skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

This content will become publicly available on December 19, 2019

Title: A quasi-static Monte Carlo algorithm for the simulation of sub-prompt critical transients

Abstract

A pseudo-time-dependent Monte Carlo algorithm suitable for simulating thermal reactor transients with timescales on the order of seconds is presented. An initial experimental implementation has been written into the Monte Carlo Application ToolKit (MCATK) developed at Los Alamos National Laboratory. The algorithm is essentially a combination of the fully time-dependent Monte Carlo algorithm, including the explicit simulation of delayed neutron precursors, and a quasi-static algorithm that does not use the point-kinetics equations. The fully time-dependent calculation is performed for some number of inactive and active micro time steps. The dynamic reactor time constant and delayed neutron precursor production rates are calculated directly from the active cycles, rather than from point-kinetics parameters. These quantities are then used to advance the neutron population and delayed neutron precursors forward in time across a macro time step. As a result, the method is applied to the C5G7-TD benchmark operating in steady state and in transient mode.

Authors:
 [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1494480
Report Number(s):
LA-UR-18-28351
Journal ID: ISSN 0306-4549
Grant/Contract Number:  
89233218CNA000001
Resource Type:
Accepted Manuscript
Journal Name:
Annals of Nuclear Energy (Oxford)
Additional Journal Information:
Journal Name: Annals of Nuclear Energy (Oxford); Journal Volume: 127; Journal Issue: C; Journal ID: ISSN 0306-4549
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS; Monte Carlo Time-dependent Quasi-static Reactor transient Delayed neutrons

Citation Formats

Trahan, Travis John. A quasi-static Monte Carlo algorithm for the simulation of sub-prompt critical transients. United States: N. p., 2018. Web. doi:10.1016/j.anucene.2018.11.055.
Trahan, Travis John. A quasi-static Monte Carlo algorithm for the simulation of sub-prompt critical transients. United States. doi:10.1016/j.anucene.2018.11.055.
Trahan, Travis John. Wed . "A quasi-static Monte Carlo algorithm for the simulation of sub-prompt critical transients". United States. doi:10.1016/j.anucene.2018.11.055.
@article{osti_1494480,
title = {A quasi-static Monte Carlo algorithm for the simulation of sub-prompt critical transients},
author = {Trahan, Travis John},
abstractNote = {A pseudo-time-dependent Monte Carlo algorithm suitable for simulating thermal reactor transients with timescales on the order of seconds is presented. An initial experimental implementation has been written into the Monte Carlo Application ToolKit (MCATK) developed at Los Alamos National Laboratory. The algorithm is essentially a combination of the fully time-dependent Monte Carlo algorithm, including the explicit simulation of delayed neutron precursors, and a quasi-static algorithm that does not use the point-kinetics equations. The fully time-dependent calculation is performed for some number of inactive and active micro time steps. The dynamic reactor time constant and delayed neutron precursor production rates are calculated directly from the active cycles, rather than from point-kinetics parameters. These quantities are then used to advance the neutron population and delayed neutron precursors forward in time across a macro time step. As a result, the method is applied to the C5G7-TD benchmark operating in steady state and in transient mode.},
doi = {10.1016/j.anucene.2018.11.055},
journal = {Annals of Nuclear Energy (Oxford)},
number = C,
volume = 127,
place = {United States},
year = {2018},
month = {12}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on December 19, 2019
Publisher's Version of Record

Save / Share: