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Research Papers

Inverse Simulation Under Uncertainty by Optimization

[+] Author and Article Information
Xiaoping Du

Department of Mechanical and Aerospace Engineering,
Missouri University of Science and Technology,
400 West 13th Street,
Toomey Hall 290D,
Rolla, MO 65409
e-mail: dux@mst.edu

Contributed by the Computers and Information Division of ASME for publication in the Journal of Computing and Information Science in Engineering. Manuscript received April 29, 2012; final manuscript received February 6, 2013; published online April 22, 2013. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 13(2), 021005 (Apr 22, 2013) (8 pages) Paper No: JCISE-12-1071; doi: 10.1115/1.4023859 History: Received April 29, 2012; Revised February 06, 2013

Inverse simulation is an inverse process of a direct simulation. During the process, unknown simulation input variables are identified for a given set of known simulation output variables. Uncertainties such as random parameters may exist in engineering applications of inverse simulation. An optimization method is developed in this work to estimate the probability distributions of unknown input variables. The first order reliability method is employed and modified so that the inverse simulation is embedded within the reliability analysis. This treatment avoids the separate executions of reliability analysis and inverse simulation and consequently maintains high efficiency. In addition, the means and standard deviations of the unknown input variables can also be obtained. A particle impact problem is presented to demonstrate the proposed method for inverse simulation under uncertainty.

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Figures

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Fig. 1

A simulation model

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Fig. 2

Flow chart of inverse simulation

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Fig. 3

Double-loop procedure for inverse simulation under uncertainty

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Fig. 4

Single-loop procedure for inverse simulation under uncertainty

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Fig. 5

Impact of two rigid bodies

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Fig. 6

CDF of the velocity of body A before impact

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Fig. 7

CDF of the velocity of body B before impact

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