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Numerical Approach Predicts Corrosion Rates of Austenitic Stainless Steel

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— 1 min read

Researchers at the Technical University Chemnitz (TU Chemnitz) have developed a numerical approach to predict corrosion rates of austenitic stainless steel 316L after cold rolling. The study, published in JOM, found that forming processes significantly affect the material's microstructure, influencing its corrosion behavior. The research team used x-ray diffraction and numerical simulations to experimentally determine and predict residual stress state, phase fractions, crystallite sizes, and microstrain.

Key Takeaways:

  • The study highlights the importance of considering forming processes in the development of corrosion-resistant materials, as they can significantly impact the material's microstructure and corrosion behavior.
  • The numerical approach introduced in the study allows for the prediction of corrosion rates of 316L after cold rolling, taking into account the component surface and near-surface microstructure.
  • The research facilitates the optimization of workpiece designs and forming processes, making it adaptable to other materials and forming operations.
  • The study demonstrated the effectiveness of using x-ray diffraction and numerical simulations to determine and predict material properties.
  • The research team consisted of Sandra Friedrich, Carolin Binotsch, Till Clausmeyer, Birgit Awiszus, Thomas Mehner, Axel Dittes, and Thomas Lampke.
  • Financial supporters for the research included Deutsche Forschungsgemeinschaft and Technische Universität Chemnitz.

Statistics:

  • 316L stainless steel is widely used in chemical plant engineering applications due to its exceptional corrosion resistance.
  • The material's microstructure is significantly affected by forming processes, which in turn influences its corrosion behavior.
  • Local martensite formation occurs at least on the surface up to a few micrometers into the bulk of the material during forming processes with tool contact.
  • The numerical approach introduced in the study can be applied to other materials and forming operations.

Sources:

  • "Prediction of Corrosion In the Stainless Steel 316l In the Near-surface Zone By Numerical Simulation." JOM, 2025;77(10):7529-7539.
  • NewsRx. Investigators at Technical University Chemnitz (TU Chemnitz) Report Findings in Mathematics (Prediction of Corrosion In the Stainless Steel 316l In the Near-surface Zone By Numerical Simulation). Mathematics Week. October 14, 2025; p 1555.

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