NDE & NDT | DIGITAL TRANSFORMATION Integrating AI into the NDE inspection process will
increase reliability and efficiency by helping inspection professionals make well-informed, data-driven decisions. Recently, EPRI conducted NDE field trials on partial penetration J-groove welds and dissimilar metal welds (DMWs) at various nuclear stations. The AI programme collected a vast amount of data and raised flags for further review by examiners. AI automated much of the confirmation process and shaved off substantial time throughout this process. In one instance, AI cut the data analysis process down from four days to just four hours without loss of assessment integrity. This advancement can enhance nuclear safety by allowing examiners to focus more time assessing areas of welds that require a more detailed evaluation. It can also ease staffing issues for NDE personnel with the added advantage of the AI program’s ability to significantly shorten inspection time. For example, as a part of its training for a Reactor
Vessel Upper Head (RVUH) application, an AI model was fed a large volume of UT data from a two-unit PWR that had been slated for decommissioning. Experts instructed the model to evaluate the data and alert the examiner if further review and consideration were needed. Although most of the data volume yielded no flagged indications of interest, the AI tool was able to identify benign conditions such as fabrication-related responses that require review from a qualified examiner to confirm their status. As the AI application performed the monotonous task of searching through all the UT data looking for indications of interest, the UT examiners could spend more time evaluating each pre-identified indication by comparing the response in the new UT data against the long history of archived data files from the previous examinations. If any changes to the UT indication were noted to have occurred over time, any changes to the UT responses were further scrutinised as potentially originating from service-induced degradation. Such a detailed historical comparison requires significant time, and the use of AI provided time savings in other areas that then afforded examiners the ability to expend this additional time where it mattered the most. In the future, experts plan to develop an AI program for manual and automated PAUT inspections that will be more heavily involved and complex with the ability to evaluate the data in real time.
As experts address areas of improvement for Reactor
Vessel Upper Head AI tools, new program field trials for AI applications for other nuclear components have already begun to launch. Experts are now exploring a comparable program development and testing process for dissimilar metal welds that may enable them to build an AI application to examine core shroud welds in BWRs and core barrel welds in PWRs. Through these field trials, the industry is seeking a
way to close the technology gap. Online monitoring will perhaps then be able to replace NDE data collection where it is unsafe for human inspectors to evaluate the reactor components. With permanent sensors, examiners can continuously monitor for defects in the component and track flaws that might trigger a need for repairs. In addition to AI, uncrewed inspection systems, such
as drones and permanent sensors, are emerging automation tools. By integrating all these advanced technologies into NDE inspection, examiners can use remote inspection for a potentially fully automated analysis. Automation is the key to efficiency and reliability. It can also improve the quality of data and lower the cost of inspections.
Future evolution of NDE As countries focus their attention on advancing nuclear power generation capabilities, it will become increasingly important for engineers to invest in effective and cost- efficient advanced monitoring and sensor technology. The integration of automation into NDE techniques will continue to develop across the nuclear energy industry. Although experts are still working out the kinks of using advanced technologies, it is paramount that inspection methodologies evolve as surrounding technologies evolve to ensure reliable and cost-effective asset integrity evaluation and monitoring. The success of today’s NDE digital transformation will also rely on comprehensive training for examiners to become proficient in the latest and newest tools and technology. Given nuclear plant inspections continue to evolve from
the cumbersome original tools to increasingly advanced, powerful, and efficient new toolsets, the transformation of NDE will continue to ensure the safe and sustainable future of nuclear energy. ■
Above: Safety-related reactor systems are required to undergo regular inspections, in addition to routine assessments of primary reactor components and containment vessels
30 | March 2024 |
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