Data-driven numerical simulation and evaluation methods for mechanical properties of corroded high-strength steel wire for bridge cable structure

Purpose: Cables composed of parallel steel wires are easily subject to environmental corrosion, which leads to a decrease in the bearing capacity and seriously affects the safe operation. This paper aims to propose a data-driven numerical method and evaluation framework for the mechanical properties of corroded cable structures. Design/methodology/approach: Based on the stress-corrosion test data, a data-driven prediction method for the corrosion characteristic parameters of high-strength steel wire was proposed. According to the prediction results of corrosion morphology parameters, an ABAQUS plug-in was developed to form random corrosion pits on the surface of steel wire, and then a numerical simulation method for corroded steel wire was proposed. Combined with the monitoring data, a mechanical properties evaluation method for the corroded cable structure was constructed with corrosion time and stress level as input values. Findings: The accuracy of the proposed method was verified by comparing the calculated results with the experiment. The gradient boosting decision tree model is the best for predicting the mechanical properties of corroded cables. The mechanical properties of steel wires decrease with increasing corrosion level. The proposed framework can accurately calculate the performance degradation of cable structures at different service stages. Originality/value: The proposed method does not require a large number of expensive tests. Through numerical calculations combined with monitoring data, the mechanical properties of the steel wire inside the cable can be evaluated. The conclusion can provide a reference for performance assessment and maintenance decision-making of bridge structures.