Digitization and asset information modelling to support nuclear power plant decommissioning

世界上现有的核电站有近三分之一的寿命超过30年，平均寿命为27年。其中许多将不得不在不久的将来退役，这一过程需要得到安全管理。具体到安大略省，安大略省发电公司（OPG）将于2025年开始退役皮克林设施，预计需要大约40年才能完成。退役过程的各个中间阶段包括安全储存、转移到临时废物管理设施、实际拆除设施和将燃料转移到场外更永久的储存。已建成条件的三维语义丰富模型，通常被称为建筑信息模型，可以成为反建筑规划和自动化和半自动化拆除活动的强大工具。这一伙伴关系的主要目标是开发数字工作流程，包括针对核设施关键退役活动的数据收集平台、方法和决策支持工具。

Nearly a third of the existing nuclear power plants in the world are over 30 years of age, with an average age of 27 years. A large number of them will have to be decommissioned in the near future, and this process needs to be safely managed. Specific to Ontario, Ontario Power Generation (OPG) will start decommissioning the Pickering facility in 2025, which is expected to take approximately 40 years to complete. Various intermediate stages in the decommissioning process consist of safe storage, transfer to a temporary waste management facility, physical demolition of the facility and transfer of fuel to more permanent storage off site. Three dimensional semantically enriched models of as-built conditions, popularly known as building information models, can be a powerful tool in de-construction planning and automated and semi-automated dismantling activities. The main goal of this partnership is to develop digital workflows consisting of data collection platforms, methodologies and decision support tools targeting key decommissioning activities for nuclear facilities. The main objectives of this proposal are to: (i) develop digital scanning and the attendant decision support tools in order to rapidly digitize nuclear assets and track their evolution during decommissioning; (ii) develop algorithms and work processes for optimal packing of waste produced during decommissioning and develop visualization tools to aid in the packing process; and (iii) develop non-destructive methods to profile the activation depth in concrete and augment digital models with condition data objects. Ultimately, these activities are targeted towards systematic decommissioning management and reducing the overall radiation exposure to humans. A majority of the requested budget will be used to train highly qualified personnel, namely MASc and PhD students.