期刊
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
卷 273, 期 -, 页码 204-218出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2014.01.018
关键词
Robust topology optimization; Loading uncertainty; Monte Carlo; Orthogonal diagonalization
资金
- State Key Laboratory of Virtual Reality Technology and Systems (Beihang University)
This paper proposes an efficient approach to solving robust topology optimization problem of structures under loading uncertainty. The objective is to minimize a weighted sum of the mean and standard deviation of structural compliance. Loading uncertainties can be in either concentrated loads or uniformly distributed loads. By exploiting of the linear elastic nature of structure, Monte Carlo sampling is completely separated from the topology optimization process, thus accurate calculation of objective function becomes possible. Efficient sensitivity analysis method is developed and its computational cost is only linearly proportional to the number of uncertain loads. The sensitivity analysis is also integrated into the density based topology optimization approach to solve the robust topology optimization problems. The numerical examples demonstrate the effectiveness of the proposed approach. The effect of uncertainty level, probability distribution of uncertainty and different influence of loading magnitude and directional uncertainty on the robust designs are also shown by the numerical examples. (C) 2014 Elsevier B.V. All rights reserved.
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