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Development of a Stochastic Approach for Vehicle FE Models

[+] Author Affiliations
David Riha

Southwest Research Institute, San Antonio, TX

Joseph Hassan, Marlon Forrest, Ke Ding

DaimlerChrysler Corporation, Auburn Hills, MI

Paper No. IMECE2003-55107, pp. 37-69; 33 pages
  • ASME 2003 International Mechanical Engineering Congress and Exposition
  • Transportation: Making Tracks for Tomorrow’s Transportation
  • Washington, DC, USA, November 15–21, 2003
  • Conference Sponsors: Transportation
  • ISBN: 0-7918-3730-0 | eISBN: 0-7918-4663-6, 0-7918-4664-4, 0-7918-4665-2
  • Copyright © 2003 by ASME


This paper describes the development of a mathematical model capable of providing realistic simulations of vehicle crashes by accounting for uncertainty in the model input parameters. The approach taken was to couple advanced and efficient probabilistic and reliability analysis methods with well-established, high fidelity finite element and occupant modeling software. Southwest Research Institute has developed probabilistic analysis software called NESSUS. This code was used as the framework for a stochastic crashworthiness FE model. The LS-DYNA finite element model of vehicle frontal offset impact and the MADYMO model of a 50th percentile male Hybrid III dummy were integrated with NESSUS to comprise the crashworthiness characteristics. The system reliability of the vehicle is computed by defining ten acceptance criteria performance functions; four occupant injury criteria and six compartment intrusion criteria. The reliability for each acceptance criteria was computed using NESSUS to identify the dominant acceptance criteria of the original design. The femur axial load acceptance criteria event has the lowest reliability (46%) followed by the HIC event (58%) and the door aperture closure event (73%). One approach to improve the reliability is to change vehicle parameters to improve the reliability for the dominant criteria. However, a parameter change such as vehicle strength/stiffness may have a beneficial effect on certain acceptance criteria but be detrimental to others. A system reliability analysis was used to include the contribution of all acceptance criteria to correctly quantify the vehicle reliability and identify important parameters. A redesign analysis was performed using the computed probabilistic sensitivity factors. These sensitivities were used to identify the most effective changes in model parameters to improve the reliability. A redesign using 11 design modifications was performed that increased the original reliability from 23% to 86%. Several of the design changes include increasing the rail material yield strength and reducing its variation, reducing the variation of the bumper and rail installation tolerances, and increasing the rail weld stiffness and reducing its variation. The results show that major reliability improvements for occupant injury and compartment intrusion can be realized by certain specific modifications to the model input parameters. A traditional (deterministic) method of analysis would not have suggested these modifications.

Copyright © 2003 by ASME



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