Topic
Modeling and simulation
About: Modeling and simulation is a research topic. Over the lifetime, 10273 publications have been published within this topic receiving 111550 citations.
Papers published on a yearly basis
Papers
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TL;DR: An integrated framework for agent-based inventory–production–transportation modeling and distributed simulation of supply chains with strong flexibility in multiple layers, multiple granularities, reusability, and scalability in simulation modeling is proposed.
82 citations
TL;DR: In this article, the authors present a new approach to predictive filtering based on a process called "quantization", which abstracts a sender model into a DEVS representation and provides an alternative, efficient approach to embedding continuous models within distributed discrete event simulations.
Abstract: In the context of a DARPA ASTT project, we are developing an HLA-compliant distributed simulation environment based on the DEVS formalism. This environment will provide a user- friendly, high-level tool-set for developing interoperable discrete and continuous simulation models. One application is the study of contract-based predictive filtering. This paper presents a new approach to predictive filtering based on a process called 'quantization' to reduce state update transmission. Quantization, which generates state updates only at quantum level crossings, abstracts a sender model into a DEVS representation. This affords an alternative, efficient approach to embedding continuous models within distributed discrete event simulations. Applications of quantization to message traffic reduction are discussed. The theory has been validated by DEVSJAVA simulations of test cases. It will be subject to further test in actual distributed simulations using the DEVS/HLA modeling and simulation environment.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
82 citations
01 Feb 1999
TL;DR: An overview of a design environment for alternative powertrains that has modularity, allowing a system to be built by combining components; flexibility, allowing different levels of fidelity and different existing codes to be used; and, rigor, since it is based an mathematical methods of decision making is provided.
Abstract: Alternative powertrains for automotive applications aim at improving emissions and fuel economy. Lack of experience with these relatively new technologies makes them ideal applications for computer-based modeling and simulation studies. There is a variety of configurations, control strategies, and design variable choices that can be made. If mathematical models exist, rigorous optimization techniques can be used to explore the design space. This paper provides an overview of a design environment for alternative powertrains that has these characteristics: modularity, allowing a system to be built by combining components; flexibility allowing different levels of fidelity and different existing codes to be used; and, rigor, since it is based an mathematical methods of decision making. A simple application to a hybrid diesel-electric powertrain is included.
81 citations
TL;DR: This paper surveys the most significant simulation models for wireless signal propagation, dedicated short-range communication technologies, and vehicular mobility and provides handy hints and references to help determine the most appropriate tools and models.
81 citations
05 Oct 2015
TL;DR: In this article, the authors report on the state of the art in power hardware in the loop (PHIL) and its challenges and present sample case studies illustrating the impact of PHIL.
Abstract: The area of modeling and simulation is a critical aspect in the basic research to commercialization and instantiation cycle. This paper reports on modeling and simulation in the context of verification, validation, and experimentation of power and energy systems and associated electrical apparatus via the utilization of power hardware in the loop (PHIL)-based strategies. PHIL is a powerful technique for testing and demonstration of systems in a rigorous and dynamic manner that is not achievable with other methodologies; however, it must only be conducted with foreknowledge of the technique and its challenges in order to realize its significant benefits. This paper reports on the state of the art in PHIL and its challenges and presents sample case studies illustrating its impact.
81 citations