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| Probabilistic analysis method of thermos-mechanical coupling of functional gradient materials structure |
| Received:January 20, 2021 Revised:November 05, 2021 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20210120001 |
| KeyWord:functional gradient thermal response uncertainty probabilistic analysis surrogate model reduced order model |
| Author | Institution |
| 刘健 |
重庆大学 航空航天学院, 重庆 |
| 张琨 |
重庆大学 航空航天学院, 重庆 |
| 李滕 |
重庆大学 航空航天学院, 重庆 |
| 辛健强 |
中国航天科技集团公司第一研究院 系统工程业务部, 北京 |
| 姚建尧 |
重庆大学 航空航天学院, 重庆 ;重庆大学 非均质材料力学重庆市重点实验室, 重庆 |
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| Abstract: |
| A probabilistic thermo-mechanical coupling analysis tool based on the self-consistent mean micromechanical (Wakashima-Tsukamoto,W-T) model and Latin hypercube sampling is proposed in this paper.The Kriging surrogate model for thermal analysis and the Proper Orthogonal Decomposition (POD) reduced-order Kriging model for structural analysis are constructed by using uncertain random parameters to describe the physical properties and spatial distribution of the material as inputs to the probabilistic analysis and the thermal stress as outputs.The results show that the uncertainty of the thermal expansion coefficient and the thermal conductivity of the ceramic material have a significant effect on the thermal response of the structure;The use of the POD reduced order method for thermal stress prediction over time can significantly optimize the Kriging surrogate models;Meanwhile the proposed probabilistic analysis method can consider the effects of multiple random factors on the thermal response of functional gradient materials,and verifies the accuracy and validity of the method,which provides a reference for the design and sensitivity analysis improvement of functional gradient materials. |