A Novel Model for Transformation-Induced Plasticity and Its Performance in Predicting Residual Stress in Quenched AISI 4140 Steel Cylinders

A better residual stress prediction model can lead to more accurate life assessments, better manufacturing process design and improved component reliability. Accurate modeling of transformation-induced plasticity (TRIP) is critical for improving residual stress simulation fidelity in advanced manufacturing processes. In this work, a novel TRIP model is implemented within a finite element framework to predict residual stress in quenched AISI 4140 steel cylinders. The proposed model incorporates a dual-exponential normalized saturation function to capture TRIP kinetics. Residual stress characterization through X-ray diffraction (XRD) is employed to validate the predictive capability of the finite element model that couples the new TRIP model. In addition, the performance of the new TRIP model in predicting residual stress is compared with traditional TRIP models such as Leblond and Desalos model. Systematic comparison of finite element models incorporating different TRIP models reveals that traditional TRIP models exhibit more deviations from the measurements, while the new TRIP model demonstrates more accurate predictive accuracy, with both the axial and hoop residual stress distribution curves showing a better degree of agreement with XRD results. The findings of this study provide a reliable numerical simulation tool for optimizing the quenching process, particularly for improving fatigue life predictions of critical components such as gears and bearings.