A Stochastic Bias Corrected Response Surface Method and its Application to Reliability-Based Design Optimization 2014-01-0731
In vehicle design, response surface model (RSM) is commonly used as a surrogate of the high fidelity Finite Element (FE) model to reduce the computational time and improve the efficiency of design process. However, RSM introduces additional sources of uncertainty, such as model bias, which largely affect the reliability and robustness of the prediction results. The bias of RSM need to be addressed before the model is ready for extrapolation and design optimization. This paper further investigates the Bayesian inference based model extrapolation method which is previously proposed by the authors, and provides a systematic and integrated stochastic bias corrected model extrapolation and robustness design process under uncertainty. A real world vehicle design example is used to demonstrate the validity of the proposed method.
Citation: Zhan, Z., Fu, Y., and Yang, R., "A Stochastic Bias Corrected Response Surface Method and its Application to Reliability-Based Design Optimization," SAE Int. J. Mater. Manf. 7(2):262-268, 2014, https://doi.org/10.4271/2014-01-0731. Download Citation
Author(s):
Zhenfei Zhan, Yan Fu, Ren-Jye Yang
Affiliated:
Chongqing Univ., Ford Motor Co.
Pages: 7
Event:
SAE 2014 World Congress & Exhibition
ISSN:
1946-3979
e-ISSN:
1946-3987
Also in:
SAE International Journal of Materials and Manufacturing-V123-5, SAE International Journal of Materials and Manufacturing-V123-5EJ
Related Topics:
Design processes
Computer simulation
Optimization
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