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NASA NTRS2016

In Search of a Time Efficient Approach to Crack and Delamination Growth Predictions in Composites

Analysis benchmarking was used to assess the accuracy and time efficiency of algorithms suitable for automated delamination growth analysis. First, the Floating Node Method (FNM) was introduced and its combination with a simple exponential growth law (Paris Law) and Virtual Crack Closure technique (VCCT) was discussed. Implementation of the method into a user element (UEL) in Abaqus/Standard(Registered TradeMark) was also presented. For the assessment of growth prediction capabilities, an existing benchmark case based on the Double Cantilever Beam (DCB) specimen was briefly summarized. Additionally, the development of new benchmark cases based on the Mixed-Mode Bending (MMB) specimen to assess the growth prediction capabilities under mixed-mode I/II conditions was discussed in detail. A comparison was presented, in which the benchmark cases were used to assess the existing low-cycle fatigue analysis tool in Abaqus/Standard(Registered TradeMark) in comparison to the FNM-VCCT fatigue growth analysis implementation. The low-cycle fatigue analysis tool in Abaqus/Standard(Registered TradeMark) was able to yield results that were in good agreement with the DCB benchmark example. Results for the MMB benchmark cases, however, only captured the trend correctly. The user element (FNM-VCCT) always yielded results that were in excellent agreement with all benchmark cases, at a fraction of the analysis time. The ability to assess the implementation of two methods in one finite element code illustrated the value of establishing benchmark solutions.

Krueger, Ronald↗
DOE OSTI2022

Updates and Validation for the n+ 63,65 Cu Cross Sections [Abstract]

The neutron induced total, elastic, and capture cross sections of 63,65 Cu isotopes were selected for evaluation in the resolved and unresolved resonance energy ranges by the National Criticality Safety Program to resolve discrepancies related to benchmark performance. This is especially evident for the series of ZEUS benchmarks in which copper is used as a reflector. Because copper is also used as structural material in both fission and fusion reactors, the need to address benchmark discrepancies linked to nuclear data deficiencies is a task of primary importance. The aim of this work is to describe the steps of evaluation work towards a consistent improvement of the benchmark performance. The R-matrix analysis with the SAMMY code focused on the 63 Cu(n,γ) reaction channel between 100-300 keV coupled to unresolved resonance region parameters up to 650 keV to fit average cross section data from a recent experiment. Due to the high sensitivity of many benchmarks to elastic scattering angular distribution data, especially for the 65 Cu isotope, the impact of these data was tested by generating Legendre coefficients from both resonance parameters and the Hauser-Feshbach model. Guided by the findings of Shaw et al., the performance of the current evaluation for 65 Cu was compared to that of ENDF/B-VII.1 and ENDF/B-VIII.0 by testing the reactivity coefficients corresponding to the validation suite of experimental criticality benchmarks for thermal, intermediate, and fast systems taken from the International Criticality Safety Benchmark Experiments Project Handbook. The benchmark performance is especially sensitive to 63 Cu(n,γ) and 65 Cu elastic scattering for neutron energies in the 100–500 keV region, whereas 100 keV is the upper limit of the resolved resonance region in the ENDF/B-VIII.0 evaluations for 63,65 Cu. The results highlight the need to handle the transition from the resolved resonance region to the high energy region carefully.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

The Case for and Against a Gadolinium Bias in SCALE: Round 2

The “Opening Arguments” for and against a gadolinium bias in SCALE were presented at the American Nuclear Society Annual Meeting in Philadelphia, Pennsylvania, in June, 2018. Some critical experiments included in the Oak Ridge National Laboratory Verified, Archived Library of Inputs and Data (VALID) indicate a significant bias as a function of gadolinium concentration. Other experiments indicate that no significant bias exists. The work presented here develops a larger suite of gadolinium-bearing benchmark models to further examine code, data, and benchmark performance. The new benchmark models have been reviewed for accuracy, but documentation and review for addition to the VALID library have not been completed. The problematic benchmarks included in VALID are HEU-SOL-THERM-014 and -016. These are two evaluations from a series of experiments from the Institute for Physics and Power Engineering (IPPE), Russia, documented in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The entire set of evaluations also includes HEU-SOL-THERM-015, -017, -018, -019, and -025. Each evaluation contains a different uranium concentration, and different configurations within each evaluation include different gadolinium concentrations. These 7 evaluations contain a total of 52 configurations and form the largest subset of experiments considered, and they allow for a more complete assessment of the performance of these benchmarks than has historically been possible using just the HEU-SOL-THERM-014 and -016 results. Additional solution experiments are considered, including MIX-SOL-THERM-006 and -007 and PU-SOL-THERM-034. MIX-SOL-THERM-007 is in the VALID library, whereas MIX-SOL-THERM-006 and PU-SOL-THERM-034 are not. The results for MIX-SOL THERM-007 have not shown a gadolinium trend. These mixed- and plutonium-fueled solutions include 28 configurations. Some experiments including solid fuel and solid gadolinium are also included. These experiments include highly enriched uranium (HEU) foils moderated with polyethylene in HEU-MET-THERM-010, -016, and -034, and low enriched uranium (LEU) pin arrays with gadolinia absorber rods in LEU-COMP THERM-036 and -043. A total 32 cases with solid fuel are included. The IPPE solution benchmarks show a fairly high degree of variability, but no clear trend as a function of gadolinium concentration can be observed. The mixed- and plutonium-fueled solutions show less variability than the HEU solutions and also no trend relative to gadolinium concentration. The solid-fueled experiments also show no trend as a function of gadolinium content. The entire set of benchmarks shows no clear trend on gadolinium content or the energy of the average neutron lethargy causing fission.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Continuous-Energy ENDF/B-VIII.0 Cross Section and SCALE 6.2.4 Performance for Nuclear Criticality Safety Applications: 1 H, C, 58,60 Ni, 182,183,184,186 W, 235,238 U, 239 Pu

As part of the nuclear data evaluation and validation cycle, the ENDF/B-VIII.0 cross-section library released in 2018 requires testing to determine areas of improvement and deterioration. Previous work by the authors investigated the performance of 16 O, 56 Fe, and 63,65 Cu cross sections, with this study acting as an extension of the prior work. In addition to the isotopes and nuclear criticality safety benchmarks of interest to the prior work, benchmarks from the International Criticality Safety Benchmark Evaluation Project Handbook were selected for their k eff sensitivity to 1 H, C, 58,60 Ni, 182,183,184,186 W, 235,238U, or 239 Pu cross sections and were modeled in the SCALE code system maintained by Oak Ridge National Laboratory. In total, 253 benchmark configurations were selected for their sensitivities and modeled using SCALE 6.2.4 Criticality Safety Analysis Sequences (CSAS) continuous-energy Monte Carlo k eff calculations. This collection includes and expands upon the 99 benchmarks in the prior work. The AMPX-processed ENDF/B-VIII.0 library was decomposed into individual ENDF/B-VIII.0 datum libraries for each isotope of interest. Doing so allowed for the individual substitution of an ENDF/B-VIII.0 cross section in the place of ENDF/B-VII.1, determining isotope-specific effects of ENDF/B-VIII.0 relative to ENDF/B-VII.1. Full library calculations with entirely ENDF/B-VII.1 data or entirely ENDF/B-VIII.0 data were also executed. As a measure of performance, the average relative deviation was determined as the ratio of the deviation between calculated and experimental keff to the propagated calculational and experimental uncertainty. With calculated full library and isotope-specific ENDF/B-VIII.0 k eff ’s, an optimized combination of data libraries was estimated and confirmed with SCALE calculations. This showed that reverting 239 Pu, 58 Ni, 16 O, and 65 Cu cross sections to ENDF/B-VII.1 resulted in improved performance relative to the full ENDF/B-VIII.0 library. Across all 253 benchmarks, the average relative deviation was 1.29σ for the full ENDF/B-VII.1 library, 1.17σ for the full ENDF/B-VIII.0 library, and 0.97σ for the optimized combination. The reversion of 239 Pu, 58 Ni, 16 O, and 65 Cu cross sections to ENDF/B-VII.1 in the 99 benchmarks of the prior work resulted in further improved experimental agreement compared to the previously reported improvement from 16 O and 65 Cu alone. Therefore, it is suggested that applications with significant sensitivities to 239 Pu, 58 Ni, 16 O, and 65 Cu consider their choice of nuclear data library.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Validation of ENDF/B-VIII.1 Nuclear Data Files [Slides]

ENDF-6 formatted files were processed into A Compact ENDF (ACE) files using NJOY2016. Several validation tests were performed: (1) LANL Legacy Benchmark Suite (2) “Modern” Benchmark Suite (3) HEU Benchmark Suite (4) LEU Benchmark Suite (5) Mixed (U+Pu) Benchmark Suite (6) Pu Benchmark Suite (7) 233 U Benchmark Suite.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

SCALE 6.3 Validation: Radiation Shielding

Safe and reliable use of scientific and engineering computer codes requires validation for the types of applications in which they will be used. An example in the nuclear reactor engineering and licensing field is radiation transport employed in shielding analyses. The validity of computer codes for shielding applications is demonstrated in this report for SCALE version 6.3.0. Representative benchmarks corresponding to shielding analyses are selected for the validation study. Typical measurement results analyzed from these benchmarks include neutron fluxes, detector count rates, detector energy response functions, neutron and gamma dose rates, neutron activation rates and activities, neutron leakage fluxes, and skyshine dose rates. Thousands of points of comparison between measurement and calculation are presented in this work. Other than rare outliers typically explained by either a lack of information or large uncertainties in the experiment conditions, material, or dimensions, the Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC) radiation transport computer code with built-in variance reduction methods distributed with the SCALE computer code system agrees well with the measurement results. In selected benchmarks, MAVRIC is also compared to Monte Carlo N- Particle® (MCNP® ) 1 calculations. Both computer codes generally agree well within the estimated uncertainties. With the release of SCALE 6.3.0, Shift was integrated as an alternative transport solver in MAVRIC, denoted MAVRIC-Shift. Although the traditional MAVRIC using Monaco was used primarily in this validation study, many results have also been generated using MAVRIC-Shift. Agreement between MAVRIC-Monaco and MAVRIC-Shift is generally very good. The benchmarks presented in this report were obtained from reliable sources such as the International Criticality Safety Benchmark Evaluation Project Handbook, the Shielding Integral Benchmark Archive & Database, and other shielding validation work found in the literature. Additional datapoints and benchmarks will be added to future versions of this report to expand the shielding validation suite.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRSDate not supplied

Space Flown Rodent Liver RNA Sequencing Data for Machine Learning in Space Biology Research

High-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. Data analysis has been accelerated in recent years by the adoption of artificial intelligence (AI) and machine learning (ML) techniques by biomedical researchers. In space biology research, RNAseq datasets from space-flown experimental samples are critical for characterizing the gene expression aberrations associated with exposure to spaceflight stressors. However, space biological experiments tend to be very low sample size, so identifying proper AI/ML algorithms for sequencing data analysis is an ongoing challenge since these algorithms typically require large sample size. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML”, focused on creating datasets meant for three main applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. These scientific benchmarks consist of an AI-ready dataset and a reference implementation on a specific scientific question. In this work, we focused on generating standardized datasets to allow the scientific community to benchmark AI/ML algorithms in the domain of space biology. We present here a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data as a collaboration between the NASA AI4LS (Artificial Intelligence for Life Sciences) working group. and NASA’s SMD. This dataset consists of space-flown and ground control mouse liver found in the NASA GeneLab omics database. However, to amplify the small sample number (n=112 samples) for ML purposes, we employ Gaussian noise and a generative adversarial network to extend this dataset to 6,000 synthetic samples, matching the original gene expression characteristics.

James Casaletto↗
DOE OSTI2023

Nuclear Criticality Safety Integral Experiment Covariance Determination

Integral benchmarks for criticality safety and nuclear data validation require expensive uncertainty quantification studies. Commonly, the uncertainty quantification ignores correlations between experiments that share components. Experiments such as the TEX (Thermal/Epithermal eXperiments) campaigns consist of many shared parts between experiments, such as fuel, which creates a strong correlation in their errors. While these correlations are known to exist, they are often not estimated due to the complexity of such calculations. This paper describes a software package that uses an intuitive method of determining the covariance for each of the experimental components, providing a correlation matrix for each family of parts across the multiple cases examined within a benchmark. The code uses the TEX-HEU campaign as a proof of concept, and we show that the correlations can be calculated with information commonly found in ICSBEP (International Criticality Safety Benchmark Evaluation Project) benchmarks. The estimated covariances are used in χ 2 trending studies to evaluate their impact on nuclear data validation. The covariance determination code can be easily integrated into current benchmark evaluations as well as reevaluating legacy benchmark uncertainties. Uncertainty correlation calculations should become the baseline for criticality safety integral experiment benchmarks and can now be easily calculated with the described software package.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Nuclear Criticality Safety Integral Experiment Covariance Determination

Integral benchmarks for criticality safety and nuclear data validation require expensive uncertainty quantification studies. Commonly, the uncertainty quantification ignores correlations between experiments that share components. Experiments such as the TEX (Thermal/Epithermal eXperiments) campaigns consist of many shared parts, such as fuel, which create a strong correlation in their uncertainties. While these correlations are known to exist, they are often not estimated due to the complexity of such calculations. This paper describes a software package that uses an intuitive method of determining the covariance for each of the experimental components, providing a correlation matrix for each family of parts across the multiple cases examined within a benchmark. The code uses the TEX-HEU campaign as a proof of concept, and we show that the correlations can be calculated with information commonly found in ICSBEP (International Criticality Safety Benchmark Evaluation Project) benchmarks. The estimated covariances are used in χ 2 trending studies to evaluate their impact on nuclear data validation. Without covariances, χ 2 per degree of freedom was calculated as 2.203 and with covariances it was 1.179. The difference shows that omitting covariance information may cause overly pessimistic bias quantifications. The covariance determination code can be easily integrated into current benchmark evaluations as well as reevaluating legacy benchmark uncertainties. Uncertainty correlation calculations should become the baseline for criticality safety integral experiment benchmarks and can now be easily calculated with the described software package.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Real-time streamflow forecasting: AI vs. Hydrologic insights

In this paper, we propose a set of simple benchmarks for the evaluation of data-based models for real-time streamflow forecasting, such as those developed with sophisticated Artificial Intelligence (AI) algorithms. The benchmarks are also data-based and provide context to judge incremental improvements in the performance metrics from the more complicated approaches. The benchmarks include temporal and spatial persistence, persistence corrected for baseflow and streamflow, as well as river distance weighted runoff obtained from space-time distributed rainfall. In the development of the benchmarks, we use basic hydrologic insights such as flow aggregation by the river network, scale-dependence in basin response, streamflow partitioning into quick flow and baseflow, water travel time, and rainfall averaging by the basin width function. The study uses 140 streamflow gauges in Iowa that cover a range of basin scales between 7 and 37,000 km 2 . The data cover 17 years. This work demonstrates that the proposed benchmarks can provide good performance according to several commonly used metrics. For example, streamflow forecasting at half of the test locations across years achieves a Kling-Gupta Efficiency (KGE) score of 0.6 or higher at one-day ahead lead time, and 20% of cases reach the KGE of 0.8 or higher. The proposed benchmarks are easy to implement and should prove useful for developers of data-based as well as physics-based hydrologic models and real-time data assimilation techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Simulating energy performance of buildings: a study using eQUEST and Energy Star ® portfolio manager

Commercial buildings consume significant energy in the United States and exhibit high potential for energy use reduction through retrofits. Benchmarking and energy simulation are well established tools in the industry to identify potential improvements and measure performance. Analysis to identify most sensitive retrofit parameters to energy performance can optimize investment and available energy savings. Presented study demonstrates methodology using a static model to determine sensitivity of building design and retrofit parameters with respect to energy performance. Calibrated simulation energy models (eQUEST) of two distribution centers (A, B) are presented. A fractional factorial analysis is conducted on retrofit parameters of efficiency measures targeting the highest energy consumers, and the results are benchmarked using Energy Star® Portfolio Manager. A custom Microsoft Excel® based simulation model is created to simulate occupancy levels, lighting, plug loads, and other equipment used in various spaces throughout the day. For Building A, efficient lighting was the most influential parameter for energy savings, carbon savings and benchmarking score; whereas, for Building B, HVAC efficiency was most influential for energy and demand controlled ventilation and economizers was most influential for benchmarking score. While retrofit projects can save energy and carbon emissions, variation in source-site ratios and state grid emissions, benchmarking scores may not always reflect equivalent improvement. State grid emissions factors, natural gas composition are difficult to model and hence not considered in this study. In conclusion, the synergistic analysis presented, emphasizes the importance of benchmarking and efficiency retrofits in promoting sustainable building practices to reduce energy consumption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Updates to the n+ 63,65 Cu Evaluations in the Resolved Resonance Region [Slides]

This presentation discusses the motivation and background of the n+ 63,65 Cu Evaluations in the Resolved Resonance Region which is to study the interaction of neutrons with copper as it is important in nuclear applications since critical assembly configurations include metallic copper as reflector. In support to the U.S. Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP), measurements and related evaluations of 63,65 Cu isotopes were selected to improve the agreement with the benchmarks and to assess the importance of the angular distribution data for reactor calculations. Previous and current evaluation work is supported by an experimental campaign initiated before 2010, the 63,65 Cu R-matrix analysis generated resonance parameters up to 300 keV. However, due to outstanding issues in the benchmark performance, ENDF/B-VIII.0 library released a truncated set of resonance parameters up to 100 keV. The goal of this work is to generate an updated set of resonance parameters in the 100-300 keV range to improve the benchmark performance of 63,65 Cu isotopes. In conclusion, R-matrix analysis to update 63,65 Cu evaluations was performed to simultaneously improve benchmark performance and extend the RRR to 300 keV. The benchmark calculations suggest the increased capture cross sections are beneficial, however, further investigation of the measured capture data is needed to understand the large normalization scaling factor needed to improve the reactivity. Also, the copper-reflected benchmarks indicate the need to further investigate angular distributions and extension of RRR to 300 keV is aided well by level statistics considerations. Work to refine the fit of individual resonances is ongoing.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Development of an Improved RELAP5-3D Model for the High Temperature Test Facility

High-temperature gas-cooled reactors (HTGRs) are rapidly approaching deployment. Confidence in transient analysis of these systems for design, optimization, and licensing calculations requires modeling and simulation tools that have been validated against data relevant to HTGR conditions. The High Temperature Test Facility (HTTF) is an integral effects thermal hydraulics test facility for prismatic HTGRs. In spring and summer of 2019, HTTF was used for a series of experiments that now serve as the basis for the OECD/NEA Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data (HTGR T/H Benchmark). This benchmark contains problems for systems code, computational fluid dynamics (CFD), and coupled systems code/CFD modeling representing lower plenum mixing and both the depressurized and pressurized conduction cooldown (DCC and PCC respectively) transients. Benchmark problems include exercises for code-to-code and code-to-data comparisons as well as an exercise for error scaling between HTTF and the Modular High Temperature Gas-Cooled Reactor, which serves as the basis for the HTTF design. Previous analysis as part of the HTGR T/H benchmark used a RELAP5-3D model developed at Idaho National Laboratory (INL) and demonstrated an ability to reproduce trends in the measured data but difficulties reproducing experimental values within their uncertainty. These difficulties were largely attributed to assumptions made during the development of the initial RELAP5-3D model, which predated the HTTF experiments. A significant cause of difficulty reproducing the measured temperatures may be the radial nodalization of the previous RELAP5-3D model. The new model provides a finer nodalization to assess the impact of radial nodalization and allows for asymmetric heating within the core, which was a feature of multiple HTTF experiments. In this paper, we present the new RELAP5-3D model of HTTF. In addition to describing the new model, this paper compares the new and old models and provides results for a full-power steady state, a DCC, and a PCC in HTTF. These analyses are based on the code-to-code comparison exercises for the DCC and PCC problems of the HTGR T/H benchmark. We present the results of these exercises from the new model and compare them to the results of the old model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Expanded Intercomparison of Nuclear Data Libraries Using Jupiter and Jupiter High-240 Experiments

There is a limited availability of plutonium experiments with sensitivity to lead in the ICSBEP (International Handbook of Evaluated Criticality Safety Benchmark Experiments) Handbook. The Jupiter and Jupiter High-240 experiments were performed at the National Criticality Experiments Research Center as a collaborative effort between Los Alamos National Laboratory and the Japan Atomic Energy Agency to assess lead void coefficients in a plutonium-lead system containing weapons- and reactor-grade plutonium, respectively. Concurrent with benchmark development, an intercomparison of calculations using different nuclear data libraries has been performed to assess the usability of the experimental data for nuclear data adjustment in a “softer-that-fast” neutron energy spectrum. Eigenvalue calculations using MCNP with the ENDF/B-VIII.0 and TENDL-2021 nuclear data libraries calculate closest to the benchmark values for Jupiter. Calculations using JENDL-5 and ENDF/B-VIII.1 match best with the Jupiter High-240 values. Lead void worth calculations using the various nuclear data libraries are all within 3σ of their respective measured values. Perturbation studies between ENDF/B-VIII.0 and ENDF/B-VIII.1 demonstrate an approximate increase in calculated eigenvalues for the Jupiter series experiments by ~240 pcm for plutonium (mostly 239 Pu) and ~120 pcm for lead accompanied by a decrease contributed by ~113 pcm for copper and ~13 pcm for stainless steel. Nuclear data sensitivities and uncertainties investigated using Whisper show slightly lower sensitivity to scatter than a lead-reflected plutonium sphere but greater sensitivity to neutron capture. The sensitivities between Jupiter and Jupiter High-240 for lead are very similar for both ENDF/B-VIII.0 and ENDF/B-VIII.1 nuclear data. These benchmarks are more sensitive to neutron capture in lead than other plutonium benchmark experiments and would be useful for both lead and 240 Pu validation. In conclusion, with the high degree of compensating effects between copper, lead, and plutonium cross sections, additional isolated Pb-Pu and Cu-Pu benchmarks would be beneficial in improving these nuclear data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Effect of Nuclear Data Covariances on Integral Experiment Design with Sensitivity and Uncertainty Analysis

Washington River Protection Solutions (WRPS) uses MCNP6.2 and the Whisper code for criticality safety analyses of the Hanford Tank Farm. Together the codes derive baseline upper subcritical limits (USLs) for the waste models using experimental benchmarks. Whisper returns higher USLs, i.e. , has less of a conservative penalty, when the neutronic similarity of the experimental benchmarks to the application is high. Unfortunately, few critical benchmarks have high similarity to the Hanford tanks. The waste in the tanks is highly dilute in plutonium and contains large masses of weakly neutron-absorbing elements like iron and manganese. Experimental benchmarks typically have low sensitivity to these absorbers because they are present as structural materials. Lacking similar benchmarks, new Thermal Epithermal eXperiment (TEX) configurations with high Pu content and interstitial iron absorbers have been designed for the criticality safety validation. The features of the design have been iterated upon to maximize the similarity between the experiment and different Hanford waste models. The similarity is quantified with sensitivity analysis and uncertainty quantification using the representativity coefficient, or c k . The representativity calculation requires nuclear data covariances, which may differ between nuclear data libraries and between library versions. Because of these variations, the optimal design may depend on the nuclear data covariances library. A scenario can be envisioned where an experiment is designed, and c k is maximized, with one set of covariance data. However, when the covariance data is changed, say from ENDF/B-VII.1 to ENDF/B-VIII.0, and the benchmark is used in a criticality safety evaluation, the experiment becomes suboptimal with respect to c k . In this paper, we present how the optimal design of the new TEX experiments varied depending on the nuclear data covariances used to calculate c k . We compare ENDF/B-VII.1 and ENDF/B-VIII.0, as if the library had been updated since the design of the experiment. Additionally, we use JEFF3.3 to simulate if the covariance data of a different library had been used. The results show that the covariances do have an important effect on the designs, less so for thermal systems (where the data are more consistent between evaluations) and more so for epithermal systems where more differences exist.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Preliminary NoMAD Results of the MUSIC Experiment

The Measurement of Uranium Subcritical and Critical (MUSiC) experiment was carried out from December 2020 through April 2021 at the National Criticality Experiments Research Center (NCERC). This measurement campaign featured bare configurations of the Rocky Flats highly-enriched uranium (HEU) shells, with each configuration having different numbers of these shells. The goal of the experiment was to test multiple neutron multiplicity detectors and measurement methods for a large range of neutron multiplication values, to see when the combination of detectors and methods break down as the configurations reach the delayed supercritical window. Adding subcritical integral benchmarks gives additional validation to nuclear data. These benchmarks provide additional parameters against which to validate the data. While critical benchmarks have just a single value, $K_{eff}$ , subcritical benchmarks can be used to infer multiple parameters. As an example, recent subcritical benchmarks utilizing the Hage-Cifarelli formalism have three quantities of interest ($R_{1}$, $R_{2}$, and $M_{L}$). This gives nuclear data evaluators additional data to use when performing their evaluations, and allows for these benchmarks to be useful for additional types of nuclear data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Assessment of Existing Transportation Packages for Use with HALEU

Commercial light water reactor operators and fuel vendors in the United States are pursuing changes to fuel that include increased 235 U enrichment. Economic studies generally anticipate maximum near-term fuel assembly designs with up to 8 wt.% 235 U. Many next-generation nuclear reactor designs require high-assay low-enriched uranium (HALEU) (19.75 wt.% > 235 U > 5 wt.%) fuel. One necessary element for the commercial-scale use of HALEU is the ability to safely transport large quantities of enriched fuel material in multiple forms. However, there is uncertainty as to whether subcriticality requirements can be satisfied with existing package designs and whether existing critical benchmark experiment data are sufficient to support criticality safety code validation for HALEU transportation applications. This study assesses the potential to use currently licensed transportation packages for the transportation of increased enrichment unirradiated U fuel forms. The assessment uses selected package designs that represent the five categories of fuel form-boiling water reactor pins and assemblies, pressurized water reactor pins and assemblies, UF 6 , U-metal and tristructural isotropic (TRISO) particles, and UO 2 pellets or powder-and focuses on demonstrating subcriticality and identifying benchmark critical experiments appropriate for use in criticality computer code validation. Key quantities of interest that relate to subcriticality are limiting conditions (e.g., optimum moderation), package or package array k eff , package capacity, and package transportation array size. The SCALE TSUNAMI-3D and TSUNAMI Indices and Parameters codes are used for sensitivity and uncertainty calculations and for identification of candidate critical benchmark experiments for code validation. The primary metric for identifying candidate benchmarks is the similarity coefficient, c k . For each fuel form category, a representative package is evaluated. Results provided for each package evaluation include enrichment and packaging limits (e.g., maximum transportation array size as a function of enrichment) and benchmark critical experiment similarity coefficients. Results indicate that there are viable means for increasing enrichments into the HALEU range across the spectrum of fuel forms with differing increase amounts available for different packages. Sources of subcriticality margin to offset increased enrichment reactivity include reduced transportation array size, reduced fissile mass, burnable absorber credit, and safety analysis margin harvesting. For all packages except the DN-30, numerous critical benchmark experiment candidates for validation were identified.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Nuclear data covariances are critical input to determine upper sub-critical limits and to design experiments to increase it [Slides]

This presentation discusses how Upper Subcritical Limits (USL) are key parameters to determine operational limits in nuclear criticality safety evaluations. It also discusses an example of plutonium casting operation using tantalum at LANL PF-4. The Whisper tool at Los Alamos relies on many inputs, including covariance data, leading the presentation to ask if an existing benchmark data be used in Whisper to adjust nuclear data and covariances to justify a higher USL. If not, Whisper can be used to help design an optimal new benchmark experiment. The presentation also seeks to determine what the possible impacts are on USL and operational limits for plutonium casting. In conclusion, nuclear data covariances are used for by Whisper for: GSSL adjustment of nuclear data and covariances, identification of most similar existing benchmark experiments to application, simulation of Upper Subcritical Limit of application, and input to optimization techniques for designing most appropriate new benchmark experiment(s) to meet requirements. This requires a complete set of nuclear data covariances, benchmarks and k-effective sensitivity profiles (for both benchmarks and applications). The presentation concludes by asking if end users should trust results that depend on current covariance data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗