Model-based and rule-based synthesis of operating procedures for planning severe accident management strategies

When severe accidents happen in nuclear power plants (NPPs), although there are candidate high-level actions (CHLAs) that can be selected from the severe accident management guidance (SAMG) to mitigate consequences, operators may still have cognitive challenges to identify available plant sources and then formulate executable action plans to implement the chosen actions. The difficulties faced by humans may be resolved by a decision support system taking advantages of computers’ knowledge representation and inferential capability. This article presents a systematic approach for synthesizing operating procedures that can achieve operational goals with currently available plant resources. Multilevel flow modeling (MFM), whose representation has been proved to be consistent with the general emergency procedure development, is used as knowledge basis for the action planning. A rule reasoning method is proposed to infer about actions from perspective of functions’ state transition. A model-based and rule-based operating procedure synthesis (OPS) system is developed with a rule engine. The OPS system is applied to elaborate existing high level strategies for dealing with station blackout (SBO) in a BWR plant as multiple executable action plans. The results shows some untypical ways of implementing available systems for achieving current safety goals, which may be considered in the further SAM. Moreover, what critical plant resources should be well prepared in advance is also indicated from the case study. Finally, limitation of MFM and the develop OPS system on planning SAM strategies are discussed.