This study quantified the coupled effects of corrosion environment and fatigue loading on the corrosion-fatigue behavior of high-strength steel wires by conducting accelerated corrosion-fatigue tests. A composite environmental index ( S ) integrating the temperature-humidity equivalent coefficient and the chloride equivalent coefficient was formulated, and ( S , t ) (with t denoting exposure duration) served as a unified set of predictors. The maximum corrosion depth ( d max ) served as an observable mediating variable linking environmental exposure to mechanical degradation. Based on this variable, a data-driven Bayesian probabilistic prediction model was developed. The results show that d max follows a power-law relationship with ( S , t ). Comparative analysis indicates that fatigue loading accelerates corrosion evolution and exacerbates performance deterioration, with ductility and fatigue life exhibiting greater sensitivity to load effects than strength metrics. Referencing the relative corrosion depth from load-free tests as baseline, a three-stage load effect evolution was identified: Stage I approximately constant; Stage II linear growth with corrosion depth; and Stage III exponential decay. The corresponding critical transition thresholds were quantified. An engineering model for direct calculation of load effects from environmental parameters was derived, with independent validation confirming 95% confidence-interval coverage. This framework provides a computable and reproducible pathway for in-service assessment and service-life prediction of cable structures.
Guo et al. (Wed,) studied this question.