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Multi-scale robust design and optimization considering load uncertainties

delete2015-01-01
delete114
PRE
AI
郭
郭旭 (Xu Guo) *
X
Xiaofang Zhao
张
张维声 (Weisheng Zhang)
阎军 封面图
阎军 (Jun Yan)
G
Guomin Sun
DOI:10.1016/j.cma.2014.10.014delete
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摘要

摘要

En 中文
Uncertainty is ubiquitous in practical engineering design applications. Recent years have witnessed a growing research interest in the study of structural topology optimization problems considering uncertainties. Most of these works, however, are focused on the optimization of macro-scale structures. In the present paper, robust concurrent optimization of material and structure under unknown-but-bounded load uncertainties is investigated in a multi-scale framework. Problem formulation that can allow for the effect of worst-case scenario in a confidence way and the corresponding numerical solution procedure are proposed. It is found that when load uncertainties are considered, optimal material distributions in microstructures tend to be isotropic and Kagome structure seems to be superior to other forms of microstructures. The conclusions drawn from the present work are helpful for manufacturing hierarchical structures with Additive Manufacturing technologies. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Multi-scale design and optimization
Load uncertainties
Confidence robust optimization formulation
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期刊

Computer Methods in Applied Mechanics and Engineering 封面图
Computer Methods in Applied Mechanics and Engineering
IF:
7.3
论文数:
1.3W
被引数:
5.6W

机构

D
dalian university of technology
学者数:
4.6K
论文数: 1.3K
被引数: 0
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