|
|
|
|
LEADER |
01861 am a22002533u 4500 |
001 |
118451 |
042 |
|
|
|a dc
|
100 |
1 |
0 |
|a Nowak, Michel
|e author
|
100 |
1 |
0 |
|a Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
|e contributor
|
100 |
1 |
0 |
|a Miao, Jilang
|e contributor
|
100 |
1 |
0 |
|a Forget, Benoit Robert Yves
|e contributor
|
100 |
1 |
0 |
|a Smith, Kord S.
|e contributor
|
700 |
1 |
0 |
|a Dumonteil, Eric
|e author
|
700 |
1 |
0 |
|a Onillon, Anthony
|e author
|
700 |
1 |
0 |
|a Zoia, Andrea
|e author
|
700 |
1 |
0 |
|a Miao, Jilang
|e author
|
700 |
1 |
0 |
|a Forget, Benoit Robert Yves
|e author
|
700 |
1 |
0 |
|a Smith, Kord S.
|e author
|
245 |
0 |
0 |
|a Monte Carlo power iteration: Entropy and spatial correlations
|
260 |
|
|
|b Elsevier BV,
|c 2018-10-11T20:04:11Z.
|
856 |
|
|
|z Get fulltext
|u http://hdl.handle.net/1721.1/118451
|
520 |
|
|
|a The behavior of Monte Carlo criticality simulations is often assessed by examining the convergence of the so-called entropy function. In this work, we shall show that the entropy function may lead to a misleading interpretation, and that potential issues occur when spatial correlations induced by fission events are important. We will support our analysis by examining the higher-order moments of the entropy function and the center of mass of the neutron population. Within the framework of a simplified model based on branching processes, we will relate the behavior of the spatial fluctuations of the fission chains to the key parameters of the simulated system, namely, the number of particles per generation, the reactor size and the migration area. Numerical simulations of a fuel rod and of a whole core suggest that the obtained results are quite general and hold true also for real-world applications. Keywords: Entropy; Clustering; Power iteration; OpenMC; Tripoli-4®
|
655 |
7 |
|
|a Article
|
773 |
|
|
|t Annals of Nuclear Energy
|