Deterministically estimated fission source distributions for Monte Carlo k-eigenvalue problems
Journal Article
·
· Annals of Nuclear Energy (Oxford)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
The standard Monte Carlo (MC) k-eigenvalue algorithm involves iteratively converging the fission source distribution using a series of potentially time-consuming inactive cycles before quantities of interest can be tallied. One strategy for reducing the computational time requirements of these inactive cycles is the Sourcerer method, in which a deterministic eigenvalue calculation is performed to obtain an improved initial guess for the fission source distribution. This method has been implemented in the Exnihilo software suite within SCALE using the SPNSPN or SNSN solvers in Denovo and the Shift MC code. The efficacy of this method is assessed with different Denovo solution parameters for a series of typical k-eigenvalue problems including small criticality benchmarks, full-core reactors, and a fuel cask. Here it is found that, in most cases, when a large number of histories per cycle are required to obtain a detailed flux distribution, the Sourcerer method can be used to reduce the computational time requirements of the inactive cycles.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
- Sponsoring Organization:
- USDOE; USDOE Office of Science (SC); USNRC
- Grant/Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1435255
- Alternate ID(s):
- OSTI ID: 1548445
- Journal Information:
- Annals of Nuclear Energy (Oxford), Journal Name: Annals of Nuclear Energy (Oxford) Journal Issue: C Vol. 119; ISSN 0306-4549
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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