Quantitative risk assessment (QRA) is the most commonly used static risk assessment framework in the process industries to quantify the risks from the "probability-consequence" perspective . The available equipment and human vulnerability assessment methods can provide reliable models to estimate the accident possibility and consequence, which are critical steps in the QRA framework. On this basis, many variations of the traditional QRA framework were proposed to cope with various major accidents such as domino accidents and Na-tech events . However, these QRA-based methods cannot fully capture the mutually amplified phenomena between various hazards, leading to the underestimation of risk in multihazard coupling scenarios. Accordingly, He et al. extended the traditional QRA framework for quantifying the risk of a multi-hazard coupling scenario involving fires, explosions, and toxicant leaks. The multi-hazard coupling effects in such scenario were divided into three categories: triggering, severity amplification, and the delay in the fire brigade intervention. The Monte Carlo simulation, the consequence analysis models, escalation models, and damage models for individual accidents were combined to assess the multihazard coupling effects. However, the damage analysis models they used were still based on the traditional single-hazard vulnerability model . Ming et al. developed a quantitative multi-hazard risk assessment framework for a compound event induced by rainfall, river flow, and storm surge. The proposed framework consists of four components: hazard frequency analysis, hydrodynamic flood simulation, vulnerability analysis, and multi-hazard risk calculation. The Copula function was adopted to combine the marginal distributions of individual hazards to generate a joint distribution function for joint frequency analysis. Similarly, the vulnerability analysis focuses only on evaluating structural damage caused by floods. The multi-hazard coupling effects suffered by hazard-affected objects are ignored.