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<p>Prediction of temperature based on the process parameters in friction stir welding (FSW) of titanium alloys, particularly Ti6Al4V, underpins the production of defect-free welded joints at reduced levels of materials and energy wastages. This work proposes a new approach to model and validate the FSW process for Ti-6Al-4V based on the process variables using computational fluid dynamics (CFD). The work uses the sections welded by a newly developed low-cost single-use tool, to join 2-m long sections, to validate the model. The validation process was based on physical experimentation and microstructural measurements of micrographs produced using an Infinite Focus Microscope (IFM), which presented a simple technique when predicting thermomechanical parameters and properties including temperature distribution, torque, strain rate, and material flow properties. The developed model provides a predictive framework for a combined thermal and material flow response of Ti6Al4V under friction stir welding.</p>

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Thermomechanical modelling to optimise friction stir welding of Ti-6Al-4V alloy validated by microstructural analysis

  • 期刊论文

  • 发表日期：

    2025年3月17日

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  • Masoumeh Faraji,
  • Montadhar Al-Moussawi,
  • Jonathan Martin

摘要

Prediction of temperature based on the process parameters in friction stir welding (FSW) of titanium alloys, particularly Ti6Al4V, underpins the production of defect-free welded joints at reduced levels of materials and energy wastages. This work proposes a new approach to model and validate the FSW process for Ti-6Al-4V based on the process variables using computational fluid dynamics (CFD). The work uses the sections welded by a newly developed low-cost single-use tool, to join 2-m long sections, to validate the model. The validation process was based on physical experimentation and microstructural measurements of micrographs produced using an Infinite Focus Microscope (IFM), which presented a simple technique when predicting thermomechanical parameters and properties including temperature distribution, torque, strain rate, and material flow properties. The developed model provides a predictive framework for a combined thermal and material flow response of Ti6Al4V under friction stir welding.