Computational inverse analysis of static recrystallization kinetics

• Computational analysis of heterogeneous static recrystallization test data.
• Careful modeling of softening with a computational inverse method.
• Experimental verification of the inverse and conventional methods.
• Merits of the inverse method for an accurate process modeling.

Accurate static recrystallization (SRX) models are necessary to improve the properties of austenitic steels by thermo-mechanical operations. This relies heavily on a careful and accurate analysis of “the interrupted test data” and conversion of the heterogeneous deformation data to the flow stress. A “computational-experimental inverse method” was presented and implemented here to analyze the SRX test data, which takes into account the heterogeneous softening of the post-interruption test sample.Conventional and “inverse” methods were used to identify the SRX kinetics for a model austenitic steel deformed at 1273 K (with a strain rate of 1 s−1) using the hot torsion test assess the merits of each method. Typical “static recrystallization distribution maps” in the test sample indicated that, at the onset of the second pass deformation with less than a critical holding time and a given pre-strain, a “partially-recrystallized zone” existed in the cylindrical core of the specimen near its center line. For the investigated scenario, the core was confined in the first half of the gauge radius when the holding time and the maximum pre strain were below 29 s and 0.5, respectively. For maximum pre strains smaller than 0.2, the specimen did not fully recrystallize, even at the gauge surface after holding for 50 s. Under such conditions, the conventional methods produced significant error.

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