Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations
Abstract
The method of successive generations used in Monte Carlo simulations of nuclear reactor models is known to suffer from intergenerational correlation between the spatial locations of fission sites. One consequence of the spatial correlation is that the convergence rate of the variance of the mean for a tally becomes worse than O(N–1). In this work, we consider how the true variance can be minimized given a total amount of work available as a function of the number of source particles per generation, the number of active/discarded generations, and the number of independent simulations. We demonstrate through both analysis and simulation that under certain conditions the solution time for highly correlated reactor problems may be significantly reduced either by running an ensemble of multiple independent simulations or simply by increasing the generation size to the extent that it is practical. However, if too many simulations or too large a generation size is used, the large fraction of source particles discarded can result in an increase in variance. We also show that there is a strong incentive to reduce the number of generations discarded through some source convergence acceleration technique. Furthermore, we discuss the efficient execution of large simulations on a parallelmore »
 Authors:
 Argonne National Laboratory, Mathematics and Computer Science Division, 9700 South Cass Avenue, Lemont, Illinois 60439
 Publication Date:
 Research Org.:
 Argonne National Lab. (ANL), Argonne, IL (United States)
 Sponsoring Org.:
 USDOE Office of Science (SC); USDOE National Nuclear Security Administration (NNSA)
 OSTI Identifier:
 1393143
 DOE Contract Number:
 AC0206CH11357
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Nuclear Science and Engineering; Journal Volume: 188; Journal Issue: 1
 Country of Publication:
 United States
 Language:
 English
 Subject:
 Monte Carlo; correlation; ensemble
Citation Formats
Romano, Paul K., Lund, Amanda L., and Siegel, Andrew R. Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations. United States: N. p., 2017.
Web. doi:10.1080/00295639.2017.1340692.
Romano, Paul K., Lund, Amanda L., & Siegel, Andrew R. Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations. United States. doi:10.1080/00295639.2017.1340692.
Romano, Paul K., Lund, Amanda L., and Siegel, Andrew R. 2017.
"Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations". United States.
doi:10.1080/00295639.2017.1340692.
@article{osti_1393143,
title = {Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations},
author = {Romano, Paul K. and Lund, Amanda L. and Siegel, Andrew R.},
abstractNote = {The method of successive generations used in Monte Carlo simulations of nuclear reactor models is known to suffer from intergenerational correlation between the spatial locations of fission sites. One consequence of the spatial correlation is that the convergence rate of the variance of the mean for a tally becomes worse than O(N–1). In this work, we consider how the true variance can be minimized given a total amount of work available as a function of the number of source particles per generation, the number of active/discarded generations, and the number of independent simulations. We demonstrate through both analysis and simulation that under certain conditions the solution time for highly correlated reactor problems may be significantly reduced either by running an ensemble of multiple independent simulations or simply by increasing the generation size to the extent that it is practical. However, if too many simulations or too large a generation size is used, the large fraction of source particles discarded can result in an increase in variance. We also show that there is a strong incentive to reduce the number of generations discarded through some source convergence acceleration technique. Furthermore, we discuss the efficient execution of large simulations on a parallel computer; we argue that several practical considerations favor using an ensemble of independent simulations over a single simulation with very large generation size.},
doi = {10.1080/00295639.2017.1340692},
journal = {Nuclear Science and Engineering},
number = 1,
volume = 188,
place = {United States},
year = 2017,
month = 6
}

No abstract prepared.

Iterated finiteorbit Monte Carlo simulations with fullwave fields for modeling tokamak ion cyclotron resonance frequency wave heating experiments
The fivedimensional finiteorbit Monte Carlo code ORBITRF [M. Choi , Phys. Plasmas 12, 1 (2005)] is successfully coupled with the twodimensional fullwave code allorders spectral algorithm (AORSA) [E. F. Jaeger , Phys. Plasmas 13, 056101 (2006)] in a selfconsistent way to achieve improved predictive modeling for ion cyclotron resonance frequency (ICRF) wave heating experiments in present fusion devices and future ITER [R. Aymar , Nucl. Fusion 41, 1301 (2001)]. The ORBITRF/AORSA simulations reproduce fastion spectra and spatial profiles qualitatively consistent with fast ion Dalpha [W. W. Heidbrink , Plasma Phys. Controlled Fusion 49, 1457 (2007)] spectroscopic data in both DIIIDmore » 
Iterated finiteorbit Monte Carlo simulations with fullwave fields for modeling tokamak ion cyclotron resonance frequency wave heating experiments
The fivedimensional finiteorbit Monte Carlo code ORBITRF[M. Choi et al., Phys. Plasmas 12, 1 (2005)] is successfully coupled with the twodimensional fullwave code allorders spectral algorithm (AORSA) [E. F. Jaeger et al., Phys. Plasmas 13, 056101 (2006)] in a selfconsistent way to achieve improved predictive modeling for ion cyclotron resonance frequency (ICRF) wave heating experiments in present fusion devices and future ITER [R. Aymar et al., Nucl. Fusion 41, 1301 (2001)]. The ORBITRF/AORSA simulations reproduce fastion spectra and spatial profiles qualitatively consistent with fast ion Dalpha [W. W. Heidbrink et al., Plasma Phys. Controlled Fusion 49, 1457 (2007)] spectroscopic datamore »