Xiaopeng Zhang
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Paper Publications
Robust topology optimization for dynamic compliance minimization under uncertain harmonic excitations with inhomogeneous eigenvalue analysis
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Indexed by:期刊论文

Date of Publication:2016-12-01

Journal:STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

Included Journals:SCIE、EI、Scopus

Volume:54

Issue:6,SI

Page Number:1469-1484

ISSN No.:1615-147X

Key Words:Robust topology optimization; Vibration; Load uncertainty; Dynamic compliance; Convex model; Inhomogeneous eigenvalue

Abstract:Variability of load magnitude/direction is a most significant source of uncertainties in practical engineering. This paper investigates robust topology optimization of structures subjected to uncertain dynamic excitations. The unknown-but-bounded dynamic loads/accelerations are described with the non-probabilistic ellipsoid convex model. The aim of the optimization problem is to minimize the absolute dynamic compliance for the worst-case loading condition. For this purpose, a generalized compliance matrix is defined to construct the objective function. To find the optimal structural layout under uncertain dynamic excitations, we first formulate the robust topology optimization problem into a nested double-loop one. Here, the inner-loop aims to seek the worst-case combination of the excitations (which depends on the current design, and is usually to be found by a global optimization algorithm), and the outer-loop optimizes the structural topology under the found worst-case excitation. To tackle the inherent difficulties associated with such an originally nested formulation, we convert the inner-loop into an inhomogeneous eigenvalue problem using the optimality condition. Thus the double-loop problem is reformulated into an equivalent single-loop one. This formulation ensures that the strictsense worst-case combination of the uncertain excitations for each intermediate design be located without resorting to a time-consuming global search algorithm. The sensitivity analysis of the worst-case objective function value is derived with the adjoint variable method, and then the optimization problem is solved by a gradient-based mathematical programming method. Numerical examples are presented to illustrate the effectiveness and efficiency of the proposed framework.

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Supervisor of Master's Candidates

Gender:Male

Alma Mater:Dalian University of Technology

Degree:Doctoral Degree

School/Department:Department of Engineering Mechanics

Discipline:Engineering Mechanics. Computational Mechanics

Business Address:Room 506,Comprehensive Experimental Building#1, DUT

Contact Information:Email: zhangxaiopeng@dlut.edu.cn

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