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Structural and Multidisciplinary Optimization

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24.01.2019 | Industrial Application

Gauge sensitivity analysis and optimization of the modular automotive body with different loadings

verfasst von: Yu Liu, Zijian Liu, Haolong Zhong, Huan Qin, Cheng Lv

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 1/2019

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Abstract

The structural optimization method based on sensitivity analysis is an effective way to reduce the mass of automotive body structure. In this paper, an effective structural optimization method is proposed to facilitate the lightweight design of modular automotive body, where gauge sensitivity analysis values are used to determine the optimized direction to increase or decrease the thickness of each beam element in the body model. An object-oriented MATLAB toolbox constructed in our previous study is adopted as a black box for the structural analysis and optimization of the body-in-white (BIW) model, in which the beam element sensitivity values of BIW structure under different loading conditions are fast calculated by the method of reverberation ray matrix (MRRM) and the finite difference method (FDM). Then, the optimized direction of each beam element is identified, and a structural optimization model is formulated and solved by the genetic algorithm (GA). In order to verify the effectiveness of this method, a simplified modular automotive body model is constructed to implement the performance indexes comparison between the initial body model and optimized body model. The analysis results show that this method is feasible and effective for the optimal design of modular automotive body structure.

Vorheriger Artikel RBF surrogate model and EN1317 collision safety-based optimization of two guardrails

Nächster Artikel Improved reliability-based design optimization of non-uniformly stiffened spherical dome

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Titel: Gauge sensitivity analysis and optimization of the modular automotive body with different loadings
verfasst von: Yu Liu
Zijian Liu
Haolong Zhong
Huan Qin
Cheng Lv
Publikationsdatum: 24.01.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Structural and Multidisciplinary Optimization / Ausgabe 1/2019
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI: https://doi.org/10.1007/s00158-019-02202-0

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