SimpleMOC - A performance abstraction for 3D MOC
Author(s)He, Tim; Gunow, Geoffrey Alexander; Tramm, John Robert; Forget, Benoit Robert Yves; Smith, Kord S.
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The method of characteristics (MOC) is a popular method for efficiently solving two-dimensional reactor problems. Extensions to three dimensions have been attempted with mitigated success bringing into question the ability of performing efficient full core three-dimensional (3D) analysis. Although the 3D problem presents many computational difficulties, some simplifications can be made that allow for more efficient computation. In this investigation, we present SimpleMOC, a “mini-app” which mimics the computational performance of a full 3D MOC solver without involving the full physics perspective, allowing for a more straightforward analysis of the computational challenges. A variety of simplifications are implemented that are intended to increase the computational feasibility, including the formation axially-quadratic neutron sources. With the addition of the quadratic approximation to the neutron source, 3D MOC is cast as a CPU-intensive method with the potential for remarkable scalability on next generation computing architectures.
DepartmentMassachusetts Institute of Technology. Department of Nuclear Science and Engineering
Proceedings of ANS MC2015 - Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method
American Nuclear Society (ANS)
Gunow, Geoffrey et al. "SimpleMOC - A PERFORMANCE ABSTRACTION FOR 3D MOC." ANS MC2015 - Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method, 19-23 April, 2015, Nashville, Tennessee, American Nuclear Society, 2015.
Author's final manuscript