Human-centric AI for engineering design changes in the nuclear industry

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As part of the through-life operation of nuclear power plants, sub-components and systems of the plant need replacing or upgrading by a number of drivers such as failures, obsolescence and efficiency improvements. The design and implementation of replacements is a time consuming and manually intensive process which requires information to be drawn from a wide variety of sources, as well as from previous operational experience. The integration of range of AI techniques could lead to automation and augmentation of the design process to deliver significant efficiency improvements and remove costly non-optimal redesigns. This will require research focused on the combination of: knowledge-based systems, case based reasoning and human-centric AI. This will require novel approaches to formal knowledge capture and representation, along with case-based reasoning techniques, to support the retention and re-use of key design decisions and lessons learned. This will include the development of a generic ontology for exchange and fusion of information between a number of systems and resources, such as safety standards, change request logs, design documents and station drawings. Human-centric AI is focused on how the human operator interacts effectively with the artificial intelligence algorithms, and this will be a key element of the PhD. Within the nuclear industry where there is a significant requirement for transparency and auditability of any decisions made in this regulated environment. Therefore, the correct interaction, explanations and justifications being made available to the user is critical. This research will create a novel framework of AI techniques which tackle the issues, and deliver design advice and can be ultimately built into an automated decision support system.