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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nuclear Data Sheets for A=98

Experimental spectroscopic data on nuclear structure and decay are evaluated for known nuclides of mass 98 (Br, Kr, Rb, Sr, Y, Zr, Nb, Mo, Tc, Ru, Rh, Pd, Ag, Cd, In). Detailed evaluation results of individual reactions and decays are presented together with the Adopted values that are recommended for level properties, γ and β radiations, and other spectroscopic information. 98 Mo remains as the most extensively studied nuclide via various reactions and decays. Level schemes of Sr, Y, Zr, Tc, and Pd nuclides in this mass chain are also well established to date; while Kr, Rb, Nb, Ag and Cd are amongst the least-studied ones for excited states, with only limited data available for each. On the neutron-rich side, 98 Br has been identified in the 9 Be(238U,F) reaction, but no spectroscopic data are yet available, while for 98 In on the proton-rich side, only the ground state and an isomer are known with half-lives measured but their spin-parities and the absolute level energy of the isomer yet to be determined. While 98 Ru and 98 Rh have also been extensively studied, large discrepancies exist between the high-spin sections of the proposed level schemes in different measurements, and these need to be clarified and resolved with further experimental investigations to improve the currently-adopted ones, which have been selected from the measurements with higher statistics, considering no other criteria of preference. Furthermore, this work supersedes all the earlier evaluations of A=98 (2003Si07, 1998Si18, 1992Si21, 1983Mu21, 1974Me34).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Advancing the Theory of Nuclear Data Evaluations [Abstract]

We present recent advances in the R-matrix formalism as well as the Bayesian evaluation framework for improved nuclear data evaluations. The advances in the R matrix formalism include: 1) direct processes, 2) doorway, as well as multistep, processes, and 3) various forms of the Reich-Moore approximation for eliminated capture channels. Furthermore, to address unreasonably small posterior uncertainties often encountered in nuclear data evaluations of large data sets using the conventional form of the Bayes’ theorem, we introduce imperfections (of the data or the model) as a formal evaluation tool for taming the evaluated uncertainties in harmony with Bayes’ theorem. These theoretical advances were motivated by the nuclear data evaluations of differential resolved resonance cross section data using the code SAMMY, as well as the integral benchmark experiments using the SCALE code system, being performed at Oak Ridge National Laboratory for the Nuclear Criticality Safety Program. Some pedagogical applications of the new formalism, as well as a snapshot of the SAMMY modernization efforts, will be presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Nuclear data for space exploration

Understanding the harmful effects of galactic cosmic rays (GCRs) on space exploration requires a substantial amount of nuclear data. Specifically, the interaction of energetic GCR charged particles with spacecraft materials generates secondary radiations that, through energy deposition, can harm astronauts and electronic systems. By identifying the gaps in our knowledge of the relevant nuclear data—such as interaction cross sections—and identifying ways to fill those gaps—with measurements, compilations, evaluations, dissemination, reaction modeling, sensitivity studies, and uncertainty quantification—the safety and viability of space exploration can be improved. This work surveys the state of the art in this interdisciplinary field and identifies promising collaborative research topics that have significant potential to advance our understanding of the effects of the space radiation environment on space exploration.

42 ENGINEERING↗
DOE OSTI2012

TENDL-2011: TALYS-based Evaluated Nuclear Data Library

The 4. release of the TENDL library, TENDL-2011 (TALYS-based Evaluated Nuclear Data Library) is described. This library consists of a complete set of nuclear reaction data for incident neutrons, photons, protons, deuterons, tritons, helions and alpha particles, from 10-5 eV up to 200 MeV, for all isotopes from {sup 6}Li to {sup 281}Ds that are either stable of have a half-life longer than 1 second. All data are completely and consistently evaluated using a software system consisting of the TALYS-1.2 nuclear reaction code, and other programs to handle resonance data, experimental data, data from existing evaluations, and to provide the final ENDF-6 formatting. The result is a nuclear data library with mutually consistent reaction information for all isotopes and a quality that increases with yearly updates. To produce this library, TALYS input parameters are adjusted for many nuclides so that calculated cross sections agree with experimental data, while for important nuclides experimental data are directly included. All information is available on www.talys.eu and www.talys.eu/TENDL-2011. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Nuclear Data Sheets for A = 198

The 2009 version of Nuclear Data Sheets for A=198 (2009Hu11) has been updated and revised on the basis of the experimental results from various decay and reaction studies before December 2014. The experimental data for all known nuclei with mass number A=198 (Re,Os,Ir,Pt,Au,Hg,Tl,Pb,Bi,Po,At,Rn,Fr) have been revised, updated, and incorporated into the ENSDF data file. The experimental methods, references, Jπ arguments, and necessary comments are given in the text. The adopted levels for 198Re and 198Fr are firstly presented in this evaluation. In addition, Q values have been updated based on 2012Wa38.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Nuclear data uncertainty quantification for the nuclide inventory of a Calvert Cliffs spent fuel sample

The impact of nuclear data cross section uncertainties and covariance matrices on the nuclide vector of spent nuclear fuel was investigated; This exercise was carried out for the Calvert Cliffs fuel assembly D047 benchmark available in the SFCOMPO database. Sample P irradiated in rod MKP109 for 4 cycles up to a burnup of approximately 44 GWd/MTU was selected for the analysis. Nuclear data uncertainties were taken from the most recent libraries released by evaluation projects JEFF, ENDF/B and JENDL, and were propagated using the SANDY code via a stochastic sampling approach. This paper provides a quantification of the uncertainty on the concentration of several actinides and fission products relevant for spent fuel management. Uncertainties generally below 5 % were predicted for the concentrations of most of the uranium, neptunium and plutonium isotopes relevant for SNF applications. Curium isotopes carry larger uncertainties that might exceed 10 %. The contribution of cross section uncertainties on the concentrations of fission products was found to be marginal with the exception of a few nuclides. These results can be significantly affected by the lack of evaluated covariance matrices for the capture cross section of several fission products. Burnup tracers such as {sup 148}Nd and {sup 137}Cs have negligible uncertainties because of the power normalisation imposed in every stochastic calculation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Using NJOY to Create MCNP ACE Files and Visualize Nuclear Data

We provide lecture materials that describe the input requirements to create various MCNP ACE files (Fast, Thermal, Dosimetry, Photo-nuclear and Photo-atomic) with the NJOY Nuclear Data Processing code system. Input instructions to visualize nuclear data with NJOY are also provided.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

Release of the ENDF/B-VII.1 Evaluated Nuclear Data File

The Cross Section Evaluation Working Group (CSEWG) released the ENDF/B-VII.1 library on December 22, 2011. The ENDF/B-VII.1 library is CSEWG's latest recommended evaluated nuclear data file for use in nuclear science and technology applications, and incorporates advances made in the five years since the release of ENDF/B-VII.0, including: many new evaluation in the neutron sublibrary (423 in all and over 190 of these contain covariances), new fission product yields and a greatly improved decay data sublibrary. This summary barely touches on the five years worth of advances present in the ENDF/B-VII.1 library. We expect that these changes will lead to improved integral performance in reactors and other applications. Furthermore, the expansion of covariance data in this release will allow for better uncertainty quantification, reducing design margins and costs. The ENDF library is an ongoing and evolving effort. Currently, the ENDF data community embarking on several parallel efforts to improve library management: (1) The adoption of a continuous integration system to provide evaluators 'instant' feedback on the quality of their evaluations and to provide data users with working 'beta' quality libraries in between major releases. (2) The transition to new hierarchical data format - the Generalized Nuclear Data (GND) format. We expect GND to enable new kinds of evaluated data which cannot be accommodated in the legacy ENDF format. (3) The development of data assimilation and uncertainty propagation techniques to enable the consistent use of integral experimental data in the evaluation process.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Bayesian Monte Carlo Evaluation Framework for Imperfect Nuclear Data

Bayesian evaluation of resolved resonance region (RRR) nuclear data has historically been carried out using the generalized least squares (GLS) formalism, as implemented in, e.g., SAMMY. We have recently developed a prototype of Bayesian Monte Carlo (BMC) evaluation framework, implemented using a Markov Chain Monte Carlo (MCMC) method with a Metropolis-Hastings (MH) acceptance criterion. This was done in order to remove the approximations underlying the conventional GLS evaluations, namely, the linear approximation, and the approximation that all probability density functions (PDFs) are of the normal kind. Recent works by others have used similar stochastic approaches to quantify cross section uncertainties from ENDF evaluated co-variances, and/or, from integral benchmark data, but those have not been conceived as an evaluation framework like the one presented here.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

User input verification and test driven development in the NJOY21 nuclear data processing code

Before physically-meaningful data can be used in nuclear simulation codes, the data must be interpreted and manipulated by a nuclear data processing code so as to extract the relevant quantities (e.g. cross sections and angular distributions). Perhaps the most popular and widely-trusted of these processing codes is NJOY, which has been developed and improved over the course of 10 major releases since its creation at Los Alamos National Laboratory in the mid-1970’s. The current phase of NJOY development is the creation of NJOY21, which will be a vast improvement from its predecessor, NJOY2016. Designed to be fast, intuitive, accessible, and capable of handling both established and modern formats of nuclear data, NJOY21 will address many issues that many NJOY users face, while remaining functional for those who prefer the existing format. Although early in its development, NJOY21 is quickly providing input validation to check user input. By providing rapid and helpful responses to users while writing input files, NJOY21 will prove to be more intuitive and easy to use than any of its predecessors. Furthermore, during its development, NJOY21 is subject to regular testing, such that its test coverage must strictly increase with the addition of any production code. This thorough testing will allow developers and NJOY users to establish confidence in NJOY21 as it gains functionality. This document serves as a discussion regarding the current state input checking and testing practices of NJOY21.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Improvements to Nuclear Data and Its Uncertainties by Theoretical Modeling

This project addresses three important gaps in existing evaluated nuclear data libraries that represent a significant hindrance against highly advanced modeling and simulation capabilities for the Advanced Fuel Cycle Initiative (AFCI). This project will: Develop advanced theoretical tools to compute prompt fission neutrons and gamma-ray characteristics well beyond average spectra and multiplicity, and produce new evaluated files of U and Pu isotopes, along with some minor actinides; Perform state-of-the-art fission cross-section modeling and calculations using global and microscopic model input parameters, leading to truly predictive fission cross-sections capabilities. Consistent calculations for a suite of Pu isotopes will be performed; Implement innovative data assimilation tools, which will reflect the nuclear data evaluation process much more accurately, and lead to a new generation of uncertainty quantification files. New covariance matrices will be obtained for Pu isotopes and compared to existing ones. The deployment of a fleet of safe and efficient advanced reactors that minimize radiotoxic waste and are proliferation-resistant is a clear and ambitious goal of AFCI. While in the past the design, construction and operation of a reactor were supported through empirical trials, this new phase in nuclear energy production is expected to rely heavily on advanced modeling and simulation capabilities. To be truly successful, a program for advanced simulations of innovative reactors will have to develop advanced multi-physics capabilities, to be run on massively parallel super- computers, and to incorporate adequate and precise underlying physics. And all these areas have to be developed simultaneously to achieve those ambitious goals. Of particular interest are reliable fission cross-section uncertainty estimates (including important correlations) and evaluations of prompt fission neutrons and gamma-ray spectra and uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

NJOY21: A Successor to the NJOY Nuclear Data Processing System

NJOY21 is an initiative at Los Alamos National Laboratory (LANL) to develop software to succeed the NJOY nuclear data processing system. Specifically, the aim of the project is to provide: - a stand-alone executable for nuclear data processing in the vein of the original NJOY and, - a hierarchy of reusable loosely-coupled, object-oriented component libraries. The name NJOY21 was chosen to denote a commitment to provide software suitable for the 21. Century; integrating modern development practices and tools from the inception of the project. This summary will expand upon the current goals and design of the project. Before going onto discuss NJOY21, it is worthwhile to briefly establish the historical context and motivating factors. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

The Activities of the European Consortium on Nuclear Data Development and Analysis for Fusion

This paper presents an overview of the activities of the European Consortium on Nuclear Data Development and Analysis for Fusion. The Consortium combines available European expertise to provide services for the generation, maintenance, and validation of nuclear data evaluations and data files relevant for ITER, IFMIF and DEMO, as well as codes and software tools required for related nuclear calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

The Role of Nuclear Data Sensitivities in Prompt α-Eigenvalue Predictions of Delayed Critical Benchmarks

Alpha (α) eigenvalues, which describe the logarithmic time derivative of the neutron population in a multiplying system, are integral to time-dependent behavior and diagnostic applications. However, uncertainties in the evaluated nuclear data can significantly impact the accuracy of transport simulations for such quantities. This work explores the use of machine learning models to predict two key outputs, α-eigenvalues and keff bias, using input features derived from α-eigenvalue sensitivities to nuclear data. The criticality safety benchmark models used in this study come from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. Three models, random forest, XGBoost, and NGBoost, are trained on both energy-resolved and energy-summed α sensitivities. For the α-eigenvalue bias prediction, NGBoost achieved the highest R 2 (0.9476) using energy-resolved features, while XGBoost performed best using summed sensitivities. In contrast, when predicting the keff bias, all the models showed moderate predictive capability (best R 2 ≈ 0.72), as the mapping from the static α-sensitivities to the static keff bias was less direct. SHAP (SHapley Additive exPlanations) analysis was used to interpret the model predictions. Across both prediction tasks, the features associated with neutron capture [H-1 (n, γ)], uranium scattering reactions (such as 235 U elastic/inelastic), and actinide capture/fission reactions (such as 239 Pu and 234 U) were consistently identified as the most impactful. This highlights the key role of specific nuclear reactions and energy ranges in shaping both time-dependent and steady-state criticality behavior. These results demonstrated that α-sensitivities, despite being computed for time-dependent metrics, can provide valuable insights for predicting both α-eigenvalues and the keff bias. Moreover, machine learning models offer a promising pathway for uncovering important nuclear data dependencies and guiding future data evaluation efforts.

Nuclear data↗
DOE OSTI2023

Nuclear Data for Spallation Neutron Radioisotope Production (Final Technical Report)

Over 50 million nuclear medicine procedures are performed annually, leading to a multi-billion dollar market for radioisotope production. The demand for new medical and research isotopes is growing, and radioisotope supply is insufficient. Most radioisotope production today utilizes charged particle or low-energy neutron irradiation of a target. Isotope production with tens to hundred MeV incident energies is a relatively unexplored option. There is a tremendous opportunity associated with a growing number of suitable domestic and international facilities buttressed by hundred million dollar global investments (e.g., the Los Alamos and Brookhaven Isotope Production Facilities, the European Spallation Source in Lund, and the Korean Multi-purpose Accelerator Complex in Gyeongbuk). In part due to a lack of supporting nuclear data that would make modeling radioisotope yields and purities possible, these facilities do not utilize their high-energy neutron fluxes for isotope production. This project attempted to measure neutron reaction excitation functions relevant to the large-scale production of critical radioisotopes, enabling development of cost-efficient isotope production methods, contributing to the improvement of theoretical models, and enhancing the value of national isotope production facilities. Reactions which form 67 Cu, 32 Si, and alpha-emitting isotopes like 225 Ac were chosen for their consistent prioritization by expert panels, representation of diverse reaction mechanisms, and relative lack of supporting nuclear data. Accurate measurement of these data is presently made only using quasi-monoenergetic neutron beams, which are produced by bombarding thin lithium targets with protons at only a few laboratories in the world. Ultimately, the projects efforts were incompletely accomplished due to a combination of multi-year technical issues at the only laboratory in the world which can make the proposed measurements, iThemba Labs in South Africa, and the onset of a global pandemic, which precluded the significant effort and time required to develop an independent measurement capability in the United States.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Nuclear data uncertainty propagation applied to the versatile test reactor conceptual design

We report the Versatile Test Reactor (VTR) currently under development is a 300 MWth sodium-cooled fast reactor (SFR) fueled with ternary metal alloy fuel, which aims to accelerate the testing of advanced nuclear fuels, materials, instrumentation, and sensors in high flux environments that are necessary to license the next generation of advanced reactor concepts. To support the VTR design process, uncertainties associated with the nuclear data has been propagated through the reactor core neutronics calculation to global parameters of interest, such as the core multiplication factor, kinetic parameters, and various reactivity feedback coefficients, following the sensitivity based uncertainty propagation approach. By folding the sensitivity coefficients, separately computed by the generalized perturbation theory code PERSENT and Monte Carlo code Serpent 2, with the variance-covariance matrices from COMMARA-2.0, we obtain the reaction-wise, isotope-wise, and overall uncertainties for each response of interest due to nuclear data uncertainty. With Serpent 2, the statistical error of the uncertainty is obtained by propagating the statistical error of the sensitivity coefficients through the same process using a newly developed uncertainty propagation method. From both codes, the overall top uncertainty contributors are found to be the cross section of Fe-56 elastic scattering, Na-23 elastic scattering, and U 238 inelastic scattering. The large contributions of the Fe-56 elastic scattering cross sections to global parameters are due to its relatively large relative uncertainty of 5–10% in nuclear data and the large volume of Fe-containing reflector assemblies in the fairly compact VTR core design. Both codes agreed well for the overall uncertainty estimates of all responses of interest, except the delayed neutron fraction, prompt neutron generation time, and the coolant density feedback coefficient, where Serpent 2 yielded a much larger value than PERSENT due to the large statistical error of sensitivity coefficients. The calculated uncertainties are also compared to those associated with other SFR cores. Another outcome of this study is a variance-covariance matrix of reactivity coefficients, which can be used in the subsequent uncertainty propagation to the system level to investigate the impact of identified uncertainties on system responses in the safety analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗