变可信度近似模型及其在复杂装备优化设计中的应用研究进展

doi:10.3901/JME.2020.24.219

机械工程学报 ›› 2020, Vol. 56 ›› Issue (24): 219-245.doi: 10.3901/JME.2020.24.219

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变可信度近似模型及其在复杂装备优化设计中的应用研究进展

周奇¹, 杨扬², 宋学官³, 韩忠华^4,5, 程远胜⁶, 胡杰翔¹, 舒乐时^7,8, 蒋平^7,8

1. 华中科技大学航空航天学院武汉 430074;
2. 华中农业大学工学院武汉 430070;
3. 大连理工大学机械工程学院大连 116024;
4. 西北工业大学翼型、叶栅空气动力学国家级重点实验室西安 710072;
5. 西北工业大学航空学院西安 710072;
6. 华中科技大学船舶与海洋工程学院武汉 430074;
7. 华中科技大学数字制造装备与技术国家重点实验室武汉 430074;
8. 华中科技大学机械科学与工程学院武汉 430074

收稿日期:2020-03-09 修回日期:2020-09-08 出版日期:2020-12-20 发布日期:2021-02-05
通讯作者: 蒋平(通信作者),男,1981年出生,博士,教授,博士研究生导师。主要研究方向为激光加工机理与工艺、基于代理模型的加工参数优化方法等。E-mail:jiangping@hust.edu.cn
作者简介:周奇,男,1990年出生,博士,副教授。主要研究方向为多学科优化设计、变可信度近似建模、装备稳健性优化设计及机器学习等。E-mail:qizhouhust@gmail.com;qizhou@hust.edu.cn;杨扬,女,1987年出生,博士,副教授。主要研究方向为数控铣削工艺、工艺参数优化方法、变可信度近似建模等。E-mail:yangyang@mail.hzau.edu.cn;宋学官,男,1982年出生,博士,教授,博士研究生导师。主要研究方向为机-电-热-流等多学科耦合建模与协同优化、工业大数据挖掘及数据驱动的预测技术、人工智能与装备智能化技术等。E-mail:sxg@dlut.edu.cn;韩忠华,男,1977年出生,博士,教授,博士研究生导师。主要研究方向为代理模型理论、算法及其在飞行器设计中的应用、飞行器气动与多学科优化设计理论与方法、计算流体力学算法及应用、计算气动声学与噪声预测、翼型设计等。E-mail:hanzh@nwpu.edu.cn;程远胜,男,1962年出生,博士,教授,博士研究生导师。主要研究方向为船舶结构分析与轻量化设计、结构冲击动力学与防护设计、基于代理模型的优化算法等。E-mail:yscheng@hust.edu.cn;胡杰翔,男,1993年出生,博士。主要研究方向为变可信度近似建模、模型验证与校核、基于代理模型的优化算法等。E-mail:jiexianghu@hust.edu.cn;舒乐时,男,1992年出生,博士。主要研究方向为变可信度近似建模、贝叶斯优化、多目标进化算法等。E-mail:leshishu@gmail.com
基金资助:
国家自然科学基金资助项目（51805179，51775203，51705182，51721092）。

Survey of Multi-fidelity Surrogate Models and their Applications in the Design and Optimization of Engineering Equipment

ZHOU Qi¹, YANG Yang², SONG Xueguan³, HAN Zhonghua^4,5, CHENG Yuansheng⁶, HU Jiexiang¹, SHU Leshi^7,8, JIANG Ping^7,8

1. School of Aerospace Engineering, Huazhong University of Science & Technology, Wuhan 430074;
2. College of Engineering, Huazhong Agricultural University, Wuhan 430070;
3. School of Mechanical Engineering, Dalian University of Technology, Dalian 116024;
4. National Key Laboratory of Science and Technology on Aerodynamic Design and Research, Northwestern Polytechnical University, Xi'an 710072;
5. School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072;
6. School of Naval Architecture and Ocean Engineering, Huazhong University of Science & Technology, Wuhan 430074;
7. The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science & Technology, Wuhan 430074;
8. School of Mechanical Science and Engineering, Huazhong University of Science & Technology, Wuhan 430074

Received:2020-03-09 Revised:2020-09-08 Online:2020-12-20 Published:2021-02-05

摘要/Abstract

摘要： 变可信度近似模型通过融合不同精度分析模型的数据，可有效平衡近似模型预测性能和建模成本之间的矛盾，在复杂装备优化设计中受到广泛的关注。综述变可信度近似模型及其在复杂装备优化设计中的应用研究进展。概述三类常用变可信度近似建模方法的基本思想，并介绍变可信度近似建模方法研究的最新进展。回顾面向变可信度近似模型试验设计方法的发展现状，包括一次性试验设计方法和序贯试验设计方法。综述直接影响变可信度近似模型优化设计求解精度和效率的两类近似模型管理策略，探讨基于变可信度近似模型的智能优化和可靠性/稳健性优化这两个领域前沿问题。归纳总结变可信度近似模型应用于复杂装备优化设计的现状。针对变可信度近似建模及其优化设计给出了一些应用建议，并指出未来值得深入研究的方向。

关键词: 变可信度近似模型, 序贯采样, 装备优化设计, 序贯优化, 多学科优化设计

Abstract: Multi-fidelity (MF) surrogate models have attracted significant attention recently in engineering design optimization since they can make a trade-off between high prediction accuracy and low computational cost by augmenting the small number of expensive high-fidelity (HF) samples with a large number of cheap low-fidelity (LF) data. This work summarizes the state-of-the-art of MF surrogate modeling approaches and their applications in engineering design optimization. Firstly, the concept of three types of commonly used MF surrogate models is provided and the developments of extensions of them are reported. Secondly, the design of experiments for the MF surrogate models are summarized, including the one-shot design and sequential design approaches. Thirdly, two model management strategies, which directly determine the accuracy and efficiency of MF surrogate model-assisted design optimization approaches, are presented. Besides, the hot topics, MF surrogate model-assisted intelligent optimization algorithms and reliability/robust optimization are discussed. Fourthly, the applications of MF surrogate models in the practical engineering design domain are summarized. Finally, some suggestions about the usage of the MF surrogate models and their applications are provided, followed by the discussion of the deserved future work.

Key words: multi-fidelity surrogate model, sequential sampling, equipment design and optimization, sequential optimization, multi-disciplinary design and optimization

中图分类号:

TH11
V221

周奇, 杨扬, 宋学官, 韩忠华, 程远胜, 胡杰翔, 舒乐时, 蒋平. 变可信度近似模型及其在复杂装备优化设计中的应用研究进展[J]. 机械工程学报, 2020, 56(24): 219-245.

ZHOU Qi, YANG Yang, SONG Xueguan, HAN Zhonghua, CHENG Yuansheng, HU Jiexiang, SHU Leshi, JIANG Ping. Survey of Multi-fidelity Surrogate Models and their Applications in the Design and Optimization of Engineering Equipment[J]. Journal of Mechanical Engineering, 2020, 56(24): 219-245.

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变可信度近似模型及其在复杂装备优化设计中的应用研究进展

Survey of Multi-fidelity Surrogate Models and their Applications in the Design and Optimization of Engineering Equipment

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