Generic Simulation Framework Research Articles

A central limit theorem for adaptive and interacting Markov chains

Adaptive and interacting Markov Chains Monte Carlo (MCMC) algorithms are a novel class of non-Markovian algorithms aimed at improving the simulation efficiency for complicated target distributions. In this paper, we study a general (non-Markovian) simulation framework covering both the adaptive and interacting MCMC algorithms. We establish a Central Limit Theorem for additive functionals of unbounded functions under a set of verifiable conditions, and identify the asymptotic variance. Our result extends all the results reported so far. An application to the interacting tempering algorithm (a simplified version of the equi-energy sampler) is presented to support our claims.

A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks.

We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey.

Adjoint-based estimation and optimization for column liquid chromatography models

Simulation and optimization of chromatographic processes are continuously gaining practical importance, as they allow for faster and cheaper process development. Although a lot of effort has been put into developing numerical schemes for simulation, fast optimization and estimation algorithms also are of importance. To determine parameters for an a priori defined model, a suited approach is the inverse method that fits the measurement data to the model response.This paper presents an adjoint method to compute model parameter derivatives for a wide range of differentiable liquid chromatography models and provides practical information for the implementation in a generic simulation framework by the example of ion-exchange chromatography.The example shows that the approach is effective for parameter estimation of model proteins and superior to forward sensitivities in terms of computational effort. An optimization of peak separation in salt step elution demonstrates that the method is not restricted to inverse parameter estimation.

An Open-Source Multiscale Framework for the Simulation of Nanoscale Devices

We present a general simulation framework for assessing the performance of nanoscale devices that combines several powerful and widely used open-source codes, and based on minimal but chemically accurate tight-binding Hamiltonians obtained from density-functional theory calculations and using maximally localized Wannier functions to represent the electronic state. Transport properties are then computed within the nonequilibrium Green's function formalism. We illustrate the capabilities of this framework applying it to a transistor with generic gate geometries, i.e., a double-gate nanoscale field-effect transistor where the channel is formed by graphene nanoribbons terminated with hydrogen, fluorine, and OH groups.

A Generic Framework for Modeling and Simulation of Cloud Computing Services

Cloud Computing is a paradigm in which tasks are assigned to a combination of computing resources, software and services accessed over a network following the pay-as–you-go financial model. It has been also described as on-demand computing. With the continuous increases of cloud service providers, it becomes crucial to develop a simulation tool to reflect the properties of such complex environment to help clients selecting the appropriate providers. Available Cloudbased tools are designed for cloud architectures and resources scheduling, not the problem of provider selection. Even the Grid-based tools who share many features with the Cloud cannot cope with such problem due to the novel characteristics and services of the Cloud. This paper provides a new simulation tool that reflects the nature of clouds embedding all its aspects, as well as its QoS parameters. Such tool is designed to simulate any framework or solution for service provider selection problem. The proposed simulation tool is validated by running a framework developed for service provider selection problem based on QoS and utility functions. The paper also reviews various mathematical approaches that have been used to model cloud services, where most of them are formulations of cloud services that aim to optimize its quality of service, performance or energy efficiency under given constraints.

A conceptual framework for hybrid system dynamics and discrete event simulation for healthcare

PurposeThe purpose of this paper is to develop a generic framework for hybrid (integrated deployment of system dynamics and discrete event simulation) simulation which can be applied in the healthcare domain.Design/methodology/approachAs hybrid simulation in an organisational context is a new topic with limited available data on deployment of hybrid simulation in organisational context, an inductive approach has been applied. On the basis of knowledge induced from literature, a generic conceptual framework for hybrid simulation has been developed. The proposed framework is demonstrated using an explanatory case study comprising an accident and emergency (A&E) department.FindingsThe framework provided detailed guidance for the development of a hybrid model of an A&E case study. Findings of this case study suggest that the hybrid model was more efficient in capturing behavioural impact on operational performances.Research limitations/implicationsThe framework is limited to only SD and DES; as agent‐based is another simulation method which is emerging as a promising tool for analysing problems such as spread of infectious diseases in healthcare context, inclusion of this into the framework will enhance the utility of the framework.Practical implicationsThis framework will aid in the development of hybrid models capable of comprehending both detail as well as dynamic complexity, which will contribute towards a deeper understanding of the problems, resulting in more effective decision making.Social implicationsIt is expected that this research will encourage those engaged in simulation (e.g. researchers, practitioners, decision makers) to realise the potential of cross‐fertilisation of the two simulation paradigms.Originality/valueCurrently, there is no conceptual framework which provides guidance for developing hybrid models. In order to address this gap, this paper contributes by proposing a conceptual framework for hybrid simulation for the healthcare domain.

Building Mic-Core, a Specialized M&S Software to Simulate Multi-State Demographic Micro Models, Based on JAMES II, a General M&S Framework

Often new modeling and simulation software is developed from scratch with no or only little reuse. The benefits that can be gained from developing a modeling and simulation environment by using (and thus reusing components of) a general modeling and simulation framework refer to reliability and efficiency of the developed software, which eventually contributes to the quality of simulation experiments. Developing the tool Mic-Core which supports continuous-time micro modeling and simulation in demography based on the plug-in-based modeling and simulation framework JAMES II will illuminate some of these benefits of reuse. Thereby, we will focus on the development process itself and on the quality of simulation studies, e.g., by analyzing the impact of random number generators on the reliability of results and of event queues on efficiency. The lessons learned summary presents a couple of insights gained by using a general purpose framework for M&S as a base to create a specialized M&S software.

Study of the response and photon-counting resolution of silicon photomultipliers using a generic simulation framework

We present a generic framework for the simulation of Silicon Photomultipliers (SiPMs) which enables detailed modelling of the SiPM response using basic SiPM parameters and geometry as an input. Depending on the specified SiPM properties which can be determined from basic characterisation measurements, the simulation generates the signal charge and pulse shape for arbitrary incident light pulse distributions.The simulation has been validated in the whole dynamic range for a Hamamatsu S10362-11-100C MPPC and was used to study the effect of different noise sources like optical cross-talk and after-pulsing on the response curve and the photon-counting resolution.

A general spectral method for the numerical simulation of one-dimensional interacting fermions

This software implements a general framework for the direct numerical simulation of systems of interacting fermions in one spatial dimension. The approach is based on a specially adapted nodal spectral Galerkin method, where the basis functions are constructed to obey the antisymmetry relations of fermionic wave functions. An efficient Matlab program for the assembly of the stiffness and potential matrices is presented, which exploits the combinatorial structure of the sparsity pattern arising from this discretization to achieve optimal run-time complexity. This program allows the accurate discretization of systems with multiple fermions subject to arbitrary potentials, e.g., for verifying the accuracy of multi-particle approximations such as Hartree–Fock in the few-particle limit. It can be used for eigenvalue computations or numerical solutions of the time-dependent Schrödinger equation.The new version includes a Python implementation of the presented approach. New version program summaryProgram title: assembleFermiMatrixCatalogue identifier: AEKO_v1_1Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKO_v1_1.htmlProgram obtainable from: CPC Program Library, Queenʼs University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 332No. of bytes in distributed program, including test data, etc.: 5418Distribution format: tar.gzProgramming language: MATLAB/GNU Octave, PythonComputer: Any architecture supported by MATLAB, GNU Octave or PythonOperating system: Any supported by MATLAB, GNU Octave or PythonRAM: Depends on the dataClassification: 4.3, 2.2.External routines: Python 2.7+, NumPy 1.3+, SciPy 0.10+Catalogue identifier of previous version: AEKO_v1_0Journal reference of previous version: Comput. Phys. Commun. 183 (2012) 405Does the new version supersede the previous version?: YesNature of problem: The direct numerical solution of the multi-particle one-dimensional Schrödinger equation in a quantum well is challenging due to the exponential growth in the number of degrees of freedom with increasing particles.Solution method: A nodal spectral Galerkin scheme is used where the basis functions are constructed to obey the antisymmetry relations of the fermionic wave function. The assembly of these matrices is performed efficiently by exploiting the combinatorial structure of the sparsity patterns.Reasons for new version: A Python implementation is now included.Summary of revisions: Added a Python implementation; small documentation fixes in Matlab implementation. No change in features of the package.Restrictions: Only one-dimensional computational domains with homogeneous Dirichlet or periodic boundary conditions are supported.Running time: Seconds to minutes.

A General Simulation Framework Based on CAN Bus for Satellite Design

The running status of a satellite can be imitated realistically through the use of an interactive simulation system, in which actual hardware can join for testing and validation. To solve the problem of interfaces and communications between different members in a satellite simulation system, an on-board interactive simulation system based on CAN bus is established. Several simulation members are built according to the composition of real system. Interfaces of drivers included in simulation members are packaged into a uniform interface, thus the on-board simulation system is established with the foundation of CAN bus simulation framework. Uniform communication interface of each simulation member is designed and realized, the framework of simulation flow is established, and foundation of intercommunion and operation between simulation members is laid. Experiment results prove that the framework can work stably with great efficiency and high flexibility, and expected effect is achieved.

Evaluation of Runtime Task Mapping Using the rSesame Framework

Performing runtime evaluation together with design time exploration enables a system to be more efficient in terms of various design constraints, such as performance, chip area, and power consumption. rSesame is a generic modeling and simulation framework, which can explore and evaluate reconfigurable systems at both design time and runtime. In this paper, we use the rSesame framework to perform a thorough evaluation (at design time and at runtime) of various task mapping heuristics from the state of the art. An extended Motion-JPEG (MJPEG) application is mapped, using the different heuristics, on a reconfigurable architecture, where different Field Programmable Gate Array (FPGA) resources and various nonfunctional design parameters, such as the execution time, the number of reconfigurations, the area usage, reusability efficiency, and other parameters, are taken into consideration. The experimental results suggest that such an extensive evaluation can provide a useful insight both into the characteristics of the reconfigurable architecture and on the efficiency of the task mapping.

CFD simulation for pedestrian wind comfort and wind safety in urban areas: General decision framework and case study for the Eindhoven University campus

Wind comfort and wind safety for pedestrians are important requirements in urban areas. Many city authorities request studies of pedestrian wind comfort and wind safety for new buildings and new urban areas. These studies involve combining statistical meteorological data, aerodynamic information and criteria for wind comfort and wind safety. Detailed aerodynamic information can be obtained using Computational Fluid Dynamics (CFD), which offers considerable advantages compared to wind tunnel testing. However, the accuracy and reliability of CFD simulations can easily be compromised. For this reason, several sets of best practice guidelines have been developed in the past decades. Based on these guidelines, this paper presents a general simulation and decision framework for the evaluation of pedestrian wind comfort and wind safety in urban areas with CFD. As a case study, pedestrian wind comfort and safety at the campus of Eindhoven University of Technology are analysed. The turbulent wind flow pattern over the campus terrain is obtained by solving the 3D steady Reynolds-averaged Navier–Stokes equations with the realisable k– ε model on an extensive high-resolution grid based on grid-convergence analysis. The simulation results are compared with long-term and short-term on-site wind speed measurements. Wind comfort and wind safety are assessed and potential design improvements are evaluated. The framework and the case study are intended to support and guide future studies of wind comfort and wind safety with CFD and, this way, to contribute to improved wind environmental quality in urban areas.

A general spectral method for the numerical simulation of one-dimensional interacting fermions

This work introduces a general framework for the direct numerical simulation of systems of interacting fermions in one spatial dimension. The approach is based on a specially adapted nodal spectral Galerkin method, where the basis functions are constructed to obey the antisymmetry relations of fermionic wave functions. An efficient Matlab program for the assembly of the stiffness and potential matrices is presented, which exploits the combinatorial structure of the sparsity pattern arising from this discretization to achieve optimal run-time complexity. This program allows the accurate discretization of systems with multiple fermions subject to arbitrary potentials, e.g., for verifying the accuracy of multi-particle approximations such as Hartree–Fock in the few-particle limit. It can be used for eigenvalue computations or numerical solutions of the time-dependent Schrödinger equation. Program summary Program title: assembleFermiMatrix Catalogue identifier: AEKO_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEKO_v1_0.html Program obtainable from: CPC Program Library, Queenʼs University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 102 No. of bytes in distributed program, including test data, etc.: 2294 Distribution format: tar.gz Programming language: MATLAB Computer: Any architecture supported by MATLAB Operating system: Any supported by MATLAB; tested under Linux (x86-64) and Mac OS X (10.6) RAM: Depends on the data Classification: 4.3, 2.2 Nature of problem: The direct numerical solution of the multi-particle one-dimensional Schrödinger equation in a quantum well is challenging due to the exponential growth in the number of degrees of freedom with increasing particles. Solution method: A nodal spectral Galerkin scheme is used where the basis functions are constructed to obey the antisymmetry relations of the fermionic wave function. The assembly of these matrices is performed efficiently by exploiting the combinatorial structure of the sparsity patterns. Restrictions: Only one-dimensional computational domains with homogeneous Dirichlet or periodic boundary conditions are supported. Running time: Seconds to minutes

From a Model of Lossy Flared Pipes to a General Framework for Simulation of Waveguides

This paper deals with the theory and application of waveguide modeling of lossy flared acoustic pipes, relying on the Webster-Lokshin equation. This model describes the propagation of longitudinal waves in axisymmetric acoustic pipes with a varying cross-section, visco-thermal losses at the walls, and without assuming planar waves or spherical waves. Solving this model for a piece of pipe leads to a two-port system made of four transfer functions which mimic the global acoustic effects. Moreover, introducing some relevant physical interpretations makes it possible to separate elementary effects due to the geometry of the piece of pipe (section, slope, and curvature) and isolate corresponding elementary transfer functions. From this decomposition a framework is obtained which allows to recover some digital waveguide models introduced earlier in the literature. This work contributes to the standardization of some different waveguide models, and brings a higher level of refinement that is visco-thermal losses combined with curvature effects.

A General Framework for Numerical Simulation of Improvised Explosive Device (IED)-Detection Scenarios Using Density Functional Theory (DFT) and Terahertz (THz) Spectra

We have developed a general framework for numerical simulation of various types of scenarios that can occur for the detection of improvised explosive devices (IEDs) through the use of excitation using incident electromagnetic waves. A central component model of this framework is an S-matrix representation of a multilayered composite material system. Each layer of the system is characterized by an average thickness and an effective electric permittivity function. The outputs of this component are the reflectivity and the transmissivity as functions of frequency and angle of the incident electromagnetic wave. The input of the component is a parameterized analytic-function representation of the electric permittivity as a function of frequency, which is provided by another component model of the framework. The permittivity function is constructed by fitting response spectra calculated using density functional theory (DFT) and parameter adjustment according to any additional information that may be available, e.g., experimentally measured spectra or theory-based assumptions concerning spectral features. A prototype simulation is described that considers response characteristics for THz excitation of the high explosive β-HMX. This prototype simulation includes a description of a procedure for calculating response spectra using DFT as input to the Smatrix model. For this purpose, the DFT software NRLMOL was adopted.

Finite element analysis of incrementally formed parts

Single point incremental forming (SPIF) processes represent a breakpoint from traditional forming processes, and possibly a new era in small batches production, customised parts or rapid prototyping. Given its easy implementation, SPIF is being currently a subject of intensive experimental and numerical research. Consequently, dimensional inaccuracy in formed parts is still a real problem to tackle, demanding a correct prediction of forming forces, springback defects and strain path effects. This work concerns a first step of a detailed numerical study, validated with available experimental results in the literature raised about simulation of SPIF processes. To this end, it is proposed a general simulation framework of SPIF processes using the finite element method with implicit solution schemes, along with innovative solid-shell elements for 3D analysis. Finally, the use of solid-shell elements provides several advantages compared to shell elements, as considering automatically full 3D stress states and constitutive laws, thickness variations, double sided contact and normal stresses.

Proper Generalized Decompositions and Separated Representations for the Numerical Solution of High Dimensional Stochastic Problems

Uncertainty quantification and propagation in physical systems appear as a critical path for the improvement of the prediction of their response. Galerkin-type spectral stochastic methods provide a general framework for the numerical simulation of physical models driven by stochastic partial differential equations. The response is searched in a tensor product space, which is the product of deterministic and stochastic approximation spaces. The computation of the approximate solution requires the solution of a very high dimensional problem, whose calculation costs are generally prohibitive. Recently, a model reduction technique, named Generalized Spectral Decomposition method, has been proposed in order to reduce these costs. This method belongs to the family of Proper Generalized Decomposition methods. It takes part of the tensor product structure of the solution function space and allows the a priori construction of a quasi optimal separated representation of the solution, which has quite the same convergence properties as a posteriori Hilbert Karhunen-Loeve decompositions. The associated algorithms only require the solution of a few deterministic problems and a few stochastic problems on deterministic reduced basis (algebraic stochastic equations), these problems being uncoupled. However, this method does not circumvent the “curse of dimensionality” which is associated with the dramatic increase in the dimension of stochastic approximation spaces, when dealing with high stochastic dimension. In this paper, we propose a marriage between the Generalized Spectral Decomposition algorithms and a separated representation methodology, which exploits the tensor product structure of stochastic functions spaces. An efficient algorithm is proposed for the a priori construction of separated representations of square integrable vector-valued functions defined on a high-dimensional probability space, which are the solutions of systems of stochastic algebraic equations.

Comprehensive modeling of optoelectronic nanostructures

This paper gives an overview of physics-based modeling of optoelectronic nanostructures, driven by diverse applications such as photovoltaics, solid-state lighting, communications and sensing. Despite this broad field of applications, some common challenges can be identified: accurate modeling of light-matter interaction, semi-coherent carrier transport in the presence of strong recombination, calculation of material properties and electromagnetic characteristics. In this contribution, the general purpose simulation framework tdkp/AQUA/LUMI is presented, with the focus on non-planar nanowire devices.

Simulation in Emergent Computational Systems.

Simulation in Emergent Computational Systems.

The MIT beer game as multiagent simulation: a practical approach using AOR-modelling and an XML-based implementation framework

This paper deals with a synthesis of theoretical and conceptual work on an MAS-model of the MIT beer game, known from the paper where it was first formulated (Luin et al., 2004), with the implementation of a general simulation framework, called absimulation, given in Raffel's (2005) work. The first goal of this study was to make the authors and the intended audience acquainted with issues that arise within processes such as MAS modelling and peculiarities of MAS implementation techniques. Though comparatively much work is associated here with the concrete case of a model of the particular supply chain management game, it was attempted to discuss much more general MAS-related problems, whenever the given implementation offered the opportunity for such a discussion.