Issue |
EPJ Web Conf.
Volume 302, 2024
Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo (SNA + MC 2024)
|
|
---|---|---|
Article Number | 09005 | |
Number of page(s) | 10 | |
Section | Variance Reduction Techniques | |
DOI | https://doi.org/10.1051/epjconf/202430209005 | |
Published online | 15 October 2024 |
https://doi.org/10.1051/epjconf/202430209005
Branchless Collisions for Reducing Spatial Correlations in Continuous Energy Monte Carlo Power Iteration
1 Engineering Department, University of Cambridge, Trumpington St., Cambridge CB2 1PZ, UK
2 Department of Mechanical, Aerospace, and Nuclear Engineering, Rensselaer Polytechnic Institute, 110 8th St., Troy, NY, USA
* e-mail: tlfab2@cam.ac.uk
** e-mail: belanh2@rpi.edu
Published online: 15 October 2024
Branchless collisions are customarily used in time-dependent Monte Carlo simulations and have been recently introduced in Monte Carlo power iteration. Previous works have shown that branchless collisions are very efficient in quenching spatial correlations in a multi-group framework, and a preliminary work was previously conducted in order to extend the use of branchless collisions to continuous energy. In that work, two variants of branchless collisions were introduced: branchless on the material, and branchless on the isotope. In this work, we analyse in depth the effect of using branchless collisions in realistic systems on spatial correlations, and we show that performing branchless collisions on the material consistently results in a smaller effect of spatial correlations than when using a standard branching collision algorithm.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.