Multi-dimensional Digital Twins for Nuclear Power Plants

该提案旨在深入研究、开发和使用核电厂（NPP）系统结构和组件（scc）资产管理背景下的数字双胞胎。该提案的主要目标是：(i)为关键核电站资产的数字孪生开发合适的系统架构，包括收集和融合信息所需的软件和硬件框架；（ii）基于核电厂ssc中数字孪生的当前和新兴用途开发决策支持系统。为了实现这些目标，我们将从全面的数据收集阶段开始，在此阶段，将定义ssc内关键资产、系统和流程之间的中心关系。在此之后，将进行全面的风险分析和信息价值研究，以确定哪些ssc需要数字孪生，哪些信息应包括在这种虚拟表示中。这项活动之后将进行深入研究，将感官信息融合到数字孪生表示中，这将作为原始信息源和资产决策支持工具之间的节点。最后，将开发一个框架，通过使用基于机械和物理的模型来丰富数字孪生。这将涉及算法的发展，将感官信息直接融合到机械模型（例如，有限元）中，使用检查信息定期更新这些模型（以促进状态评估和退化模型的开发）和计算效率高的再分析技术。拟议的工作将直接支持我们的行业合作伙伴在其整个生命周期内优化资产管理活动，同时保持NPP ssc所需的高水平安全性和可靠性。此外，这些数字孪生体将最终补充我们的行业合作伙伴在模型设施上的约7亿美元投资，同时确保有效的风险管理、公共责任、资产管理和规划。最终，该项目将为几名研究生提供高质量的跨学科培训和技能，并为下一代资产管理工作做好准备

This proposal is aimed at an in-depth investigation, development, and the use of digital twins in the context of nuclear power plant (NPP) systems structures and components (SCCs) asset management. The main objectives of this proposal are to: (i) develop a suitable system architecture for digital twins for key NPP assets, including the requisite software and hardware framework for collecting and fusing information; and, (ii) develop a decision support system based on current and emerging uses for digital twins in NPP SSCs. In pursuit of these objectives we will start with a comprehensive data collection phase, where the central relationships between key assets, systems and processes within the SSCs will be defined. Following this, a comprehensive risk analysis and value-of-information study will be carried out to prioritize which SSCs warrant a digital twin and what information should be included in such a virtual representation. This activity will be followed by an in-depth study to fuse sensory information into the digital twin representation, which will act as a node between raw information sources and asset decision support tools. Finally, a framework to enrich digital twins with the use of mechanistic and physics based models will be developed. This will involve the development of algorithms to directly fuse sensory information into mechanistic models (e.g., finite-element), update such models periodically using inspection information (to facilitate condition assessment and degradation model development) and computationally efficient re-analysis techniques. The proposed work will directly support the optimization of asset management activities for our industry partner throughout its life cycle, while maintaining a high level of safety and reliability required in NPP SSCs. In addition, such digital twins will ultimately complement the ~ $700M investment by our industry partner in mock-up facilities, while also ensuring effective risk management, public accountability, asset management, and planning. Ultimately, this project will impart high-quality inter-disciplinary training and skills to several post-graduate students and will prepare them for the next-generation jobs in asset management