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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.

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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 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 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 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↗
DOE OSTI2018

Nuclear Data Sheets for A=170☆

Nuclear structure data pertaining to all nuclei with mass number A=170 have been evaluated, and incorporated into the ENSDF data file. This evaluation supersedes the previous evaluation (Coral M. Baglin), Nuclear Data Sheets 96, 611 (2002), (cutoff date 15 August 2002) and subsequent updates of the ENSDF file for Yb to Dy (cutoff 15 April 2010), Lu (cutoff 8 October 1998), Pt (cutoff 17 February 1999) and Ta, Os (cutoff 7 April 1998). Since the previous evaluation, {sup 170}Gd has been observed and the ground state T{sub 1/2} measured. New excited states have also been observed in the neutron rich {sup 170}Dy. The ground state T{sub 1/2} of {sup 170}Tb has been determined, however, there are currently still no excited states observed in this nucleus. There remains some uncertainty in the ground state and longer-lived isomer in {sup 170}Ir which could warrent further experimental investigation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Nuclear Data Sheets for A = 183

Evaluated nuclear structure and decay data for all nuclides with mass number A=183 (Yb, Lu, Hf, Ta, W, Re, Os, Ir, Pt, Au, Hg, Tl, Pb) are presented here. At, Po and Fr have not yet been observed, but for prediction of ground state and/or isomer properties see, e.g., 2015Bh08 (At, Fr), 2013Ba41 (Tl), 2013Ho05 (Po). This evaluation includes structure and decay data information available by 15 April 2015 and supersedes that by R.B. Firestone published in Nuclear Data Sheets65, 589 (1992) (literature cutoff 9 January 1991), and subsequent revisions by C.M. Baglin for {sup 183}Au in ENSDF database (literature cutoff 13 March 1999), {sup 183}Hg in Nuclear Data Sheets91, 117 (2000) (literature cutoff 25 September 2000), {sup 183}Tl in Nuclear Data Sheets95, 49 (2002) (literature cutoff 1 January 2002) and {sup 183}Pb in ENSDF (literature cutoff 6 January 2003). Since the prior Nuclear Data Sheets publication of this mass chain: {sup 183}Yb (2012Ku26) and {sup 183}Pb (2006An11, 2006Se18, 2007De09, 2009Se13) have been observed; our knowledge of high–spin states has been significantly expanded for {sup 183}Ta (2009Sh17), {sup 183}W (1999Sa60), {sup 183}Re (1998Ha51, 2001Sh41), {sup 183}Au (2002Jo18, 2005So01) and {sup 183}Tl (2001Mu26, 2004Ra28); a large amount of new structure information for {sup 183}W has been obtained from transfer reactions (1997Pr02, 2011Bo09), (n,n'γ) (1993Pr09) and thermal neutron capture (1993Pr09, 1997Pr02, 2011Bo09, 2014Hu02), as well as from the two–photon cascade study by 2005Su29.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Working Party on International Nuclear Data Evaluation Cooperation (WPEC)

The OECD Nuclear Energy Agency (NEA) organizes cooperation between the major nuclear data evaluation projects in the world. The NEA Working Party on International Nuclear Data Evaluation Cooperation (WPEC) was established to promote the exchange of information on nuclear data evaluation, measurement, nuclear model calculation, validation, and related topics, and to provide a framework for cooperative activities between the participating projects. The working party assesses nuclear data improvement needs and addresses these needs by initiating joint activities in the framework of dedicated WPEC subgroups. Studies recently completed comprise a number of works related to nuclear data covariance and associated processing issues, as well as more specific studies related to the resonance parameter representation in the unresolved resonance region, the gamma production from fission product capture reactions, the {sup 235}U capture cross section, the EXFOR database, and the improvement of nuclear data for advanced reactor systems. Ongoing activities focus on the evaluation of {sup 239}Pu in the resonance region, scattering angular distribution in the fast energy range, and reporting/usage of experimental data for evaluation in the resolved resonance region. New activities include two subgroups on improved fission product yield evaluation methodologies and on modern nuclear database structures. Future activities under discussion include a pilot project for a Collaborative International Evaluated Library Organization (CIELO) and methods to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data. In addition to the above mentioned short-term task-oriented subgroups, WPEC also hosts a longer-term subgroup charged with reviewing and compiling the most important nuclear data requirements in a high priority request list (HPRL)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

JRC-IRMM/ORNL Collaboration on Nuclear Data for Nuclear Criticality Safety - 14486

Concerns about using cross sections recommended in the main evaluated data libraries (i.e. ENDF/B, JEFF and JENDL) for nuclear criticality calculations have been a prime motivator for new cross section measurements. The measurements and evaluations discussed in this work are part of a collaboration between the Oak Ridge National Laboratory (ORNL) and the Institute for Reference Material and Measurements of the Joint Research Center (JRC-IRMM) of the European Commission (EC). They are performed in response to the US Nuclear Criticality Safety Program (NCSP) data needs. In particular, the NCSP five-year plan encompasses a listing of elements that have been identified for measurements and evaluations to address issues on criticality safety applications. This listing is based on data deficiency concerns in practical applications that are conveyed by criticality safety practitioners. In general these deficiencies are obtained through the analysis of benchmark calculations. A wealth of evaluations in the main libraries were derived from results of measurements made with poor time-of-flight resolution, and also the description of some data in the neutron energy range above several tens of keV is crude. This impacts both the resolved and unresolved resonance region, and leads to bias effects when resonance structures play an important role. As a consequence only average corrections can be applied in calculations for nuclear criticality calculations where self-shielding, multiple scattering, or Doppler broadening are important. This can lead to erroneous results. Furthermore, many evaluations for nuclides having small neutron-capture cross sections show erroneously high cross sections because the influence of the neutron sensitivity of the old measurement systems was underestimated. Although their neutron capture cross sections are small, these nuclides, if occurring in large amounts, can be important absorbers in criticality calculations, so an accurate determination of these cross sections is required. Over the last seven years the JRC-IRMM/ORNL collaboration has produced many neutron induced cross section data using the Geel Electron Linear Accelerator (GELINA) neutron time-of-flight facility. This facility is ideally suited to measure total, fission and capture cross sections in the energy range from 1 eV to ∼600 keV, which is important for nuclear criticality calculations. In this paper the facility and experimental set-ups at GELINA will be described together with the data reduction and analysis procedures which result in experimental observables including their full covariance information. The importance of combining transmission and partial cross section data will be emphasized. We will give a list of the measured nuclides and discuss the impact of the resulting data and evaluations. (authors)

42 ENGINEERING↗
DOE OSTI2018

Nuclear Data Sheets for A=171

Experimental data pertaining to all nuclei with mass number A=171 (Tb, Dy, Ho, Er, Tm, Yb, Lu, Hf, Ta, W, Re, Os, Ir, Pt, Au, Hg) have been evaluated. Level schemes from both radioactive decay and reaction studies are presented, along with associated tables of experimental data and adopted properties for levels and γ rays. This evaluation for A=171, which considers data received by 30 June 2018, supersedes the 2002 evaluation (with a literature cutoff date of August 2002) by Coral M. Baglin, published in Nuclear Data Sheets 96, 399 (2002) and the subsequent evaluation of the ENSDF file for 171Pt by C. Baglin (literature cutoff date of 15 April 2010).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Automated Resonance Fitting for Nuclear Data Evaluation

Global and national efforts to deliver high-quality nuclear data to users have a wide-ranging impact, affecting applications in national security, reactor operations, basic science, medicine, and more. Cross section evaluation is a major part of this effort, combining theory and experimentation to produce recommended values and uncertainties for reaction probabilities. Resonance region evaluation is a specialized type of nuclear data evaluation that can require significant manual effort and months of time from expert scientists. In this article, non-convex non-linear optimization methods are combined with concepts of inferential statistics to infer a resonance model from experimental data in an automated manner that is not dependent on prior evaluation(s). This methodology aims to enhance the workflow of a resonance evaluator by minimizing time, effort, and the potential for bias from prior assumptions, while enhancing reproducibility and documentation, thereby addressing well-known challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗