Risk Assessment Method for Forecasting Time-Dependent Aging Effects on Corrosion Rate: Preemptive Bridge Assets Management

Abstract

Current bridge assets management (BAM) is based on a site inspection–based condition rating methodology. Mitigation measures are adapted to assets’ condition assessment results. The reaction approach of bridge infrastructure structural evaluation does not help in judicious planning for repair and rehabilitation in prioritization for bridge assets management. This research paper presents a risk assessment method (RAM) developed upon the statistical data analysis using analytical tools and techniques of the aging effect on the corrosion anomaly rate (CAR), as proposed by the authors. The proposed RAM methodology is developed in order to provide the bridge asset manager with an analytical tool for risk-based BAM optimization. A cluster of 92 New York City Department of Transportation (NYCDOT) steel girder with reinforced concrete deck bridges was selected. The main objectives of this research paper are to (1) develop a risk rating methodology (RAM) for preemptive bridge assets management, (2) compare the RAM-based risk rating (RR) with the primary member condition rating (CR) of 92 NYCDOT nonrehabilitated steel girder with reinforced concrete deck bridges, and (3) provide analytical tools for bridge life-cycle determination for different vulnerability levels and for forecasting the financial risk of prolonged delayed rehabilitation. This innovative paper illustrates the RAM application for predicting the aging process on the CAR and its disposition for a preemptive BAM planning and development. Extending the useful service life of aging bridges is a critical issue of global interest. One problem faced globally by the transportation industry is the degradation of structural components of bridges. The purpose and practical application of this paper is to demonstrate a risk assessment approach for BAM relying on statistical data analysis for prioritizing the repair/rehabilitation of deteriorating bridge system. This research presents the deterioration rate concept in BAM framework consisting of estimating the useful service life expectancy of deteriorating bridge system through statistical data analysis, developing a deterioration rate model. The current BAM is based on a site inspection–based condition rating methodology, which depends upon structural evaluator’s judgments. The outcomes of this research have demonstrated, through statistical data analysis, that the pattern of aging effects on the time-dependent CAR value may effectively serve as a substantial time-dependent early degradation indicator for life-cycle state evaluation and serviceability performance degradation. BAM provides valuable aid for bridge owner decision makers in forecasting the degradation rate of bridge system and making preemptive decisions for rehabilitation investment prioritization. One practical application of this research is forecasting the cost implications of deferred repair/rehabilitation along with associated financial risk.