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 February 7, 2021

Title: Application of Neutron Multiplicity Counting Experiments to Optimal Cross-Section Adjustments

Abstract

This paper presents the first application of model calibration to neutron multiplicity counting (NMC) experiments for cross-section optimization that is informed by adjoint-based sensitivity analysis (SA) and first-order uncertainty quantification (UQ). We summarize previous work on SA applied to NMC and describe notable modifications and additions. We give the procedure for first-order UQ and Bayesian-inference-based parameter estimation (PE). We then discuss model calibration applied to NMC of a 4.5-kg sphere of weapons-grade, alpha-phase plutonium metal (the BeRP ball) with the nPod neutron multiplicity counter. For the BeRP ball in bare and polyethylene-reflected configurations, we discuss the sensitivity of the first- and second-moment detector responses (i.e., first and second moments of the NMC distribution, respectively) to the cross sections. We describe the sources of uncertainty in the measured and simulated responses. Specifically, uncertainty in the measured responses is due to both random and systematic sources. Uncertainty in the simulated responses is due to the cross-section covariances. We describe in detail the adjustment to the cross sections and cross-section covariances due to the optimization. Due to the contribution of systematic uncertainties to the measured response uncertainties, the adjustment to the cross sections is similar in trend but larger in magnitude compared tomore » that recommended by previous work. We compare the measured responses to responses simulated with nominal and optimized cross sections, demonstrating that the best-estimate cross sections produce simulations of NMC experiments that are more accurate with reduced uncertainty.« less

Authors:
ORCiD logo [1];  [1];  [2]
  1. North Carolina State Univ., Raleigh, NC (United States)
  2. 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 National Nuclear Security Administration (NNSA), Office of Nonproliferation and Verification Research and Development (NA-22)
OSTI Identifier:
1671082
Report Number(s):
LA-UR-19-29039
Journal ID: ISSN 0029-5639
Grant/Contract Number:  
89233218CNA000001
Resource Type:
Accepted Manuscript
Journal Name:
Nuclear Science and Engineering
Additional Journal Information:
Journal Volume: 194; Journal Issue: 4; Journal ID: ISSN 0029-5639
Publisher:
American Nuclear Society - Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
Optimal cross section adjustment; neutron multiplicity counting; adjoint-based sensitivity analysis

Citation Formats

Clark, Alexander R., Mattingly, John, and Favorite, Jeffrey A. Application of Neutron Multiplicity Counting Experiments to Optimal Cross-Section Adjustments. United States: N. p., 2020. Web. doi:10.1080/00295639.2019.1698267.
Clark, Alexander R., Mattingly, John, & Favorite, Jeffrey A. Application of Neutron Multiplicity Counting Experiments to Optimal Cross-Section Adjustments. United States. doi:10.1080/00295639.2019.1698267.
Clark, Alexander R., Mattingly, John, and Favorite, Jeffrey A. Fri . "Application of Neutron Multiplicity Counting Experiments to Optimal Cross-Section Adjustments". United States. doi:10.1080/00295639.2019.1698267.
@article{osti_1671082,
title = {Application of Neutron Multiplicity Counting Experiments to Optimal Cross-Section Adjustments},
author = {Clark, Alexander R. and Mattingly, John and Favorite, Jeffrey A.},
abstractNote = {This paper presents the first application of model calibration to neutron multiplicity counting (NMC) experiments for cross-section optimization that is informed by adjoint-based sensitivity analysis (SA) and first-order uncertainty quantification (UQ). We summarize previous work on SA applied to NMC and describe notable modifications and additions. We give the procedure for first-order UQ and Bayesian-inference-based parameter estimation (PE). We then discuss model calibration applied to NMC of a 4.5-kg sphere of weapons-grade, alpha-phase plutonium metal (the BeRP ball) with the nPod neutron multiplicity counter. For the BeRP ball in bare and polyethylene-reflected configurations, we discuss the sensitivity of the first- and second-moment detector responses (i.e., first and second moments of the NMC distribution, respectively) to the cross sections. We describe the sources of uncertainty in the measured and simulated responses. Specifically, uncertainty in the measured responses is due to both random and systematic sources. Uncertainty in the simulated responses is due to the cross-section covariances. We describe in detail the adjustment to the cross sections and cross-section covariances due to the optimization. Due to the contribution of systematic uncertainties to the measured response uncertainties, the adjustment to the cross sections is similar in trend but larger in magnitude compared to that recommended by previous work. We compare the measured responses to responses simulated with nominal and optimized cross sections, demonstrating that the best-estimate cross sections produce simulations of NMC experiments that are more accurate with reduced uncertainty.},
doi = {10.1080/00295639.2019.1698267},
journal = {Nuclear Science and Engineering},
number = 4,
volume = 194,
place = {United States},
year = {2020},
month = {2}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on February 7, 2021
Publisher's Version of Record

Save / Share:

Works referenced in this record:

SENSMG: First-Order Sensitivities of Neutron Reaction Rates, Reaction-Rate Ratios, Leakage, k eff , and α Using PARTISN
journal, July 2018


Neutron multiplication measurements using moments of the neutron counting distribution
journal, October 1983

  • Robba, A. A.; Dowdy, E. J.; Atwater, H. F.
  • Nuclear Instruments and Methods in Physics Research, Vol. 215, Issue 3
  • DOI: 10.1016/0167-5087(83)90481-7

Denovo: A New Three-Dimensional Parallel Discrete Ordinates Code in SCALE
journal, August 2010

  • Evans, Thomas M.; Stafford, Alissa S.; Slaybaugh, Rachel N.
  • Nuclear Technology, Vol. 171, Issue 2
  • DOI: 10.13182/NT171-171

Best-Estimate Model Calibration and Prediction through Experimental Data Assimilation—I: Mathematical Framework
journal, May 2010

  • Cacuci, Dan G.; Ionescu-Bujor, Mihaela
  • Nuclear Science and Engineering, Vol. 165, Issue 1
  • DOI: 10.13182/NSE09-37B

Stochastic Neutron Transport Theory: Neutron Counting Statistics in Nuclear Assemblies
journal, February 1987

  • Muñoz-Cobo, Jose-Luis; Perez, R. B.; Verdu, Gumersindo
  • Nuclear Science and Engineering, Vol. 95, Issue 2
  • DOI: 10.13182/NSE95-83

Evaluated Nuclear Data Covariances: The Journey From ENDF/B-VII.0 to ENDF/B-VII.1
journal, December 2011


ENDF/B-VII.1 Nuclear Data for Science and Technology: Cross Sections, Covariances, Fission Product Yields and Decay Data
journal, December 2011


Sensitivity Analysis and Data Assimilation in a Subcritical Plutonium Metal Benchmark
journal, March 2014

  • Evans, Richard T.; Mattingly, John K.; Cacuci, Dan G.
  • Nuclear Science and Engineering, Vol. 176, Issue 3
  • DOI: 10.13182/NSE13-24

Adjoint-Based Sensitivity and Uncertainty Analysis for Density and Composition: A User’s Guide
journal, March 2017

  • Favorite, Jeffrey A.; Perkó, Zoltán; Kiedrowski, Brian C.
  • Nuclear Science and Engineering, Vol. 185, Issue 3
  • DOI: 10.1080/00295639.2016.1272990

Computational Evaluation of Neutron Multiplicity Measurements of Polyethylene-Reflected Plutonium Metal
journal, February 2014

  • Miller, E. C.; Mattingly, J. K.; Clarke, S. D.
  • Nuclear Science and Engineering, Vol. 176, Issue 2
  • DOI: 10.13182/NSE12-53

Statistical Theory of Fission Chains and Generalized Poisson Neutron Counting Distributions
journal, November 2012

  • Prasad, Manoj K.; Snyderman, Neal J.
  • Nuclear Science and Engineering, Vol. 172, Issue 3
  • DOI: 10.13182/NSE11-86

ENDF/B-VII.0: Next Generation Evaluated Nuclear Data Library for Nuclear Science and Technology
journal, December 2006


MULTI-PRED: A Software Module for Predictive Modeling of Coupled Multi-Physics Systems
journal, May 2018


Results for the C5G7 3-D Extension benchmark using the discrete ordinates code PANDA
journal, July 2006


Models for a three-parameter analysis of neutron signal correlation measurements for fissile material assay
journal, November 1986

  • Cifarelli, D. M.; Hage, W.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 251, Issue 3
  • DOI: 10.1016/0168-9002(86)90651-0

Distributions of Fission Neutron Numbers
journal, November 1957


Sensitivity Analysis of Neutron Multiplicity Counting Statistics Using First-Order Perturbation Theory and Application to a Subcritical Plutonium Metal Benchmark
journal, February 2017


On the theory of stochastic processes in nuclear reactors
journal, January 1958


On the Stochastic Theory of Neutron Transport
journal, March 1965

  • Bell, George I.
  • Nuclear Science and Engineering, Vol. 21, Issue 3
  • DOI: 10.13182/NSE65-1

Computation of Neutron Multiplicity Statistics Using Deterministic Transport
journal, April 2012