Research on Design Requirements Analysis for Essential Service Water System of Nuclear Power Driven by Hybrid-augmented Intelligence

doi:10.3901/JME.2025.09.383

Abstract

Abstract: The essential service water system is closely related to nuclear safety and are responsible for exporting heat from the nuclear island to the final heat sink under various operating conditions. Due to the impact of different siting and types of nuclear power plants, ocean hydrology, geographical features, meteorological and other factors on the design scheme, the essential service water system has the design-to-order engineering feature, and reasonable and intuitive design requirement analysis is an important basis for subsequent configuration design. Aiming at identifying the importance of design requirements to eliminate cognitive uncertainty accurately and establishing design requirements models to ensure their completeness and traceability normally, a hybrid-augmented intelligence-driven design requirements analysis method of the essential service water system is proposed. The purpose is to make use of human high-level cognitive ability to make up for the lack of computer processing design requirements information, and to use computer calculating power to break through the reasoning ability of human brain cognitive process. Firstly, combining the pre-training model of linguistically-motivated bi-directional encoder representation from Transformer that considers the human language characteristics, the bi-directional long short-term memory network that simulates the brain's prefrontal and hippocampus neural circuit, and the multi-head attention mechanism, the text semantics of design requirements are deeply mined. The semantic features are input into the reward-modulated spiking neural network that simulates the brain's dopamine reward system to classify design requirements. Secondly, considering the ambiguity of the semantic expression of nuclear power experts and the uncertainty of group weights, a nonlinear programming model based on hesitancy fuzzy sets is constructed to identify the importance of design requirements and make further corrections. Finally, formal and structured system models are established based on the model-based systems engineering method to express design requirements in a unified and complete manner.

Key words: design requirements analysis, hybrid-augmented intelligence, spiking neural network, hesitant fuzzy set, model-based systems engineering

CLC Number:

TG156

WU Xuanyu, LOU Shanhe, HONG Zhaoxi, SI Hengyuan, ZHANG Zhifeng, FENG Yixiong, TAN Jianrong. Research on Design Requirements Analysis for Essential Service Water System of Nuclear Power Driven by Hybrid-augmented Intelligence[J]. Journal of Mechanical Engineering, 2025, 61(9): 383-401.

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