• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2026, Vol. 62 ›› Issue (15): 195-220.doi: 10.3901/JME.260619

Previous Articles    

Review and Case Study of Structural Optimization Design of Large-aperture Mirrors

GUO Guanchen1,2, LIANG Pengwei3, PANG Yong1,2, LI Yanting1,2, SONG Xueguan1,2   

  1. 1. School of Mechanical Engineering, Dalian University of Technology, Dalian 116024;
    2. State Key Laboratory High-Performance Precision Manufacturing, Dalian University of Technology, Dalian 116024;
    3. Laser Fusion Research Center, China Academy of Engineering Physics, Mianyang 621900
  • Received:2025-08-20 Revised:2026-01-16 Published:2026-10-13

Abstract: With the increasing demand for improving the performance of large-aperture mirrors, it becomes crucial to efficiently achieve collaborative optimization of multiple components of the mirror system under the coupling effect of multiple physical fields. The optimization design of large-aperture mirrors and their supporting structures is reviewed in this study. First, the existing design and optimization analysis methods of large-aperture mirror components are reviewed, including the first-order design stage, topology optimization, sensitivity analysis, parameter optimization, and traditional surrogate model optimization methods, with a summary provided on the current optimization design framework for mirrors and their supporting structures. Secondly, the surrogate model-assisted optimization technology is applied to supplement the defects of the existing framework in solving high-dimensional collaborative optimization problems. Finally, an engineering example is used to demonstrate the effectiveness of surrogate model-assisted optimization in the optimization design of high-dimensional multi-objective problems of mirrors and their supporting components. The optimization results show that compared with the first-order design, this method can achieve the coordinated optimization of 45 parameters under dual-temperature conditions, and the RMS values are reduced by 73.32% and 82.28% respectively; compared with the traditional optimization method, this method reduces the optimization time by two orders of magnitude; compared with the traditional proxy model optimization method, this method requires less training data and can quickly converge to the Pareto solution set that meets the design requirements, has better HV indicators, and ensures the richness and accuracy of the solution. New ideas and methods are provided for the design and analysis of modern optomechanical systems through this research, which has been demonstrated to hold significant engineering application value.

Key words: large-aperture mirrors, supporting structures, design optimization, data-driven, surrogate model

CLC Number: