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<p>Self-piercing riveting (SPR) is a key mechanical joining technology for lightweight structures. The fatigue life of SPR joints depends strongly on the local stress-strain state. However, evaluating the stress field in these joints presents challenges due to complex residual stresses from cold forming, severe stress concentrations, and potential autofrettage effects during service. Although finite element methods provide high accuracy, their modelling complexity and computational demands limit applicability in large-scale engineering analyses. To address this, the present study proposes a novel stress-strain estimation model for SPR joints (SPR-SWAN) based on nominal stress-adjusted weighting. This model dynamically combines the Neuber method and Glinka’s equivalent strain energy density (ESED) method by adjusting weights according to nominal stress levels, while incorporating an autofrettage correction term. It enables efficient estimation of local stress-strain responses at low computational cost and captures stress redistribution induced by autofrettage under cyclic loading. For validation, a refined finite element model of a typical aluminum alloy SPR joint was developed, simulating the riveting process and cyclic loading behavior. Predictions from the SPR-SWAN model were compared with these simulation results. The proposed model demonstrates superior accuracy over conventional approaches, reducing average absolute error and root mean square error by approximately 40%–58%. It effectively captures stress accumulation and redistribution arising from autofrettage. This study offers an efficient theoretical tool for fatigue life prediction and reliable design of SPR joints.</p>

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Characterization model for local stress-strain reconfiguration in self-piercing riveted joints considering autofrettage effects

  • 期刊论文

  • 发表日期：

    2026年5月1日

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  • Yahui Dong,
  • Na Yang,
  • Haisheng Song,
  • Changming Han,
  • Haotian Guo,
  • Zhiyong Chen,
  • Yanming Hu

摘要

Self-piercing riveting (SPR) is a key mechanical joining technology for lightweight structures. The fatigue life of SPR joints depends strongly on the local stress-strain state. However, evaluating the stress field in these joints presents challenges due to complex residual stresses from cold forming, severe stress concentrations, and potential autofrettage effects during service. Although finite element methods provide high accuracy, their modelling complexity and computational demands limit applicability in large-scale engineering analyses. To address this, the present study proposes a novel stress-strain estimation model for SPR joints (SPR-SWAN) based on nominal stress-adjusted weighting. This model dynamically combines the Neuber method and Glinka’s equivalent strain energy density (ESED) method by adjusting weights according to nominal stress levels, while incorporating an autofrettage correction term. It enables efficient estimation of local stress-strain responses at low computational cost and captures stress redistribution induced by autofrettage under cyclic loading. For validation, a refined finite element model of a typical aluminum alloy SPR joint was developed, simulating the riveting process and cyclic loading behavior. Predictions from the SPR-SWAN model were compared with these simulation results. The proposed model demonstrates superior accuracy over conventional approaches, reducing average absolute error and root mean square error by approximately 40%–58%. It effectively captures stress accumulation and redistribution arising from autofrettage. This study offers an efficient theoretical tool for fatigue life prediction and reliable design of SPR joints.