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North American construction is back—smaller and faster—at OPG’s Darlington
“The nuclear renaissance is real here,” said Ontario Power Generation’s Subo Sinnathamby on May 8, one year to the day after OPG secured a final investment decision to build the first of four planned BWRX-300 reactors at its Darlington nuclear power plant, and shortly after the new reactor’s foundation was lifted into place. “We got our license to construct in April and our [final investment decision] in May, and we’ve been off to the races since.”
Matthew Ellis, Derek Gaston, Benoit Forget, Kord Smith
Nuclear Science and Engineering | Volume 185 | Number 1 | January 2017 | Pages 184-193
Technical Paper | doi.org/10.13182/NSE16-26
Articles are hosted by Taylor and Francis Online.
In recent years, the use of Monte Carlo methods for modeling reactors has become feasible due to the increasing availability of massively parallel computer systems. One of the primary challenges yet to be fully resolved, however, is the efficient and accurate inclusion of multiphysics feedback in Monte Carlo simulations. The research in this paper presents a preliminary coupling of the open-source Monte Carlo code OpenMC with the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE). The coupling of OpenMC and MOOSE will be used to investigate efficient and accurate numerical methods needed to include multiphysics feedback in Monte Carlo codes. An investigation into the sensitivity of Doppler feedback to fuel temperature approximations using a two-dimensional 17 × 17 pressurized water reactor (PWR) fuel assembly is presented in this paper. The results show a functioning multiphysics coupling between OpenMC and MOOSE. The coupling utilizes functional expansion tallies to transfer accurately and efficiently pin power distributions tallied in OpenMC to unstructured finite element meshes used in MOOSE. The two-dimensional PWR fuel assembly case also demonstrates that for a simplified model, the pin-by-pin Doppler feedback can be adequately replicated by scaling a representative pin based on pin relative powers.