复合材料蜂窝夹芯结构低速冲击后压缩强度的可靠性与灵敏度分析

doi:10.19936/j.cnki.2096-8000.20240228.001

复合材料科学与工程 ›› 2024, Vol. 0 ›› Issue (2): 5-12.DOI: 10.19936/j.cnki.2096-8000.20240228.001

• 基础研究 • 下一篇

复合材料蜂窝夹芯结构低速冲击后压缩强度的可靠性与灵敏度分析

李洪年¹, 石强斌², 王轩², 邹润文², 张峰³

1.中国商用飞机有限责任公司上海飞机设计研究院,上海 201210;
2.中国民航大学航空工程学院,天津 300300;
3.西北工业大学力学与土木建筑学院,西安 710072

收稿日期:2022-12-13 出版日期:2024-02-28 发布日期:2024-04-22
作者简介:李洪年(1978—),男,硕士,高级工程师,主要从事民用飞机复合材料结构试验验证方面的研究,lhndnlhn@163.com。
基金资助:
国家973计划项目(20014CB046200);天津市科技计划项目(20YDTPJC00380);中央高校基本科研业务费项目中国民航大学专项(3122019099)

Reliability and sensitivity analysis of compressive strength after low-speed impact for composite honeycomb sandwich structure

LI Hongnian¹, SHI Qiangbin², WANG Xuan², ZOU Runwen², ZHANG Feng³

1. Shanghai Aircraft Design and Research Institute, Commercial Aircraft Corporation of China Ltd., Shanghai 201210, China;
2. College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China;
3. College of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, Xi'an 710072, China

Received:2022-12-13 Online:2024-02-28 Published:2024-04-22

摘要/Abstract

摘要： 建立了一种复合材料蜂窝夹芯结构低速冲击后压缩强度的可靠性与灵敏度分析方法。利用ABAQUS有限元分析软件和VUMAT子程序建立了蜂窝夹芯结构冲击后压缩渐进损伤失效分析模型,并通过试验验证模型的有效性;在此基础上,利用Python语言对模型中材料力学性能和面板厚度、蜂窝芯子厚度进行参数化;采用径向基神经网络代理模型替代渐进损伤失效分析模型;基于蒙特卡洛法进行冲击后压缩强度的可靠性分析;分别采用基于方差和基于失效概率的方法进行参数的灵敏度分析,并研究参数的变异系数对结构可靠性的影响。结果表明:在外载荷低于10 000 N,结构失效概率小于0.000 17的情况下,当外载荷达到12 700 N时,结构失效概率达到0.9;面板的力学性能、面板厚度、蜂窝芯厚度对冲击后压缩强度的影响较大;冲击后压缩强度的变异系数随着参数变异系数的增大而增大。

关键词: 蜂窝夹芯结构, 冲击后压缩, 神经网络, 可靠性, 灵敏度, 复合材料

Abstract: A reliability and sensitivity analysis method of compressive strength of composite honeycomb sandwich structure after low-speed impact is established. The progressive damage failure analysis model of composite honeycomb sandwich structure is established by using ABAQUS finite element analysis software and VUMAT subroutine, and the effectiveness of the model is verified by experiments. On this basis, the material mechanical properties, panel thickness and honeycomb core thickness in the model are parameterized by Python language. The radial basis function neural network agent model is used to replace the progressive damage failure analysis model. The reliability analysis of compressive strength after impact is carried out based on Monte Carlo method. The methods based on variance and failure probability are respectively used to analyze the sensitivity of parameters, and the influence of variation coefficient of parameters on structural reliability is studied. The results show that when the external load is less than 10 000 N, the probability of structural failure is less than 0.000 17, and when the external load reaches 12 700 N, the probability of structural failure reaches 0.9. The mechanical properties of the panel, the thickness of the panel and the thickness of the honeycomb core have a great influence on the compressive strength after impact. The coefficient of variation of compressive strength after impact increases with the increase of the coefficient of variation of parameter.

Key words: honeycomb sandwich structure, compression after impact, neural network, reliability, sensitivity, composites

中图分类号:

TB332

李洪年, 石强斌, 王轩, 邹润文, 张峰. 复合材料蜂窝夹芯结构低速冲击后压缩强度的可靠性与灵敏度分析[J]. 复合材料科学与工程, 2024, 0(2): 5-12.

LI Hongnian, SHI Qiangbin, WANG Xuan, ZOU Runwen, ZHANG Feng. Reliability and sensitivity analysis of compressive strength after low-speed impact for composite honeycomb sandwich structure[J]. COMPOSITES SCIENCE AND ENGINEERING, 2024, 0(2): 5-12.

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复合材料蜂窝夹芯结构低速冲击后压缩强度的可靠性与灵敏度分析

Reliability and sensitivity analysis of compressive strength after low-speed impact for composite honeycomb sandwich structure

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