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Growth beyond megawatts
Hash Hashemianpresident@ans.org
When talking about growth in the nuclear sector, there can be a somewhat myopic focus on increasing capacity from year to year. Certainly, we all feel a degree of excitement when new projects are announced, and such announcements are undoubtedly a reflection of growth in the field, but it’s important to keep in mind that growth in nuclear has many metrics and takes many forms.
Nuclear growth—beyond megawatts—also takes the form of increasing international engagement. That engagement looks like newcomer countries building their nuclear sectors for the first time. It also looks like countries with established nuclear sectors deepening their connections and collaborations. This is one of the reasons I have been focused throughout my presidency on bringing more international members and organizations into the fold of the American Nuclear Society.
J. Rogers, Y. Parlatan
Nuclear Science and Engineering | Volume 199 | Number 12 | December 2025 | Pages 2055-2065
Research Article | doi.org/10.1080/00295639.2025.2462895
Articles are hosted by Taylor and Francis Online.
This paper describes the development of a statistical model of uncertainty in channel powers predicted for a 480-channel CANada Deuterium Uranium (CANDU) reactor. It is expressed as the sum of ripple prediction uncertainty and reactor power uncertainty. Ripples are ratios of instantaneous channel powers (prorated to 100% of full power) to reference channel powers. The ripple prediction uncertainty model is a multivariate normal distribution whose covariance matrix captures a unique variance for every channel as well as a unique covariance between every pair of channels. Reactor power uncertainty is common to all 480 channels.
Central to this work is the distinction between apparent uncertainty, measurement uncertainty, and prediction uncertainty. Ripple prediction uncertainty is quantified by removing the contribution of ripple measurement uncertainty to ripple apparent uncertainty (differences between computer code–predicted ripples and measured ripples). This is done because measurement uncertainty causes apparent uncertainty to exceed prediction uncertainty. Measurement uncertainty is quantified using a novel approach referred to as the sister channel approach with time shifting. This approach uses differences between measured ripples in sister channels to quantify actual measurement uncertainty. The time-shifting aspect of the approach accounts for the fact that true ripples in sister channels are not identical at the same time, mainly because sister channels and their neighboring channels are refueled at different times.