Thesis
Towards a data analytics framework to support prognostics & health management in nuclear power plants
- Creator
- Rights statement
- Awarding institution
- University of Strathclyde
- Date of award
- 2022
- Thesis identifier
- T16364
- Person Identifier (Local)
- 201751368
- Qualification Level
- Qualification Name
- Department, School or Faculty
- Abstract
- The global nuclear reactor fleet is ageing but will play a vital role in low carbon energy generation for decades to come. This thesis presents an overview of some of the ways that these reactors are fully leveraged via effective monitoring and management. Ultimately, a methodical framework is proposed to support the digestion and understanding of the data they produce.To that end, a summary of Prognostics and Health Management concepts and techniques are first introduced and discussed, reviewing some common analytical techniques for specific operational challenges, and discussing various approaches that have been proposed for nuclear analytics more generally.The Assisted Data Visualisation & Analysis for Nuclear Core Evaluation (ADVANCE) framework is subsequently introduced, designed to promote a methodical process of fully exploiting the data available to the analyst and to delineate individual roles and responsibilities during the analysis process.The application of this framework is then demonstrated via three case studies: the first showing the way in which the framework was used to support the interrogation and understanding of CANDU reactor fuel monitoring data. Secondly an improved fuel defect detection process was developed, introducing some data processing steps to an existing analysis process in order to identify any anomalous trends faster than previously possible. Thirdly, a further dataset is introduced and assessed under the guidance of the ADVANCE framework. It is shown that specific insights can be derived from this power dataset, and that these insights can be related to the original dataset under investigation.Finally, some ways this framework may be extended are discussed in relation to the existing and future worldwide reactor fleet.
- Advisor / supervisor
- West, Graeme
- Resource Type
- DOI
关系
项目
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PDF of thesis T16364 | 2022-10-19 | 公开 | 下载 |