From Initiation to Propagation, A Data-Driven, Multi-scale Modeling of Pitting Corrosion in W18Cr4V High-Speed Steel under Acetic Acid Environment

Localized corrosion of W18Cr4V high-speed steel in organic acid environments is a key bottleneck limiting its engineering applications. However, the full-chain failure mechanism, from microscopic nucleation to macroscopic propagation, remains unclear, thereby constraining accurate lifetime prediction.To address this issue, this study constructs and validates a data-driven, multi-scale, progressive multiphysics simulation framework.This framework first elucidates the pit nucleation mechanism driven by intrinsic material heterogeneity using a micro-galvanic model, and subsequently employs an axisymmetric model to analyze the propagation behavior of a single pit within an occluded microenvironment. All critical electrochemical kinetic parameters in the model were derived from potentiodynamic polarization experiments conducted on this specific system.The simulation results accurately reproduce and explain key features of the corrosion process. Corrosion is found to initiate from the micro-galvanic effect between the Fe-rich matrix and the carbide phase.The corrosion rate was found to be non-monotonically dependent on the acetic acid concentration, peaking at ~15%wt. This behavior is demonstrated to arise from a dynamic competition between the promotion of reaction kinetics by reactant supply and the inhibition caused by mass transport limitations.Furthermore, the study reveals that pit growth is an autocatalytic process dominated by ion enrichment, hydrolytic self-acidification, and a positive feedback loop within the occluded micro-region. Key predictions of the model, particularly the non-monotonic corrosion trend, were strongly validated by microscopic morphology and compositional characterization from static immersion experiments.The primary contribution of this work is not limited to the systematic elucidation of the complete corrosion chain. Rather, its core value is the delivery of a high-fidelity "digital tool," rigorously validated by experiments, that links macroscopic kinetic parameters to microscopic morphological evolution. This represents a paradigm shift for research in this field, moving beyond traditional "phenomenological observation" toward a new era of "mechanism-driven quantitative prediction." This work thus establishes a robust theoretical and methodological foundation for the corrosion-resistant design and service life assessment of high-performance tool steels.