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使用年限超过30年，平均使用年限为27年。其中大量核电站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Pickering设施，预计需要大约40年的时间才能完成。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、实际拆除该设施以及将燃料转移到场外更永久的储存。竣工条件的三维语义丰富的模型，通常被称为建筑信息模型，可以成为拆除规划以及自动和半自动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。 这项提议的主要目标是：(1)开发数字扫描和相应的决策支持工具，以便迅速将核资产数字化，并跟踪其在退役期间的演变情况；(2)制定算法和工作流程，对退役期间产生的废物进行最佳包装，并开发可视化工具，协助包装过程；(3)开发非破坏性方法，以描述具体的激活深度，并用条件数据对象增强数字模型。归根结底，这些活动的目标是系统的退役管理和减少对人类的总体辐射暴露。申请预算的大部分将用于培训高素质人才，即硕士和博士生。

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.