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<p>Low-carbon microalloyed steels with predominantly ferritic matrix hardened by nanoprecipitation have emerged as a vital grade of advanced high-strength steels for applications in the automotive, aerospace, and marine sectors. These materials are produced by controlled thermomechanical treatment, and therefore, the constitutive equation of these steels is a prerequisite for the automation of their industrial manufacturing. With an aim to identify the best constitutive model, the current article performs a comparative analysis of eight phenomenological models to predict the flow behavior of V and Mo microalloyed steel utilizing experimentally generated isothermal hot compression results conducted across a broad range of temperatures (1073-1423 K), strain rates (0.001-10 s<sup>-1</sup>), and true strain value upto 0.8. The predictability of the Johnson-Cook (JC), modified JC (mJC), polynomial strain-compensated Arrhenius-type (PSCAT), exponential strain-compensated Arrhenius-type (ESCAT), Fields-Backofen (FB), modified FB (mFB), Khan-Huang-Liang (KHL), and modified KHL (mKHL) models has been assessed through the application of various statistical parameters, such as root mean squared error (RMSE), mean absolute error (MAE), absolute average relative error (AARE), and correlation coefficient (R). The higher values of RMSE (&gt;13 MPa) and MAE (&gt;9 MPa) reveal that the flow stress prediction by the FB, KHL, JC, mKHL, and ESCAT models is unsatisfactory as they deviate significantly from the experimental values, except only at high temperature. In contrast, mJC, PSCAT, and mFB models accurately predict flow behavior; however, the performance of the mFB model is higher regarding all statistical indexes. The mFB model can be implemented in the finite element (FE) frameworks to facilitate industrial-scale simulation and process optimization.</p>

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Prediction of the Hot Flow Behavior of Interphase Precipitation Strengthened Steel by Phenomenological Models

  • 期刊论文

  • 发表日期：

    2025年10月21日

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  • Bishal Kanrar,
  • Subrata Mukherjee,
  • Debdulal Das

摘要

Low-carbon microalloyed steels with predominantly ferritic matrix hardened by nanoprecipitation have emerged as a vital grade of advanced high-strength steels for applications in the automotive, aerospace, and marine sectors. These materials are produced by controlled thermomechanical treatment, and therefore, the constitutive equation of these steels is a prerequisite for the automation of their industrial manufacturing. With an aim to identify the best constitutive model, the current article performs a comparative analysis of eight phenomenological models to predict the flow behavior of V and Mo microalloyed steel utilizing experimentally generated isothermal hot compression results conducted across a broad range of temperatures (1073-1423 K), strain rates (0.001-10 s-1), and true strain value upto 0.8. The predictability of the Johnson-Cook (JC), modified JC (mJC), polynomial strain-compensated Arrhenius-type (PSCAT), exponential strain-compensated Arrhenius-type (ESCAT), Fields-Backofen (FB), modified FB (mFB), Khan-Huang-Liang (KHL), and modified KHL (mKHL) models has been assessed through the application of various statistical parameters, such as root mean squared error (RMSE), mean absolute error (MAE), absolute average relative error (AARE), and correlation coefficient (R). The higher values of RMSE (>13 MPa) and MAE (>9 MPa) reveal that the flow stress prediction by the FB, KHL, JC, mKHL, and ESCAT models is unsatisfactory as they deviate significantly from the experimental values, except only at high temperature. In contrast, mJC, PSCAT, and mFB models accurately predict flow behavior; however, the performance of the mFB model is higher regarding all statistical indexes. The mFB model can be implemented in the finite element (FE) frameworks to facilitate industrial-scale simulation and process optimization.