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Advances in nuclear power system design and fault-based condition monitoring towards safety of nuclear-powered ships

Adumene, S, Islam, R ORCID: 0000-0003-1577-6971, Amin, MDT, Nitonye, S, Yazdi, M and Johnson, KT 2022 , 'Advances in nuclear power system design and fault-based condition monitoring towards safety of nuclear-powered ships' , Ocean Engineering, vol. 251 , p. 111156 , doi: 10.1016/j.oceaneng.2022.111156.

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Abstract

The increasing need for cleaner and sustainable shipping operations, especially in the Arctic waters, has informed the rising technological advancements in ship nuclear power machinery (SNPM) design, such as the generation IV (GenIV) small modular reactor (SMR). Nuclear technology has also provided a potential alternative to decarbonization in the maritime industry. The recent design advances present safety challenges that need to be comprehensively studied and understood. The current study shows a review of the advancements in nuclear plant design and fault-based analysis towards safety in maritime operations. A systematic approach is adopted to explore the design improvements, operational challenges, fault diagnostics methodologies, and risk assessment frameworks for SNPM. While exploring the current state of knowledge on system design and fault-based risk assessment, the study highlights key research opportunities to provide a robust risk management framework towards safer nuclear-powered shipping operations, such as digitalization, resilient system design, and the internet of things (IoT). This study finds that the state of knowledge is inexhaustive and proposes a preliminary hybrid framework, able to integrate the hierarchical hazard structure into a fault-based risk aggregation methodology for risk-informed decision making in nuclear-powered shipping operations.

Item Type: Article
Authors/Creators:Adumene, S and Islam, R and Amin, MDT and Nitonye, S and Yazdi, M and Johnson, KT
Keywords: fault detection and diagnosis, nuclear powered shipping operations, small modular reactor, risk management, data-driven model, trustworthiness
Journal or Publication Title: Ocean Engineering
Publisher: Pergamon-Elsevier Science Ltd
ISSN: 0029-8018
DOI / ID Number: 10.1016/j.oceaneng.2022.111156
Copyright Information:

© 2022 Elsevier Ltd. All rights reserved.

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