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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: bn@nmsu.edu, lytrieu@nmsu.edu, stran@nmsu.edu)
LY LY T TRIEU
Affiliation:
Computer Science Department, New Mexico State University, Las Cruces, New Mexico, USA (e-mail: bn@nmsu.edu, lytrieu@nmsu.edu, stran@nmsu.edu)
TRAN C. SON
Affiliation:
Computer Science Department, New Mexico State University, Las Cruces, New Mexico, USA (e-mail: bn@nmsu.edu, lytrieu@nmsu.edu, stran@nmsu.edu)
NAM T. DINH
Affiliation:
Department of Nuclear Engineering, North Carolina State University, Raleigh, North Carolina, USA (e-mail: ntdinh@ncsu.edu)
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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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References

Balduccini, M. and Gelfond, M. 2003. Diagnostic reasoning with a-prolog. Theory and Practice of Logic Programming 3, 4+ 5, 425–461.Google Scholar
Boroushaki, M., Ghofrani, M. B., Lucas, C., and Yazdanpanah, M. J. 2003. An intelligent nuclear reactor core controller for load following operations, using recurrent neural networks and fuzzy systems. Annals of Nuclear Energy 30, 1, 63–80.Google Scholar
Chang, S. H., Kang, K. S., Choi, S. S., Kim, H. G., Jeong, H. K., and Yi, C. U. 1995. Development of the on-line operator aid system oasys using a rule-based expert system and fuzzy logic for nuclear power plants. Nuclear technology 112, 2, 266–294.Google Scholar
Clocksin, W. F. and Mellish, C. S. 2012. Programming in Prolog: Using the ISO standard. Springer Science & Business Media.Google Scholar
Darling, M. C., Luger, G. F., Jones, T. B., Denman, M. R., and Groth, K. M. 2018. Intelligent modeling for nuclear power plant accident management. International Journal on Artificial Intelligence Tools 27, 02, 1850003.Google Scholar
Derivan, Michael. 2014. The Davis Besse nuclear power plant Three Mile Island Accident precursor event. http://www.nukeknews.com/TMI Google Scholar
DOE. 2009. Human performance improvement handbook volume 1: concepts and principles, 1 ed. Vol. 1. US Department of Energy.Google Scholar
Gelfond, M. and Lifschitz, V. 1990. Logic programs with classical negation. In Logic Programming: Proceedings of the Seventh International Conference, Warren, D. and Szeredi, P., Eds. 579–597.Google Scholar
Hanna, B., Son, T. C., and Dinh, N. 2019. An artificial intelligence-guided decision support system for the nuclear power plant management. In Proceedings of the 18th International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH 2019).Google Scholar
Lew, R., Boring, R. L., and Ulrich, T. A. 2018. Transitioning nuclear power plant main control room from paper based procedures to computer based procedures. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, 1, 1605–1609.Google Scholar
Liang, S., Fodor, P., Wan, H., and Kifer, M. 2009. Openrulebench: an analysis of the performance of rule engines. In Proceedings of the 18th international conference on World wide web. 601–610.Google Scholar
Lind, M. and Zhang, X. 2014. Functional modelling for fault diagnosis and its application for npp. Nuclear Engineering and Technology 46, 6, 753–772.Google Scholar
Marek, V. and Truszczyński, M. 1999. Stable models and an alternative logic programming paradigm. In The Logic Programming Paradigm: a 25-year Perspective. 375–398.Google Scholar
Niemelä, I. 1999. Logic programming with stable model semantics as a constraint programming paradigm. Annals of Mathematics and Artificial Intelligence 25, 3,4, 241–273.Google Scholar
NRC. 1979. Investigation into the March 28, 1979 Three Mile Island accident by office of inspection and enforcement. technical report NUREG-0600. Tech. rep., U.S. Nuclear Regulatory Commission, Washington, DC (USA).Google Scholar
NSAC. 1980. Analysis of Three Mile Island-Unit 2 accident. Tech. rep., Electric Power Research Inst., Palo Alto, CA (USA). Nuclear Safety Analysis Center.Google Scholar
Park, Y. S. and Vilim, R. 2017. Implementation of new prodiag algorithm and simulation-based acceptance test. In Proc. Nuclear Power Instrumentation, Control and Human-Machine Interface Technologies Conf.(NPIC&HMIT 2017). 11–15.Google Scholar
Peng, M.-j., Wang, H., Chen, S.-s., Xia, G.-l., Liu, Y.-k., Yang, X., and Ayodeji, A. 2018. An intelligent hybrid methodology of on-line system-level fault diagnosis for nuclear power plant. Nuclear Engineering and Technology 50, 3, 396–410.Google Scholar
Pontelli, E., Son, T., and El-Khatib, O. 2009. Justifications for logic programs under answer set semantics. TPLP 9, 1, 1–56.Google Scholar
Reifman, J. and Wei, T. Y. 1999. Prodiag: a process-independent transient diagnostic system—i: theoretical concepts. Nuclear science and engineering 131, 3, 329–347.Google Scholar
Rempe, J. L. and Knudson, D. L. 2014. Instrumentation performance during the TMI-2 accident. IEEE Transactions on Nuclear Science 61, 4, 1963–1970.Google Scholar
U.S.NRC. 2018. Backgrounder on the Three Mile Island Accident. https://www.nrc.gov/reading-rm/doc-collections/fact-sheets/3mile-isle.html.Google Scholar