Risk-based optimization of emergency response systems for accidental gas leakage in utility tunnels

Focusing on the effective configuration of emergency response systems in utility tunnels, this study proposes an innovative approach to optimize existing emergency response systems based on a consequence rapid prediction model and genetic algorithm. In the proposed approach, the interactions between different emergency response components are considered to perform a rapid gas dispersion prediction. Furthermore, the predicted gas concentration distribution is employed to estimate the quantitative explosion risks by combining the equivalent cloud method and the Baker-Strehlow model. Finally, the cumulative and cascading risk index are proposed and combined for systematic optimization by using a genetic algorithm. A case study is performed to demonstrate the feasibility of the proposed approach. The results indicate that the optimized emergency response systems effectively reduce both the cumulative and cascading risk level. This study provides technical support for emergency response system design and helps to improve the safety -risk -control capabilities of utility tunnels.