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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nuclear Data–Induced Uncertainties in Criticality Safety Analyses for High-Burnup and Extended Enrichment Fuels

Criticality safety analyses are conducted to show compliance with regulatory standards and to demonstrate safe operational conditions during the storage and transportation of spent nuclear fuel. Given the increased interest in the industry in low-enriched uranium plus (LEU+) and higher-burnup fuel, it is important to study the impact of such fuels’ use on criticality safety analyses and the resulting nuclear data–induced uncertainties. Here, in this work, nominal pressurized water reactor assemblies with LEU+ fuel enrichments up to 8 wt% 235 U and high burnups up to 80 GWd/tonne U were studied. The assemblies were placed in a generic burnup credit cask GBC-32. As a result of the different covariance libraries, using the ENDF/B-VII.1 nuclear data library consistently resulted in lower nuclear data uncertainties than did the use of the ENDF/B-VIII.0 data library. The highest contribution in the nuclear data–induced uncertainties resulted from the major actinides, and their contribution increased with increasing burnup and enrichment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Measurement of leakage neutron spectra for zirconium with D-T neutrons and validation of evaluated nuclear data

Integral neutronics experiments have been a powerful tool and method for examining the reliability of evaluated nuclear data. In the present paper, the accuracy of evaluated nuclear data for Zirconium has been validated by comparing measured leakage neutron spectra with calculated ones. Leakage neutron spectra from the irradiation of D-T neutrons on Zirconium samples were experimentally measured at 60° and 120° by using a time-of-flight method. Theoretical calculations are carried out by Monte Carlo neutron transport code MCNP-4C with evaluated nuclear data of the ENDF/B-VII.0, ENDF/B-VIII.0, JENDL-4.0 and CENDL-3.1 libraries. From the comparisons, it is found that the calculations with JENDL-4.0 gives better agreements with the experiments at 60° while a large discrepancies are observed in the 4–13.5 MeV energy range at 120°. However, the calculated spectra using the data from ENDF/B-VII.0, ENDF/B-VIII.0 and CENDL-3.1 libraries showed some discrepancies with the measured ones, especially caused by the difference of the elastic and inelastic angular distributions and the secondary neutron energy distributions in the continuum inelastic scattering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Nuclear Data Assessment for Advanced Reactors

Advanced reactor concepts 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 important for ensuring that the nuclear design for advanced reactor concepts include appropriate margins. Nuclear data are a major source of input uncertainties in reactor physics analysis. As part of a project sponsored by the US Nuclear Regulatory Commission at Oak Ridge National Laboratory (ORNL), key nuclear data relevant to reactor safety analysis in selected advanced reactor technologies were identified, and their impacts on important key figures of merit were assessed based on (1) a review of available advanced reactor specifications, (2) analysis of previous studies performed at ORNL and other research institutions, and (3) sensitivity and uncertainty analyses performed for six selected benchmarks—three experimental and three computational—to quantify the impacts of the identified key nuclear data on several key metrics. This report summarizes the key nuclear data—nominal data and nuclear data uncertainties— considering the most important nuclear reactions in the fuel and in various materials for the moderator, coolant, and structure of the considered advanced reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Using Whisper-1.1 to Guide Improvements to Nuclear Data Evaluations [Slides]

This presentation covers the use of Whisper-1.1 to guide improvements to nuclear data evaluations. This presentation provides a brief overview on what Whisper-1.1 is. Additionally covered is the benchmark selection: using benchmark and application correlations (ck) computed using nuclear data sensitivity profiles and covariance data. Next the presentation touches on compute bias and bias uncertainty based on selected benchmarks using Extreme Value Theory Finally the presentation shows the additional margin for nuclear data uncertainty estimated by GLLS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Nuclear data uncertainty propagation and modeling uncertainty impact evaluation in neutronics core simulation

Uncertainty analysis is a critical requirement in reactor simulation as it is used to quantify the reliability of best-estimate calculation. A comprehensive uncertainty analysis should characterize all sources of uncertainties in a computationally-feasible and scientifically-defendable manner. Here we employ a well-established reduced order modeling (ROM) based uncertainty quantification methodology to propagate uncertainties throughout neutronic calculations. ROM relies on recent advances in randomized data mining techniques applied to large data streams. In our proposed implementation, the nuclear data uncertainties are first propagated from multi-group level through lattice physics calculation to generate few-group parameter uncertainties, described using a vector of mean values and a covariance matrix. Employing an ROM-based compression of the covariance matrix, the few-group uncertainties are then propagated through downstream core simulation in a computationally efficient manner. This straightforward approach, albeit efficient as compared to brute force forward and/or adjoint-based methods, often employs a number of assumptions that have been unquestioned in the literature of neutronic uncertainty analysis. This manuscript argues that these assumptions could introduce another source of uncertainty referred to as modeling uncertainties, whose magnitude needs to be quantified in tandem with nuclear data uncertainties. Thus, our primary goal is to explore the interactions between these two uncertainty sources in order to assess whether modeling uncertainties have an impact on parameter uncertainties. To explore this endeavor, the impact of a number of modeling assumptions on core attributes uncertainties is quantified. The study employs a CANDU reactor model, with Serpent and NEWT as lattice physics solvers and NESTLE-C as core simulator. The modeling assumptions investigated include those related with the uncertainty propagation method employed, e.g., deterministic vs. stochastic, the few-group energy structure employed to represent the cross-sections, the resonance treatment in lattice physics calculation, the reference values for the cross-section, and the number of samples employed to render ROM compression. Results indicate that some of the modeling assumptions could have a non-negligible impact on the core responses propagated uncertainties, highlighting the need for a more comprehensive approach to combine parameter and modeling uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Proceedings of the Nuclear Data Roadmapping and Enhancement Workshop (NDREW) for Nonproliferation

On January 23–25, 2018 in Washington, DC, the National Nuclear Security Administration (NNSA) Office of Defense Nuclear Nonproliferation (DNN) Research and Development (NA-22) supported the three-day Nuclear Data Roadmapping and Enhancement Workshop (NDREW) to enable nonproliferation missions. The goal was to assemble users and producers of nuclear data to provide input to identify nuclear data needs, suggest solutions to address these needs, and rank potential solutions with regard to mission impact. The workshop was organized into 12 discussion sessions which were bookended by introductory and concluding presentations. Eight discussion topics were defined by specific nuclear reaction or data types, while the other four covered infrastructure, benchmarks, uncertainties, and code development needs. Over 110 attendees represented national laboratories, universities, and headquarters, as well as international collaborators and industry representatives. Based on survey results and other feedback, attendees found the workshop valuable since it initiated a new conversation between programs and provided collaborative opportunities across stakeholder groups such as data users and experimentalists/evaluators. The proceedings presented herein summarize the content of the workshop, provide session notes and important highlights, and documents recommendations from the attendees.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

AMPX and SCALE Nuclear Data Libraries for Depletion [Slides]

This presentation touches on AMPX and SCALE nuclear data libraries for depletion. AMPX is a nuclear data processing code suite that generates continuous-energy and multigroup neutron and gamma libraries used in SCALE and VERA, covariance data used in S/U calculations, and depletion, activation and decay origin data for Oak Ridge Isotope Generation code (ORIGEN).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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

Example on how to (intelligently) augment the nuclear-data pipeline with machine learning [Slides]

The presentation discusses how machine learning has helped the Los Alamos National Laboratory (LANL) nuclear-data pipeline. It also discusses the strengths of machine learning as it finds trends in large amounts of data where human brains are overwhelmed and that this information may be crucial to improve our nuclear data. It does stress, however, that machine learning is no "silver bullet" and that it is critical to feed it expert knowledge and use physics intuition to interpret the results. The presentation discusses the need to develop infrastructure and tools to provide data in an easily readable and unambiguously interpretable format (e.g., EXFOR format), to develop experimental data and theory to solve physics questions, and that statisticians and nuclear-data experts must be brought together to correctly interpret the results. The presentation concludes by stating that machine learning is a great tool and that LANL needs to use the algorithms along with developing physics data, tools and infrastructure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Development of a Representative Molten Chloride Fast Reactor Model to Assess the Impact of Nuclear Data

The SCALE code system was employed to conduct a preliminary investigation of nuclear data impacts for a fast spectrum molten chloride salt reactor. A computationally effective depletion model that is representative of the reactor system was successfully developed and used to conduct fuel depletion simulations. Development of this model draws from the SLICE method that was developed at Oak Ridge National Laboratory to enable generation of fuel compositions for an advanced reactor core at equilibrium operation. Eigenvalue uncertainty calculations using the ENDF/B-VII.1 nuclear data library were performed for the reactor in the fresh fuel state and an irradiated fuel state. It was determined that the primary driver of eigenvalue uncertainty was the uncertainty in the 235U (n, 𝛾) cross section. Uncertainty calculation results from this study were compared to results available for a different fast system, a sodium-cooled fast reactor, to confirm similarities and identify differences with respect to nuclear data impacts between the two fast advanced reactor systems.

Hirji, Rakim [Georgia Institute of Technology]↗
DOE OSTI2024

Legacy (NDF & MCF), GNDS and Direct forms of the ENDL2009.5 Evaluated Nuclear Data Library

The ENDL2009.5 Evaluated Nuclear Data Library is now available three different processed forms for users: (1) the Legacy form using NDF and MCF processing of the ENDL files, (2) the GNDS form which uses FUDGE and Merced to process the translations in to GNDS of the ENDL files, and (3) the Direct form which uses FUDGE and Merced to process where available the original ENDF6- format source files used to make the ENDL files. If original files are not available for various protares in the Direct form, then the ENDL forms are used.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Evaluated Nuclear Data Requirements in Support of Fission and Fusion Applications [Slides]

This presentation touches on thermal scattering cross section and scattering lengths including criticality benchmarks (fission). Secondly, development and completeness of charged ­particle libraries: criticality benchmarks (fission), neutron source (fission/fusion), simulation benchmarks and light elements generation (fusion). Additionally, this presentation details on the covariances (methodology and completeness) with adjustment and optimization of nuclear data libraries (fission/fusion). Finally nuclear data reproducibility and conclusions are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Nuclear Data Sheets for A = 52

The nuclear structure data belonging to all nuclei with mass number A=52 have been compiled and evaluated using experimental nuclear reaction data and decay data available before July 10, 2015. This evaluaton supersedes the previous publication for this msss chain (2007Hu08, Nuclear Data Sheets 108, 773 (2007)). The data for the ε decay of {sup 52}Co (104 ms) and the ε decay of {sup 52}Ni (40.8 ms) are both incomplete, so new studies would be useful.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Contributions to Integral Nuclear Data in ICSBEP and IRPhEP since ND 2013

The status of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and the International Reactor Physics Experiment Evaluation Project (IRPhEP) was last discussed directly with the international nuclear data community at ND2013. Since ND2013, integral benchmark data that are available for nuclear data testing has continued to increase. The status of the international benchmark efforts and the latest contributions to integral nuclear data for testing is discussed. Select benchmark configurations that have been added to the ICSBEP and IRPhEP Handbooks since ND2013 are highlighted. The 2015 edition of the ICSBEP Handbook now contains 567 evaluations with benchmark specifications for 4,874 critical, near-critical, or subcritical configurations, 31 criticality alarm placement/shielding configuration with multiple dose points apiece, and 207 configurations that have been categorized as fundamental physics measurements that are relevant to criticality safety applications. The 2015 edition of the IRPhEP Handbook contains data from 143 different experimental series that were performed at 50 different nuclear facilities. Currently 139 of the 143 evaluations are published as approved benchmarks with the remaining four evaluations published in draft format only. Measurements found in the IRPhEP Handbook include criticality, buckling and extrapolation length, spectral characteristics, reactivity effects, reactivity coefficients, kinetics, reaction-rate distributions, power distributions, isotopic compositions, and/or other miscellaneous types of measurements for various types of reactor systems. Annual technical review meetings for both projects were held in April 2016; additional approved benchmark evaluations will be included in the 2016 editions of these handbooks.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Making sense of uncertain nuclear data

At its core, and in an imperfect world, the scientific method relies heavily on the concept of uncertain knowledge. Understanding the nature and magnitude of our lack of knowledge on nuclear data has important ramifications on a wide range of nuclear technologies that encompass defense, energy, medicine, astrophysics, among others. Over the span of a long and fruitful carrier, Dr. Massimo Salvatores has made significant contributions to the fields of nuclear reactor physics, nuclear data, and uncertainty quantification and propagation. Advances in machine learning techniques and computational capabilities are enabling a new level of confidence in our ability to predict key nuclear metrics as well as their associated uncertainties across many applications. Here this short article reviews some of those concepts with an eye towards developing a new paradigm to provide nuclear data libraries of benefit to various applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Nuclear Data Sensitivity/Uncertainty Studies of Tantalum-Reflected Systems

Tantalum (Ta) is a refractory metal with high melting point and high corrosion resistance. This makes it useful as a mold material for plutonium casting operations. Unfortunately, there are few criticality benchmarks with high nuclear data sensitivities. Given that, it is desirable to design new experiments to provide additional validation data for nuclear criticality safety, which is the objective of the Thales project. Multiple application models were used to represent process conditions (either normal conditions or credible upset conditions) both at Los Alamos National Laboratory (LANL) and Savannah River Site (SRS). A total of 40 application models were obtained. Given this, it was useful to down-select the number of needed application models. This work documents the down-selection based on several nuclear data sensitivity/uncertainty metrics. In addition to showing the result of the specific down-selection used for the Thales project, this work discusses potential ways to represent a large number of application models with a smaller number of proposed experiment designs.

42 ENGINEERING↗
DOE OSTI2021

Which nuclear data can be validated with LLNL pulsed-sphere experiments? [Slides]

LLNL pulsed sphere are a very valuable experiment series to validate scattering and fission nuclear data. It would be great if they could be evaluated as benchmarks and make it into SINBAD! We see potential issues in ENDF/B-VIII.0 6 Li, 12 C, 16 O, 24- 26 Mg, 27 Al, 48 Ti, 56 Fe, and 208 Pb nuclear data. Good agreement is found with 1,2 H, 7 Li, 9 Be, 14 N, 235,238 U, and 239 Pu nuclear data.

16O and 12C Spheres↗