Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Nuclear Data”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CEA/DAM - CEA/DEN - LANL - IAEA - IPHC Collaboration Meeting on Nuclear Data, Nuclear Reaction Theories, and Machine Learning (Summary Report)

Dupuis hosted our biennial CEA/NNSA collaboration meeting, and Kawano and Lovell of LANL and Tamagno of CEA/DEN (Cadarache) visited CEA/DAM to discuss current issues and further developments in nuclear reaction modeling, nuclear data evaluation, and relevant programs of modern computer science, especially the machine learning technology. The discussions included topics of our common interest such as neutron inelastic scattering, capture, and fission, with particular emphasis on the actinide nuclear data evaluations. We report briefly the summary of our discussions. We also had a half-day video meeting with Capote of IAEA and Kerveno of IPHC to discuss nuclear reactions on actinides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

How can a diverse set of integral and semi-integral measurements inform identification of discrepant nuclear data?

Nuclear data are used for a variety of applications, including criticality safety, reactor performance, and material safeguards. Despite the breadth of use-cases, the effective neutron multiplication factor, keff, of ICSBEP critical assemblies are primarily used for nuclear data validation; these are sensitive to specific energy regions and nuclides and are unable to uniquely constrain nuclear data. As a consequence, general-purpose nuclear data libraries, such as ENDF/B-VIII.0, may have deficiencies that, while not apparent in criticality applications, negatively impact other applications, such as non-destructive analysis of special nuclear material and neutron diagnosed subcritical experiments. Recent work by the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project developed a machine learning tool, RAFIEKI, which uses random forests and the SHAP metric to determine which nuclear data contribute most to predicted bias between measured and simulated responses (e.g. keff). This paper contrasts RAFIEKI analysis applied to keff only against RAFIEKI analysis with keff paired with either LLNL pulsed sphere measurements or subcritical benchmarks. Two examples show that a) including pulsed sphere measurements substantially increases 9Be nuclear data importance to bias between 2 and 15 MeV, and b) including subcritical benchmarks has the potential for disentangling compensating errors between 240Pu (n,el) and (n,il) cross-sections between 0.1 and 10 MeV. These results show that RAFIEKI analysis applied to response sets that include, but go beyond, keff can aid nuclear data evaluators in identifying issues in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

Generalized Nuclear Data: A New Structure (with Supporting Infrastructure) for Handling Nuclear Data

The Evaluated Nuclear Data File (ENDF) format was designed in the 1960s to accommodate neutron reaction data to support nuclear engineering applications in power, national security and criticality safety. Over the years, the scope of the format has been extended to handle many other kinds of data including charged particle, decay, atomic, photo-nuclear and thermal neutron scattering. Although ENDF has wide acceptance and support for many data types, its limited support for correlated particle emission, limited numeric precision, and general lack of extensibility mean that the nuclear data community cannot take advantage of many emerging opportunities. More generally, the ENDF format provides an unfriendly environment that makes it difficult for new data evaluators and users to create and access nuclear data. The Cross Section Evaluation Working Group (CSEWG) has begun the design of a new Generalized Nuclear Data (or 'GND') structure, meant to replace older formats with a hierarchy that mirrors the underlying physics, and is aligned with modern coding and database practices. In support of this new structure, Lawrence Livermore National Laboratory (LLNL) has updated its nuclear data/reactions management package Fudge to handle GND structured nuclear data. Fudge provides tools for converting both the latest ENDF format (ENDF-6) and the LLNL Evaluated Nuclear Data Library (ENDL) format to and from GND, as well as for visualizing, modifying and processing (i.e., converting evaluated nuclear data into a form more suitable to transport codes) GND structured nuclear data. GND defines the structure needed for storing nuclear data evaluations and the type of data that needs to be stored. But unlike ENDF and ENDL, GND does not define how the data are to be stored in a file. Currently, Fudge writes the structured GND data to a file using the eXtensible Markup Language (XML), as it is ASCII based and can be viewed with any text editor. XML is a meta-language, meaning that it has a primitive set of definitions for representing hierarchical data/text in a file. Other meta-languages, like HDF5 which stores the data in binary form, can also be used to store GND in a file. In this paper, we will present an overview of the new GND data structures along with associated tools in Fudge.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Verification of MCNP6.2 with ENDF/B-VIII.0 Nuclear Data for Nuclear Criticality Safety Applications

MCNP6.2 was released in 2018 and is the latest production release of MCNP ® available from RSICC. MCNP6.2 includes all of the standard features for nuclear criticality safety (NCS) calculations that have been available for the past 15 years, along with new features for sensitivity-uncertainty based methods using Whisper for NCS validation. MCNP6.2 verification using ENDF/B-VII.1 nuclear data was previously reported in. This report focuses on the initial testing and verification of MCNP6.2 using the ENDF/B-VIII.0 nuclear data that were released in 2018. The sections that follow provide guidance for NCS users on modifying existing MCNP input files to use the new ENDF/B-VIII.0 ACE nuclear data, discussion of results for several ICSBEP-based benchmark suites using MCNP6.2 with ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Integral Benchmark Data for Nuclear Data Testing Through the ICSBEP & IRPhEP

The status of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and International Reactor Physics Experiment Evaluation Project (IRPhEP) was last discussed directly with the nuclear data community at ND2007. Since ND2007, integral benchmark data that are available for nuclear data testing have increased significantly. The status of the ICSBEP and the IRPhEP is discussed and selected benchmark configurations that have been added to the ICSBEP and IRPhEP Handbooks since ND2007 are highlighted.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Nuclear Data Sheets for A = 109

Evaluated nuclear structure and decay data for all nuclei with mass number A = 109 (Y, Zr, Nb, Mo, Tc, Ru, Rh, Pd, Ag, Cd, In, Sn, Sb, Te, I, Xe) are presented. The experimental data are compiled and evaluated, and the best values for level and gamma-ray energies, quantum numbers, lifetimes, gamma-ray intensities, and other nuclear properties are recommended. Inconsistencies and discrepancies that exist in the literature are noted. This work supersedes the earlier evaluation by J. Blachot (2006Bl02), published in Nuclear Data Sheets107, 355 (2006).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Nuclear Data Sheets for A=188☆

Evaluated nuclear structure and decay data for all nuclei with mass number A=188 (Lu, Hf, Ta, W, Re, Os, Ir, Pt, Au, Hg, Tl, Pb, Bi, Po) are presented. The experimental data are compiled and evaluated, and best values for level and gamma-ray energies, quantum numbers, lifetimes, gamma-ray intensities, and other nuclear properties are recommended. Inconsistencies and discrepancies that exist in the literature are noted. This work supersedes the earlier evaluation by Balraj Singh (2002Si10), published in Nuclear Data Sheets 95, 387 (2002). The gamma-ray transition probabilities were calculated using the ENSDF analysis program ruler (www-nds.iaea.org/public/ensdf{sub p}gm/). However, the reader should be warned that the program may produce incorrect results when dealing with non-symmetric uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Nuclear Data – Benchmarking 19 F(α,n) Yield Data for Nuclear Safeguards

Fluorine compounds of U and Pu are ubiquitous in the nuclear fuel cycle, so F(α,n) neutrons are an important signature and quantitative source term that needs to be understood for physics-based interpretation of nondestructive assay measurements. Historically there have been large differences in the basic nuclear data for this reaction reported by various groups. UF 6 is the most prominent material in the nuclear fuel cycle, with the potential for short-term production into weaponizable form. Verification of bulk quantities, natural feed, depleted tails, and especially low enriched product in cylinders is particularly important. The principal physical measurement is neutron counting. For enriched material, the 19 F(α,n) reaction, driven by 234U, is the dominant source of neutrons. Basic nuclear data, cross sections, needed to calculate the yield, as well as information on the source spectrum for sensitivity studies are sparse and highly discrepant. This limits defensible physics-based performance evaluations. The same applies to holdup and criticality studies in which hydrated uranyl fluoride is the material of interest which accumulates in enrichment facilities. In the future we anticipate that the physics community will have made improved accelerator-based measurements and undertaken a more thorough evaluation and adjustment of all relevant available data. But in the short term, this does not help the safeguards community face the pressing real-world nondestructive assay requirements. To address this need, we have performed quality neutron measurements on UF6 materials using well-known material and high-capability neutron counters. A robust determination of the n/s/g of 234 U in UF 6 was generated along with a scientifically defensible uncertainty analysis. The weighted average value of the neutron yield is 509 n/s/g 234 U with a random uncertainty of approximately 1%. Dominant sources of systematic uncertainty are in the efficiency determination where we incur approximately 1.1% relative standard deviation associated with the 252 Cf reference source and about 0.9% uncertainty coming from the uncertainty in the F(α,n) spectrum. The stated uncertainties are an order of magnitude better than current data based on accelerator data reported in the literature. Aside from being of immediate and direct use by the safeguards community, this result will serve as an enduring integral benchmark for subsequent data evaluations that will need to match it in order to be credible. In addition to yield normalization, safeguards users of F(α,n) data also need guidance of the neutron emission spectrum. We have generated a neutron emission using a modified version of the well-known SOURCES 4C code, updated with new alpha stopping power coefficients, and a blended microscopic cross section data set. The yield and spectra are available in a form that MCNP users can readily use.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Nuclear Data and Benchmarking Program: Nuclear Data Performance Assessment for Advanced Reactors

Over the last several Evaluated Nuclear Data File (ENDF)/B releases, many updates have been introduced to the nuclear data libraries that can significantly change computational results. These changes can be particularly important for advanced reactor concepts, which are not as thoroughly investigated as those used in light water reactor (LWR) systems. Therefore, a performance assessment of the ENDF/B libraries using the SCALE 6.2.3 code package was conducted under the auspices of the U.S., Department of Energy Office of Nuclear Energy (DOE-NE). The following systems relevant to the advanced reactor community were chosen as subject for investigation in this report: sodium cooled fast reactor systems, graphite moderated high temperature gas-cooled reactors, and several molten salt reactor models. At first, the similarity of the integral performance of the ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data libraries caused by compensating errors in important differential data was demonstrated. In calculations for a shipping container of high-assay low enriched uranium, the data of individual isotopes were systematically swapped between the two ENDF/B libraries. An eigenvalue difference of up to 450 pcm was found due to the use of 235 U and 238 U from one library and 1 H and 16 O from the other library. This clearly demonstrates a cross-correlation between reaction data sets of different isotopes within a library that should be reported in the evaluations. For sodium-cooled fast reactor (SFR) fuel assemblies, significant eigenvalue (k inf ) differences (200– 450 pcm) were found between calculations using the 2011 ENDF/B-VII.1 data and 2018 ENDF/B-VIII.0 data. These differences were mainly caused by updates of 238 U and 239 Pu neutron cross sections. Results from the multigroup (MG) calculations further revealed that the group structure of the applied MG library strongly influences the MG bias due to the importance of an appropriate energy resolution of the resonances in higher energy ranges. The application of previously used MG libraries requires new verification for advanced reactor simulation in comparisons with reference continuous-energy calculations. Nuclear data uncertainty analyses of these SFR systems resulted in eigenvalue uncertainties between 1,400 and 1,800 pcm, which are three to four times higher than corresponding uncertainties in light water reactor (LWR) systems. The main contributor to this uncertainty was found to be inelastic scattering on 238 U, which shows an uncertainty of up to 50% in the fast energy range. Other important contributors are the scattering reactions of 56 Fe and 23 Na which have so far not appeared in LWR analysis. Since the largest contribution to the eigenvalue uncertainty of SFR systems is coming from scattering reactions, it is expected that uncertainties in the angular scattering distributions also have a significant impact. Those uncertainties are, however, not available for the majority of nuclides, and the capabilities to determine sensitivities to this data are currently underdeveloped. For two graphite moderated high temperature gas-cooled reactor (HTGR) benchmarks, only the ENDF/BVII. 1 calculations resulted in consistent eigenvalues (k eff ) with the corresponding experimental measurements. Eigenvalue differences of about 1,000 pcm were found between the 2006 ENDF/B-VII.0 data and the 2011 ENDF/B-VII.1 data, primarily due to an updated carbon capture cross section in the thermal energy range in the later ENDF/B release. The ENDF/B-VIII.0 eigenvalue was larger than the ENDF/B-VII.1 eigenvalue by about 300 pcm mainly due to updates in multiple 235 U neutron cross sections, with offsetting updates in the 238 U cross sections. With ENDF/B-VIII.0, graphite can be modeled as perfect crystal or with two different porosities. The choice of the graphite evaluation can have a significant influence of the eigenvalue. For a HTGR benchmark, maximum eigenvalue differences as high as 650 pcm due to different porosities were observed. More detailed studies of the impact of the porosity are necessary while considering that the graphite porosity can vary between the used materials and changes as a function of neutron fluence. xii The uncertainty of the HTGR eigenvalues due to nuclear data uncertainties was found between 500 and 600 pcm, with the top contributor being the neutron multiplicity of 235 U. A gap in the form of missing uncertainties in graphite thermal scattering data, that might have significant impact on HTGR reactors, was identified. This gap is being investigated by the DOE-NE Nuclear Data and Benchmarking Program, as documented in a separate report The fast spectrum molten salt reactor calculations revealed similar comparisons as for the SFR assemblies. The eigenvalue uncertainties were significantly influenced by inelastic scattering on 238 U, while the impact of angular scattering distributions is unknown. For the graphite and zirconium hydride moderated system, eigenvalue uncertainties of up to 700 pcm were observed, requiring in depth analyses of the cross sections and corresponding uncertainties of the included materials. In general, it was observed that the flux spectra of the various molten salt reactor systems show significant differences, even between a fresh state and a depleted state. The choice of the energy group structure of MG calculations is therefore highly relevant; the applicability of previously used MG libraries needs to be verified. Due the unavailability of pin power measurements of advanced reactor systems, pin power calculations with both ENDF/B-VII.1 and VIII.0 data were performed for a light water reactor and compared to corresponding measurements. Both calculations show good agreement with the measurements. A comparison between the ENDF/B-VII.1 and VIII.0 results revealed small differences, mostly in the range of about 0.2%.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Nuclear Data Sheets for A=140☆

The 2006 evaluation of A=140 was updated using experimental results published before November 2018 from the various reaction and decay studies leading to the nuclei {sup 140}Sb, {sup 140}Te, {sup 140}I, {sup 140}Xe, {sup 140}Cs, {sup 140}Ba, {sup 140}La, {sup 140}Ce, {sup 140}Pr, {sup 140}Nd, {sup 140}Pm, {sup 140}Sm, {sup 140}Eu, {sup 140}Gd, {sup 140}Tb, {sup 140}Dy, {sup 140}Ho. These data are summarized and presented, together with adopted level schemes and properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Nuclear Data Sheets for A = 209

The experimental data are evaluated for known nuclides of mass number A = 209 (Au,Hg,Tl,Pb,Bi,Po,At,Rn, Fr,Ra,Ac,Th). Detailed evaluated level properties and related nuclear structure information are presented, with the best values recommended for level energies, half-lives, γ–ray energies and intensities, decay data (energies, intensities and placement of radiations), and other spectroscopic data. This work supersedes the earlier full evaluation of A = 209 by M.J. Martin (1991Ma16)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Estimating List-Mode Data Sensitivities to Nuclear Data with MCNP6

Nuclear data are a vital component of predictive simulations used in applications like experiment design, stockpile stewardship, nuclear nonproliferation/safeguards, health physics, and criticality safety. A singular simulation requires the coalescence of different areas of nuclear data such as cross sections, angular distributions, and energy distributions of emitted neutrons for different materials and energy ranges. Improving nuclear data and thus reducing the uncertainty in simulated parameters could enable smaller, better-informed safety factors and ultimately reduce operational and procedural costs. There is a constant effort to garner a better understanding of the physical quantities represented by nuclear data through experiments. Integral experiment benchmarks use simulated and measured results to validate current nuclear data values. In the past, benchmarks primarily focused on the effective multiplication factor (k eff ); however, this limited scope has caused compensating errors and areas of nuclear data that lack validation. Compensating errors are inaccuracies in nuclear data that are obfuscated by cancellation when observing integrated values such as k eff . Diverse integral benchmark experiments that look for quantities of interest other than k eff and include multiple responses minimize the possibility of compensating errors and provides validation to areas of nuclear data previously lacking experimental validation. Benchmark experiments can be optimized during the design process to be highly dependent on specific areas of nuclear data. The dependence of a response in an experiment to a specific area/type of nuclear data is defined as sensitivity. A larger sensitivity means that nuclear data uncertainties will play a larger role in the response(s) resulting in larger bias. Currently, the sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®1 ) transport code are limited to responses of k eff and tallied values (e.g., flux, surface current). As a part of the EUCLID project, this work explores estimating list-mode nuclear data sensitivities that can be used to design experiments aimed to constrain and reduce compensating errors in nuclear data by focusing on responses other than k eff . Tallied values are ideal quantities that are estimated with detectors during experiments. List-mode data (a list of neutron collection times) are the direct output of detector systems in subcritical neutron noise experiments. Expanding MCNP sensitivity capabilities to include the sensitivity of responses estimated from list-mode data, such as the prompt neutron decay constant (α) and multiplicity estimates (S and D), enables more direct comparison of simulated and measured experimental quantities. Additionally, deterministic tools such as SENSMG are capable of obtaining sensitivities to a wide variety of responses; however, these tools cannot handle complex geometries due to the assumptions made in discretizing the phase-space variables of the Boltzman transport equation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

New Improved Nuclear Data for Nuclear Criticality and Safety

The Geel Electron Linear Accelerator (GELINA) was used to measure neutron total and capture cross sections of 182,183,184,186 W and 63,65 Cu in the energy range from 100 eV to {approx}200 keV using the time-of-flight method. GELINA is the only high-power white neutron source with excellent timing resolution and ideally suited for these experiments. Concerns about the use of existing cross-section data in nuclear criticality calculations using Monte Carlo codes and benchmarks were a prime motivator for the new cross-section measurements. To support the Nuclear Criticality Safety Program, neutron cross-section measurements were initiated using GELINA at the EC-JRC-IRMM. Concerns about data deficiencies in some existing cross-section evaluations from libraries such as ENDF/B, JEFF, or JENDL for nuclear criticality calculations were the prime motivator for new cross-section measurements. Over the past years many troubles with existing nuclear data have emerged, such as problems related to proper normalization, neutron sensitivity backgrounds, poorly characterized samples, and use of improper pulse-height weighting functions. These deficiencies may occur in the resolved- and unresolved-resonance region and may lead to erroneous nuclear criticality calculations. An example is the use of the evaluated neutron cross-section data for tungsten in nuclear criticality safety calculations, which exhibit discrepancies in benchmark calculations and show the need for reliable covariance data. We measured the neutron total and capture cross sections of 182,183,184,186 W and 63,65 Cu in the neutron energy range from 100 eV to several hundred keV. This will help to improve the representation of the cross sections since most of the available evaluated data rely only on old measurements. Usually, these measurements were done with poor experimental resolution or only over a very limited energy range, which is insufficient for the current application.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Nuclear Data Uncertainty Quantification: Past, Present and Future

An historical overview is provided of the mathematical foundations of uncertainty quantification and the roles played in the more recent past by nuclear data uncertainties in nuclear data evaluations and nuclear applications. Significant advances that have established the mathematical framework for contemporary nuclear data evaluation methods, as well as the use of uncertainty information in nuclear data evaluation and nuclear applications, are described. This is followed by a brief examination of the current status concerning nuclear data evaluation methodology, covariance data generation, and the application of evaluated nuclear data uncertainties in contemporary nuclear technology. A few possible areas for future investigation of this subject are also suggested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗