Predictive Maintenance of Critical Systems & Components in Canada's Nuclear Energy Infrastructure Under Seismic Risk

核电厂安全运行面临的两个主要挑战是：1)超出设计基础的地震危险；2)核电厂内关键的、与安全有关的系统和部件因相互依赖而变得复杂。*对于北美东部的岩石场地，加拿大标准协会和美国核管理委员会推荐的设计反应谱对于17赫兹以上的频率是不安全的，对于更低的频率则过于保守。这种情况对加拿大构成了重大威胁，因为加拿大的核基础设施集中在东部的安大略省、魁北克省和新不伦瑞克省，而目前的设计建议是基于西方的地震记录；特别是考虑到加拿大在不久的将来发生地震的可能性很高(S)。第二个核电厂安全运行挑战与安全相关的系统和部件的功能有关，它们形成了一个相互依赖的复杂系统，其运行方式通常只在部件级才能理解，而其系统级的行为往往对操作员隐藏。工厂经理目前无法提供(系统级)系统性故障的可靠预测，其中少数部件相对较小的损坏可能会导致一系列后果，最终导致完全(而且往往不安全)核电厂关闭。在这种情况下，电动阀门(MOV)是一个主要问题，因为它们对核电站的安全运行是多么重要。更好地了解MOV相互依赖的网络是预测和预防未来灾难性事件的关键。*为了降低服务中断的风险，本研究将专注于开发智能工具，旨在帮助核电站运营商完成具有挑战性的预测性维护任务。将开发一个三级模型来预测MOVS和MOV网络在对应于加拿大核电厂场地的地面运动激励下的行为。根据模型输出，工厂经理将能够优先考虑未来的维护和功能优化干预，以最大限度地减少停电的持续时间、频率和总成本。在重点领域I，研究将仅限于原始状态的MOV网络；在重点领域II，将扩展模型以考虑MOV共同原因故障和地面震动的同时和复合影响，并将通过振动台试验验证结果；在重点领域III，将开发基于风险的监测工具，以促进拟议的MOV网络预测性维护工具。*这项研究计划将加强核工业的安全性和生产率，该部门每年创造60亿美元的收入，并提供30,000个直接就业机会，同时通过减少与服务中断、维护和基础设施更新相关的成本，通过低温室气体排放促进环境的治理。

Two of the main challenges facing safe nuclear power plants (NPPs) operations are: 1) Beyond design-basis seismic hazards; and 2) Interdependence-induced complexity of critical, safety related, systems and components within NPPs. ******For rock sites in eastern North America, design response spectra recommended by the Canadian Standard Association and the US Nuclear Regulatory Commission are unsafe for frequencies above 17 Hz and overly conservative for lower frequencies. This situation poses a significant threat for Canada, because its nuclear infrastructure is clustered in the eastern provinces of Ontario, Québec, and New Brunswick, while current design recommendations are based on western seismological records; especially considering the high likelihood that Canada will experience a seismic event(s) in the near future.******The second NPPs safe operation challenge pertains to the functionality of safety related systems and components, which form an intricate complex system of interdependent components that operates in a manner often understood only at a component-level, while its system-level behaviour is often concealed to the operators. Plant managers are currently unable to provide robust predictions of (system-level) systemic failures, wherein relatively minor damage of a handful of components may lead to a cascade of consequences culminating in complete (and often unsafe) NPP shutdown. In this context, motor operated valves (MOVs) are a primary concern, given how central to the safe operation of NPPs they are. A greater understanding of MOV interdependent networks is key to predict and prevent future catastrophic events.******In order to mitigate the risk of service interruption, this research will focus on the development of intelligent tools designed to aid NPP operators in the challenging task of predictive maintenance. A tri-level model will be developed to predict the behaviour of MOVs and MOV network when excited by ground motion corresponding to Canadian NPP sites. Based on the model output, plant managers will be able to prioritize future intervention of maintenance and functional optimization, to minimize the duration, frequency and overall cost of power outages. In Focus Area I, the study will be limited to MOV networks in original condition; in Focus Area II, the model will be extended to incorporate the concurrent and compounding effects of MOV common cause failures and ground shaking, and the results will be validated via shake table testing; in Focus Area III, risk-based monitoring tools will be developed to facilitate the proposed MOV network predictive maintenance tool.******This research program will bolster safety and augment productivity in the nuclear industrya sector that generates $6 billion in revenues every year and provides 30,000 direct jobs, while contributing to the tutelage of the environment via low GHG emissionsby reducing the costs associated with the interruption of service, maintenance, and infrastructure renewal.