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August 24–27, 2026
Dallas, TX|Hilton Anatole
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Long-term strategy calls for up to 10 new reactors in Canada
Canada has launched a Nuclear Energy Strategy, a long-term vision of its nuclear power potential that includes plans to deploy up to 10 new large-scale reactors in the country by 2040.
The June 22 announcement, along with ongoing projects at Darlington and Bruce Power, further confirm Canada's ambitions to expand its nuclear power presence not just domestically but also abroad. Four pillars stand at the heart of the country’s Nuclear Energy Strategy: new nuclear builds in Canada, maintaining its status as a top nuclear supplier and exporter, expanding uranium production, and continuing nuclear fission and fusion innovations.
Jin Li, Volkan Seker, Andrew Ward, Thomas Downar
Nuclear Science and Engineering | Volume 199 | Number 5 | May 2025 | Pages 772-792
Research Article | doi.org/10.1080/00295639.2024.2397621
Articles are hosted by Taylor and Francis Online.
Monte Carlo codes have become increasingly popular for generating homogenized few-group cross-section data, especially for advanced reactor designs that have complex geometries and nontraditional compositions. However, the stochastic nature of Monte Carlo processes has the potential to introduce additional statistical uncertainties in the overall uncertainty in the prediction of core behavior. The work performed in this research quantified the additional uncertainty introduced by the use of Monte Carlo multigroup cross sections into the analysis of graphite-moderated pebble bed reactors. In this research, the objective was achieved by performing uncertainty quantification for the key output parameters in deterministic steady-state and transient safety calculations. The results show that when the homogenized multigroup cross sections are generated with a sufficient number of neutron histories in the Monte Carlo calculation, the uncertainties in the subsequent deterministic simulations caused by the Monte Carlo cross-section uncertainty are negligible compared to the contributions from the uncertainties of other input parameters.