• Donnelly, S., MacIntosh, S., McIvor, A., Medri, M., Lam, R., Lung, P. (2023). Emerging Digital Technologies Within the Canadian Nuclear Industry. Canadian Standards Association, Toronto, ON.

Executive Summary

There has been rapid development and use of emerging digital technologies in the Canadian nuclear industry. In this report, emerging digital technologies refers to the use or adoption of existing or emerging digital technologies for lifecycle activities of nuclear facilities. There is a need to provide a common understanding of the different types of emerging digital technologies in the Canadian nuclear sector and how they may be used and categorized based on application context. There is also a need to identify any existing assumptions that could differ for the implementation of emerging digital technologies so the current suite of CSA nuclear standards can be assessed and updated as needed to be fit for purpose.

The research conducted for this report included a literature review to provide an overview of the current emerging digital technologies landscape in the Canadian nuclear industry. Example use cases in the nuclear industry were outlined for the following five areas of interest:

  1. Advanced analytical (AA) methods;
  2. Plant information models (PIMs);
  3. Augmented reality (AR) and virtual reality (VR);
  4. Advanced condition monitoring (ACM); and
  5. Cloud computing.

A review of key software categories in relation to existing CSA nuclear standards was also conducted to map the overlap of emerging digital technologies and the software categories within existing applicable standards. This included gathering inputs from members of relevant CSA nuclear program technical committees and from subject matter experts from across the nuclear industry. Input was also gathered on the key sections of standards pertaining to each software category’s interface with emerging digital technology, potential gaps in those interfaces, and methods to address those gaps. Lastly, information was gathered on risks associated with the emerging technologies, and potential changes in assumptions and underlying workflows as a result of technology adoption. This information was gathered through the use of focus groups and through surveys sent to industry experts and technical committee members.

The following key findings were identified through this research:

  1. Further requirements are recommended for the handling of static and dynamic AA models within analytical and operational technology (OT) software, including real-time and process control (RTPC) software;
  2. Clarification is needed on the governing standards and requirements pertaining to the use of information in a PIM for support of operational decision-making;
  3. Reference to standards regarding the development and use of AR and VR applications may help to ensure that verification and human factor considerations are adequately addressed; and
  4. Clarification of the categorization of AA model development software dependent on its use in either a static or dynamic model may facilitate the interpretation of requirements for the development of AA-based software.