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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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High temperature fission chambers engineered for AMR/SMR safety and performance
As the global energy landscape shifts towards safer, smaller, and more flexible nuclear power, Small Modular Reactors (SMRs) and Gen. IV* technologies are at the forefront of innovation. These advanced designs pose new challenges in size, efficiency, and operating environment that traditional instrumentation and control solutions aren’t always designed to handle.
Andrew Young, Michael Devereux, Blair Brown, Bruce Stephen, Graeme West, Stephen McArthur
Nuclear Technology | Volume 210 | Number 12 | December 2024 | Pages 2362-2372
Research Article | doi.org/10.1080/00295450.2024.2342187
Articles are hosted by Taylor and Francis Online.
To function effectively, nuclear power plants rely on the effective filtration of air, water, and process fluids, examples of which include inlet sea water, reactor coolant, plant drinking water, and moderator purification. Filtration assets degrade over time, which impairs their filtering performance and reduces the flow rate. Being able to determine the remaining useful life (RUL) of a filter could result in benefits, particularly when moving from a time-based to a condition-based maintenance strategy that would optimize the filter replacement procedure and reduce early replacement of filters that are still fit for purpose. For many filter applications, a time-based strategy is sufficient. For strategically important assets, such as fueling machines, there are benefits to be gained from the development of predictive maintenance strategies.
In this paper, we propose a predictive condition-based strategy using differential pressure data as a proxy for filter health. The key objective in this work was the creation of a model that could predict a filter asset RUL. The differential pressure for 7 to 14 days is predicted by a heuristic-based regression model of the history of each filter. This approach has been demonstrated using a civil nuclear generation application but could be applied to wider applications. While this model is still undergoing on-site evaluation, it has been estimated that there will be an operationally significant lifetime cost reduction.