Study on the Reliability Evaluation Method and Diagnosis of Bridges in Cold Regions Based on the Theory of MCS and Bayesian Networks

The safety assessment of bridges in cold areas under the special environmental effects of extremely low temperatures, frequent freezing and thawing, and chloride ion erosion from snow removal with deicing salt, presents challenges that requiring solving. Thus, this paper proposes a new method of safety assessment based on a combination of Monte Carlo simulation (MCS) and Bayesian theory that achieves the reliability evaluation and reverse diagnosis of the overall safety performance of reinforced concrete bridges in cold areas. Additionally, the new method accomplishes the intelligent grading of various safety performance aspects of the bridge, which provides substantial references for the maintenance and reinforcement of in-service bridges.