ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
Mar 2026
Jan 2026
Latest Journal Issues
Nuclear Science and Engineering
April 2026
Nuclear Technology
February 2026
Fusion Science and Technology
Latest News
State news: Microreactors, legislation, executive orders, and more
Discussions and actions on nuclear energy have penetrated several state capitol buildings, congressional hearings, and industry gatherings across the United States this month, including in Alaska, Connecticut, Louisiana, Massachusetts, Minnesota, and New York.
N. Odry, J.-J. Lautard, J.-F. Vidal, G. Rimpault
Nuclear Science and Engineering | Volume 187 | Number 3 | September 2017 | Pages 240-253
Technical Paper | doi.org/10.1080/00295639.2017.1320891
Articles are hosted by Taylor and Francis Online.
An iterative domain decomposition method (DDM) is implemented inside the APOLLO3 Sn transport core solver MINARET. Based on a block-Jacobi algorithm, the method inherently suffers a convergence penalty in terms of both computing time and number of iterations. An acceleration method has to be developed in order to overcome this difficulty. This paper investigates a nonlinear coarse mesh rebalance (CMR) method that favors the way information propagates through the core when domain decomposition is used. The fundamental idea involves updating each subdomain boundary condition thanks to a core-sized low-order calculation on a coarse spatial mesh. The numerical convergence is sped up. Performances are meeting the expectations since the CMR acceleration systematically succeeds in overbalancing the domain decomposition additional cost. The aim of such a DDM + CMR algorithm is eventually to introduce more parallelism when solving the spatial transport equation. Nevertheless, parallel computing is not addressed in this paper.