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Multidisciplinary design optimization on vehicle tailor rolled blank design

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TLDR
In this paper, the authors combine the advanced multidisciplinary design optimization (MDO) methodology to optimize vehicle structure by using uniform Latin hypercube sampling and subset selection regression methods to construct the response surface models for the highly nonlinear impact and seatbelt pull responses.
Abstract
Tailor rolled blank (TRB) is an emerging steel rolling process to produce lightweight vehicle components. It allows continuous metal thickness changes, and as a result, it offers opportunities for automotive design in weight reduction, part complexity reduction, reduced capital investment, yet, maintains equal to or better strength characteristics. The objective of this research is to take advantages of the TRB manufacturing technology and combine with the advanced multidisciplinary design optimization (MDO) methodology to optimize vehicle structure. The process begins with noise vibration and harshness (NVH) optimization. The outputs of the optimal NVH response sensitivities are employed to build the first order response surface models. Uniform Latin Hypercube sampling and subset selection regression methods are used to construct the response surface models for the highly nonlinear impact and seatbelt pull responses. The optimal NVH design is then used as the starting point for MDO to obtain the optimal thickness profiles for the TRB parts. A vehicle application considering multiple impact modes, seatbelt pulls, and NVH, is used to demonstrate the proposed process for vehicle underbody TRB design. Results of this MDO TRB study is presented and discussed.

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Citations
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Journal ArticleDOI

Subset Selection in Regression

TL;DR: Chapman and Miller as mentioned in this paper, Subset Selection in Regression (Monographs on Statistics and Applied Probability, no. 40, 1990) and Section 5.8.
Journal ArticleDOI

A review on tailored blanks—Production, applications and evaluation

TL;DR: The state of the art in scientific research concerning tailored blanks can be found in this article, where the authors present the potentials of the technology and chances for further scientific investigations.
Journal ArticleDOI

On design optimization for structural crashworthiness and its state of the art

TL;DR: A comprehensive review of the important studies on design optimization for structural crashworthiness and energy absorption is provided in this article, where the authors provide some conclusions and recommendations to enable academia and industry to become more aware of the available capabilities and recent developments in design optimization.
Journal ArticleDOI

A review on functionally graded structures and materials for energy absorption

TL;DR: In this article, the effects of the graded properties on their crashworthiness are discussed, and the authors demonstrate that thin-walled structures and cellular materials could exhibit more efficient and effective energy-absorbing performance by introducing graded properties.
Journal ArticleDOI

Axial crushing and optimal design of square tubes with graded thickness

TL;DR: In this paper, the deformation mode and energy absorption of square tubes with graded thickness during axial loading were investigated and the experimental and numerical results showed that the introduction of graded thickness in cross-section can lead to up to 30-35% increase in energy absorption efficiency (specific energy absorption) without the increase of the initial peak force.
References
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Journal ArticleDOI

A comparison of three methods for selecting values of input variables in the analysis of output from a computer code

TL;DR: In this paper, two sampling plans are examined as alternatives to simple random sampling in Monte Carlo studies and they are shown to be improvements over simple sampling with respect to variance for a class of estimators which includes the sample mean and the empirical distribution function.
Book

Subset Selection in Regression

TL;DR: In this paper, Efroymson's algorithm was used to replace two variables at a time with all subsets using branch-and-bound techniques. But the results showed that one subset was better than another.
Journal ArticleDOI

Subset Selection in Regression

TL;DR: Chapman and Miller as mentioned in this paper, Subset Selection in Regression (Monographs on Statistics and Applied Probability, no. 40, 1990) and Section 5.8.
Journal ArticleDOI

Uniform Design: Theory and Application

TL;DR: It is shown that UD's have many desirable properties for a wide variety of applications and the global optimization algorithm, threshold accepting, is used to generate UD's with low discrepancy.
Journal ArticleDOI

Subset Selection in Regression.

G. M. Raab, +1 more
- 01 Dec 1991 - 
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