2014Unpublished venueRequires access

Multi-fidelity modeling & simulation methodology for simulation speed up

Seon Han Choi, Sun Ju Lee, Tag Gon Kim

Open publisher page 12 citations

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.

About this research paper

What this paper is about

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.

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Available 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.

Key concepts: Fidelity, Reusability, Computer science, Discrete event simulation, High fidelity, Modeling and simulation, Simulation modeling, Speedup

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