Abstract

Reliably assessing the condition and safety of suspension bridges poses the problem of determining the remaining strength of bridge cables in their present state. Corrosion of the steel wires, which together comprise the main cable, is universally recognized as the main cause of the reduction in strength. Hidden by the protective cable wrapping, this corrosion often goes undetected and unmonitored for years, discovered only during costly and intrusive inspections. This paper presents a method for estimating the remaining capacity of cables that is based on monitored environmental condition data. The long-term corrosion rate of bridge wires, C(t), can be described by the exponential expression C(t)=Atn where A is the annual corrosion rate for a metal free of corrosion products, t is the time in years, and n is an exponent dependent on the type of metal as well as the prevalent environmental conditions. In this study, a novel approach that relies on tensile test data gathered during a bridge inspection, coupled with environmental condition data typical to the locality of the bridge was used to quantify n. Temperature and relative humidity distributions across the cable section required to estimate the corrosion rate were correlated to externally monitored inputs using data from a full-scale mock-up cable subject to cyclic temperature and humidity conditions. Using the developed method, the evolution of cable strength over time under typical environmental conditions was simulated for a 100-year-old cable (Williamsburg Bridge in New York City) as well as a new, hypothetical bridge cable composed of galvanized wires. In the numerical simulation of the Williamsburg Bridge cable, the reduction in cable strength between the years 1988 and 2100 was estimated between 3.2 and 7.0%. Extending this concept, the methodology presented in this paper for estimating the remaining strength of suspension bridge cables may be readily adapted to other bridges and can be used to complement the current best practices for bridge inspection.

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