Multi-fidelity modeling & simulation methodology for simulation speed up

S. Choi, Sun Ju Lee, T. Kim
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引用次数: 15

Abstract

M&S-based analysis has been performed for simulation experiments of all possible input combinations as a 'what-if' analysis causing the simulation to be extremely time-consuming. To resolve this problem, this paper proposes a multi-fidelity M&S methodology for enhancing simulation speed while minimizing accuracy loss and maximizing model reusability, in the M&S-based analysis. Target systems of this methodology are continuous and discrete event system. The proposed multi-fidelity M&S methodology consists of 4 steps: 1) target model selection and Interest Region definition, 2) low-fidelity model development, 3) multi-fidelity model composition, 4) selected target model substitution. Also this methodology proposes structure of multi-fidelity model and its mathematical specifications for the third step. This methodology is applied without any modification of existing models and simulation engine for maximizing model reusability. Case study applies this methodology to Torpedo Tactics Simulation model and the Vehicle Allocation Simulation model. The result shows that simulation speed increases at least 1.21 times with 5% accuracy loss. We expect that this methodology will be applicable in various M&S-based analysis for enhancing simulation speed.
提高仿真速度的多保真建模与仿真方法
基于m&s的分析已经对所有可能的输入组合进行了模拟实验,作为“假设”分析,导致模拟非常耗时。为了解决这一问题,本文提出了一种多保真度M&S方法,在基于M&S的分析中提高仿真速度,同时最小化精度损失和最大化模型可重用性。该方法的目标系统是连续事件系统和离散事件系统。本文提出的多保真度M&S方法包括4个步骤:1)目标模型选择和兴趣区域定义,2)低保真度模型开发,3)多保真度模型组成,4)选定目标模型替换。该方法还提出了多保真度模型的结构及其第三步的数学规范。该方法的应用不需要对现有模型和仿真引擎进行任何修改,以最大限度地提高模型的可重用性。实例研究将该方法应用于鱼雷战术仿真模型和车辆分配仿真模型。结果表明,在精度损失5%的情况下,仿真速度提高了至少1.21倍。我们期望该方法能够应用于各种基于m&s的分析,以提高仿真速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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