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Research Papers

Probabilistic Inverse Simulation and Its Application in Vehicle Accident Reconstruction

[+] Author and Article Information
Xiaoyun Zhang

Associate Professor
School of Mechanical Engineering,
Shanghai Jiaotong University,
909 Mechanical Building,
800 Dong Chuan Road,
Shanghai 200240, China
e-mail: general_zhang@sjtu.edu.cn

Zhen Hu

Research Assistant
e-mail: zh4hd@mst.edu

Xiaoping Du

Associate Professor
e-mail: dux@mst.edu
Department of Mechanical
and Aerospace Engineering,
Missouri University of Science and Technology,
290D Toomey Hall,
400 West 13th Street,
Rolla, MO 65409-0500

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received March 25, 2013; final manuscript received August 19, 2013; published online September 19, 2013. Assoc. Editor: David Gorsich.

J. Mech. Des 135(12), 121006 (Sep 19, 2013) (10 pages) Paper No: MD-13-1135; doi: 10.1115/1.4025296 History: Received March 25, 2013; Revised August 19, 2013

Inverse simulation is an inverse process of direct simulation. It determines unknown input variables of the direct simulation for a given set of simulation output variables. Uncertainties usually exist, making it difficult to solve inverse simulation problems. The objective of this research is to account for uncertainties in inverse simulation in order to produce high confidence in simulation results. The major approach is the use of the maximum probability density function (PDF), which determines not only unknown deterministic input variables but also the realizations of random input variables. Both types of variables are solved on the condition that the joint probability density of all the random variables is maximum. The proposed methodology is applied to a traffic accident reconstruction problem where the simulation output (accident consequences) is known and the simulation input (velocities of the vehicle at the beginning of crash) is sought.

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References

Figures

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Fig. 1

A simulation model

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Fig. 2

Joint PDF of u1 and u2

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Fig. 5

3D simulation of the accident

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Fig. 6

Simulation parameters

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Fig. 7

Vehicle accident simulation

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Fig. 8

Pedestrian's injury and deformation of vehicle body

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Fig. 10

Lateral Torque of the pedestrian's lower limbs

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Fig. 9

Acceleration of the pedestrian's head

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