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<p>Duplex stainless steel (DSS) welding involves complex thermal cycles that modify the ferrite/austenite balance and promote redistribution of alloying elements in the heat-affected zone (HAZ), strongly affecting the mechanical properties and corrosion resistance of the joint. In this work, two coupled numerical models based on the finite element method (FEM) were developed to predict the phase balance and the solid-state diffusion of alloying elements during gas metal arc welding (GMAW) of UNS S32001 and UNS S32205 duplex stainless steels. The phase transformation model predicted the ferrite content at each mesh node with an accuracy higher than 90% when compared with experimental measurements. In addition, the diffusion model successfully estimated the local chemical composition as a function of the thermal cycle experienced in the HAZ. The models showed similar predictive capability for both DSS grades and provided detailed information on the evolution of microstructure and composition. These results demonstrate that the proposed methodology is a useful tool for selecting welding parameters and reducing the number of experimental trials required to optimise DSS welded joints.</p>

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New mathematical models for determining phase balance and solid-state alloy diffusion in the Heat-Affected Zone of GMAW-Welded Duplex Stainless Steels

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月29日

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  • Sandra Chacón-Fernández,
  • Antonio Portolés García

摘要

Duplex stainless steel (DSS) welding involves complex thermal cycles that modify the ferrite/austenite balance and promote redistribution of alloying elements in the heat-affected zone (HAZ), strongly affecting the mechanical properties and corrosion resistance of the joint. In this work, two coupled numerical models based on the finite element method (FEM) were developed to predict the phase balance and the solid-state diffusion of alloying elements during gas metal arc welding (GMAW) of UNS S32001 and UNS S32205 duplex stainless steels. The phase transformation model predicted the ferrite content at each mesh node with an accuracy higher than 90% when compared with experimental measurements. In addition, the diffusion model successfully estimated the local chemical composition as a function of the thermal cycle experienced in the HAZ. The models showed similar predictive capability for both DSS grades and provided detailed information on the evolution of microstructure and composition. These results demonstrate that the proposed methodology is a useful tool for selecting welding parameters and reducing the number of experimental trials required to optimise DSS welded joints.