Collaborative optimization of discrete structures based on a substructuring method
ZHONG Wei1, SU Ruiyi2, GUI Liangjin1, FAN Zijie1
1. State Key Laboratory of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing 100084, China;
2. Beijing System Design Institute of Electromechanical Engineering, Beijing 100854, China
Abstract：A decomposition strategy based on substructuring is developed for optimizing complex discrete structures with a large number of design variables and a collaborative architecture is used as the solver. A large structure is decomposed into several small substructures with no overlap, where each substructure corresponds to a discipline. The variables, objectives and constraints in the original problem are assigned to the separate disciplines. Only one finite element analysis of the complete structure is performed at the system level during each iteration with optimization and finite element analyses of the substructures at the discipline levels. Coupled state variables are passed from the system level to the disciplines as constants. The coupled state variables are updated after each finite element analysis of the complete structure at the system level to coordinate the differences in the coupled state variables among disciplines. Thus, a complex structural optimization problem is decomposed into several parallel, self-governed subproblems. The results of numerical examples demonstrate that this cooperative optimization method requires less evaluations of the complete structure and is able to obtain better results with better stability than optimizing the complete structure as a whole.
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