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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.
Ilham Variansyah, Ryan G. McClarren
Nuclear Science and Engineering | Volume 196 | Number 11 | November 2022 | Pages 1280-1305
Technical Paper | doi.org/10.1080/00295639.2022.2091906
Articles are hosted by Taylor and Francis Online.
An extensive study of population control techniques (PCTs) for time-dependent and eigenvalue Monte Carlo (MC) neutron transport calculations is presented. We define PCT as a technique that takes a censused population and returns a controlled, unbiased population. A new perspective based on an abstraction of particle census and population control is explored, paving the way to improved understanding and application of the concepts. Five distinct PCTs identified from the literature are reviewed: simple sampling, splitting-roulette (SR), combing (CO), modified combing, and duplicate-discard (DD). A theoretical analysis of how much uncertainty is introduced to a population by each PCT is presented. Parallel algorithms for the PCTs, applicable for both time-dependent and eigenvalue MC simulations, are proposed. The relative performance of the PCTs based on run time and tally mean error or standard deviation is assessed by solving time-dependent and eigenvalue test problems. It is found that SR and CO are equally the most performing techniques, closely followed by DD.
