Resumen
Safety issues are a major concern for the long-term maintenance and operation of utility tunnels, of which the focal point lies in the reliability of critical facilities. Conventional evaluation methods have failed to reflect the time-dependency and objectivity of the reliability of critical facilities, hence reducing the credibility of the analysis results and posing serious risks to the safety of utility tunnels. Taking joint waterproof facilities as an example, this paper focuses on the scientific problem of how to achieve a dynamic estimation of the reliability of critical facilities throughout the project life cycle of utility tunnels. To this end, an improved Weibull distribution model is proposed to incorporate the actual field conditions that affect the reliability of joint waterproof facilities of utility tunnels. Bayesian methods and Hamiltonian Monte Carlo methods are used to realize the posterior estimation of the model parameters via the observed failure data. The case study shows that the posterior prediction results fit well with the actual observation data. The proposed model can be used to estimate in real time such key reliability indicators as failure rate, failure warning time and expected failure time, which facilitate the safe operation and targeted maintenance of utility tunnels.