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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2015, Vol. 36 ›› Issue (8): 2681-2687.doi: 10.7527/S1000-6893.2015.0105

• Solid Mechanics and Vehicle Conceptual Design • Previous Articles     Next Articles

Topology optimization of flexible support structure for trailing edge

JIN Dongping, JI Bin   

  1. State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2015-04-09 Revised:2015-04-13 Online:2015-08-15 Published:2015-04-27
  • Contact: 10.7527/S1000-6893.2015.0105 E-mail:jindp@nuaa.edu.cn
  • Supported by:

    National Natural Science Foundation of China (91016022); Priority Academic Program Development of Jiangsu Higher Education Institutions

Abstract:

Non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) with connectivity analysis is employed for the multi-objective topology optimization of the flexible support structure for morphing trailing edge, in which bit-matrix is used as the representation of a chromosome. Starting with the analysis of optimization target of the flexible support structure for trailing edge, the objective functions of multi-objective topology optimization are established. In order to improve the efficiency and make the optimization results better, the connectivity analysis and similar individual filter are put forward. The objectives such as mass, performances of deformation and load bearing ability of the feasible individuals are obtained by finite element analysis (FEA) using ANSYS, and the bit-matrix-based NSGA-Ⅱ is realized in MATLAB by penalizing the infeasible individuals. Subsequently, the feasible configurations of the support structure are obtained. The results show that the bit-matrix-based NSGA-Ⅱ with the connectivity analysis and similar individual filter can provide feasible and effective solutions for multi-objective topology optimization of the flexible support structure for morphing trailing edge.

Key words: flexible structure, trailing edge, topology optimization, genetic algorithms, multi-objective optimization

CLC Number: