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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Nondestructive Assay Technical Infrastructure Program Mission and Vision

The Nondestructive Assay Program (NDAP) mission and vision is achieved by identifying and accomplishing a set of programmatic goals that correspond with eight broad technical program elements. The NDAP was created as a result of Defense Nuclear Facility Safety Board Recommendation 2007-1, entitled “Safety-Related In Situ Nondestructive Assay of Radioactive Materials,” which emphasized the need to improve in situ measurements of radioactive material at US Department of Energy (DOE) defense nuclear facilities. An NDAP five-year plan will define tasks to accomplish specific goals identified in the NDAP mission and vision. This mission and vision is applicable for eight technical program elements: Hardware/Software Development, Algorithm Development and Nuclear Data, Uncertainty Quantification, Nuclear Materials, Staffing, Personnel, And Training, Data Management, Requirement and Standards, and Information Preservation and Dissemination. An additional program element is technical support, which provides daily execution management support for the NDAP, site scope, and deliverable tracking via site task managers, along with technical advisement and support from the technical support group. The NDAP mission and vision provides attributes with specific goals for each program element, and some goals benefit multiple program elements. The goals and attributes defined herein are implemented via an NDAP five-year execution plan that defines site work scope, budget, and deliverables, all of which are updated annually. The NDAP is designed to benefit nondestructive assay (NDA) needs to support DOE nuclear criticality safety programs, ensuring that NDA technology is sufficiently capable of guaranteeing the safety of those who handle, store, process, or transport fissionable materials in the complex. Especially important for the NDAP is to maximize capabilities to identify, characterize, and manage in situ fissile material deposits in process equipment to ensure nuclear criticality safety at processing facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

MONK10: A Monte Carlo Code for Criticality Analysis - 14574

The MONK{sup R} code, if we include its predecessor GEM, has now been in use for 50 years. It is a Monte Carlo code for nuclear criticality and reactor physics analyses which is used extensively in the UK nuclear industry and worldwide. In 2014 a major new version of the code, MONK10A, was released introducing many new features; these are described with example applications presented where appropriate. Experience with MONK9A models indicates that MONK10A has increased run-time performance for all cases and on average runs 2.4 times faster. New geometry options include the direct import of CAD generated models using the new IGES body, POLY body, TETMESH Hole and TETMESH Zone features. Example calculations for a selection of CAD import options are presented and compared with the intrinsic MONK geometry representation, with relative merits discussed. New Features are included to assist with the modeling of distributed parameters; such features include Unified Tally (UT), Action Tallies (AT) in UT and Shannon entropy. The latter is useful in assessing the convergence of distributed parameters, such as scalar neutron flux. As such it is an important tool in determining the appropriate point to stop settling and begin scoring stages in a Monte Carlo simulation. The utility of UT, AT-in-UT and Shannon entropy is demonstrated using calculations employing the new CAD import geometry options. Runtime Doppler broadening is included to allow accurate representation of temperature distributions within models. Example calculations which further demonstrate UT and AT-in-UT are presented for different bodies at different temperatures to evaluate the effects of temperature differences on k-effective and reaction rates. The MONK10A code was issued with a new set of continuous energy and group nuclear data libraries. These include JEFF3.1, JEFF3.1.1, JEFF 3.1.2, ENDF/B-VII.0 and CENDL 3.1 libraries. The inclusion of a range of libraries allows the user to evaluate the impact of different international nuclear data evaluations on their results and an example is provided to illustrate the differences that can arise from the use of different nuclear data evaluations. The code was also issued with a new version of the VisualWorkshop IDE to allow easy construction and editing of input decks, running of calculations and display of geometry and results. Examples are provided of the geometry and results display and showing how results can be superimposed upon the geometry. (authors)

42 ENGINEERING↗
DOE OSTI2021

RPI LINAC refurbishment and upgrade project

The Electron Linear Accelerator at Rensselaer Polytechnic Institute (RPI) was constructed in the late 1950s and started operation in 1961 [1]. The facility was designed and used primarily for measurements of Nuclear Data (ND) with emphasis on the resonance energy region. As such it was designed to produce short pulses of neutrons (5-5000 ns) and equipped with detection stations at different neutron flight path distances from the source (15 m-250 m). When the LINAC started operation it was one of the most powerful accelerators in the world for high energy-resolution measurements in the resonance region. The original LINAC with some upgrades is still in operation but no longer provides world class capabilities for measurements with short pulses. In 2011 discussions between the RPI ND group, Naval Reactors, and the Nuclear Criticality Safety Program about the future of the LINAC concluded that maintaining the capability to perform world-class nuclear data measurements at RPI was desirable. To that end, it was decided to refurbish the facility and upgrade the accelerator capabilities to enable high accuracy measurement in the resonance region with narrow neutron pulse and high electron beam power. Located at a major US technical university, this project provides a needed US nuclear data capability for both research and education, and also includes external users and industrial applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Development and Testing of Neutron Cross Section Covariance Data for SCALE 6.2

Neutron cross-section covariance data are essential for many sensitivity/uncertainty and uncertainty quantification assessments performed both within the TSUNAMI suite and more broadly throughout the SCALE code system. The release of ENDF/B-VII.1 included a more complete set of neutron cross-section covariance data: these data form the basis for a new cross-section covariance library to be released in SCALE 6.2. A range of testing is conducted to investigate the properties of these covariance data and ensure that the data are reasonable. These tests include examination of the uncertainty in critical experiment benchmark model k eff values due to nuclear data uncertainties, as well as similarity assessments of irradiated pressurized water reactor (PWR) and boiling water reactor (BWR) fuel with suites of critical experiments. The contents of the new covariance library, the testing performed, and the behavior of the new covariance data are described in this paper. The neutron cross-section covariances can be combined with a sensitivity data file generated using the TSUNAMI suite of codes within SCALE to determine the uncertainty in system k eff caused by nuclear data uncertainties. The Verified, Archived Library of Inputs and Data (VALID) maintained at Oak Ridge National Laboratory (ORNL) contains over 400 critical experiment benchmark models, and sensitivity data are generated for each of these models. The nuclear data uncertainty in k eff is generated for each experiment, and the resulting uncertainties are tabulated and compared to the differences in measured and calculated results. The magnitude of the uncertainty for categories of nuclides (such as actinides, fission products, and structural materials) is calculated for irradiated PWR and BWR fuel to quantify the effect of covariance library changes between the SCALE 6.1 and 6.2 libraries. One of the primary applications of sensitivity/uncertainty methods within SCALE is the assessment of similarities between benchmark experiments and safety applications. This is described by a c k value for each experiment with each application. Several studies have analyzed typical c k values for a range of critical experiments compared with hypothetical irradiated fuel applications. The c k value is sensitive to the cross-section covariance data because the contribution of each nuclide is influenced by its uncertainty; large uncertainties indicate more likely bias sources and are thus given more weight. Changes in c k values resulting from different covariance data can be used to examine and assess underlying data changes. These comparisons are performed for PWR and BWR fuel in storage and transportation systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Addressing fission product validation in MCNP burnup credit criticality calculations - 14508

The US Nuclear Regulatory Commission (NRC) Division of Spent Fuel Storage and Transportation issued Interim Staff Guidance (ISG) 8, Revision 3 in September 2012. This ISG provides guidance for NRC staff members' review of burnup credit (BUC) analyses supporting transport and dry storage of pressurized water reactor spent nuclear fuel (SNF) in casks. The ISG includes guidance for addressing validation of criticality (k{sub eff}) calculations crediting the presence of a limited set of fission products and minor actinides (FP and MAs). Based on previous work documented in NRC Regulatory Guide (NUREG) Contractor Report (CR)-7109, the ISG recommends that NRC staff members accept the use of either 1.5 or 3% of the FP and MA worth - in addition to bias and bias uncertainty resulting from validation of k{sub eff} calculations for the major actinides in SNF - to conservatively account for the bias and bias uncertainty associated with the specified unvalidated FP and MAs. The ISG recommends (1) use of 1.5% of the FP and MA worth if a modern version of SCALE and its nuclear data are used and (2) 3% of the FP and MA worth for well qualified, industry standard code systems other than SCALE with the Evaluated Nuclear Data Files, Part B (ENDF/B),-V, ENDF/B-VI, or ENDF/B-VII cross sections libraries. The work presented in this paper provides a basis for extending the use of the 1.5% of the FP and MA worth bias to BUC criticality calculations performed using the Monte Carlo N-Particle (MCNP) code. The extended use of the 1.5% FP and MA worth bias is shown to be acceptable by comparison of FP and MA worths calculated using SCALE and MCNP with ENDF/B-V, -VI, and -VII-based nuclear data. The comparison supports use of the 1.5% FP and MA worth bias when the MCNP code is used for criticality calculations, provided that the cask design is similar to the hypothetical generic BUC-32 cask model and that the credited FP and MA worth is no more than 0.1 Δk{sub eff} (ISG-8, Rev. 3, Recommendation 4). (authors)

42 ENGINEERING↗
DOE OSTI2019

ENDF/B-VIII.0 Covariance Data Development and Testing for Advanced Reactors

This report documents the ENDF/B-VIII.0 covariance data development and testing performed at Oak Ridge National Laboratory performed under the auspices of the US Department of Energy Office of Nuclear Energy. This work supports modeling and simulation of advanced reactor designs in the US by analyzing, validating and improving the nuclear data that provide underlying physics for calculations. This report assesses nuclear data uncertainty information for neutron cross sections, provided in the form of covariance matrices, in the 2018 ENDF/B-VIII.0 library. A review and interpretation of some of the issues with the current covariance library is provided. A new approach to augment the ENDF/B-VIII.0 covariance matrix to accurately reflect uncertainties in the results of modeling and simulation reliant on the current nuclear data library is documented. Rigorous testing of the ENDF/B-VIII.0 covariance data is documented. Finally, the performance of the ENDF/B-VIII.0 covariance data for advanced reactor applications is assessed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Updated Godiva-IV Benchmark Preview

A note of errata prepended to the Godiva-IV delayed-critical benchmark (HEU-MET-FAST- 086) identifies two corrections to be made to the model: The glory hole in the spindle should be made larger, and the height of the safety block should be made smaller (and therefore its density made larger). In addition, the safety block at its full-in position is closer to the inner subassembly plate than was modeled in the benchmark. These changes have been made to HEU-MET-FAST-086 Case 4 in order to estimate the effect on $\kappa$ eff and on the neutron flux spectrum. Using smaller separation, a smaller safety block, and a larger glory hole caused keff to increase by 453 ± 1 pcm from the benchmark. The latest nuclear data, ENDF/B-VIII.0, have also been used, causing $\kappa$ eff to increase another 37 ± 1 pcm. Flux spectra were compared in a modeled fission foil (near the center of Godiva-IV in the glory hole) and at three external (point) detectors. Within the fission foil, using ENDF/B-VIII.0 induced changes in the flux spectrum similar in size to the changes due to using smaller separation, a smaller safety block, and a larger glory hole. At the detectors, using ENDF/B- VIII.0 induced changes in the flux spectrum much larger than those due to changing the model. In other words, the corrections to the benchmark model cause a large increase in $\kappa$ eff , but the changes to the neutron flux spectrum are small compared to those caused by using the latest nuclear data. This study presents a preview of results expected during the reevaluation of the Godiva IV benchmark, but it is not a substitute for the full reevaluation.A note of errata prepended to the Godiva-IV delayed-critical benchmark (HEU-MET-FAST- 086) identifies two corrections to be made to the model: The glory hole in the spindle should be made larger, and the height of the safety block should be made smaller (and therefore its density made larger). In addition, the safety block at its full-in position is closer to the inner subassembly plate than was modeled in the benchmark. These changes have been made to HEU-MET-FAST-086 Case 4 in order to estimate the effect on $\kappa$ eff and on the neutron flux spectrum. Using smaller separation, a smaller safety block, and a larger glory hole caused $\kappa$ eff to increase by 453 ± 1 pcm from the benchmark. The latest nuclear data, ENDF/B-VIII.0, have also been used, causing $\kappa$ eff to increase another 37 ± 1 pcm. Flux spectra were compared in a modeled fission foil (near the center of Godiva-IV in the glory hole) and at three external (point) detectors. Within the fission foil, using ENDF/B-VIII.0 induced changes in the flux spectrum similar in size to the changes due to using smaller separation, a smaller safety block, and a larger glory hole. At the detectors, using ENDF/B- VIII.0 induced changes in the flux spectrum much larger than those due to changing the model. In other words, the corrections to the benchmark model cause a large increase in $\kappa$ eff , but the changes to the neutron flux spectrum are small compared to those caused by using the latest nuclear data. This study presents a preview of results expected during the reevaluation of the Godiva IV benchmark, but it is not a substitute for the full reevaluation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Development code for sensitivity and uncertainty analysis of input on the MCNPX for neutronic calculation in PWR core

This research was carried out on the development of code for uncertainty analysis is based on a statistical approach for assessing the uncertainty input parameters. In the butn-up calculation of fuel, uncertainty analysis performed for input parameters fuel density, coolant density and fuel temperature. This calculation is performed during irradiation using Monte Carlo N-Particle Transport. The Uncertainty method based on the probabilities density function. Development code is made in python script to do coupling with MCNPX for criticality and burn-up calculations. Simulation is done by modeling the geometry of PWR terrace, with MCNPX on the power 54 MW with fuel type UO2 pellets. The calculation is done by using the data library continuous energy cross-sections ENDF / B-VI. MCNPX requires nuclear data in ACE format. Development of interfaces for obtaining nuclear data in the form of ACE format of ENDF through special process NJOY calculation to temperature changes in a certain range.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Scoping Study of Machine Learning Techniques for Visualization and Analysis of Multi-source Data in Nuclear Safeguards

In implementation of nuclear safeguards, many different techniques are being used to monitor operation of nuclear facilities and safeguard nuclear materials, ranging from radiation detectors, flow monitors, video surveillance, satellite imagers, digital seals to open source search and reports of onsite inspections/verifications. Each technique measures one or more unique properties related to nuclear materials or operation processes. Because these data sets have no or loose correlations, it could be beneficial to analyze the data sets together to improve the effectiveness and efficiency of safeguards processes. Advanced visualization techniques and machine-learning based multi-modality analysis could be effective tools in such integrated analysis. In this project, we will conduct a survey of existing visualization and analysis techniques for multi-source data and assess their potential values in nuclear safeguards.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Nuclear Decay Data Evaluations at IFIN-HH, Romania

An IAEA Coordinated Research Project (CRP) on Updated Decay Data Library for Actinides was implemented during the period 2005-2012. The author participated in the CRP, as a representative of the Horia Hulubei National Institute of Physics and Nuclear Engineering (IFIN-HH), the Radionuclide Metrology Laboratory. Decay data for five actinide nuclides were evaluated by the author, according to the procedures and rules of the international cooperation Decay Data Evaluation Project (DDEP): {sup 236}U, {sup 234}Th, {sup 228}Ra, {sup 211}Bi and {sup 211}Po. The most important results, conclusions and some recommendations of the evaluator are presented. The IFIN-HH involvement in several new international and national research projects in the field is briefly mentioned; new evaluations and experimental determination of some nuclear decay data (photon absolute emission probability, half-life) for nuclear medicine applications are foreseen.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Methodology for Sensitivity and Uncertainty-Based Criticality Safety Validation

Monte Carlo radiation transport software is used extensively for determining the effective multiplication factor k of fissionable systems towards assessing the criticality safety of operations. Understanding the predictive capability of the Monte Carlo software and nuclear data libraries for calculations of specific applications is vital towards making these assessments. Recently, sensitivity and uncertainty (S/U) methods have been developed for this purpose. A computational tool has been developed that uses the S/U methods with MCNP6 to select critical experiment benchmarks that have similar sources of computational bias, and extreme value theory is then used to determine suitable and conservative calculational margins. The S/U techniques are then used to perform nuclear data adjustments, which are then used to determine a suitable margin of subcriticality from cross section uncertainties. This document gives an overview of the theory of S/U methods used for criticality safety validation. First an overview is given for using the sensitivity coefficients and nuclear co variance data towards determining neutronic similarity factors is then discussed. Next, the extreme value theory (EVT) to determine a calculational margin is given along with how the similarity factors are used in the analysis. Then, the Generalized Linear Least Squares (GLLS) method for performing data adjustment and how that method is used to reject benchmarks and compute adjusted nuclear data uncertainties in k are discussed. Last, a discussion of the margin of subcriticality is given along with how to apply of the GLLS data adjustment methods to quantify the effect of nuclear data variability on k.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

ALPHANSO: Open-source modeling of (α, n) neutron source terms

Applications ranging from nuclear safeguards to dark matter detection require accurate predictions of neutron yields and energy spectra produced by (α, n) reactions. Legacy tools like SOURCES-4C remain widely used despite significant limitations, including outdated nuclear data, missing target nuclides, and restricted accessibility. Here, we present ALPHANSO, an open-source Python package for calculating (α, n) neutron source terms. ALPHANSO incorporates modern nuclear data libraries and formats covering all naturally occurring target nuclides and provides a transparent, modular framework for updating or extending the data as new evaluations are released. Comparison with an updated version of SOURCES-4A, NeuCBOT, and experimental measurements across a range of elements and materials shows that ALPHANSO reproduces neutron yields and spectra in good agreement with experimental data and state-of-the-art (α, n) calculations. These results demonstrate that ALPHANSO is a reliable, accessible, and modern alternative to legacy (α, n) source term codes such as SOURCES-4C. Its open-source design and modular data handling make it readily extensible to future evaluated nuclear data and low-background applications.

(α, n) reactions↗
DOE OSTI2022

A framework to collect human reliability analysis data for nuclear power plants using a simplified simulator and student operators

Data scarcity in human reliability analysis (HRA) has been a major challenge in the quantification process. Many institutes have collected HRA data through experiments using full-scope simulators with actual operators. Nevertheless, there are still some limitations to relying solely on full-scope studies. This paper aims to propose how full-scope data collection studies can be supported through the Simplified Human Error Experimental Program (SHEEP). The SHEEP framework was developed by Idaho National Laboratory (INL) to collect HRA data through a simplified simulator and student operators. This paper introduces the major tasks in the SHEEP framework, with a particular focus on differences that arise due to participant type (i.e., student vs. actual operator), based on experiments using a simplified simulator (i.e., the Rancor Microworld). This paper also describes whether the data collected via this approach could support a representative full-scope data collection study (i.e., the HuREX study) based on the experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Uncertainty quantification in (α,n) neutron source calculations for an oxide matrix

Here we present a methodology to propagate nuclear data covariance information in neutron source calculations from (α,n) reactions. The approach is applied to estimate the uncertainty in the neutron generation rates for uranium oxide fuel types due to uncertainties on 1) 17,18 O( α,n) reaction cross sections and 2) uranium and oxygen stopping power cross sections. The procedure to generate reaction cross section covariance information is based on the Bayesian fitting method implemented in the R-matrix SAMMY code. The evaluation methodology uses the Reich-Moore approximation to fit the 17,18 O(α,n) reaction cross-sections in order to derive a set of resonance parameters and a related covariance matrix that is then used to calculate the energydependent cross section covariance matrix. The stopping power cross sections and related covariance information for uranium and oxygen were obtained by the fit of stopping power data in the -energy range of 1 keV up to 12 MeV. Cross section perturbation factors based on the covariance information relative to the evaluated 17,18 O( α,n) reaction cross sections, as well as uranium and oxygen stopping power cross sections, were used to generate a varied set of nuclear data libraries used in SOURCES4C and ORIGEN for inventory and source term calculations. The set of randomly perturbed output (α,n) source responses, provide the mean values and standard deviations of the calculated responses reflecting the uncertainties in nuclear data used in the calculations. Lastly, the results and related uncertainties are compared with experiment thick target (α,n) yields for uranium oxide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

Neutronics qualification of the Jules Horowitz reactor fuel by interpretation of the VALMONT experimental program - Transposition of the uncertainties on the reactivity of JHR with JEF2.2 and JEFF3.1.1

The new European material testing Jules Horowitz Reactor (JHR), currently under construction in Cadarache center (CEA France), will use LEU (20% enrichment in {sup 235}U) fuels (U{sub 3}Si{sub 2} for the start up and UMoAl in the future) which are quite different from the industrial oxide fuel, for which an extensive neutronics qualification database has been established. The HORUS3D/N neutronics calculation scheme, used for the design and safety studies of the JHR, is being developed within the framework of a rigorous verification-validation-qualification methodology. In this framework, the experimental VALMONT (Validation of Aluminium Molybdenum uranium fuel for Neutronics) program has been performed in the MINERVE facility of CEA Cadarache (France), in order to qualify the capability of HORUS3D/N to accurately calculate the reactivity of the JHR reactor. The MINERVE facility using the oscillation technique provides accurate measurements of reactivity effect of samples. The VALMONT program includes oscillations of samples of UAl{sub x}/Al and UMo/Al with enrichments ranging from 0.2% to 20% and Uranium densities from 2.2 to 8 g/cm{sup 3}. The geometry of the samples and the pitch of the experimental lattice ensure maximum representativeness with the neutron spectrum expected for JHR. By comparing the effect of the sample with the one of a known fuel specimen, the reactivity effect can be measured in absolute terms and be compared to computational results. Special attention was paid to the rigorous determination and reduction of the experimental uncertainties. The calculational analysis of the VALMONT results was performed with the French deterministic code APOLLO2. A comparison of the impact of the different calculation methods, data libraries and energy meshes that were tested is presented. The interpretation of the VALMONT experimental program allowed the qualification of JHR fuel UMoAl8 (with an enrichment of 19.75% {sup 235}U) by the Minerve-dedicated interpretation tool: PIMS. The effect of energy meshes and evaluations put forward the JEFF3.1.1/SHEM scheme that leads to a better calculation of the reactivity effect of VALMONT samples. Then, in order to quantify the impact of the uncertainties linked to the basic nuclear data, their propagation from the cross section measurement to the final computational result was analysed in a rigorous way by using a nuclear data re-estimation method based on Gauss-Newton iterations. This study concludes that the prior uncertainties due to nuclear data (uranium, aluminium, beryllium and water) on the reactivity of the Begin Of Cycle (BOC) for the JHR core reach 1217 pcm at 2{sigma}. Now, the uppermost uncertainty on the JHR reactivity is due to aluminium. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Fission Product Yield Data Adjustment in a Prototype Version of TSURFER

The TSURFER (Tool for Sensitivity/Uncertainty analysis of Response Functionals using Experimental Results) module of Oak Ridge National Laboratory’s (ORNL’s) SCALE code system has been updated to perform nuclear data adjustments for fixed-source irradiation/depletion problems. TSURFER uses a generalized linear least squares (GLLS) approach to consolidate a prior set of measured responses and corresponding calculated values to create the most self-consistent set of nuclear data. Traditionally, TSURFER adjustments have been performed for multigroup nuclear data such as reaction cross sections. In this work, TSURFER is expanded to perform adjustments to independent fission product yields and branching ratios that need equality constraints. To preserve equality constraints after the data adjustment procedure, an updated GLLS formulation includes a new Lagrange multiplier that forces data adjustment to sum to 0 for a given fission yield/branching ratio parent. A test problem illustrates that the newly updated TSURFER module satisfies the required constraint that adjustments for fission yield data sum to 0.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Software Quality Assurance and Verification for the MPACT Library Generation Process

This report fulfills the requirements for the Consortium for the Advanced Simulation of Light-Water Reactors (CASL) milestone L2:RTM.P14.02, “SQA and Verification for MPACT Library Generation,” by documenting the current status of the software quality, verification, and acceptance testing of nuclear data libraries for MPACT. It provides a brief overview of the library generation process, from general-purpose evaluated nuclear data files (ENDF/B) to a problem-dependent cross section library for modeling of light-water reactors (LWRs). The software quality assurance (SQA) programs associated with each of the software used to generate the nuclear data libraries are discussed; specific tests within the SCALE/AMPX and VERA/XSTools repositories are described. The methods and associated tests to verify the quality of the library during the generation process are described in detail. The library generation process has been automated to a degree to (1) ensure that it can be run without user intervention and (2) to ensure that the library can be reproduced. Finally, the acceptance testing process that will be performed by representatives from the Radiation Transport Methods (RTM) Focus Area prior to the production library’s release is described in detail.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Minimum critical masses and their uncertainties for several fissile nuclides and reflectors - 14296

A systematic effort was undertaken to reevaluate the minimum critical mass for several fissile nuclides and reflectors. This was done using MCNP6 in combination with several modern nuclear data libraries, viz. ENDF/B-VII.1, JENDL-4.0 and JEFF-3.1.1. This combination was benchmarked extensively against criticality safety benchmarks. The procedure to extract the minimum critical mass from the MCNP6 calculations was carefully implemented, so that it would have a negligible impact on the accuracy of the end results. All parts of the calculation, i.e. nuclear data processing, MCNP6 models, and post-processing, were applied consistently for all cases, involving varying fissile nuclides and reflectors. Results for the minimum critical mass were generated for {sup 233,235}U, {sup 236,239,241}Pu, {sup 242m}Am, {sup 243,245,247}Cm, and {sup 249,251}Cf, for the case of water moderation and water reflection. For {sup 235}U, the minimum critical mass was also calculated for cases with other reflectors, such as beryllium, heavy water, graphite, lead, and concrete. The results for the water reflection cases are in good agreement with most of the literature values, but for the cases with reflectors such as graphite, lead, or concrete, there are sizable differences. The accuracy of the results was assessed in two ways. First, a comparison was made with criticality safety benchmark results, by selecting benchmarks that resemble the minimum mass systems the most. It was clear that for {sup 233,235}U and {sup 239}Pu with water reflection, the differences in minimum critical masses between the libraries are consistent with the differences obtained for benchmark cases. The difference between the benchmark calculations and the benchmark values is then an indication of the accuracy with which one can simulate comparable systems. Secondly, sensitivity runs were performed with the new MCNP6 sensitivity option, based on ENDF/B-VII.1 nuclear data. For each fissile nuclide, the sensitivity of k{sub eff} to cross sections such as capture, fission, elastic, inelastic was calculated for the minimum critical mass case. The same was done for the {sup 1}H and {sup 16}O cross sections in the moderator and reflector. The uncertainty in k{sub eff} was calculated by combining the sensitivity profiles with the appropriate ENDF/B-VII.1 covariance matrix, using the SUSD code. As a final step, the uncertainty in k{sub eff} can be translated to an uncertainty in the minimum critical mass. (author)

42 ENGINEERING↗