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<p>Rectangular punch-shear (RPS) clinching, as an emerging joining technology for advanced multi-material stacks, is increasingly adopted in lightweight automotive and aerospace structures. However, this technology lacks reliable strength prediction methods to guide industrial applications. Conventional mechanical tests are time-consuming and labor-intensive, and finite element analysis requires prohibitive computational costs. To address these limitations, this study has developed the first principal stress-based analytical model specifically adapted for the tensile strength of RPS clinched joints, which achieves exceptional prediction accuracy with a maximum error of 4.73% for HC340LA high-strength low-alloy steel (HC340LA)/AA5052-H32 aluminum–magnesium alloy (AA5052-H32) dissimilar material combinations. Dominant process parameters are novelly identified through Sobol sensitivity analysis, with quantitative demonstration that the friction coefficient accounts for 85% of the variance in the predicted joint strength. Furthermore, the systematic optimization of the forming force in this study indicates that a forming force of 32&#xa0;kN results in a maximum tensile strength of 1267.94&#xa0;N, thereby providing a scientific basis for the parameter selection in industrial manufacturing processes. These advancements provide the first theoretically grounded and experimentally validated methodology for implementing rectangular clinching in industrial practice.</p>

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Study on tensile strength prediction model of rectangular punch-shear clinched joint

  • 期刊论文

  • 发表日期：

    2025年8月2日

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  • Hanghang Wen,
  • Chao Chen

摘要

Rectangular punch-shear (RPS) clinching, as an emerging joining technology for advanced multi-material stacks, is increasingly adopted in lightweight automotive and aerospace structures. However, this technology lacks reliable strength prediction methods to guide industrial applications. Conventional mechanical tests are time-consuming and labor-intensive, and finite element analysis requires prohibitive computational costs. To address these limitations, this study has developed the first principal stress-based analytical model specifically adapted for the tensile strength of RPS clinched joints, which achieves exceptional prediction accuracy with a maximum error of 4.73% for HC340LA high-strength low-alloy steel (HC340LA)/AA5052-H32 aluminum–magnesium alloy (AA5052-H32) dissimilar material combinations. Dominant process parameters are novelly identified through Sobol sensitivity analysis, with quantitative demonstration that the friction coefficient accounts for 85% of the variance in the predicted joint strength. Furthermore, the systematic optimization of the forming force in this study indicates that a forming force of 32 kN results in a maximum tensile strength of 1267.94 N, thereby providing a scientific basis for the parameter selection in industrial manufacturing processes. These advancements provide the first theoretically grounded and experimentally validated methodology for implementing rectangular clinching in industrial practice.