe STEPS, a stochastic reaction–diffusion simulator developed with an emphasis on simulating biochemical signaling pathways accurately and efficiently. STEPS supports all the above-mentioned features, and well-validated support for SBML allows many existing biochemical models to be imported reliably. Complex boundaries can be represented accurately in externally generated 3D tetrahedral meshes imported by STEPS. The powerful Python interface facilitates model construction and simulation control. STEPS implements the composition and rejection method, a variation of the Gillespie SSA, supporting diffusion between tetrahedral elements within an efficient search and update engine. Additional support for well-mixed conditions and for deterministic model solution is implemented. Solver accuracy is confirmed with an original and extensive validation set consisting of isolated reaction, diffusion and reaction–diffusion systems. Accuracy imposes upper and lower limits on tetrahedron sizes, which are described in detail. By comparing to Smoldyn, we show how the voxel-based approach in STEPS is often faster than particle-based methods, with increasing advantage in larger systems, and by comparing to MesoRD we show the efficiency of the STEPS implementation. Conclusion STEPS simulates models of cellular reaction–diffusion systems with complex boundaries with high accuracy and high performance in C/C++, controlled by a powerful and user-friendly Python interface. STEPS is free for use and is available at http://steps.sourceforge.net/ PMID:22574658
NASA Astrophysics Data System (ADS)
Schilling, Oleg
2016-11-01
Two-, three- and four-equation, single-velocity, multicomponent Reynolds-averaged Navier-Stokes (RANS) models, based on the turbulent kinetic energy dissipation rate or lengthscale, are used to simulate At = 0 . 5 Rayleigh-Taylor turbulent mixing with constant and complex accelerations. The constant acceleration case is inspired by the Cabot and Cook (2006) DNS, and the complex acceleration cases are inspired by the unstable/stable and unstable/neutral cases simulated using DNS (Livescu, Wei & Petersen 2011) and the unstable/stable/unstable case simulated using ILES (Ramaprabhu, Karkhanis & Lawrie 2013). The four-equation models couple equations for the mass flux a and negative density-specific volume correlation b to the K- ɛ or K- L equations, while the three-equation models use a two-fluid algebraic closure for b. The lengthscale-based models are also applied with no buoyancy production in the L equation to explore the consequences of neglecting this term. Predicted mixing widths, turbulence statistics, fields, and turbulent transport equation budgets are compared among these models to identify similarities and differences in the turbulence production, dissipation and diffusion physics represented by the closures used in these models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Organization and Dynamics of Receptor Proteins in a Plasma Membrane.
Koldsø, Heidi; Sansom, Mark S P
2015-11-25
The interactions of membrane proteins are influenced by their lipid environment, with key lipid species able to regulate membrane protein function. Advances in high-resolution microscopy can reveal the organization and dynamics of proteins and lipids within living cells at resolutions <200 nm. Parallel advances in molecular simulations provide near-atomic-resolution models of the dynamics of the organization of membranes of in vivo-like complexity. We explore the dynamics of proteins and lipids in crowded and complex plasma membrane models, thereby closing the gap in length and complexity between computations and experiments. Our simulations provide insights into the mutual interplay between lipids and proteins in determining mesoscale (20-100 nm) fluctuations of the bilayer, and in enabling oligomerization and clustering of membrane proteins.
Hybrid deterministic/stochastic simulation of complex biochemical systems.
Lecca, Paola; Bagagiolo, Fabio; Scarpa, Marina
2017-11-21
In a biological cell, cellular functions and the genetic regulatory apparatus are implemented and controlled by complex networks of chemical reactions involving genes, proteins, and enzymes. Accurate computational models are indispensable means for understanding the mechanisms behind the evolution of a complex system, not always explored with wet lab experiments. To serve their purpose, computational models, however, should be able to describe and simulate the complexity of a biological system in many of its aspects. Moreover, it should be implemented by efficient algorithms requiring the shortest possible execution time, to avoid enlarging excessively the time elapsing between data analysis and any subsequent experiment. Besides the features of their topological structure, the complexity of biological networks also refers to their dynamics, that is often non-linear and stiff. The stiffness is due to the presence of molecular species whose abundance fluctuates by many orders of magnitude. A fully stochastic simulation of a stiff system is computationally time-expensive. On the other hand, continuous models are less costly, but they fail to capture the stochastic behaviour of small populations of molecular species. We introduce a new efficient hybrid stochastic-deterministic computational model and the software tool MoBioS (MOlecular Biology Simulator) implementing it. The mathematical model of MoBioS uses continuous differential equations to describe the deterministic reactions and a Gillespie-like algorithm to describe the stochastic ones. Unlike the majority of current hybrid methods, the MoBioS algorithm divides the reactions' set into fast reactions, moderate reactions, and slow reactions and implements a hysteresis switching between the stochastic model and the deterministic model. Fast reactions are approximated as continuous-deterministic processes and modelled by deterministic rate equations. Moderate reactions are those whose reaction waiting time is greater than the fast reaction waiting time but smaller than the slow reaction waiting time. A moderate reaction is approximated as a stochastic (deterministic) process if it was classified as a stochastic (deterministic) process at the time at which it crosses the threshold of low (high) waiting time. A Gillespie First Reaction Method is implemented to select and execute the slow reactions. The performances of MoBios were tested on a typical example of hybrid dynamics: that is the DNA transcription regulation. The simulated dynamic profile of the reagents' abundance and the estimate of the error introduced by the fully deterministic approach were used to evaluate the consistency of the computational model and that of the software tool.
Simulating the evolution of glyphosate resistance in grains farming in northern Australia.
Thornby, David F; Walker, Steve R
2009-09-01
The evolution of resistance to herbicides is a substantial problem in contemporary agriculture. Solutions to this problem generally consist of the use of practices to control the resistant population once it evolves, and/or to institute preventative measures before populations become resistant. Herbicide resistance evolves in populations over years or decades, so predicting the effectiveness of preventative strategies in particular relies on computational modelling approaches. While models of herbicide resistance already exist, none deals with the complex regional variability in the northern Australian sub-tropical grains farming region. For this reason, a new computer model was developed. The model consists of an age- and stage-structured population model of weeds, with an existing crop model used to simulate plant growth and competition, and extensions to the crop model added to simulate seed bank ecology and population genetics factors. Using awnless barnyard grass (Echinochloa colona) as a test case, the model was used to investigate the likely rate of evolution under conditions expected to produce high selection pressure. Simulating continuous summer fallows with glyphosate used as the only means of weed control resulted in predicted resistant weed populations after approx. 15 years. Validation of the model against the paddock history for the first real-world glyphosate-resistant awnless barnyard grass population shows that the model predicted resistance evolution to within a few years of the real situation. This validation work shows that empirical validation of herbicide resistance models is problematic. However, the model simulates the complexities of sub-tropical grains farming in Australia well, and can be used to investigate, generate and improve glyphosate resistance prevention strategies.
Yu, Hesheng; Thé, Jesse
2017-05-01
The dispersion of gaseous pollutant around buildings is complex due to complex turbulence features such as flow detachment and zones of high shear. Computational fluid dynamics (CFD) models are one of the most promising tools to describe the pollutant distribution in the near field of buildings. Reynolds-averaged Navier-Stokes (RANS) models are the most commonly used CFD techniques to address turbulence transport of the pollutant. This research work studies the use of [Formula: see text] closure model for the gas dispersion around a building by fully resolving the viscous sublayer for the first time. The performance of standard [Formula: see text] model is also included for comparison, along with results of an extensively validated Gaussian dispersion model, the U.S. Environmental Protection Agency (EPA) AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model). This study's CFD models apply the standard [Formula: see text] and the [Formula: see text] turbulence models to obtain wind flow field. A passive concentration transport equation is then calculated based on the resolved flow field to simulate the distribution of pollutant concentrations. The resultant simulation of both wind flow and concentration fields are validated rigorously by extensive data using multiple validation metrics. The wind flow field can be acceptably modeled by the [Formula: see text] model. However, the [Formula: see text] model fails to simulate the gas dispersion. The [Formula: see text] model outperforms [Formula: see text] in both flow and dispersion simulations, with higher hit rates for dimensionless velocity components and higher "factor of 2" of observations (FAC2) for normalized concentration. All these validation metrics of [Formula: see text] model pass the quality assurance criteria recommended by The Association of German Engineers (Verein Deutscher Ingenieure, VDI) guideline. Furthermore, these metrics are better than or the same as those in the literature. Comparison between the performances of [Formula: see text] and AERMOD shows that the CFD simulation is superior to Gaussian-type model for pollutant dispersion in the near wake of obstacles. AERMOD can perform as a screening tool for near-field gas dispersion due to its expeditious calculation and the ability to handle complicated cases. The utilization of [Formula: see text] to simulate gaseous pollutant dispersion around an isolated building is appropriate and is expected to be suitable for complex urban environment. Multiple validation metrics of [Formula: see text] turbulence model in CFD quantitatively indicated that this turbulence model was appropriate for the simulation of gas dispersion around buildings. CFD is, therefore, an attractive alternative to wind tunnel for modeling gas dispersion in urban environment due to its excellent performance, and lower cost.
NASA Astrophysics Data System (ADS)
Amezquita-Brooks, Luis; Liceaga-Castro, Eduardo; Gonzalez-Sanchez, Mario; Garcia-Salazar, Octavio; Martinez-Vazquez, Daniel
2017-11-01
Applications based on quad-rotor-vehicles (QRV) are becoming increasingly wide-spread. Many of these applications require accurate mathematical representations for control design, simulation and estimation. However, there is no consensus on a standardized model for these purposes. In this article a review of the most common elements included in QRV models reported in the literature is presented. This survey shows that some elements are recurrent for typical non-aerobatic QRV applications; in particular, for control design and high-performance simulation. By synthesising the common features of the reviewed models a standard generic model SGM is proposed. The SGM is cast as a typical state-space model without memory-less transformations, a structure which is useful for simulation and controller design. The survey also shows that many QRV applications use simplified representations, which may be considered simplifications of the SGM here proposed. In order to assess the effectiveness of the simplified models, a comprehensive comparison based on digital simulations is presented. With this comparison, it is possible to determine the accuracy of each model under particular operating ranges. Such information is useful for the selection of a model according to a particular application. In addition to the models found in the literature, in this article a novel simplified model is derived. The main characteristics of this model are that its inner dynamics are linear, it has low complexity and it has a high level of accuracy in all the studied operating ranges, a characteristic found only in more complex representations. To complement the article the main elements of the SGM are evaluated with the aid of experimental data and the computational complexity of all surveyed models is briefly analysed. Finally, the article presents a discussion on how the structural characteristics of the models are useful to suggest particular QRV control structures.
Calibration of 3D ALE finite element model from experiments on friction stir welding of lap joints
NASA Astrophysics Data System (ADS)
Fourment, Lionel; Gastebois, Sabrina; Dubourg, Laurent
2016-10-01
In order to support the design of such a complex process like Friction Stir Welding (FSW) for the aeronautic industry, numerical simulation software requires (1) developing an efficient and accurate Finite Element (F.E.) formulation that allows predicting welding defects, (2) properly modeling the thermo-mechanical complexity of the FSW process and (3) calibrating the F.E. model from accurate measurements from FSW experiments. This work uses a parallel ALE formulation developed in the Forge® F.E. code to model the different possible defects (flashes and worm holes), while pin and shoulder threads are modeled by a new friction law at the tool / material interface. FSW experiments require using a complex tool with scroll on shoulder, which is instrumented for providing sensitive thermal data close to the joint. Calibration of unknown material thermal coefficients, constitutive equations parameters and friction model from measured forces, torques and temperatures is carried out using two F.E. models, Eulerian and ALE, to reach a satisfactory agreement assessed by the proper sensitivity of the simulation to process parameters.
Constitutive Modelling of Resins in the Stiffness Domain
NASA Astrophysics Data System (ADS)
Klasztorny, M.
2004-09-01
An analytic method for inverting the constitutive compliance equations of viscoelasticity for resins is developed. These equations describe the HWKK/H rheological model, which makes it possible to simulate, with a good accuracy, short-, medium- and long-term viscoelastic processes in epoxy and polyester resins. These processes are of first-rank reversible isothermal type. The time histories of deviatoric stresses are simulated with three independent strain history functions of fractional and normal exponential types. The stiffness equations are described by two elastic and six viscoelastic constants having a clear physic meaning (three long-term relaxation coefficients and three relaxation times). The time histories of axiatoric stresses are simulated as perfectly elastic. The inversion method utilizes approximate constitutive stiffness equations of viscoelasticity for the HWKK/H model. The constitutive compliance equations for the model are a basis for determining the exact complex shear stiffness, whereas the approximate constitutive stiffness equations are used for determining the approximate complex shear stiffness. The viscoelastic constants in the stiffness domain are derived by equating the exact and approximate complex shear stiffnesses. The viscoelastic constants are obtained for Epidian 53 epoxy and Polimal 109 polyester resins. The accuracy of the approximate constitutive stiffness equations are assessed by comparing the approximate and exact complex shear stiffnesses. The constitutive stiffness equations for the HWKK/H model are presented in uncoupled (shear/bulk) and coupled forms. Formulae for converting the constants of shear viscoelasticity into the constants of coupled viscoelasticity are given as well.
Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods
Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.
2016-09-01
Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less
Understanding GPU Power. A Survey of Profiling, Modeling, and Simulation Methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bridges, Robert A.; Imam, Neena; Mintz, Tiffany M.
Modern graphics processing units (GPUs) have complex architectures that admit exceptional performance and energy efficiency for high throughput applications.Though GPUs consume large amounts of power, their use for high throughput applications facilitate state-of-the-art energy efficiency and performance. Consequently, continued development relies on understanding their power consumption. Our work is a survey of GPU power modeling and profiling methods with increased detail on noteworthy efforts. Moreover, as direct measurement of GPU power is necessary for model evaluation and parameter initiation, internal and external power sensors are discussed. Hardware counters, which are low-level tallies of hardware events, share strong correlation to powermore » use and performance. Statistical correlation between power and performance counters has yielded worthwhile GPU power models, yet the complexity inherent to GPU architectures presents new hurdles for power modeling. Developments and challenges of counter-based GPU power modeling is discussed. Often building on the counter-based models, research efforts for GPU power simulation, which make power predictions from input code and hardware knowledge, provide opportunities for optimization in programming or architectural design. Noteworthy strides in power simulations for GPUs are included along with their performance or functional simulator counterparts when appropriate. Lastly, possible directions for future research are discussed.« less
2017-06-01
Chemical Transformation Simulator (CTS) was developed by the U.S. Environmental Protection Agency to provide physicochemical properties of complex...Site Model CTS Chemical Transformation Simulator developed by EPA D4EM Data for Environmental Modeling Demo Demolition area DNAN 2,4...U.S. Environmental Protection Agency (EPA), was the technical point-of-contact for the Contaminant Transformation Simulator (CTS) that was
Detached-Eddy Simulations of Attached and Detached Boundary Layers
NASA Astrophysics Data System (ADS)
Caruelle, B.; Ducros, F.
2003-12-01
This article presents Detached-Eddy Simulations (DESs) of attached and detached turbulent boundary layers. This hybrid Reynolds Averaged Navier-Stokes (RANS) / Large Eddy Simulation (LES) model goes continuously from RANS to LES according to the mesh definition. We propose a parametric study of the model over two "academic" configurations, in order to get information on the influence of the mesh to correctly treat complex flow with attached and detached boundary layers.
Modeling Interfacial Glass-Water Reactions: Recent Advances and Current Limitations
Pierce, Eric M.; Frugier, Pierre; Criscenti, Louise J.; ...
2014-07-12
Describing the reactions that occur at the glass-water interface and control the development of the altered layer constitutes one of the main scientific challenges impeding existing models from providing accurate radionuclide release estimates. Radionuclide release estimates are a critical component of the safety basis for geologic repositories. The altered layer (i.e., amorphous hydrated surface layer and crystalline reaction products) represents a complex region, both physically and chemically, sandwiched between two distinct boundaries pristine glass surface at the inner most interface and aqueous solution at the outer most interface. Computational models, spanning different length and time-scales, are currently being developed tomore » improve our understanding of this complex and dynamic process with the goal of accurately describing the pore-scale changes that occur as the system evolves. These modeling approaches include geochemical simulations [i.e., classical reaction path simulations and glass reactivity in allowance for alteration layer (GRAAL) simulations], Monte Carlo simulations, and Molecular Dynamics methods. Finally, in this manuscript, we discuss the advances and limitations of each modeling approach placed in the context of the glass-water reaction and how collectively these approaches provide insights into the mechanisms that control the formation and evolution of altered layers.« less
Passananti, Monica; Vinatier, Virginie; Delort, Anne-Marie; Mailhot, Gilles; Brigante, Marcello
2016-09-06
In the present work, the photoreactivity of a mixture of iron(III)–pyoverdin (Fe(III)–Pyo) complexes was investigated under simulated cloud conditions. Pyoverdins are expected to complex ferric ions naturally present in cloudwater, thus modifying their availability and photoreactivity. The spectroscopic properties and photoreactivity of Fe(III)-Pyo were investigated, with particular attention to their fate under solar irradiation, also studied through simulations. The photolysis of the Fe(III)–Pyo complex leads to the generation of Fe(II), with rates of formation (RFe(II)f) of 6.98 and 3.96 × 10–9 M s–1 at pH 4.0 and 6.0, respectively. Interestingly, acetate formation was observed during the iron-complex photolysis, suggesting that fragmentation can occur after the ligand-to-metal charge transfer (LMCT) via a complex reaction mechanism. Moreover, photogenerated Fe(II) represent an important source of hydroxyl radical via the Fenton reaction in cloudwater. This reactivity might be relevant for the estimation of the rates of formation and steady-state concentrations of the hydroxyl radical by cloud chemistry models and for organic matter speciation in the cloud aqueous phase. In fact, the conventional models, which describe the iron photoreactivity in terms of iron–aqua and oxalate complexes, are not in accordance with our results.
Simulation of anaerobic digestion processes using stochastic algorithm.
Palanichamy, Jegathambal; Palani, Sundarambal
2014-01-01
The Anaerobic Digestion (AD) processes involve numerous complex biological and chemical reactions occurring simultaneously. Appropriate and efficient models are to be developed for simulation of anaerobic digestion systems. Although several models have been developed, mostly they suffer from lack of knowledge on constants, complexity and weak generalization. The basis of the deterministic approach for modelling the physico and bio-chemical reactions occurring in the AD system is the law of mass action, which gives the simple relationship between the reaction rates and the species concentrations. The assumptions made in the deterministic models are not hold true for the reactions involving chemical species of low concentration. The stochastic behaviour of the physicochemical processes can be modeled at mesoscopic level by application of the stochastic algorithms. In this paper a stochastic algorithm (Gillespie Tau Leap Method) developed in MATLAB was applied to predict the concentration of glucose, acids and methane formation at different time intervals. By this the performance of the digester system can be controlled. The processes given by ADM1 (Anaerobic Digestion Model 1) were taken for verification of the model. The proposed model was verified by comparing the results of Gillespie's algorithms with the deterministic solution for conversion of glucose into methane through degraders. At higher value of 'τ' (timestep), the computational time required for reaching the steady state is more since the number of chosen reactions is less. When the simulation time step is reduced, the results are similar to ODE solver. It was concluded that the stochastic algorithm is a suitable approach for the simulation of complex anaerobic digestion processes. The accuracy of the results depends on the optimum selection of tau value.
Handling Uncertainty in Palaeo-Climate Models and Data
NASA Astrophysics Data System (ADS)
Voss, J.; Haywood, A. M.; Dolan, A. M.; Domingo, D.
2017-12-01
The study of palaeoclimates can provide data on the behaviour of the Earth system with boundary conditions different from the ones we observe in the present. One of the main challenges in this approach is that data on past climates comes with large uncertainties, since quantities of interest cannot be observed directly, but must be derived from proxies instead. We consider proxy-derived data from the Pliocene (around 3 millions years ago; the last interval in Earth history when CO2 was at modern or near future levels) and contrast this data to the output of complex climate models. In order to perform a meaningful data-model comparison, uncertainties must be taken into account. In this context, we discuss two examples of complex data-model comparison problems. Both examples have in common that they involve fitting a statistical model to describe how the output of the climate simulations depends on various model parameters, including atmospheric CO2 concentration and orbital parameters (obliquity, excentricity, and precession). This introduces additional uncertainties, but allows to explore a much larger range of model parameters than would be feasible by only relying on simulation runs. The first example shows how Gaussian process emulators can be used to perform data-model comparison when simulation runs only differ in the choice of orbital parameters, but temperature data is given in the (somewhat inconvenient) form of "warm peak averages". The second example shows how a simpler approach, based on linear regression, can be used to analyse a more complex problem where we use a larger and more varied ensemble of climate simulations with the aim to estimate Earth System Sensitivity.
Characterizing bias correction uncertainty in wheat yield predictions
NASA Astrophysics Data System (ADS)
Ortiz, Andrea Monica; Jones, Julie; Freckleton, Robert; Scaife, Adam
2017-04-01
Farming systems are under increased pressure due to current and future climate change, variability and extremes. Research on the impacts of climate change on crop production typically rely on the output of complex Global and Regional Climate Models, which are used as input to crop impact models. Yield predictions from these top-down approaches can have high uncertainty for several reasons, including diverse model construction and parameterization, future emissions scenarios, and inherent or response uncertainty. These uncertainties propagate down each step of the 'cascade of uncertainty' that flows from climate input to impact predictions, leading to yield predictions that may be too complex for their intended use in practical adaptation options. In addition to uncertainty from impact models, uncertainty can also stem from the intermediate steps that are used in impact studies to adjust climate model simulations to become more realistic when compared to observations, or to correct the spatial or temporal resolution of climate simulations, which are often not directly applicable as input into impact models. These important steps of bias correction or calibration also add uncertainty to final yield predictions, given the various approaches that exist to correct climate model simulations. In order to address how much uncertainty the choice of bias correction method can add to yield predictions, we use several evaluation runs from Regional Climate Models from the Coordinated Regional Downscaling Experiment over Europe (EURO-CORDEX) at different resolutions together with different bias correction methods (linear and variance scaling, power transformation, quantile-quantile mapping) as input to a statistical crop model for wheat, a staple European food crop. The objective of our work is to compare the resulting simulation-driven hindcasted wheat yields to climate observation-driven wheat yield hindcasts from the UK and Germany in order to determine ranges of yield uncertainty that result from different climate model simulation input and bias correction methods. We simulate wheat yields using a General Linear Model that includes the effects of seasonal maximum temperatures and precipitation, since wheat is sensitive to heat stress during important developmental stages. We use the same statistical model to predict future wheat yields using the recently available bias-corrected simulations of EURO-CORDEX-Adjust. While statistical models are often criticized for their lack of complexity, an advantage is that we are here able to consider only the effect of the choice of climate model, resolution or bias correction method on yield. Initial results using both past and future bias-corrected climate simulations with a process-based model will also be presented. Through these methods, we make recommendations in preparing climate model output for crop models.
Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla
2016-11-01
Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.
Models and Simulations as a Service: Exploring the Use of Galaxy for Delivering Computational Models
Walker, Mark A.; Madduri, Ravi; Rodriguez, Alex; Greenstein, Joseph L.; Winslow, Raimond L.
2016-01-01
We describe the ways in which Galaxy, a web-based reproducible research platform, can be used for web-based sharing of complex computational models. Galaxy allows users to seamlessly customize and run simulations on cloud computing resources, a concept we refer to as Models and Simulations as a Service (MaSS). To illustrate this application of Galaxy, we have developed a tool suite for simulating a high spatial-resolution model of the cardiac Ca2+ spark that requires supercomputing resources for execution. We also present tools for simulating models encoded in the SBML and CellML model description languages, thus demonstrating how Galaxy’s reproducible research features can be leveraged by existing technologies. Finally, we demonstrate how the Galaxy workflow editor can be used to compose integrative models from constituent submodules. This work represents an important novel approach, to our knowledge, to making computational simulations more accessible to the broader scientific community. PMID:26958881
An example of complex modelling in dentistry using Markov chain Monte Carlo (MCMC) simulation.
Helfenstein, Ulrich; Menghini, Giorgio; Steiner, Marcel; Murati, Francesca
2002-09-01
In the usual regression setting one regression line is computed for a whole data set. In a more complex situation, each person may be observed for example at several points in time and thus a regression line might be calculated for each person. Additional complexities, such as various forms of errors in covariables may make a straightforward statistical evaluation difficult or even impossible. During recent years methods have been developed allowing convenient analysis of problems where the data and the corresponding models show these and many other forms of complexity. The methodology makes use of a Bayesian approach and Markov chain Monte Carlo (MCMC) simulations. The methods allow the construction of increasingly elaborate models by building them up from local sub-models. The essential structure of the models can be represented visually by directed acyclic graphs (DAG). This attractive property allows communication and discussion of the essential structure and the substantial meaning of a complex model without needing algebra. After presentation of the statistical methods an example from dentistry is presented in order to demonstrate their application and use. The dataset of the example had a complex structure; each of a set of children was followed up over several years. The number of new fillings in permanent teeth had been recorded at several ages. The dependent variables were markedly different from the normal distribution and could not be transformed to normality. In addition, explanatory variables were assumed to be measured with different forms of error. Illustration of how the corresponding models can be estimated conveniently via MCMC simulation, in particular, 'Gibbs sampling', using the freely available software BUGS is presented. In addition, how the measurement error may influence the estimates of the corresponding coefficients is explored. It is demonstrated that the effect of the independent variable on the dependent variable may be markedly underestimated if the measurement error is not taken into account ('regression dilution bias'). Markov chain Monte Carlo methods may be of great value to dentists in allowing analysis of data sets which exhibit a wide range of different forms of complexity.
A simulation framework for the CMS Track Trigger electronics
NASA Astrophysics Data System (ADS)
Amstutz, C.; Magazzù, G.; Weber, M.; Palla, F.
2015-03-01
A simulation framework has been developed to test and characterize algorithms, architectures and hardware implementations of the vastly complex CMS Track Trigger for the high luminosity upgrade of the CMS experiment at the Large Hadron Collider in Geneva. High-level SystemC models of all system components have been developed to simulate a portion of the track trigger. The simulation of the system components together with input data from physics simulations allows evaluating figures of merit, like delays or bandwidths, under realistic conditions. The use of SystemC for high-level modelling allows co-simulation with models developed in Hardware Description Languages, e.g. VHDL or Verilog. Therefore, the simulation framework can also be used as a test bench for digital modules developed for the final system.
Evaluation of unsaturated-zone solute-transport models for studies of agricultural chemicals
Nolan, Bernard T.; Bayless, E. Randall; Green, Christopher T.; Garg, Sheena; Voss, Frank D.; Lampe, David C.; Barbash, Jack E.; Capel, Paul D.; Bekins, Barbara A.
2005-01-01
Of the models tested, RZWQM, HYDRUS2D, VS2DT, GLEAMS and PRZM had graphical user interfaces. Extensive documentation was available for RZWQM, HYDRUS2D, and VS2DT. RZWQM can explicitly simulate water and solute flux in macropores, and both HYDRUS2D and VS2DT can simulate water and solute flux in two dimensions. The version of RZWQM tested had a maximum simulation depth of 3 meters. The complex models simulate the formation, transport, and fate of degradates of up to three to five compounds including the parent, with the exception of VS2DT, which simulates the transport and fate of a single compound.
Saeedi, Mostafa; Vahidi, Omid; Goodarzi, Vahabodin; Saeb, Mohammad Reza; Izadi, Leila; Mozafari, Masoud
2017-11-01
Distribution patterns/performance of magnetic nanoparticles (MNPs) was visualized by computer simulation and experimental validation on agarose gel tissue-mimicking phantom (AGTMP) models. The geometry of a complex three-dimensional mathematical phantom model of a cancer tumor was examined by tomography imaging. The capability of mathematical model to predict distribution patterns/performance in AGTMP model was captured. The temperature profile vs. hyperthermia duration was obtained by solving bio-heat equations for four different MNPs distribution patterns and correlated with cell death rate. The outcomes indicated that bio-heat model was able to predict temperature profile throughout the tissue model with a reasonable precision, to be applied for complex tissue geometries. The simulation results on the cancer tumor model shed light on the effectiveness of the studied parameters. Copyright © 2017 Elsevier Inc. All rights reserved.
Quasi steady-state aerodynamic model development for race vehicle simulations
NASA Astrophysics Data System (ADS)
Mohrfeld-Halterman, J. A.; Uddin, M.
2016-01-01
Presented in this paper is a procedure to develop a high fidelity quasi steady-state aerodynamic model for use in race car vehicle dynamic simulations. Developed to fit quasi steady-state wind tunnel data, the aerodynamic model is regressed against three independent variables: front ground clearance, rear ride height, and yaw angle. An initial dual range model is presented and then further refined to reduce the model complexity while maintaining a high level of predictive accuracy. The model complexity reduction decreases the required amount of wind tunnel data thereby reducing wind tunnel testing time and cost. The quasi steady-state aerodynamic model for the pitch moment degree of freedom is systematically developed in this paper. This same procedure can be extended to the other five aerodynamic degrees of freedom to develop a complete six degree of freedom quasi steady-state aerodynamic model for any vehicle.
System-level simulation of liquid filling in microfluidic chips.
Song, Hongjun; Wang, Yi; Pant, Kapil
2011-06-01
Liquid filling in microfluidic channels is a complex process that depends on a variety of geometric, operating, and material parameters such as microchannel geometry, flow velocity∕pressure, liquid surface tension, and contact angle of channel surface. Accurate analysis of the filling process can provide key insights into the filling time, air bubble trapping, and dead zone formation, and help evaluate trade-offs among the various design parameters and lead to optimal chip design. However, efficient modeling of liquid filling in complex microfluidic networks continues to be a significant challenge. High-fidelity computational methods, such as the volume of fluid method, are prohibitively expensive from a computational standpoint. Analytical models, on the other hand, are primarily applicable to idealized geometries and, hence, are unable to accurately capture chip level behavior of complex microfluidic systems. This paper presents a parametrized dynamic model for the system-level analysis of liquid filling in three-dimensional (3D) microfluidic networks. In our approach, a complex microfluidic network is deconstructed into a set of commonly used components, such as reservoirs, microchannels, and junctions. The components are then assembled according to their spatial layout and operating rationale to achieve a rapid system-level model. A dynamic model based on the transient momentum equation is developed to track the liquid front in the microchannels. The principle of mass conservation at the junction is used to link the fluidic parameters in the microchannels emanating from the junction. Assembly of these component models yields a set of differential and algebraic equations, which upon integration provides temporal information of the liquid filling process, particularly liquid front propagation (i.e., the arrival time). The models are used to simulate the transient liquid filling process in a variety of microfluidic constructs and in a multiplexer, representing a complex microfluidic network. The accuracy (relative error less than 7%) and orders-of-magnitude speedup (30 000X-4 000 000X) of our system-level models are verified by comparison against 3D high-fidelity numerical studies. Our findings clearly establish the utility of our models and simulation methodology for fast, reliable analysis of liquid filling to guide the design optimization of complex microfluidic networks.
Linear-algebraic bath transformation for simulating complex open quantum systems
Huh, Joonsuk; Mostame, Sarah; Fujita, Takatoshi; ...
2014-12-02
In studying open quantum systems, the environment is often approximated as a collection of non-interacting harmonic oscillators, a configuration also known as the star-bath model. It is also well known that the star-bath can be transformed into a nearest-neighbor interacting chain of oscillators. The chain-bath model has been widely used in renormalization group approaches. The transformation can be obtained by recursion relations or orthogonal polynomials. Based on a simple linear algebraic approach, we propose a bath partition strategy to reduce the system-bath coupling strength. As a result, the non-interacting star-bath is transformed into a set of weakly coupled multiple parallelmore » chains. Furthermore, the transformed bath model allows complex problems to be practically implemented on quantum simulators, and it can also be employed in various numerical simulations of open quantum dynamics.« less
Hydrological model parameter dimensionality is a weak measure of prediction uncertainty
NASA Astrophysics Data System (ADS)
Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.
2015-04-01
This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-04-05
... (CDRH) believes that computer modeling and simulation (M&S) has the potential to substantially augment... simulate multiple use conditions and to visualize and display complex processes and data can revolutionize...
Miller, Brian W.; Morisette, Jeffrey T.
2014-01-01
Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution models provide data-driven estimates of the future distributions of species of interest, but they face several limitations and their output alone is not sufficient to guide complex decisions for how best to manage resources given social and economic considerations along with dynamic and uncertain future conditions. Researchers and managers are increasingly exploring potential futures of social-ecological systems through scenario planning, but this process often lacks quantitative response modeling and validation procedures. Simulation models are well placed to provide added rigor to scenario planning because of their ability to reproduce complex system dynamics, but the scenarios and management options explored in simulations are often not developed by stakeholders, and there is not a clear consensus on how to include climate model outputs. We see these strengths and weaknesses as complementarities and offer an analytical framework for integrating these three tools. We then describe the ways in which this framework can help shift climate change research from useful to usable.
Modeling of the Human - Operator in a Complex System Functioning Under Extreme Conditions
NASA Astrophysics Data System (ADS)
Getzov, Peter; Hubenova, Zoia; Yordanov, Dimitar; Popov, Wiliam
2013-12-01
Problems, related to the explication of sophisticated control systems of objects, operating under extreme conditions, have been examined and the impact of the effectiveness of the operator's activity on the systems as a whole. The necessity of creation of complex simulation models, reflecting operator's activity, is discussed. Organizational and technical system of an unmanned aviation complex is described as a sophisticated ergatic system. Computer realization of main subsystems of algorithmic system of the man as a controlling system is implemented and specialized software for data processing and analysis is developed. An original computer model of a Man as a tracking system has been implemented. Model of unmanned complex for operators training and formation of a mental model in emergency situation, implemented in "matlab-simulink" environment, has been synthesized. As a unit of the control loop, the pilot (operator) is simplified viewed as an autocontrol system consisting of three main interconnected subsystems: sensitive organs (perception sensors); central nervous system; executive organs (muscles of the arms, legs, back). Theoretical-data model of prediction the level of operator's information load in ergatic systems is proposed. It allows the assessment and prediction of the effectiveness of a real working operator. Simulation model of operator's activity in takeoff based on the Petri nets has been synthesized.
Wei, Gaofeng; Tang, Gang; Fu, Zengliang; Sun, Qiuming; Tian, Feng
2010-10-01
The China Mechanical Virtual Human (CMVH) is a human musculoskeletal biomechanical simulation platform based on China Visible Human slice images; it has great realistic application significance. In this paper is introduced the construction method of CMVH 3D models. Then a simulation system solution based on Creator/Vega is put forward for the complex and gigantic data characteristics of the 3D models. At last, combined with MFC technology, the CMVH simulation system is developed and a running simulation scene is given. This paper provides a new way for the virtual reality application of CMVH.
Hierarchical analytical and simulation modelling of human-machine systems with interference
NASA Astrophysics Data System (ADS)
Braginsky, M. Ya; Tarakanov, D. V.; Tsapko, S. G.; Tsapko, I. V.; Baglaeva, E. A.
2017-01-01
The article considers the principles of building the analytical and simulation model of the human operator and the industrial control system hardware and software. E-networks as the extension of Petri nets are used as the mathematical apparatus. This approach allows simulating complex parallel distributed processes in human-machine systems. The structural and hierarchical approach is used as the building method for the mathematical model of the human operator. The upper level of the human operator is represented by the logical dynamic model of decision making based on E-networks. The lower level reflects psychophysiological characteristics of the human-operator.
Harriss-Phillips, W M; Bezak, E; Yeoh, E K
2011-01-01
Objective A temporal Monte Carlo tumour growth and radiotherapy effect model (HYP-RT) simulating hypoxia in head and neck cancer has been developed and used to analyse parameters influencing cell kill during conventionally fractionated radiotherapy. The model was designed to simulate individual cell division up to 108 cells, while incorporating radiobiological effects, including accelerated repopulation and reoxygenation during treatment. Method Reoxygenation of hypoxic tumours has been modelled using randomised increments of oxygen to tumour cells after each treatment fraction. The process of accelerated repopulation has been modelled by increasing the symmetrical stem cell division probability. Both phenomena were onset immediately or after a number of weeks of simulated treatment. Results The extra dose required to control (total cell kill) hypoxic vs oxic tumours was 15–25% (8–20 Gy for 5×2 Gy per week) depending on the timing of accelerated repopulation onset. Reoxygenation of hypoxic tumours resulted in resensitisation and reduction in total dose required by approximately 10%, depending on the time of onset. When modelled simultaneously, accelerated repopulation and reoxygenation affected cell kill in hypoxic tumours in a similar manner to when the phenomena were modelled individually; however, the degree was altered, with non-additive results. Simulation results were in good agreement with standard linear quadratic theory; however, differed for more complex comparisons where hypoxia, reoxygenation as well as accelerated repopulation effects were considered. Conclusion Simulations have quantitatively confirmed the need for patient individualisation in radiotherapy for hypoxic head and neck tumours, and have shown the benefits of modelling complex and dynamic processes using Monte Carlo methods. PMID:21933980
Liang Wei; Marshall John; Jianwei Zhang; Hang Zhou; Robert Powers
2014-01-01
Models can be powerful tools for estimating forest productivity and guiding forest management, but their credibility and complexity are often an issue for forest managers. We parameterized a process-based forest growth model, 3-PG (Physiological Principles Predicting Growth), to simulate growth of ponderosa pine (Pinus ponderosa) plantations in...
Mind the Noise When Identifying Computational Models of Cognition from Brain Activity.
Kolossa, Antonio; Kopp, Bruno
2016-01-01
The aim of this study was to analyze how measurement error affects the validity of modeling studies in computational neuroscience. A synthetic validity test was created using simulated P300 event-related potentials as an example. The model space comprised four computational models of single-trial P300 amplitude fluctuations which differed in terms of complexity and dependency. The single-trial fluctuation of simulated P300 amplitudes was computed on the basis of one of the models, at various levels of measurement error and at various numbers of data points. Bayesian model selection was performed based on exceedance probabilities. At very low numbers of data points, the least complex model generally outperformed the data-generating model. Invalid model identification also occurred at low levels of data quality and under low numbers of data points if the winning model's predictors were closely correlated with the predictors from the data-generating model. Given sufficient data quality and numbers of data points, the data-generating model could be correctly identified, even against models which were very similar to the data-generating model. Thus, a number of variables affects the validity of computational modeling studies, and data quality and numbers of data points are among the main factors relevant to the issue. Further, the nature of the model space (i.e., model complexity, model dependency) should not be neglected. This study provided quantitative results which show the importance of ensuring the validity of computational modeling via adequately prepared studies. The accomplishment of synthetic validity tests is recommended for future applications. Beyond that, we propose to render the demonstration of sufficient validity via adequate simulations mandatory to computational modeling studies.
Coarse-grained simulations of protein-protein association: an energy landscape perspective.
Ravikumar, Krishnakumar M; Huang, Wei; Yang, Sichun
2012-08-22
Understanding protein-protein association is crucial in revealing the molecular basis of many biological processes. Here, we describe a theoretical simulation pipeline to study protein-protein association from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via molecular dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examination on molecular forces shows that the formation of associated protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein association occurring in functional biomolecular complexes. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Coarse-Grained Simulations of Protein-Protein Association: An Energy Landscape Perspective
Ravikumar, Krishnakumar M.; Huang, Wei; Yang, Sichun
2012-01-01
Understanding protein-protein association is crucial in revealing the molecular basis of many biological processes. Here, we describe a theoretical simulation pipeline to study protein-protein association from an energy landscape perspective. First, a coarse-grained model is implemented and its applications are demonstrated via molecular dynamics simulations for several protein complexes. Second, an enhanced search method is used to efficiently sample a broad range of protein conformations. Third, multiple conformations are identified and clustered from simulation data and further projected on a three-dimensional globe specifying protein orientations and interacting energies. Results from several complexes indicate that the crystal-like conformation is favorable on the energy landscape even if the landscape is relatively rugged with metastable conformations. A closer examination on molecular forces shows that the formation of associated protein complexes can be primarily electrostatics-driven, hydrophobics-driven, or a combination of both in stabilizing specific binding interfaces. Taken together, these results suggest that the coarse-grained simulations and analyses provide an alternative toolset to study protein-protein association occurring in functional biomolecular complexes. PMID:22947945
NASA Technical Reports Server (NTRS)
Seldner, K.
1976-01-01
The development of control systems for jet engines requires a real-time computer simulation. The simulation provides an effective tool for evaluating control concepts and problem areas prior to actual engine testing. The development and use of a real-time simulation of the Pratt and Whitney F100-PW100 turbofan engine is described. The simulation was used in a multi-variable optimal controls research program using linear quadratic regulator theory. The simulation is used to generate linear engine models at selected operating points and evaluate the control algorithm. To reduce the complexity of the design, it is desirable to reduce the order of the linear model. A technique to reduce the order of the model; is discussed. Selected results between high and low order models are compared. The LQR control algorithms can be programmed on digital computer. This computer will control the engine simulation over the desired flight envelope.
Complex Langevin simulation of a random matrix model at nonzero chemical potential
NASA Astrophysics Data System (ADS)
Bloch, J.; Glesaaen, J.; Verbaarschot, J. J. M.; Zafeiropoulos, S.
2018-03-01
In this paper we test the complex Langevin algorithm for numerical simulations of a random matrix model of QCD with a first order phase transition to a phase of finite baryon density. We observe that a naive implementation of the algorithm leads to phase quenched results, which were also derived analytically in this article. We test several fixes for the convergence issues of the algorithm, in particular the method of gauge cooling, the shifted representation, the deformation technique and reweighted complex Langevin, but only the latter method reproduces the correct analytical results in the region where the quark mass is inside the domain of the eigenvalues. In order to shed more light on the issues of the methods we also apply them to a similar random matrix model with a milder sign problem and no phase transition, and in that case gauge cooling solves the convergence problems as was shown before in the literature.
Biocellion: accelerating computer simulation of multicellular biological system models
Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya
2014-01-01
Motivation: Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. Results: We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Availability and implementation: Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. Contact: seunghwa.kang@pnnl.gov PMID:25064572
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bostani, Maryam, E-mail: mbostani@mednet.ucla.edu; McMillan, Kyle; Cagnon, Chris H.
2014-11-01
Purpose: Monte Carlo (MC) simulation methods have been widely used in patient dosimetry in computed tomography (CT), including estimating patient organ doses. However, most simulation methods have undergone a limited set of validations, often using homogeneous phantoms with simple geometries. As clinical scanning has become more complex and the use of tube current modulation (TCM) has become pervasive in the clinic, MC simulations should include these techniques in their methodologies and therefore should also be validated using a variety of phantoms with different shapes and material compositions to result in a variety of differently modulated tube current profiles. The purposemore » of this work is to perform the measurements and simulations to validate a Monte Carlo model under a variety of test conditions where fixed tube current (FTC) and TCM were used. Methods: A previously developed MC model for estimating dose from CT scans that models TCM, built using the platform of MCNPX, was used for CT dose quantification. In order to validate the suitability of this model to accurately simulate patient dose from FTC and TCM CT scan, measurements and simulations were compared over a wide range of conditions. Phantoms used for testing range from simple geometries with homogeneous composition (16 and 32 cm computed tomography dose index phantoms) to more complex phantoms including a rectangular homogeneous water equivalent phantom, an elliptical shaped phantom with three sections (where each section was a homogeneous, but different material), and a heterogeneous, complex geometry anthropomorphic phantom. Each phantom requires varying levels of x-, y- and z-modulation. Each phantom was scanned on a multidetector row CT (Sensation 64) scanner under the conditions of both FTC and TCM. Dose measurements were made at various surface and depth positions within each phantom. Simulations using each phantom were performed for FTC, detailed x–y–z TCM, and z-axis-only TCM to obtain dose estimates. This allowed direct comparisons between measured and simulated dose values under each condition of phantom, location, and scan to be made. Results: For FTC scans, the percent root mean square (RMS) difference between measurements and simulations was within 5% across all phantoms. For TCM scans, the percent RMS of the difference between measured and simulated values when using detailed TCM and z-axis-only TCM simulations was 4.5% and 13.2%, respectively. For the anthropomorphic phantom, the difference between TCM measurements and detailed TCM and z-axis-only TCM simulations was 1.2% and 8.9%, respectively. For FTC measurements and simulations, the percent RMS of the difference was 5.0%. Conclusions: This work demonstrated that the Monte Carlo model developed provided good agreement between measured and simulated values under both simple and complex geometries including an anthropomorphic phantom. This work also showed the increased dose differences for z-axis-only TCM simulations, where considerable modulation in the x–y plane was present due to the shape of the rectangular water phantom. Results from this investigation highlight details that need to be included in Monte Carlo simulations of TCM CT scans in order to yield accurate, clinically viable assessments of patient dosimetry.« less
NASA Astrophysics Data System (ADS)
Suppachoknirun, Theerapat; Tutuncu, Azra N.
2017-12-01
With increasing production from shale gas and tight oil reservoirs, horizontal drilling and multistage hydraulic fracturing processes have become a routine procedure in unconventional field development efforts. Natural fractures play a critical role in hydraulic fracture growth, subsequently affecting stimulated reservoir volume and the production efficiency. Moreover, the existing fractures can also contribute to the pressure-dependent fluid leak-off during the operations. Hence, a reliable identification of the discrete fracture network covering the zone of interest prior to the hydraulic fracturing design needs to be incorporated into the hydraulic fracturing and reservoir simulations for realistic representation of the in situ reservoir conditions. In this research study, an integrated 3-D fracture and fluid flow model have been developed using a new approach to simulate the fluid flow and deliver reliable production forecasting in naturally fractured and hydraulically stimulated tight reservoirs. The model was created with three key modules. A complex 3-D discrete fracture network model introduces realistic natural fracture geometry with the associated fractured reservoir characteristics. A hydraulic fracturing model is created utilizing the discrete fracture network for simulation of the hydraulic fracture and flow in the complex discrete fracture network. Finally, a reservoir model with the production grid system is used allowing the user to efficiently perform the fluid flow simulation in tight formations with complex fracture networks. The complex discrete natural fracture model, the integrated discrete fracture model for the hydraulic fracturing, the fluid flow model, and the input dataset have been validated against microseismic fracture mapping and commingled production data obtained from a well pad with three horizontal production wells located in the Eagle Ford oil window in south Texas. Two other fracturing geometries were also evaluated to optimize the cumulative production and for the three wells individually. Significant reduction in the production rate in early production times is anticipated in tight reservoirs regardless of the fracturing techniques implemented. The simulations conducted using the alternating fracturing technique led to more oil production than when zipper fracturing was used for a 20-year production period. Yet, due to the decline experienced, the differences in cumulative production get smaller, and the alternating fracturing is not practically implementable while field application of zipper fracturing technique is more practical and widely used.
Numerical simulation of turbulent combustion: Scientific challenges
NASA Astrophysics Data System (ADS)
Ren, ZhuYin; Lu, Zhen; Hou, LingYun; Lu, LiuYan
2014-08-01
Predictive simulation of engine combustion is key to understanding the underlying complicated physicochemical processes, improving engine performance, and reducing pollutant emissions. Critical issues as turbulence modeling, turbulence-chemistry interaction, and accommodation of detailed chemical kinetics in complex flows remain challenging and essential for high-fidelity combustion simulation. This paper reviews the current status of the state-of-the-art large eddy simulation (LES)/prob-ability density function (PDF)/detailed chemistry approach that can address the three challenging modelling issues. PDF as a subgrid model for LES is formulated and the hybrid mesh-particle method for LES/PDF simulations is described. Then the development need in micro-mixing models for the PDF simulations of turbulent premixed combustion is identified. Finally the different acceleration methods for detailed chemistry are reviewed and a combined strategy is proposed for further development.
Simulation gravity modeling to spacecraft-tracking data - Analysis and application
NASA Technical Reports Server (NTRS)
Phillips, R. J.; Sjogren, W. L.; Abbott, E. A.; Zisk, S. H.
1978-01-01
It is proposed that line-of-sight gravity measurements derived from spacecraft-tracking data can be used for quantitative subsurface density modeling by suitable orbit simulation procedures. Such an approach avoids complex dynamic reductions and is analogous to the modeling of conventional surface gravity data. This procedure utilizes the vector calculations of a given gravity model in a simplified trajectory integration program that simulates the line-of-sight gravity. Solutions from an orbit simulation inversion and a dynamic inversion on Doppler observables compare well (within 1% in mass and size), and the error sources in the simulation approximation are shown to be quite small. An application of this technique is made to lunar crater gravity anomalies by simulating the complete Bouguer correction to several large young lunar craters. It is shown that the craters all have negative Bouguer anomalies.
Vilallonga, Gabriel D.; de Almeida, Antônio-Carlos G.; Ribeiro, Kelison T.; Campos, Sergio V. A.
2018-01-01
The sodium–potassium pump (Na+/K+ pump) is crucial for cell physiology. Despite great advances in the understanding of this ionic pumping system, its mechanism is not completely understood. We propose the use of a statistical model checker to investigate palytoxin (PTX)-induced Na+/K+ pump channels. We modelled a system of reactions representing transitions between the conformational substates of the channel with parameters, concentrations of the substates and reaction rates extracted from simulations reported in the literature, based on electrophysiological recordings in a whole-cell configuration. The model was implemented using the UPPAAL-SMC platform. Comparing simulations and probabilistic queries from stochastic system semantics with experimental data, it was possible to propose additional reactions to reproduce the single-channel dynamic. The probabilistic analyses and simulations suggest that the PTX-induced Na+/K+ pump channel functions as a diprotomeric complex in which protein–protein interactions increase the affinity of the Na+/K+ pump for PTX. PMID:29657808
Modeling and simulation of ocean wave propagation using lattice Boltzmann method
NASA Astrophysics Data System (ADS)
Nuraiman, Dian
2017-10-01
In this paper, we present on modeling and simulation of ocean wave propagation from the deep sea to the shoreline. This requires high computational cost for simulation with large domain. We propose to couple a 1D shallow water equations (SWE) model with a 2D incompressible Navier-Stokes equations (NSE) model in order to reduce the computational cost. The coupled model is solved using the lattice Boltzmann method (LBM) with the lattice Bhatnagar-Gross-Krook (BGK) scheme. Additionally, a special method is implemented to treat the complex behavior of free surface close to the shoreline. The result shows the coupled model can reduce computational cost significantly compared to the full NSE model.
Simulation for transthoracic echocardiography of aortic valve
Nanda, Navin C.; Kapur, K. K.; Kapoor, Poonam Malhotra
2016-01-01
Simulation allows interactive transthoracic echocardiography (TTE) learning using a virtual three-dimensional model of the heart and may aid in the acquisition of the cognitive and technical skills needed to perform TTE. The ability to link probe manipulation, cardiac anatomy, and echocardiographic images using a simulator has been shown to be an effective model for training anesthesiology residents in transesophageal echocardiography. A proposed alternative to real-time reality patient-based learning is simulation-based training that allows anesthesiologists to learn complex concepts and procedures, especially for specific structures such as aortic valve. PMID:27397455
Wind Energy System Time-domain (WEST) analyzers using hybrid simulation techniques
NASA Technical Reports Server (NTRS)
Hoffman, J. A.
1979-01-01
Two stand-alone analyzers constructed for real time simulation of the complex dynamic characteristics of horizontal-axis wind energy systems are described. Mathematical models for an aeroelastic rotor, including nonlinear aerodynamic and elastic loads, are implemented with high speed digital and analog circuitry. Models for elastic supports, a power train, a control system, and a rotor gimbal system are also included. Limited correlation efforts show good comparisons between results produced by the analyzers and results produced by a large digital simulation. The digital simulation results correlate well with test data.
Simulation of land use change in the three gorges reservoir area based on CART-CA
NASA Astrophysics Data System (ADS)
Yuan, Min
2018-05-01
This study proposes a new method to simulate spatiotemporal complex multiple land uses by using classification and regression tree algorithm (CART) based CA model. In this model, we use classification and regression tree algorithm to calculate land class conversion probability, and combine neighborhood factor, random factor to extract cellular transformation rules. The overall Kappa coefficient is 0.8014 and the overall accuracy is 0.8821 in the land dynamic simulation results of the three gorges reservoir area from 2000 to 2010, and the simulation results are satisfactory.
Mesoscale acid deposition modeling studies
NASA Technical Reports Server (NTRS)
Kaplan, Michael L.; Proctor, F. H.; Zack, John W.; Karyampudi, V. Mohan; Price, P. E.; Bousquet, M. D.; Coats, G. D.
1989-01-01
The work performed in support of the EPA/DOE MADS (Mesoscale Acid Deposition) Project included the development of meteorological data bases for the initialization of chemistry models, the testing and implementation of new planetary boundary layer parameterization schemes in the MASS model, the simulation of transport and precipitation for MADS case studies employing the MASS model, and the use of the TASS model in the simulation of cloud statistics and the complex transport of conservative tracers within simulated cumuloform clouds. The work performed in support of the NASA/FAA Wind Shear Program included the use of the TASS model in the simulation of the dynamical processes within convective cloud systems, the analyses of the sensitivity of microburst intensity and general characteristics as a function of the atmospheric environment within which they are formed, comparisons of TASS model microburst simulation results to observed data sets, and the generation of simulated wind shear data bases for use by the aviation meteorological community in the evaluation of flight hazards caused by microbursts.
Cannon, Robert C; Gleeson, Padraig; Crook, Sharon; Ganapathy, Gautham; Marin, Boris; Piasini, Eugenio; Silver, R Angus
2014-01-01
Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties.
Cannon, Robert C.; Gleeson, Padraig; Crook, Sharon; Ganapathy, Gautham; Marin, Boris; Piasini, Eugenio; Silver, R. Angus
2014-01-01
Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties. PMID:25309419
Trayanova, Natalia A; Tice, Brock M
2009-01-01
Simulation of cardiac electrical function, and specifically, simulation aimed at understanding the mechanisms of cardiac rhythm disorders, represents an example of a successful integrative multiscale modeling approach, uncovering emergent behavior at the successive scales in the hierarchy of structural complexity. The goal of this article is to present a review of the integrative multiscale models of realistic ventricular structure used in the quest to understand and treat ventricular arrhythmias. It concludes with the new advances in image-based modeling of the heart and the promise it holds for the development of individualized models of ventricular function in health and disease. PMID:20628585
Evolutionary Development of the Simulation by Logical Modeling System (SIBYL)
NASA Technical Reports Server (NTRS)
Wu, Helen
1995-01-01
Through the evolutionary development of the Simulation by Logical Modeling System (SIBYL) we have re-engineered the expensive and complex IBM mainframe based Long-term Hardware Projection Model (LHPM) to a robust cost-effective computer based mode that is easy to use. We achieved significant cost reductions and improved productivity in preparing long-term forecasts of Space Shuttle Main Engine (SSME) hardware. The LHPM for the SSME is a stochastic simulation model that projects the hardware requirements over 10 years. SIBYL is now the primary modeling tool for developing SSME logistics proposals and Program Operating Plan (POP) for NASA and divisional marketing studies.
Modeling Effects of RNA on Capsid Assembly Pathways via Coarse-Grained Stochastic Simulation
Smith, Gregory R.; Xie, Lu; Schwartz, Russell
2016-01-01
The environment of a living cell is vastly different from that of an in vitro reaction system, an issue that presents great challenges to the use of in vitro models, or computer simulations based on them, for understanding biochemistry in vivo. Virus capsids make an excellent model system for such questions because they typically have few distinct components, making them amenable to in vitro and modeling studies, yet their assembly can involve complex networks of possible reactions that cannot be resolved in detail by any current experimental technology. We previously fit kinetic simulation parameters to bulk in vitro assembly data to yield a close match between simulated and real data, and then used the simulations to study features of assembly that cannot be monitored experimentally. The present work seeks to project how assembly in these simulations fit to in vitro data would be altered by computationally adding features of the cellular environment to the system, specifically the presence of nucleic acid about which many capsids assemble. The major challenge of such work is computational: simulating fine-scale assembly pathways on the scale and in the parameter domains of real viruses is far too computationally costly to allow for explicit models of nucleic acid interaction. We bypass that limitation by applying analytical models of nucleic acid effects to adjust kinetic rate parameters learned from in vitro data to see how these adjustments, singly or in combination, might affect fine-scale assembly progress. The resulting simulations exhibit surprising behavioral complexity, with distinct effects often acting synergistically to drive efficient assembly and alter pathways relative to the in vitro model. The work demonstrates how computer simulations can help us understand how assembly might differ between the in vitro and in vivo environments and what features of the cellular environment account for these differences. PMID:27244559
Modeling of the ground-to-SSFMB link networking features using SPW
NASA Technical Reports Server (NTRS)
Watson, John C.
1993-01-01
This report describes the modeling and simulation of the networking features of the ground-to-Space Station Freedom manned base (SSFMB) link using COMDISCO signal processing work-system (SPW). The networking features modeled include the implementation of Consultative Committee for Space Data Systems (CCSDS) protocols in the multiplexing of digitized audio and core data into virtual channel data units (VCDU's) in the control center complex and the demultiplexing of VCDU's in the onboard baseband signal processor. The emphasis of this work has been placed on techniques for modeling the CCSDS networking features using SPW. The objectives for developing the SPW models are to test the suitability of SPW for modeling networking features and to develop SPW simulation models of the control center complex and space station baseband signal processor for use in end-to-end testing of the ground-to-SSFMB S-band single access forward (SSAF) link.
Digital Rock Simulation of Flow in Carbonate Samples
NASA Astrophysics Data System (ADS)
Klemin, D.; Andersen, M.
2014-12-01
Reservoir engineering has becomes more complex to deal with current challenges, so core analysts must understand and model pore geometries and fluid behaviors at pores scales more rapidly and realistically. We introduce an industry-unique direct hydrodynamic pore flow simulator that operates on pore geometries from digital rock models obtained using microCT or 3D scanning electron microscope (SEM) images. The PVT and rheological models used in the simulator represent real reservoir fluids. Fluid-solid interactions are introduced using distributed micro-scale wetting properties. The simulator uses density functional approach applied for hydrodynamics of complex systems. This talk covers selected applications of the simulator. We performed microCT scanning of six different carbonate rock samples from homogeneous limestones to vuggy carbonates. From these, we constructed digital rock models representing pore geometries for the simulator. We simulated nonreactive tracer flow in all six digital models using a digital fluid description that included a passive tracer solution. During the simulation, we evaluated the composition of the effluent. Results of tracer flow simulations corresponded well with experimental data of nonreactive tracer floods for the same carbonate rock types. This simulation data of the non-reactive tracer flow can be used to calculate the volume of the rock accessible by the fluid, which can be further used to predict response of a porous medium to a reactive fluid. The described digital core analysis workflow provides a basis for a wide variety of activities, including input to design acidizing jobs and evaluating treatment efficiency and EOR economics. Digital rock multiphase flow simulations of a scanned carbonate rock evaluated the effect of wettability on flow properties. Various wetting properties were tested: slightly oil wet, slightly water wet, and water wet. Steady-state relative permeability simulations yielded curves for all three ranges of wetting properties. The wetting variation affected phase mobility and residual phase saturations for primary oil flood and floods with varying ratios of oil and water.
Ftmp-Based Simulation of Twin Nucleation and Substructure Evolution Under Hypervelocity Impact
NASA Astrophysics Data System (ADS)
Okuda, Tatsuya; Imiya, Kazuhiro; Hasebe, Tadashi
2013-01-01
The deformation twinning model based on Field Theory of Multiscale Plasticity (FTMP) represents the twin degrees of freedom with the incompatibility tensor, which is incorporated into the hardening law of the FTMP-based crystalline plasticity framework. The model is further implemented into a finite element code. In the present study, the model is adapted to a single slip-oriented FCC single crystal sample, and preliminary simulations are conducted under static conditions to confirm the model's basic capabilities. The simulation results exhibit nucleation and growth of twinned regions, accompanied by serrated stress response and overall softening. Simulations under hypervelocity impact conditions are also conducted to investigate the model's descriptive capabilities of induced complex substructures composing of both twins and dislocations. The simulated nucleation of twins is examined in detail by using duality diagrams in terms of the flow-evolutionary hypothesis.
Predictive performance models and multiple task performance
NASA Technical Reports Server (NTRS)
Wickens, Christopher D.; Larish, Inge; Contorer, Aaron
1989-01-01
Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.
NASA Astrophysics Data System (ADS)
Byrne, Michael P.; O'Gorman, Paul A.
2016-12-01
Climate models simulate a strong land-ocean contrast in the response of near-surface relative humidity to global warming: relative humidity tends to increase slightly over oceans but decrease substantially over land. Surface energy balance arguments have been used to understand the response over ocean but are difficult to apply over more complex land surfaces. Here, a conceptual box model is introduced, involving moisture transport between the land and ocean boundary layers and evapotranspiration, to investigate the decreases in land relative humidity as the climate warms. The box model is applied to idealized and full-complexity (CMIP5) general circulation model simulations, and it is found to capture many of the features of the simulated changes in land relative humidity. The box model suggests there is a strong link between fractional changes in specific humidity over land and ocean, and the greater warming over land than ocean then implies a decrease in land relative humidity. Evapotranspiration is of secondary importance for the increase in specific humidity over land, but it matters more for the decrease in relative humidity. Further analysis shows there is a strong feedback between changes in surface-air temperature and relative humidity, and this can amplify the influence on relative humidity of factors such as stomatal conductance and soil moisture.
Numerical simulation of radiation fog in complex terrain
NASA Astrophysics Data System (ADS)
Zhang, X.; Musson-Genon, L.; Carissimo, B.; Dupont, E.
2009-09-01
The interest for micro-scale modeling of the atmosphere is growing for environmental applications related, for example, to energy production, transport and urban development. The turbulence in the stable layers where pollutant dispersion is low and can lead to strong pollution events. This could be further complicated by the presence of clouds or fog and is specifically difficult in urban or industrial area due to the presence of buildings. In this context, radiation fog formation and dissipation over complex terrain were therefore investigated with a state-of-the-art model. This study is divided into two phases. The first phase is a pilot stage, which consist of employing a database from the ParisFog campaign which took place in the south of Paris during winter 2006-07 to assess the ability of the cloud model to reproduce the detailed structure of radiation fog. The second phase use the validated model for the study of influence of complex terrain on fog evolution. Special attention is given to the detailed and complete simulations and validation technique used is to compare the simulated results using the 3D cloud model of computational fluid dynamical software Code_Saturne with one of the best collected in situ data during the ParisFog campaign. Several dynamical, microphysical parameterizations and simulation conditions have been described. The resulting 3D cloud model runs at a horizontal resolution of 30 m and a vertical resolution comparable to the 1D model. First results look very promising and are able to reproduce the spatial distribution of fog. The analysis of the behavior of the different parameterized physical processes suggests that the subtle balance between the various processes is achieved.
Building an intelligent tutoring system for procedural domains
NASA Technical Reports Server (NTRS)
Warinner, Andrew; Barbee, Diann; Brandt, Larry; Chen, Tom; Maguire, John
1990-01-01
Jobs that require complex skills that are too expensive or dangerous to develop often use simulators in training. The strength of a simulator is its ability to mimic the 'real world', allowing students to explore and experiment. A good simulation helps the student develop a 'mental model' of the real world. The closer the simulation is to 'real life', the less difficulties there are transferring skills and mental models developed on the simulator to the real job. As graphics workstations increase in power and become more affordable they become attractive candidates for developing computer-based simulations for use in training. Computer based simulations can make training more interesting and accessible to the student.
Evolution of Software-Only-Simulation at NASA IV and V
NASA Technical Reports Server (NTRS)
McCarty, Justin; Morris, Justin; Zemerick, Scott
2014-01-01
Software-Only-Simulations have been an emerging but quickly developing field of study throughout NASA. The NASA Independent Verification Validation (IVV) Independent Test Capability (ITC) team has been rapidly building a collection of simulators for a wide range of NASA missions. ITC specializes in full end-to-end simulations that enable developers, VV personnel, and operators to test-as-you-fly. In four years, the team has delivered a wide variety of spacecraft simulations that have ranged from low complexity science missions such as the Global Precipitation Management (GPM) satellite and the Deep Space Climate Observatory (DSCOVR), to the extremely complex missions such as the James Webb Space Telescope (JWST) and Space Launch System (SLS).This paper describes the evolution of ITCs technologies and processes that have been utilized to design, implement, and deploy end-to-end simulation environments for various NASA missions. A comparison of mission simulators are discussed with focus on technology and lessons learned in complexity, hardware modeling, and continuous integration. The paper also describes the methods for executing the missions unmodified flight software binaries (not cross-compiled) for verification and validation activities.
How to understand atomistic molecular dynamics simulations of RNA and protein-RNA complexes?
Šponer, Jiří; Krepl, Miroslav; Banáš, Pavel; Kührová, Petra; Zgarbová, Marie; Jurečka, Petr; Havrila, Marek; Otyepka, Michal
2017-05-01
We provide a critical assessment of explicit-solvent atomistic molecular dynamics (MD) simulations of RNA and protein/RNA complexes, written primarily for non-specialists with an emphasis to explain the limitations of MD. MD simulations can be likened to hypothetical single-molecule experiments starting from single atomistic conformations and investigating genuine thermal sampling of the biomolecules. The main advantage of MD is the unlimited temporal and spatial resolution of positions of all atoms in the simulated systems. Fundamental limitations are the short physical time-scale of simulations, which can be partially alleviated by enhanced-sampling techniques, and the highly approximate atomistic force fields describing the simulated molecules. The applicability and present limitations of MD are demonstrated on studies of tetranucleotides, tetraloops, ribozymes, riboswitches and protein/RNA complexes. Wisely applied simulations respecting the approximations of the model can successfully complement structural and biochemical experiments. WIREs RNA 2017, 8:e1405. doi: 10.1002/wrna.1405 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.
Challenges of NDE Simulation Tool Challenges of NDE Simulation Tool
NASA Technical Reports Server (NTRS)
Leckey, Cara A. C.; Juarez, Peter D.; Seebo, Jeffrey P.; Frank, Ashley L.
2015-01-01
Realistic nondestructive evaluation (NDE) simulation tools enable inspection optimization and predictions of inspectability for new aerospace materials and designs. NDE simulation tools may someday aid in the design and certification of advanced aerospace components; potentially shortening the time from material development to implementation by industry and government. Furthermore, modeling and simulation are expected to play a significant future role in validating the capabilities and limitations of guided wave based structural health monitoring (SHM) systems. The current state-of-the-art in ultrasonic NDE/SHM simulation cannot rapidly simulate damage detection techniques for large scale, complex geometry composite components/vehicles with realistic damage types. This paper discusses some of the challenges of model development and validation for composites, such as the level of realism and scale of simulation needed for NASA' applications. Ongoing model development work is described along with examples of model validation studies. The paper will also discuss examples of the use of simulation tools at NASA to develop new damage characterization methods, and associated challenges of validating those methods.
Testing MODFLOW-LGR for simulating flow around buried Quaternary valleys - synthetic test cases
NASA Astrophysics Data System (ADS)
Vilhelmsen, T. N.; Christensen, S.
2009-12-01
In this study the Local Grid Refinement (LGR) method developed for MODFLOW-2005 (Mehl and Hill, 2005) is utilized to describe groundwater flow in areas containing buried Quaternary valley structures. The tests are conducted as comparative analysis between simulations run with a globally refined model, a locally refined model, and a globally coarse model, respectively. The models vary from simple one layer models to more complex ones with up to 25 model layers. The comparisons of accuracy are conducted within the locally refined area and focus on water budgets, simulated heads, and simulated particle traces. Simulations made with the globally refined model are used as reference (regarded as “true” values). As expected, for all test cases the application of local grid refinement resulted in more accurate results than when using the globally coarse model. A significant advantage of utilizing MODFLOW-LGR was that it allows increased numbers of model layers to better resolve complex geology within local areas. This resulted in more accurate simulations than when using either a globally coarse model grid or a locally refined model with lower geological resolution. Improved accuracy in the latter case could not be expected beforehand because difference in geological resolution between the coarse parent model and the refined child model contradicts the assumptions of the Darcy weighted interpolation used in MODFLOW-LGR. With respect to model runtimes, it was sometimes found that the runtime for the locally refined model is much longer than for the globally refined model. This was the case even when the closure criteria were relaxed compared to the globally refined model. These results are contradictory to those presented by Mehl and Hill (2005). Furthermore, in the complex cases it took some testing (model runs) to identify the closure criteria and the damping factor that secured convergence, accurate solutions, and reasonable runtimes. For our cases this is judged to be a serious disadvantage of applying MODFLOW-LGR. Another disadvantage in the studied cases was that the MODFLOW-LGR results proved to be somewhat dependent on the correction method used at the parent-child model interface. This indicates that when applying MODFLOW-LGR there is a need for thorough and case-specific considerations regarding choice of correction method. References: Mehl, S. and M. C. Hill (2005). "MODFLOW-2005, THE U.S. GEOLOGICAL SURVEY MODULAR GROUND-WATER MODEL - DOCUMENTATION OF SHARED NODE LOCAL GRID REFINEMENT (LGR) AND THE BOUNDARY FLOW AND HEAD (BFH) PACKAGE " U.S. Geological Survey Techniques and Methods 6-A12
Dong, Xiaotian; Su, Xiaoru; Yu, Jiong; Liu, Jingqi; Shi, Xiaowei; Pan, Qiaoling; Yang, Jinfeng; Chen, Jiajia; Li, Lanjuan; Cao, Hongcui
2017-01-01
Hypoxia-inducible factor 2 alpha (HIF2α), prolyl hydroxylase domain protein 2 (PHD2), and the von Hippel Lindau tumor suppressor protein (pVHL) are three principal proteins in the oxygen-sensing pathway. Under normoxic conditions, a conserved proline in HIF2α is hydroxylated by PHD2 in an oxygen-dependent manner, and then pVHL binds and promotes the degradation of HIF2α. However, the crystal structure of the HIF2α-pVHL complex has not yet been established, and this has limited research on the interaction between HIF and pVHL. Here, we constructed a structural model of a 23-residue HIF2α peptide (528-550)-pVHL-ElonginB-ElonginC complex by using homology modeling and molecular dynamics simulations. We also applied these methods to HIF2α mutants (HYP531PRO, F540L, A530 V, A530T, and G537R) to reveal structural defects that explain how these mutations weaken the interaction with pVHL. Homology modeling and molecular dynamics simulations were used to construct a three-dimensional (3D) structural model of the HIF2α-VHL complex. Subsequently, MolProbity, an active validation tool, was used to analyze the reliability of the model. Molecular mechanics energies combined with the generalized Born and surface area continuum solvation (MM-GBSA) and solvated interaction energy (SIE) methods were used to calculate the binding free energy between HIF2a and pVHL, and the stability of the simulation system was evaluated by using root mean square deviation (RMSD) analysis. We also determined the secondary structure of the system by using the definition of secondary structure of proteins (DSSP) algorithm. Finally, we investigated the structural significance of specific point mutations known to have clinical implications. We established a reliable structural model of the HIF2α-pVHL complex, which is similar to the crystal structure of HIF1α in 1LQB. Furthermore, we compared the structural model of the HIF2α-pVHL complex and the HIF2α (HYP531P, F540L, A530V, A530T, and G537R)-pVHL mutants on the basis of RMSD, DSSP, binding free energy, and hydrogen bonding. The experimental data indicate that the stability of the structural model of the HIF2α-pVHL complex is higher than that of the mutants, consistently with clinical observations. The structural model of the HIF2α-pVHL complex presented in this study enhances understanding of how HIF2α is captured by pVHL. Moreover, the important contact amino acids that we identified may be useful in the development of drugs to treat HIF2a-related diseases. Copyright © 2016 Elsevier Inc. All rights reserved.
Statistical and Probabilistic Extensions to Ground Operations' Discrete Event Simulation Modeling
NASA Technical Reports Server (NTRS)
Trocine, Linda; Cummings, Nicholas H.; Bazzana, Ashley M.; Rychlik, Nathan; LeCroy, Kenneth L.; Cates, Grant R.
2010-01-01
NASA's human exploration initiatives will invest in technologies, public/private partnerships, and infrastructure, paving the way for the expansion of human civilization into the solar system and beyond. As it is has been for the past half century, the Kennedy Space Center will be the embarkation point for humankind's journey into the cosmos. Functioning as a next generation space launch complex, Kennedy's launch pads, integration facilities, processing areas, launch and recovery ranges will bustle with the activities of the world's space transportation providers. In developing this complex, KSC teams work through the potential operational scenarios: conducting trade studies, planning and budgeting for expensive and limited resources, and simulating alternative operational schemes. Numerous tools, among them discrete event simulation (DES), were matured during the Constellation Program to conduct such analyses with the purpose of optimizing the launch complex for maximum efficiency, safety, and flexibility while minimizing life cycle costs. Discrete event simulation is a computer-based modeling technique for complex and dynamic systems where the state of the system changes at discrete points in time and whose inputs may include random variables. DES is used to assess timelines and throughput, and to support operability studies and contingency analyses. It is applicable to any space launch campaign and informs decision-makers of the effects of varying numbers of expensive resources and the impact of off nominal scenarios on measures of performance. In order to develop representative DES models, methods were adopted, exploited, or created to extend traditional uses of DES. The Delphi method was adopted and utilized for task duration estimation. DES software was exploited for probabilistic event variation. A roll-up process was used, which was developed to reuse models and model elements in other less - detailed models. The DES team continues to innovate and expand DES capabilities to address KSC's planning needs.
NASA Astrophysics Data System (ADS)
Chicea, Anca-Lucia
2015-09-01
The paper presents the process of building geometric and kinematic models of a technological equipment used in the process of manufacturing devices. First, the process of building the model for a six axes industrial robot is presented. In the second part of the paper, the process of building the model for a five-axis CNC milling machining center is also shown. Both models can be used for accurate cutting processes simulation of complex parts, such as prosthetic devices.
Adaptive tracking for complex systems using reduced-order models
NASA Technical Reports Server (NTRS)
Carnigan, Craig R.
1990-01-01
Reduced-order models are considered in the context of parameter adaptive controllers for tracking workspace trajectories. A dual-arm manipulation task is used to illustrate the methodology and provide simulation results. A parameter adaptive controller is designed to track a payload trajectory using a four-parameter model instead of the full-order, nine-parameter model. Several simulations with different payload-to-arm mass ratios are used to illustrate the capabilities of the reduced-order model in tracking the desired trajectory.
Adaptive tracking for complex systems using reduced-order models
NASA Technical Reports Server (NTRS)
Carignan, Craig R.
1990-01-01
Reduced-order models are considered in the context of parameter adaptive controllers for tracking workspace trajectories. A dual-arm manipulation task is used to illustrate the methodology and provide simulation results. A parameter adaptive controller is designed to track the desired position trajectory of a payload using a four-parameter model instead of a full-order, nine-parameter model. Several simulations with different payload-to-arm mass ratios are used to illustrate the capabilities of the reduced-order model in tracking the desired trajectory.
Techniques and resources for storm-scale numerical weather prediction
NASA Technical Reports Server (NTRS)
Droegemeier, Kelvin; Grell, Georg; Doyle, James; Soong, Su-Tzai; Skamarock, William; Bacon, David; Staniforth, Andrew; Crook, Andrew; Wilhelmson, Robert
1993-01-01
The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software.
Architecting a Simulation Framework for Model Rehosting
NASA Technical Reports Server (NTRS)
Madden, Michael M.
2004-01-01
The utility of vehicle math models extends beyond human-in-the-loop simulation. It is desirable to deploy a given model across a multitude of applications that target design, analysis, and research. However, the vehicle model alone represents an incomplete simulation. One must also replicate the environment models (e.g., atmosphere, gravity, terrain) to achieve identical vehicle behavior across all applications. Environment models are increasing in complexity and represent a substantial investment to re-engineer for a new application. A software component that can be rehosted in each application is one solution to the deployment problem. The component must encapsulate both the vehicle and environment models. The component must have a well-defined interface that abstracts the bulk of the logic to operate the models. This paper examines the characteristics of a rehostable modeling component from the perspective of a human-in-the-loop simulation framework. The Langley Standard Real-Time Simulation in C++ (LaSRS++) is used as an example. LaSRS++ was recently redesigned to transform its modeling package into a rehostable component.
USDA-ARS?s Scientific Manuscript database
Integration and synthesis of data accruing from complex alternative crop rotation experiments across locations and climates is a challenge to agriculturists. System simulation models are potential tools to address this challenge. In this study, we simulated three long-term (1991 to 2008) dryland c...
Simulating tracer transport in variably saturated soils and shallow groundwater
USDA-ARS?s Scientific Manuscript database
The objective of this study was to develop a realistic model to simulate the complex processes of flow and tracer transport in variably saturated soils and to compare simulation results with the detailed monitoring observations. The USDA-ARS OPE3 field site was selected for the case study due to ava...
Interactive visualization to advance earthquake simulation
Kellogg, L.H.; Bawden, G.W.; Bernardin, T.; Billen, M.; Cowgill, E.; Hamann, B.; Jadamec, M.; Kreylos, O.; Staadt, O.; Sumner, D.
2008-01-01
The geological sciences are challenged to manage and interpret increasing volumes of data as observations and simulations increase in size and complexity. For example, simulations of earthquake-related processes typically generate complex, time-varying data sets in two or more dimensions. To facilitate interpretation and analysis of these data sets, evaluate the underlying models, and to drive future calculations, we have developed methods of interactive visualization with a special focus on using immersive virtual reality (VR) environments to interact with models of Earth's surface and interior. Virtual mapping tools allow virtual "field studies" in inaccessible regions. Interactive tools allow us to manipulate shapes in order to construct models of geological features for geodynamic models, while feature extraction tools support quantitative measurement of structures that emerge from numerical simulation or field observations, thereby enabling us to improve our interpretation of the dynamical processes that drive earthquakes. VR has traditionally been used primarily as a presentation tool, albeit with active navigation through data. Reaping the full intellectual benefits of immersive VR as a tool for scientific analysis requires building on the method's strengths, that is, using both 3D perception and interaction with observed or simulated data. This approach also takes advantage of the specialized skills of geological scientists who are trained to interpret, the often limited, geological and geophysical data available from field observations. ?? Birkhaueser 2008.
Phast4Windows: A 3D graphical user interface for the reactive-transport simulator PHAST
Charlton, Scott R.; Parkhurst, David L.
2013-01-01
Phast4Windows is a Windows® program for developing and running groundwater-flow and reactive-transport models with the PHAST simulator. This graphical user interface allows definition of grid-independent spatial distributions of model properties—the porous media properties, the initial head and chemistry conditions, boundary conditions, and locations of wells, rivers, drains, and accounting zones—and other parameters necessary for a simulation. Spatial data can be defined without reference to a grid by drawing, by point-by-point definitions, or by importing files, including ArcInfo® shape and raster files. All definitions can be inspected, edited, deleted, moved, copied, and switched from hidden to visible through the data tree of the interface. Model features are visualized in the main panel of the interface, so that it is possible to zoom, pan, and rotate features in three dimensions (3D). PHAST simulates single phase, constant density, saturated groundwater flow under confined or unconfined conditions. Reactions among multiple solutes include mineral equilibria, cation exchange, surface complexation, solid solutions, and general kinetic reactions. The interface can be used to develop and run simple or complex models, and is ideal for use in the classroom, for analysis of laboratory column experiments, and for development of field-scale simulations of geochemical processes and contaminant transport.
Systems modeling and simulation applications for critical care medicine
2012-01-01
Critical care delivery is a complex, expensive, error prone, medical specialty and remains the focal point of major improvement efforts in healthcare delivery. Various modeling and simulation techniques offer unique opportunities to better understand the interactions between clinical physiology and care delivery. The novel insights gained from the systems perspective can then be used to develop and test new treatment strategies and make critical care delivery more efficient and effective. However, modeling and simulation applications in critical care remain underutilized. This article provides an overview of major computer-based simulation techniques as applied to critical care medicine. We provide three application examples of different simulation techniques, including a) pathophysiological model of acute lung injury, b) process modeling of critical care delivery, and c) an agent-based model to study interaction between pathophysiology and healthcare delivery. Finally, we identify certain challenges to, and opportunities for, future research in the area. PMID:22703718
Stochastic molecular model of enzymatic hydrolysis of cellulose for ethanol production
2013-01-01
Background During cellulosic ethanol production, cellulose hydrolysis is achieved by synergistic action of cellulase enzyme complex consisting of multiple enzymes with different mode of actions. Enzymatic hydrolysis of cellulose is one of the bottlenecks in the commercialization of the process due to low hydrolysis rates and high cost of enzymes. A robust hydrolysis model that can predict hydrolysis profile under various scenarios can act as an important forecasting tool to improve the hydrolysis process. However, multiple factors affecting hydrolysis: cellulose structure and complex enzyme-substrate interactions during hydrolysis make it diffucult to develop mathematical kinetic models that can simulate hydrolysis in presence of multiple enzymes with high fidelity. In this study, a comprehensive hydrolysis model based on stochastic molecular modeling approch in which each hydrolysis event is translated into a discrete event is presented. The model captures the structural features of cellulose, enzyme properties (mode of actions, synergism, inhibition), and most importantly dynamic morphological changes in the substrate that directly affect the enzyme-substrate interactions during hydrolysis. Results Cellulose was modeled as a group of microfibrils consisting of elementary fibrils bundles, where each elementary fibril was represented as a three dimensional matrix of glucose molecules. Hydrolysis of cellulose was simulated based on Monte Carlo simulation technique. Cellulose hydrolysis results predicted by model simulations agree well with the experimental data from literature. Coefficients of determination for model predictions and experimental values were in the range of 0.75 to 0.96 for Avicel hydrolysis by CBH I action. Model was able to simulate the synergistic action of multiple enzymes during hydrolysis. The model simulations captured the important experimental observations: effect of structural properties, enzyme inhibition and enzyme loadings on the hydrolysis and degree of synergism among enzymes. Conclusions The model was effective in capturing the dynamic behavior of cellulose hydrolysis during action of individual as well as multiple cellulases. Simulations were in qualitative and quantitative agreement with experimental data. Several experimentally observed phenomena were simulated without the need for any additional assumptions or parameter changes and confirmed the validity of using the stochastic molecular modeling approach to quantitatively and qualitatively describe the cellulose hydrolysis. PMID:23638989
Lattice Boltzmann method for rain-induced overland flow
NASA Astrophysics Data System (ADS)
Ding, Yu; Liu, Haifei; Peng, Yong; Xing, Liming
2018-07-01
Complex rainfall situations can generate overland flow with complex hydrodynamic characteristics, affecting the surface configuration (i.e. sheet erosion) and environment to varying degrees. Reliable numerical simulations can provide a scientific method for the optimization of environmental management. A mesoscopic numerical method, the lattice Boltzmann method, was employed to simulate overland flows. To deal with complex rainfall, two schemes were introduced to improve the lattice Boltzmann equation and the local equilibrium function, respectively. Four typical cases with differences in rainfall, bed roughness, and slopes were selected to test the accuracy and applicability of the proposed schemes. It was found that the simulated results were in good agreement with the experimental data, analytical values, and the results produced by other models.
Gustafsson, Leif; Sternad, Mikael
2007-10-01
Population models concern collections of discrete entities such as atoms, cells, humans, animals, etc., where the focus is on the number of entities in a population. Because of the complexity of such models, simulation is usually needed to reproduce their complete dynamic and stochastic behaviour. Two main types of simulation models are used for different purposes, namely micro-simulation models, where each individual is described with its particular attributes and behaviour, and macro-simulation models based on stochastic differential equations, where the population is described in aggregated terms by the number of individuals in different states. Consistency between micro- and macro-models is a crucial but often neglected aspect. This paper demonstrates how the Poisson Simulation technique can be used to produce a population macro-model consistent with the corresponding micro-model. This is accomplished by defining Poisson Simulation in strictly mathematical terms as a series of Poisson processes that generate sequences of Poisson distributions with dynamically varying parameters. The method can be applied to any population model. It provides the unique stochastic and dynamic macro-model consistent with a correct micro-model. The paper also presents a general macro form for stochastic and dynamic population models. In an appendix Poisson Simulation is compared with Markov Simulation showing a number of advantages. Especially aggregation into state variables and aggregation of many events per time-step makes Poisson Simulation orders of magnitude faster than Markov Simulation. Furthermore, you can build and execute much larger and more complicated models with Poisson Simulation than is possible with the Markov approach.
SAINT: A combined simulation language for modeling man-machine systems
NASA Technical Reports Server (NTRS)
Seifert, D. J.
1979-01-01
SAINT (Systems Analysis of Integrated Networks of Tasks) is a network modeling and simulation technique for design and analysis of complex man machine systems. SAINT provides the conceptual framework for representing systems that consist of discrete task elements, continuous state variables, and interactions between them. It also provides a mechanism for combining human performance models and dynamic system behaviors in a single modeling structure. The SAINT technique is described and applications of the SAINT are discussed.