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<p>To gain insights into the mechanical properties and microstructure evolution of welded joints under different process parameters of Al6061-T6 thin-walled parts through tungsten inert gas welding (TIGW). The welding experiments, numerical simulation and tensile tests are carried out in this work. Utilizing a 3D scanner, the point cloud features of T-welded joint thin-walled parts are obtained, and a point set mapping algorithm is proposed to calculate welding deformation. A grain nucleation and growth model is established using the cellular automaton (CA) method, and a microstructure evolution simulation system is developed to reveal the microstructure evolution laws through a macro–micro temperature field coupling interpolation model. The simulated grain size distributions&#xa0;are aligned well with electron back scatter diffraction (EBSD) experimental results, confirming the high accuracy of the weld pool microstructure simulation. Furthermore, a response relationship model linking welding deformation, residual stress, tensile strength, and grain size under different welding conditions is established based on the grey wolf optimization (GWO) algorithm, combined with weight coefficient and a normalized objective function. A relative error of less than 2.5% for tensile strength prediction is demonstrated. Through welding process optimization, the optimal tensile strength value is 13% higher than that achieved with the initial welding current setting. This work will provide an analysis basis foundation for enhancing the welding quality and service performance of large-sized thin-walled structures in the future.</p>

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Microstructure evolution, mechanical properties of T-welded joint for different TIG welding currents and process parameters optimization with GWO algorithm

  • 期刊论文

  • 发表日期：

    2025年6月10日

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  • Minghui Pan,
  • Yuchao Li,
  • Wentao Chen,
  • Aolin Sun,
  • Xiantong Li,
  • Xiangfei Li,
  • Wenhe Liao,
  • Wencheng Tang

摘要

To gain insights into the mechanical properties and microstructure evolution of welded joints under different process parameters of Al6061-T6 thin-walled parts through tungsten inert gas welding (TIGW). The welding experiments, numerical simulation and tensile tests are carried out in this work. Utilizing a 3D scanner, the point cloud features of T-welded joint thin-walled parts are obtained, and a point set mapping algorithm is proposed to calculate welding deformation. A grain nucleation and growth model is established using the cellular automaton (CA) method, and a microstructure evolution simulation system is developed to reveal the microstructure evolution laws through a macro–micro temperature field coupling interpolation model. The simulated grain size distributions are aligned well with electron back scatter diffraction (EBSD) experimental results, confirming the high accuracy of the weld pool microstructure simulation. Furthermore, a response relationship model linking welding deformation, residual stress, tensile strength, and grain size under different welding conditions is established based on the grey wolf optimization (GWO) algorithm, combined with weight coefficient and a normalized objective function. A relative error of less than 2.5% for tensile strength prediction is demonstrated. Through welding process optimization, the optimal tensile strength value is 13% higher than that achieved with the initial welding current setting. This work will provide an analysis basis foundation for enhancing the welding quality and service performance of large-sized thin-walled structures in the future.