Modeling and simulation of crew to crew response variability due to problem-solving styles

Abstract An accurate and prompt diagnosis of the power plant state is crucial for the operators to successfully handle an accident or anomaly. A successful situation diagnosis is the result of a series of reasoning and a thought process which integrate the operator's observations, knowledge, and experiences. Simulating reasoning processes is useful for analyzing operator performance on situation diagnosis. Reasoning and other cognitive and physical response of operators are in part influenced by behavioral tendencies. This paper introduces a new capability of the ADS-IDAC dynamic PRA model to simulate the effects of different cognitive tendencies (problem-solving styles) of the operating crew. To do so a set of generic rules are defined and implemented in the operator model of the ADS-IDAC simulation platform. These rules cover three distinctly problem-solving styles, named Vagabond, Hamlet, and Garden-path operators. Each problem-solving style represents a set of behavioral or cognitive tendencies. Modeling techniques are proposed for these problem-solving styles and implemented in a new version of ADS-IDAC. A simulation case study based on an international benchmark study on HRA methods is used to demonstrate the new capabilities in partially explaining some of the crew-to-crew variability observed in the empirical study.