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Multi-objective optimization of T-shaped bilateral laser welding parameters based on NSGA-II and MOPSO

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Abstract

In the realm of welding production, optimizing parameters for enhanced quality and efficiency remains a challenge. This study introduces a novel approach using ABAQUS for simulating the thermal–mechanical behavior in T-shaped double-sided welded joints of Q345 steel. Initial simulations were experimentally validated. A range of welding parameters was then established, and the “Unifrnd” function helped sample within this range. This study considers eight welding parameters as input variables for an artificial neural network (ANN), trained to predict residual stress and deformation. Optimization algorithms NSGA-II (non-dominated sorting genetic algorithm-II) and MOPSO (multi-objective particle swarm optimization) algorithm were employed to refine the ANN's outputs. Notably, the Pareto front revealed an optimal balance between minimizing residual stress and deformation. While single optimization achieved up to 5.12% reduction in residual stress and over 50% in deformations, the tri-objective optimization resulted in a more balanced reduction (about 1.88% in residual stress and over 20% in deformations). This highlights the need for parameters weighting in decision-making. The findings demonstrate the effectiveness of integrating ANN with optimization algorithms for welding parameter optimization, with implications for improved welding practices.

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Acknowledgements

This study was supported by Jilin Provincial Department of Science and Technology (Grant No. 20170204071GX).

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Authors and Affiliations

  1. School of Mechanical and Aerospace Engineering, Jilin University, Changchun, 130025, China

    Yunjie Tan, Guoren Zhu, Fengjun Tian, Zhonghao Zhao & Bosen Chai

  2. Chain Transmission Research Institute, Jilin University, Changchun, 130025, China

    Guoren Zhu

  3. Chongqing Research Institute, Jilin University, Chongqing, 401120, China

    Bosen Chai

  4. National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University, Changchun, 130025, China

    Bosen Chai

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  1. Yunjie Tan
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Contributions

Yunjie Tan contributed to writing—original draft, conceptualization, investigation, software, validation, and methodology. Guoren Zhu and Bosen Chai contributed to methodology, validation, investigation, and revision. Fengjun Tian contributed to validation, investigation, and revision. Zhonghao Zhao contributed to software, validation, investigation, and revision.

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Correspondence to Bosen Chai.

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Tan, Y., Zhu, G., Tian, F. et al. Multi-objective optimization of T-shaped bilateral laser welding parameters based on NSGA-II and MOPSO. J Mater Sci 59, 9547–9573 (2024). https://doi.org/10.1007/s10853-024-09727-w

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