Dynamic availability analysis considering environmental and maintenance variability: A Tsinghua High Flux Reactor case study by EMRALD

Dynamic availability analysis of safety-related systems should account for operating environments and maintenance activities. Many existing studies still use static failure rates and fixed mean repair times, so the resulting indicators cannot fully represent such dynamic behavior. This paper proposes a dynamic availability framework for the Tsinghua High-Flux Reactor (THFR) that integrates environment-adjusted failure rates and variable maintenance strategies within the Event Modeling Risk Assessment using Linked Diagrams (EMRALD) platform. Two adjustment schemes are used: a detailed multi-factor model with environmental multipliers and a simplified single-parameter model based on a dominant environmental variable, while maintenance is represented by alternative repair time distributions and durations. A case study of the component cooling water system (CCWS) quantifies the impact of environment-adjusted failure rates and repair assumptions on mission availability, showing that the framework provides more realistic availability estimates under changing conditions and supports risk-informed maintenance planning. • EMRALD-based dynamic availability with environment and maintenance variability. • Two failure-rate adjustments: multi-factor multipliers and single-parameter. • CM/PM modeled via repair-time distributions and configurable durations. • Mission window and PM exposure dominate unavailability. • THFR–CCWS case: temperature-driven pump rates enable risk-informed planning.

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Publication Details

Journal
Progress in Nuclear Energy
Published
2026-02-21
DOI
https://doi.org/10.1016/j.pnucene.2026.106292
Primary Topic
Reliability and Maintenance Optimization
Type
article
Field-Weighted Citation Impact
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article

Dynamic availability analysis considering environmental and maintenance variability: A Tsinghua High Flux Reactor case study by EMRALD

Lin Wang, Zefeng Li, Chunguo Wang, Jiejuan Tong et al.
Progress in Nuclear Energy
Reliability and Maintenance Optimization
article

Dynamic availability analysis considering environmental and maintenance variability: A Tsinghua High Flux Reactor case study by EMRALD

Lin Wang, Zefeng Li, Chunguo Wang, Jiejuan Tong, Yi Wu, Jiaqun Wang, Tao Liu
article en

Abstract

Dynamic availability analysis of safety-related systems should account for operating environments and maintenance activities. Many existing studies still use static failure rates and fixed mean repair times, so the resulting indicators cannot fully represent such dynamic behavior. This paper proposes a dynamic availability framework for the Tsinghua High-Flux Reactor (THFR) that integrates environment-adjusted failure rates and variable maintenance strategies within the Event Modeling Risk Assessment using Linked Diagrams (EMRALD) platform. Two adjustment schemes are used: a detailed multi-factor model with environmental multipliers and a simplified single-parameter model based on a dominant environmental variable, while maintenance is represented by alternative repair time distributions and durations. A case study of the component cooling water system (CCWS) quantifies the impact of environment-adjusted failure rates and repair assumptions on mission availability, showing that the framework provides more realistic availability estimates under changing conditions and supports risk-informed maintenance planning. • EMRALD-based dynamic availability with environment and maintenance variability. • Two failure-rate adjustments: multi-factor multipliers and single-parameter. • CM/PM modeled via repair-time distributions and configurable durations. • Mission window and PM exposure dominate unavailability. • THFR–CCWS case: temperature-driven pump rates enable risk-informed planning.

Progress in Nuclear EnergyVol. 195
Ministry of Education of the People's Republic of China (CN), Wuhan Ship Development & Design Institute (CN), China State Shipbuilding (China) (CN), Tsinghua University (CN)
Openalex Percentile: Top 58%
Reliability and Maintenance Optimization
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