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Numerical prediction of the tensile strength of composite T-joints considering multiple failure criteria and damage degradation models

Xiaoqiang WangShenyang Aerospace UniversityRui ZhangShenyang Aerospace UniversityChengkun MaShenyang UniversityShaowei LuCollege of Material Science and Engineering, Shenyang Aerospace University Shenyang, Liaoning 110136, P. R. ChinaLu ZhangShenyang Aerospace UniversityCong ZhouShenyang Aerospace UniversityShuaihao LiuShenyang Aerospace UniversityWenbo ZhangCollege of Aerospace Engineering, Shenyang Aerospace University Shenyang, Liaoning 110136, P. R. ChinaWeitao ZhaoCollege of Aerospace Engineering, Shenyang Aerospace University Shenyang, Liaoning 110136, P. R. ChinaЭ. У. АрзикуловSamarkand State University Named After Sharof Rashidov, University Boulevard 15 Samarkand 140104, Republic of Uzbekistan

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This study focuses on evaluating the accuracy of two composite failure criteria and three damage degradation methods in predicting the strength of composite T-joints. It also investigates the effectiveness of using a quasi-static tensile model to simulate the failure of composite T-joints. A finite element (FE) model of the T-joint was developed. Load–displacement curves were obtained under various failure criteria and degradation approaches, and the results were compared with experimental data. Among the predictions, the FE model based on the Tsai–Wu criterion showed good agreement with both the initial and final failure loads of the joint, with an error of 1.99%. For models based on the Hashin criterion, the energy-based equivalent displacement degradation method provided the most accurate results, with an error of 4.88%. The quasi-static tensile model, using displacement boundary conditions, also delivered high prediction accuracy. Its error compared with experimental data was only 1.72%. This work provides insights into the selection of failure degradation strategies in numerical simulations of composite joints. It also demonstrates the applicability of quasi-static models for solving similar problems.

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