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At least 73 records · Page 4

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark—A Bayesian Inverse UQ-Based Approach for Data Assimilation

The Organisation for Economic Co-operation and Development Working Party on Nuclear Criticality Safety has proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian inverse uncertainty quantification (IUQ) employing scientific machine learning surrogate models as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of generalized linear least squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. Here, when comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that the GLLS predictions failed to replicate the computed response distributions for nonlinear applications, while MOCABA showed near agreement, and IUQ used the computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.

Bayesian calibration↗

The MUSIC Critical Benchmark and Nuclear Data

The Measurement of Uranium Subcritical and Critical (MUSIC) experiment was a series of measurements of critical and subcritical configurations of bare highly enriched uranium. The goal was to compare measurement methods, analysis techniques, and simulation methods across regimes of criticality and to provide high-quality validation of 235 U nuclear data. A benchmark evaluation of the two critical configurations of the MUSIC experiments will soon be published in the release of the International Criticality Safety Benchmark Evaluation Project Handbook. The recent execution of the experiment aids in proper quantification of model simplifications and all uncertainties associated with the experiment. Historical benchmark evaluations are heavily relied on for uranium nuclear data validation despite the fact that the same level of documentation and comparable uncertainty analysis may not be present. The MUSIC evaluation is less likely to include “unknown unknowns” that could impede accurately modeling the system. Presented are both highly detailed and very simplified models, which represent the experimental configurations accurately, aiding the users of the benchmark for nuclear data or transport code validation. The sensitivities of k eff to nuclear data and nuclear data–related uncertainties are very similar between this experiment and previous bare uranium sphere experiments. In addition, the nuclear data uncertainties to any nuclides other than 235 U are small. For all these reasons, the recently evaluated MUSIC benchmark critical configurations could prove very useful for 235 U nuclear data validation. Currently, major libraries have good agreement with the experimental results, within 200 pcm for all nuclear data libraries, and within one standard deviation of the experimental result for most. Suggested nuclear data adjustments based on MUSIC and Lady Godiva are also presented, with posterior improvements to both the agreement in k eff and the uncertainty associated with the nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark -- A Bayesian Inverse UQ-based Approach for Data Assimilation

The Organization for Economic Cooperation and Development (OECD) Working Party on Nuclear Criticality Safety (WPNCS) proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian Inverse Uncertainty Quantification (IUQ) as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of Generalized Linear Least Squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. When comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that GLLS predictions fail to replicate computed response distributions for nonlinear applications, while MOCABA shows near agreement, and IUQ uses computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.

FOS: Computer and information sciences↗

ANDES (ARGONNE NUCLEAR DATA EXPLORATION SOFTWARE) - ndviz

The Argonne Nuclear Data Exploration Software (ANDES) is a collection of open-source C++ codes and ROOT scripts that enable the visualization of patterns emerging from nuclear data. From this global view, well-known phenomena such as major nuclear shell closures and pairing effects near N=Z nuclei, as well as more subtle features, such as quantum phase transition around the Zr isotopes or the charge radius staggering in the Hg isotopes, can be observed. This visualization tool apart from having pedagogic application can serve as a tool for discovering previously unknown phenomena in the nuclear chart.

Santiago-Gonzalez, Daniel↗

Nuclear Data: What is the big deal? [Slides]

This presentation begins with a look at the practical application: differential and integral data. It also includes a nuclear data evaluation: cross section formalisms, data processing and cross section library generation, computer tools, and criticality safety assessment: nuclear data. The presentation ends with some concluding remarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Key nuclear data for non-LWR reactivity analysis

An assessment of nuclear data performance for non-light-water reactor (non-LWR) reactivity calculations was performed at Oak Ridge National Laboratory that involved a thorough literature review to collect related observations made across different research institutions, an interrogation of the latest ENDF/B evaluated nuclear data libraries, and propagation of nuclear data uncertainties to key figures of merit associated with reactor safety for six non-LWR benchmarks. The outcome of this comprehensive study was published in a technical report issued by the US Nuclear Regulatory Commission. This paper provides a summary of the study’s key observations and conclusions and demonstrates with two examples how the various methods available in the SCALE code system were used to identify key cross section uncertainties for non-LWR reactivity analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Understanding the impact of nuclear-data covariances on various integral responses using adjustment

The EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) project created a library of sensitivities for nine different integral responses with respect to nuclear data. These integral responses were obtained from measurements at LLNL (Lawrence Livermore National Laboratory) pulsed spheres, critical and sub-critical assemblies. At the same time, covariances for ENDF/B-VIII.0 were processed at LANL (Los Alamos National Laboratory). The combination of these data allow us to study the impact of nuclear-data covariances on various integral responses, either by forward-propagating covariances via sensitivities, or by using nuclear data, integral responses, and sensitivities for adjustment. Here, we will present: the impact of 1 H, 9 Be, 12 C, 27 Al, 56 Fe, 235,238 U, and 239,240 Pu ENDF/B-VIII.0 covariances on simulated bounds of the following integral responses: LLNL pulsed-spheres neutron-leakage spectra, the effective neutron multiplication factor, reaction rates, and reactivity coefficients of ICSBEP critical assemblies. Also, adjustment results with the same nuclear-data covariances and responses will be discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

EUCLID: Experiments Underpinned by Computational Learning for Improvements in Nuclear Data [Slides]

EUCLID will design validation experiments optimized to resolve compensating errors and adjust nuclear data to experiments. A big part of the success of the EUCLID proposal was due to previous work supported by NCSP (MCNP, nuclear data, and NCERC capabilities). The work performed under EUCLID will similarly benefit the NCSP mission. It will lead to new MCNP capabilities, improved nuclear data and nuclear data capabilities, and new methodology and tools that will have large impact on future NCERC experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Definitions for Testing Whether Evaluated Nuclear Data Relative Uncertainties are Realistic in Size

This document describes various tests that can be used to check whether evaluated relative uncertainties stored in nuclear-data covariances are realistic. To be more specific, these tests check whether nuclear-data uncertainties could be either over- or under-estimated given the input that usually enters the evaluation of nuclear-data mean values and covariances. Warning and error messages on the reliability of nuclear-data uncertainties will result from these tests. If uncertainties of one specific nuclear-data observable trigger warning messages from multiple tests, an evaluator should counter-check the reliability of the relative uncertainties of this particular nuclear-data covariance matrix.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nuclear Data and Cross Section Testing Using ENDF/B-VIII.0

With the release of the Evaluated Nuclear Data File (ENDF)/B-VIII.0 library, nuclear criticality safety practitioners and engineers have access to the latest cross section sets available for their analyses. However, these cross sections must be rigorously tested and validated to ensure that the nuclear data are responsive to the needs of the individuals responsible for developing, implementing, and maintaining computational tools for criticality safety applications. Thus, the ENDF/B-VIII.0 library is tested and validated with a large collection of experiments that were vetted by the International Criticality Safety Benchmark Evaluation Project and made available in the International Handbook of Evaluated Criticality Safety Benchmark Experiments. A selection of benchmark experiments for use within the criticality safety community were prepared and reviewed within the Verified, Archived Library of Inputs and Data (VALID), which is maintained by the Nuclear Energy and Fuel Cycle Division at Oak Ridge National Laboratory. The performance of the ENDF/B-VIII.0 library is assessed by using VALID models of benchmark experiments with the beta 12 version of SCALE 6.3 KENO V.a and KENO-VI Monte Carlo codes. The performance is compared with the results obtained from with the ENDF/B-VII.1 library. This report considers multigroup (MG) and continuous energy (CE) formats of the ENDF/B-VIII.0 and -VII.1 libraries. The benchmark experiments within VALID that validate the ENDF/B-VIII.0 library cover 15 broad system categories by using a range of fissile materials, uranium enrichments, plutonium isotopic vectors, and mixed uranium/plutonium systems. These forms are represented as metals, solutions, or various arrays of rods or plates that cover a variety of neutron energy spectra: thermal, fast, mixed, and intermediate. Over 600 cases were considered for use with the KENO V.a and KENO-VI codes with the ENDF/B-VIII.0 library. The results of the Monte Carlo comparison of ENDF/B-VIII.0 to ENDF/B-VII.1 with both KENO V.a and KENO-VI indicate that there is a less than 0.53% Δk difference between the bias of calculated k eff from the expected values. The CE ENDF/B-VIII.0 library results in smaller magnitude biases than the ENDF/B-VII.1 data for HEU-MET-FAST, HEU-SOL-THERM, IEU-MET-FAST, LEU-SOL-THERM, PU-SOL-THERM, and U233-MET-FAST systems, while the MG results yielded smaller magnitude biases for HEU-MET-FAST, HEU-SOL-THERM, IEU-MET-FAST, LEU-COMP-THERM, LEU-SOL THERM, MIX-COMP-FAST, and U233-MET-FAST systems. Most notable are the adjustments to the plutonium and 233 U cross section data, which has resulted in noticeably lower biases in the ENDF/B VIII.0 results for the mixed, plutonium, and 233 U systems. Results of the sensitivity data file comparison generated from TSUNAMI-3D for selected VALID cases for the ENDF/B-VIII.0 library indicate a very high level of agreement with correlation coefficients of the effect of nuclear data uncertainty on k eff (the c k integral parameter) all above 0.99. This indicates that cases with the ENDF/B-VIII.0 library would see very similar responses to any nuclear data errors or change as those with the ENDF/B-VII.1 library.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The EUCLID Experiment and Nuclear Data Library Comparisons

The EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) project at Los Alamos National Laboratory (LANL) was a Laboratory Directed Research and Development project which aimed to reduce compensating errors in nuclear data. One major component of the project was a series of critical experiments, both measuring k eff and various other observables with the goal of using these experiments to constrain 239 Pu nuclear data uncertainties and identify compensating errors. This paper details some of the experiment design and how various nuclear data libraries simulate the EUCLID system, including sensitivities compared to Jezebel.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Application of Machine Learning Algorithms to Identify Problematic Nuclear Data

In this work we aim to show that Machine learning algorithms are promising tools for the identification of nuclear data that contribute to increased errors in transport simulations. We demonstrate this through an application of a machine learning algorithm (Random Forest) to the Whisper/MCNP6 criticality validation library to identify nuclear data that are associated with an increase of the bias (simulated - experimental $k_{eff}$) in the calculations. Specifically, the $k_{eff}$ sensitivity profiles (w.r.t. nuclear data) of 233 U solution benchmarks are used to predict the bias and Shapley Additive Explanations (SHAP) are used to explain how the sensitivities are related to the predicted bias. The SHAP values can be interpreted as sensitivity coefficients of the machine learning model to the $k_{eff}$ sensitivities which are used to make predictions of bias. Using the SHAP values we can identify specific subsets of nuclear data which have the highest probability of influencing bias. We demonstrate the utility of this method by showing how SHAP values were used to identify an inconsistency in the 19 F inelastic scattering nuclear data. The methodology presented here is not limited to transport problems and can be applied to other simulations if there are experimental measurements to compare against, simulations of those experimental measurements, and the ability to calculate sensitivities of the model output with respect to the data inputs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Key Nuclear Data Impacting Reactivity in Advanced Reactors

Advanced reactor concepts currently being developed throughout the industry are significantly different from light water reactor (LWR) designs with respect to geometry, materials, and operating conditions, and consequently, with respect to their reactor physics behavior. Given the limited operating experience with non-LWRs, the accurate simulation of reactor physics and the quantification of associated uncertainties are critical for ensuring that advanced reactor concepts operate within the appropriate safety margins. Nuclear data are a major source of input uncertainties in reactor physics analysis. As part of an ongoing project at Oak Ridge National Laboratory (ORNL), the effects of nuclear data uncertainties on key figures of merit associated with advanced reactor safety are being assessed for selected advanced reactor technologies. Key nuclear data relevant for reactor safety analysis for each selected advanced reactor technology were identified, and their impact on important key figures of merit was assessed. Available advanced reactor specifications were reviewed, results from studies performed at ORNL and other research institutions were consulted, and available evaluated nuclear data libraries were analyzed. This report summarizes the key nuclear data for nuclides in the fuel, as well as other significant data, including scattering and neutron capture in various materials for the moderator, coolant, and structure of the considered advanced reactors. For the considered advanced reactors that use low-enriched uranium (LEU) fuel, results from LWR studies provided insight into relevant nuclear data given the lack of available studies specifically addressing these new systems. The major nominal missing data that were identified consist of thermal scattering data and 135m Xe cross section data for molten salt reactor (MSR) analysis. The identified major gaps with respect to nuclear data uncertainties are missing uncertainties of thermal scattering data for high temperature gas-cooled reactors and moderated MSR systems, and incomplete uncertainties on angular distributions in particular for fast spectrum systems, such as sodiumcooled fast reactors, fast molten salt reactors, and heat pipe reactors. Furthermore, it was found that special attention should be paid to cross section and uncertainty differences between different evaluated nuclear data library releases, because significant differences in nuclear data that can lead to major differences in reactivity calculations were found, even for well-known nuclides.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Nuclear data resources and initiatives for nuclear astrophysics

Research into the cosmic synthesis of the elements, the evolution and explosion of stars, the nature of the early Universe, and other important topics in nuclear astrophysics are at the forefront of nuclear science. These studies are motivating laboratory measurements and theoretical calculations that, after significant investments, are pushing the boundaries of what is possible. The latest nuclear results, however, must be specially prepared before they can be used to advance our knowledge of the cosmos. This processing requires a set of resources unique to nuclear astrophysics, and an impressive collection of nuclear reaction and nuclear structure datasets, processing codes, thermonuclear reaction rate libraries, and simulation codes and services have been developed for the field. There are, however, some serious challenges to these efforts that will only worsen in the future, making it important to develop strategies and act now to ensure a sustainable future for this work. After detailing the specific data types needed for nuclear astrophysics and the available data resources, the major challenges in this work and their implications are discussed. A set of initiatives are proposed to meet those challenges along with suggested implementations and possible ways that they may advance our understanding of the Universe and strengthen the field of nuclear astrophysics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Utilization of ACE nuclear data file toolkit ACEtk to calculate relative sensitivity coefficients of point-kinetics parameters

Sensitivity and uncertainty methods are quintessential for nuclear criticality safety and experiment design. This type of analysis relies on calculations of sensitivity coefficients; sensitivity coefficients of the effective neutron multiplication factor with respect to some nuclear data are predominantly calculated and used. As a part of the Laboratory Directed Research & Development project EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data) at Los Alamos National Laboratory, sensitivity coefficients of many radiation detector measurement responses with respect to nuclear data were investigated. Specifically, this paper outlines a method to calculate point-kinetics parameters relative sensitivity coefficients with respect to nuclear data. Point-kinetics parameters such as the prompt neutron decay constant, effective delayed neutron fraction, and neutron generation time are especially important to experimenters and reactor operators designing systems with dynamic neutron populations. This method couples capabilities of the ACE (A Compact ENDF) nuclear data file toolkit, ACEtk, with the ability to load cross sections into the radiation transport code Monte Carlo N-Particle (MCNP). In conclusion, key aspects of optimizing this method for a particular application and sensitivity profiles of the Jezebel criticality experiment are examined and discussed.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NCSP Related Nuclear Data Research at RPI [Slides]

This lecture is on NCSP related nuclear data research at the Rensselaer Polytechnic Institute (RPI). This presentation includes an overview of fiscal year 2022 activity. Additionally, it has a talk on the RPI Nuclear Data (ND) Group Research, an update on Linear Accelerators (LINAC) refurbishment, and the Enhanced Thermal Target & Cold Moderator (ETTC) Target System.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Survey of emerging nuclear data needs for nonproliferation applications with advanced reactors

Nuclear science plays a key role in non-proliferation activities supporting advanced reactor technologies. Nuclear data underpin predictions and interpretations of nuclear material behavior and signatures in reactor fuel production, use, transport, and storage. Advanced reactors provide new challenges compared to the current fleet of thermal fission reactors. This report consolidates reported nuclear data needs from representative workshops, conferences, and publications, identifying six themes for recommended future investments supporting non-proliferation and safeguards applications. While also identified as data needs, major fission product evaluations and (α,n) reactions were omitted as there are ongoing activities producing new data under NA22/Objective O. Each theme is summarized below with example data and association with the nonproliferation mission for advanced fuels and reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗