In the Nuclear Power Plant (NPP) control room, the operators’ performance under emergencies is impacted by the need to monitor many indicators on the control room boards, the limited time to interact with dynamic events and the weaknesses in operator’s knowledge. Recent research has been directed toward increasing the level of automation in the NPP system by employing modern AI techniques that support the operator’s decisions. In previous work, the authors have employed a novel AI-guided declarative approach (namely, Answer Set Programming (ASP)) to represent human qualitative knowledge and mimic human reasoning using logic programming. This represented knowledge is structured to form a reasoning-based operator support system that assists the operator and compensates for any knowledge weaknesses by performing reasoning to identify faults (diagnosis) and recommend executing actions in real time. A general ASP code structure has been proposed and tested against simple scenarios e.g. diagnosis of different types of pump failures that result in loss of flow transients, informing the operator of expected scenarios given the occurrence of specific failures, and generating the needed plans for resolving the issue of stuck valves in the secondary loop.

In this work, the potential of the previously proposed ASP structure is investigated by applying ASP to the case study of the Three Mile Island (TMI) accident event sequence (in particular, the first 142 minutes). The TMI scenario presents many challenges for a reasoning system including a large number of variables, the complexity of the scenario, and the misleading readings. The capability of the ASP-based reasoning system is tested for diagnosis and recommending actions throughout the scenario. Additionally, the reasoning system is shown to give explanations of the automatic actions that the system executes (e.g. the automatic start of the high-pressure injection system).


Benchmarking an AI-Guided Reasoning-Based Operator Support System on the Three Mile Island Accident Scenario

Division / Sponsors: 
Power Division & Nuclear Engineering Division (NED)

Power Conference
Paper Proceedings: https://asmedigitalcollection.asme.org/POWER/POWER2020/volume/83747

International Conference on Nuclear Engineering
Paper Proceedings: https://asmedigitalcollection.asme.org/ICONE/ICONE2020/volume/83761

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