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An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario

Published online by Cambridge University Press:  22 September 2020

BOTROS N. HANNA ,
LY LY T TRIEU ,
TRAN C. SON Open the ORCID record for TRAN C. SON [Opens in a new window]  and
NAM T. DINH
BOTROS N. HANNA
Affiliation:
Computer Science Department, New Mexico State University, Las Cruces, New Mexico, USA (e-mail: [email protected], [email protected], [email protected])
LY LY T TRIEU
Affiliation:
Computer Science Department, New Mexico State University, Las Cruces, New Mexico, USA (e-mail: [email protected], [email protected], [email protected])
TRAN C. SON
Affiliation:
Computer Science Department, New Mexico State University, Las Cruces, New Mexico, USA (e-mail: [email protected], [email protected], [email protected])
NAM T. DINH
Affiliation:
Department of Nuclear Engineering, North Carolina State University, Raleigh, North Carolina, USA (e-mail: [email protected])
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Abstract

The paper describes an ongoing effort in developing a declarative system for supporting operators in the Nuclear Power Plant (NPP) control room. The focus is on two modules: diagnosis and explanation of events that happened in NPPs. We describe an Answer Set Programming (ASP) representation of an NPP, which consists of declarations of state variables, components, their connections, and rules encoding the plant behavior. We then show how the ASP program can be used to explain the series of events that occurred in the Three Mile Island, Unit 2 (TMI-2) NPP accident, the most severe accident in the USA nuclear power plant operating history. We also describe an explanation module aimed at addressing answers to questions such as “why an event occurs?” or “what should be done?” given the collected data.

Keywords

Three Mile Island AccidentAnswer Set Programming (ASP)Explainable AI
Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 20 , Issue 6: 36th International Conference on Logic Programming Special Issue II , November 2020 , pp. 926 - 941
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Copyright
© The Author(s), 2020. Published by Cambridge University Press

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