Reliability-based robust design optimization using the eigenvector dimension reduction (EDR) method

2008 ◽  
Vol 37 (5) ◽  
pp. 475-492 ◽  
Author(s):  
Byeng D. Youn ◽  
Zhimin Xi
Keyword(s):  
Dimension Reduction ◽  
Design Optimization ◽  
Robust Design ◽  
Robust Design Optimization ◽  
Eigenvector Dimension Reduction

Dimension reduction method for reliability-based robust design optimization

2008 ◽  
Vol 86 (13-14) ◽  
pp. 1550-1562 ◽  
Author(s):  
Ikjin Lee ◽  
K.K. Choi ◽  
Liu Du ◽  
David Gorsich
Keyword(s):  
Dimension Reduction ◽  
Design Optimization ◽  
Robust Design ◽  
Reduction Method ◽  
Robust Design Optimization ◽  
Dimension Reduction Method

Sensitivity-Free Approach for Reliability-Based Robust Design Optimization

2007 ◽  
Author(s):  
Byeng D. Youn ◽  
Zhimin Xi ◽  
Lee J. Wells ◽  
David J. Gorsich
Keyword(s):  
Design Optimization ◽  
Robust Design ◽  
Free Probability ◽  
Probability Analysis ◽  
Side Impact ◽  
Robust Design Optimization ◽  
Analysis Method ◽  
Reliability Method ◽  
Lower Control Arm ◽  
Eigenvector Dimension Reduction

This paper attempts to integrate a derivative-free probability analysis method to Reliability-Based Robust Design Optimization (RBRDO). The Eigenvector Dimension Reduction (EDR) method is used for the probability analysis method. It has been demonstrated that the EDR method is more accurate and efficient than the Second-Order Reliability Method (SORM) for reliability and quality assessment. Moreover, it can simultaneously evaluate both reliability and quality without any extra expense. Three practical engineering problems (vehicle side impact, layered bonding plates, and lower control arm) are used to demonstrate the effectiveness of the EDR method.

Robust Design Optimization for Crashworthiness of Vehicle Side Impact

2017 ◽  
Vol 3 (3) ◽  
Author(s):  
Souvik Chakraborty ◽  
Tanmoy Chatterjee ◽  
Rajib Chowdhury ◽  
Sondipon Adhikari
Keyword(s):  
Design Optimization ◽  
New Product Development ◽  
Robust Design ◽  
Automobile Industry ◽  
Human Error ◽  
Differential Evolution Algorithm ◽  
Side Impact ◽  
Robust Design Optimization ◽  
Parameter Uncertainties ◽  
Design Engineers

Optimization for crashworthiness is of vast importance in automobile industry. Recent advancement in computational prowess has enabled researchers and design engineers to address vehicle crashworthiness, resulting in reduction of cost and time for new product development. However, a deterministic optimum design often resides at the boundary of failure domain, leaving little or no room for modeling imperfections, parameter uncertainties, and/or human error. In this study, an operational model-based robust design optimization (RDO) scheme has been developed for designing crashworthiness of vehicle against side impact. Within this framework, differential evolution algorithm (DEA) has been coupled with polynomial correlated function expansion (PCFE). An adaptive framework for determining the optimum basis order in PCFE has also been presented. It is argued that the coupled DEA–PCFE is more efficient and accurate, as compared to conventional techniques. For RDO of vehicle against side impact, minimization of the weight and lower rib deflection of the vehicle are considered to be the primary design objectives. Case studies by providing various emphases on the two objectives have also been performed. For all the cases, DEA–PCFE is found to yield highly accurate results.

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