Delivering Enhanced Through-Life Nuclear Asset Management

提供增强的全生命周期核资产管理

• 批准号: EP/R004889/1
• 负责人: Stephen McArthur
• 金额: $ 275.32万
• 依托单位: University of Strathclyde
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR004889%2F1
• 关键词: Delivering; Enhanced; Through; Life; Nuclear

Nuclear engineering has returned to the forefront of UK industrial attention with an unprecedented government economic infrastructure spend programme not seen for over 50 years. The combined life extension and new build programmes in Civil Nuclear, running in parallel with life extension and new build in submarine nuclear programmes places a significant demand on an area of engineering already dealing with a National and International skills shortage. Existing and new assets in both civil and naval sectors are important as civil nuclear power accounts for 21% of the UK's electrical generation and nuclear submarines provide the UK's independent continuous at-sea nuclear deterrent. A strategic partnership comprising Babcock International Group, BAM Nutall, Bruce Power, EDF-Energy, Kinectrics, The Weir Group and the University of Strathclyde will establish a nationally significant research programme to increase capability and multidisciplinary expertise focussed on enhanced through-life nuclear asset management. The overall aim of the partnership is two-fold. First, the drive is to create new knowledge and understanding to underpin the operational management/maintenance of existing infrastructure and to improve understanding and knowledge of lifetime and degradation processes. This will significantly increase the life of existing assets, minimise operational risk and reduce through life costs. Second, this novel knowledge can then be fed into the development of the next generation of nuclear plants and equipment, and hence translate these breakthroughs into the design and build of future nuclear assets. In doing this, the partnership will provide game changing knowledge, understanding and technology to deliver significant impact for the partners, the UK economy and global nuclear industry.Additionally it will ensure UK scientific and engineering companies remain at the forefront of global markets. The research in this programme targets low technology readiness level (TRL) advances that are required to support the ambitions of the industry partners and will deliver specific research outcomes which:- Deliver improved understanding and knowledge of lifetime and degradation processes;- Deliver a novel method or system for diagnosing or predicting degradation in plant;- Deliver novel predictive models that allow the lifetime of plant items to be extended; or- Deliver novel solutions to repairing critical plant to allow plant lifetime to be extended.The research programme and the pathway to impact will result in the whole life cycle of nuclear assets being more effectively implemented at a value higher than the sum of the individual parts. Operators will see increases in generation and reductions in costs, resulting in lower cost energy for consumers. As nuclear energy is a carbon neutral energy, investment in nuclear will help decrease CO2 emissions and global warming.The programme targets Energy Security and Efficiency, aiming to meet National Strategic Needs in the Nuclear Sector by investing in nuclear plant life extensions and efficiencies which will help increase electrical generation capacity and reduce the burden on existing electrical assets at a time when the UK faces a shortage in energy and electricity supplies in the coming years.In addition, some of the industry partners' interests span a number of sectors and the research themes in this programme are also highly relevant to other sectors including aerospace, energy and marine. Finally, an additional aim of the programme, relates to development of supply chains to deliver the next generation of technologies and components for nuclear assets. Moreover, as a number of the industrial members of the research centres are non-UK based, outputs from this research programme and subsequent products and services can be exported into international markets. This will lead to UK companies being part of foreign supply chains.

凭借 50 多年来未见的史无前例的政府经济基础设施支出计划，核工程重新回到英国工业界关注的前沿。民用核能的寿命延长和新建项目与潜艇核项目的寿命延长和新建项目并行运行，对已经解决国内和国际技能短缺问题的工程领域提出了巨大的需求。民用和海军领域的现有资产和新资产都很重要，因为民用核电占英国发电量的 21%，而核潜艇为英国提供了独立的持续海上核威慑力量。由 Babcock International Group、BAM Nutall、Bruce Power、EDF-Energy、Kinetrics、The Weir Group 和斯特拉斯克莱德大学组成的战略合作伙伴关系将建立一个具有全国意义的研究计划，以提高能力和多学科专业知识，重点关注加强全生命周期核资产管理。此次合作的总体目标有两个。首先，驱动力是创造新的知识和理解，以支持现有基础设施的运营管理/维护，并提高对生命周期和退化过程的理解和认识。这将显着延长现有资产的使用寿命，最大限度地降低运营风险并降低生命周期成本。其次，这些新知识可以被输入到下一代核电站和设备的开发中，从而将这些突破转化为未来核资产的设计和建造。在此过程中，该合作伙伴关系将提供改变游戏规则的知识、理解和技术，为合作伙伴、英国经济和全球核工业带来重大影响。此外，还将确保英国科学和工程公司保持在全球市场的前沿。该计划的研究目标是支持行业合作伙伴的雄心壮志所需的低技术准备水平（TRL）进步，并将提供具体的研究成果： - 提供对寿命和降解过程更好的理解和知识； - 提供用于诊断或预测植物降解的新方法或系统； - 提供新颖的预测模型，以延长植物的寿命； - 提供新的预测模型，以延长植物的寿命；或者- 提供新颖的解决方案来修复关键核电站，以延长核电站的使用寿命。研究计划和影响途径将使核资产的整个生命周期得到更有效的实施，其价值高于各个部分的总和。运营商将看到发电量的增加和成本的降低，从而为消费者带来更低的能源成本。由于核能是一种碳中性能源，对核能的投资将有助于减少二氧化碳排放和全球变暖。该计划以能源安全和效率为目标，旨在通过投资延长核电站寿命和提高效率来满足核部门的国家战略需求，这将有助于在英国未来几年面临能源和电力供应短缺的情况下增加发电能力并减轻现有电力资产的负担。此外，一些行业 合作伙伴的兴趣涵盖多个领域，该项目的研究主题也与航空航天、能源和海洋等其他领域高度相关。最后，该计划的另一个目标涉及开发供应链，以提供下一代核资产技术和组件。此外，由于研究中心的许多工业成员并非英国本土，因此该研究项目的成果以及后续产品和服务可以出口到国际市场。这将导致英国公司成为外国供应链的一部分。

项目成果

Bayesian Probabilistic Numerical Methods

• DOI: 10.1137/17m1139357
• 发表时间: 2019-12-01
• 期刊: SIAM REVIEW
• 影响因子: 10.2
• 作者: Cockayne, Jon;Oates, Chris J.;Girolami, Mark
• 通讯作者: Girolami, Mark

Improved power transformer condition monitoring under uncertainty through soft computing and probabilistic health index

• DOI: 10.1016/j.asoc.2019.105530
• 发表时间: 2019-06
• 期刊: Appl. Soft Comput.
• 作者: J. Aizpurua;B. Stewart;S. Mcarthur;B. Lambert;J. Cross;V. Catterson

Statistical Finite Elements via Langevin Dynamics

Langevin Dynamics 的统计有限元

• DOI: 10.48550/arxiv.2110.11131
• 发表时间: 2021
• 期刊: arXiv e-prints
• 作者: Akyildiz D

Uncertainty-Aware Fusion of Probabilistic Classifiers for Improved Transformer Diagnostics

用于改进变压器诊断的概率分类器的不确定性感知融合

• DOI: 10.1109/tsmc.2018.2880930
• 发表时间: 2021
• 期刊: Systems
• 影响因子: 1.9
• 作者: Aizpurua J

Power transformer dissolved gas analysis through Bayesian networks and hypothesis testing

• DOI: 10.1109/tdei.2018.006766
• 发表时间: 2018-04
• 期刊: IEEE Transactions on Dielectrics and Electrical Insulation
• 影响因子: 3.1
• 作者: J. Aizpurua;V. Catterson;B. Stewart;S. Mcarthur;B. Lambert;Bismark Ampofo;Gavin Pereira;J. Cross