{'fraction_non_alphanumeric': 0.01819154628143392, 'fraction_numerical': 0.0, 'mean_word_length': 5.56140350877193, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Information Requirements of a Decision Support System for Severe Accident Management in Nuclear Power Plants

In nuclear power plants, a severe accident is a critical accident involving significant nuclear core damage and it is managed by using a set of Severe Accident Management Guidelines (SAMG). Prepared as a guideline that provides lists of suggestions rather than strict instructions, SAMG’s contents require frequent decision-making by the operators, causing high cognitive load and creating an error-prone situation that is also amplified by the stressful environment during the severe accident mitigation efforts. A decision support system (DSS), designed by considering the human decision-making process and the system’s holistic view, can help the operators in making informed and appropriate decisions. In this study, we aim to identify the information requirements in designing such DSS for severe accident management of nuclear power plants. We combined two methods: Functional Resonance Analysis Method (FRAM) and decision ladder to identify the information requirements. FRAM provides a systematic analysis of the functions involved in severe accident management and decision ladder captures the human decision-making processes. We developed the FRAM model and the decision ladder model based on SAMG’s contents to identify the set of information requirements. The identified information requirements and their implementation suggestions are provided. This study is the first step in designing a decision support system that considers human cognitive load and holistic system concepts. The method used in this study shall contribute to the design and implementation of a DSS capable of supporting the operators in achieving safer decision-making, not only in nuclear power plants’ severe accident management but also in similar safety-critical systems.