LI Rong, BAI Shuai, YANG Meng, LIANG Bin, HU Ke-jun. ACCURATE AND RAPID STRENGTH PREDICTION OF MULTI-TYPE SINGLE LAP JOINTS BASED ON THE STRESS RATIO AT INTERFACE END[J]. Engineering Mechanics. DOI: 10.6052/j.issn.1000-4750.2024.06.0491
Citation: LI Rong, BAI Shuai, YANG Meng, LIANG Bin, HU Ke-jun. ACCURATE AND RAPID STRENGTH PREDICTION OF MULTI-TYPE SINGLE LAP JOINTS BASED ON THE STRESS RATIO AT INTERFACE END[J]. Engineering Mechanics. DOI: 10.6052/j.issn.1000-4750.2024.06.0491

ACCURATE AND RAPID STRENGTH PREDICTION OF MULTI-TYPE SINGLE LAP JOINTS BASED ON THE STRESS RATIO AT INTERFACE END

  • The intensity of singular stress field (ISSF) at the interface end of a single lap joint is affected by material combination, by configuration geometry and by other factors, therefore, it is difficult for the existing bonding strength prediction methods to guarantee the accuracy, high efficiency and universality at the same time. The stress ratio method for a single lap joint with an isotropic plate is introduced into the strength prediction problem of the single lap joint with the anisotropic composite plate by using a plane strain model, and the common expression of ISSF is constructed. Based on the linear law of critical ISSF and the proportional relationship between critical ISSF and peel stress at the interface end, the simplified common expressions for the interface strength prediction of single lap joints with isotropic material plates and anisotropic composite plates are constructed. The accurate and rapid prediction expressions of test data are developed. The results show that only 2D model and 1 or 2 sets of test data are enough for the strength prediction requirements of different material types, of geometry and of manufacturing processes. For the joint with an aluminum alloy plate, 93% prediction errors of experiment results can be controlled within 8.5%. For the joint with a Carbon Fiber Reinforced Polymer (CFRP) plate, the minimum prediction error of experiment results is only -0.6%, and 68% of the predicted data is better than that in the references.
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