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.
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TL;DR: The long-term aim of this research is to develop a collaborative modeling and simulation platform, which will provide an integrated environment for multi-disciplinary teams to create, share, and integrate simulation services on the Internet.
30 citations
Proceedings Article•
20 Aug 2000TL;DR: A method is described that is able to deal with large and complex systems, and its performance in simulation experiments with random regulatory networks is discussed.
Abstract: Modeling and simulation techniques developed within qualitative reasoning might be profitably used for the analysis of genetic regulatory systems. A major problem with current qualitative simulation techniques is their lack of upscalability. We describe a method that is able to deal with large and complex systems, and discuss its performance in simulation experiments with random regulatory networks.
30 citations
03 Mar 2003
30 citations
TL;DR: In this article, an analytical model for the simulation of traction drive dynamics and control in ratio change processes is presented, which is implemented in Matlab/Simulink block diagrams and is capable of predicting traction drive performances under various ratio change conditions.
Abstract: This paper presents an analytical model for the simulation of traction drive dynamics and control in ratio change processes. The model systematically incorporates the formulations on the kinematics, dynamics and control characteristics of traction drives. In the model, the motion parameters of traction drive components are coupled to CVT inputs and outputs, torque losses, as well as ratio variations. The characteristics of a dual-feedback ratio control system are formulated in Laplace transform and integrated into the overall CVT system. The model is implemented in Matlab/Simulink block diagrams and is capable of predicting traction drive performances under various ratio change conditions. The effectiveness of the model is illustrated in a numerical example by the comparison between the simulation and experimental data on key CVT performance parameters.
30 citations
01 Sep 2005
TL;DR: points of contact are increasing between security and simulation, particularly in several security evaluation areas, including: 1) impact assessment for determining how security measures affect system and application performance; 2) emulation, in which real and virtual worlds are combined to study the interaction between malware and systems.
Abstract: Digital computers' earliest applications evaluated models of physical systems to predict their behavior under controlled conditions. To do this, they used simulation, computing changes to the models' state variables as a function of time. Since then, simulation has become fundamental to computer science. Developments in security have their roots elsewhere, but points of contact are increasing between security and simulation, particularly in several security evaluation areas, including: 1) impact assessment for determining how security measures affect system and application performance; 2) emulation, in which real and virtual worlds are combined to study the interaction between malware and systems, and probe for new system weaknesses; 3) cyberattack exercises and training scenarios; and 4) risk assessment based on known vulnerabilities, exploits, attack capabilities, and system configuration.
30 citations