Performance Optimization of Self-Piercing Rivets through Analytical Rivet Strength Estimation

Sun, Xin; Khaleel, Mohammad A

doi:10.1016/S1526-6125(05)70085-2

Title: Performance Optimization of Self-Piercing Rivets through Analytical Rivet Strength Estimation

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Abstract

This paper presents the authors' work on strength optimization and failure mode prediction of self-piercing rivets (SPR) for automotive applications. The limit load-based strength estimator is used to estimate the static strength of an SPR under cross tension loading configuration. Failure modes associated with the estimated failure strength are also predicted. Experimental strength and failure mode observations are used to validate the model. It is shown that the strength of an SPR joint depends on the material and gage combinations, rivet design, die design and riveting direction. The rivet strength estimator is then used to optimize the rivet strength by comparing the measured rivet strength and failure mode with the predicted ones. Two illustrative examples are used in which rivet strength is optimized by changing rivet design and riveting direction from the original manufacturing parameters.

Authors:: Sun, Xin; Khaleel, Mohammad A

Publication Date:: Mon Aug 01 00:00:00 EDT 2005

Research Org.:: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 878674

Report Number(s):: PNNL-SA-45668
VT0502010; TRN: US200611%%270

DOE Contract Number:: AC05-76RL01830

Resource Type:: Journal Article

Journal Name:: Journal of Manufacturing Processes

Additional Journal Information:: Journal Volume: 7; Journal Issue: 1

Country of Publication:: United States

Language:: English

Subject:: 36 MATERIALS SCIENCE; DESIGN; MANUFACTURING; PERFORMANCE; FAILURE MODE ANALYSIS; FASTENERS; MECHANICAL PROPERTIES; Self-piercing rivets; rivet strength; analytical rivet strength estimation; rivet strength optimization; dissimilar materials joints

Citation Formats


                    Sun, Xin, and Khaleel, Mohammad A. Performance Optimization of Self-Piercing Rivets through Analytical Rivet Strength Estimation.  United States: N. p., 2005. 
        Web.  doi:10.1016/S1526-6125(05)70085-2.

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                    Sun, Xin, & Khaleel, Mohammad A. Performance Optimization of Self-Piercing Rivets through Analytical Rivet Strength Estimation.  United States.  https://doi.org/10.1016/S1526-6125(05)70085-2

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                    Sun, Xin, and Khaleel, Mohammad A. 2005.  
        "Performance Optimization of Self-Piercing Rivets through Analytical Rivet Strength Estimation".  United States.  https://doi.org/10.1016/S1526-6125(05)70085-2.

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@article{osti_878674,

  title        = {Performance Optimization of Self-Piercing Rivets through Analytical Rivet Strength Estimation},

  author       = {Sun, Xin and Khaleel, Mohammad A},

  abstractNote = {This paper presents the authors' work on strength optimization and failure mode prediction of self-piercing rivets (SPR) for automotive applications. The limit load-based strength estimator is used to estimate the static strength of an SPR under cross tension loading configuration. Failure modes associated with the estimated failure strength are also predicted. Experimental strength and failure mode observations are used to validate the model. It is shown that the strength of an SPR joint depends on the material and gage combinations, rivet design, die design and riveting direction. The rivet strength estimator is then used to optimize the rivet strength by comparing the measured rivet strength and failure mode with the predicted ones. Two illustrative examples are used in which rivet strength is optimized by changing rivet design and riveting direction from the original manufacturing parameters.},

  doi          = {10.1016/S1526-6125(05)70085-2},

  url          = {https://www.osti.gov/biblio/878674},
  journal      = {Journal of Manufacturing Processes},
number       = 1,

  volume       = 7,

  place        = {United States},

  year         = {Mon Aug 01 00:00:00 EDT 2005},

  month        = {Mon Aug 01 00:00:00 EDT 2005}

}

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