Abstract #301678

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JSM 2002 Abstract #301678
Activity Number: 143
Type: Topic Contributed
Date/Time: Monday, August 12, 2002 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #301678
Title: A New Algorithm for Stochastic Programming for Vehicle Crashworthiness of Side Impact
Author(s): Yan Fu+ and Ren-Jye Yang and Steve Kang and Urmila Diwekar and Kemal Sahin*
Affiliation(s): Ford Motor Company and Ford Motor Company and Ford Motor Company and Carnegie Mellon University and Carnegie Mellon University
Address: 2101 Village Road, MD 2115, SRL, Dearborn, Michigan, 48124, U.S.A.
Keywords: Stochastic programming ; Nonlinear Programming ; Optimization under uncertainty
Abstract:

This paper presents an application of a new algorithm for stochastic programming to the vehicle design for side impact. A nonlinear response surface-based model is used to construct the "efficient-to-compute" surrogate model. The main goal is to enhance vehicle-side impact crash performance while minimizing vehicle weight under various uncertain impacts. The new nonlinear programming algorithm avoids the computational burden of excessive model evaluations for determining the search direction through a reweighting method. The efficiency of this algorithm is presented through a real-world vehicle safety design problem.

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Revised March 2002