Gasifier system is one of the important components of coal gasification device. The technical characteristics of this system mainly lie in the following facts as huge technical scale and high complexity, and there is a dynamic correlation between the failure modes of gasification equipment. Traditional safety analysis methods such as fault tree and bow-tie diagram suffer from drawbacks as being static and ineffective in handling uncertainty, which hamper their application to risk analysis of process systems. This paper presents a newly developed model based on Dynamic Bow-Tie (DBT) and Dynamic Bayesian network (DBN) for quantitative dynamic risk assessment of gasifier system. In the meantime, in order to cope with the uncertainty of the failure data, fuzzy numbers and the defuzzification method are used to transform the experts' language into the failure rates. The results showed that dynamic risk assessment can solve the difficulties dealing with complex dynamic systems which have process variables and characteristics such as multiple, failure correlations, and noncoherence. And it also has important theoretical significance and application value for coal chemical industry to improve the scientificity of risk assessment.
High throughput diagnostics and dynamic risk assessment of SARS-CoV-2 variants of concern
