Moving beyond traditional reactive maintenance decisions, this study explores a preventive maintenance strategy for highway bridges by integrating long-term durability forecasting. This need is addressed by analyzing two decades of historical inspection data from China. Visual condition records were sourced from a management system covering 2854 bridges, while durability parameters were obtained through 31 field tests on 23 bridges. This research introduces an instantaneous carbonation coefficient, which quantifies the carbonation rate specific to each discrete condition rating. The analysis reveals a 700% surge in the carbonation rate for poor condition states relative to intact ones, significantly higher than the 300% increase projected by traditional averaged models. Under the premise that maintenance can restore a bridge’s condition by one rating grade, three maintenance strategies are evaluated. Results indicate that initiating preventive interventions at a qualified condition can reduce long-term maintenance frequency by about 20%, offering a practical, condition-informed framework for optimizing maintenance planning and resource allocation.
Fang et al. (Sun,) studied this question.