Robotics and automation for optimal characterization for nuclear power plant decommissioning

用于核电站退役最佳表征的机器人和自动化

• 批准号: 507757-2016
• 负责人: Haas, Carl
• 金额: $ 5.16万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=691597
• 关键词: Robotics; automation; optimal; characterization; nuclear

Nearly a third of the world's nuclear power plants (NPPs) are over 30 years old, and a large number of these will be decommissioned in the coming decades, including the Ontario Power Generation's Pickering NPP. Decommissioning refers to the safe management of the facility following the decision to shut down a NPP, which includes demolition, packaging and removal of debris, and safe storage activities. The focus of this proposal is on developing automation and robotic methods, specifically environment characterization to aid in the deconstruction of NPPs, with the ultimate goal of reducing exposure of humans as a result of decommissioning activities. It is anticipated that the results of this study will significantly enhance the tools and the process of providing semantic model inputs regarding the facility environment to decommissioning robots, automated waste selection, and packing optimization for low to intermediate waste disposal. Given the context, this proposal focuses on addressing the following main goals: (i) develop efficient methods to create as-built Building Information Models; (ii) develop and implement the requisite characterization information necessary to populate such models, specifically targeting and optimizing automated decommissioning tasks and the types of equipment to be used; (iii) proof-of-concept demonstration of the concepts and tools which will be developed during this project; and (iv) build on the knowledge gained in meeting the preceding objectives to address inventory assessment and selective disassembly for optimization of demolition, disassembly and packing. While this phase of the study will focus on the facility characterization using sensors, it is anticipated that this work will lay the groundwork for the design and development of robotic tools and equipment to assist with decontamination and dismantling activities in the subsequent planned phases of this research partnership.

世界上近三分之一的核电站（NPP）已经超过30年，其中大量将在未来几十年内退役，包括安大略发电公司的皮克林核电站。退役是指在决定关闭核电站后对设施进行安全管理，包括拆除、包装和清除碎片以及安全储存活动。该提案的重点是开发自动化和机器人方法，特别是环境特征描述，以帮助核电站的拆除，最终目标是减少人类因退役活动而受到的辐射。预计这项研究的结果将显着增强工具和过程中提供的语义模型输入有关的设施环境退役机器人，自动废物选择和包装优化低到中等的废物处理。鉴于这一背景，本提案侧重于解决以下主要目标：（i）制定有效的方法来创建竣工建筑信息模型;（ii）开发和实施填充此类模型所需的必要特征信息，特别是针对和优化自动退役任务和所使用的设备类型;（三）对将在本项目期间开发的概念和工具进行概念验证演示;（四）利用在实现上述目标过程中获得的知识，开展库存评估和选择性拆卸，以优化拆除、拆卸和包装。虽然这一阶段的研究将侧重于利用传感器确定设施的特征，但预计这项工作将为设计和开发机器人工具和设备奠定基础，以协助这一研究伙伴关系随后计划阶段的去污和拆除活动。