Abstract
AbstractNowadays, the emerging digital technologies and digitalization trend in safety‐critical industrial process systems are bringing great opportunities for system performance improvements. However, new big challenges are also encountered in the reliability and safety evaluation of large complex industrial process systems due to its multi‐state, multi‐phase dynamic interactions, resilience on software and inter‐dependencies among digital components. The objectives of this study are i) to present an introductory overview of a hybrid computing framework as a supplementary to conventional fault tree analysis toolkit for risk‐oriented reliability analysis in dynamic probabilistic safety assessment context; ii) to illustrate how to combine the three methods of DDET, Markov/CCMT, and GO‐FLOW for integrated risk solutions by a case study of small‐break LOCA in nuclear power plants. Within the hybrid computing framework, the DDET model is implemented based on graph‐based search and sequence diagram refactoring by linking with Markov/CCMT and GO‐FLOW solver for branch probability estimation. The dynamic event tree model is adopted to represent the accident sequence of small‐break LOCA, where the heading events of system failure of digital RPS and phased‐mission ECCS in realization of safety‐critical functions of reactivity control and emergency core cooling are respectively modeled and analyzed by Markov chain and GO‐FLOW method. The demonstration results show that the failure analysis of complex dynamic process interactions together with time‐dependent mission reliability analysis of safety systems involved in accident prevention and mitigation can be easily implemented with accurate modeling and fast evaluation within the hybrid integration platform. The core algorithms and principles implemented for dynamic risk scenarios development by DDET, modeling, and analysis of dynamic process interactions by Markov/CCMT, time‐dependent and multi‐phase mission reliability analysis by GO‐FLOW as well as their integration to provide comprehensive solutions for the application of dynamic reliability in risk assessment are also discussed as open problems for future research.
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