Published February 2023 | Version v1
Journal article

Retrieval methodology for similar NPP LCO cases based on domain specific NLP

  • 1. Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of)
  • 2. KHNP Central Research Institute, Daejeon (Korea, Republic of)

Description

Nuclear power plants (NPPs) have technical specifications (Tech Specs) to ensure that the equipment and key operating parameters necessary for the safe operation of the power plant are maintained within limiting conditions for operation (LCO) determined by a safety analysis. The LCO of Tech Specs that identify the lowest functional capability of equipment required for safe operation for a facility must be complied for the safe operation of NPP. There have been previous studies to aid in compliance with LCO relevant to rule-based expert systems; however, there is an obvious limit to expert systems for implementing the rules for many situations related to LCO. Therefore, in this study, we present a retrieval methodology for similar LCO cases in determining whether LCO is met or not met. To reflect the natural language processing of NPP features, a domain dictionary was built, and the optimal term frequency-inverse document frequency variant was selected. The retrieval performance was improved by adding a Boolean retrieval model based on terms related to the LCO in addition to the vector space model. The developed domain dictionary and retrieval methodology are expected to be exceedingly useful in determining whether LCO is met

Additional details

Publishing Information

Journal Title
Nuclear Engineering and Technology
Journal Volume
55
Journal Issue
2
Journal Page Range
p. 421-431
ISSN
1738-5733

Optional Information

Notes
29 refs, 10 figs, 18 tabs