Dynamic Computation of Change Operations in Version Management of Business Process Models

Science.gov (United States)

Küster, Jochen Malte; Gerth, Christian; Engels, Gregor

Version management of business process models requires that changes can be resolved by applying change operations. In order to give a user maximal freedom concerning the application order of change operations, position parameters of change operations must be computed dynamically during change resolution. In such an approach, change operations with computed position parameters must be applicable on the model and dependencies and conflicts of change operations must be taken into account because otherwise invalid models can be constructed. In this paper, we study the concept of partially specified change operations where parameters are computed dynamically. We provide a formalization for partially specified change operations using graph transformation and provide a concept for their applicability. Based on this, we study potential dependencies and conflicts of change operations and show how these can be taken into account within change resolution. Using our approach, a user can resolve changes of business process models without being unnecessarily restricted to a certain order.

A Model for the Acceptance of Cloud Computing Technology Using DEMATEL Technique and System Dynamics Approach

Directory of Open Access Journals (Sweden)

seyyed mohammad zargar

2018-03-01

Full Text Available Cloud computing is a new method to provide computing resources and increase computing power in organizations. Despite the many benefits this method shares, it has not been universally used because of some obstacles including security issues and has become a concern for IT managers in organization. In this paper, the general definition of cloud computing is presented. In addition, having reviewed previous studies, the researchers identified effective variables on technology acceptance and, especially, cloud computing technology. Then, using DEMATEL technique, the effectiveness and permeability of the variable were determined. The researchers also designed a model to show the existing dynamics in cloud computing technology using system dynamics approach. The validity of the model was confirmed through evaluation methods in dynamics model by using VENSIM software. Finally, based on different conditions of the proposed model, a variety of scenarios were designed. Then, the implementation of these scenarios was simulated within the proposed model. The results showed that any increase in data security, government support and user training can lead to the increase in the adoption and use of cloud computing technology.

Global dynamics of a novel multi-group model for computer worms

International Nuclear Information System (INIS)

Gong Yong-Wang; Song Yu-Rong; Jiang Guo-Ping

2013-01-01

In this paper, we study worm dynamics in computer networks composed of many autonomous systems. A novel multi-group SIQR (susceptible-infected-quarantined-removed) model is proposed for computer worms by explicitly considering anti-virus measures and the network infrastructure. Then, the basic reproduction number of worm R 0 is derived and the global dynamics of the model are established. It is shown that if R 0 is less than or equal to 1, the disease-free equilibrium is globally asymptotically stable and the worm dies out eventually, whereas, if R 0 is greater than 1, one unique endemic equilibrium exists and it is globally asymptotically stable, thus the worm persists in the network. Finally, numerical simulations are given to illustrate the theoretical results. (general)

Computational Fluid Dynamics model of stratified atmospheric boundary-layer flow

DEFF Research Database (Denmark)

Koblitz, Tilman; Bechmann, Andreas; Sogachev, Andrey

2015-01-01

For wind resource assessment, the wind industry is increasingly relying on computational fluid dynamics models of the neutrally stratified surface-layer. So far, physical processes that are important to the whole atmospheric boundary-layer, such as the Coriolis effect, buoyancy forces and heat...

A paradigm for modeling and computation of gas dynamics

Science.gov (United States)

Xu, Kun; Liu, Chang

2017-02-01

In the continuum flow regime, the Navier-Stokes (NS) equations are usually used for the description of gas dynamics. On the other hand, the Boltzmann equation is applied for the rarefied flow. These two equations are based on distinguishable modeling scales for flow physics. Fortunately, due to the scale separation, i.e., the hydrodynamic and kinetic ones, both the Navier-Stokes equations and the Boltzmann equation are applicable in their respective domains. However, in real science and engineering applications, they may not have such a distinctive scale separation. For example, around a hypersonic flying vehicle, the flow physics at different regions may correspond to different regimes, where the local Knudsen number can be changed significantly in several orders of magnitude. With a variation of flow physics, theoretically a continuous governing equation from the kinetic Boltzmann modeling to the hydrodynamic Navier-Stokes dynamics should be used for its efficient description. However, due to the difficulties of a direct modeling of flow physics in the scale between the kinetic and hydrodynamic ones, there is basically no reliable theory or valid governing equations to cover the whole transition regime, except resolving flow physics always down to the mean free path scale, such as the direct Boltzmann solver and the Direct Simulation Monte Carlo (DSMC) method. In fact, it is an unresolved problem about the exact scale for the validity of the NS equations, especially in the small Reynolds number cases. The computational fluid dynamics (CFD) is usually based on the numerical solution of partial differential equations (PDEs), and it targets on the recovering of the exact solution of the PDEs as mesh size and time step converging to zero. This methodology can be hardly applied to solve the multiple scale problem efficiently because there is no such a complete PDE for flow physics through a continuous variation of scales. For the non-equilibrium flow study, the direct

Computational Fluid Dynamics Modeling of Bacillus anthracis ...

Science.gov (United States)

Journal Article Three-dimensional computational fluid dynamics and Lagrangian particle deposition models were developed to compare the deposition of aerosolized Bacillus anthracis spores in the respiratory airways of a human with that of the rabbit, a species commonly used in the study of anthrax disease. The respiratory airway geometries for each species were derived from computed tomography (CT) or µCT images. Both models encompassed airways that extended from the external nose to the lung with a total of 272 outlets in the human model and 2878 outlets in the rabbit model. All simulations of spore deposition were conducted under transient, inhalation-exhalation breathing conditions using average species-specific minute volumes. Four different exposure scenarios were modeled in the rabbit based upon experimental inhalation studies. For comparison, human simulations were conducted at the highest exposure concentration used during the rabbit experimental exposures. Results demonstrated that regional spore deposition patterns were sensitive to airway geometry and ventilation profiles. Despite the complex airway geometries in the rabbit nose, higher spore deposition efficiency was predicted in the upper conducting airways of the human at the same air concentration of anthrax spores. This greater deposition of spores in the upper airways in the human resulted in lower penetration and deposition in the tracheobronchial airways and the deep lung than that predict

New weighted sum of gray gases model applicable to Computational Fluid Dynamics (CFD) modeling of oxy-fuel combustion

DEFF Research Database (Denmark)

Yin, Chungen; Johansen, Lars Christian Riis; Rosendahl, Lasse

2010-01-01

gases model (WSGGM) is derived, which is applicable to computational fluid dynamics (CFD) modeling of both air-fuel and oxy-fuel combustion. First, a computer code is developed to evaluate the emissivity of any gas mixture at any condition by using the exponential wide band model (EWBM...

Cardioplegia heat exchanger design modelling using computational fluid dynamics.

Science.gov (United States)

van Driel, M R

2000-11-01

A new cardioplegia heat exchanger has been developed by Sorin Biomedica. A three-dimensional computer-aided design (CAD) model was optimized using computational fluid dynamics (CFD) modelling. CFD optimization techniques have commonly been applied to velocity flow field analysis, but CFD analysis was also used in this study to predict the heat exchange performance of the design before prototype fabrication. The iterative results of the optimization and the actual heat exchange performance of the final configuration are presented in this paper. Based on the behaviour of this model, both the water and blood fluid flow paths of the heat exchanger were optimized. The simulation predicted superior heat exchange performance using an optimal amount of energy exchange surface area, reducing the total contact surface area, the device priming volume and the material costs. Experimental results confirm the empirical results predicted by the CFD analysis.

A meta-model for computer executable dynamic clinical safety checklists.

Science.gov (United States)

Nan, Shan; Van Gorp, Pieter; Lu, Xudong; Kaymak, Uzay; Korsten, Hendrikus; Vdovjak, Richard; Duan, Huilong

2017-12-12

Safety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. This is due to the lack of a formal representation format that is both understandable by clinical experts and executable by computer programs. We developed a dynamic checklist meta-model with a three-step approach. Dynamic checklist modeling requirements were extracted by performing a domain analysis. Then, existing modeling approaches and tools were investigated with the purpose of reusing these languages. Finally, the meta-model was developed by eliciting domain concepts and their hierarchies. The feasibility of using the meta-model was validated by two case studies. The meta-model was mapped to specific modeling languages according to the requirements of hospitals. Using the proposed meta-model, a comprehensive coronary artery bypass graft peri-operative checklist set and a percutaneous coronary intervention peri-operative checklist set have been developed in a Dutch hospital and a Chinese hospital, respectively. The result shows that it is feasible to use the meta-model to facilitate the modeling and execution of dynamic checklists. We proposed a novel meta-model for the dynamic checklist with the purpose of facilitating creating dynamic checklists. The meta-model is a framework of reusing existing modeling languages and tools to model dynamic checklists. The feasibility of using the meta-model is validated by implementing a use case in the system.

Computational Fluid Dynamics

International Nuclear Information System (INIS)

Myeong, Hyeon Guk

1999-06-01

This book deals with computational fluid dynamics with basic and history of numerical fluid dynamics, introduction of finite volume method using one-dimensional heat conduction equation, solution of two-dimensional heat conduction equation, solution of Navier-Stokes equation, fluid with heat transport, turbulent flow and turbulent model, Navier-Stokes solution by generalized coordinate system such as coordinate conversion, conversion of basic equation, program and example of calculation, application of abnormal problem and high speed solution of numerical fluid dynamics.

Topics in Modeling of Cochlear Dynamics: Computation, Response and Stability Analysis

Science.gov (United States)

Filo, Maurice G.

This thesis touches upon several topics in cochlear modeling. Throughout the literature, mathematical models of the cochlea vary according to the degree of biological realism to be incorporated. This thesis casts the cochlear model as a continuous space-time dynamical system using operator language. This framework encompasses a wider class of cochlear models and makes the dynamics more transparent and easier to analyze before applying any numerical method to discretize space. In fact, several numerical methods are investigated to study the computational efficiency of the finite dimensional realizations in space. Furthermore, we study the effects of the active gain perturbations on the stability of the linearized dynamics. The stability analysis is used to explain possible mechanisms underlying spontaneous otoacoustic emissions and tinnitus. Dynamic Mode Decomposition (DMD) is introduced as a useful tool to analyze the response of nonlinear cochlear models. Cochlear response features are illustrated using DMD which has the advantage of explicitly revealing the spatial modes of vibrations occurring in the Basilar Membrane (BM). Finally, we address the dynamic estimation problem of BM vibrations using Extended Kalman Filters (EKF). Due to the limitations of noninvasive sensing schemes, such algorithms are inevitable to estimate the dynamic behavior of a living cochlea.

LION: A dynamic computer model for the low-latitude ionosphere

Directory of Open Access Journals (Sweden)

J. A. Bittencourt

2007-11-01

Full Text Available A realistic fully time-dependent computer model, denominated LION (Low-latitude Ionospheric model, that simulates the dynamic behavior of the low-latitude ionosphere is presented. The time evolution and spatial distribution of the ionospheric particle densities and velocities are computed by numerically solving the time-dependent, coupled, nonlinear system of continuity and momentum equations for the ions O⁺, O₂⁺, NO⁺, N₂⁺ and N⁺, taking into account photoionization of the atmospheric species by the solar extreme ultraviolet radiation, chemical and ionic production and loss reactions, and plasma transport processes, including the ionospheric effects of thermospheric neutral winds, plasma diffusion and electromagnetic E×B plasma drifts. The Earth's magnetic field is represented by a tilted centered magnetic dipole. This set of coupled nonlinear equations is solved along a given magnetic field line in a Lagrangian frame of reference moving vertically, in the magnetic meridian plane, with the electromagnetic E×B plasma drift velocity. The spatial and time distribution of the thermospheric neutral wind velocities and the pattern of the electromagnetic drifts are taken as known quantities, given through specified analytical or empirical models. The model simulation results are presented in the form of computer-generated color maps and reproduce the typical ionization distribution and time evolution normally observed in the low-latitude ionosphere, including details of the equatorial Appleton anomaly dynamics. The specific effects on the ionosphere due to changes in the thermospheric neutral winds and the electromagnetic plasma drifts can be investigated using different wind and drift models, including the important longitudinal effects associated with magnetic declination dependence and latitudinal separation between geographic and

LION: A dynamic computer model for the low-latitude ionosphere

Directory of Open Access Journals (Sweden)

J. A. Bittencourt

2007-11-01

Full Text Available A realistic fully time-dependent computer model, denominated LION (Low-latitude Ionospheric model, that simulates the dynamic behavior of the low-latitude ionosphere is presented. The time evolution and spatial distribution of the ionospheric particle densities and velocities are computed by numerically solving the time-dependent, coupled, nonlinear system of continuity and momentum equations for the ions O+, O2+, NO+, N2+ and N+, taking into account photoionization of the atmospheric species by the solar extreme ultraviolet radiation, chemical and ionic production and loss reactions, and plasma transport processes, including the ionospheric effects of thermospheric neutral winds, plasma diffusion and electromagnetic E×B plasma drifts. The Earth's magnetic field is represented by a tilted centered magnetic dipole. This set of coupled nonlinear equations is solved along a given magnetic field line in a Lagrangian frame of reference moving vertically, in the magnetic meridian plane, with the electromagnetic E×B plasma drift velocity. The spatial and time distribution of the thermospheric neutral wind velocities and the pattern of the electromagnetic drifts are taken as known quantities, given through specified analytical or empirical models. The model simulation results are presented in the form of computer-generated color maps and reproduce the typical ionization distribution and time evolution normally observed in the low-latitude ionosphere, including details of the equatorial Appleton anomaly dynamics. The specific effects on the ionosphere due to changes in the thermospheric neutral winds and the electromagnetic plasma drifts can be investigated using different wind and drift models, including the important longitudinal effects associated with magnetic declination dependence and latitudinal separation between geographic and geomagnetic equators. The model runs in a normal personal computer (PC and generates color maps illustrating the

Dynamic computer model for the metallogenesis and tectonics of the Circum-North Pacific

Science.gov (United States)

Scotese, Christopher R.; Nokleberg, Warren J.; Monger, James W.H.; Norton, Ian O.; Parfenov, Leonid M.; Khanchuk, Alexander I.; Bundtzen, Thomas K.; Dawson, Kenneth M.; Eremin, Roman A.; Frolov, Yuri F.; Fujita, Kazuya; Goryachev, Nikolai A.; Pozdeev, Anany I.; Ratkin, Vladimir V.; Rodinov, Sergey M.; Rozenblum, Ilya S.; Scholl, David W.; Shpikerman, Vladimir I.; Sidorov, Anatoly A.; Stone, David B.

2001-01-01

The digital files on this report consist of a dynamic computer model of the metallogenesis and tectonics of the Circum-North Pacific, and background articles, figures, and maps. The tectonic part of the dynamic computer model is derived from a major analysis of the tectonic evolution of the Circum-North Pacific which is also contained in directory tectevol. The dynamic computer model and associated materials on this CD-ROM are part of a project on the major mineral deposits, metallogenesis, and tectonics of the Russian Far East, Alaska, and the Canadian Cordillera. The project provides critical information on bedrock geology and geophysics, tectonics, major metalliferous mineral resources, metallogenic patterns, and crustal origin and evolution of mineralizing systems for this region. The major scientific goals and benefits of the project are to: (1) provide a comprehensive international data base on the mineral resources of the region that is the first, extensive knowledge available in English; (2) provide major new interpretations of the origin and crustal evolution of mineralizing systems and their host rocks, thereby enabling enhanced, broad-scale tectonic reconstructions and interpretations; and (3) promote trade and scientific and technical exchanges between North America and Eastern Asia.

Critical Analysis of Underground Coal Gasification Models. Part II: Kinetic and Computational Fluid Dynamics Models

Directory of Open Access Journals (Sweden)

Alina Żogała

2014-01-01

Originality/value: This paper presents state of art in the field of coal gasification modeling using kinetic and computational fluid dynamics approach. The paper also presents own comparative analysis (concerned with mathematical formulation, input data and parameters, basic assumptions, obtained results etc. of the most important models of underground coal gasification.

Computational fluid dynamics modelling in cardiovascular medicine.

Science.gov (United States)

Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P

2016-01-01

This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. Published by the BMJ Publishing Group Limited. For permission

The performance model of dynamic virtual organization (VO) formations within grid computing context

International Nuclear Information System (INIS)

Han Liangxiu

2009-01-01

Grid computing aims to enable 'resource sharing and coordinated problem solving in dynamic, multi-institutional virtual organizations (VOs)'. Within the grid computing context, successful dynamic VO formations mean a number of individuals and institutions associated with certain resources join together and form new VOs in order to effectively execute tasks within given time steps. To date, while the concept of VOs has been accepted, few research has been done on the impact of effective dynamic virtual organization formations. In this paper, we develop a performance model of dynamic VOs formation and analyze the effect of different complex organizational structures and their various statistic parameter properties on dynamic VO formations from three aspects: (1) the probability of a successful VO formation under different organizational structures and statistic parameters change, e.g. average degree; (2) the effect of task complexity on dynamic VO formations; (3) the impact of network scales on dynamic VO formations. The experimental results show that the proposed model can be used to understand the dynamic VO formation performance of the simulated organizations. The work provides a good path to understand how to effectively schedule and utilize resources based on the complex grid network and therefore improve the overall performance within grid environment.

Computational neuropharmacology: dynamical approaches in drug discovery.

Science.gov (United States)

Aradi, Ildiko; Erdi, Péter

2006-05-01

Computational approaches that adopt dynamical models are widely accepted in basic and clinical neuroscience research as indispensable tools with which to understand normal and pathological neuronal mechanisms. Although computer-aided techniques have been used in pharmaceutical research (e.g. in structure- and ligand-based drug design), the power of dynamical models has not yet been exploited in drug discovery. We suggest that dynamical system theory and computational neuroscience--integrated with well-established, conventional molecular and electrophysiological methods--offer a broad perspective in drug discovery and in the search for novel targets and strategies for the treatment of neurological and psychiatric diseases.

Teachers' Use of Computational Tools to Construct and Explore Dynamic Mathematical Models

Science.gov (United States)

Santos-Trigo, Manuel; Reyes-Rodriguez, Aaron

2011-01-01

To what extent does the use of computational tools offer teachers the possibility of constructing dynamic models to identify and explore diverse mathematical relations? What ways of reasoning or thinking about the problems emerge during the model construction process that involves the use of the tools? These research questions guided the…

Computational social dynamic modeling of group recruitment.

Energy Technology Data Exchange (ETDEWEB)

Berry, Nina M.; Lee, Marinna; Pickett, Marc; Turnley, Jessica Glicken (Sandia National Laboratories, Albuquerque, NM); Smrcka, Julianne D. (Sandia National Laboratories, Albuquerque, NM); Ko, Teresa H.; Moy, Timothy David (Sandia National Laboratories, Albuquerque, NM); Wu, Benjamin C.

2004-01-01

The Seldon software toolkit combines concepts from agent-based modeling and social science to create a computationally social dynamic model for group recruitment. The underlying recruitment model is based on a unique three-level hybrid agent-based architecture that contains simple agents (level one), abstract agents (level two), and cognitive agents (level three). This uniqueness of this architecture begins with abstract agents that permit the model to include social concepts (gang) or institutional concepts (school) into a typical software simulation environment. The future addition of cognitive agents to the recruitment model will provide a unique entity that does not exist in any agent-based modeling toolkits to date. We use social networks to provide an integrated mesh within and between the different levels. This Java based toolkit is used to analyze different social concepts based on initialization input from the user. The input alters a set of parameters used to influence the values associated with the simple agents, abstract agents, and the interactions (simple agent-simple agent or simple agent-abstract agent) between these entities. The results of phase-1 Seldon toolkit provide insight into how certain social concepts apply to different scenario development for inner city gang recruitment.

A computational fluid dynamics model for designing heat exchangers based on natural convection

NARCIS (Netherlands)

Dirkse, M.H.; Loon, van W.K.P.; Walle, van der T.; Speetjens, S.L.; Bot, G.P.A.

2006-01-01

A computational fluid dynamics model was created for the design of a natural convection shell-and-tube heat exchanger with baffles. The flow regime proved to be turbulent and this was modelled using the k¿¿ turbulence model. The features of the complex geometry were simplified considerably resulting

Computational fluid dynamics modeling of mixed convection flows in buildings enclosures

Energy Technology Data Exchange (ETDEWEB)

Kayne, Alexander; Agarwal, Ramesh K. [Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, MO 63130 (United States)

2013-07-01

In recent years Computational Fluid Dynamics (CFD) simulations are increasingly used to model the air circulation and temperature environment inside the rooms of residential and office buildings to gain insight into the relative energy consumptions of various HVAC systems for cooling/heating for climate control and thermal comfort. This requires accurate simulation of turbulent flow and heat transfer for various types of ventilation systems using the Reynolds-Averaged Navier-Stokes (RANS) equations of fluid dynamics. Large Eddy Simulation (LES) or Direct Numerical Simulation (DNS) of Navier-Stokes equations is computationally intensive and expensive for simulations of this kind. As a result, vast majority of CFD simulations employ RANS equations in conjunction with a turbulence model. In order to assess the modeling requirements (mesh, numerical algorithm, turbulence model etc.) for accurate simulations, it is critical to validate the calculations against the experimental data. For this purpose, we use three well known benchmark validation cases, one for natural convection in 2D closed vertical cavity, second for forced convection in a 2D rectangular cavity and the third for mixed convection in a 2D square cavity. The simulations are performed on a number of meshes of different density using a number of turbulence models. It is found that k-epsilon two-equation turbulence model with a second-order algorithm on a reasonable mesh gives the best results. This information is then used to determine the modeling requirements (mesh, numerical algorithm, turbulence model etc.) for flows in 3D enclosures with different ventilation systems. In particular two cases are considered for which the experimental data is available. These cases are (1) air flow and heat transfer in a naturally ventilated room and (2) airflow and temperature distribution in an atrium. Good agreement with the experimental data and computations of other investigators is obtained.

Perspectives for the application of computer models to forest dynamics forecasting in bieszczadzki national park (Poland

Directory of Open Access Journals (Sweden)

Kozak Ihor

2014-03-01

Full Text Available This paper presents the perspectives for application of computer models in forecasting the dynamics of forest development on example of Moczarne area, in Bieszczadzki National Park, based on authors’ computer models. First, the possibilities for forecasting the dynamics of forest development in a local scale, i.e. within single rectangular or circular study plot, are presented. For this purpose, a computer prognostic model FORKOM E has been applied, using both general mathematical relationships functioning within a forest ecosystem and empirical ones, characteristic for tree stands at analysed plots. Additionally, a layer of 3D visualisation of a tree stand, which is an integral part of the mentioned model, is also presented. Presented also are the possibilities for forecasting the dynamics of forest development at landscape scale, applying the theory of cellular automata. For this purpose, a prognostic computer model CELLAUT was used in which the whole analysed tree stand is understood as a set of single cells, where stages of landscape development dominating within those cells are considered as also the influence of particular cells upon their neighbours. The paper also describes the perspectives for application of self-learning neural networks in the process of supplementation and verification of some parameters of a tree stand, calculated by the above-mentioned models.

Vascular dynamics aid a coupled neurovascular network learn sparse independent features: A computational model

Directory of Open Access Journals (Sweden)

Ryan Thomas Philips

2016-02-01

Full Text Available Cerebral vascular dynamics are generally thought to be controlled by neural activity in a unidirectional fashion. However, both computational modeling and experimental evidence point to the feedback effects of vascular dynamics on neural activity. Vascular feedback in the form of glucose and oxygen controls neuronal ATP, either directly or via the agency of astrocytes, which in turn modulates neural firing. Recently, a detailed model of the neuron-astrocyte-vessel system has shown how vasomotion can modulate neural firing. Similarly, arguing from known cerebrovascular physiology, an approach known as `hemoneural hypothesis' postulates functional modulation of neural activity by vascular feedback. To instantiate this perspective, we present a computational model in which a network of `vascular units' supplies energy to a neural network. The complex dynamics of the vascular network, modeled by a network of oscillators, turns neurons ON and OFF randomly. The informational consequence of such dynamics is explored in the context of an auto-encoder network. In the proposed model, each vascular unit supplies energy to a subset of hidden neurons of an autoencoder network, which constitutes its `projective field'. Neurons that receive adequate energy in a given trial have reduced threshold, and thus are prone to fire. Dynamics of the vascular network are governed by changes in the reconstruction error of the auto-encoder network, interpreted as the neuronal demand. Vascular feedback causes random inactivation of a subset of hidden neurons in every trial. We observe that, under conditions of desynchronized vascular dynamics, the output reconstruction error is low and the feature vectors learnt are sparse and independent. Our earlier modeling study highlighted the link between desynchronized vascular dynamics and efficient energy delivery in skeletal muscle. We now show that desynchronized vascular dynamics leads to efficient training in an auto

Modeling behavior dynamics using computational psychometrics within virtual worlds.

Science.gov (United States)

Cipresso, Pietro

2015-01-01

In case of fire in a building, how will people behave in the crowd? The behavior of each individual affects the behavior of others and, conversely, each one behaves considering the crowd as a whole and the individual others. In this article, I propose a three-step method to explore a brand new way to study behavior dynamics. The first step relies on the creation of specific situations with standard techniques (such as mental imagery, text, video, and audio) and an advanced technique [Virtual Reality (VR)] to manipulate experimental settings. The second step concerns the measurement of behavior in one, two, or many individuals focusing on parameters extractions to provide information about the behavior dynamics. Finally, the third step, which uses the parameters collected and measured in the previous two steps in order to simulate possible scenarios to forecast through computational models, understand, and explain behavior dynamics at the social level. An experimental study was also included to demonstrate the three-step method and a possible scenario.

Bayesian model calibration of computational models in velocimetry diagnosed dynamic compression experiments.

Energy Technology Data Exchange (ETDEWEB)

Brown, Justin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hund, Lauren [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-02-01

Dynamic compression experiments are being performed on complicated materials using increasingly complex drivers. The data produced in these experiments are beginning to reach a regime where traditional analysis techniques break down; requiring the solution of an inverse problem. A common measurement in dynamic experiments is an interface velocity as a function of time, and often this functional output can be simulated using a hydrodynamics code. Bayesian model calibration is a statistical framework to estimate inputs into a computational model in the presence of multiple uncertainties, making it well suited to measurements of this type. In this article, we apply Bayesian model calibration to high pressure (250 GPa) ramp compression measurements in tantalum. We address several issues speci c to this calibration including the functional nature of the output as well as parameter and model discrepancy identi ability. Speci cally, we propose scaling the likelihood function by an e ective sample size rather than modeling the autocorrelation function to accommodate the functional output and propose sensitivity analyses using the notion of `modularization' to assess the impact of experiment-speci c nuisance input parameters on estimates of material properties. We conclude that the proposed Bayesian model calibration procedure results in simple, fast, and valid inferences on the equation of state parameters for tantalum.

A Computational Fluid Dynamic Model for a Novel Flash Ironmaking Process

Science.gov (United States)

Perez-Fontes, Silvia E.; Sohn, Hong Yong; Olivas-Martinez, Miguel

A computational fluid dynamic model for a novel flash ironmaking process based on the direct gaseous reduction of iron oxide concentrates is presented. The model solves the three-dimensional governing equations including both gas-phase and gas-solid reaction kinetics. The turbulence-chemistry interaction in the gas-phase is modeled by the eddy dissipation concept incorporating chemical kinetics. The particle cloud model is used to track the particle phase in a Lagrangian framework. A nucleation and growth kinetics rate expression is adopted to calculate the reduction rate of magnetite concentrate particles. Benchmark experiments reported in the literature for a nonreacting swirling gas jet and a nonpremixed hydrogen jet flame were simulated for validation. The model predictions showed good agreement with measurements in terms of gas velocity, gas temperature and species concentrations. The relevance of the computational model for the analysis of a bench reactor operation and the design of an industrial-pilot plant is discussed.

Computable Types for Dynamic Systems

NARCIS (Netherlands)

P.J. Collins (Pieter); K. Ambos-Spies; B. Loewe; W. Merkle

2009-01-01

textabstractIn this paper, we develop a theory of computable types suitable for the study of dynamic systems in discrete and continuous time. The theory uses type-two effectivity as the underlying computational model, but we quickly develop a type system which can be manipulated abstractly, but for

DNA Self-Assembly and Computation Studied with a Coarse-grained Dynamic Bonded Model

DEFF Research Database (Denmark)

Svaneborg, Carsten; Fellermann, Harold; Rasmussen, Steen

2012-01-01

We utilize a coarse-grained directional dynamic bonding DNA model [C. Svaneborg, Comp. Phys. Comm. (In Press DOI:10.1016/j.cpc.2012.03.005)] to study DNA self-assembly and DNA computation. In our DNA model, a single nucleotide is represented by a single interaction site, and complementary sites can...

Modeling Behavior Dynamics using Computational Psychometrics within Virtual Worlds

Directory of Open Access Journals (Sweden)

Pietro eCipresso

2015-11-01

Full Text Available In case of fire in a building, how will people behave in the crowd? The behavior of each individual affects the behavior of others and, conversely, each one behaves considering the crowd as a whole and the individual others. In this article, I propose a three-step method to explore a brand new way to study behavior dynamics. The first step relies on the creation of specific situations with standard techniques (such as mental imagery, text, video and audio and an advanced technique (Virtual Reality to manipulate experimental settings. The second step concerns the measurement of behavior in one, two or many individuals focusing on parameters extractions to provide information about the behavior dynamics. Finally, the third step, which uses the parameters collected and measured in the previous two steps in order to simulate possible scenarios to forecast through computational models, understand and explain behavior dynamics at the social level. An experimental study was also included to demonstrate the three-step method and a possible scenario.

Computer Programme for the Dynamic Analysis of Tall Regular ...

African Journals Online (AJOL)

The traditional method of dynamic analysis of tall rigid frames assumes the shear frame model. Models that allow joint rotations with/without the inclusion of the column axial loads give improved results but pose much more computational difficulty. In this work a computer program Natfrequency that determines the dynamic ...

Dynamics and computation in functional shifts

Science.gov (United States)

Namikawa, Jun; Hashimoto, Takashi

2004-07-01

We introduce a new type of shift dynamics as an extended model of symbolic dynamics, and investigate the characteristics of shift spaces from the viewpoints of both dynamics and computation. This shift dynamics is called a functional shift, which is defined by a set of bi-infinite sequences of some functions on a set of symbols. To analyse the complexity of functional shifts, we measure them in terms of topological entropy, and locate their languages in the Chomsky hierarchy. Through this study, we argue that considering functional shifts from the viewpoints of both dynamics and computation gives us opposite results about the complexity of systems. We also describe a new class of shift spaces whose languages are not recursively enumerable.

HTTR plant dynamic simulation using a hybrid computer

International Nuclear Information System (INIS)

Shimazaki, Junya; Suzuki, Katsuo; Nabeshima, Kunihiko; Watanabe, Koichi; Shinohara, Yoshikuni; Nakagawa, Shigeaki.

1990-01-01

A plant dynamic simulation of High-Temperature Engineering Test Reactor has been made using a new-type hybrid computer. This report describes a dynamic simulation model of HTTR, a hybrid simulation method for SIMSTAR and some results obtained from dynamics analysis of HTTR simulation. It concludes that the hybrid plant simulation is useful for on-line simulation on account of its capability of computation at high speed, compared with that of all digital computer simulation. With sufficient accuracy, 40 times faster computation than real time was reached only by changing an analog time scale for HTTR simulation. (author)

Computational fluid dynamic modeling of fluidized-bed polymerization reactors

Energy Technology Data Exchange (ETDEWEB)

Rokkam, Ram [Iowa State Univ., Ames, IA (United States)

2012-01-01

Polyethylene is one of the most widely used plastics, and over 60 million tons are produced worldwide every year. Polyethylene is obtained by the catalytic polymerization of ethylene in gas and liquid phase reactors. The gas phase processes are more advantageous, and use fluidized-bed reactors for production of polyethylene. Since they operate so close to the melting point of the polymer, agglomeration is an operational concern in all slurry and gas polymerization processes. Electrostatics and hot spot formation are the main factors that contribute to agglomeration in gas-phase processes. Electrostatic charges in gas phase polymerization fluidized bed reactors are known to influence the bed hydrodynamics, particle elutriation, bubble size, bubble shape etc. Accumulation of electrostatic charges in the fluidized-bed can lead to operational issues. In this work a first-principles electrostatic model is developed and coupled with a multi-fluid computational fluid dynamic (CFD) model to understand the effect of electrostatics on the dynamics of a fluidized-bed. The multi-fluid CFD model for gas-particle flow is based on the kinetic theory of granular flows closures. The electrostatic model is developed based on a fixed, size-dependent charge for each type of particle (catalyst, polymer, polymer fines) phase. The combined CFD model is first verified using simple test cases, validated with experiments and applied to a pilot-scale polymerization fluidized-bed reactor. The CFD model reproduced qualitative trends in particle segregation and entrainment due to electrostatic charges observed in experiments. For the scale up of fluidized bed reactor, filtered models are developed and implemented on pilot scale reactor.

Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons.

Science.gov (United States)

Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang

2011-11-01

The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of neural systems in the brain. In principle there exists a powerful computational framework for stochastic computations, probabilistic inference by sampling, which can explain a large number of macroscopic experimental data in neuroscience and cognitive science. But it has turned out to be surprisingly difficult to create a link between these abstract models for stochastic computations and more detailed models of the dynamics of networks of spiking neurons. Here we create such a link and show that under some conditions the stochastic firing activity of networks of spiking neurons can be interpreted as probabilistic inference via Markov chain Monte Carlo (MCMC) sampling. Since common methods for MCMC sampling in distributed systems, such as Gibbs sampling, are inconsistent with the dynamics of spiking neurons, we introduce a different approach based on non-reversible Markov chains that is able to reflect inherent temporal processes of spiking neuronal activity through a suitable choice of random variables. We propose a neural network model and show by a rigorous theoretical analysis that its neural activity implements MCMC sampling of a given distribution, both for the case of discrete and continuous time. This provides a step towards closing the gap between abstract functional models of cortical computation and more detailed models of networks of spiking neurons.

Dynamics of nuclear fuel assemblies in vertical flow channels: computer modelling and associated studies

International Nuclear Information System (INIS)

Mason, V.A.; Pettigrew, M.J.; Lelli, G.; Kates, L.; Reimer, E.

1978-10-01

A computer model, designed to predict the dynamic behaviour of nuclear fuel assemblies in axial flow, is described in this report. The numerical methods used to construct and solve the matrix equations of motion in the model are discussed together with an outline of the method used to interpret the fuel assembly stability data. The mathematics developed for forced response calculations are described in detail. Certain structural and hydrodynamic modelling parameters must be determined by experiment. These parameters are identified and the methods used for their evaluation are briefly described. Examples of typical applications of the dynamic model are presented towards the end of the report. (author)

Programming Unconventional Computers: Dynamics, Development, Self-Reference

Directory of Open Access Journals (Sweden)

Susan Stepney

2012-10-01

Full Text Available Classical computing has well-established formalisms for specifying, refining, composing, proving, and otherwise reasoning about computations. These formalisms have matured over the past 70 years or so. Unconventional Computing includes the use of novel kinds of substrates–from black holes and quantum effects, through to chemicals, biomolecules, even slime moulds–to perform computations that do not conform to the classical model. Although many of these unconventional substrates can be coerced into performing classical computation, this is not how they “naturally” compute. Our ability to exploit unconventional computing is partly hampered by a lack of corresponding programming formalisms: we need models for building, composing, and reasoning about programs that execute in these substrates. What might, say, a slime mould programming language look like? Here I outline some of the issues and properties of these unconventional substrates that need to be addressed to find “natural” approaches to programming them. Important concepts include embodied real values, processes and dynamical systems, generative systems and their meta-dynamics, and embodied self-reference.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

Directory of Open Access Journals (Sweden)

Mark G Orr

Full Text Available The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior, does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence. To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

Science.gov (United States)

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

Finite-element-model updating using computational intelligence techniques applications to structural dynamics

CERN Document Server

Marwala, Tshilidzi

2010-01-01

Finite element models (FEMs) are widely used to understand the dynamic behaviour of various systems. FEM updating allows FEMs to be tuned better to reflect measured data and may be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. Finite Element Model Updating Using Computational Intelligence Techniques applies both strategies to the field of structural mechanics, an area vital for aerospace, civil and mechanical engineering. Vibration data is used for the updating process. Following an introduction a number of computational intelligence techniques to facilitate the updating process are proposed; they include: • multi-layer perceptron neural networks for real-time FEM updating; • particle swarm and genetic-algorithm-based optimization methods to accommodate the demands of global versus local optimization models; • simulated annealing to put the methodologies into a sound statistical basis; and • response surface methods and expectation m...

Research Summary 3-D Computational Fluid Dynamics (CFD) Model Of The Human Respiratory System

Science.gov (United States)

The U.S. EPA’s Office of Research and Development (ORD) has developed a 3-D computational fluid dynamics (CFD) model of the human respiratory system that allows for the simulation of particulate based contaminant deposition and clearance, while being adaptable for age, ethnicity,...

A parametric study of a solar calcinator using computational fluid dynamics

International Nuclear Information System (INIS)

Fidaros, D.K.; Baxevanou, C.A.; Vlachos, N.S.

2007-01-01

In this work a horizontal rotating solar calcinator is studied numerically using computational fluid dynamics. The specific solar reactor is a 10 kW model designed and used for efficiency studies. The numerical model is based on the solution of the Navier-Stokes equations for the gas flow, and on Lagrangean dynamics for the discrete particles. All necessary mathematical models were developed and incorporated into a computational fluid dynamics model with the influence of turbulence simulated by a two-equation (RNG k-ε) model. The efficiency of the reactor was calculated for different thermal inputs, feed rates, rotational speeds and particle diameters. The numerically computed degrees of calcination compared well with equivalent experimental results

Developing a computationally efficient dynamic multilevel hybrid optimization scheme using multifidelity model interactions.

Energy Technology Data Exchange (ETDEWEB)

Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr. (; .); Giunta, Anthony Andrew

2006-01-01

Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and

Computational fluid dynamics modelling of hydraulics and sedimentation in process reactors during aeration tank settling.

Science.gov (United States)

Jensen, M D; Ingildsen, P; Rasmussen, M R; Laursen, J

2006-01-01

Aeration tank settling is a control method allowing settling in the process tank during high hydraulic load. The control method is patented. Aeration tank settling has been applied in several waste water treatment plants using the present design of the process tanks. Some process tank designs have shown to be more effective than others. To improve the design of less effective plants, computational fluid dynamics (CFD) modelling of hydraulics and sedimentation has been applied. This paper discusses the results at one particular plant experiencing problems with partly short-circuiting of the inlet and outlet causing a disruption of the sludge blanket at the outlet and thereby reducing the retention of sludge in the process tank. The model has allowed us to establish a clear picture of the problems arising at the plant during aeration tank settling. Secondly, several process tank design changes have been suggested and tested by means of computational fluid dynamics modelling. The most promising design changes have been found and reported.

Unsteady Vibration Aerodynamic Modeling and Evaluation of Dynamic Derivatives Using Computational Fluid Dynamics

Directory of Open Access Journals (Sweden)

Xu Liu

2015-01-01

Full Text Available Unsteady aerodynamic system modeling is widely used to solve the dynamic stability problems encountering aircraft design. In this paper, single degree-of-freedom (SDF vibration model and forced simple harmonic motion (SHM model for dynamic derivative prediction are developed on the basis of modified Etkin model. In the light of the characteristics of SDF time domain solution, the free vibration identification methods for dynamic stability parameters are extended and applied to the time domain numerical simulation of blunted cone calibration model examples. The dynamic stability parameters by numerical identification are no more than 0.15% deviated from those by experimental simulation, confirming the correctness of SDF vibration model. The acceleration derivatives, rotary derivatives, and combination derivatives of Army-Navy Spinner Rocket are numerically identified by using unsteady N-S equation and solving different SHV patterns. Comparison with the experimental result of Army Ballistic Research Laboratories confirmed the correctness of the SHV model and dynamic derivative identification. The calculation result of forced SHM is better than that by the slender body theory of engineering approximation. SDF vibration model and SHM model for dynamic stability parameters provide a solution to the dynamic stability problem encountering aircraft design.

Reduced-Order Computational Model for Low-Frequency Dynamics of Automobiles

Directory of Open Access Journals (Sweden)

A. Arnoux

2013-01-01

Full Text Available A reduced-order model is constructed to predict, for the low-frequency range, the dynamical responses in the stiff parts of an automobile constituted of stiff and flexible parts. The vehicle has then many elastic modes in this range due to the presence of many flexible parts and equipment. A nonusual reduced-order model is introduced. The family of the elastic modes is not used and is replaced by an adapted vector basis of the admissible space of global displacements. Such a construction requires a decomposition of the domain of the structure in subdomains in order to control the spatial wave length of the global displacements. The fast marching method is used to carry out the subdomain decomposition. A probabilistic model of uncertainties is introduced. The parameters controlling the level of uncertainties are estimated solving a statistical inverse problem. The methodology is validated with a large computational model of an automobile.

Interface between computational fluid dynamics (CFD) and plant analysis computer codes

International Nuclear Information System (INIS)

Coffield, R.D.; Dunckhorst, F.F.; Tomlinson, E.T.; Welch, J.W.

1993-01-01

Computational fluid dynamics (CFD) can provide valuable input to the development of advanced plant analysis computer codes. The types of interfacing discussed in this paper will directly contribute to modeling and accuracy improvements throughout the plant system and should result in significant reduction of design conservatisms that have been applied to such analyses in the past

Computer-graphic visualization of dynamics

International Nuclear Information System (INIS)

Stewart, H.B.

1986-01-01

As engineered systems become increasingly sophisticated and complex, questions of efficiency, reliability, and safety demand the application of more powerful methods of analysis. One indication of this is the accelerating trend away from purely static or quasi-steady system modeling toward models that include essentially dynamic behavior. It is here that the qualitative ideas of nonlinear dynamics, dealing as they do with the most typical behavior in real dynamical systems, can be expected to play an increasingly prominent role. As part of a continuing investigation of the most important low-order differential equations, an interactive computer graphics environment has been created for the study of systems in three-dimensional phase space. This environment makes available the basic control of both numerical simulation and graphic visualization by a specially designed menu system. A key ingredient in this environment is the possibility of graphic communication not only from machine to man, but also from man to machine. Thus to specify the starting point for a numerical integration, for example, the user points to a location in phase space on the screen of the graphics terminal (using crosshairs or a mouse and cursor), bypassing the necessity to give numerical values of the phase-space coordinates. By devising a flexible computer interface which implements conceptual approaches to phase-space analysis of dynamical systems, significant advances in understanding of prototypical differential equations have been achieved

Computational model to simulate the interplay effect in dynamic IMRT delivery

International Nuclear Information System (INIS)

Yoganathan, S A; Maria Das, K J; Kumar, Shaleen

2014-01-01

The purpose of this study was to develop and experimentally verify a patient specific model for simulating the interplay effect in a DMLC based IMRT delivery. A computational model was developed using MATLAB program to incorporate the interplay effect in a 2D beams eye view fluence of dynamic IMRT fields. To simulate interplay effect, the model requires two inputs: IMRT field (DMLC file with dose rate and MU) and the patient specific respiratory motion. The interplay between the DMLC leaf motion and target was simulated for three lung patients. The target trajectory data was acquired using RPM system during the treatment simulation. The model was verified experimentally for the same patients using Imatrix 2D array device placed over QUASAR motion platform in CL2100 linac. The simulated fluences and measured fluences were compared with the TPS generated static fluence (no motion) using an in-house developed gamma evaluation program (2%/2mm). The simulated results were well within agreement with the measured. Comparison of the simulated and measured fluences with the TPS static fluence resulted 55.3% and 58.5% pixels passed the gamma criteria. A patient specific model was developed and validated for simulating the interplay effect in the dynamic IMRT delivery. This model can be clinically used to quantify the dosimetric uncertainty due to the interplay effect prior to the treatment delivery.

Computational model of lightness perception in high dynamic range imaging

Science.gov (United States)

Krawczyk, Grzegorz; Myszkowski, Karol; Seidel, Hans-Peter

2006-02-01

An anchoring theory of lightness perception by Gilchrist et al. [1999] explains many characteristics of human visual system such as lightness constancy and its spectacular failures which are important in the perception of images. The principal concept of this theory is the perception of complex scenes in terms of groups of consistent areas (frameworks). Such areas, following the gestalt theorists, are defined by the regions of common illumination. The key aspect of the image perception is the estimation of lightness within each framework through the anchoring to the luminance perceived as white, followed by the computation of the global lightness. In this paper we provide a computational model for automatic decomposition of HDR images into frameworks. We derive a tone mapping operator which predicts lightness perception of the real world scenes and aims at its accurate reproduction on low dynamic range displays. Furthermore, such a decomposition into frameworks opens new grounds for local image analysis in view of human perception.

Dynamics of global supply chain and electric power networks: Models, pricing analysis, and computations

Science.gov (United States)

Matsypura, Dmytro

In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following

Computational Fluid Dynamics Modeling of the Human Pulmonary Arteries with Experimental Validation.

Science.gov (United States)

Bordones, Alifer D; Leroux, Matthew; Kheyfets, Vitaly O; Wu, Yu-An; Chen, Chia-Yuan; Finol, Ender A

2018-05-21

Pulmonary hypertension (PH) is a chronic progressive disease characterized by elevated pulmonary arterial pressure, caused by an increase in pulmonary arterial impedance. Computational fluid dynamics (CFD) can be used to identify metrics representative of the stage of PH disease. However, experimental validation of CFD models is often not pursued due to the geometric complexity of the model or uncertainties in the reproduction of the required flow conditions. The goal of this work is to validate experimentally a CFD model of a pulmonary artery phantom using a particle image velocimetry (PIV) technique. Rapid prototyping was used for the construction of the patient-specific pulmonary geometry, derived from chest computed tomography angiography images. CFD simulations were performed with the pulmonary model with a Reynolds number matching those of the experiments. Flow rates, the velocity field, and shear stress distributions obtained with the CFD simulations were compared to their counterparts from the PIV flow visualization experiments. Computationally predicted flow rates were within 1% of the experimental measurements for three of the four branches of the CFD model. The mean velocities in four transversal planes of study were within 5.9 to 13.1% of the experimental mean velocities. Shear stresses were qualitatively similar between the two methods with some discrepancies in the regions of high velocity gradients. The fluid flow differences between the CFD model and the PIV phantom are attributed to experimental inaccuracies and the relative compliance of the phantom. This comparative analysis yielded valuable information on the accuracy of CFD predicted hemodynamics in pulmonary circulation models.

AIR INGRESS ANALYSIS: COMPUTATIONAL FLUID DYNAMIC MODELS

Energy Technology Data Exchange (ETDEWEB)

Chang H. Oh; Eung S. Kim; Richard Schultz; Hans Gougar; David Petti; Hyung S. Kang

2010-08-01

The Idaho National Laboratory (INL), under the auspices of the U.S. Department of Energy, is performing research and development that focuses on key phenomena important during potential scenarios that may occur in very high temperature reactors (VHTRs). Phenomena Identification and Ranking Studies to date have ranked an air ingress event, following on the heels of a VHTR depressurization, as important with regard to core safety. Consequently, the development of advanced air ingress-related models and verification and validation data are a very high priority. Following a loss of coolant and system depressurization incident, air will enter the core of the High Temperature Gas Cooled Reactor through the break, possibly causing oxidation of the in-the core and reflector graphite structure. Simple core and plant models indicate that, under certain circumstances, the oxidation may proceed at an elevated rate with additional heat generated from the oxidation reaction itself. Under postulated conditions of fluid flow and temperature, excessive degradation of the lower plenum graphite can lead to a loss of structural support. Excessive oxidation of core graphite can also lead to the release of fission products into the confinement, which could be detrimental to a reactor safety. Computational fluid dynamic model developed in this study will improve our understanding of this phenomenon. This paper presents two-dimensional and three-dimensional CFD results for the quantitative assessment of the air ingress phenomena. A portion of results of the density-driven stratified flow in the inlet pipe will be compared with results of the experimental results.

Computational fluid dynamics modeling of two-phase flow in a BWR fuel assembly

International Nuclear Information System (INIS)

Andrey Ioilev; Maskhud Samigulin; Vasily Ustinenko; Simon Lo; Adrian Tentner

2005-01-01

Full text of publication follows: The goal of this project is to develop an advanced Computational Fluid Dynamics (CFD) computer code (CFD-BWR) that allows the detailed analysis of the two-phase flow and heat transfer phenomena in a Boiling Water Reactor (BWR) fuel bundle under various operating conditions. This code will include more fundamental physical models than the current generation of sub-channel codes and advanced numerical algorithms for improved computational accuracy, robustness, and speed. It is highly desirable to understand the detailed two-phase flow phenomena inside a BWR fuel bundle. These phenomena include coolant phase changes and multiple flow regimes which directly influence the coolant interaction with fuel assembly and, ultimately, the reactor performance. Traditionally, the best analysis tools for the analysis of two-phase flow phenomena inside the BWR fuel assembly have been the sub-channel codes. However, the resolution of these codes is still too coarse for analyzing the detailed intra-assembly flow patterns, such as flow around a spacer element. Recent progress in Computational Fluid Dynamics (CFD), coupled with the rapidly increasing computational power of massively parallel computers, shows promising potential for the fine-mesh, detailed simulation of fuel assembly two-phase flow phenomena. However, the phenomenological models available in the commercial CFD programs are not as advanced as those currently being used in the sub-channel codes used in the nuclear industry. In particular, there are no models currently available which are able to reliably predict the nature of the flow regimes, and use the appropriate sub-models for those flow regimes. The CFD-BWR code is being developed as a customized module built on the foundation of the commercial CFD Code STAR-CD which provides general two-phase flow modeling capabilities. The paper describes the model development strategy which has been adopted by the development team for the

Computational fluid dynamics a practical approach

CERN Document Server

Tu, Jiyuan; Liu, Chaoqun

2018-01-01

Computational Fluid Dynamics: A Practical Approach, Third Edition, is an introduction to CFD fundamentals and commercial CFD software to solve engineering problems. The book is designed for a wide variety of engineering students new to CFD, and for practicing engineers learning CFD for the first time. Combining an appropriate level of mathematical background, worked examples, computer screen shots, and step-by-step processes, this book walks the reader through modeling and computing, as well as interpreting CFD results. This new edition has been updated throughout, with new content and improved figures, examples and problems.

Simulation of windblown dust transport from a mine tailings impoundment using a computational fluid dynamics model

Science.gov (United States)

Stovern, Michael; Felix, Omar; Csavina, Janae; Rine, Kyle P.; Russell, MacKenzie R.; Jones, Robert M.; King, Matt; Betterton, Eric A.; Sáez, A. Eduardo

2014-01-01

Mining operations are potential sources of airborne particulate metal and metalloid contaminants through both direct smelter emissions and wind erosion of mine tailings. The warmer, drier conditions predicted for the Southwestern US by climate models may make contaminated atmospheric dust and aerosols increasingly important, due to potential deleterious effects on human health and ecology. Dust emissions and dispersion of dust and aerosol from the Iron King Mine tailings in Dewey-Humboldt, Arizona, a Superfund site, are currently being investigated through in situ field measurements and computational fluid dynamics modeling. These tailings are heavily contaminated with lead and arsenic. Using a computational fluid dynamics model, we model dust transport from the mine tailings to the surrounding region. The model includes gaseous plume dispersion to simulate the transport of the fine aerosols, while individual particle transport is used to track the trajectories of larger particles and to monitor their deposition locations. In order to improve the accuracy of the dust transport simulations, both regional topographical features and local weather patterns have been incorporated into the model simulations. Results show that local topography and wind velocity profiles are the major factors that control deposition. PMID:25621085

Simulation of windblown dust transport from a mine tailings impoundment using a computational fluid dynamics model.

Science.gov (United States)

Stovern, Michael; Felix, Omar; Csavina, Janae; Rine, Kyle P; Russell, MacKenzie R; Jones, Robert M; King, Matt; Betterton, Eric A; Sáez, A Eduardo

2014-09-01

Mining operations are potential sources of airborne particulate metal and metalloid contaminants through both direct smelter emissions and wind erosion of mine tailings. The warmer, drier conditions predicted for the Southwestern US by climate models may make contaminated atmospheric dust and aerosols increasingly important, due to potential deleterious effects on human health and ecology. Dust emissions and dispersion of dust and aerosol from the Iron King Mine tailings in Dewey-Humboldt, Arizona, a Superfund site, are currently being investigated through in situ field measurements and computational fluid dynamics modeling. These tailings are heavily contaminated with lead and arsenic. Using a computational fluid dynamics model, we model dust transport from the mine tailings to the surrounding region. The model includes gaseous plume dispersion to simulate the transport of the fine aerosols, while individual particle transport is used to track the trajectories of larger particles and to monitor their deposition locations. In order to improve the accuracy of the dust transport simulations, both regional topographical features and local weather patterns have been incorporated into the model simulations. Results show that local topography and wind velocity profiles are the major factors that control deposition.

Computationally efficient dynamic modeling of robot manipulators with multiple flexible-links using acceleration-based discrete time transfer matrix method

DEFF Research Database (Denmark)

Zhang, Xuping; Sørensen, Rasmus; RahbekIversen, Mathias

2018-01-01

This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations, and then is linea......This paper presents a novel and computationally efficient modeling method for the dynamics of flexible-link robot manipulators. In this method, a robot manipulator is decomposed into components/elements. The component/element dynamics is established using Newton–Euler equations......, and then is linearized based on the acceleration-based state vector. The transfer matrices for each type of components/elements are developed, and used to establish the system equations of a flexible robot manipulator by concatenating the state vector from the base to the end-effector. With this strategy, the size...... manipulators, and only involves calculating and transferring component/element dynamic equations that have small size. The numerical simulations and experimental testing of flexible-link manipulators are conducted to validate the proposed methodologies....

Dynamic Modelling Of A SCARA Robot

Science.gov (United States)

Turiel, J. Perez; Calleja, R. Grossi; Diez, V. Gutierrez

1987-10-01

This paper describes a method for modelling industrial robots that considers dynamic approach to manipulation systems motion generation, obtaining the complete dynamic model for the mechanic part of the robot and taking into account the dynamic effect of actuators acting at the joints. For a four degree of freedom SCARA robot we obtain the dynamic model for the basic (minimal) configuration, that is, the three degrees of freedom that allow us to place the robot end effector in a desired point, using the Lagrange Method to obtain the dynamic equations in matrix form. The manipulator is considered to be a set of rigid bodies inter-connected by joints in the form of simple kinematic pairs. Then, the state space model is obtained for the actuators that move the robot joints, uniting the models of the single actuators, that is, two DC permanent magnet servomotors and an electrohydraulic actuator. Finally, using a computer simulation program written in FORTRAN language, we can compute the matrices of the complete model.

The comparisons of computational models of pavement due to the dynamic load act

Directory of Open Access Journals (Sweden)

Valašková Veronika

2017-01-01

Full Text Available Finite element method (FEM is frequently used to solve current problems of the structural mechanics in engineering practice. The dynamic interaction of the two systems is one of the topics that can be solved using FEM. To simplify the solution of the interaction, it is possible to divide the system in two independent subsystems, vehicle and pavement. Computing software ADINA, based on the principles of the finite element modelling, was adopted to solve the given problem. The results from the first computational model can be used as the inputs for the second model. To analyse stress state of the pavement with different composition, three specific types of pavements were selected – concrete pavement, semi-rigid pavement and flexible pavement. The pavements represent the typical pavement types used for the regular road structures. This article is focused on the analysis of the stress state and the displacements of the pavement induced by the moving load from the traffic.

The Modeling and Complexity of Dynamical Systems by Means of Computation and Information Theories

Directory of Open Access Journals (Sweden)

Robert Logozar

2011-12-01

Full Text Available We present the modeling of dynamical systems and finding of their complexity indicators by the use of concepts from computation and information theories, within the framework of J. P. Crutchfield's theory of  ε-machines. A short formal outline of the  ε-machines is given. In this approach, dynamical systems are analyzed directly from the time series that is received from a properly adjusted measuring instrument. The binary strings are parsed through the parse tree, within which morphologically and probabilistically unique subtrees or morphs are recognized as system states. The outline and precise interrelation of the information-theoretic entropies and complexities emanating from the model is given. The paper serves also as a theoretical foundation for the future presentation of the DSA program that implements the  ε-machines modeling up to the stochastic finite automata level.

Engineering applications of computational fluid dynamics

CERN Document Server

Awang, Mokhtar

2015-01-01

This volume presents the results of Computational Fluid Dynamics (CFD) analysis that can be used for conceptual studies of product design, detail product development, process troubleshooting. It demonstrates the benefit of CFD modeling as a cost saving, timely, safe and easy to scale-up methodology.

APPLICATION OF COMPUTATIONAL FLUID DYNAMICS MODELLING TO A HORIZONTAL SEDIMENTATION TANK IN IRAQ

OpenAIRE

Ali Hadi GHAWI

2017-01-01

Computational Fluid Dynamics modeling has been applied to examine the hydrodynamic behavior of water treatment sedimentation tanks at Baghdad Water Works, operated by Alkurech Water in Baghdad in Iraq. The existing tanks perform poorly at current flows and flow is unevenly split among online tanks, Therefore, CFD was used to investigate velocity profiles at current and projected loadings for the existing basins. Results from the CFD analysis were used to develop retrofit strategies to improve...

ADDRESSING HUMAN EXPOSURE TO AIR POLLUTANTS AROUND BUILDINGS IN URBAN AREAS WITH COMPUTATIONAL FLUID DYNAMICS (CFD) MODELS

Science.gov (United States)

Computational Fluid Dynamics (CFD) simulations provide a number of unique opportunities for expanding and improving capabilities for modeling exposures to environmental pollutants. The US Environmental Protection Agency's National Exposure Research Laboratory (NERL) has been c...

A discrete force allocation algorithm for modelling wind turbines in computational fluid dynamics

DEFF Research Database (Denmark)

Réthoré, Pierre-Elouan; Sørensen, Niels N.

2012-01-01

at the position of the wind turbine rotor to estimate correctly the power production and the rotor loading. The method proposed in this paper solves this issue by spreading the force on the direct neighbouring cells and applying an equivalent pressure jump at the cell faces. This can potentially open......This paper describes an algorithm for allocating discrete forces in computational fluid dynamics (CFD). Discrete forces are useful in wind energy CFD. They are used as an approximation of the wind turbine blades’ action on the wind (actuator disc/line), to model forests and to model turbulent...

A Computational Model Based on Multi-Regional Calcium Imaging Represents the Spatio-Temporal Dynamics in a Caenorhabditis elegans Sensory Neuron.

Directory of Open Access Journals (Sweden)

Masahiro Kuramochi

Full Text Available Due to the huge number of neuronal cells in the brain and their complex circuit formation, computer simulation of neuronal activity is indispensable to understanding whole brain dynamics. Recently, various computational models have been developed based on whole-brain calcium imaging data. However, these analyses monitor only the activity of neuronal cell bodies and treat the cells as point unit. This point-neuron model is inexpensive in computational costs, but the model is unrealistically simplistic at representing intact neural activities in the brain. Here, we describe a novel three-unit Ordinary Differential Equation (ODE model based on the neuronal responses derived from a Caenorhabditis elegans salt-sensing neuron. We recorded calcium responses in three regions of the ASER neuron using a simple downstep of NaCl concentration. Our simple ODE model generated from a single recording can adequately reproduce and predict the temporal responses of each part of the neuron to various types of NaCl concentration changes. Our strategy which combines a simple recording data and an ODE mathematical model may be extended to realistically understand whole brain dynamics by computational simulation.

A Computation Fluid Dynamic Model for Gas Lift Process Simulation in a Vertical Oil Well

Directory of Open Access Journals (Sweden)

Kadivar Arash

2017-03-01

Full Text Available Continuous gas-lift in a typical oil well was simulated using computational fluid dynamic (CFD technique. A multi fluid model based on the momentum transfer between liquid and gas bubbles was employed to simulate two-phase flow in a vertical pipe. The accuracy of the model was investigated through comparison of numerical predictions with experimental data. The model then was used to study the dynamic behaviour of the two-phase flow around injection point in details. The predictions by the model were compared with other empirical correlations, as well. To obtain an optimum condition of gas-lift, the influence of the effective parameters including the quantity of injected gas, tubing diameter and bubble size distribution were investigated. The results revealed that increasing tubing diameter, the injected gas rate and decreasing bubble diameter improve gas-lift performance.

Dynamic modelling of an adsorption storage tank using a hybrid approach combining computational fluid dynamics and process simulation

Science.gov (United States)

Mota, J.P.B.; Esteves, I.A.A.C.; Rostam-Abadi, M.

2004-01-01

A computational fluid dynamics (CFD) software package has been coupled with the dynamic process simulator of an adsorption storage tank for methane fuelled vehicles. The two solvers run as independent processes and handle non-overlapping portions of the computational domain. The codes exchange data on the boundary interface of the two domains to ensure continuity of the solution and of its gradient. A software interface was developed to dynamically suspend and activate each process as necessary, and be responsible for data exchange and process synchronization. This hybrid computational tool has been successfully employed to accurately simulate the discharge of a new tank design and evaluate its performance. The case study presented here shows that CFD and process simulation are highly complementary computational tools, and that there are clear benefits to be gained from a close integration of the two. ?? 2004 Elsevier Ltd. All rights reserved.

Computational fluid dynamics modeling of a lithium/thionyl chloride battery with electrolyte flow

Energy Technology Data Exchange (ETDEWEB)

Gu, W.B.; Wang, C.Y.; Weidner, J.W.; Jungst, R.G.; Nagasubramanian, G.

2000-02-01

A two-dimensional model is developed to simulate discharge of a lithium/thionyl chloride primary battery. As in earlier one-dimensional models, the model accounts for transport of species and charge, and electrode porosity variations and electrolyte flow induced by the volume reduction caused by electrochemical reactions. Numerical simulations are performed using a finite volume method of computational fluid dynamics. The predicted discharge curves for various temperatures show good agreement with published experimental data, and are essentially identical to results published for one-dimensional models. The detailed two-dimensional flow simulations show that the electrolyte is replenished from the cell head space predominantly through the separator into the front of the cathode during most parts of the discharge, especially for higher cell temperatures.

Computational Fluid and Particle Dynamics in the Human Respiratory System

CERN Document Server

Tu, Jiyuan; Ahmadi, Goodarz

2013-01-01

Traditional research methodologies in the human respiratory system have always been challenging due to their invasive nature. Recent advances in medical imaging and computational fluid dynamics (CFD) have accelerated this research. This book compiles and details recent advances in the modelling of the respiratory system for researchers, engineers, scientists, and health practitioners. It breaks down the complexities of this field and provides both students and scientists with an introduction and starting point to the physiology of the respiratory system, fluid dynamics and advanced CFD modeling tools. In addition to a brief introduction to the physics of the respiratory system and an overview of computational methods, the book contains best-practice guidelines for establishing high-quality computational models and simulations. Inspiration for new simulations can be gained through innovative case studies as well as hands-on practice using pre-made computational code. Last but not least, students and researcher...

Computation of magnetic suspension of maglev systems using dynamic circuit theory

Science.gov (United States)

He, J. L.; Rote, D. M.; Coffey, H. T.

1992-01-01

Dynamic circuit theory is applied to several magnetic suspensions associated with maglev systems. These suspension systems are the loop-shaped coil guideway, the figure-eight-shaped null-flux coil guideway, and the continuous sheet guideway. Mathematical models, which can be used for the development of computer codes, are provided for each of these suspension systems. The differences and similarities of the models in using dynamic circuit theory are discussed in the paper. The paper emphasizes the transient and dynamic analysis and computer simulation of maglev systems. In general, the method discussed here can be applied to many electrodynamic suspension system design concepts. It is also suited for the computation of the performance of maglev propulsion systems. Numerical examples are presented in the paper.

Dissertation Defense Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

Science.gov (United States)

Groves, Curtis Edward

2014-01-01

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional "validation by test only" mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics

Dissertation Defense: Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

Science.gov (United States)

Groves, Curtis Edward

2014-01-01

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional validation by test only mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions.Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations. This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions

Computational Fluid Dynamics (CFD) Technology Programme 1995- 1999

Energy Technology Data Exchange (ETDEWEB)

Haekkinen, R.J.; Hirsch, C.; Krause, E.; Kytoemaa, H.K. [eds.

1997-12-31

The report is a mid-term evaluation of the Computational Fluid Dynamics (CFD) Technology Programme started by Technology Development Centre Finland (TEKES) in 1995 as a five-year initiative to be concluded in 1999. The main goal of the programme is to increase the know-how and application of CFD in Finnish industry, to coordinate and thus provide a better basis for co-operation between national CFD activities and encouraging research laboratories and industry to establish co-operation with the international CFD community. The projects of the programme focus on the following areas: (1) studies of modeling the physics and dynamics of the behaviour of fluid material, (2) expressing the physical models in a numerical mode and developing a computer codes, (3) evaluating and testing current physical models and developing new ones, (4) developing new numerical algorithms, solvers, and pre- and post-processing software, and (5) applying the new computational tools to problems relevant to their ultimate industrial use. The report consists of two sections. The first considers issues concerning the whole programme and the second reviews each project

HIGH-FIDELITY SIMULATION-DRIVEN MODEL DEVELOPMENT FOR COARSE-GRAINED COMPUTATIONAL FLUID DYNAMICS

Energy Technology Data Exchange (ETDEWEB)

Hanna, Botros N.; Dinh, Nam T.; Bolotnov, Igor A.

2016-06-01

Nuclear reactor safety analysis requires identifying various credible accident scenarios and determining their consequences. For a full-scale nuclear power plant system behavior, it is impossible to obtain sufficient experimental data for a broad range of risk-significant accident scenarios. In single-phase flow convective problems, Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) can provide us with high fidelity results when physical data are unavailable. However, these methods are computationally expensive and cannot be afforded for simulation of long transient scenarios in nuclear accidents despite extraordinary advances in high performance scientific computing over the past decades. The major issue is the inability to make the transient computation parallel, thus making number of time steps required in high-fidelity methods unaffordable for long transients. In this work, we propose to apply a high fidelity simulation-driven approach to model sub-grid scale (SGS) effect in Coarse Grained Computational Fluid Dynamics CG-CFD. This approach aims to develop a statistical surrogate model instead of the deterministic SGS model. We chose to start with a turbulent natural convection case with volumetric heating in a horizontal fluid layer with a rigid, insulated lower boundary and isothermal (cold) upper boundary. This scenario of unstable stratification is relevant to turbulent natural convection in a molten corium pool during a severe nuclear reactor accident, as well as in containment mixing and passive cooling. The presented approach demonstrates how to create a correction for the CG-CFD solution by modifying the energy balance equation. A global correction for the temperature equation proves to achieve a significant improvement to the prediction of steady state temperature distribution through the fluid layer.

Agent Based Modeling on Organizational Dynamics of Terrorist Network

OpenAIRE

Bo Li; Duoyong Sun; Renqi Zhu; Ze Li

2015-01-01

Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model ...

Computational Fluid Dynamics Modeling of a Lithium/Thionyl Chloride Battery with Electrolyte Flow

Energy Technology Data Exchange (ETDEWEB)

Gu, W.B.; Jungst, Rudolph G.; Nagasubramanian, Ganesan; Wang, C.Y.; Weidner, John.

1999-06-11

A two-dimensional model is developed to simulate discharge of a lithium/thionyl chloride primary battery. The model accounts for not only transport of species and charge, but also the electrode porosity variations and the electrolyte flow induced by the volume reduction caused by electrochemical reactions. Numerical simulations are performed using a finite volume method of computational fluid dynamics. The predicted discharge curves for various temperatures are compared to the experimental data with excellent agreement. Moreover, the simulation results. in conjunction with computer visualization and animation techniques, confirm that cell utilization in the temperature and current range of interest is limited by pore plugging or clogging of the front side of the cathode as a result of LiCl precipitation. The detailed two-dimensional flow simulation also shows that the electrolyte is replenished from the cell header predominantly through the separator into the front of the cathode during most parts of the discharge, especially for higher cell temperatures.

Computational fluid dynamic model for glycerol gasification in supercritical water in a tee junction shaped cylindrical reactor

NARCIS (Netherlands)

Yukananto, Riza; Pozarlik, Artur K.; Brem, Gerrit

2018-01-01

Gasification in supercritical water is a very promising technology to process wet biomass into a valuable gas. Providing insight of the process behavior is therefore very important. In this research a computational fluid dynamic model is developed to investigate glycerol gasification in

Development of a dynamic computational model of social cognitive theory.

Science.gov (United States)

Riley, William T; Martin, Cesar A; Rivera, Daniel E; Hekler, Eric B; Adams, Marc A; Buman, Matthew P; Pavel, Misha; King, Abby C

2016-12-01

Social cognitive theory (SCT) is among the most influential theories of behavior change and has been used as the conceptual basis of health behavior interventions for smoking cessation, weight management, and other health behaviors. SCT and other behavior theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed as new technologies allow for intensive longitudinal measures and interventions adapted from these inputs. These within-person explanatory theoretical applications can be modeled as dynamical systems. SCT constructs, such as reciprocal determinism, are inherently dynamical in nature, but SCT has not been modeled as a dynamical system. This paper describes the development of a dynamical system model of SCT using fluid analogies and control systems principles drawn from engineering. Simulations of this model were performed to assess if the model performed as predicted based on theory and empirical studies of SCT. This initial model generates precise and testable quantitative predictions for future intensive longitudinal research. Dynamic modeling approaches provide a rigorous method for advancing health behavior theory development and refinement and for guiding the development of more potent and efficient interventions.

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

OpenAIRE

Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constrain...

Privacy context model for dynamic privacy adaptation in ubiquitous computing

NARCIS (Netherlands)

Schaub, Florian; Koenings, Bastian; Dietzel, Stefan; Weber, M.; Kargl, Frank

Ubiquitous computing is characterized by the merger of physical and virtual worlds as physical artifacts gain digital sensing, processing, and communication capabilities. Maintaining an appropriate level of privacy in the face of such complex and often highly dynamic systems is challenging. We argue

Corruption dynamics model

Science.gov (United States)

Malafeyev, O. A.; Nemnyugin, S. A.; Rylow, D.; Kolpak, E. P.; Awasthi, Achal

2017-07-01

The corruption dynamics is analyzed by means of the lattice model which is similar to the three-dimensional Ising model. Agents placed at nodes of the corrupt network periodically choose to perfom or not to perform the act of corruption at gain or loss while making decisions based on the process history. The gain value and its dynamics are defined by means of the Markov stochastic process modelling with parameters established in accordance with the influence of external and individual factors on the agent's gain. The model is formulated algorithmically and is studied by means of the computer simulation. Numerical results are obtained which demonstrate asymptotic behaviour of the corruption network under various conditions.

Computational fluid dynamic modelling of cavitation

Science.gov (United States)

Deshpande, Manish; Feng, Jinzhang; Merkle, Charles L.

1993-01-01

Models in sheet cavitation in cryogenic fluids are developed for use in Euler and Navier-Stokes codes. The models are based upon earlier potential-flow models but enable the cavity inception point, length, and shape to be determined as part of the computation. In the present paper, numerical solutions are compared with experimental measurements for both pressure distribution and cavity length. Comparisons between models are also presented. The CFD model provides a relatively simple modification to an existing code to enable cavitation performance predictions to be included. The analysis also has the added ability of incorporating thermodynamic effects of cryogenic fluids into the analysis. Extensions of the current two-dimensional steady state analysis to three-dimensions and/or time-dependent flows are, in principle, straightforward although geometrical issues become more complicated. Linearized models, however offer promise of providing effective cavitation modeling in three-dimensions. This analysis presents good potential for improved understanding of many phenomena associated with cavity flows.

Static/dynamic fluid-structure interaction analysis for 3-D rotary blade model

International Nuclear Information System (INIS)

Kim, Dong Hyun; Kim, Yu Sung; Kim, Dong Man; Park, Kang Kyun

2009-01-01

In this study, static/dynamic fluid-structure interaction analyses have been conducted for a 3D rotary blade model like a turbo-machinery or wind turbine blade. Advanced computational analysis system based on Computational Fluid Dynamics (CFD) and Computational Structural Dynamics (CSD) has been developed in order to investigate detailed dynamic responses of rotary type models. Fluid domains are modeled using the computational grid system with local grid deforming techniques. Reynolds-averaged Navier-Stokes equations with various turbulence model are solved for unsteady flow problems of the rotating blade model. Detailed static/dynamic responses and instantaneous pressure contours on the blade surfaces considering flow-separation effects are presented to show the multi-physical phenomenon of the rotating blades.

Structure and dynamics of amorphous polymers: computer simulations compared to experiment and theory

International Nuclear Information System (INIS)

Paul, Wolfgang; Smith, Grant D

2004-01-01

This contribution considers recent developments in the computer modelling of amorphous polymeric materials. Progress in our capabilities to build models for the computer simulation of polymers from the detailed atomistic scale up to coarse-grained mesoscopic models, together with the ever-improving performance of computers, have led to important insights from computer simulations into the structural and dynamic properties of amorphous polymers. Structurally, chain connectivity introduces a range of length scales from that of the chemical bond to the radius of gyration of the polymer chain covering 2-4 orders of magnitude. Dynamically, this range of length scales translates into an even larger range of time scales observable in relaxation processes in amorphous polymers ranging from about 10 -13 to 10 -3 s or even to 10 3 s when glass dynamics is concerned. There is currently no single simulation technique that is able to describe all these length and time scales efficiently. On large length and time scales basic topology and entropy become the governing properties and this fact can be exploited using computer simulations of coarse-grained polymer models to study universal aspects of the structure and dynamics of amorphous polymers. On the largest length and time scales chain connectivity is the dominating factor leading to the strong increase in longest relaxation times described within the reptation theory of polymer melt dynamics. Recently, many of the universal aspects of this behaviour have been further elucidated by computer simulations of coarse-grained polymer models. On short length scales the detailed chemistry and energetics of the polymer are important, and one has to be able to capture them correctly using chemically realistic modelling of specific polymers, even when the aim is to extract generic physical behaviour exhibited by the specific chemistry. Detailed studies of chemically realistic models highlight the central importance of torsional dynamics

Neural Computations in a Dynamical System with Multiple Time Scales.

Science.gov (United States)

Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

Simple Models for the Dynamic Modeling of Rotating Tires

Directory of Open Access Journals (Sweden)

J.C. Delamotte

2008-01-01

Full Text Available Large Finite Element (FE models of tires are currently used to predict low frequency behavior and to obtain dynamic model coefficients used in multi-body models for riding and comfort. However, to predict higher frequency behavior, which may explain irregular wear, critical rotating speeds and noise radiation, FE models are not practical. Detailed FE models are not adequate for optimization and uncertainty predictions either, as in such applications the dynamic solution must be computed a number of times. Therefore, there is a need for simpler models that can capture the physics of the tire and be used to compute the dynamic response with a low computational cost. In this paper, the spectral (or continuous element approach is used to derive such a model. A circular beam spectral element that takes into account the string effect is derived, and a method to simulate the response to a rotating force is implemented in the frequency domain. The behavior of a circular ring under different internal pressures is investigated using modal and frequency/wavenumber representations. Experimental results obtained with a real untreaded truck tire are presented and qualitatively compared with the simple model predictions with good agreement. No attempt is made to obtain equivalent parameters for the simple model from the real tire results. On the other hand, the simple model fails to represent the correct variation of the quotient of the natural frequency by the number of circumferential wavelengths with the mode count. Nevertheless, some important features of the real tire dynamic behavior, such as the generation of standing waves and part of the frequency/wavenumber behavior, can be investigated using the proposed simplified model.

Sierra toolkit computational mesh conceptual model

International Nuclear Information System (INIS)

Baur, David G.; Edwards, Harold Carter; Cochran, William K.; Williams, Alan B.; Sjaardema, Gregory D.

2010-01-01

The Sierra Toolkit computational mesh is a software library intended to support massively parallel multi-physics computations on dynamically changing unstructured meshes. This domain of intended use is inherently complex due to distributed memory parallelism, parallel scalability, heterogeneity of physics, heterogeneous discretization of an unstructured mesh, and runtime adaptation of the mesh. Management of this inherent complexity begins with a conceptual analysis and modeling of this domain of intended use; i.e., development of a domain model. The Sierra Toolkit computational mesh software library is designed and implemented based upon this domain model. Software developers using, maintaining, or extending the Sierra Toolkit computational mesh library must be familiar with the concepts/domain model presented in this report.

Nonlinear dynamics as an engine of computation.

Science.gov (United States)

Kia, Behnam; Lindner, John F; Ditto, William L

2017-03-06

Control of chaos teaches that control theory can tame the complex, random-like behaviour of chaotic systems. This alliance between control methods and physics-cybernetical physics-opens the door to many applications, including dynamics-based computing. In this article, we introduce nonlinear dynamics and its rich, sometimes chaotic behaviour as an engine of computation. We review our work that has demonstrated how to compute using nonlinear dynamics. Furthermore, we investigate the interrelationship between invariant measures of a dynamical system and its computing power to strengthen the bridge between physics and computation.This article is part of the themed issue 'Horizons of cybernetical physics'. © 2017 The Author(s).

Moving on to the modeling and simulation using computational fluid dynamics

International Nuclear Information System (INIS)

Norasalwa Zakaria; Rohyiza Baan; Muhd Noor Muhd Yunus

2006-01-01

The heat is on but not at the co-combustor plant. Using the Computational Fluid Dynamics (CFD), modeling and simulation of an incinerator has been made easy and possible from the comfort of cozy room. CFD has become an important design tool in nearly every industrial field because it provides understanding of flow patterns. CFD provide values for fluid velocity, fluid temperature, pressure and species concentrations throughout a flow domain. MINT has acquired a complete CFD software recently, consisting of GAMBIT, which is use to build geometry and meshing, and FLUENT as the processor or solver. This paper discusses on several trial runs that was carried out on several parts of the co-combustor plant namely the under fire section and the mixing chamber section

Computational Methods in Stochastic Dynamics Volume 2

CERN Document Server

Stefanou, George; Papadopoulos, Vissarion

2013-01-01

The considerable influence of inherent uncertainties on structural behavior has led the engineering community to recognize the importance of a stochastic approach to structural problems. Issues related to uncertainty quantification and its influence on the reliability of the computational models are continuously gaining in significance. In particular, the problems of dynamic response analysis and reliability assessment of structures with uncertain system and excitation parameters have been the subject of continuous research over the last two decades as a result of the increasing availability of powerful computing resources and technology.   This book is a follow up of a previous book with the same subject (ISBN 978-90-481-9986-0) and focuses on advanced computational methods and software tools which can highly assist in tackling complex problems in stochastic dynamic/seismic analysis and design of structures. The selected chapters are authored by some of the most active scholars in their respective areas and...

Computational fluid dynamic applications

Energy Technology Data Exchange (ETDEWEB)

Chang, S.-L.; Lottes, S. A.; Zhou, C. Q.

2000-04-03

The rapid advancement of computational capability including speed and memory size has prompted the wide use of computational fluid dynamics (CFD) codes to simulate complex flow systems. CFD simulations are used to study the operating problems encountered in system, to evaluate the impacts of operation/design parameters on the performance of a system, and to investigate novel design concepts. CFD codes are generally developed based on the conservation laws of mass, momentum, and energy that govern the characteristics of a flow. The governing equations are simplified and discretized for a selected computational grid system. Numerical methods are selected to simplify and calculate approximate flow properties. For turbulent, reacting, and multiphase flow systems the complex processes relating to these aspects of the flow, i.e., turbulent diffusion, combustion kinetics, interfacial drag and heat and mass transfer, etc., are described in mathematical models, based on a combination of fundamental physics and empirical data, that are incorporated into the code. CFD simulation has been applied to a large variety of practical and industrial scale flow systems.

Accidental release of chlorine in Chicago: Coupling of an exposure model with a Computational Fluid Dynamics model

Science.gov (United States)

Sanchez, E. Y.; Colman Lerner, J. E.; Porta, A.; Jacovkis, P. M.

2013-01-01

The adverse health effects of the release of hazardous substances into the atmosphere continue being a matter of concern, especially in densely populated urban regions. Emergency responders need to have estimates of these adverse health effects in the local population to aid planning, emergency response, and recovery efforts. For this purpose, models that predict the transport and dispersion of hazardous materials are as necessary as those that estimate the adverse health effects in the population. In this paper, we present the results obtained by coupling a Computational Fluid Dynamics model, FLACS (FLame ACceleration Simulator), with an exposure model, DDC (Damage Differential Coupling). This coupled model system is applied to a scenario of hypothetical release of chlorine with obstacles, such as buildings, and the results show how it is capable of predicting the atmospheric dispersion of hazardous chemicals, and the adverse health effects in the exposed population, to support decision makers both in charge of emergency planning and in charge of real-time response. The results obtained show how knowing the influence of obstacles in the trajectory of the toxic cloud and in the diffusion of the pollutants transported, and obtaining dynamic information of the potentially affected population and of associated symptoms, contribute to improve the planning of the protection and response measures.

Vehicle - Bridge interaction, comparison of two computing models

Science.gov (United States)

Melcer, Jozef; Kuchárová, Daniela

2017-07-01

The paper presents the calculation of the bridge response on the effect of moving vehicle moves along the bridge with various velocities. The multi-body plane computing model of vehicle is adopted. The bridge computing models are created in two variants. One computing model represents the bridge as the Bernoulli-Euler beam with continuously distributed mass and the second one represents the bridge as the lumped mass model with 1 degrees of freedom. The mid-span bridge dynamic deflections are calculated for both computing models. The results are mutually compared and quantitative evaluated.

Computational fluid dynamics in ventilation design

CERN Document Server

Allard, Francis; Awbi, Hazim B; Davidson, Lars; Schälin, Alois

2007-01-01

CFD-calculations have been rapidly developed to a powerful tool for the analysis of air pollution distribution in various spaces. However, the user of CFD-calculation should be aware of the basic principles of calculations and specifically the boundary conditions. Computational Fluid Dynamics (CFD) – in Ventilation Design models is written by a working group of highly qualified international experts representing research, consulting and design.

Surface Modeling, Grid Generation, and Related Issues in Computational Fluid Dynamic (CFD) Solutions

Science.gov (United States)

Choo, Yung K. (Compiler)

1995-01-01

The NASA Steering Committee for Surface Modeling and Grid Generation (SMAGG) sponsored a workshop on surface modeling, grid generation, and related issues in Computational Fluid Dynamics (CFD) solutions at Lewis Research Center, Cleveland, Ohio, May 9-11, 1995. The workshop provided a forum to identify industry needs, strengths, and weaknesses of the five grid technologies (patched structured, overset structured, Cartesian, unstructured, and hybrid), and to exchange thoughts about where each technology will be in 2 to 5 years. The workshop also provided opportunities for engineers and scientists to present new methods, approaches, and applications in SMAGG for CFD. This Conference Publication (CP) consists of papers on industry overview, NASA overview, five grid technologies, new methods/ approaches/applications, and software systems.

Computational Model and Numerical Simulation for Submerged Mooring Monitoring Platform’s Dynamical Response

Directory of Open Access Journals (Sweden)

He Kongde

2015-01-01

Full Text Available Computational model and numerical simulation for submerged mooring monitoring platform were formulated aimed at the dynamical response by the action of flow force, which based on Hopkinson impact load theory, taken into account the catenoid effect of mooring cable and revised the difference of tension and tangential direction action force by equivalent modulus of elasticity. Solved the equation by hydraulics theory and structural mechanics theory of oceaneering, studied the response of buoy on flow force. The validity of model were checked and the results were in good agreement; the result show the buoy will engender biggish heave and swaying displacement, but the swaying displacement got stable quickly and the heaven displacement cause vibration for the vortex-induced action by the flow.

Computationally Modeling Interpersonal Trust

Directory of Open Access Journals (Sweden)

Jin Joo eLee

2013-12-01

Full Text Available We present a computational model capable of predicting—above human accuracy—the degree of trust a person has toward their novel partner by observing the trust-related nonverbal cues expressed in their social interaction. We summarize our prior work, in which we identify nonverbal cues that signal untrustworthy behavior and also demonstrate the human mind’s readiness to interpret those cues to assess the trustworthiness of a social robot. We demonstrate that domain knowledge gained from our prior work using human-subjects experiments, when incorporated into the feature engineering process, permits a computational model to outperform both human predictions and a baseline model built in naivete' of this domain knowledge. We then present the construction of hidden Markov models to incorporate temporal relationships among the trust-related nonverbal cues. By interpreting the resulting learned structure, we observe that models built to emulate different levels of trust exhibit different sequences of nonverbal cues. From this observation, we derived sequence-based temporal features that further improve the accuracy of our computational model. Our multi-step research process presented in this paper combines the strength of experimental manipulation and machine learning to not only design a computational trust model but also to further our understanding of the dynamics of interpersonal trust.

A Computational Fluid Dynamics Algorithm on a Massively Parallel Computer

Science.gov (United States)

Jespersen, Dennis C.; Levit, Creon

1989-01-01

The discipline of computational fluid dynamics is demanding ever-increasing computational power to deal with complex fluid flow problems. We investigate the performance of a finite-difference computational fluid dynamics algorithm on a massively parallel computer, the Connection Machine. Of special interest is an implicit time-stepping algorithm; to obtain maximum performance from the Connection Machine, it is necessary to use a nonstandard algorithm to solve the linear systems that arise in the implicit algorithm. We find that the Connection Machine ran achieve very high computation rates on both explicit and implicit algorithms. The performance of the Connection Machine puts it in the same class as today's most powerful conventional supercomputers.

Computational Fluid Dynamics Modeling Of Scaled Hanford Double Shell Tank Mixing - CFD Modeling Sensitivity Study Results

International Nuclear Information System (INIS)

Jackson, V.L.

2011-01-01

The primary purpose of the tank mixing and sampling demonstration program is to mitigate the technical risks associated with the ability of the Hanford tank farm delivery and celtification systems to measure and deliver a uniformly mixed high-level waste (HLW) feed to the Waste Treatment and Immobilization Plant (WTP) Uniform feed to the WTP is a requirement of 24590-WTP-ICD-MG-01-019, ICD-19 - Interface Control Document for Waste Feed, although the exact definition of uniform is evolving in this context. Computational Fluid Dynamics (CFD) modeling has been used to assist in evaluating scaleup issues, study operational parameters, and predict mixing performance at full-scale.

Formal Analysis of Dynamics Within Philosophy of Mind by Computer Simulation

NARCIS (Netherlands)

Bosse, T.; Schut, M.C.; Treur, J.

2009-01-01

Computer simulations can be useful tools to support philosophers in validating their theories, especially when these theories concern phenomena showing nontrivial dynamics. Such theories are usually informal, whilst for computer simulation a formally described model is needed. In this paper, a

Computational fluid dynamics analysis of an innovative start-up method of high temperature fuel cells using dynamic 3d model

Directory of Open Access Journals (Sweden)

Kupecki Jakub

2017-03-01

Full Text Available The article presents a numerical analysis of an innovative method for starting systems based on high temperature fuel cells. The possibility of preheating the fuel cell stacks from the cold state to the nominal working conditions encounters several limitations related to heat transfer and stability of materials. The lack of rapid and safe start-up methods limits the proliferation of MCFCs and SOFCs. For that reason, an innovative method was developed and verified using the numerical analysis presented in the paper. A dynamic 3D model was developed that enables thermo-fluidic investigations and determination of measures for shortening the preheating time of the high temperature fuel cell stacks. The model was implemented in ANSYS Fluent computational fluid dynamic (CFD software and was used for verification of the proposed start-up method. The SOFC was chosen as a reference fuel cell technology for the study. Results obtained from the study are presented and discussed.

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

Science.gov (United States)

Pyle, Ryan; Rosenbaum, Robert

2017-01-01

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks.

Science.gov (United States)

Pyle, Ryan; Rosenbaum, Robert

2017-01-06

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

Generating Computational Models for Serious Gaming

NARCIS (Netherlands)

Westera, Wim

2018-01-01

Many serious games include computational models that simulate dynamic systems. These models promote enhanced interaction and responsiveness. Under the social web paradigm more and more usable game authoring tools become available that enable prosumers to create their own games, but the inclusion of

Integrating aerodynamic surface modeling for computational fluid dynamics with computer aided structural analysis, design, and manufacturing

Science.gov (United States)

Thorp, Scott A.

1992-01-01

This presentation will discuss the development of a NASA Geometry Exchange Specification for transferring aerodynamic surface geometry between LeRC systems and grid generation software used for computational fluid dynamics research. The proposed specification is based on a subset of the Initial Graphics Exchange Specification (IGES). The presentation will include discussion of how the NASA-IGES standard will accommodate improved computer aided design inspection methods and reverse engineering techniques currently being developed. The presentation is in viewgraph format.

A Comparative Study of Three Methodologies for Modeling Dynamic Stall

Science.gov (United States)

Sankar, L.; Rhee, M.; Tung, C.; ZibiBailly, J.; LeBalleur, J. C.; Blaise, D.; Rouzaud, O.

2002-01-01

During the past two decades, there has been an increased reliance on the use of computational fluid dynamics methods for modeling rotors in high speed forward flight. Computational methods are being developed for modeling the shock induced loads on the advancing side, first-principles based modeling of the trailing wake evolution, and for retreating blade stall. The retreating blade dynamic stall problem has received particular attention, because the large variations in lift and pitching moments encountered in dynamic stall can lead to blade vibrations and pitch link fatigue. Restricting to aerodynamics, the numerical prediction of dynamic stall is still a complex and challenging CFD problem, that, even in two dimensions at low speed, gathers the major difficulties of aerodynamics, such as the grid resolution requirements for the viscous phenomena at leading-edge bubbles or in mixing-layers, the bias of the numerical viscosity, and the major difficulties of the physical modeling, such as the turbulence models, the transition models, whose both determinant influences, already present in static maximal-lift or stall computations, are emphasized by the dynamic aspect of the phenomena.

Computational Fluid Dynamics Model for Saltstone Vault 4 Vapor Space

International Nuclear Information System (INIS)

Lee, Si Young

2005-01-01

Computational fluid dynamics (CFD) methods have been used to estimate the flow patterns for vapor space inside the Saltstone Vault No.4 under different operating scenarios. The purpose of this work is to examine the gas motions inside the vapor space under the current vault configurations. A CFD model took three-dimensional transient momentum-energy coupled approach for the vapor space domain of the vault. The modeling calculations were based on prototypic vault geometry and expected normal operating conditions as defined by Waste Solidification Engineering. The modeling analysis was focused on the air flow patterns near the ventilated corner zones of the vapor space inside the Saltstone vault. The turbulence behavior and natural convection mechanism used in the present model were benchmarked against the literature information and theoretical results. The verified model was applied to the Saltstone vault geometry for the transient assessment of the air flow patterns inside the vapor space of the vault region using the boundary conditions as provided by the customer. The present model considered two cases for the estimations of the flow patterns within the vapor space. One is the reference baseline case. The other is for the negative temperature gradient between the roof inner and top grout surface temperatures intended for the potential bounding condition. The flow patterns of the vapor space calculated by the CFD model demonstrate that the ambient air comes into the vapor space of the vault through the lower-end ventilation hole, and it gets heated up by the Benard-cell type circulation before leaving the vault via the higher-end ventilation hole. The calculated results are consistent with the literature information

Computational fluid dynamics model of avian tracheal temperature control as a model for extant and extinct animals.

Science.gov (United States)

Sverdlova, N S; Arkali, F; Witzel, U; Perry, S F

2013-10-01

Respiratory evaporative cooling is an important mechanism of temperature control in bird. A computational simulation of the breathing cycle, heat and water loss in anatomical avian trachea/air sac model has not previously been conducted. We report a first attempt to simulate a breathing cycle in a three-dimensional model of avian trachea and air sacs (domestic fowl) using transient computational fluid dynamics. The airflow in the trachea of the model is evoked by changing the volume of the air sacs based on the measured tidal volume and inspiratory/expiratory times for the domestic fowl. We compare flow parameters and heat transfer results with in vivo data and with our previously reported results for a two-dimensional model. The total respiratory heat loss corresponds to about 13-19% of the starvation metabolic rate of domestic fowl. The present study can lend insight into a possible thermoregulatory function in species with long necks and/or a very long trachea, as found in swans and birds of paradise. Assuming the structure of the sauropod dinosaur respiratory system was close to avian, the simulation of the respiratory temperature control (using convective and evaporative cooling) in the extensively experimentally studied domestic fowl may also help in making simulations of respiratory heat control in these extinct animals. Copyright © 2013 Elsevier B.V. All rights reserved.

Fluid Dynamics Theory, Computation, and Numerical Simulation

CERN Document Server

Pozrikidis, Constantine

2009-01-01

Fluid Dynamics: Theory, Computation, and Numerical Simulation is the only available book that extends the classical field of fluid dynamics into the realm of scientific computing in a way that is both comprehensive and accessible to the beginner. The theory of fluid dynamics, and the implementation of solution procedures into numerical algorithms, are discussed hand-in-hand and with reference to computer programming. This book is an accessible introduction to theoretical and computational fluid dynamics (CFD), written from a modern perspective that unifies theory and numerical practice. There are several additions and subject expansions in the Second Edition of Fluid Dynamics, including new Matlab and FORTRAN codes. Two distinguishing features of the discourse are: solution procedures and algorithms are developed immediately after problem formulations are presented, and numerical methods are introduced on a need-to-know basis and in increasing order of difficulty. Matlab codes are presented and discussed for ...

Quantum vertex model for reversible classical computing.

Science.gov (United States)

Chamon, C; Mucciolo, E R; Ruckenstein, A E; Yang, Z-C

2017-05-12

Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without 'learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.

Computational Modelling of Piston Ring Dynamics in 3D

Directory of Open Access Journals (Sweden)

Dlugoš Jozef

2014-12-01

Full Text Available Advanced computational models of a piston assembly based on the level of virtual prototypes require a detailed description of piston ring behaviour. Considering these requirements, the piston rings operate in regimes that cannot, in general, be simplified into an axisymmetric model. The piston and the cylinder liner do not have a perfect round shape, mainly due to machining tolerances and external thermo-mechanical loads. If the ring cannot follow the liner deformations, a local loss of contact occurs resulting in blow-by and increased consumption of lubricant oil in the engine. Current computational models are unable to implement such effects. The paper focuses on the development of a flexible 3D piston ring model based on the Timoshenko beam theory using the multibody system (MBS. The MBS model is compared to the finite element method (FEM solution.

Hybrid computer simulation of the dynamics of the Hoger Onderwijs Reactor

International Nuclear Information System (INIS)

Moers, J.C.; Vries, J.W. de.

1976-01-01

A distributed parameter model for the dynamics of the Hoger Onderwijs Reactor (HOR) at Delft is presented. The neutronic and the thermodynamic part of this model have been separately implemented on the AD4-IBM1800 Hybrid Computer of the Delft University of Technology Computation Centre. A continuous Space/Discrete Time solution method has been employed. Some test results of the simulation are included

Fluid dynamics theory, computation, and numerical simulation

CERN Document Server

Pozrikidis, C

2001-01-01

Fluid Dynamics Theory, Computation, and Numerical Simulation is the only available book that extends the classical field of fluid dynamics into the realm of scientific computing in a way that is both comprehensive and accessible to the beginner The theory of fluid dynamics, and the implementation of solution procedures into numerical algorithms, are discussed hand-in-hand and with reference to computer programming This book is an accessible introduction to theoretical and computational fluid dynamics (CFD), written from a modern perspective that unifies theory and numerical practice There are several additions and subject expansions in the Second Edition of Fluid Dynamics, including new Matlab and FORTRAN codes Two distinguishing features of the discourse are solution procedures and algorithms are developed immediately after problem formulations are presented, and numerical methods are introduced on a need-to-know basis and in increasing order of difficulty Matlab codes are presented and discussed for a broad...

Dynamic wake meandering modeling

Energy Technology Data Exchange (ETDEWEB)

Larsen, Gunner C.; Aagaard Madsen, H.; Bingoel, F. (and others)

2007-06-15

We present a consistent, physically based theory for the wake meandering phenomenon, which we consider of crucial importance for the overall description of wind turbine loadings in wind farms. In its present version the model is confined to single wake situations. The model philosophy does, however, have the potential to include also mutual wake interaction phenomenons. The basic conjecture behind the dynamic wake meandering model is that wake transportation in the atmospheric boundary layer is driven by the large scale lateral- and vertical turbulence components. Based on this conjecture a stochastic model of the downstream wake meandering is formulated. In addition to the kinematic formulation of the dynamics of the 'meandering frame of reference', models characterizing the mean wake deficit as well as the added wake turbulence, described in the meandering frame of reference, are an integrated part the model complex. For design applications, the computational efficiency of wake deficit prediction is a key issue. Two computationally low cost models are developed for this purpose. The character of the added wake turbulence, generated by the up-stream turbine in the form of shed and trailed vorticity, has been approached by analytical as well as by numerical studies. The dynamic wake meandering philosophy has been verified by comparing model predictions with extensive full-scale measurements. These comparisons have demonstrated good agreement, both qualitatively and quantitatively, concerning both flow characteristics and turbine load characteristics. Contrary to previous attempts to model wake loading, the dynamic wake meandering approach opens for a unifying description in the sense that turbine power and load aspects can be treated simultaneously. This capability is a direct and attractive consequence of the model being based on the underlying physical process, and it potentially opens for optimization of wind farm topology, of wind farm operation as

SmartShadow models and methods for pervasive computing

CERN Document Server

Wu, Zhaohui

2013-01-01

SmartShadow: Models and Methods for Pervasive Computing offers a new perspective on pervasive computing with SmartShadow, which is designed to model a user as a personality ""shadow"" and to model pervasive computing environments as user-centric dynamic virtual personal spaces. Just like human beings' shadows in the physical world, it follows people wherever they go, providing them with pervasive services. The model, methods, and software infrastructure for SmartShadow are presented and an application for smart cars is also introduced.  The book can serve as a valuable reference work for resea

Nonlinear structural mechanics theory, dynamical phenomena and modeling

CERN Document Server

Lacarbonara, Walter

2013-01-01

Nonlinear Structural Mechanics: Theory, Dynamical Phenomena and Modeling offers a concise, coherent presentation of the theoretical framework of nonlinear structural mechanics, computational methods, applications, parametric investigations of nonlinear phenomena and their mechanical interpretation towards design. The theoretical and computational tools that enable the formulation, solution, and interpretation of nonlinear structures are presented in a systematic fashion so as to gradually attain an increasing level of complexity of structural behaviors, under the prevailing assumptions on the geometry of deformation, the constitutive aspects and the loading scenarios. Readers will find a treatment of the foundations of nonlinear structural mechanics towards advanced reduced models, unified with modern computational tools in the framework of the prominent nonlinear structural dynamic phenomena while tackling both the mathematical and applied sciences. Nonlinear Structural Mechanics: Theory, Dynamical Phenomena...

Predictive modeling of liquid-sodium thermal–hydraulics experiments and computations

International Nuclear Information System (INIS)

Arslan, Erkan; Cacuci, Dan G.

2014-01-01

Highlights: • We applied the predictive modeling method of Cacuci and Ionescu-Bujor (2010). • We assimilated data from sodium flow experiments. • We used computational fluid dynamics simulations of sodium experiments. • The predictive modeling method greatly reduced uncertainties in predicted results. - Abstract: This work applies the predictive modeling procedure formulated by Cacuci and Ionescu-Bujor (2010) to assimilate data from liquid-sodium thermal–hydraulics experiments in order to reduce systematically the uncertainties in the predictions of computational fluid dynamics (CFD) simulations. The predicted CFD-results for the best-estimate model parameters and results describing sodium-flow velocities and temperature distributions are shown to be significantly more precise than the original computations and experiments, in that the predicted uncertainties for the best-estimate results and model parameters are significantly smaller than both the originally computed and the experimental uncertainties

Reduced-order computational model in nonlinear structural dynamics for structures having numerous local elastic modes in the low-frequency range. Application to fuel assemblies

International Nuclear Information System (INIS)

Batou, A.; Soize, C.; Brie, N.

2013-01-01

Highlights: • A ROM of a nonlinear dynamical structure is built with a global displacements basis. • The reduced order model of fuel assemblies is accurate and of very small size. • The shocks between grids of a row of seven fuel assemblies are computed. -- Abstract: We are interested in the construction of a reduced-order computational model for nonlinear complex dynamical structures which are characterized by the presence of numerous local elastic modes in the low-frequency band. This high modal density makes the use of the classical modal analysis method not suitable. Therefore the reduced-order computational model is constructed using a basis of a space of global displacements, which is constructed a priori and which allows the nonlinear dynamical response of the structure observed on the stiff part to be predicted with a good accuracy. The methodology is applied to a complex industrial structure which is made up of a row of seven fuel assemblies with possibility of collisions between grids and which is submitted to a seismic loading

Reduced-order computational model in nonlinear structural dynamics for structures having numerous local elastic modes in the low-frequency range. Application to fuel assemblies

Energy Technology Data Exchange (ETDEWEB)

Batou, A., E-mail: anas.batou@univ-paris-est.fr [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-la-Vallee (France); Soize, C., E-mail: christian.soize@univ-paris-est.fr [Université Paris-Est, Laboratoire Modélisation et Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-la-Vallee (France); Brie, N., E-mail: nicolas.brie@edf.fr [EDF R and D, Département AMA, 1 avenue du général De Gaulle, 92140 Clamart (France)

2013-09-15

Highlights: • A ROM of a nonlinear dynamical structure is built with a global displacements basis. • The reduced order model of fuel assemblies is accurate and of very small size. • The shocks between grids of a row of seven fuel assemblies are computed. -- Abstract: We are interested in the construction of a reduced-order computational model for nonlinear complex dynamical structures which are characterized by the presence of numerous local elastic modes in the low-frequency band. This high modal density makes the use of the classical modal analysis method not suitable. Therefore the reduced-order computational model is constructed using a basis of a space of global displacements, which is constructed a priori and which allows the nonlinear dynamical response of the structure observed on the stiff part to be predicted with a good accuracy. The methodology is applied to a complex industrial structure which is made up of a row of seven fuel assemblies with possibility of collisions between grids and which is submitted to a seismic loading.

A computational growth model for measuring dynamic cortical development in the first year of life.

Science.gov (United States)

Nie, Jingxin; Li, Gang; Wang, Li; Gilmore, John H; Lin, Weili; Shen, Dinggang

2012-10-01

Human cerebral cortex develops extremely fast in the first year of life. Quantitative measurement of cortical development during this early stage plays an important role in revealing the relationship between cortical structural and high-level functional development. This paper presents a computational growth model to simulate the dynamic development of the cerebral cortex from birth to 1 year old by modeling the cerebral cortex as a deformable elastoplasticity surface driven via a growth model. To achieve a high accuracy, a guidance model is also incorporated to estimate the growth parameters and cortical shapes at later developmental stages. The proposed growth model has been applied to 10 healthy subjects with longitudinal brain MR images acquired at every 3 months from birth to 1 year old. The experimental results show that our proposed method can capture the dynamic developmental process of the cortex, with the average surface distance error smaller than 0.6 mm compared with the ground truth surfaces, and the results also show that 1) the curvedness and sharpness decrease from 2 weeks to 12 months and 2) the frontal lobe shows rapidly increasing cortical folding during this period, with relatively slower increase of the cortical folding in the occipital and parietal lobes.

On turbulence models for rod bundle flow computations

International Nuclear Information System (INIS)

Hazi, Gabor

2005-01-01

In commercial computational fluid dynamics codes there is more than one turbulence model built in. It is the user responsibility to choose one of those models, suitable for the problem studied. In the last decade, several computations were presented using computational fluid dynamics for the simulation of various problems of the nuclear industry. A common feature in a number of those simulations is that they were performed using the standard k-ε turbulence model without justifying the choice of the model. The simulation results were rarely satisfactory. In this paper, we shall consider the flow in a fuel rod bundle as a case study and discuss why the application of the standard k-ε model fails to give reasonable results in this situation. We also show that a turbulence model based on the Reynolds stress transport equations can provide qualitatively correct results. Generally, our aim is pedagogical, we would like to call the readers attention to the fact that turbulence models have to be selected based on theoretical considerations and/or adequate information obtained from measurements

Computational fluid dynamics (CFD) modelling of coal/biomass co-firing in pulverised fuel boilers

Energy Technology Data Exchange (ETDEWEB)

Moghtaderi, B.; Meesri, C. [University of Newcastle, Callaghan, NSW (Australia). CRC for Coal in Sustainable Development, Dept. of Chemical Engineering

2002-07-01

The present study is concerned with computational fluid dynamics (CFD) modelling of coal/biomass blends co-fired under conditions pertinent to pulverised fuel (PF) boilers. The attention is particularly focused on the near burner zone to examine the impact of biomass on the flame geometry and temperature. The predictions are obtained by numerical solution of the conservation equations for the gas and particle phases. The gas phase is solved in the Eulerian domain using steady-state time-averaged Navier-Stokes equations while the solution of the particle phase is obtained from a series of Lagrangian particle tracking equations. Turbulence is modelled using the {kappa}-{epsilon} and Reynolds Stress models. The comparison between the predictions and experimental measurement reported in the literature resulted in a good agreement. Other influences of biomass co-firing are observed for fuel devolatilisation and burnout. 19 refs., 6 figs.

Indonesia’s Electricity Demand Dynamic Modelling

Science.gov (United States)

Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

2017-06-01

Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

PETRI NET MODELING OF COMPUTER VIRUS LIFE CYCLE

African Journals Online (AJOL)

Dr Obe

dynamic system analysis is applied to model the virus life cycle. Simulation of the derived model ... Keywords: Virus lifecycle, Petri nets, modeling. simulation. .... complex process. Figure 2 .... by creating Matlab files for five different computer ...

Network Unfolding Map by Vertex-Edge Dynamics Modeling.

Science.gov (United States)

Verri, Filipe Alves Neto; Urio, Paulo Roberto; Zhao, Liang

2018-02-01

The emergence of collective dynamics in neural networks is a mechanism of the animal and human brain for information processing. In this paper, we develop a computational technique using distributed processing elements in a complex network, which are called particles, to solve semisupervised learning problems. Three actions govern the particles' dynamics: generation, walking, and absorption. Labeled vertices generate new particles that compete against rival particles for edge domination. Active particles randomly walk in the network until they are absorbed by either a rival vertex or an edge currently dominated by rival particles. The result from the model evolution consists of sets of edges arranged by the label dominance. Each set tends to form a connected subnetwork to represent a data class. Although the intrinsic dynamics of the model is a stochastic one, we prove that there exists a deterministic version with largely reduced computational complexity; specifically, with linear growth. Furthermore, the edge domination process corresponds to an unfolding map in such way that edges "stretch" and "shrink" according to the vertex-edge dynamics. Consequently, the unfolding effect summarizes the relevant relationships between vertices and the uncovered data classes. The proposed model captures important details of connectivity patterns over the vertex-edge dynamics evolution, in contrast to the previous approaches, which focused on only vertex or only edge dynamics. Computer simulations reveal that the new model can identify nonlinear features in both real and artificial data, including boundaries between distinct classes and overlapping structures of data.

Wind Farm Decentralized Dynamic Modeling With Parameters

DEFF Research Database (Denmark)

Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

2010-01-01

Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

Dynamic modeling method for infrared smoke based on enhanced discrete phase model

Science.gov (United States)

Zhang, Zhendong; Yang, Chunling; Zhang, Yan; Zhu, Hongbo

2018-03-01

The dynamic modeling of infrared (IR) smoke plays an important role in IR scene simulation systems and its accuracy directly influences the system veracity. However, current IR smoke models cannot provide high veracity, because certain physical characteristics are frequently ignored in fluid simulation; simplifying the discrete phase as a continuous phase and ignoring the IR decoy missile-body spinning. To address this defect, this paper proposes a dynamic modeling method for IR smoke, based on an enhanced discrete phase model (DPM). A mathematical simulation model based on an enhanced DPM is built and a dynamic computing fluid mesh is generated. The dynamic model of IR smoke is then established using an extended equivalent-blackbody-molecule model. Experiments demonstrate that this model realizes a dynamic method for modeling IR smoke with higher veracity.

Dynamic complexities in a parasitoid-host-parasitoid ecological model

International Nuclear Information System (INIS)

Yu Hengguo; Zhao Min; Lv Songjuan; Zhu Lili

2009-01-01

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model

Dynamic complexities in a parasitoid-host-parasitoid ecological model

Energy Technology Data Exchange (ETDEWEB)

Yu Hengguo [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China); Zhao Min [School of Life and Environmental Science, Wenzhou University, Wenzhou, Zhejiang 325027 (China)], E-mail: zmcn@tom.com; Lv Songjuan; Zhu Lili [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China)

2009-01-15

Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model.

The use of computers for instruction in fluid dynamics

Science.gov (United States)

Watson, Val

1987-01-01

Applications for computers which improve instruction in fluid dynamics are examined. Computers can be used to illustrate three-dimensional flow fields and simple fluid dynamics mechanisms, to solve fluid dynamics problems, and for electronic sketching. The usefulness of computer applications is limited by computer speed, memory, and software and the clarity and field of view of the projected display. Proposed advances in personal computers which will address these limitations are discussed. Long range applications for computers in education are considered.

High performance computations using dynamical nucleation theory

International Nuclear Information System (INIS)

Windus, T L; Crosby, L D; Kathmann, S M

2008-01-01

Chemists continue to explore the use of very large computations to perform simulations that describe the molecular level physics of critical challenges in science. In this paper, we describe the Dynamical Nucleation Theory Monte Carlo (DNTMC) model - a model for determining molecular scale nucleation rate constants - and its parallel capabilities. The potential for bottlenecks and the challenges to running on future petascale or larger resources are delineated. A 'master-slave' solution is proposed to scale to the petascale and will be developed in the NWChem software. In addition, mathematical and data analysis challenges are described

The Architectural Designs of a Nanoscale Computing Model

Directory of Open Access Journals (Sweden)

Mary M. Eshaghian-Wilner

2004-08-01

Full Text Available A generic nanoscale computing model is presented in this paper. The model consists of a collection of fully interconnected nanoscale computing modules, where each module is a cube of cells made out of quantum dots, spins, or molecules. The cells dynamically switch between two states by quantum interactions among their neighbors in all three dimensions. This paper includes a brief introduction to the field of nanotechnology from a computing point of view and presents a set of preliminary architectural designs for fabricating the nanoscale model studied.

Combining dynamical decoupling with fault-tolerant quantum computation

International Nuclear Information System (INIS)

Ng, Hui Khoon; Preskill, John; Lidar, Daniel A.

2011-01-01

We study how dynamical decoupling (DD) pulse sequences can improve the reliability of quantum computers. We prove upper bounds on the accuracy of DD-protected quantum gates and derive sufficient conditions for DD-protected gates to outperform unprotected gates. Under suitable conditions, fault-tolerant quantum circuits constructed from DD-protected gates can tolerate stronger noise and have a lower overhead cost than fault-tolerant circuits constructed from unprotected gates. Our accuracy estimates depend on the dynamics of the bath that couples to the quantum computer and can be expressed either in terms of the operator norm of the bath's Hamiltonian or in terms of the power spectrum of bath correlations; we explain in particular how the performance of recursively generated concatenated pulse sequences can be analyzed from either viewpoint. Our results apply to Hamiltonian noise models with limited spatial correlations.

Computational Fluid Dynamics Modelling of Hydraulics and Sedimentation in Process Reactors During Aeration Tank Settling

DEFF Research Database (Denmark)

Dam Jensen, Mette; Ingildsen, Pernille; Rasmussen, Michael R.

2005-01-01

Aeration Tank Settling is a control method alowing settling in the process tank during high hydraulic load. The control method is patented. Aeration Tank Settling has been applied in several waste water treatment plant's using present design of the process tanks. Some process tank designs have...... shown to be more effective than others. To improve the design of less effective plants Computational Fluid Dynamics (CFD) modelling of hydraulics and sedimentation has been applied. The paper discusses the results at one particular plant experiencing problems with partly short-circuiting of the inlet...

Validation of a multidimensional computational fluid dynamics model for subcooled flow boiling analysis

Energy Technology Data Exchange (ETDEWEB)

Braz Filho, Francisco A.; Caldeira, Alexandre D.; Borges, Eduardo M., E-mail: fbraz@ieav.cta.b, E-mail: alexdc@ieav.cta.b, E-mail: eduardo@ieav.cta.b [Instituto de Estudos Avancados (IEAv/CTA), Sao Jose dos Campos, SP (Brazil). Div. de Energia Nuclear

2011-07-01

In a heated vertical channel, the subcooled flow boiling regime occurs when the bulk fluid temperature is lower than the saturation temperature, but the fluid temperature reaches the saturation point near the channel wall. This phenomenon produces a significant increase in heat flux, limited by the critical heat flux. This study is particularly important to the thermal-hydraulics analysis of pressurized water reactors. The purpose of this work is the validation of a multidimensional model to analyze the subcooled flow boiling comparing the results with experimental data found in literature. The computational fluid dynamics code FLUENT was used with Eulerian multiphase model option. The calculated values of wall temperature in the liquid-solid interface presented an excellent agreement when compared to the experimental data. Void fraction calculations presented satisfactory results in relation to the experimental data in pressures of 15, 30 and 45 bars. (author)

Validation of a multidimensional computational fluid dynamics model for subcooled flow boiling analysis

International Nuclear Information System (INIS)

Braz Filho, Francisco A.; Caldeira, Alexandre D.; Borges, Eduardo M.

2011-01-01

In a heated vertical channel, the subcooled flow boiling regime occurs when the bulk fluid temperature is lower than the saturation temperature, but the fluid temperature reaches the saturation point near the channel wall. This phenomenon produces a significant increase in heat flux, limited by the critical heat flux. This study is particularly important to the thermal-hydraulics analysis of pressurized water reactors. The purpose of this work is the validation of a multidimensional model to analyze the subcooled flow boiling comparing the results with experimental data found in literature. The computational fluid dynamics code FLUENT was used with Eulerian multiphase model option. The calculated values of wall temperature in the liquid-solid interface presented an excellent agreement when compared to the experimental data. Void fraction calculations presented satisfactory results in relation to the experimental data in pressures of 15, 30 and 45 bars. (author)

A Computational Fluid Dynamics Study of Turbulence, Radiation, and Combustion Models for Natural Gas Combustion Burner

Directory of Open Access Journals (Sweden)

Yik Siang Pang

2018-01-01

Full Text Available This paper presents a Computational Fluid Dynamics (CFD study of a natural gas combustion burner focusing on the effect of combustion, thermal radiation and turbulence models on the temperature and chemical species concentration fields. The combustion was modelled using the finite rate/eddy dissipation (FR/EDM and partially premixed flame models. Detailed chemistry kinetics CHEMKIN GRI-MECH 3.0 consisting of 325 reactions was employed to model the methane combustion. Discrete ordinates (DO and spherical harmonics (P1 model were employed to predict the thermal radiation. The gas absorption coefficient dependence on the wavelength is resolved by the weighted-sum-of-gray-gases model (WSGGM. Turbulence flow was simulated using Reynolds-averaged Navier-Stokes (RANS based models. The findings showed that a combination of partially premixed flame, P1 and standard k-ε (SKE gave the most accurate prediction with an average deviation of around 7.8% of combustion temperature and 15.5% for reactant composition (methane and oxygen. The results show the multi-step chemistry in the partially premixed model is more accurate than the two-step FR/EDM. Meanwhile, inclusion of thermal radiation has a minor effect on the heat transfer and species concentration. SKE turbulence model yielded better prediction compared to the realizable k-ε (RKE and renormalized k-ε (RNG. The CFD simulation presented in this work may serve as a useful tool to evaluate a performance of a natural gas combustor. Copyright © 2018 BCREC Group. All rights reserved Received: 26th July 2017; Revised: 9th October 2017; Accepted: 30th October 2017; Available online: 22nd January 2018; Published regularly: 2nd April 2018 How to Cite: Pang, Y.S., Law, W.P., Pung, K.Q., Gimbun, J. (2018. A Computational Fluid Dynamics Study of Turbulence, Radiation, and Combustion Models for Natural Gas Combustion Burner. Bulletin of Chemical Reaction Engineering & Catalysis, 13 (1: 155-169 (doi:10.9767/bcrec

International Conference on Computer Modelling of Seas and Coastal Regions and Boundary Elements and Fluid Dynamics

CERN Document Server

Partridge, P; Boundary Elements in Fluid Dynamics

1992-01-01

This book Boundary Elements in Fluid Dynamics is the second volume of the two volume proceedings of the International Conference on Computer Modelling of Seas and Coastal Regions and Boundary Elements and Fluid Dynamics, held in Southampton, U.K., in April 1992. The Boundary Element Method (BEM) is now fully established as an ac­ curate and successful technique for solving engineering problems in a wide range of fields. The success of the method is due to its advantages in data reduction, as only the boundary of the region is modelled. Thus moving boundaries may be more easily handled, which is not the case if domain methods are used. In addition, the method is easily able to model regions to extending to infinity. Fluid mechanics is traditionally one of the most challenging areas of engi­ neering, the simulation of fluid motion, particularly in three dimensions, is always a serious test for any numerical method, and is an area in which BEM analysis may be used taking full advantage of its special character...

Computer - based modeling in extract sciences research -I ...

African Journals Online (AJOL)

Specifically, in the discipline of chemistry, it has been of great utility. Its use dates back to the 17th Century and includes such wide areas as computational chemistry, chemoinformatics, molecular mechanics, chemical dynamics, molecular dynamics, molecular graphics and algorithms. Modeling has been employed ...

A future for computational fluid dynamics at CERN

CERN Document Server

Battistin, M

2005-01-01

Computational Fluid Dynamics (CFD) is an analysis of fluid flow, heat transfer and associated phenomena in physical systems using computers. CFD has been used at CERN since 1993 by the TS-CV group, to solve thermo-fluid related problems, particularly during the development, design and construction phases of the LHC experiments. Computer models based on CFD techniques can be employed to reduce the effort required for prototype testing, saving not only time and money but offering possibilities of additional investigations and design optimisation. The development of a more efficient support team at CERN depends on to two important factors: available computing power and experienced engineers. Available computer power IS the limiting resource of CFD. Only the recent increase of computer power had allowed important high tech and industrial applications. Computer Grid is already now (OpenLab at CERN) and will be more so in the future natural environment for CFD science. At CERN, CFD activities have been developed by...

ATEFlap aerodynamic model, a dynamic stall model including the effects of trailing edge flap deflection

Energy Technology Data Exchange (ETDEWEB)

Bergami, L.; Gaunaa, M.

2012-02-15

The report presents the ATEFlap aerodynamic model, which computes the unsteady lift, drag and moment on a 2D airfoil section equipped with Adaptive Trailing Edge Flap. The model captures the unsteady response related to the effects of the vorticity shed into the wake, and the dynamics of flow separation a thin-airfoil potential flow model is merged with a dynamic stall model of the Beddoes-Leishmann type. The inputs required by the model are steady data for lift, drag, and moment coefficients as function of angle of attack and flap deflection. Further steady data used by the Beddoes- Leishmann dynamic stall model are computed in an external preprocessor application, which gives the user the possibility to verify, and eventually correct, the steady data passed to the aerodynamic model. The ATEFlap aerodynamic model is integrated in the aeroelastic simulation tool HAWC2, thus al- lowing to simulate the response of a wind turbine with trailing edge flaps on the rotor. The algorithms used by the preprocessor, and by aerodynamic model are presented, and modifications to previous implementations of the aerodynamic model are briefly discussed. The performance and the validity of the model are verified by comparing the dynamic response computed by the ATEFlap with solutions from CFD simulations. (Author)

Neural Computations in a Dynamical System with Multiple Time Scales

Directory of Open Access Journals (Sweden)

Yuanyuan Mi

2016-09-01

Full Text Available Neural systems display rich short-term dynamics at various levels, e.g., spike-frequencyadaptation (SFA at single neurons, and short-term facilitation (STF and depression (STDat neuronal synapses. These dynamical features typically covers a broad range of time scalesand exhibit large diversity in different brain regions. It remains unclear what the computationalbenefit for the brain to have such variability in short-term dynamics is. In this study, we proposethat the brain can exploit such dynamical features to implement multiple seemingly contradictorycomputations in a single neural circuit. To demonstrate this idea, we use continuous attractorneural network (CANN as a working model and include STF, SFA and STD with increasing timeconstants in their dynamics. Three computational tasks are considered, which are persistent activity,adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, andhence cannot be implemented by a single dynamical feature or any combination with similar timeconstants. However, with properly coordinated STF, SFA and STD, we show that the network isable to implement the three computational tasks concurrently. We hope this study will shed lighton the understanding of how the brain orchestrates its rich dynamics at various levels to realizediverse cognitive functions.

Fluid dynamics theory, computation, and numerical simulation

CERN Document Server

Pozrikidis, C

2017-01-01

This book provides an accessible introduction to the basic theory of fluid mechanics and computational fluid dynamics (CFD) from a modern perspective that unifies theory and numerical computation. Methods of scientific computing are introduced alongside with theoretical analysis and MATLAB® codes are presented and discussed for a broad range of topics: from interfacial shapes in hydrostatics, to vortex dynamics, to viscous flow, to turbulent flow, to panel methods for flow past airfoils. The third edition includes new topics, additional examples, solved and unsolved problems, and revised images. It adds more computational algorithms and MATLAB programs. It also incorporates discussion of the latest version of the fluid dynamics software library FDLIB, which is freely available online. FDLIB offers an extensive range of computer codes that demonstrate the implementation of elementary and advanced algorithms and provide an invaluable resource for research, teaching, classroom instruction, and self-study. This ...

Numerical solution of dynamic equilibrium models under Poisson uncertainty

DEFF Research Database (Denmark)

Posch, Olaf; Trimborn, Timo

2013-01-01

We propose a simple and powerful numerical algorithm to compute the transition process in continuous-time dynamic equilibrium models with rare events. In this paper we transform the dynamic system of stochastic differential equations into a system of functional differential equations of the retar...... solution to Lucas' endogenous growth model under Poisson uncertainty are used to compute the exact numerical error. We show how (potential) catastrophic events such as rare natural disasters substantially affect the economic decisions of households....

Computer Modelling of Photochemical Smog Formation

Science.gov (United States)

Huebert, Barry J.

1974-01-01

Discusses a computer program that has been used in environmental chemistry courses as an example of modelling as a vehicle for teaching chemical dynamics, and as a demonstration of some of the factors which affect the production of smog. (Author/GS)

Modeling near-road air quality using a computational fluid dynamics model, CFD-VIT-RIT.

Science.gov (United States)

Wang, Y Jason; Zhang, K Max

2009-10-15

It is well recognized that dilution is an important mechanism governing the near-road air pollutant concentrations. In this paper, we aim to advance our understanding of turbulent mixing mechanisms on and near roadways using computation fluid dynamics. Turbulent mixing mechanisms can be classified into three categories according to their origins: vehicle-induced turbulence (VIT), road-induced turbulence (RIT), and atmospheric boundary layer turbulence. RIT includes the turbulence generated by road embankment, road surface thermal effects, and roadside structures. Both VIT and RIT are affected by the roadway designs. We incorporate the detailed treatment of VIT and RIT into the CFD (namely CFD-VIT-RIT) and apply the model in simulating the spatial gradients of carbon monoxide near two major highways with different traffic mix and roadway configurations. The modeling results are compared to the field measurements and those from CALINE4 and CFD without considering VIT and RIT. We demonstrate that the incorporation of VIT and RIT considerably improves the modeling predictions, especially on vertical gradients and seasonal variations of carbon monoxide. Our study implies that roadway design can significantly influence the near-road air pollution. Thus we recommend that mitigating near-road air pollution through roadway designs be considered in the air quality and transportation management In addition, thanks to the rigorous representation of turbulent mixing mechanisms, CFD-VIT-RIT can become valuable tools in the roadway designs process.

Mathematical modeling and computational prediction of cancer drug resistance.

Science.gov (United States)

Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of

GASFLOW-MPI. A scalable computational fluid dynamics code for gases, aerosols and combustion. Vol. 1. Theory and computational model (Revision 1.0)

Energy Technology Data Exchange (ETDEWEB)

Xiao, Jianjun; Travis, Jack; Royl, Peter; Necker, Gottfried; Svishchev, Anatoly; Jordan, Thomas

2016-07-01

Karlsruhe Institute of Technology (KIT) is developing the parallel computational fluid dynamics code GASFLOW-MPI as a best-estimate tool for predicting transport, mixing, and combustion of hydrogen and other gases in nuclear reactor containments and other facility buildings. GASFLOW-MPI is a finite-volume code based on proven computational fluid dynamics methodology that solves the compressible Navier-Stokes equations for three-dimensional volumes in Cartesian or cylindrical coordinates.

Modelling the Dynamics of an Aedes albopictus Population

Directory of Open Access Journals (Sweden)

Thomas Anung Basuki

2010-08-01

Full Text Available We present a methodology for modelling population dynamics with formal means of computer science. This allows unambiguous description of systems and application of analysis tools such as simulators and model checkers. In particular, the dynamics of a population of Aedes albopictus (a species of mosquito and its modelling with the Stochastic Calculus of Looping Sequences (Stochastic CLS are considered. The use of Stochastic CLS to model population dynamics requires an extension which allows environmental events (such as changes in the temperature and rainfalls to be taken into account. A simulator for the constructed model is developed via translation into the specification language Maude, and used to compare the dynamics obtained from the model with real data.

Assessment of Computational Fluid Dynamics (CFD) Models for Shock Boundary-Layer Interaction

Science.gov (United States)

DeBonis, James R.; Oberkampf, William L.; Wolf, Richard T.; Orkwis, Paul D.; Turner, Mark G.; Babinsky, Holger

2011-01-01

A workshop on the computational fluid dynamics (CFD) prediction of shock boundary-layer interactions (SBLIs) was held at the 48th AIAA Aerospace Sciences Meeting. As part of the workshop numerous CFD analysts submitted solutions to four experimentally measured SBLIs. This paper describes the assessment of the CFD predictions. The assessment includes an uncertainty analysis of the experimental data, the definition of an error metric and the application of that metric to the CFD solutions. The CFD solutions provided very similar levels of error and in general it was difficult to discern clear trends in the data. For the Reynolds Averaged Navier-Stokes methods the choice of turbulence model appeared to be the largest factor in solution accuracy. Large-eddy simulation methods produced error levels similar to RANS methods but provided superior predictions of normal stresses.

AFDM: An Advanced Fluid-Dynamics Model

International Nuclear Information System (INIS)

Bohl, W.R.; Parker, F.R.; Wilhelm, D.; Goutagny, L.; Ninokata, H.

1990-09-01

AFDM, or the Advanced Fluid-Dynamics Model, is a computer code that investigates new approaches simulating the multiphase-flow fluid-dynamics aspects of severe accidents in fast reactors. The AFDM formalism starts with differential equations similar to those in the SIMMER-II code. These equations are modified to treat three velocity fields and supplemented with a variety of new models. The AFDM code has 12 topologies describing what material contacts are possible depending on the presence or absence of a given material in a computational cell, on the dominant liquid, and on the continuous phase. Single-phase, bubbly, churn-turbulent, cellular, and dispersed flow regimes are permitted for the pool situations modeled. Virtual mass terms are included for vapor in liquid-continuous flow. Interfacial areas between the continuous and discontinuous phases are convected to allow some tracking of phenomenological histories. Interfacial areas are also modified by models of nucleation, dynamic forces, turbulence, flashing, coalescence, and mass transfer. Heat transfer is generally treated using engineering correlations. Liquid-vapor phase transitions are handled with the nonequilibrium, heat-transfer-limited model, whereas melting and freezing processes are based on equilibrium considerations. Convection is treated using a fractional-step method of time integration, including a semi-implicit pressure iteration. A higher-order differencing option is provided to control numerical diffusion. The Los Alamos SESAME equation-of-state has been implemented using densities and temperatures as the independent variables. AFDM programming has vectorized all computational loops consistent with the objective of producing an exportable code. 24 refs., 4 figs

Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

Directory of Open Access Journals (Sweden)

Kiuru Aaro

2003-01-01

Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

Modeling Techniques for a Computational Efficient Dynamic Turbofan Engine Model

Directory of Open Access Journals (Sweden)

Rory A. Roberts

2014-01-01

Full Text Available A transient two-stream engine model has been developed. Individual component models developed exclusively in MATLAB/Simulink including the fan, high pressure compressor, combustor, high pressure turbine, low pressure turbine, plenum volumes, and exit nozzle have been combined to investigate the behavior of a turbofan two-stream engine. Special attention has been paid to the development of transient capabilities throughout the model, increasing physics model, eliminating algebraic constraints, and reducing simulation time through enabling the use of advanced numerical solvers. The lessening of computation time is paramount for conducting future aircraft system-level design trade studies and optimization. The new engine model is simulated for a fuel perturbation and a specified mission while tracking critical parameters. These results, as well as the simulation times, are presented. The new approach significantly reduces the simulation time.

A novel grid-based mesoscopic model for evacuation dynamics

Science.gov (United States)

Shi, Meng; Lee, Eric Wai Ming; Ma, Yi

2018-05-01

This study presents a novel grid-based mesoscopic model for evacuation dynamics. In this model, the evacuation space is discretised into larger cells than those used in microscopic models. This approach directly computes the dynamic changes crowd densities in cells over the course of an evacuation. The density flow is driven by the density-speed correlation. The computation is faster than in traditional cellular automata evacuation models which determine density by computing the movements of each pedestrian. To demonstrate the feasibility of this model, we apply it to a series of practical scenarios and conduct a parameter sensitivity study of the effect of changes in time step δ. The simulation results show that within the valid range of δ, changing δ has only a minor impact on the simulation. The model also makes it possible to directly acquire key information such as bottleneck areas from a time-varied dynamic density map, even when a relatively large time step is adopted. We use the commercial software AnyLogic to evaluate the model. The result shows that the mesoscopic model is more efficient than the microscopic model and provides more in-situ details (e.g., pedestrian movement pattern) than the macroscopic models.

Computational fluid dynamics modeling of bun baking process under different oven load conditions.

Science.gov (United States)

Tank, A; Chhanwal, N; Indrani, D; Anandharamakrishnan, C

2014-09-01

A computational fluid dynamics (CFD) model was developed to study the temperature profile of the bun during baking process. Evaporation-condensation mechanism and effect of the latent heat during phase change of water was incorporated in this model to represent actual bun baking process. Simulation results were validated with experimental measurements of bun temperature at two different positions. Baking process is completed within 20 min, after the temperature of crumb become stable at 98 °C. Further, this study was extended to investigate the effect of partially (two baking trays) loaded and fully loaded (eight baking trays) oven on temperature profile of bun. Velocity and temperature profile differs in partially loaded and fully loaded oven. Bun placed in top rack showed rapid baking while bun placed in bottom rack showed slower baking due to uneven temperature distribution in the oven. Hence, placement of bun inside the oven affects temperature of bun and consequently, the quality of the product.

Optimization of a new flow design for solid oxide cells using computational fluid dynamics modelling

DEFF Research Database (Denmark)

Duhn, Jakob Dragsbæk; Jensen, Anker Degn; Wedel, Stig

2016-01-01

Design of a gas distributor to distribute gas flow into parallel channels for Solid Oxide Cells (SOC) is optimized, with respect to flow distribution, using Computational Fluid Dynamics (CFD) modelling. The CFD model is based on a 3d geometric model and the optimized structural parameters include...... the width of the channels in the gas distributor and the area in front of the parallel channels. The flow of the optimized design is found to have a flow uniformity index value of 0.978. The effects of deviations from the assumptions used in the modelling (isothermal and non-reacting flow) are evaluated...... and it is found that a temperature gradient along the parallel channels does not affect the flow uniformity, whereas a temperature difference between the channels does. The impact of the flow distribution on the maximum obtainable conversion during operation is also investigated and the obtainable overall...

Magnetically nonlinear dynamic model of synchronous motor with permanent magnets

International Nuclear Information System (INIS)

Hadziselimovic, Miralem; Stumberger, Gorazd; Stumberger, Bojan; Zagradisnik, Ivan

2007-01-01

This paper deals with a magnetically nonlinear two-axis dynamic model of a permanent magnet synchronous motor (PMSM). The geometrical and material properties of iron core and permanent magnets, the effects of winding distribution, saturation, cross-saturation and slotting effects are, for the first time, simultaneously accounted for in a single two-axis dynamic model of a three-phase PMSM. They are accounted for by current- and position-dependent characteristics of flux linkages. These characteristics can be determined either experimentally or by the finite element (FE) computations. The results obtained by the proposed dynamic model show a very good agreement with the measured ones and those obtained by the FE computation

New Frontiers in Analyzing Dynamic Group Interactions: Bridging Social and Computer Science.

Science.gov (United States)

Lehmann-Willenbrock, Nale; Hung, Hayley; Keyton, Joann

2017-10-01

This special issue on advancing interdisciplinary collaboration between computer scientists and social scientists documents the joint results of the international Lorentz workshop, "Interdisciplinary Insights into Group and Team Dynamics," which took place in Leiden, The Netherlands, July 2016. An equal number of scholars from social and computer science participated in the workshop and contributed to the papers included in this special issue. In this introduction, we first identify interaction dynamics as the core of group and team models and review how scholars in social and computer science have typically approached behavioral interactions in groups and teams. Next, we identify key challenges for interdisciplinary collaboration between social and computer scientists, and we provide an overview of the different articles in this special issue aimed at addressing these challenges.

Dynamic behaviour of raft and pile foundations tests and computational models. Pt. 1

International Nuclear Information System (INIS)

Betbeder, J.; Garnier, J.C.; Gauvain, J.; Jeandidier, C.

1981-01-01

Pile foundations are commonly used for many types of buildings where the bearing capacity of soil is poor. For nuclear power plants buildings, however, there seems to be a fairly general reluctancy to accept design on piles, as it is considered difficult to demonstrate the safety of these foundations with respect to earthquakes, due to the relative lack of validation of the currently available aseismic design methods. Being conscious that pile foundations might be worth considering for future nuclear sites in France and that the reliability of design methods should be backed by experimental data, ELECTRICITE DE FRANCE decided in 1978 to undertake a series of tests, aimed at assessing the validity of computational models for seismic behaviour of pile foundations and trying to define better models if necessary. These tests on reduced scale structure, including various types of raft and pile foundations and different kinds of dynamic excitation (harmonic, earthquake simulation, impulsive release of a static force) have been made at the NICE airport site. The present paper deals with the general description of the tests and the first part of interpretation work, limited to in-structure harmonic excitation and earthquake simulation tests analyzed by simple spring -dashpot analytical models. The two following papers (K5-6 and K5-7) are devoted to specialized topics in relation with the interpretation of tests, i-e ground motions analysis for earthquake simulation and research work on a new computational model. Although preliminary conclusions can be drawn from the results obtained so far, further work will be necessary to reach a conclusive assessment on this difficult subject. (orig.)

Preliminary analysis of the MER magnetic properties experiment using a computational fluid dynamics model

DEFF Research Database (Denmark)

Kinch, K.M.; Merrison, J.P.; Gunnlaugsson, H.P.

2006-01-01

Motivated by questions raised by the magnetic properties experiments on the NASA Mars Pathfinder and Mars Exploration Rover (MER) missions, we have studied in detail the capture of airborne magnetic dust by permanent magnets using a computational fluid dynamics (CFD) model supported by laboratory...... simulations. The magnets studied are identical to the capture magnet and filter magnet on MER, though results are more generally applicable. The dust capture process is found to be dependent upon wind speed, dust magnetization, dust grain size and dust grain mass density. Here we develop an understanding...... of how these parameters affect dust capture rates and patterns on the magnets and set bounds for these parameters based on MER data and results from the numerical model. This results in a consistent picture of the dust as containing varying amounts of at least two separate components with different...

A hybrid computer simulation of reactor spatial dynamics

International Nuclear Information System (INIS)

Hinds, H.W.

1977-08-01

The partial differential equations describing the one-speed spatial dynamics of thermal neutron reactors were converted to a set of ordinary differential equations, using finite-difference approximations for the spatial derivatives. The variables were then normalized to a steady-state reference condition in a novel manner, to yield an equation set particularly suitable for implementation on a hybrid computer. One Applied Dynamics AD/FIVE analog-computer console is capable of solving, all in parallel, up to 30 simultaneous differential equations. This corresponds roughly to eight reactor nodes, each with two active delayed-neutron groups. To improve accuracy, an increase in the number of nodes is usually required. Using the Hsu-Howe multiplexing technique, an 8-node, one-dimensional module was switched back and forth between the left and right halves of the reactor, to simulate a 16-node model, also in one dimension. These two versions (8 or 16 nodes) of the model were tested on benchmark problems of the loss-of-coolant type, which were also solved using the digital code FORSIM, with two energy groups and 26 nodes. Good agreement was obtained between the two solution techniques. (author)

Brain systems for probabilistic and dynamic prediction: computational specificity and integration.

Directory of Open Access Journals (Sweden)

Jill X O'Reilly

2013-09-01

Full Text Available A computational approach to functional specialization suggests that brain systems can be characterized in terms of the types of computations they perform, rather than their sensory or behavioral domains. We contrasted the neural systems associated with two computationally distinct forms of predictive model: a reinforcement-learning model of the environment obtained through experience with discrete events, and continuous dynamic forward modeling. By manipulating the precision with which each type of prediction could be used, we caused participants to shift computational strategies within a single spatial prediction task. Hence (using fMRI we showed that activity in two brain systems (typically associated with reward learning and motor control could be dissociated in terms of the forms of computations that were performed there, even when both systems were used to make parallel predictions of the same event. A region in parietal cortex, which was sensitive to the divergence between the predictions of the models and anatomically connected to both computational networks, is proposed to mediate integration of the two predictive modes to produce a single behavioral output.

Computational fluid dynamics (CFD) simulation of hot air flow ...

African Journals Online (AJOL)

Computational Fluid Dynamics simulation of air flow distribution, air velocity and pressure field pattern as it will affect moisture transient in a cabinet tray dryer is performed using SolidWorks Flow Simulation (SWFS) 2014 SP 4.0 program. The model used for the drying process in this experiment was designed with Solid ...

Dynamic optimization deterministic and stochastic models

CERN Document Server

Hinderer, Karl; Stieglitz, Michael

2016-01-01

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

Three-Dimensional Computational Fluid Dynamics

Energy Technology Data Exchange (ETDEWEB)

Haworth, D.C.; O' Rourke, P.J.; Ranganathan, R.

1998-09-01

Computational fluid dynamics (CFD) is one discipline falling under the broad heading of computer-aided engineering (CAE). CAE, together with computer-aided design (CAD) and computer-aided manufacturing (CAM), comprise a mathematical-based approach to engineering product and process design, analysis and fabrication. In this overview of CFD for the design engineer, our purposes are three-fold: (1) to define the scope of CFD and motivate its utility for engineering, (2) to provide a basic technical foundation for CFD, and (3) to convey how CFD is incorporated into engineering product and process design.

A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements.

Directory of Open Access Journals (Sweden)

Daniel Durstewitz

2017-06-01

Full Text Available The computational and cognitive properties of neural systems are often thought to be implemented in terms of their (stochastic network dynamics. Hence, recovering the system dynamics from experimentally observed neuronal time series, like multiple single-unit recordings or neuroimaging data, is an important step toward understanding its computations. Ideally, one would not only seek a (lower-dimensional state space representation of the dynamics, but would wish to have access to its statistical properties and their generative equations for in-depth analysis. Recurrent neural networks (RNNs are a computationally powerful and dynamically universal formal framework which has been extensively studied from both the computational and the dynamical systems perspective. Here we develop a semi-analytical maximum-likelihood estimation scheme for piecewise-linear RNNs (PLRNNs within the statistical framework of state space models, which accounts for noise in both the underlying latent dynamics and the observation process. The Expectation-Maximization algorithm is used to infer the latent state distribution, through a global Laplace approximation, and the PLRNN parameters iteratively. After validating the procedure on toy examples, and using inference through particle filters for comparison, the approach is applied to multiple single-unit recordings from the rodent anterior cingulate cortex (ACC obtained during performance of a classical working memory task, delayed alternation. Models estimated from kernel-smoothed spike time data were able to capture the essential computational dynamics underlying task performance, including stimulus-selective delay activity. The estimated models were rarely multi-stable, however, but rather were tuned to exhibit slow dynamics in the vicinity of a bifurcation point. In summary, the present work advances a semi-analytical (thus reasonably fast maximum-likelihood estimation framework for PLRNNs that may enable to recover

Issues in computational fluid dynamics code verification and validation

Energy Technology Data Exchange (ETDEWEB)

Oberkampf, W.L.; Blottner, F.G.

1997-09-01

A broad range of mathematical modeling errors of fluid flow physics and numerical approximation errors are addressed in computational fluid dynamics (CFD). It is strongly believed that if CFD is to have a major impact on the design of engineering hardware and flight systems, the level of confidence in complex simulations must substantially improve. To better understand the present limitations of CFD simulations, a wide variety of physical modeling, discretization, and solution errors are identified and discussed. Here, discretization and solution errors refer to all errors caused by conversion of the original partial differential, or integral, conservation equations representing the physical process, to algebraic equations and their solution on a computer. The impact of boundary conditions on the solution of the partial differential equations and their discrete representation will also be discussed. Throughout the article, clear distinctions are made between the analytical mathematical models of fluid dynamics and the numerical models. Lax`s Equivalence Theorem and its frailties in practical CFD solutions are pointed out. Distinctions are also made between the existence and uniqueness of solutions to the partial differential equations as opposed to the discrete equations. Two techniques are briefly discussed for the detection and quantification of certain types of discretization and grid resolution errors.

Analog computing for a new nuclear reactor dynamic model based on a time-dependent second order form of the neutron transport equation

International Nuclear Information System (INIS)

Pirouzmand, Ahmad; Hadad, Kamal; Suh, Kune Y.

2011-01-01

This paper considers the concept of analog computing based on a cellular neural network (CNN) paradigm to simulate nuclear reactor dynamics using a time-dependent second order form of the neutron transport equation. Instead of solving nuclear reactor dynamic equations numerically, which is time-consuming and suffers from such weaknesses as vulnerability to transient phenomena, accumulation of round-off errors and floating-point overflows, use is made of a new method based on a cellular neural network. The state-of-the-art shows the CNN as being an alternative solution to the conventional numerical computation method. Indeed CNN is an analog computing paradigm that performs ultra-fast calculations and provides accurate results. In this study use is made of the CNN model to simulate the space-time response of scalar flux distribution in steady state and transient conditions. The CNN model also is used to simulate step perturbation in the core. The accuracy and capability of the CNN model are examined in 2D Cartesian geometry for two fixed source problems, a mini-BWR assembly, and a TWIGL Seed/Blanket problem. We also use the CNN model concurrently for a typical small PWR assembly to simulate the effect of temperature feedback, poisons, and control rods on the scalar flux distribution

Computational complexity of symbolic dynamics at the onset of chaos

Science.gov (United States)

Lakdawala, Porus

1996-05-01

In a variety of studies of dynamical systems, the edge of order and chaos has been singled out as a region of complexity. It was suggested by Wolfram, on the basis of qualitative behavior of cellular automata, that the computational basis for modeling this region is the universal Turing machine. In this paper, following a suggestion of Crutchfield, we try to show that the Turing machine model may often be too powerful as a computational model to describe the boundary of order and chaos. In particular we study the region of the first accumulation of period doubling in unimodal and bimodal maps of the interval, from the point of view of language theory. We show that in relation to the ``extended'' Chomsky hierarchy, the relevant computational model in the unimodal case is the nested stack automaton or the related indexed languages, while the bimodal case is modeled by the linear bounded automaton or the related context-sensitive languages.

Advances in engineering turbulence modeling. [computational fluid dynamics

Science.gov (United States)

Shih, T.-H.

1992-01-01

Some new developments in two equation models and second order closure models are presented. In this paper, modified two equation models are proposed to remove shortcomings such as computing flows over complex geometries and the ad hoc treatment near the separation and reattachment points. The calculations using various two equation models are compared with direct numerical solutions of channel flows and flat plate boundary layers. Development of second order closure models will also be discussed with emphasis on the modeling of pressure related correlation terms and dissipation rates in the second moment equations. All existing models poorly predict the normal stresses near the wall and fail to predict the three dimensional effect of mean flow on the turbulence. The newly developed second order near-wall turbulence model to be described in this paper is capable of capturing the near-wall behavior of turbulence as well as the effect of three dimension mean flow on the turbulence.

Function of dynamic models in systems biology: linking structure to behaviour.

Science.gov (United States)

Knüpfer, Christian; Beckstein, Clemens

2013-10-08

Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process

Agent Based Modeling on Organizational Dynamics of Terrorist Network

Directory of Open Access Journals (Sweden)

Bo Li

2015-01-01

Full Text Available Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model are developed for modeling the hybrid relational structure and complex operational processes, respectively. To intuitively elucidate this method, the agent based modeling is used to simulate the terrorist network and test the performance in diverse scenarios. Based on the experimental results, we show how the changes of operational environments affect the development of terrorist organization in terms of its recovery and capacity to perform future tasks. The potential strategies are also discussed, which can be used to restrain the activities of terrorists.

Modeling centrifugal cell washers using computational fluid dynamics.

Science.gov (United States)

Kellet, Beth E; Han, Binbing; Dandy, David S; Wickramasinghe, S Ranil

2004-11-01

Reinfusion of shed blood during surgery could avoid the need for blood transfusions. Prior to reinfusion of the red blood cells, the shed blood must be washed in order to remove leukocytes, platelets, and other contaminants. Further, the hematocrit of the washed blood must be increased. The feasibility of using computational fluid dynamics (CFD) to guide the design of better centrifuges for processing shed blood is explored here. The velocity field within a centrifuge bowl and the rate of protein removal from the shed blood has been studied. The results obtained indicate that CFD could help screen preliminary centrifuge bowl designs, thus reducing the number of initial experimental tests required when developing new centrifuge bowls. Although the focus of this work is on washing shed blood, the methods developed here are applicable to the design of centrifuge bowls for other blood-processing applications.

Quality control of computational fluid dynamics in indoor environments

DEFF Research Database (Denmark)

Sørensen, Dan Nørtoft; Nielsen, P. V.

2003-01-01

Computational fluid dynamics (CFD) is used routinely to predict air movement and distributions of temperature and concentrations in indoor environments. Modelling and numerical errors are inherent in such studies and must be considered when the results are presented. Here, we discuss modelling as...... the quality of CFD calculations, as well as guidelines for the minimum information that should accompany all CFD-related publications to enable a scientific judgment of the quality of the study....

Modeling of temperature profiles in an environmental transmission electron microscope using computational fluid dynamics

International Nuclear Information System (INIS)

Mølgaard Mortensen, Peter; Willum Hansen, Thomas; Birkedal Wagner, Jakob; Degn Jensen, Anker

2015-01-01

The temperature and velocity field, pressure distribution, and the temperature variation across the sample region inside an environmental transmission electron microscope (ETEM) have been modeled by means of computational fluid dynamics (CFD). Heating the sample area by a furnace type TEM holder gives rise to temperature gradients over the sample area. Three major mechanisms have been identified with respect to heat transfer in the sample area: radiation from the grid, conduction in the grid, and conduction in the gas. A parameter sensitivity analysis showed that the sample temperature was affected by the conductivity of the gas, the emissivity of the sample grid, and the conductivity of the grid. Ideally the grid should be polished and made from a material with good conductivity, e.g. copper. With hydrogen gas, which has the highest conductivity of the gases studied, the temperature difference over the TEM grid is less than 5 °C, at what must be considered typical conditions, and it is concluded that the conditions on the sample grid in the ETEM can be considered as isothermal during general use. - Highlights: • Computational fluid dynamics used for mapping flow and temperature in ETEM setup. • Temperature gradient across TEM grid in furnace based heating holder very small in ETEM. • Conduction from TEM grid and gas in addition to radiation from TEM grid most important. • Pressure drop in ETEM limited to the pressure limiting apertures

A Novel Computer Virus Propagation Model under Security Classification

Directory of Open Access Journals (Sweden)

Qingyi Zhu

2017-01-01

Full Text Available In reality, some computers have specific security classification. For the sake of safety and cost, the security level of computers will be upgraded with increasing of threats in networks. Here we assume that there exists a threshold value which determines when countermeasures should be taken to level up the security of a fraction of computers with low security level. And in some specific realistic environments the propagation network can be regarded as fully interconnected. Inspired by these facts, this paper presents a novel computer virus dynamics model considering the impact brought by security classification in full interconnection network. By using the theory of dynamic stability, the existence of equilibria and stability conditions is analysed and proved. And the above optimal threshold value is given analytically. Then, some numerical experiments are made to justify the model. Besides, some discussions and antivirus measures are given.

Irrigant flow in the root canal: experimental validation of an unsteady Computational Fluid Dynamics model using high-speed imaging.

Science.gov (United States)

Boutsioukis, C; Verhaagen, B; Versluis, M; Kastrinakis, E; van der Sluis, L W M

2010-05-01

To compare the results of a Computational Fluid Dynamics (CFD) simulation of the irrigant flow within a prepared root canal, during final irrigation with a syringe and a needle, with experimental high-speed visualizations and theoretical calculations of an identical geometry and to evaluate the effect of off-centre positioning of the needle inside the root canal. A CFD model was created to simulate irrigant flow from a side-vented needle inside a prepared root canal. Calculations were carried out for four different positions of the needle inside a prepared root canal. An identical root canal model was made from poly-dimethyl-siloxane (PDMS). High-speed imaging of the flow seeded with particles and Particle Image Velocimetry (PIV) were combined to obtain the velocity field inside the root canal experimentally. Computational, theoretical and experimental results were compared to assess the validity of the computational model. Comparison between CFD computations and experiments revealed good agreement in the velocity magnitude and vortex location and size. Small lateral displacements of the needle inside the canal had a limited effect on the flow field. High-speed imaging experiments together with PIV of the flow inside a simulated root canal showed a good agreement with the CFD model, even though the flow was unsteady. Therefore, the CFD model is able to predict reliably the flow in similar domains.

An introduction to Computational Fluid Dynamics

DEFF Research Database (Denmark)

Sørensen, Lars Schiøtt

1999-01-01

CFD is the shortname for Computational Fluid Dynamics and is a numerical method by means of which we can analyze systems containing fluids. For instance systems dealing with heat flow or smoke control systems acting when a fire occur in a building.......CFD is the shortname for Computational Fluid Dynamics and is a numerical method by means of which we can analyze systems containing fluids. For instance systems dealing with heat flow or smoke control systems acting when a fire occur in a building....

Computational Models for Calcium-Mediated Astrocyte Functions

Directory of Open Access Journals (Sweden)

Tiina Manninen

2018-04-01

Full Text Available The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro, but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop

Computational Models for Calcium-Mediated Astrocyte Functions.

Science.gov (United States)

Manninen, Tiina; Havela, Riikka; Linne, Marja-Leena

2018-01-01

The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro , but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop the models. Thus

Notions of similarity for computational biology models

KAUST Repository

Waltemath, Dagmar

2016-03-21

Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users\\' intuition about model similarity, and to support complex model searches in databases.

Notions of similarity for computational biology models

KAUST Repository

Waltemath, Dagmar; Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knuepfer, Christian; Liebermeister, Wolfram

2016-01-01

Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of similarity may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here, we introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users' intuition about model similarity, and to support complex model searches in databases.

Temperature control of CMS Barrel ECAL (EB) : computational thermo-hydraulic model for dynamic behaviour, control aspects

CERN Document Server

Wertelaers, P

2010-01-01

The current design foresees a central heat exchanger followed by a controlled post heater, for all ECAL. We discuss the scheme and try to assess its performance, from a Barrel viewpoint. This is based on computational work. The coolant transfer pipes play an essential role in building a dynamical model. After some studies on the behaviour of the cooling circuit itself, a strong yet simple controller is proposed. Then, the system with feedback control is scrutinized, with emphasis on disturbance rejection. The most relevant disturbances are cooling ripple, pipe heat attack, and electronics’ switching.

Computational fluid dynamics in fire engineering theory, modelling and practice

CERN Document Server

Yuen, Kwok Kit

2009-01-01

Fire and combustion presents a significant engineering challenge to mechanical, civil and dedicated fire engineers, as well as specialists in the process and chemical, safety, buildings and structural fields. We are reminded of the tragic outcomes of 'untenable' fire disasters such as at King's Cross underground station or Switzerland's St Gotthard tunnel. In these and many other cases, computational fluid dynamics (CFD) is at the forefront of active research into unravelling the probable causes of fires and helping to design structures and systems to ensure that they are less likely in the f

Modeling fires in adjacent ship compartments with computational fluid dynamics

International Nuclear Information System (INIS)

Wix, S.D.; Cole, J.K.; Koski, J.A.

1998-01-01

This paper presents an analysis of the thermal effects on radioactive (RAM) transportation pack ages with a fire in an adjacent compartment. An assumption for this analysis is that the adjacent hold fire is some sort of engine room fire. Computational fluid dynamics (CFD) analysis tools were used to perform the analysis in order to include convective heat transfer effects. The analysis results were compared to experimental data gathered in a series of tests on the United States Coast Guard ship Mayo Lykes located at Mobile, Alabama. (authors)

Development and Validation of Computational Fluid Dynamics Models for Prediction of Heat Transfer and Thermal Microenvironments of Corals

Science.gov (United States)

Ong, Robert H.; King, Andrew J. C.; Mullins, Benjamin J.; Cooper, Timothy F.; Caley, M. Julian

2012-01-01

We present Computational Fluid Dynamics (CFD) models of the coupled dynamics of water flow, heat transfer and irradiance in and around corals to predict temperatures experienced by corals. These models were validated against controlled laboratory experiments, under constant and transient irradiance, for hemispherical and branching corals. Our CFD models agree very well with experimental studies. A linear relationship between irradiance and coral surface warming was evident in both the simulation and experimental result agreeing with heat transfer theory. However, CFD models for the steady state simulation produced a better fit to the linear relationship than the experimental data, likely due to experimental error in the empirical measurements. The consistency of our modelling results with experimental observations demonstrates the applicability of CFD simulations, such as the models developed here, to coral bleaching studies. A study of the influence of coral skeletal porosity and skeletal bulk density on surface warming was also undertaken, demonstrating boundary layer behaviour, and interstitial flow magnitude and temperature profiles in coral cross sections. Our models compliment recent studies showing systematic changes in these parameters in some coral colonies and have utility in the prediction of coral bleaching. PMID:22701582

Error suppression and error correction in adiabatic quantum computation: non-equilibrium dynamics

International Nuclear Information System (INIS)

Sarovar, Mohan; Young, Kevin C

2013-01-01

While adiabatic quantum computing (AQC) has some robustness to noise and decoherence, it is widely believed that encoding, error suppression and error correction will be required to scale AQC to large problem sizes. Previous works have established at least two different techniques for error suppression in AQC. In this paper we derive a model for describing the dynamics of encoded AQC and show that previous constructions for error suppression can be unified with this dynamical model. In addition, the model clarifies the mechanisms of error suppression and allows the identification of its weaknesses. In the second half of the paper, we utilize our description of non-equilibrium dynamics in encoded AQC to construct methods for error correction in AQC by cooling local degrees of freedom (qubits). While this is shown to be possible in principle, we also identify the key challenge to this approach: the requirement of high-weight Hamiltonians. Finally, we use our dynamical model to perform a simplified thermal stability analysis of concatenated-stabilizer-code encoded many-body systems for AQC or quantum memories. This work is a companion paper to ‘Error suppression and error correction in adiabatic quantum computation: techniques and challenges (2013 Phys. Rev. X 3 041013)’, which provides a quantum information perspective on the techniques and limitations of error suppression and correction in AQC. In this paper we couch the same results within a dynamical framework, which allows for a detailed analysis of the non-equilibrium dynamics of error suppression and correction in encoded AQC. (paper)

Colour in visualisation for computational fluid dynamics

OpenAIRE

Kinnear, D; Atherton, MA; Collins, MW; Dokhan, J; Karayiannis, TG

2006-01-01

Colour is used in computational fluid dynamic (CFD) simulations in two key ways. First it is used to visualise the geometry and allow the engineers to be confident that the model constructed is a good representation of the engineering situation. Once an analysis has been completed, colour is used in post-processing the data from the simulations to illustrate the complex fluid mechanic phenomena under investigation. This paper describes these two uses of colour and provides some examples to il...

Computational Fluid Dynamics of Choanoflagellate Filter-Feeding

DEFF Research Database (Denmark)

Asadzadeh, Seyed Saeed; Walther, Jens Honore; Nielsen, Lasse Tor

Choanoflagellates are unicellular aquatic organisms with a single flagellum that drives a feeding current through a funnel-shaped collar filter on which bacteria-sized prey are caught. Using computational fluid dynamics (CFD) we model the beating flagellum and the complex filter flow of the choanoflagell...... to suggest a radically different filtration mechanism that requires a flagellar vane (sheet), and addition of a wide vane in our CFD model allows us to correctly predict the observed clearance rate....

Dynamic modeling and optimal joint torque coordination of advanced robotic systems

Science.gov (United States)

Kang, Hee-Jun

The development is documented of an efficient dynamic modeling algorithm and the subsequent optimal joint input load coordination of advanced robotic systems for industrial application. A closed-form dynamic modeling algorithm for the general closed-chain robotic linkage systems is presented. The algorithm is based on the transfer of system dependence from a set of open chain Lagrangian coordinates to any desired system generalized coordinate set of the closed-chain. Three different techniques for evaluation of the kinematic closed chain constraints allow the representation of the dynamic modeling parameters in terms of system generalized coordinates and have no restriction with regard to kinematic redundancy. The total computational requirement of the closed-chain system model is largely dependent on the computation required for the dynamic model of an open kinematic chain. In order to improve computational efficiency, modification of an existing open-chain KIC based dynamic formulation is made by the introduction of the generalized augmented body concept. This algorithm allows a 44 pct. computational saving over the current optimized one (O(N4), 5995 when N = 6). As means of resolving redundancies in advanced robotic systems, local joint torque optimization is applied for effectively using actuator power while avoiding joint torque limits. The stability problem in local joint torque optimization schemes is eliminated by using fictitious dissipating forces which act in the necessary null space. The performance index representing the global torque norm is shown to be satisfactory. In addition, the resulting joint motion trajectory becomes conservative, after a transient stage, for repetitive cyclic end-effector trajectories. The effectiveness of the null space damping method is shown. The modular robot, which is built of well defined structural modules from a finite-size inventory and is controlled by one general computer system, is another class of evolving

Computationally efficient statistical differential equation modeling using homogenization

Science.gov (United States)

Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.

2013-01-01

Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.

Understanding Emergency Care Delivery Through Computer Simulation Modeling.

Science.gov (United States)

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.

An efficient nonlinear finite-difference approach in the computational modeling of the dynamics of a nonlinear diffusion-reaction equation in microbial ecology.

Science.gov (United States)

Macías-Díaz, J E; Macías, Siegfried; Medina-Ramírez, I E

2013-12-01

In this manuscript, we present a computational model to approximate the solutions of a partial differential equation which describes the growth dynamics of microbial films. The numerical technique reported in this work is an explicit, nonlinear finite-difference methodology which is computationally implemented using Newton's method. Our scheme is compared numerically against an implicit, linear finite-difference discretization of the same partial differential equation, whose computer coding requires an implementation of the stabilized bi-conjugate gradient method. Our numerical results evince that the nonlinear approach results in a more efficient approximation to the solutions of the biofilm model considered, and demands less computer memory. Moreover, the positivity of initial profiles is preserved in the practice by the nonlinear scheme proposed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Computational fluid dynamics modeling of Bacillus anthracis spore deposition in rabbit and human respiratory airways

Energy Technology Data Exchange (ETDEWEB)

Kabilan, S.; Suffield, S. R.; Recknagle, K. P.; Jacob, R. E.; Einstein, D. R.; Kuprat, A. P.; Carson, J. P.; Colby, S. M.; Saunders, J. H.; Hines, S. A.; Teeguarden, J. G.; Straub, T. M.; Moe, M.; Taft, S. C.; Corley, R. A.

2016-09-01

Three-dimensional computational fluid dynamics and Lagrangian particle deposition models were developed to compare the deposition of aerosolized Bacillus anthracis spores in the respiratory airways of a human with that of the rabbit, a species commonly used in the study of anthrax disease. The respiratory airway geometries for each species were derived respectively from computed tomography (CT) and µCT images. Both models encompassed airways that extended from the external nose to the lung with a total of 272 outlets in the human model and 2878 outlets in the rabbit model. All simulations of spore deposition were conducted under transient, inhalation–exhalation breathing conditions using average species-specific minute volumes. Two different exposure scenarios were modeled in the rabbit based upon experimental inhalation studies. For comparison, human simulations were conducted at the highest exposure concentration used during the rabbit experimental exposures. Results demonstrated that regional spore deposition patterns were sensitive to airway geometry and ventilation profiles. Due to the complex airway geometries in the rabbit nose, higher spore deposition efficiency was predicted in the nasal sinus compared to the human at the same air concentration of anthrax spores. In contrast, higher spore deposition was predicted in the lower conducting airways of the human compared to the rabbit lung due to differences in airway branching pattern. This information can be used to refine published and ongoing biokinetic models of inhalation anthrax spore exposures, which currently estimate deposited spore concentrations based solely upon exposure concentrations and inhaled doses that do not factor in species-specific anatomy and physiology for deposition.

Computational Fluid Dynamics Modeling of Bacillus anthracis Spore Deposition in Rabbit and Human Respiratory Airways

Energy Technology Data Exchange (ETDEWEB)

Kabilan, Senthil; Suffield, Sarah R.; Recknagle, Kurtis P.; Jacob, Rick E.; Einstein, Daniel R.; Kuprat, Andrew P.; Carson, James P.; Colby, Sean M.; Saunders, James H.; Hines, Stephanie; Teeguarden, Justin G.; Straub, Tim M.; Moe, M.; Taft, Sarah; Corley, Richard A.

2016-09-30

Three-dimensional computational fluid dynamics and Lagrangian particle deposition models were developed to compare the deposition of aerosolized Bacillus anthracis spores in the respiratory airways of a human with that of the rabbit, a species commonly used in the study of anthrax disease. The respiratory airway geometries for each species were derived from computed tomography (CT) or µCT images. Both models encompassed airways that extended from the external nose to the lung with a total of 272 outlets in the human model and 2878 outlets in the rabbit model. All simulations of spore deposition were conducted under transient, inhalation-exhalation breathing conditions using average species-specific minute volumes. The highest exposure concentration was modeled in the rabbit based upon prior acute inhalation studies. For comparison, human simulation was also conducted at the same concentration. Results demonstrated that regional spore deposition patterns were sensitive to airway geometry and ventilation profiles. Due to the complex airway geometries in the rabbit nose, higher spore deposition efficiency was predicted in the upper conducting airways compared to the human at the same air concentration of anthrax spores. As a result, higher particle deposition was predicted in the conducting airways and deep lung of the human compared to the rabbit lung due to differences in airway branching pattern. This information can be used to refine published and ongoing biokinetic models of inhalation anthrax spore exposures, which currently estimate deposited spore concentrations based solely upon exposure concentrations and inhaled doses that do not factor in species-specific anatomy and physiology.

Dynamic computer simulation of the Fort St. Vrain steam turbines

International Nuclear Information System (INIS)

Conklin, J.C.

1983-01-01

A computer simulation is described for the dynamic response of the Fort St. Vrain nuclear reactor regenerative intermediate- and low-pressure steam turbines. The fundamental computer-modeling assumptions for the turbines and feedwater heaters are developed. A turbine heat balance specifying steam and feedwater conditions at a given generator load and the volumes of the feedwater heaters are all that are necessary as descriptive input parameters. Actual plant data for a generator load reduction from 100 to 50% power (which occurred as part of a plant transient on November 9, 1981) are compared with computer-generated predictions, with reasonably good agreement

The extended RBAC model based on grid computing

Institute of Scientific and Technical Information of China (English)

CHEN Jian-gang; WANG Ru-chuan; WANG Hai-yan

2006-01-01

This article proposes the extended role-based access control (RBAC) model for solving dynamic and multidomain problems in grid computing, The formulated description of the model has been provided. The introduction of context and the mapping relations of context-to-role and context-to-permission help the model adapt to dynamic property in grid environment.The multidomain role inheritance relation by the authorization agent service realizes the multidomain authorization amongst the autonomy domain. A function has been proposed for solving the role inheritance conflict during the establishment of the multidomain role inheritance relation.

Analytical, Computational Fluid Dynamics and Flight Dynamics of Coandă MAV

Science.gov (United States)

Djojodihardjo, H.; Ahmed, RI

2016-11-01

The paper establishes the basic working relationships among various relevant variables and parameters governing the aerodynamics forces and performance measures of Coandă MAV in hover and translatory motion. With such motivation, capitalizing on the basic fundamental principles, the Fluid Dynamics and Flight Mechanics of semi-spherical Coandă MAV configurations are revisited and analyzed as a baseline. To gain better understanding on the principle of Coandă MAV lift generation, a mathematical model for a spherical Coandă MAV is developed and analyzed from first physical principles. To gain further insight into the prevailing flow field around a Coandă MAV, as well as to verify the theoretical prediction presented in the work, a computational fluid dynamic CFD simulation for a Coandă MAV generic model are elaborated using commercial software FLUENT®. In addition, the equation of motion for translatory motion of Coandă MAV is elaborated. The mathematical model and derived performance measures are shown to be capable in describing the physical phenomena of the flow field of the semi-spherical Coandă MAV. The relationships between the relevant parameters of the mathematical model of the Coandă MAV to the forces acting on it are elaborated subsequently.

An Accurate and Dynamic Computer Graphics Muscle Model

Science.gov (United States)

Levine, David Asher

1997-01-01

A computer based musculo-skeletal model was developed at the University in the departments of Mechanical and Biomedical Engineering. This model accurately represents human shoulder kinematics. The result of this model is the graphical display of bones moving through an appropriate range of motion based on inputs of EMGs and external forces. The need existed to incorporate a geometric muscle model in the larger musculo-skeletal model. Previous muscle models did not accurately represent muscle geometries, nor did they account for the kinematics of tendons. This thesis covers the creation of a new muscle model for use in the above musculo-skeletal model. This muscle model was based on anatomical data from the Visible Human Project (VHP) cadaver study. Two-dimensional digital images from the VHP were analyzed and reconstructed to recreate the three-dimensional muscle geometries. The recreated geometries were smoothed, reduced, and sliced to form data files defining the surfaces of each muscle. The muscle modeling function opened these files during run-time and recreated the muscle surface. The modeling function applied constant volume limitations to the muscle and constant geometry limitations to the tendons.

Contact dynamics math model

Science.gov (United States)

Glaese, John R.; Tobbe, Patrick A.

1986-01-01

The Space Station Mechanism Test Bed consists of a hydraulically driven, computer controlled six degree of freedom (DOF) motion system with which docking, berthing, and other mechanisms can be evaluated. Measured contact forces and moments are provided to the simulation host computer to enable representation of orbital contact dynamics. This report describes the development of a generalized math model which represents the relative motion between two rigid orbiting vehicles. The model allows motion in six DOF for each body, with no vehicle size limitation. The rotational and translational equations of motion are derived. The method used to transform the forces and moments from the sensor location to the vehicles' centers of mass is also explained. Two math models of docking mechanisms, a simple translational spring and the Remote Manipulator System end effector, are presented along with simulation results. The translational spring model is used in an attempt to verify the simulation with compensated hardware in the loop results.

Modelling of dynamic equivalents in electric power grids

International Nuclear Information System (INIS)

Craciun, Diana Iuliana

2010-01-01

In a first part, this research thesis proposes a description of the context and new constraints of electric grids: architecture, decentralized production with the impact of distributed energy resource systems, dynamic simulation, and interest of equivalent models. Then, the author discusses the modelling of the different components of electric grids: synchronous and asynchronous machines, distributed energy resource with power electronic interface, loading models. She addresses the techniques of reduction of electric grid models: conventional reduction methods, dynamic equivalence methods using non linear approaches or evolutionary algorithm-based methods of assessment of parameters. This last approach is then developed and implemented, and a new method of computation of dynamic equivalents is described

Adaptive Dynamic Process Scheduling on Distributed Memory Parallel Computers

Directory of Open Access Journals (Sweden)

Wei Shu

1994-01-01

Full Text Available One of the challenges in programming distributed memory parallel machines is deciding how to allocate work to processors. This problem is particularly important for computations with unpredictable dynamic behaviors or irregular structures. We present a scheme for dynamic scheduling of medium-grained processes that is useful in this context. The adaptive contracting within neighborhood (ACWN is a dynamic, distributed, load-dependent, and scalable scheme. It deals with dynamic and unpredictable creation of processes and adapts to different systems. The scheme is described and contrasted with two other schemes that have been proposed in this context, namely the randomized allocation and the gradient model. The performance of the three schemes on an Intel iPSC/2 hypercube is presented and analyzed. The experimental results show that even though the ACWN algorithm incurs somewhat larger overhead than the randomized allocation, it achieves better performance in most cases due to its adaptiveness. Its feature of quickly spreading the work helps it outperform the gradient model in performance and scalability.

Security Management Model in Cloud Computing Environment

OpenAIRE

Ahmadpanah, Seyed Hossein

2016-01-01

In the cloud computing environment, cloud virtual machine (VM) will be more and more the number of virtual machine security and management faced giant Challenge. In order to address security issues cloud computing virtualization environment, this paper presents a virtual machine based on efficient and dynamic deployment VM security management model state migration and scheduling, study of which virtual machine security architecture, based on AHP (Analytic Hierarchy Process) virtual machine de...

An introduction to modeling neuronal dynamics

CERN Document Server

Börgers, Christoph

2017-01-01

This book is intended as a text for a one-semester course on Mathematical and Computational Neuroscience for upper-level undergraduate and beginning graduate students of mathematics, the natural sciences, engineering, or computer science. An undergraduate introduction to differential equations is more than enough mathematical background. Only a slim, high school-level background in physics is assumed, and none in biology. Topics include models of individual nerve cells and their dynamics, models of networks of neurons coupled by synapses and gap junctions, origins and functions of population rhythms in neuronal networks, and models of synaptic plasticity. An extensive online collection of Matlab programs generating the figures accompanies the book. .

A Lagrangian dynamic subgrid-scale model turbulence

Science.gov (United States)

Meneveau, C.; Lund, T. S.; Cabot, W.

1994-01-01

A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.

High-Precision Computation: Mathematical Physics and Dynamics

International Nuclear Information System (INIS)

Bailey, D.H.; Barrio, R.; Borwein, J.M.

2010-01-01

At the present time, IEEE 64-bit oating-point arithmetic is suficiently accurate for most scientic applications. However, for a rapidly growing body of important scientic computing applications, a higher level of numeric precision is required. Such calculations are facilitated by high-precision software packages that include high-level language translation modules to minimize the conversion e ort. This pa- per presents a survey of recent applications of these techniques and provides someanalysis of their numerical requirements. These applications include supernova simulations, climate modeling, planetary orbit calculations, Coulomb n-body atomic systems, studies of the one structure constant, scattering amplitudes of quarks, glu- ons and bosons, nonlinear oscillator theory, experimental mathematics, evaluation of orthogonal polynomials, numerical integration of ODEs, computation of periodic orbits, studies of the splitting of separatrices, detection of strange nonchaotic at- tractors, Ising theory, quantum held theory, and discrete dynamical systems. We conclude that high-precision arithmetic facilities are now an indispensable compo- nent of a modern large-scale scientic computing environment.

High-Precision Computation: Mathematical Physics and Dynamics

Energy Technology Data Exchange (ETDEWEB)

Bailey, D. H.; Barrio, R.; Borwein, J. M.

2010-04-01

At the present time, IEEE 64-bit oating-point arithmetic is suficiently accurate for most scientic applications. However, for a rapidly growing body of important scientic computing applications, a higher level of numeric precision is required. Such calculations are facilitated by high-precision software packages that include high-level language translation modules to minimize the conversion e ort. This pa- per presents a survey of recent applications of these techniques and provides someanalysis of their numerical requirements. These applications include supernova simulations, climate modeling, planetary orbit calculations, Coulomb n-body atomic systems, studies of the one structure constant, scattering amplitudes of quarks, glu- ons and bosons, nonlinear oscillator theory, experimental mathematics, evaluation of orthogonal polynomials, numerical integration of ODEs, computation of periodic orbits, studies of the splitting of separatrices, detection of strange nonchaotic at- tractors, Ising theory, quantum held theory, and discrete dynamical systems. We conclude that high-precision arithmetic facilities are now an indispensable compo- nent of a modern large-scale scientic computing environment.

Advanced computational multi-fluid dynamics: a new model for understanding electrokinetic phenomena in porous media

Science.gov (United States)

Gulamali, M. Y.; Saunders, J. H.; Jackson, M. D.; Pain, C. C.

2009-04-01

We present results from a new computational multi-fluid dynamics code, designed to model the transport of heat, mass and chemical species during flow of single or multiple immiscible fluid phases through porous media, including gravitational effects and compressibility. The model also captures the electrical phenomena which may arise through electrokinetic, electrochemical and electrothermal coupling. Building on the advanced computational technology of the Imperial College Ocean Model, this new development leads the way towards a complex multiphase code using arbitrary unstructured and adaptive meshes, and domains decomposed to run in parallel over a cluster of workstations or a dedicated parallel computer. These facilities will allow efficient and accurate modelling of multiphase flows which capture large- and small-scale transport phenomena, while preserving the important geology and/or surface topology to make the results physically meaningful and realistic. Applications include modelling of contaminant transport in aquifers, multiphase flow during hydrocarbon production, migration of carbon dioxide during sequestration, and evaluation of the design and safety of nuclear reactors. Simulations of the streaming potential resulting from multiphase flow in laboratory- and field-scale models demonstrate that streaming potential signals originate at fluid fronts, and at geologic boundaries where fluid saturation changes. This suggests that downhole measurements of streaming potential may be used to inform production strategies in oil and gas reservoirs. As water encroaches on an oil production well, the streaming-potential signal associated with the water front encompasses the well even when the front is up to 100 m away, so the potential measured at the well starts to change significantly relative to a distant reference electrode. Variations in the geometry of the encroaching water front could be characterized using an array of electrodes positioned along the well

Modeling biological pathway dynamics with timed automata.

Science.gov (United States)

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Modelling the Dynamics of Emotional Awareness

NARCIS (Netherlands)

Thilakarathne, D.J.; Treur, J.; Schaub, T.

2014-01-01

In this paper, based on literature from Cognitive and Affective Neuroscience, a computational agent model is introduced incorporating the role of emotional awareness states in the dynamics of action generation. More specifically, it covers both automatic, unconscious (bottom-up) and more cognitive

Computational Fluid Dynamics and Room Air Movement

DEFF Research Database (Denmark)

Nielsen, Peter Vilhelm

2004-01-01

on the mass fraction transport equation. The importance of ?false? or numerical diffusion is also addressed in connection with the simple description of a supply opening. The different aspects of boundary conditions in the indoor environment as e.g. the simulation of Air Terminal Devices and the simulation......Nielsen, P.V. Computational Fluid Dynamics and Room Air Movement. Indoor Air, International Journal of Indoor Environment and Health, Vol. 14, Supplement 7, pp. 134-143, 2004. ABSTRACT Computational Fluid Dynamics (CFD) and new developments of CFD in the indoor environment as well as quality...... considerations are important elements in the study of energy consumption, thermal comfort and indoor air quality in buildings. The paper discusses the quality level of Computational Fluid Dynamics and the involved schemes (first, second and third order schemes) by the use of the Smith and Hutton problem...

Computer processing of dynamic scintigraphic studies

International Nuclear Information System (INIS)

Ullmann, V.

1985-01-01

The methods are discussed of the computer processing of dynamic scintigraphic studies which were developed, studied or implemented by the authors within research task no. 30-02-03 in nuclear medicine within the five year plan 1981 to 85. This was mainly the method of computer processing radionuclide angiography, phase radioventriculography, regional lung ventilation, dynamic sequential scintigraphy of kidneys and radionuclide uroflowmetry. The problems are discussed of the automatic definition of fields of interest, the methodology of absolute volumes of the heart chamber in radionuclide cardiology, the design and uses are described of the multipurpose dynamic phantom of heart activity for radionuclide angiocardiography and ventriculography developed within the said research task. All methods are documented with many figures showing typical clinical (normal and pathological) and phantom measurements. (V.U.)

Dynamical duality of type- and token-computation as an abstract brain

Energy Technology Data Exchange (ETDEWEB)

Gunji, Yukio-Pegio [Department of Earth and Planetary Sciences, Faculty of Science, Kobe University (Japan); Graduate School of Science and Technology, Kobe University (Japan)] e-mail: yukio@kobe-u.ac.jp; Miyoshi, Hiroyuki [Department of Computer Sciences, Faculty of Science, Kyoto Sangyo University (Japan); Takahashi, Tatsuji [Graduate School of Science and Technology, Kobe University (Japan); Kamiura, Moto [Graduate School of Science and Technology, Kobe University (Japan)

2006-03-01

In brain science, there are few researches focusing on the theoretical relation between cognition (top-down processing) and perception (bottom-up processing). Philosophically they were regarded as the alternative leading to the dualism of mind and body, while it is an adequate problem for the endo-physics. Qualia are conjectured as the hard problem under those situations. To overcome such an impasse, we propose an abstract brain model featuring the dynamical duality of two parts of computations in a brain, in a term of endo-physics and internal measurement. Two parts of computations are expressed as binary relations, and the relationship between them is expressed as a pair of maps, called an infomorphism [Barwise J, Seligman J. Information flow, the logic of distributed systems. Cambridge University Press 1997]. Dynamical duality is implemented by the interaction between a binary relation and an infomorphism, and that leads to a dynamical change of a pair of binary relations. When a binary relation is expressed as a partial ordered set, one can check whether a part of computation is closed with respect to logical operations (i.e., a lattice) or not. By estimating a binary relation in terms of properties of lattice, we show that dynamical infomorphism robustly develops to a pair of logical computations corresponding to type cognition and non-logical one corresponding to qualia perception. It implies origin of differentiation and robust co-existence of type-cognition and qualia-perception. It is easy to see that dynamical infomorphism can also develop to a pair of singleton sets corresponding to savants' special cognitive style.

Dynamical duality of type- and token-computation as an abstract brain

International Nuclear Information System (INIS)

Gunji, Yukio-Pegio; Miyoshi, Hiroyuki; Takahashi, Tatsuji; Kamiura, Moto

2006-01-01

In brain science, there are few researches focusing on the theoretical relation between cognition (top-down processing) and perception (bottom-up processing). Philosophically they were regarded as the alternative leading to the dualism of mind and body, while it is an adequate problem for the endo-physics. Qualia are conjectured as the hard problem under those situations. To overcome such an impasse, we propose an abstract brain model featuring the dynamical duality of two parts of computations in a brain, in a term of endo-physics and internal measurement. Two parts of computations are expressed as binary relations, and the relationship between them is expressed as a pair of maps, called an infomorphism [Barwise J, Seligman J. Information flow, the logic of distributed systems. Cambridge University Press 1997]. Dynamical duality is implemented by the interaction between a binary relation and an infomorphism, and that leads to a dynamical change of a pair of binary relations. When a binary relation is expressed as a partial ordered set, one can check whether a part of computation is closed with respect to logical operations (i.e., a lattice) or not. By estimating a binary relation in terms of properties of lattice, we show that dynamical infomorphism robustly develops to a pair of logical computations corresponding to type cognition and non-logical one corresponding to qualia perception. It implies origin of differentiation and robust co-existence of type-cognition and qualia-perception. It is easy to see that dynamical infomorphism can also develop to a pair of singleton sets corresponding to savants' special cognitive style

Accuracy of the microcanonical Lanczos method to compute real-frequency dynamical spectral functions of quantum models at finite temperatures

Science.gov (United States)

Okamoto, Satoshi; Alvarez, Gonzalo; Dagotto, Elbio; Tohyama, Takami

2018-04-01

We examine the accuracy of the microcanonical Lanczos method (MCLM) developed by Long et al. [Phys. Rev. B 68, 235106 (2003), 10.1103/PhysRevB.68.235106] to compute dynamical spectral functions of interacting quantum models at finite temperatures. The MCLM is based on the microcanonical ensemble, which becomes exact in the thermodynamic limit. To apply the microcanonical ensemble at a fixed temperature, one has to find energy eigenstates with the energy eigenvalue corresponding to the internal energy in the canonical ensemble. Here, we propose to use thermal pure quantum state methods by Sugiura and Shimizu [Phys. Rev. Lett. 111, 010401 (2013), 10.1103/PhysRevLett.111.010401] to obtain the internal energy. After obtaining the energy eigenstates using the Lanczos diagonalization method, dynamical quantities are computed via a continued fraction expansion, a standard procedure for Lanczos-based numerical methods. Using one-dimensional antiferromagnetic Heisenberg chains with S =1 /2 , we demonstrate that the proposed procedure is reasonably accurate, even for relatively small systems.

From Occasional Choices to Inevitable Musts: A Computational Model of Nicotine Addiction

Directory of Open Access Journals (Sweden)

Selin Metin

2012-01-01

Full Text Available Although, there are considerable works on the neural mechanisms of reward-based learning and decision making, and most of them mention that addiction can be explained by malfunctioning in these cognitive processes, there are very few computational models. This paper focuses on nicotine addiction, and a computational model for nicotine addiction is proposed based on the neurophysiological basis of addiction. The model compromises different levels ranging from molecular basis to systems level, and it demonstrates three different possible behavioral patterns which are addict, nonaddict, and indecisive. The dynamical behavior of the proposed model is investigated with tools used in analyzing nonlinear dynamical systems, and the relation between the behavioral patterns and the dynamics of the system is discussed.

Dynamic neutron scattering from conformational dynamics. I. Theory and Markov models.

Science.gov (United States)

Lindner, Benjamin; Yi, Zheng; Prinz, Jan-Hendrik; Smith, Jeremy C; Noé, Frank

2013-11-07

The dynamics of complex molecules can be directly probed by inelastic neutron scattering experiments. However, many of the underlying dynamical processes may exist on similar timescales, which makes it difficult to assign processes seen experimentally to specific structural rearrangements. Here, we show how Markov models can be used to connect structural changes observed in molecular dynamics simulation directly to the relaxation processes probed by scattering experiments. For this, a conformational dynamics theory of dynamical neutron and X-ray scattering is developed, following our previous approach for computing dynamical fingerprints of time-correlation functions [F. Noé, S. Doose, I. Daidone, M. Löllmann, J. Chodera, M. Sauer, and J. Smith, Proc. Natl. Acad. Sci. U.S.A. 108, 4822 (2011)]. Markov modeling is used to approximate the relaxation processes and timescales of the molecule via the eigenvectors and eigenvalues of a transition matrix between conformational substates. This procedure allows the establishment of a complete set of exponential decay functions and a full decomposition into the individual contributions, i.e., the contribution of every atom and dynamical process to each experimental relaxation process.

Computational Fluid Dynamics (CFD) Modeling for High Rate Pulverized Coal Injection (PCI) to Blast Furnaces

International Nuclear Information System (INIS)

Zhou, Chenn

2008-01-01

Pulverized coal injection (PCI) into the blast furnace (BF) has been recognized as an effective way to decrease the coke and total energy consumption along with minimization of environmental impacts. However, increasing the amount of coal injected into the BF is currently limited by the lack of knowledge of some issues related to the process. It is therefore important to understand the complex physical and chemical phenomena in the PCI process. Due to the difficulty in attaining trus BF measurements, Computational fluid dynamics (CFD) modeling has been identified as a useful technology to provide such knowledge. CFD simulation is powerful for providing detailed information on flow properties and performing parametric studies for process design and optimization. In this project, comprehensive 3-D CFD models have been developed to simulate the PCI process under actual furnace conditions. These models provide raceway size and flow property distributions. The results have provided guidance for optimizing the PCI process

Quantum molecular dynamics study of the Su-Schrieffer-Heeger model

NARCIS (Netherlands)

Michielsen, Kristel; Raedt, Hans De

A quantum molecular dynamics technique is presented to compute the static and dynamic properties of a system of fermions coupled to classical degrees of freedom. The method is employed to investigate the properties of the Su-Schrieffer-Heeger model, an electron-phonon model which is often used to

Computer modelling as a tool for understanding language evolution

NARCIS (Netherlands)

de Boer, Bart; Gontier, N; VanBendegem, JP; Aerts, D

2006-01-01

This paper describes the uses of computer models in studying the evolution of language. Language is a complex dynamic system that can be studied at the level of the individual and at the level of the population. Much of the dynamics of language evolution and language change occur because of the

Dynamical modeling of tidal streams

International Nuclear Information System (INIS)

Bovy, Jo

2014-01-01

I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its 'track') in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of 'orphan' streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.

Reduced combustion mechanism for C1-C4 hydrocarbons and its application in computational fluid dynamics flare modeling.

Science.gov (United States)

Damodara, Vijaya; Chen, Daniel H; Lou, Helen H; Rasel, Kader M A; Richmond, Peyton; Wang, Anan; Li, Xianchang

2017-05-01

Emissions from flares constitute unburned hydrocarbons, carbon monoxide (CO), soot, and other partially burned and altered hydrocarbons along with carbon dioxide (CO 2 ) and water. Soot or visible smoke is of particular concern for flare operators/regulatory agencies. The goal of the study is to develop a computational fluid dynamics (CFD) model capable of predicting flare combustion efficiency (CE) and soot emission. Since detailed combustion mechanisms are too complicated for (CFD) application, a 50-species reduced mechanism, LU 3.0.1, was developed. LU 3.0.1 is capable of handling C 4 hydrocarbons and soot precursor species (C 2 H 2 , C 2 H 4 , C 6 H 6 ). The new reduced mechanism LU 3.0.1 was first validated against experimental performance indicators: laminar flame speed, adiabatic flame temperature, and ignition delay. Further, CFD simulations using LU 3.0.1 were run to predict soot emission and CE of air-assisted flare tests conducted in 2010 in Tulsa, Oklahoma, using ANSYS Fluent software. Results of non-premixed probability density function (PDF) model and eddy dissipation concept (EDC) model are discussed. It is also noteworthy that when used in conjunction with the EDC turbulence-chemistry model, LU 3.0.1 can reasonably predict volatile organic compound (VOC) emissions as well. A reduced combustion mechanism containing 50 C 1 -C 4 species and soot precursors has been developed and validated against experimental data. The combustion mechanism is then employed in the computational fluid dynamics (CFD) of modeling of soot emission and combustion efficiency (CE) of controlled flares for which experimental soot and CE data are available. The validated CFD modeling tools are useful for oil, gas, and chemical industries to comply with U.S. Environmental Protection Agency's (EPA) mandate to achieve smokeless flaring with a high CE.

Computational plasticity algorithm for particle dynamics simulations

Science.gov (United States)

Krabbenhoft, K.; Lyamin, A. V.; Vignes, C.

2018-01-01

The problem of particle dynamics simulation is interpreted in the framework of computational plasticity leading to an algorithm which is mathematically indistinguishable from the common implicit scheme widely used in the finite element analysis of elastoplastic boundary value problems. This algorithm provides somewhat of a unification of two particle methods, the discrete element method and the contact dynamics method, which usually are thought of as being quite disparate. In particular, it is shown that the former appears as the special case where the time stepping is explicit while the use of implicit time stepping leads to the kind of schemes usually labelled contact dynamics methods. The framing of particle dynamics simulation within computational plasticity paves the way for new approaches similar (or identical) to those frequently employed in nonlinear finite element analysis. These include mixed implicit-explicit time stepping, dynamic relaxation and domain decomposition schemes.

RETRAN dynamic slip model

International Nuclear Information System (INIS)

McFadden, J.H.; Paulsen, M.P.; Gose, G.C.

1981-01-01

Thermal-hydraulic codes in general use for system calculations are based on extensive analyses of loss-of-coolant accidents following the postulated rupture of a large coolant pipe. In this study, time-dependent equation for the slip velocity in a two-phase flow condition has been incorporated into the RETRAN-02 computer code. This model addition was undertaken to remove a limitation in RETRAN-01 associated with the homogeneous equilibrium mixture model. The dynamic slip equation was derived from a set of two-fluid conservation equations. 18 refs

Advanced data analysis in neuroscience integrating statistical and computational models

CERN Document Server

Durstewitz, Daniel

2017-01-01

This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering.  Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerfu...

Advances in computational dynamics of particles, materials and structures a unified approach

CERN Document Server

Har, Jason

2012-01-01

Computational methods for the modeling and simulation of the dynamic response and behavior of particles, materials and structural systems have had a profound influence on science, engineering and technology. Complex science and engineering applications dealing with complicated structural geometries and materials that would be very difficult to treat using analytical methods have been successfully simulated using computational tools. With the incorporation of quantum, molecular and biological mechanics into new models, these methods are poised to play an even bigger role in the future. Ad

Computational fluid dynamics modelling of left valvular heart diseases during atrial fibrillation

Directory of Open Access Journals (Sweden)

Stefania Scarsoglio

2016-07-01

Full Text Available Background: Although atrial fibrillation (AF, a common arrhythmia, frequently presents in patients with underlying valvular disease, its hemodynamic contributions are not fully understood. The present work aimed to computationally study how physical conditions imposed by pathologic valvular anatomy act on AF hemodynamics. Methods: We simulated AF with different severity grades of left-sided valvular diseases and compared the cardiovascular effects that they exert during AF, compared to lone AF. The fluid dynamics model used here has been recently validated for lone AF and relies on a lumped parameterization of the four heart chambers, together with the systemic and pulmonary circulation. The AF modelling involves: (i irregular, uncorrelated and faster heart rate; (ii atrial contractility dysfunction. Three different grades of severity (mild, moderate, severe were analyzed for each of the four valvulopathies (AS, aortic stenosis, MS, mitral stenosis, AR, aortic regurgitation, MR, mitral regurgitation, by varying–through the valve opening angle–the valve area. Results: Regurgitation was hemodynamically more relevant than stenosis, as the latter led to inefficient cardiac flow, while the former introduced more drastic fluid dynamics variation. Moreover, mitral valvulopathies were more significant than aortic ones. In case of aortic valve diseases, proper mitral functioning damps out changes at atrial and pulmonary levels. In the case of mitral valvulopathy, the mitral valve lost its regulating capability, thus hemodynamic variations almost equally affected regions upstream and downstream of the valve. In particular, the present study revealed that both mitral and aortic regurgitation strongly affect hemodynamics, followed by mitral stenosis, while aortic stenosis has the least impact among the analyzed valvular diseases. Discussion: The proposed approach can provide new mechanistic insights as to which valvular pathologies merit more aggressive

Dynamic modeling of the advanced neutron source reactor

International Nuclear Information System (INIS)

March-Leuba, J.; Ibn-Khayat, M.

1990-01-01

The purpose of this paper is to provide a summary description and some applications of a computer model that has been developed to simulate the dynamic behavior of the advanced neutron source (ANS) reactor. The ANS dynamic model is coded in the advanced continuous simulation language (ACSL), and it represents the reactor core, vessel, primary cooling system, and secondary cooling systems. The use of a simple dynamic model in the early stages of the reactor design has proven very valuable not only in the development of the control and plant protection system but also of components such as pumps and heat exchangers that are usually sized based on steady-state calculations

Benchmarking computational fluid dynamics models of lava flow simulation for hazard assessment, forecasting, and risk management

Science.gov (United States)

Dietterich, Hannah; Lev, Einat; Chen, Jiangzhi; Richardson, Jacob A.; Cashman, Katharine V.

2017-01-01

Numerical simulations of lava flow emplacement are valuable for assessing lava flow hazards, forecasting active flows, designing flow mitigation measures, interpreting past eruptions, and understanding the controls on lava flow behavior. Existing lava flow models vary in simplifying assumptions, physics, dimensionality, and the degree to which they have been validated against analytical solutions, experiments, and natural observations. In order to assess existing models and guide the development of new codes, we conduct a benchmarking study of computational fluid dynamics (CFD) models for lava flow emplacement, including VolcFlow, OpenFOAM, FLOW-3D, COMSOL, and MOLASSES. We model viscous, cooling, and solidifying flows over horizontal planes, sloping surfaces, and into topographic obstacles. We compare model results to physical observations made during well-controlled analogue and molten basalt experiments, and to analytical theory when available. Overall, the models accurately simulate viscous flow with some variability in flow thickness where flows intersect obstacles. OpenFOAM, COMSOL, and FLOW-3D can each reproduce experimental measurements of cooling viscous flows, and OpenFOAM and FLOW-3D simulations with temperature-dependent rheology match results from molten basalt experiments. We assess the goodness-of-fit of the simulation results and the computational cost. Our results guide the selection of numerical simulation codes for different applications, including inferring emplacement conditions of past lava flows, modeling the temporal evolution of ongoing flows during eruption, and probabilistic assessment of lava flow hazard prior to eruption. Finally, we outline potential experiments and desired key observational data from future flows that would extend existing benchmarking data sets.

Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

Science.gov (United States)

Ma, Zhanshan (Sam)

In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three

Simulation of Tailrace Hydrodynamics Using Computational Fluid Dynamics Models

Energy Technology Data Exchange (ETDEWEB)

Cook, Christopher B.; Richmond, Marshall C.

2001-05-01

This report investigates the feasibility of using computational fluid dynamics (CFD) tools to investigate hydrodynamic flow fields surrounding the tailrace zone below large hydraulic structures. Previous and ongoing studies using CFD tools to simulate gradually varied flow with multiple constituents and forebay/intake hydrodynamics have shown that CFD tools can provide valuable information for hydraulic and biological evaluation of fish passage near hydraulic structures. These studies however are incapable of simulating the rapidly varying flow fields that involving breakup of the free-surface, such as those through and below high flow outfalls and spillways. Although the use of CFD tools for these types of flow are still an active area of research, initial applications discussed in this report show that these tools are capable of simulating the primary features of these highly transient flow fields.

Fast reactor safety and computational thermo-fluid dynamics approaches

International Nuclear Information System (INIS)

Ninokata, Hisashi; Shimizu, Takeshi

1993-01-01

This article provides a brief description of the safety principle on which liquid metal cooled fast breeder reactors (LMFBRs) is based and the roles of computations in the safety practices. A number of thermohydraulics models have been developed to date that successfully describe several of the important types of fluids and materials motion encountered in the analysis of postulated accidents in LMFBRs. Most of these models use a mixture of implicit and explicit numerical solution techniques in solving a set of conservation equations formulated in Eulerian coordinates, with special techniques included to specific situations. Typical computational thermo-fluid dynamics approaches are discussed in particular areas of analyses of the physical phenomena relevant to the fuel subassembly thermohydraulics design and that involve describing the motion of molten materials in the core over a large scale. (orig.)

Time series modeling, computation, and inference

CERN Document Server

Prado, Raquel

2010-01-01

The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit

Transmitted wavefront testing with large dynamic range based on computer-aided deflectometry

Science.gov (United States)

Wang, Daodang; Xu, Ping; Gong, Zhidong; Xie, Zhongmin; Liang, Rongguang; Xu, Xinke; Kong, Ming; Zhao, Jun

2018-06-01

The transmitted wavefront testing technique is demanded for the performance evaluation of transmission optics and transparent glass, in which the achievable dynamic range is a key issue. A computer-aided deflectometric testing method with fringe projection is proposed for the accurate testing of transmitted wavefronts with a large dynamic range. Ray tracing of the modeled testing system is carried out to achieve the virtual ‘null’ testing of transmitted wavefront aberrations. The ray aberration is obtained from the ray tracing result and measured slope, with which the test wavefront aberration can be reconstructed. To eliminate testing system modeling errors, a system geometry calibration based on computer-aided reverse optimization is applied to realize accurate testing. Both numerical simulation and experiments have been carried out to demonstrate the feasibility and high accuracy of the proposed testing method. The proposed testing method can achieve a large dynamic range compared with the interferometric method, providing a simple, low-cost and accurate way for the testing of transmitted wavefronts from various kinds of optics and a large amount of industrial transmission elements.

The Dynamic Geometrisation of Computer Programming

Science.gov (United States)

Sinclair, Nathalie; Patterson, Margaret

2018-01-01

The goal of this paper is to explore dynamic geometry environments (DGE) as a type of computer programming language. Using projects created by secondary students in one particular DGE, we analyse the extent to which the various aspects of computational thinking--including both ways of doing things and particular concepts--were evident in their…

Steady-state and dynamic models for particle engulfment during solidification

Science.gov (United States)

Tao, Yutao; Yeckel, Andrew; Derby, Jeffrey J.

2016-06-01

Steady-state and dynamic models are developed to study the physical mechanisms that determine the pushing or engulfment of a solid particle at a moving solid-liquid interface. The mathematical model formulation rigorously accounts for energy and momentum conservation, while faithfully representing the interfacial phenomena affecting solidification phase change and particle motion. A numerical solution approach is developed using the Galerkin finite element method and elliptic mesh generation in an arbitrary Lagrangian-Eulerian implementation, thus allowing for a rigorous representation of forces and dynamics previously inaccessible by approaches using analytical approximations. We demonstrate that this model accurately computes the solidification interface shape while simultaneously resolving thin fluid layers around the particle that arise from premelting during particle engulfment. We reinterpret the significance of premelting via the definition an unambiguous critical velocity for engulfment from steady-state analysis and bifurcation theory. We also explore the complicated transient behaviors that underlie the steady states of this system and posit the significance of dynamical behavior on engulfment events for many systems. We critically examine the onset of engulfment by comparing our computational predictions to those obtained using the analytical model of Rempel and Worster [29]. We assert that, while the accurate calculation of van der Waals repulsive forces remains an open issue, the computational model developed here provides a clear benefit over prior models for computing particle drag forces and other phenomena needed for the faithful simulation of particle engulfment.

Fluid dynamics applications of the Illiac IV computer

Science.gov (United States)

Maccormack, R. W.; Stevens, K. G., Jr.

1976-01-01

The Illiac IV is a parallel-structure computer with computing power an order of magnitude greater than that of conventional computers. It can be used for experimental tasks in fluid dynamics which can be simulated more economically, for simulating flows that cannot be studied by experiment, and for combining computer and experimental simulations. The architecture of Illiac IV is described, and the use of its parallel operation is demonstrated on the example of its solution of the one-dimensional wave equation. For fluid dynamics problems, a special FORTRAN-like vector programming language was devised, called CFD language. Two applications are described in detail: (1) the determination of the flowfield around the space shuttle, and (2) the computation of transonic turbulent separated flow past a thick biconvex airfoil.

Zonal methods and computational fluid dynamics

International Nuclear Information System (INIS)

Atta, E.H.

1985-01-01

Recent advances in developing numerical algorithms for solving fluid flow problems, and the continuing improvement in the speed and storage of large scale computers have made it feasible to compute the flow field about complex and realistic configurations. Current solution methods involve the use of a hierarchy of mathematical models ranging from the linearized potential equation to the Navier Stokes equations. Because of the increasing complexity of both the geometries and flowfields encountered in practical fluid flow simulation, there is a growing emphasis in computational fluid dynamics on the use of zonal methods. A zonal method is one that subdivides the total flow region into interconnected smaller regions or zones. The flow solutions in these zones are then patched together to establish the global flow field solution. Zonal methods are primarily used either to limit the complexity of the governing flow equations to a localized region or to alleviate the grid generation problems about geometrically complex and multicomponent configurations. This paper surveys the application of zonal methods for solving the flow field about two and three-dimensional configurations. Various factors affecting their accuracy and ease of implementation are also discussed. From the presented review it is concluded that zonal methods promise to be very effective for computing complex flowfields and configurations. Currently there are increasing efforts to improve their efficiency, versatility, and accuracy

Computational Fluid Dynamic Modeling of Rocket Based Combined Cycle Engine Flowfields

Science.gov (United States)

Daines, Russell L.; Merkle, Charles L.

1994-01-01

Computational Fluid Dynamic techniques are used to study the flowfield of a fixed geometry Rocket Based Combined Cycle engine operating in rocket ejector mode. Heat addition resulting from the combustion of injected fuel causes the subsonic engine flow to choke and go supersonic in the slightly divergent combustor-mixer section. Reacting flow computations are undertaken to predict the characteristics of solutions where the heat addition is determined by the flowfield. Here, adaptive gridding is used to improve resolution in the shear layers. Results show that the sonic speed is reached in the unheated portions of the flow first, while the heated portions become supersonic later. Comparison with results from another code show reasonable agreement. The coupled solutions show that the character of the combustion-based thermal choking phenomenon can be controlled reasonably well such that there is opportunity to optimize the length and expansion ratio of the combustor-mixer.

The computer code EURDYN - 1 M (release 1) for transient dynamic fluid-structure interaction. Pt.1: governing equations and finite element modelling

International Nuclear Information System (INIS)

Donea, J.; Fasoli-Stella, P.; Giuliani, S.; Halleux, J.P.; Jones, A.V.

1980-01-01

This report describes the governing equations and the finite element modelling used in the computer code EURDYN - 1 M. The code is a non-linear transient dynamic program for the analysis of coupled fluid-structure systems; It is designed for safety studies on LMFBR components (primary containment and fuel subassemblies)

One-dimensional computational modeling on nuclear reactor problems

International Nuclear Information System (INIS)

Alves Filho, Hermes; Baptista, Josue Costa; Trindade, Luiz Fernando Santos; Heringer, Juan Diego dos Santos

2013-01-01

In this article, we present a computational modeling, which gives us a dynamic view of some applications of Nuclear Engineering, specifically in the power distribution and the effective multiplication factor (keff) calculations. We work with one-dimensional problems of deterministic neutron transport theory, with the linearized Boltzmann equation in the discrete ordinates (SN) formulation, independent of time, with isotropic scattering and then built a software (Simulator) for modeling computational problems used in a typical calculations. The program used in the implementation of the simulator was Matlab, version 7.0. (author)

Physical and computational fluid dynamics models for the hemodynamics of the artiodactyl carotid rete.

Science.gov (United States)

O'Brien, Haley D; Bourke, Jason

2015-12-07

In the mammalian order Artiodactyla, the majority of arterial blood entering the intracranial cavity is supplied by a large arterial meshwork called the carotid rete. This vascular structure functionally replaces the internal carotid artery. Extensive experimentation has demonstrated that the artiodactyl carotid rete drives one of the most effective selective brain cooling mechanisms among terrestrial vertebrates. Less well understood is the impact that the unique morphology of the carotid rete may have on the hemodynamics of blood flow to the cerebrum. It has been hypothesized that, relative to the tubular internal carotid arteries of most other vertebrates, the highly convoluted morphology of the carotid rete may increase resistance to flow during extreme changes in cerebral blood pressure, essentially protecting the brain by acting as a resistor. We test this hypothesis by employing simple and complex physical models to a 3D surface rendering of the carotid rete of the domestic goat, Capra hircus. First, we modeled the potential for increased resistance across the carotid rete using an electrical circuit analog. The extensive branching of the rete equates to a parallel circuit that is bound in series by single tubular arteries, both upstream and downstream. This method calculated a near-zero increase in resistance across the rete. Because basic equations do not incorporate drag, shear-stress, and turbulence, we used computational fluid dynamics to simulate the impact of these computationally intensive factors on resistance. Ultimately, both simple and complex models demonstrated negligible changes in resistance and blood pressure across the arterial meshwork. We further tested the resistive potential of the carotid rete by simulating blood pressures known to occur in giraffes. Based on these models, we found resistance (and blood pressure mitigation as a whole) to be an unlikely function for the artiodactyl carotid rete. Copyright © 2015 Elsevier Ltd. All

Computer codes for beam dynamics analysis of cyclotronlike accelerators

Science.gov (United States)

Smirnov, V.

2017-12-01

Computer codes suitable for the study of beam dynamics in cyclotronlike (classical and isochronous cyclotrons, synchrocyclotrons, and fixed field alternating gradient) accelerators are reviewed. Computer modeling of cyclotron segments, such as the central zone, acceleration region, and extraction system is considered. The author does not claim to give a full and detailed description of the methods and algorithms used in the codes. Special attention is paid to the codes already proven and confirmed at the existing accelerating facilities. The description of the programs prepared in the worldwide known accelerator centers is provided. The basic features of the programs available to users and limitations of their applicability are described.

On-line supercapacitor dynamic models for energy conversion and management

International Nuclear Information System (INIS)

Wu, C.H.; Hung, Y.H.; Hong, C.W.

2012-01-01

Highlights: ► On-line supercapacitor dynamic models are derived from time and frequency domains. ► Equivalent circuits with an ANN identifier are derived for nonlinear effects. ► Nonlinear effects include environmental temperature and operating voltage. ► Supercapacitor models can achieve both system fidelity and computation efficiency. - Abstract: This paper develops on-line nonlinear dynamic models of electrochemical supercapacitors which are for energy conversion and management. Based on the theory of electrochemical impedance spectroscopy, extensive alternative current impedance tests have been conducted to investigate the frequency-domain dynamics of these supercapacitors. A Nyquist diagram is plotted to help establish an equivalent electric circuit, which is regarded as the first-phase linear model. Two performance-influencing factors, environmental temperature and operating voltage, are considered as nonlinear effects. The nonlinear relationships among parameters of the capacitances and resistances in the first-phase model are established by a multi-layer artificial neural network. The neural parameters are trained using a back-propagation algorithm by feeding the experimental data bank. Combining the first-phase model and the on-line neural “parameter identifier”, the algorithm produces an on-line nonlinear dynamic model. Simulation results have proved that this proposed model is able to achieve both system fidelity and computational efficiency.

Cellular-automata supercomputers for fluid-dynamics modeling

International Nuclear Information System (INIS)

Margolus, N.; Toffoli, T.; Vichniac, G.

1986-01-01

We report recent developments in the modeling of fluid dynamics, and give experimental results (including dynamical exponents) obtained using cellular automata machines. Because of their locality and uniformity, cellular automata lend themselves to an extremely efficient physical realization; with a suitable architecture, an amount of hardware resources comparable to that of a home computer can achieve (in the simulation of cellular automata) the performance of a conventional supercomputer

Computational Fluid Dynamics of Choanoflagellate Filter-Feeding

Science.gov (United States)

Asadzadeh, Seyed Saeed; Walther, Jens; Nielsen, Lasse Tore; Kiorboe, Thomas; Dolger, Julia; Andersen, Anders

2017-11-01

Choanoflagellates are unicellular aquatic organisms with a single flagellum that drives a feeding current through a funnel-shaped collar filter on which bacteria-sized prey are caught. Using computational fluid dynamics (CFD) we model the beating flagellum and the complex filter flow of the choanoflagellate Diaphanoeca grandis. Our CFD simulations based on the current understanding of the morphology underestimate the experimentally observed clearance rate by more than an order of magnitude: The beating flagellum is simply unable to draw enough water through the fine filter. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet), and addition of a wide vane in our CFD model allows us to correctly predict the observed clearance rate.

Integrating Cloud-Computing-Specific Model into Aircraft Design

Science.gov (United States)

Zhimin, Tian; Qi, Lin; Guangwen, Yang

Cloud Computing is becoming increasingly relevant, as it will enable companies involved in spreading this technology to open the door to Web 3.0. In the paper, the new categories of services introduced will slowly replace many types of computational resources currently used. In this perspective, grid computing, the basic element for the large scale supply of cloud services, will play a fundamental role in defining how those services will be provided. The paper tries to integrate cloud computing specific model into aircraft design. This work has acquired good results in sharing licenses of large scale and expensive software, such as CFD (Computational Fluid Dynamics), UG, CATIA, and so on.

Development and calibration of a model for the dynamic simulation of fans with induction motors

International Nuclear Information System (INIS)

Vaccarini, Massimo; Carbonari, Alessandro; Casals, Miquel

2017-01-01

Highlights: • A model for dynamic simulation of fans with induction motors was developed. • The performances of control logics applied to air supply systems can be simulated. • The model was validated against empirical data. • The model was compared with both dynamic time domain and non-transient models. - Abstract: In this paper a model for the dynamic simulation of fans used in mechanical air supply systems is described. Thanks to this model, the behavior of fans subject to control by variable frequency drives (VFD) can be predicted, which includes power absorbed by the fan and expected ventilation rates. Hence, it can help design energy control systems for buildings. The proposed model was based on the Modelica language and was developed from the dynamic phasor domain representation, because this representation is a trade-off between the basic non transient representation, that is computationally efficient but cannot describe fan dynamics, and the dynamic time domain model, that is the most representative one but computationally very demanding. A comparison among these models showed that, within fan frequency variations typical of ventilation systems in buildings, the phasor domain model is as representative as the more complex dynamic time domain model in terms of prediction of the dynamic behavior, that is neglected by the basic non transient model. Moreover, the new phasor domain model was validated against measured data relative to a fan installed in a subway station in Barcelona. Thanks to this model, energy consumption of dynamically driven fans can be estimated at the simulation stage, at the expense of a reasonable computational effort.

Improving coal flotation recovery using computational fluid dynamics

Energy Technology Data Exchange (ETDEWEB)

Peter Koh [CSIRO Minerals (Australia)

2009-06-15

This work involves using the latest advances in computational fluid dynamics (CFD) to increase understanding of the hydrodynamics in coal flotation and to identify any opportunities to improve design and operation of both the Microcel column and Jameson cell. The CSIRO CFD model incorporates micro-processes from cell hydrodynamics that affect particle-bubble attachments and detachments. CFD simulation results include the liquid velocities, turbulent dissipation rates, gas hold-up, particle-bubble attachment rates and detachment rates. This work has demonstrated that CFD modelling is a cost effective means of developing an understanding of particle-bubble attachments and detachments, and can be used to identify and test potential cell or process modifications.

Fast computation of statistical uncertainty for spatiotemporal distributions estimated directly from dynamic cone beam SPECT projections

International Nuclear Information System (INIS)

Reutter, Bryan W.; Gullberg, Grant T.; Huesman, Ronald H.

2001-01-01

The estimation of time-activity curves and kinetic model parameters directly from projection data is potentially useful for clinical dynamic single photon emission computed tomography (SPECT) studies, particularly in those clinics that have only single-detector systems and thus are not able to perform rapid tomographic acquisitions. Because the radiopharmaceutical distribution changes while the SPECT gantry rotates, projections at different angles come from different tracer distributions. A dynamic image sequence reconstructed from the inconsistent projections acquired by a slowly rotating gantry can contain artifacts that lead to biases in kinetic parameters estimated from time-activity curves generated by overlaying regions of interest on the images. If cone beam collimators are used and the focal point of the collimators always remains in a particular transaxial plane, additional artifacts can arise in other planes reconstructed using insufficient projection samples [1]. If the projection samples truncate the patient's body, this can result in additional image artifacts. To overcome these sources of bias in conventional image based dynamic data analysis, we and others have been investigating the estimation of time-activity curves and kinetic model parameters directly from dynamic SPECT projection data by modeling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view [2-8]. In our previous work we developed a computationally efficient method for fully four-dimensional (4-D) direct estimation of spatiotemporal distributions from dynamic SPECT projection data [5], which extended Formiconi's least squares algorithm for reconstructing temporally static distributions [9]. In addition, we studied the biases that result from modeling various orders temporal continuity and using various time samplings [5]. the present work, we address computational issues associated with evaluating the statistical uncertainty of

Development of real-time visualization system for Computational Fluid Dynamics on parallel computers

International Nuclear Information System (INIS)

Muramatsu, Kazuhiro; Otani, Takayuki; Matsumoto, Hideki; Takei, Toshifumi; Doi, Shun

1998-03-01

A real-time visualization system for computational fluid dynamics in a network connecting between a parallel computing server and the client terminal was developed. Using the system, a user can visualize the results of a CFD (Computational Fluid Dynamics) simulation on the parallel computer as a client terminal during the actual computation on a server. Using GUI (Graphical User Interface) on the client terminal, to user is also able to change parameters of the analysis and visualization during the real-time of the calculation. The system carries out both of CFD simulation and generation of a pixel image data on the parallel computer, and compresses the data. Therefore, the amount of data from the parallel computer to the client is so small in comparison with no compression that the user can enjoy the swift image appearance comfortably. Parallelization of image data generation is based on Owner Computation Rule. GUI on the client is built on Java applet. A real-time visualization is thus possible on the client PC only if Web browser is implemented on it. (author)

Extensive use of computational fluid dynamics in the upgrading of hydraulic turbines

Energy Technology Data Exchange (ETDEWEB)

Sabourin, M.; Eremeef, R.; De Henau, V.

1995-12-31

Computational fluid dynamics codes, based on turbulent Navier-Stokes equations, allow evaluation of the hydraulic losses of each turbine component with precision. Using those codes with the new generation of computers enables a wide variety of component geometries to be modelled and compared to the original designs under flow conditions obtained from testing, at a reasonable cost and in a relatively short time. This paper reviews the actual method used in the design of a solution to a turbine rehabilitation project involving runner replacement, redesign of upstream components (stay vanes and wicket gates), and downstream components (draft tubes and runner outlets). The paper shows how computational fluid dynamics can help hydraulic engineers to obtain valuable information not only on performance enhancement but also on the phenomena that produce the enhancement, and to reduce the variety of modifications to be tested.

Leatherbacks swimming in silico: modeling and verifying their momentum and heat balance using computational fluid dynamics.

Science.gov (United States)

Dudley, Peter N; Bonazza, Riccardo; Jones, T Todd; Wyneken, Jeanette; Porter, Warren P

2014-01-01

As global temperatures increase throughout the coming decades, species ranges will shift. New combinations of abiotic conditions will make predicting these range shifts difficult. Biophysical mechanistic niche modeling places bounds on an animal's niche through analyzing the animal's physical interactions with the environment. Biophysical mechanistic niche modeling is flexible enough to accommodate these new combinations of abiotic conditions. However, this approach is difficult to implement for aquatic species because of complex interactions among thrust, metabolic rate and heat transfer. We use contemporary computational fluid dynamic techniques to overcome these difficulties. We model the complex 3D motion of a swimming neonate and juvenile leatherback sea turtle to find power and heat transfer rates during the stroke. We combine the results from these simulations and a numerical model to accurately predict the core temperature of a swimming leatherback. These results are the first steps in developing a highly accurate mechanistic niche model, which can assists paleontologist in understanding biogeographic shifts as well as aid contemporary species managers about potential range shifts over the coming decades.

Leatherbacks swimming in silico: modeling and verifying their momentum and heat balance using computational fluid dynamics.

Directory of Open Access Journals (Sweden)

Peter N Dudley

Full Text Available As global temperatures increase throughout the coming decades, species ranges will shift. New combinations of abiotic conditions will make predicting these range shifts difficult. Biophysical mechanistic niche modeling places bounds on an animal's niche through analyzing the animal's physical interactions with the environment. Biophysical mechanistic niche modeling is flexible enough to accommodate these new combinations of abiotic conditions. However, this approach is difficult to implement for aquatic species because of complex interactions among thrust, metabolic rate and heat transfer. We use contemporary computational fluid dynamic techniques to overcome these difficulties. We model the complex 3D motion of a swimming neonate and juvenile leatherback sea turtle to find power and heat transfer rates during the stroke. We combine the results from these simulations and a numerical model to accurately predict the core temperature of a swimming leatherback. These results are the first steps in developing a highly accurate mechanistic niche model, which can assists paleontologist in understanding biogeographic shifts as well as aid contemporary species managers about potential range shifts over the coming decades.

A System Computational Model of Implicit Emotional Learning.

Science.gov (United States)

Puviani, Luca; Rama, Sidita

2016-01-01

Nowadays, the experimental study of emotional learning is commonly based on classical conditioning paradigms and models, which have been thoroughly investigated in the last century. Unluckily, models based on classical conditioning are unable to explain or predict important psychophysiological phenomena, such as the failure of the extinction of emotional responses in certain circumstances (for instance, those observed in evaluative conditioning, in post-traumatic stress disorders and in panic attacks). In this manuscript, starting from the experimental results available from the literature, a computational model of implicit emotional learning based both on prediction errors computation and on statistical inference is developed. The model quantitatively predicts (a) the occurrence of evaluative conditioning, (b) the dynamics and the resistance-to-extinction of the traumatic emotional responses, (c) the mathematical relation between classical conditioning and unconditioned stimulus revaluation. Moreover, we discuss how the derived computational model can lead to the development of new animal models for resistant-to-extinction emotional reactions and novel methodologies of emotions modulation.

Probabilistic Methods for the Quantification of Uncertainty and Error in Computational Fluid Dynamic Simulations

National Research Council Canada - National Science Library

Faragher, John

2004-01-01

... conservatism to allow for them. This report examines the feasibility of using a probabilistic approach for modelling the component temperatures in an engine using CFD (Computational Fluid Dynamics).

Accuracy of the microcanonical Lanczos method to compute real-frequency dynamical spectral functions of quantum models at finite temperatures.

Science.gov (United States)

Okamoto, Satoshi; Alvarez, Gonzalo; Dagotto, Elbio; Tohyama, Takami

2018-04-01

We examine the accuracy of the microcanonical Lanczos method (MCLM) developed by Long et al. [Phys. Rev. B 68, 235106 (2003)PRBMDO0163-182910.1103/PhysRevB.68.235106] to compute dynamical spectral functions of interacting quantum models at finite temperatures. The MCLM is based on the microcanonical ensemble, which becomes exact in the thermodynamic limit. To apply the microcanonical ensemble at a fixed temperature, one has to find energy eigenstates with the energy eigenvalue corresponding to the internal energy in the canonical ensemble. Here, we propose to use thermal pure quantum state methods by Sugiura and Shimizu [Phys. Rev. Lett. 111, 010401 (2013)PRLTAO0031-900710.1103/PhysRevLett.111.010401] to obtain the internal energy. After obtaining the energy eigenstates using the Lanczos diagonalization method, dynamical quantities are computed via a continued fraction expansion, a standard procedure for Lanczos-based numerical methods. Using one-dimensional antiferromagnetic Heisenberg chains with S=1/2, we demonstrate that the proposed procedure is reasonably accurate, even for relatively small systems.

CO2, energy and economy interactions: A multisectoral, dynamic, computable general equilibrium model for Korea

Science.gov (United States)

Kang, Yoonyoung

While vast resources have been invested in the development of computational models for cost-benefit analysis for the "whole world" or for the largest economies (e.g. United States, Japan, Germany), the remainder have been thrown together into one model for the "rest of the world." This study presents a multi-sectoral, dynamic, computable general equilibrium (CGE) model for Korea. This research evaluates the impacts of controlling COsb2 emissions using a multisectoral CGE model. This CGE economy-energy-environment model analyzes and quantifies the interactions between COsb2, energy and economy. This study examines interactions and influences of key environmental policy components: applied economic instruments, emission targets, and environmental tax revenue recycling methods. The most cost-effective economic instrument is the carbon tax. The economic effects discussed include impacts on main macroeconomic variables (in particular, economic growth), sectoral production, and the energy market. This study considers several aspects of various COsb2 control policies, such as the basic variables in the economy: capital stock and net foreign debt. The results indicate emissions might be stabilized in Korea at the expense of economic growth and with dramatic sectoral allocation effects. Carbon dioxide emissions stabilization could be achieved to the tune of a 600 trillion won loss over a 20 year period (1990-2010). The average annual real GDP would decrease by 2.10% over the simulation period compared to the 5.87% increase in the Business-as-Usual. This model satisfies an immediate need for a policy simulation model for Korea and provides the basic framework for similar economies. It is critical to keep the central economic question at the forefront of any discussion regarding environmental protection. How much will reform cost, and what does the economy stand to gain and lose? Without this model, the policy makers might resort to hesitation or even blind speculation. With

Introduction to Focus Issue: Rhythms and Dynamic Transitions in Neurological Disease: Modeling, Computation, and Experiment

Energy Technology Data Exchange (ETDEWEB)

Kaper, Tasso J., E-mail: tasso@bu.edu; Kramer, Mark A., E-mail: mak@bu.edu [Department of Mathematics and Statistics, Boston University, Boston, Massachusetts 02215 (United States); Rotstein, Horacio G., E-mail: horacio@njit.edu [Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, New Jersey 07102 (United States)

2013-12-15

Rhythmic neuronal oscillations across a broad range of frequencies, as well as spatiotemporal phenomena, such as waves and bumps, have been observed in various areas of the brain and proposed as critical to brain function. While there is a long and distinguished history of studying rhythms in nerve cells and neuronal networks in healthy organisms, the association and analysis of rhythms to diseases are more recent developments. Indeed, it is now thought that certain aspects of diseases of the nervous system, such as epilepsy, schizophrenia, Parkinson's, and sleep disorders, are associated with transitions or disruptions of neurological rhythms. This focus issue brings together articles presenting modeling, computational, analytical, and experimental perspectives about rhythms and dynamic transitions between them that are associated to various diseases.

Introduction to Focus Issue: Rhythms and Dynamic Transitions in Neurological Disease: Modeling, Computation, and Experiment

International Nuclear Information System (INIS)

Kaper, Tasso J.; Kramer, Mark A.; Rotstein, Horacio G.

2013-01-01

Rhythmic neuronal oscillations across a broad range of frequencies, as well as spatiotemporal phenomena, such as waves and bumps, have been observed in various areas of the brain and proposed as critical to brain function. While there is a long and distinguished history of studying rhythms in nerve cells and neuronal networks in healthy organisms, the association and analysis of rhythms to diseases are more recent developments. Indeed, it is now thought that certain aspects of diseases of the nervous system, such as epilepsy, schizophrenia, Parkinson's, and sleep disorders, are associated with transitions or disruptions of neurological rhythms. This focus issue brings together articles presenting modeling, computational, analytical, and experimental perspectives about rhythms and dynamic transitions between them that are associated to various diseases

Investigation of Swirling Flow in Rod Bundle Subchannels Using Computational Fluid Dynamics

International Nuclear Information System (INIS)

Holloway, Mary V.; Beasley, Donald E.; Conner, Michael E.

2006-01-01

The fluid dynamics for turbulent flow through rod bundles representative of those used in pressurized water reactors is examined using computational fluid dynamics (CFD). The rod bundles of the pressurized water reactor examined in this study consist of a square array of parallel rods that are held on a constant pitch by support grids spaced axially along the rod bundle. Split-vane pair support grids are often used to create swirling flow in the rod bundle in an effort to improve the heat transfer characteristics for the rod bundle during both normal operating conditions and in accident condition scenarios. Computational fluid dynamics simulations for a two subchannel portion of the rod bundle were used to model the flow downstream of a split-vane pair support grid. A high quality computational mesh was used to investigate the choice of turbulence model appropriate for the complex swirling flow in the rod bundle subchannels. Results document a central swirling flow structure in each of the subchannels downstream of the split-vane pairs. Strong lateral flows along the surface of the rods, as well as impingement regions of lateral flow on the rods are documented. In addition, regions of lateral flow separation and low axial velocity are documented next to the rods. Results of the CFD are compared to experimental particle image velocimetry (PIV) measurements documenting the lateral flow structures downstream of the split-vane pairs. Good agreement is found between the computational simulation and experimental measurements for locations close to the support grid. (authors)

Dynamic modeling of IGCC power plants

International Nuclear Information System (INIS)

Casella, F.; Colonna, P.

2012-01-01

Integrated Gasification Combined Cycle (IGCC) power plants are an effective option to reduce emissions and implement carbon-dioxide sequestration. The combination of a very complex fuel-processing plant and a combined cycle power station leads to challenging problems as far as dynamic operation is concerned. Dynamic performance is extremely relevant because recent developments in the electricity market push toward an ever more flexible and varying operation of power plants. A dynamic model of the entire system and models of its sub-systems are indispensable tools in order to perform computer simulations aimed at process and control design. This paper presents the development of the lumped-parameters dynamic model of an entrained-flow gasifier, with special emphasis on the modeling approach. The model is implemented into software by means of the Modelica language and validated by comparison with one set of data related to the steady operation of the gasifier of the Buggenum power station in the Netherlands. Furthermore, in order to demonstrate the potential of the proposed modeling approach and the use of simulation for control design purposes, a complete model of an exemplary IGCC power plant, including its control system, has been developed, by re-using existing models of combined cycle plant components; the results of a load dispatch ramp simulation are presented and shortly discussed. - Highlights: ► The acausal dynamic model of an entrained gasifier has been developed. ► The model can be used to perform system optimization and control studies. ► The model has been validated using field data. ► Model use is illustrated with an example showing the transient of an IGCC plant.

A Dynamic/Anisotropic Low Earth Orbit (LEO) Ionizing Radiation Model

Science.gov (United States)

Badavi, Francis F.; West, Katie J.; Nealy, John E.; Wilson, John W.; Abrahms, Briana L.; Luetke, Nathan J.

2006-01-01

The International Space Station (ISS) provides the proving ground for future long duration human activities in space. Ionizing radiation measurements in ISS form the ideal tool for the experimental validation of ionizing radiation environmental models, nuclear transport code algorithms, and nuclear reaction cross sections. Indeed, prior measurements on the Space Transportation System (STS; Shuttle) have provided vital information impacting both the environmental models and the nuclear transport code development by requiring dynamic models of the Low Earth Orbit (LEO) environment. Previous studies using Computer Aided Design (CAD) models of the evolving ISS configurations with Thermo Luminescent Detector (TLD) area monitors, demonstrated that computational dosimetry requires environmental models with accurate non-isotropic as well as dynamic behavior, detailed information on rack loading, and an accurate 6 degree of freedom (DOF) description of ISS trajectory and orientation.

Dynamic stability calculations for power grids employing a parallel computer

Energy Technology Data Exchange (ETDEWEB)

Schmidt, K

1982-06-01

The aim of dynamic contingency calculations in power systems is to estimate the effects of assumed disturbances, such as loss of generation. Due to the large dimensions of the problem these simulations require considerable computing time and costs, to the effect that they are at present only used in a planning state but not for routine checks in power control stations. In view of the homogeneity of the problem, where a multitude of equal generator models, having different parameters, are to be integrated simultaneously, the use of a parallel computer looks very attractive. The results of this study employing a prototype parallel computer (SMS 201) are presented. It consists of up to 128 equal microcomputers bus-connected to a control computer. Each of the modules is programmed to simulate a node of the power grid. Generators with their associated control are represented by models of 13 states each. Passive nodes are complemented by 'phantom'-generators, so that the whole power grid is homogenous, thus removing the need for load-flow-iterations. Programming of microcomputers is essentially performed in FORTRAN.

Modeling Juvenile Salmon Egress Conditions in The Dalles Dam Tailrace using Computational Fluid Dynamics

Energy Technology Data Exchange (ETDEWEB)

Richmond, Marshall C.; Rakowski, Cynthia L.; Perkins, William A.; Serkowski, John A.; Ebner, Laurie L.; Schlenker, Stephen J.

2009-07-27

At The Dalles Dam, located between Oregon and Washington on the Columbia River, juvenile salmon passing over the spillway have a survival rate that is below acceptable levels. An important factor affecting survival is the egress route fish take through the immediate tailrace of the dam. Passage through the high-energy spillway and stilling basin environment can leave fish disoriented and vulnerable to predators. Egress conditions can be improved through structural and operational modifications that provide flow paths that move fish more rapidly into the thalweg of the river hence reducing their exposure to predators. We used the results from free-surface computational fluid dynamics (CFD) modeling combined with Lagrangian particle tracking to evaluate the tailrace egress conditions at The Dalles Dam for different alignments of a proposed guidance wall and for different spillway discharge scenarios.

Modeling of temperature profiles in an environmental transmission electron microscope using computational fluid dynamics

DEFF Research Database (Denmark)

Mortensen, Peter Mølgaard; Jensen, Anker Degn; Hansen, Thomas Willum

2015-01-01

The temperature and velocity field, pressure distribution, and the temperature variation across the sample region inside an environmental transmission electron microscope (ETEM) have been modeled by means of computational fluid dynamics (CFD). Heating the sample area by a furnace type TEM holder...... gives rise to temperature gradients over the sample area. Three major mechanisms have been identified with respect to heat transfer in the sample area: radiation from the grid, conduction in the grid, and conduction in the gas. A parameter sensitivity analysis showed that the sample temperature...... was affected by the conductivity of the gas, the emissivity of the sample grid, and the conductivity of the grid. Ideally the grid should be polished and made from a material with good conductivity, e.g. copper. With hydrogen gas, which has the highest conductivity of the gases studied, the temperature...

Petri Net Modeling of Computer Virus Life Cycle | Ikekonwu ...

African Journals Online (AJOL)

Virus life cycle, which refers to the stages of development of a computer virus, is presented as a suitable area for the application of Petri nets. Petri nets a powerful modeling tool in the field of dynamic system analysis is applied to model the virus life cycle. Simulation of the derived model is also presented. The intention of ...

Symposium on computational fluid dynamics: technology and applications

International Nuclear Information System (INIS)

1988-01-01

A symposium on the technology and applications of computational fluid dynamics (CFD) was held in Pretoria from 21-23 Nov 1988. The following aspects were covered: multilevel adaptive methods and multigrid solvers in CFD, a symbolic processing approach to CFD, interplay between CFD and analytical approximations, CFD on a transfer array, the application of CFD in high speed aerodynamics, numerical simulation of laminar blood flow, two-phase flow modelling in nuclear accident analysis, and the finite difference scheme for the numerical solution of fluid flow

Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation.

Science.gov (United States)

Reagan, Andrew J; Dubief, Yves; Dodds, Peter Sheridan; Danforth, Christopher M

2016-01-01

A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth's weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA) methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF) to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD) of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction.

Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation.

Directory of Open Access Journals (Sweden)

Andrew J Reagan

Full Text Available A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth's weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction.

Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models

Science.gov (United States)

Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Li, Huiyan; Loparo, Kenneth A.; Fietkiewicz, Chris

2015-11-01

Computational models play a significant role in exploring novel theories to complement the findings of physiological experiments. Various computational models have been developed to reveal the mechanisms underlying brain functions. Particularly, in the development of therapies to modulate behavioral and pathological abnormalities, computational models provide the basic foundations to exhibit transitions between physiological and pathological conditions. Considering the significant roles of the intrinsic properties of the globus pallidus and the coupling connections between neurons in determining the firing patterns and the dynamical activities of the basal ganglia neuronal network, we propose a hypothesis that pathological behaviors under the Parkinsonian state may originate from combined effects of intrinsic properties of globus pallidus neurons and synaptic conductances in the whole neuronal network. In order to establish a computational efficient network model, hybrid Izhikevich neuron model is used due to its capacity of capturing the dynamical characteristics of the biological neuronal activities. Detailed analysis of the individual Izhikevich neuron model can assist in understanding the roles of model parameters, which then facilitates the establishment of the basal ganglia-thalamic network model, and contributes to a further exploration of the underlying mechanisms of the Parkinsonian state. Simulation results show that the hybrid Izhikevich neuron model is capable of capturing many of the dynamical properties of the basal ganglia-thalamic neuronal network, such as variations of the firing rates and emergence of synchronous oscillations under the Parkinsonian condition, despite the simplicity of the two-dimensional neuronal model. It may suggest that the computational efficient hybrid Izhikevich neuron model can be used to explore basal ganglia normal and abnormal functions. Especially it provides an efficient way of emulating the large-scale neuron network

Computational fluid dynamics study of viscous fingering in supercritical fluid chromatography.

Science.gov (United States)

Subraveti, Sai Gokul; Nikrityuk, Petr; Rajendran, Arvind

2018-01-26

Axi-symmetric numerical simulations are carried out to study the dynamics of a plug introduced through a mixed-stream injection in supercritical fluid chromatographic columns. The computational fluid dynamics model developed in this work takes into account both the hydrodynamics and adsorption equilibria to describe the phenomena of viscous fingering and plug effect that contribute to peak distortions in mixed-stream injections. The model was implemented into commercial computational fluid dynamics software using user-defined functions. The simulations describe the propagation of both the solute and modifier highlighting the interplay between the hydrodynamics and plug effect. The simulated peaks showed good agreement with experimental data published in the literature involving different injection volumes (5 μL, 50 μL, 1 mL and 2 mL) of flurbiprofen on Chiralpak AD-H column using a mobile phase of CO 2 and methanol. The study demonstrates that while viscous fingering is the main source of peak distortions for large-volume injections (1 mL and 2 mL) it has negligible impact on small-volume injections (5 μL and 50 μL). Band broadening in small-volume injections arise mainly due to the plug effect. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Analytic Intermodel Consistent Modeling of Volumetric Human Lung Dynamics.

Science.gov (United States)

Ilegbusi, Olusegun; Seyfi, Behnaz; Neylon, John; Santhanam, Anand P

2015-10-01

Human lung undergoes breathing-induced deformation in the form of inhalation and exhalation. Modeling the dynamics is numerically complicated by the lack of information on lung elastic behavior and fluid-structure interactions between air and the tissue. A mathematical method is developed to integrate deformation results from a deformable image registration (DIR) and physics-based modeling approaches in order to represent consistent volumetric lung dynamics. The computational fluid dynamics (CFD) simulation assumes the lung is a poro-elastic medium with spatially distributed elastic property. Simulation is performed on a 3D lung geometry reconstructed from four-dimensional computed tomography (4DCT) dataset of a human subject. The heterogeneous Young's modulus (YM) is estimated from a linear elastic deformation model with the same lung geometry and 4D lung DIR. The deformation obtained from the CFD is then coupled with the displacement obtained from the 4D lung DIR by means of the Tikhonov regularization (TR) algorithm. The numerical results include 4DCT registration, CFD, and optimal displacement data which collectively provide consistent estimate of the volumetric lung dynamics. The fusion method is validated by comparing the optimal displacement with the results obtained from the 4DCT registration.

Dynamic skin deformation simulation using musculoskeletal model and soft tissue dynamics

Institute of Scientific and Technical Information of China (English)

Akihiko Murai; Q. Youn Hong; Katsu Yamane; Jessica K. Hodgins

2017-01-01

Deformation of skin and muscle is essential for bringing an animated character to life. This deformation is difficult to animate in a realistic fashion using traditional techniques because of the subtlety of the skin deformations that must move appropriately for the character design. In this paper, we present an algorithm that generates natural, dynamic, and detailed skin deformation (movement and jiggle) from joint angle data sequences. The algorithm has two steps: identification of parameters for a quasi-static muscle deformation model, and simulation of skin deformation. In the identification step, we identify the model parameters using a musculoskeletal model and a short sequence of skin deformation data captured via a dense marker set. The simulation step first uses the quasi-static muscle deformation model to obtain the quasi-static muscle shape at each frame of the given motion sequence (slow jump). Dynamic skin deformation is then computed by simulating the passive muscle and soft tissue dynamics modeled as a mass–spring–damper system. Having obtained the model parameters, we can simulate dynamic skin deformations for subjects with similar body types from new motion data. We demonstrate our method by creating skin deformations for muscle co-contraction and external impacts from four different behaviors captured as skeletal motion capture data. Experimental results show that the simulated skin deformations are quantitatively and qualitatively similar to measured actual skin deformations.

Dynamic skin deformation simulation using musculoskeletal model and soft tissue dynamics

Institute of Scientific and Technical Information of China (English)

Akihiko Murai; Q.Youn Hong; Katsu Yamane; Jessica K.Hodgins

2017-01-01

Deformation of skin and muscle is essential for bringing an animated character to life. This deformation is difficult to animate in a realistic fashion using traditional techniques because of the subtlety of the skin deformations that must move appropriately for the character design. In this paper, we present an algorithm that generates natural, dynamic, and detailed skin deformation(movement and jiggle) from joint angle data sequences. The algorithm has two steps: identification of parameters for a quasi-static muscle deformation model, and simulation of skin deformation. In the identification step, we identify the model parameters using a musculoskeletal model and a short sequence of skin deformation data captured via a dense marker set. The simulation step first uses the quasi-static muscle deformation model to obtain the quasi-static muscle shape at each frame of the given motion sequence(slow jump). Dynamic skin deformation is then computed by simulating the passive muscle and soft tissue dynamics modeled as a mass–spring–damper system. Having obtained the model parameters, we can simulate dynamic skin deformations for subjects with similar body types from new motion data. We demonstrate our method by creating skin deformations for muscle co-contraction and external impacts from four different behaviors captured as skeletal motion capture data. Experimental results show that the simulated skin deformations are quantitatively and qualitatively similar to measured actual skin deformations.

Single-polymer dynamics under constraints: scaling theory and computer experiment

International Nuclear Information System (INIS)

Milchev, Andrey

2011-01-01

The relaxation, diffusion and translocation dynamics of single linear polymer chains in confinement is briefly reviewed with emphasis on the comparison between theoretical scaling predictions and observations from experiment or, most frequently, from computer simulations. Besides cylindrical, spherical and slit-like constraints, related problems such as the chain dynamics in a random medium and the translocation dynamics through a nanopore are also considered. Another particular kind of confinement is imposed by polymer adsorption on attractive surfaces or selective interfaces-a short overview of single-chain dynamics is also contained in this survey. While both theory and numerical experiments consider predominantly coarse-grained models of self-avoiding linear chain molecules with typically Rouse dynamics, we also note some recent studies which examine the impact of hydrodynamic interactions on polymer dynamics in confinement. In all of the aforementioned cases we focus mainly on the consequences of imposed geometric restrictions on single-chain dynamics and try to check our degree of understanding by assessing the agreement between theoretical predictions and observations. (topical review)

The Effects of Computer-assisted and Distance Learning of Geometric Modeling

Directory of Open Access Journals (Sweden)

Omer Faruk Sozcu

2013-01-01

Full Text Available The effects of computer-assisted and distance learning of geometric modeling and computer aided geometric design are studied. It was shown that computer algebra systems and dynamic geometric environments can be considered as excellent tools for teaching mathematical concepts of mentioned areas, and distance education technologies would be indispensable for consolidation of successfully passed topics

Environmental Factors Affecting Computer Assisted Language Learning Success: A Complex Dynamic Systems Conceptual Model

Science.gov (United States)

Marek, Michael W.; Wu, Wen-Chi Vivian

2014-01-01

This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…

What can be learned from computer modeling? Comparing expository and modeling approaches to teaching dynamic systems behavior

NARCIS (Netherlands)

van Borkulo, S.P.; van Joolingen, W.R.; Savelsbergh, E.R.; de Jong, T.

2012-01-01

Computer modeling has been widely promoted as a means to attain higher order learning outcomes. Substantiating these benefits, however, has been problematic due to a lack of proper assessment tools. In this study, we compared computer modeling with expository instruction, using a tailored assessment

Task-and-role-based access-control model for computational grid

Institute of Scientific and Technical Information of China (English)

LONG Tao; HONG Fan; WU Chi; SUN Ling-li

2007-01-01

Access control in a grid environment is a challenging issue because the heterogeneous nature and independent administration of geographically dispersed resources in grid require access control to use fine-grained policies. We established a task-and-role-based access-control model for computational grid (CG-TRBAC model), integrating the concepts of role-based access control (RBAC) and task-based access control (TBAC). In this model, condition restrictions are defined and concepts specifically tailored to Workflow Management System are simplified or omitted so that role assignment and security administration fit computational grid better than traditional models; permissions are mutable with the task status and system variables, and can be dynamically controlled. The CG-TRBAC model is proved flexible and extendible. It can implement different control policies. It embodies the security principle of least privilege and executes active dynamic authorization. A task attribute can be extended to satisfy different requirements in a real grid system.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

Science.gov (United States)

Kappel, David; Legenstein, Robert; Habenschuss, Stefan; Hsieh, Michael; Maass, Wolfgang

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations.

Computer modeling of ORNL storage tank sludge mobilization and mixing

International Nuclear Information System (INIS)

Terrones, G.; Eyler, L.L.

1993-09-01

This report presents and analyzes the results of the computer modeling of mixing and mobilization of sludge in horizontal, cylindrical storage tanks using submerged liquid jets. The computer modeling uses the TEMPEST computational fluid dynamics computer program. The horizontal, cylindrical storage tank configuration is similar to the Melton Valley Storage Tanks (MVST) at Oak Ridge National (ORNL). The MVST tank contents exhibit non-homogeneous, non-Newtonian rheology characteristics. The eventual goals of the simulations are to determine under what conditions sludge mobilization using submerged liquid jets is feasible in tanks of this configuration, and to estimate mixing times required to approach homogeneity of the contents of the tanks

Qweak Data Analysis for Target Modeling Using Computational Fluid Dynamics

Science.gov (United States)

Moore, Michael; Covrig, Silviu

2015-04-01

The 2.5 kW liquid hydrogen (LH2) target used in the Qweak parity violation experiment is the highest power LH2 target in the world and the first to be designed with Computational Fluid Dynamics (CFD) at Jefferson Lab. The Qweak experiment determined the weak charge of the proton by measuring the parity-violating elastic scattering asymmetry of longitudinally polarized electrons from unpolarized liquid hydrogen at small momentum transfer (Q2 = 0 . 025 GeV2). This target met the design goals of bench-marked with the Qweak target data. This work is an essential ingredient in future designs of very high power low noise targets like MOLLER (5 kW, target noise asymmetry contribution < 25 ppm) and MESA (4.5 kW).

GASFLOW: A Computational Fluid Dynamics Code for Gases, Aerosols, and Combustion, Volume 1: Theory and Computational Model

International Nuclear Information System (INIS)

Nichols, B.D.; Mueller, C.; Necker, G.A.; Travis, J.R.; Spore, J.W.; Lam, K.L.; Royl, P.; Redlinger, R.; Wilson, T.L.

1998-01-01

Los Alamos National Laboratory (LANL) and Forschungszentrum Karlsruhe (FzK) are developing GASFLOW, a three-dimensional (3D) fluid dynamics field code as a best-estimate tool to characterize local phenomena within a flow field. Examples of 3D phenomena include circulation patterns; flow stratification; hydrogen distribution mixing and stratification; combustion and flame propagation; effects of noncondensable gas distribution on local condensation and evaporation; and aerosol entrainment, transport, and deposition. An analysis with GASFLOW will result in a prediction of the gas composition and discrete particle distribution in space and time throughout the facility and the resulting pressure and temperature loadings on the walls and internal structures with or without combustion. A major application of GASFLOW is for predicting the transport, mixing, and combustion of hydrogen and other gases in nuclear reactor containments and other facilities. It has been applied to situations involving transporting and distributing combustible gas mixtures. It has been used to study gas dynamic behavior (1) in low-speed, buoyancy-driven flows, as well as sonic flows or diffusion dominated flows; and (2) during chemically reacting flows, including deflagrations. The effects of controlling such mixtures by safety systems can be analyzed. The code version described in this manual is designated GASFLOW 2.1, which combines previous versions of the United States Nuclear Regulatory Commission code HMS (for Hydrogen Mixing Studies) and the Department of Energy and FzK versions of GASFLOW. The code was written in standard Fortran 90. This manual comprises three volumes. Volume I describes the governing physical equations and computational model. Volume II describes how to use the code to set up a model geometry, specify gas species and material properties, define initial and boundary conditions, and specify different outputs, especially graphical displays. Sample problems are included

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

Science.gov (United States)

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.

ADAM: analysis of discrete models of biological systems using computer algebra.

Science.gov (United States)

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web

Computational Analysis of Static and Dynamic Behaviour of Magnetic Suspensions and Magnetic Bearings

Science.gov (United States)

Britcher, Colin P. (Editor); Groom, Nelson J.

1996-01-01

Static modelling of magnetic bearings is often carried out using magnetic circuit theory. This theory cannot easily include nonlinear effects such as magnetic saturation or the fringing of flux in air-gaps. Modern computational tools are able to accurately model complex magnetic bearing geometries, provided some care is exercised. In magnetic suspension applications, the magnetic fields are highly three-dimensional and require computational tools for the solution of most problems of interest. The dynamics of a magnetic bearing or magnetic suspension system can be strongly affected by eddy currents. Eddy currents are present whenever a time-varying magnetic flux penetrates a conducting medium. The direction of flow of the eddy current is such as to reduce the rate-of-change of flux. Analytic solutions for eddy currents are available for some simplified geometries, but complex geometries must be solved by computation. It is only in recent years that such computations have been considered truly practical. At NASA Langley Research Center, state-of-the-art finite-element computer codes, 'OPERA', 'TOSCA' and 'ELEKTRA' have recently been installed and applied to the magnetostatic and eddy current problems. This paper reviews results of theoretical analyses which suggest general forms of mathematical models for eddy currents, together with computational results. A simplified circuit-based eddy current model proposed appears to predict the observed trends in the case of large eddy current circuits in conducting non-magnetic material. A much more difficult case is seen to be that of eddy currents in magnetic material, or in non-magnetic material at higher frequencies, due to the lower skin depths. Even here, the dissipative behavior has been shown to yield at least somewhat to linear modelling. Magnetostatic and eddy current computations have been carried out relating to the Annular Suspension and Pointing System, a prototype for a space payload pointing and vibration

Particle hopping vs. fluid-dynamical models for traffic flow

Energy Technology Data Exchange (ETDEWEB)

Nagel, K.

1995-12-31

Although particle hopping models have been introduced into traffic science in the 19509, their systematic use has only started recently. Two reasons for this are, that they are advantageous on modem computers, and that recent theoretical developments allow analytical understanding of their properties and therefore more confidence for their use. In principle, particle hopping models fit between microscopic models for driving and fluiddynamical models for traffic flow. In this sense, they also help closing the conceptual gap between these two. This paper shows connections between particle hopping models and traffic flow theory. It shows that the hydrodynamical limits of certain particle hopping models correspond to the Lighthill-Whitham theory for traffic flow, and that only slightly more complex particle hopping models produce already the correct traffic jam dynamics, consistent with recent fluid-dynamical models for traffic flow. By doing so, this paper establishes that, on the macroscopic level, particle hopping models are at least as good as fluid-dynamical models. Yet, particle hopping models have at least two advantages over fluid-dynamical models: they straightforwardly allow microscopic simulations, and they include stochasticity.

[The implementation of computer model in research of dynamics of proliferation of cells of thyroid gland follicle].

Science.gov (United States)

Abduvaliev, A A; Gil'dieva, M S; Khidirov, B N; Saĭdalieva, M; Khasanov, A A; Musaeva, Sh N; Saatov, T S

2012-04-01

The article deals with the results of computational experiments in research of dynamics of proliferation of cells of thyroid gland follicle in normal condition and in the case of malignant neoplasm. The model studies demonstrated that the chronic increase of parameter of proliferation of cells of thyroid gland follicle results in abnormal behavior of numbers of cell cenosis of thyroid gland follicle. The stationary state interrupts, the auto-oscillations occur with transition to irregular oscillations with unpredictable cell proliferation and further to the "black hole" effect. It is demonstrated that the present medical biologic experimental data and theory propositions concerning the structural functional organization of thyroid gland on cell level permit to develop mathematical models for quantitative analysis of numbers of cell cenosis of thyroid gland follicle in normal conditions. The technique of modeling of regulative mechanisms of living systems and equations of cell cenosis regulations was used

Computational Fluid Dynamics Modeling of a Supersonic Nozzle and Integration into a Variable Cycle Engine Model

Science.gov (United States)

Connolly, Joseph W.; Friedlander, David; Kopasakis, George

2015-01-01

This paper covers the development of an integrated nonlinear dynamic simulation for a variable cycle turbofan engine and nozzle that can be integrated with an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. A previously developed variable cycle turbofan engine model is used for this study and is enhanced here to include variable guide vanes allowing for operation across the supersonic flight regime. The primary focus of this study is to improve the fidelity of the model's thrust response by replacing the simple choked flow equation convergent-divergent nozzle model with a MacCormack method based quasi-1D model. The dynamic response of the nozzle model using the MacCormack method is verified by comparing it against a model of the nozzle using the conservation element/solution element method. A methodology is also presented for the integration of the MacCormack nozzle model with the variable cycle engine.

Dynamic process model of a plutonium oxalate precipitator. Final report

Energy Technology Data Exchange (ETDEWEB)

Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

1977-11-01

In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts.

Dynamic process model of a plutonium oxalate precipitator. Final report

International Nuclear Information System (INIS)

Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

1977-11-01

In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts

Development of effect assessment methodology for the deployment of fast reactor cycle system with dynamic computable general equilibrium model

International Nuclear Information System (INIS)

Shiotani, Hiroki; Ono, Kiyoshi

2009-01-01

The Global Trade and Analysis Project (GTAP) is a widely used computable general equilibrium (CGE) model developed by Purdue University. Although the GTAP-E, an energy environmental version of the GTAP model, is useful for surveying the energy-economy-environment-trade linkage is economic policy analysis, it does not have the decomposed model of the electricity sector and its analyses are comparatively static. In this study, a recursive dynamic CGE model with a detailed electricity technology bundle with nuclear power generation including FR was developed based on the GTAP-E to evaluate the long-term socioeconomic effects of FR deployment. The capital stock changes caused by international investments and some dynamic constraints of the FR deployment and operation (e.g., load following capability and plutonium mass balance) were incorporated in the analyses. The long-term socioeconomic effects resulting from the deployment of economic competitive FR with innovative technologies can be assessed; the cumulative effects of the FR deployment on GDP calculated using this model costed over 40 trillion yen in Japan and 400 trillion yen worldwide, which were several times more than the cost of the effects calculated using the conventional cost-benefit analysis tool, because of ripple effects and energy substitutions among others. (author)

Computational Methods for Modeling Aptamers and Designing Riboswitches

Directory of Open Access Journals (Sweden)

Sha Gong

2017-11-01

Full Text Available Riboswitches, which are located within certain noncoding RNA region perform functions as genetic “switches”, regulating when and where genes are expressed in response to certain ligands. Understanding the numerous functions of riboswitches requires computation models to predict structures and structural changes of the aptamer domains. Although aptamers often form a complex structure, computational approaches, such as RNAComposer and Rosetta, have already been applied to model the tertiary (three-dimensional (3D structure for several aptamers. As structural changes in aptamers must be achieved within the certain time window for effective regulation, kinetics is another key point for understanding aptamer function in riboswitch-mediated gene regulation. The coarse-grained self-organized polymer (SOP model using Langevin dynamics simulation has been successfully developed to investigate folding kinetics of aptamers, while their co-transcriptional folding kinetics can be modeled by the helix-based computational method and BarMap approach. Based on the known aptamers, the web server Riboswitch Calculator and other theoretical methods provide a new tool to design synthetic riboswitches. This review will represent an overview of these computational methods for modeling structure and kinetics of riboswitch aptamers and for designing riboswitches.

Dynamic optimization of CELSS crop photosynthetic rate by computer-assisted feedback control

Science.gov (United States)

Chun, C.; Mitchell, C. A.

1997-01-01

A procedure for dynamic optimization of net photosynthetic rate (Pn) for crop production in Controlled Ecological Life-Support Systems (CELSS) was developed using leaf lettuce as a model crop. Canopy Pn was measured in real time and fed back for environmental control. Setpoints of photosynthetic photon flux (PPF) and CO_2 concentration for each hour of the crop-growth cycle were decided by computer to reach a targeted Pn each day. Decision making was based on empirical mathematical models combined with rule sets developed from recent experimental data. Comparisons showed that dynamic control resulted in better yield per unit energy input to the growth system than did static control. With comparable productivity parameters and potential for significant energy savings, dynamic control strategies will contribute greatly to the sustainability of space-deployed CELSS.

Dynamic computer simulations of electrophoresis: three decades of active research.

Science.gov (United States)

Thormann, Wolfgang; Caslavska, Jitka; Breadmore, Michael C; Mosher, Richard A

2009-06-01

Dynamic models for electrophoresis are based upon model equations derived from the transport concepts in solution together with user-inputted conditions. They are able to predict theoretically the movement of ions and are as such the most versatile tool to explore the fundamentals of electrokinetic separations. Since its inception three decades ago, the state of dynamic computer simulation software and its use has progressed significantly and Electrophoresis played a pivotal role in that endeavor as a large proportion of the fundamental and application papers were published in this periodical. Software is available that simulates all basic electrophoretic systems, including moving boundary electrophoresis, zone electrophoresis, ITP, IEF and EKC, and their combinations under almost exactly the same conditions used in the laboratory. This has been employed to show the detailed mechanisms of many of the fundamental phenomena that occur in electrophoretic separations. Dynamic electrophoretic simulations are relevant for separations on any scale and instrumental format, including free-fluid preparative, gel, capillary and chip electrophoresis. This review includes a historical overview, a survey of current simulators, simulation examples and a discussion of the applications and achievements of dynamic simulation.

Immersive visualization of dynamic CFD model results

International Nuclear Information System (INIS)

Comparato, J.R.; Ringel, K.L.; Heath, D.J.

2004-01-01

With immersive visualization the engineer has the means for vividly understanding problem causes and discovering opportunities to improve design. Software can generate an interactive world in which collaborators experience the results of complex mathematical simulations such as computational fluid dynamic (CFD) modeling. Such software, while providing unique benefits over traditional visualization techniques, presents special development challenges. The visualization of large quantities of data interactively requires both significant computational power and shrewd data management. On the computational front, commodity hardware is outperforming large workstations in graphical quality and frame rates. Also, 64-bit commodity computing shows promise in enabling interactive visualization of large datasets. Initial interactive transient visualization methods and examples are presented, as well as development trends in commodity hardware and clustering. Interactive, immersive visualization relies on relevant data being stored in active memory for fast response to user requests. For large or transient datasets, data management becomes a key issue. Techniques for dynamic data loading and data reduction are presented as means to increase visualization performance. (author)

Statistical properties of dynamical systems – Simulation and abstract computation

International Nuclear Information System (INIS)

Galatolo, Stefano; Hoyrup, Mathieu; Rojas, Cristóbal

2012-01-01

Highlights: ► A survey on results about computation and computability on the statistical properties of dynamical systems. ► Computability and non-computability results for invariant measures. ► A short proof for the computability of the convergence speed of ergodic averages. ► A kind of “constructive” version of the pointwise ergodic theorem. - Abstract: We survey an area of recent development, relating dynamics to theoretical computer science. We discuss some aspects of the theoretical simulation and computation of the long term behavior of dynamical systems. We will focus on the statistical limiting behavior and invariant measures. We present a general method allowing the algorithmic approximation at any given accuracy of invariant measures. The method can be applied in many interesting cases, as we shall explain. On the other hand, we exhibit some examples where the algorithmic approximation of invariant measures is not possible. We also explain how it is possible to compute the speed of convergence of ergodic averages (when the system is known exactly) and how this entails the computation of arbitrarily good approximations of points of the space having typical statistical behaviour (a sort of constructive version of the pointwise ergodic theorem).

Quadratic tracer dynamical models tobacco growth

International Nuclear Information System (INIS)

Qiang Jiyi; Hua Cuncai; Wang Shaohua

2011-01-01

In order to study the non-uniformly transferring process of some tracer dosages, we assume that the absorption of some tracer by tobacco is a quadratic function of the tracer quantity of the tracer in the case of fast absorption, whereas the exclusion of the tracer from tobacco is a linear function of the tracer quantity in the case of slow exclusion, after the tracer is introduced into tobacco once at zero time. A single-compartment quadratic dynamical model of Logistic type is established for the leaves of tobacco. Then, a two-compartment quadratic dynamical model is established for leaves and calms of the tobacco. Qualitative analysis of the models shows that the tracer applied to the leaves of the tobacco is excluded finally; however, the tracer stays at the tobacco for finite time. Two methods are also given for computing the parameters in the models. Finally, the results of the models are verified by the 32 P experiment for the absorption of tobacco. (authors)

Markov dynamic models for long-timescale protein motion.

KAUST Repository

Chiang, Tsung-Han

2010-06-01

Molecular dynamics (MD) simulation is a well-established method for studying protein motion at the atomic scale. However, it is computationally intensive and generates massive amounts of data. One way of addressing the dual challenges of computation efficiency and data analysis is to construct simplified models of long-timescale protein motion from MD simulation data. In this direction, we propose to use Markov models with hidden states, in which the Markovian states represent potentially overlapping probabilistic distributions over protein conformations. We also propose a principled criterion for evaluating the quality of a model by its ability to predict long-timescale protein motions. Our method was tested on 2D synthetic energy landscapes and two extensively studied peptides, alanine dipeptide and the villin headpiece subdomain (HP-35 NleNle). One interesting finding is that although a widely accepted model of alanine dipeptide contains six states, a simpler model with only three states is equally good for predicting long-timescale motions. We also used the constructed Markov models to estimate important kinetic and dynamic quantities for protein folding, in particular, mean first-passage time. The results are consistent with available experimental measurements.

Markov dynamic models for long-timescale protein motion.

KAUST Repository

Chiang, Tsung-Han; Hsu, David; Latombe, Jean-Claude

2010-01-01

Molecular dynamics (MD) simulation is a well-established method for studying protein motion at the atomic scale. However, it is computationally intensive and generates massive amounts of data. One way of addressing the dual challenges of computation efficiency and data analysis is to construct simplified models of long-timescale protein motion from MD simulation data. In this direction, we propose to use Markov models with hidden states, in which the Markovian states represent potentially overlapping probabilistic distributions over protein conformations. We also propose a principled criterion for evaluating the quality of a model by its ability to predict long-timescale protein motions. Our method was tested on 2D synthetic energy landscapes and two extensively studied peptides, alanine dipeptide and the villin headpiece subdomain (HP-35 NleNle). One interesting finding is that although a widely accepted model of alanine dipeptide contains six states, a simpler model with only three states is equally good for predicting long-timescale motions. We also used the constructed Markov models to estimate important kinetic and dynamic quantities for protein folding, in particular, mean first-passage time. The results are consistent with available experimental measurements.

Benchmarking Computational Fluid Dynamics for Application to PWR Fuel

International Nuclear Information System (INIS)

Smith, L.D. III; Conner, M.E.; Liu, B.; Dzodzo, B.; Paramonov, D.V.; Beasley, D.E.; Langford, H.M.; Holloway, M.V.

2002-01-01

The present study demonstrates a process used to develop confidence in Computational Fluid Dynamics (CFD) as a tool to investigate flow and temperature distributions in a PWR fuel bundle. The velocity and temperature fields produced by a mixing spacer grid of a PWR fuel assembly are quite complex. Before using CFD to evaluate these flow fields, a rigorous benchmarking effort should be performed to ensure that reasonable results are obtained. Westinghouse has developed a method to quantitatively benchmark CFD tools against data at conditions representative of the PWR. Several measurements in a 5 x 5 rod bundle were performed. Lateral flow-field testing employed visualization techniques and Particle Image Velocimetry (PIV). Heat transfer testing involved measurements of the single-phase heat transfer coefficient downstream of the spacer grid. These test results were used to compare with CFD predictions. Among the parameters optimized in the CFD models based on this comparison with data include computational mesh, turbulence model, and boundary conditions. As an outcome of this effort, a methodology was developed for CFD modeling that provides confidence in the numerical results. (authors)

SD-CAS: Spin Dynamics by Computer Algebra System.

Science.gov (United States)

Filip, Xenia; Filip, Claudiu

2010-11-01

A computer algebra tool for describing the Liouville-space quantum evolution of nuclear 1/2-spins is introduced and implemented within a computational framework named Spin Dynamics by Computer Algebra System (SD-CAS). A distinctive feature compared with numerical and previous computer algebra approaches to solving spin dynamics problems results from the fact that no matrix representation for spin operators is used in SD-CAS, which determines a full symbolic character to the performed computations. Spin correlations are stored in SD-CAS as four-entry nested lists of which size increases linearly with the number of spins into the system and are easily mapped into analytical expressions in terms of spin operator products. For the so defined SD-CAS spin correlations a set of specialized functions and procedures is introduced that are essential for implementing basic spin algebra operations, such as the spin operator products, commutators, and scalar products. They provide results in an abstract algebraic form: specific procedures to quantitatively evaluate such symbolic expressions with respect to the involved spin interaction parameters and experimental conditions are also discussed. Although the main focus in the present work is on laying the foundation for spin dynamics symbolic computation in NMR based on a non-matrix formalism, practical aspects are also considered throughout the theoretical development process. In particular, specific SD-CAS routines have been implemented using the YACAS computer algebra package (http://yacas.sourceforge.net), and their functionality was demonstrated on a few illustrative examples. Copyright © 2010 Elsevier Inc. All rights reserved.

Moving finite elements: A continuously adaptive method for computational fluid dynamics

International Nuclear Information System (INIS)

Glasser, A.H.; Miller, K.; Carlson, N.

1991-01-01

Moving Finite Elements (MFE), a recently developed method for computational fluid dynamics, promises major advances in the ability of computers to model the complex behavior of liquids, gases, and plasmas. Applications of computational fluid dynamics occur in a wide range of scientifically and technologically important fields. Examples include meteorology, oceanography, global climate modeling, magnetic and inertial fusion energy research, semiconductor fabrication, biophysics, automobile and aircraft design, industrial fluid processing, chemical engineering, and combustion research. The improvements made possible by the new method could thus have substantial economic impact. Moving Finite Elements is a moving node adaptive grid method which has a tendency to pack the grid finely in regions where it is most needed at each time and to leave it coarse elsewhere. It does so in a manner which is simple and automatic, and does not require a large amount of human ingenuity to apply it to each particular problem. At the same time, it often allows the time step to be large enough to advance a moving shock by many shock thicknesses in a single time step, moving the grid smoothly with the solution and minimizing the number of time steps required for the whole problem. For 2D problems (two spatial variables) the grid is composed of irregularly shaped and irregularly connected triangles which are very flexible in their ability to adapt to the evolving solution. While other adaptive grid methods have been developed which share some of these desirable properties, this is the only method which combines them all. In many cases, the method can save orders of magnitude of computing time, equivalent to several generations of advancing computer hardware

Use of personal computers in performing a linear modal analysis of a large finite-element model

International Nuclear Information System (INIS)

Wagenblast, G.R.

1991-01-01

This paper presents the use of personal computers in performing a dynamic frequency analysis of a large (2,801 degrees of freedom) finite-element model. Large model linear time history dynamic evaluations of safety related structures were previously restricted to mainframe computers using direct integration analysis methods. This restriction was a result of the limited memory and speed of personal computers. With the advances in memory capacity and speed of the personal computers, large finite-element problems now can be solved in the office in a timely and cost effective manner. Presented in three sections, this paper describes the procedure used to perform the dynamic frequency analysis of the large (2,801 degrees of freedom) finite-element model on a personal computer. Section 2.0 describes the structure and the finite-element model that was developed to represent the structure for use in the dynamic evaluation. Section 3.0 addresses the hardware and software used to perform the evaluation and the optimization of the hardware and software operating configuration to minimize the time required to perform the analysis. Section 4.0 explains the analysis techniques used to reduce the problem to a size compatible with the hardware and software memory capacity and configuration

Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I

Energy Technology Data Exchange (ETDEWEB)

Schmalz, Mark S

2011-07-24

Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G} for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient

Analysis of the flow dynamics characteristics of an axial piston pump based on the computational fluid dynamics method

Directory of Open Access Journals (Sweden)

Bin Zhang

2017-01-01

Full Text Available To improve its working performance, the flow ripple characteristics of an axial piston pump were investigated with software which uses computational fluid dynamics (CFD technology. The simulation accuracy was significantly optimized through the use of the improved compressible fluid model. Flow conditions of the pump were tested using a pump flow ripple test rig, and the simulation results of the CFD model showed good agreement with the experimental data. Additionally, the composition of the flow ripple was analyzed using the improved CFD model, and the results showed that the compression ripple makes up 88% of the flow ripple. The flow dynamics of the piston pump is mainly caused by the pressure difference between the intake and discharge ports of the valve plates and the fluid oil compressibility.

Dynamic X-ray computed tomography

International Nuclear Information System (INIS)

Grangeat, P.

2003-01-01

Paper Dynamic computed tomography (CT) imaging aims at reconstructing image sequences where the dynamic nature of the living human body is of primary interest. Main concerned applications are image-guided interventional procedures, functional studies and cardiac imaging. The introduction of ultra-fast rotating gantries along with multi-row detectors and in near future area detectors allows a huge progress toward the imaging of moving organs with low-contrast resolution. This paper gives an overview of the different concepts used in dynamic CT. A new reconstruction algorithm based on a voxel-specific dynamic evolution compensation is also presented. It provides four-dimensional image sequences with accurate spatio-temporal information, where each frame is reconstructed using a long-scan acquisition mode on several half-turns. In the same time, this technique permits to reduce the dose delivered per rotation while keeping the same signal to noise ratio for every frame using an adaptive motion-compensated temporal averaging. Results are illustrated on simulated data. (authors)

A Symbolic and Graphical Computer Representation of Dynamical Systems

Science.gov (United States)

Gould, Laurence I.

2005-04-01

AUTONO is a Macsyma/Maxima program, designed at the University of Hartford, for solving autonomous systems of differential equations as well as for relating Lagrangians and Hamiltonians to their associated dynamical equations. AUTONO can be used in a number of fields to decipher a variety of complex dynamical systems with ease, producing their Lagrangian and Hamiltonian equations in seconds. These equations can then be incorporated into VisSim, a modeling and simulation program, which yields graphical representations of motion in a given system through easily chosen input parameters. The program, along with the VisSim differential-equations graphical package, allows for resolution and easy understanding of complex problems in a relatively short time; thus enabling quicker and more advanced computing of dynamical systems on any number of platforms---from a network of sensors on a space probe, to the behavior of neural networks, to the effects of an electromagnetic field on components in a dynamical system. A flowchart of AUTONO, along with some simple applications and VisSim output, will be shown.

Computer modeling of the dynamic processes in the Maryland University Training Reactor - (MUTR)

International Nuclear Information System (INIS)

White, Bernard H. IV; Ebert, David

1988-01-01

The simulator described in this paper models the behaviour of the Maryland University Training Reactor (MUTR). The reactor is a 250 kW, TRIGA reactor. The computer model is based on a system of five primary equations and eight auxiliary equations. The primary equations consist of the prompt jump approximation, a heat balance equation for the fuel and the moderator, and iodine and xenon buildup equations. For the comparison with the computer program, data from the reactor was acquired by using a personal computer (pc) which contained a Strawberry Tree data acquisition Card, connected to the reactor. The systems monitored by the pc were: two neutron detectors, fuel temperature, water temperature, three control rod positions and the period meter. The time differenced equations were programmed in the basic language. It has been shown by this paper, that the MUTR power rise from low power critical to high power, can be modelled by a relatively simple computer program. The program yields accurate agreement considering the simplicity of the program. The steady state error between the reactor and computer power is 4.4%. The difference in steady state temperatures, 112 deg. C and 117 deg. C, of the reactor and computer program, respectively, also yields a 4.5% error. Further fine tuning of the coefficients will yield higher accuracies

Shroud leakage flow models and a multi-dimensional coupling CFD (computational fluid dynamics) method for shrouded turbines

International Nuclear Information System (INIS)

Zou, Zhengping; Liu, Jingyuan; Zhang, Weihao; Wang, Peng

2016-01-01

Multi-dimensional coupling simulation is an effective approach for evaluating the flow and aero-thermal performance of shrouded turbines, which can balance the simulation accuracy and computing cost effectively. In this paper, 1D leakage models are proposed based on classical jet theories and dynamics equations, which can be used to evaluate most of the main features of shroud leakage flow, including the mass flow rate, radial and circumferential momentum, temperature and the jet width. Then, the 1D models are expanded to 2D distributions on the interface by using a multi-dimensional scaling method. Based on the models and multi-dimensional scaling, a multi-dimensional coupling simulation method for shrouded turbines is developed, in which, some boundary source and sink are set on the interface between the shroud and the main flow passage. To verify the precision, some simulations on the design point and off design points of a 1.5 stage turbine are conducted. It is indicated that the models and methods can give predictions with sufficient accuracy for most of the flow field features and will contribute to pursue deeper understanding and better design methods of shrouded axial turbines, which are the important devices in energy engineering. - Highlights: • Free and wall attached jet theories are used to model the leakage flow in shrouds. • Leakage flow rate is modeled by virtual labyrinth number and residual-energy factor. • A scaling method is applied to 1D model to obtain 2D distributions on interfaces. • A multi-dimensional coupling CFD method for shrouded turbines is proposed. • The proposed coupling method can give accurate predictions with low computing cost.

Modeling the economic costs of disasters and recovery: analysis using a dynamic computable general equilibrium model

Science.gov (United States)

Xie, W.; Li, N.; Wu, J.-D.; Hao, X.-L.

2014-04-01

Disaster damages have negative effects on the economy, whereas reconstruction investment has positive effects. The aim of this study is to model economic causes of disasters and recovery involving the positive effects of reconstruction activities. Computable general equilibrium (CGE) model is a promising approach because it can incorporate these two kinds of shocks into a unified framework and furthermore avoid the double-counting problem. In order to factor both shocks into the CGE model, direct loss is set as the amount of capital stock reduced on the supply side of the economy; a portion of investments restores the capital stock in an existing period; an investment-driven dynamic model is formulated according to available reconstruction data, and the rest of a given country's saving is set as an endogenous variable to balance the fixed investment. The 2008 Wenchuan Earthquake is selected as a case study to illustrate the model, and three scenarios are constructed: S0 (no disaster occurs), S1 (disaster occurs with reconstruction investment) and S2 (disaster occurs without reconstruction investment). S0 is taken as business as usual, and the differences between S1 and S0 and that between S2 and S0 can be interpreted as economic losses including reconstruction and excluding reconstruction, respectively. The study showed that output from S1 is found to be closer to real data than that from S2. Economic loss under S2 is roughly 1.5 times that under S1. The gap in the economic aggregate between S1 and S0 is reduced to 3% at the end of government-led reconstruction activity, a level that should take another four years to achieve under S2.

Threshold-based queuing system for performance analysis of cloud computing system with dynamic scaling

Energy Technology Data Exchange (ETDEWEB)

Shorgin, Sergey Ya.; Pechinkin, Alexander V. [Institute of Informatics Problems, Russian Academy of Sciences (Russian Federation); Samouylov, Konstantin E.; Gaidamaka, Yuliya V.; Gudkova, Irina A.; Sopin, Eduard S. [Telecommunication Systems Department, Peoples’ Friendship University of Russia (Russian Federation)

2015-03-10

Cloud computing is promising technology to manage and improve utilization of computing center resources to deliver various computing and IT services. For the purpose of energy saving there is no need to unnecessarily operate many servers under light loads, and they are switched off. On the other hand, some servers should be switched on in heavy load cases to prevent very long delays. Thus, waiting times and system operating cost can be maintained on acceptable level by dynamically adding or removing servers. One more fact that should be taken into account is significant server setup costs and activation times. For better energy efficiency, cloud computing system should not react on instantaneous increase or instantaneous decrease of load. That is the main motivation for using queuing systems with hysteresis for cloud computing system modelling. In the paper, we provide a model of cloud computing system in terms of multiple server threshold-based infinite capacity queuing system with hysteresis and noninstantanuous server activation. For proposed model, we develop a method for computing steady-state probabilities that allow to estimate a number of performance measures.

Threshold-based queuing system for performance analysis of cloud computing system with dynamic scaling

International Nuclear Information System (INIS)

Shorgin, Sergey Ya.; Pechinkin, Alexander V.; Samouylov, Konstantin E.; Gaidamaka, Yuliya V.; Gudkova, Irina A.; Sopin, Eduard S.

2015-01-01

Cloud computing is promising technology to manage and improve utilization of computing center resources to deliver various computing and IT services. For the purpose of energy saving there is no need to unnecessarily operate many servers under light loads, and they are switched off. On the other hand, some servers should be switched on in heavy load cases to prevent very long delays. Thus, waiting times and system operating cost can be maintained on acceptable level by dynamically adding or removing servers. One more fact that should be taken into account is significant server setup costs and activation times. For better energy efficiency, cloud computing system should not react on instantaneous increase or instantaneous decrease of load. That is the main motivation for using queuing systems with hysteresis for cloud computing system modelling. In the paper, we provide a model of cloud computing system in terms of multiple server threshold-based infinite capacity queuing system with hysteresis and noninstantanuous server activation. For proposed model, we develop a method for computing steady-state probabilities that allow to estimate a number of performance measures

Coupling fast fluid dynamics and multizone airflow models in Modelica Buildings library to simulate the dynamics of HVAC systems

Energy Technology Data Exchange (ETDEWEB)

Tian, Wei [Univ. of Miami, FL (United States). Dept. of Civil, Architectural and Environmental Engineering; Sevilla, Thomas Alonso [Univ. of Miami, FL (United States). Dept. of Civil, Architectural and Environmental Engineering; Zuo, Wangda [Univ. of Miami, FL (United States). Dept. of Civil, Architectural and Environmental Engineering; Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis and Environmental Impacts Div.

2017-06-08

Historically, multizone models are widely used in building airflow and energy performance simulations due to their fast computing speed. However, multizone models assume that the air in a room is well mixed, consequently limiting their application. In specific rooms where this assumption fails, the use of computational fluid dynamics (CFD) models may be an alternative option. Previous research has mainly focused on coupling CFD models and multizone models to study airflow in large spaces. While significant, most of these analyses did not consider the coupled simulation of the building airflow with the building's Heating, Ventilation, and Air-Conditioning (HVAC) systems. This paper tries to fill the gap by integrating the models for HVAC systems with coupled multizone and CFD simulations for airflows, using the Modelica simul ation platform. To improve the computational efficiency, we incorporated a simplified CFD model named fast fluid dynamics (FFD). We first introduce the data synchronization strategy and implementation in Modelica. Then, we verify the implementation using two case studies involving an isothermal and a non-isothermal flow by comparing model simulations to experiment data. Afterward, we study another three cases that are deemed more realistic. This is done by attaching a variable air volume (VAV) terminal box and a VAV system to previous flows to assess the capability of the models in studying the dynamic control of HVAC systems. Finally, we discuss further research needs on the coupled simulation using the models.

Computational Fluid Dynamics in Ventilation

DEFF Research Database (Denmark)

Nielsen, Peter V.; Allard, Francis; Awbi, Hazim B.

2008-01-01

Computational Fluid Dynamics in Ventilation Design is a new title in the is a new title in the REHVA guidebook series. The guidebook is written for people who need to use and discuss results based on CFD predictions, and it gives insight into the subject for those who are not used to work with CFD...

How Levins’ dynamics emerges from a Ricker metapopulation model

KAUST Repository

Elí as-Wolff, F.; Eriksson, Anders; Manica, A.; Mehlig, B.

2015-01-01

Understanding the dynamics of metapopulations close to extinction is of vital importance for management. Levins-like models, in which local patches are treated as either occupied or empty, have been used extensively to explore the extinction dynamics of metapopulations, but they ignore the important role of local population dynamics. In this paper, we consider a stochastic metapopulation model where local populations follow a stochastic, density-dependent dynamics (the Ricker model), and use this framework to investigate the behaviour of the metapopulation on the brink of extinction. We determine under which circumstances the metapopulation follows a time evolution consistent with Levins’ dynamics. We derive analytical expressions for the colonisation and extinction rates (c and e) in Levins-type models in terms of reproduction, survival and dispersal parameters of the local populations, providing an avenue to parameterising Levins-like models from the type of information on local demography that is available for a number of species. To facilitate applying our results, we provide a numerical algorithm for computing c and e.

How Levins’ dynamics emerges from a Ricker metapopulation model

KAUST Repository

Elías-Wolff, F.

2015-09-24

Understanding the dynamics of metapopulations close to extinction is of vital importance for management. Levins-like models, in which local patches are treated as either occupied or empty, have been used extensively to explore the extinction dynamics of metapopulations, but they ignore the important role of local population dynamics. In this paper, we consider a stochastic metapopulation model where local populations follow a stochastic, density-dependent dynamics (the Ricker model), and use this framework to investigate the behaviour of the metapopulation on the brink of extinction. We determine under which circumstances the metapopulation follows a time evolution consistent with Levins’ dynamics. We derive analytical expressions for the colonisation and extinction rates (c and e) in Levins-type models in terms of reproduction, survival and dispersal parameters of the local populations, providing an avenue to parameterising Levins-like models from the type of information on local demography that is available for a number of species. To facilitate applying our results, we provide a numerical algorithm for computing c and e.

Mechatronic Model Based Computed Torque Control of a Parallel Manipulator

Directory of Open Access Journals (Sweden)

Zhiyong Yang

2008-11-01

Full Text Available With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme employing the computed torque control algorithm are presented in this paper. First, the integrated dynamic coupling model is deduced, according to equivalent torques between the mechanical structure and the PM (Permanent Magnetism servomotor. Second, computed torque controller is described in detail for the above proposed model. At last, a series of numerical simulations and experiments are carried out to test the effectiveness of the system, and the results verify the favourable tracking ability and robustness.

Mechatronic Model Based Computed Torque Control of a Parallel Manipulator

Directory of Open Access Journals (Sweden)

Zhiyong Yang

2008-03-01

Full Text Available With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme employing the computed torque control algorithm are presented in this paper. First, the integrated dynamic coupling model is deduced, according to equivalent torques between the mechanical structure and the PM (Permanent Magnetism servomotor. Second, computed torque controller is described in detail for the above proposed model. At last, a series of numerical simulations and experiments are carried out to test the effectiveness of the system, and the results verify the favourable tracking ability and robustness.

Variability of dynamic source parameters inferred from kinematic models of past earthquakes

KAUST Repository

Causse, M.; Dalguer, L. A.; Mai, Paul Martin

2013-01-01

We analyse the scaling and distribution of average dynamic source properties (fracture energy, static, dynamic and apparent stress drops) using 31 kinematic inversion models from 21 crustal earthquakes. Shear-stress histories are computed by solving

Open-end tube dynamic flow model with an oscillatory extortion

Directory of Open Access Journals (Sweden)

Tulwin Tytus

2017-01-01

Full Text Available This paper presents a derivation of dynamic 2d mathematical model for open end tube with oscillatory extortion in the region of the closed end. The aim the research is to investigate possible uses of the increased pressure in the enclosed tube chamber, especially for energy efficient lift generation. The mathematical model allows to test and predict how flow modifications impact the resultant lifting force. A derivation of the proposed mathematical model is shown. The mathematical model is then compared to the computational fluid dynamics discrete model. The results prove the accuracy of the mathematical physical model.

Reverse Engineering the Inflammatory "Clock": From Computational Modeling to Rational Resetting.

Science.gov (United States)

Vodovotz, Yoram

2016-01-01

Properly-regulated inflammation is central to homeostasis. Traumatic injury, hemorrhagic shock, septic shock, and other injury-related processes such as wound healing are associated with dysregulated inflammation. Like many biological processes, inflammation is a dynamic, complex system whose function, like that of an analog clock, cannot be discerned simply from a laundry list of its parts (data). The advent of multiplexed platforms for gathering biological data, while providing an unprecedented level of detailed information about the inflammatory response, has paradoxically also proven to be overwhelming. This problem is especially acute when the datasets involve time courses, since typical statistical analyses and data-driven modeling are geared towards single time points. Various groups have addressed this problem using dynamic approaches to data-driven and mechanistic computational modeling. These modeling tools can be thought of as the "gears" and "hands" of the "clock," and have led to insights regarding principal drivers, dynamic networks, feedbacks, and regulatory switches that characterize and perhaps regulate the inflammatory response. In parallel, mechanistic computational models have given an abstracted sense of how the inflammatory "clock" works, leading to in silico models of critically ill individuals and populations. Integrating data-driven and mechanistic modeling may point the way to a rational "resetting" of inflammation via model-driven precision medicine.

Quantitative comparison of hemodynamics in simulated and 3D angiography models of cerebral aneurysms by use of computational fluid dynamics.

Science.gov (United States)

Saho, Tatsunori; Onishi, Hideo

2015-07-01

In this study, we evaluated hemodynamics using simulated models and determined how cerebral aneurysms develop in simulated and patient-specific models based on medical images. Computational fluid dynamics (CFD) was analyzed by use of OpenFOAM software. Flow velocity, stream line, and wall shear stress (WSS) were evaluated in a simulated model aneurysm with known geometry and in a three-dimensional angiographic model. The ratio of WSS at the aneurysm compared with that at the basilar artery was 1:10 in simulated model aneurysms with a diameter of 10 mm and 1:18 in the angiographic model, indicating similar tendencies. Vortex flow occurred in both model aneurysms, and the WSS decreased in larger model aneurysms. The angiographic model provided accurate CFD information, and the tendencies of simulated and angiographic models were similar. These findings indicate that hemodynamic effects are involved in the development of aneurysms.

The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

Science.gov (United States)

Schirner, Michael; McIntosh, Anthony R.; Jirsa, Viktor K.

2013-01-01

Abstract Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected—ideally functionally relevant—aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept. PMID:23442172

On the Impact of Execution Models: A Case Study in Computational Chemistry

Energy Technology Data Exchange (ETDEWEB)

Chavarría-Miranda, Daniel; Halappanavar, Mahantesh; Krishnamoorthy, Sriram; Manzano Franco, Joseph B.; Vishnu, Abhinav; Hoisie, Adolfy

2015-05-25

Efficient utilization of high-performance computing (HPC) platforms is an important and complex problem. Execution models, abstract descriptions of the dynamic runtime behavior of the execution stack, have significant impact on the utilization of HPC systems. Using a computational chemistry kernel as a case study and a wide variety of execution models combined with load balancing techniques, we explore the impact of execution models on the utilization of an HPC system. We demonstrate a 50 percent improvement in performance by using work stealing relative to a more traditional static scheduling approach. We also use a novel semi-matching technique for load balancing that has comparable performance to a traditional hypergraph-based partitioning implementation, which is computationally expensive. Using this study, we found that execution model design choices and assumptions can limit critical optimizations such as global, dynamic load balancing and finding the correct balance between available work units and different system and runtime overheads. With the emergence of multi- and many-core architectures and the consequent growth in the complexity of HPC platforms, we believe that these lessons will be beneficial to researchers tuning diverse applications on modern HPC platforms, especially on emerging dynamic platforms with energy-induced performance variability.

Computational fluid dynamics research at the United Technologies Research Center requiring supercomputers

Science.gov (United States)

Landgrebe, Anton J.

1987-01-01

An overview of research activities at the United Technologies Research Center (UTRC) in the area of Computational Fluid Dynamics (CFD) is presented. The requirement and use of various levels of computers, including supercomputers, for the CFD activities is described. Examples of CFD directed toward applications to helicopters, turbomachinery, heat exchangers, and the National Aerospace Plane are included. Helicopter rotor codes for the prediction of rotor and fuselage flow fields and airloads were developed with emphasis on rotor wake modeling. Airflow and airload predictions and comparisons with experimental data are presented. Examples are presented of recent parabolized Navier-Stokes and full Navier-Stokes solutions for hypersonic shock-wave/boundary layer interaction, and hydrogen/air supersonic combustion. In addition, other examples of CFD efforts in turbomachinery Navier-Stokes methodology and separated flow modeling are presented. A brief discussion of the 3-tier scientific computing environment is also presented, in which the researcher has access to workstations, mid-size computers, and supercomputers.

Computational Fluid Dynamics for nuclear applications: from CFD to multi-scale CMFD

International Nuclear Information System (INIS)

Yadigaroglu, G.

2005-01-01

New trends in computational methods for nuclear reactor thermal-hydraulics are discussed; traditionally, these have been based on the two-fluid model. Although CFD computations for single phase flows are commonplace, Computational Multi-Fluid Dynamics (CMFD) is still under development. One-fluid methods coupled with interface tracking techniques provide interesting opportunities and enlarge the scope of problems that can be solved. For certain problems, one may have to conduct 'cascades' of computations at increasingly finer scales to resolve all issues. The case study of condensation of steam/air mixtures injected from a downward-facing vent into a pool of water and a proposed CMFD initiative to numerically model Critical Heat Flux (CHF) illustrate such cascades. For the venting problem, a variety of tools are used: a system code for system behaviour; an interface-tracking method (Volume of Fluid, VOF) to examine the behaviour of large bubbles; direct-contact condensation can be treated either by Direct Numerical Simulation (DNS) or by analytical methods

Computational Fluid Dynamics for nuclear applications: from CFD to multi-scale CMFD

Energy Technology Data Exchange (ETDEWEB)

Yadigaroglu, G. [Swiss Federal Institute of Technology-Zurich (ETHZ), Nuclear Engineering Laboratory, ETH-Zentrum, CLT CH-8092 Zurich (Switzerland)]. E-mail: yadi@ethz.ch

2005-02-01

New trends in computational methods for nuclear reactor thermal-hydraulics are discussed; traditionally, these have been based on the two-fluid model. Although CFD computations for single phase flows are commonplace, Computational Multi-Fluid Dynamics (CMFD) is still under development. One-fluid methods coupled with interface tracking techniques provide interesting opportunities and enlarge the scope of problems that can be solved. For certain problems, one may have to conduct 'cascades' of computations at increasingly finer scales to resolve all issues. The case study of condensation of steam/air mixtures injected from a downward-facing vent into a pool of water and a proposed CMFD initiative to numerically model Critical Heat Flux (CHF) illustrate such cascades. For the venting problem, a variety of tools are used: a system code for system behaviour; an interface-tracking method (Volume of Fluid, VOF) to examine the behaviour of large bubbles; direct-contact condensation can be treated either by Direct Numerical Simulation (DNS) or by analytical methods.

The dynamical core of the Aeolus 1.0 statistical-dynamical atmosphere model: validation and parameter optimization

Science.gov (United States)

Totz, Sonja; Eliseev, Alexey V.; Petri, Stefan; Flechsig, Michael; Caesar, Levke; Petoukhov, Vladimir; Coumou, Dim

2018-02-01

We present and validate a set of equations for representing the atmosphere's large-scale general circulation in an Earth system model of intermediate complexity (EMIC). These dynamical equations have been implemented in Aeolus 1.0, which is a statistical-dynamical atmosphere model (SDAM) and includes radiative transfer and cloud modules (Coumou et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is computationally efficient and thus enables us to perform climate simulations at multimillennia timescales, which is a prime aim of our model development. Further, this computational efficiency enables us to scan large and high-dimensional parameter space to tune the model parameters, e.g., for sensitivity studies.Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0.We optimize the dynamical core parameter values by tuning all relevant dynamical fields to ERA-Interim reanalysis data (1983-2009) forcing the dynamical core with prescribed surface temperature, surface humidity and cumulus cloud fraction. We test the model's performance in reproducing the seasonal cycle and the influence of the El Niño-Southern Oscillation (ENSO). We use a simulated annealing optimization algorithm, which approximates the global minimum of a high-dimensional function.With non-tuned parameter values, the model performs reasonably in terms of its representation of zonal-mean circulation, planetary waves and storm tracks. The simulated annealing optimization improves in particular the model's representation of the Northern Hemisphere jet stream and storm tracks as well as the Hadley circulation.The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower

Grid computing in large pharmaceutical molecular modeling.

Science.gov (United States)

Claus, Brian L; Johnson, Stephen R

2008-07-01

Most major pharmaceutical companies have employed grid computing to expand their compute resources with the intention of minimizing additional financial expenditure. Historically, one of the issues restricting widespread utilization of the grid resources in molecular modeling is the limited set of suitable applications amenable to coarse-grained parallelization. Recent advances in grid infrastructure technology coupled with advances in application research and redesign will enable fine-grained parallel problems, such as quantum mechanics and molecular dynamics, which were previously inaccessible to the grid environment. This will enable new science as well as increase resource flexibility to load balance and schedule existing workloads.

System Dynamics Modeling of Multipurpose Reservoir Operation

Directory of Open Access Journals (Sweden)

Ebrahim Momeni

2006-03-01

Full Text Available System dynamics, a feedback – based object – oriented simulation approach, not only represents complex dynamic systemic systems in a realistic way but also allows the involvement of end users in model development to increase their confidence in modeling process. The increased speed of model development, the possibility of group model development, the effective communication of model results, and the trust developed in the model due to user participation are the main strengths of this approach. The ease of model modification in response to changes in the system and the ability to perform sensitivity analysis make this approach more attractive compared with systems analysis techniques for modeling water management systems. In this study, a system dynamics model was developed for the Zayandehrud basin in central Iran. This model contains river basin, dam reservoir, plains, irrigation systems, and groundwater. Current operation rule is conjunctive use of ground and surface water. Allocation factor for each irrigation system is computed based on the feedback from groundwater storage in its zone. Deficit water is extracted from groundwater.The results show that applying better rules can not only satisfy all demands such as Gawkhuni swamp environmental demand, but it can also  prevent groundwater level drawdown in future.

The Efficient Use of Vector Computers with Emphasis on Computational Fluid Dynamics : a GAMM-Workshop

CERN Document Server

Gentzsch, Wolfgang

1986-01-01

The GAMM Committee for Numerical Methods in Fluid Mechanics organizes workshops which should bring together experts of a narrow field of computational fluid dynamics (CFD) to exchange ideas and experiences in order to speed-up the development in this field. In this sense it was suggested that a workshop should treat the solution of CFD problems on vector computers. Thus we organized a workshop with the title "The efficient use of vector computers with emphasis on computational fluid dynamics". The workshop took place at the Computing Centre of the University of Karlsruhe, March 13-15,1985. The participation had been restricted to 22 people of 7 countries. 18 papers have been presented. In the announcement of the workshop we wrote: "Fluid mechanics has actively stimulated the development of superfast vector computers like the CRAY's or CYBER 205. Now these computers on their turn stimulate the development of new algorithms which result in a high degree of vectorization (sca1ar/vectorized execution-time). But w...

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

A computationally fast, reduced model for simulating landslide dynamics and tsunamis generated by landslides in natural terrains

Science.gov (United States)

Mohammed, F.

2016-12-01

Landslide hazards such as fast-moving debris flows, slow-moving landslides, and other mass flows cause numerous fatalities, injuries, and damage. Landslide occurrences in fjords, bays, and lakes can additionally generate tsunamis with locally extremely high wave heights and runups. Two-dimensional depth-averaged models can successfully simulate the entire lifecycle of the three-dimensional landslide dynamics and tsunami propagation efficiently and accurately with the appropriate assumptions. Landslide rheology is defined using viscous fluids, visco-plastic fluids, and granular material to account for the possible landslide source materials. Saturated and unsaturated rheologies are further included to simulate debris flow, debris avalanches, mudflows, and rockslides respectively. The models are obtained by reducing the fully three-dimensional Navier-Stokes equations with the internal rheological definition of the landslide material, the water body, and appropriate scaling assumptions to obtain the depth-averaged two-dimensional models. The landslide and tsunami models are coupled to include the interaction between the landslide and the water body for tsunami generation. The reduced models are solved numerically with a fast semi-implicit finite-volume, shock-capturing based algorithm. The well-balanced, positivity preserving algorithm accurately accounts for wet-dry interface transition for the landslide runout, landslide-water body interface, and the tsunami wave flooding on land. The models are implemented as a General-Purpose computing on Graphics Processing Unit-based (GPGPU) suite of models, either coupled or run independently within the suite. The GPGPU implementation provides up to 1000 times speedup over a CPU-based serial computation. This enables simulations of multiple scenarios of hazard realizations that provides a basis for a probabilistic hazard assessment. The models have been successfully validated against experiments, past studies, and field data

Real-time management (RTM) by cloud computing system dynamics (CCSD) for risk analysis of Fukushima nuclear power plant (NPP) accident

Energy Technology Data Exchange (ETDEWEB)

Cho, Hyo Sung [Yonsei Univ., Wonju Gangwon-do (Korea, Republic of). Dept. of Radiation Convergence Engineering; Woo, Tae Ho [Yonsei Univ., Wonju Gangwon-do (Korea, Republic of). Dept. of Radiation Convergence Engineering; The Cyber Univ. of Korea, Seoul (Korea, Republic of). Dept. of Mechanical and Control Engineering

2017-03-15

The earthquake and tsunami induced accident of nuclear power plant (NPP) in Fukushima disaster is investigated by the real-time management (RTM) method. This non-linear logic of the safety management is applied to enhance the methodological confidence in the NPP reliability. The case study of the earthquake is modeled for the fast reaction characteristics of the RTM. The system dynamics (SD) modeling simulations and cloud computing are applied for the RTM method where the real time simulation has the fast and effective communication for the accident remediation and prevention. Current tablet computing system can improve the safety standard of the NPP. Finally, the procedure of the cloud computing system dynamics (CCSD) modeling is constructed.

Real-time management (RTM) by cloud computing system dynamics (CCSD) for risk analysis of Fukushima nuclear power plant (NPP) accident

International Nuclear Information System (INIS)

Cho, Hyo Sung; Woo, Tae Ho; The Cyber Univ. of Korea, Seoul

2017-01-01

The earthquake and tsunami induced accident of nuclear power plant (NPP) in Fukushima disaster is investigated by the real-time management (RTM) method. This non-linear logic of the safety management is applied to enhance the methodological confidence in the NPP reliability. The case study of the earthquake is modeled for the fast reaction characteristics of the RTM. The system dynamics (SD) modeling simulations and cloud computing are applied for the RTM method where the real time simulation has the fast and effective communication for the accident remediation and prevention. Current tablet computing system can improve the safety standard of the NPP. Finally, the procedure of the cloud computing system dynamics (CCSD) modeling is constructed.

Bio-Inspired Neural Model for Learning Dynamic Models

Science.gov (United States)

Duong, Tuan; Duong, Vu; Suri, Ronald

2009-01-01

A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

Synthetic tetracycline-inducible regulatory networks: computer-aided design of dynamic phenotypes

Directory of Open Access Journals (Sweden)

Kaznessis Yiannis N

2007-01-01

Full Text Available Abstract Background Tightly regulated gene networks, precisely controlling the expression of protein molecules, have received considerable interest by the biomedical community due to their promising applications. Among the most well studied inducible transcription systems are the tetracycline regulatory expression systems based on the tetracycline resistance operon of Escherichia coli, Tet-Off (tTA and Tet-On (rtTA. Despite their initial success and improved designs, limitations still persist, such as low inducer sensitivity. Instead of looking at these networks statically, and simply changing or mutating the promoter and operator regions with trial and error, a systematic investigation of the dynamic behavior of the network can result in rational design of regulatory gene expression systems. Sophisticated algorithms can accurately capture the dynamical behavior of gene networks. With computer aided design, we aim to improve the synthesis of regulatory networks and propose new designs that enable tighter control of expression. Results In this paper we engineer novel networks by recombining existing genes or part of genes. We synthesize four novel regulatory networks based on the Tet-Off and Tet-On systems. We model all the known individual biomolecular interactions involved in transcription, translation, regulation and induction. With multiple time-scale stochastic-discrete and stochastic-continuous models we accurately capture the transient and steady state dynamics of these networks. Important biomolecular interactions are identified and the strength of the interactions engineered to satisfy design criteria. A set of clear design rules is developed and appropriate mutants of regulatory proteins and operator sites are proposed. Conclusion The complexity of biomolecular interactions is accurately captured through computer simulations. Computer simulations allow us to look into the molecular level, portray the dynamic behavior of gene regulatory

APPLICATION OF MODELLING SYSTEMS IN THE DISCIPLINE «MODERN THEORY OF THE DYNAMIC SYSTEMS CONTROL» OF BACHELOR DEGREE FOR THE «COMPUTER SCIENCES» SPECIALTY

Directory of Open Access Journals (Sweden)

ERSHOVA N. M.

2017-05-01

Full Text Available Annotation. Purpose of the article. To present the capabilities of the MVTU 3.7 simulation system while the transient processes studying of complex dynamic systems and the appropriateness of its using in the learning process. Methodology of the research. Computer technology and information technologies are the main tools of the modern IT specialist, therefore, the qualitative preparation of students in this field has a great importance in the general system of specialists training and largely determines the material mastering degree at the senior courses. The absence of standard programs libraries for solving the most frequently encountered engineering problems in modern algorithmic programming languages makes the creating software products process for research of complex dynamic systems very difficult. For help come systems of modeling, mathematical base of which is the theory of automatic control. There are unified principles for their creation, which are based on the description of structural schemes, that is the graphical representation of a mathematical model. The MVTU 3.7 simulation system allows you to model transient processes, investigate stability and perform the synthesis of the parameters of the oscillatory processes of various technical devices: mechanical, hydraulic, heat engineering, electrotechnical, etc., including means and automation systems. The restricted version is applicable to technical devices with 15 degrees of freedom. In the MVTU 3.7 simulation system, the main role is assigned to the graphic editor, with its help a simulation scheme is created on the display screen according to the structural scheme of the research system. Block structures are selected from the graphics database using the mouse. The graphical database is located on the display screen next to the working field. After the simulation scheme creating the function block parameters are assigned, the integration method is selected and the integration

Computational Cellular Dynamics Based on the Chemical Master Equation: A Challenge for Understanding Complexity.

Science.gov (United States)

Liang, Jie; Qian, Hong

2010-01-01

Modern molecular biology has always been a great source of inspiration for computational science. Half a century ago, the challenge from understanding macromolecular dynamics has led the way for computations to be part of the tool set to study molecular biology. Twenty-five years ago, the demand from genome science has inspired an entire generation of computer scientists with an interest in discrete mathematics to join the field that is now called bioinformatics. In this paper, we shall lay out a new mathematical theory for dynamics of biochemical reaction systems in a small volume (i.e., mesoscopic) in terms of a stochastic, discrete-state continuous-time formulation, called the chemical master equation (CME). Similar to the wavefunction in quantum mechanics, the dynamically changing probability landscape associated with the state space provides a fundamental characterization of the biochemical reaction system. The stochastic trajectories of the dynamics are best known through the simulations using the Gillespie algorithm. In contrast to the Metropolis algorithm, this Monte Carlo sampling technique does not follow a process with detailed balance. We shall show several examples how CMEs are used to model cellular biochemical systems. We shall also illustrate the computational challenges involved: multiscale phenomena, the interplay between stochasticity and nonlinearity, and how macroscopic determinism arises from mesoscopic dynamics. We point out recent advances in computing solutions to the CME, including exact solution of the steady state landscape and stochastic differential equations that offer alternatives to the Gilespie algorithm. We argue that the CME is an ideal system from which one can learn to understand "complex behavior" and complexity theory, and from which important biological insight can be gained.

K-TIF: a two-fluid computer program for downcomer flow dynamics. [PWR

Energy Technology Data Exchange (ETDEWEB)

Amsden, A.A.; Harlow, F.H.

1977-10-01

The K-TIF computer program has been developed for numerical solution of the time-varying dynamics of steam and water in a pressurized water reactor downcomer. The current status of physical and mathematical modeling is presented in detail. The report also contains a complete description of the numerical solution technique, a full description and listing of the computer program, instructions for its use, with a sample printout for a specific test problem. A series of calculations, performed with no change in the modeling parameters, shows consistent agreement with the experimental trends over a wide range of conditions, which gives confidence to the calculations as a basis for investigating the complicated physics of steam-water flows in the downcomer.

Three-dimensional computer simulation at vehicle collision using dynamic model. Application to various collision types; Rikigaku model ni yoru jidosha shototsuji no sanjigen kyodo simulation. Shushu no shototsu keitai eno tekiyo

Energy Technology Data Exchange (ETDEWEB)

Abe, M; Morisawa, M [Musashi Institute of Technology, Tokyo (Japan); Sato, T [Keio University, Tokyo (Japan); Kobayashi, K [Molex-Japan Co. Ltd., Tokyo (Japan)

1997-10-01

The past study of safety at vehicle collision pays attention to phenomena within the short time from starting collision, and the behavior of rollover is studied separating from that at collision. Most simulations of traffic accident are two-dimensional simulations. Therefore, it is indispensable for vehicle design to the analyze three-dimensional and continuous behavior from crash till stopping. Accordingly, in this study, the three-dimensional behavior of two vehicles at collision was simulated by computer using dynamic models. Then, by comparison of the calculated results with real vehicles` collision test data, it was confirmed that dynamic model of this study was reliable. 10 refs., 6 figs., 3 tabs.

A stochastic phase-field model determined from molecular dynamics

KAUST Repository

von Schwerin, Erik

2010-03-17

The dynamics of dendritic growth of a crystal in an undercooled melt is determined by macroscopic diffusion-convection of heat and by capillary forces acting on the nanometer scale of the solid-liquid interface width. Its modelling is useful for instance in processing techniques based on casting. The phase-field method is widely used to study evolution of such microstructural phase transformations on a continuum level; it couples the energy equation to a phenomenological Allen-Cahn/Ginzburg-Landau equation modelling the dynamics of an order parameter determining the solid and liquid phases, including also stochastic fluctuations to obtain the qualitatively correct result of dendritic side branching. This work presents a method to determine stochastic phase-field models from atomistic formulations by coarse-graining molecular dynamics. It has three steps: (1) a precise quantitative atomistic definition of the phase-field variable, based on the local potential energy; (2) derivation of its coarse-grained dynamics model, from microscopic Smoluchowski molecular dynamics (that is Brownian or over damped Langevin dynamics); and (3) numerical computation of the coarse-grained model functions. The coarse-grained model approximates Gibbs ensemble averages of the atomistic phase-field, by choosing coarse-grained drift and diffusion functions that minimize the approximation error of observables in this ensemble average. © EDP Sciences, SMAI, 2010.