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Title: On-the-Fly Generation of Differential Resonance Scattering Probability Distribution Functions for Monte Carlo Codes

Abstract

Current Monte Carlo codes use one of three models: (1) the asymptotic scattering model, (2) the free gas scattering model, or (3) the S(α,β) model, depending on the neutron energy and the specific Monte Carlo code. This thesis addresses the consequences of using the free gas scattering model, which assumes that the neutron interacts with atoms in thermal motion in a monatomic gas in thermal equilibrium at material temperature, T. Most importantly, the free gas model assumes the scattering cross section is constant over the neutron energy range, which is usually a good approximation for light nuclei, but not for heavy nuclei where the scattering cross section may have several resonances in the epithermal region. Several researchers in the field have shown that the exact resonance scattering model is temperaturedependent, and neglecting the resonances in the lower epithermal range can under-predict resonance absorption due to the upscattering phenomenon mentioned above, leading to an over-prediction of keff by several hundred pcm. Existing methods to address this issue involve changing the neutron weights or implementing an extra rejection scheme in the free gas sampling scheme, and these all involve performing the collision analysis in the center-of-mass frame, followed by a conversion backmore » to the laboratory frame to continue the random walk of the neutron. The goal of this paper was to develop a sampling methodology that (1) accounted for the energydependent scattering cross sections in the collision analysis and (2) was performed in the laboratory frame,avoiding the conversion to the center-of-mass frame. The energy dependence of the scattering cross section was modeled with even-ordered polynomials (2nd and 4th order) to approximate the scattering cross section in Blackshaw’s equations for the moments of the differential scattering PDFs. These moments were used to sample the outgoing neutron speed and angle in the laboratory frame on-the-fly during the random walk of the neutron. Results for criticality studies on fuel pin and fuel assembly calculations using methods developed in this dissertation showed very close comparison to results using the reference Dopplerbroadened rejection correction (DBRC) scheme.« less

Authors:
 [1];  [1]
  1. Univ. of Michigan, Ann Arbor, MI (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1394437
Grant/Contract Number:
AC05-00OR22725
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Nuclear Science and Engineering
Additional Journal Information:
Journal Volume: 187; Journal Issue: 1; Journal ID: ISSN 0029-5639
Publisher:
American Nuclear Society - Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; Resonance upscattering; Monte Carlo; free gas scattering model

Citation Formats

Davidson, Eva E., and Martin, William R. On-the-Fly Generation of Differential Resonance Scattering Probability Distribution Functions for Monte Carlo Codes. United States: N. p., 2017. Web. doi:10.1080/00295639.2017.1294931.
Davidson, Eva E., & Martin, William R. On-the-Fly Generation of Differential Resonance Scattering Probability Distribution Functions for Monte Carlo Codes. United States. doi:10.1080/00295639.2017.1294931.
Davidson, Eva E., and Martin, William R. Fri . "On-the-Fly Generation of Differential Resonance Scattering Probability Distribution Functions for Monte Carlo Codes". United States. doi:10.1080/00295639.2017.1294931.
@article{osti_1394437,
title = {On-the-Fly Generation of Differential Resonance Scattering Probability Distribution Functions for Monte Carlo Codes},
author = {Davidson, Eva E. and Martin, William R.},
abstractNote = {Current Monte Carlo codes use one of three models: (1) the asymptotic scattering model, (2) the free gas scattering model, or (3) the S(α,β) model, depending on the neutron energy and the specific Monte Carlo code. This thesis addresses the consequences of using the free gas scattering model, which assumes that the neutron interacts with atoms in thermal motion in a monatomic gas in thermal equilibrium at material temperature, T. Most importantly, the free gas model assumes the scattering cross section is constant over the neutron energy range, which is usually a good approximation for light nuclei, but not for heavy nuclei where the scattering cross section may have several resonances in the epithermal region. Several researchers in the field have shown that the exact resonance scattering model is temperaturedependent, and neglecting the resonances in the lower epithermal range can under-predict resonance absorption due to the upscattering phenomenon mentioned above, leading to an over-prediction of keff by several hundred pcm. Existing methods to address this issue involve changing the neutron weights or implementing an extra rejection scheme in the free gas sampling scheme, and these all involve performing the collision analysis in the center-of-mass frame, followed by a conversion back to the laboratory frame to continue the random walk of the neutron. The goal of this paper was to develop a sampling methodology that (1) accounted for the energydependent scattering cross sections in the collision analysis and (2) was performed in the laboratory frame,avoiding the conversion to the center-of-mass frame. The energy dependence of the scattering cross section was modeled with even-ordered polynomials (2nd and 4th order) to approximate the scattering cross section in Blackshaw’s equations for the moments of the differential scattering PDFs. These moments were used to sample the outgoing neutron speed and angle in the laboratory frame on-the-fly during the random walk of the neutron. Results for criticality studies on fuel pin and fuel assembly calculations using methods developed in this dissertation showed very close comparison to results using the reference Dopplerbroadened rejection correction (DBRC) scheme.},
doi = {10.1080/00295639.2017.1294931},
journal = {Nuclear Science and Engineering},
number = 1,
volume = 187,
place = {United States},
year = {Fri May 26 00:00:00 EDT 2017},
month = {Fri May 26 00:00:00 EDT 2017}
}

Journal Article:
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  • Current Monte Carlo codes use one of three models to model neutron scattering in the epithermal energy range: (1) the asymptotic scattering model, (2) the free gas scattering model, or (3) the S({alpha},{beta}) model, depending on the neutron energy and the specific Monte Carlo code. The free gas scattering model assumes the scattering cross section is constant over the neutron energy range, which is usually a good approximation for light nuclei, but not for heavy nuclei where the scattering cross section may have several resonances in the epithermal region. Several researchers in the field have shown that using the freemore » gas scattering model in the vicinity of the resonances in the lower epithermal range can under-predict resonance absorption due to the up-scattering phenomenon. Existing methods all involve performing the collision analysis in the center-of-mass frame, followed by a conversion back to the laboratory frame. In this paper, we will present a new sampling methodology that (1) accounts for the energy-dependent scattering cross sections in the collision analysis and (2) acts in the laboratory frame, avoiding the conversion to the center-of-mass frame. The energy dependence of the scattering cross section was modeled with even-ordered polynomials to approximate the scattering cross section in Blackshaw's equations for the moments of the differential scattering PDFs. These moments were used to sample the outgoing neutron speed and angle in the laboratory frame on-the-fly during the random walk of the neutron. Results for criticality studies on fuel pin and fuel assembly calculations using these methods showed very close comparison to results using the reference Doppler-broadened rejection correction (DBRC) scheme. (authors)« less
  • In this paper, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challengemore » in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.« less
  • We develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challenge in estimating CDFsmore » is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. Additionally, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. Furthermore, the numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.« less