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1.湖南大学 整车先进设计制造技术全国重点实验室,长沙 410082
2.湖南大学 设计艺术学院 麓山实验室,长沙 410082
3.北京强度环境研究所 可靠性与环境工程技术重点实验室,北京 100076
CAO Lixiong, E-mail: clx_328@hnu.edu.cn
Received:09 June 2023,
Revised:04 September 2023,
Published:15 February 2025
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刘玉琢,曹立雄,吴建国,等. 基于自适应代理模型的加筋壳结构可靠性优化设计[J]. 机械强度,2025,47(2):68-74.
LIU Yuzhuo,CAO Lixiong,WU Jianguo,et al. Structural reliability optimization design of reinforced shell structure based on adaptive surrogate model[J]. Journal of Mechanical Strength,2025,47(2):68-74.
刘玉琢,曹立雄,吴建国,等. 基于自适应代理模型的加筋壳结构可靠性优化设计[J]. 机械强度,2025,47(2):68-74. DOI: 10.16579/j.issn.1001.9669.2025.02.009.
LIU Yuzhuo,CAO Lixiong,WU Jianguo,et al. Structural reliability optimization design of reinforced shell structure based on adaptive surrogate model[J]. Journal of Mechanical Strength,2025,47(2):68-74. DOI: 10.16579/j.issn.1001.9669.2025.02.009.
加筋壳结构具有较高的比刚度和比强度,被广泛应用于航空航天承力结构中。可靠性优化设计(Reliability-Based Design Optimization,RBDO)方法通过综合考虑结构参数中的不确定性和风险因素,可避免结构的过保守设计,保证其在服役环境中的可靠性和安全性。提出了一种基于自适应代理模型的高效RBDO方法,来解决屈曲可靠性约束下的加筋壳结构轻量化设计问题。基于预期可行性函数准则实现了样本点的自适应添加,并通过构建分段函数将离散变量连续化,进而在保证设计结果可靠性的前提下提高优化效率。最后,通过将可靠性优化设计结果与确定性优化结果对比,验证了所提方法的有效性。
Reinforced shell structure is widely used in aerospace load-bearing structures because its high specific stiffness and specific strength.By considering the uncertainty and risk factors in the structural parameters
the reliability-based design optimization (RBDO) can avoid the overly conservative design of the structure and ensure its reliability and safety.An efficient RBDO method based on adaptive surrogate model was proposed to solve the problem of lightweight design of reinforced shell structure under buckling reliability constraints.The adaptive addition of sample points was implemented through the expected feasibility function criterion
and the discrete variables was continued by constructing piecewise functions.This increases optimization efficiency while ensuring the reliability of design results.Finally
the effectiveness of the proposed method is verified by comparing the RBDO results with the deterministic optimization results.
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