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<p>The aim of this work is to present a workflow for the application of a multi-class grain size model, which describes the microstructure evolution during dynamic and post-dynamic recrystallization in forged UDIMET720LI components. In a first step, the distribution of the local microstructure in the as-received condition is characterized, which serves as an initial condition for the multi-class model. The recrystallization kinetics is analyzed through thermo-mechanical compression tests on a Gleeble<sup>®</sup> 3800 simulator and large-area electron backscatter diffraction analysis providing recrystallized fractions and size distributions. A finite element approach is used to translate the global test parameters to the local strain history of the samples during thermo-mechanical testing. Subsequently, the results from experimental characterization and simulated Gleeble tests are utilized to calibrate a semi-empirical Avarami-type recrystallization model. Finally, the application of the multi-class model is demonstrated by predicting the grain size distribution for two different thermo-mechanical processing routes.</p>

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Novel Multi-Class Grain Size Model for UDIMET720LI

  • 期刊论文

  • 发表日期：

    2026年2月25日

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  • Drazen Brescakovic,
  • Thomas Hönigmann,
  • Johannes Neumüller,
  • Christian Gruber,
  • Peter Raninger,
  • Philipp Retzl,
  • Piotr Warczok,
  • Konstantin Prabitz,
  • Vitor Rielli,
  • Sophie Primig,
  • Gerald Ressel,
  • Martin Stockinger

摘要

The aim of this work is to present a workflow for the application of a multi-class grain size model, which describes the microstructure evolution during dynamic and post-dynamic recrystallization in forged UDIMET720LI components. In a first step, the distribution of the local microstructure in the as-received condition is characterized, which serves as an initial condition for the multi-class model. The recrystallization kinetics is analyzed through thermo-mechanical compression tests on a Gleeble® 3800 simulator and large-area electron backscatter diffraction analysis providing recrystallized fractions and size distributions. A finite element approach is used to translate the global test parameters to the local strain history of the samples during thermo-mechanical testing. Subsequently, the results from experimental characterization and simulated Gleeble tests are utilized to calibrate a semi-empirical Avarami-type recrystallization model. Finally, the application of the multi-class model is demonstrated by predicting the grain size distribution for two different thermo-mechanical processing routes.