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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Data Evaluation of Actinide Cross Sections: 230 Th and 231 Th

A new evaluation of the ENDL cross section set for Thorium (Z=90) is developed using the TALYS statistical model cross section code. The primary goal of this effort is to produce an evaluation that attempts to match as closely as possible fission cross sections developed through surrogate reaction techniques on actinide targets 230 Th and 231 Th. This evaluation effort and the processing needed to render its results into data libraries is a necessary step in making the efforts of nuclear experimentalists useful to the broad community of researchers engaged in simulations of nuclear fusion for basic and applied science. Another aspect, verification and validation against various AGEX experiments, is also presented. The end-product is an updated library that includes the latest measurements of fission cross sections for comparison against those measured via traditional techniques. All the steps in the evaluation, processing, validation and verification, and library release are described in the following sections. For completeness, the appendix contains all the parameters used in the TALYS cross section evaluation for neutrons incident on 230 Th and 231 Th.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Study of Excited Cascade Baryons and Preliminary Cross-Sections for Ξ(1530) Using Data from the GlueX Experiment

The spectra of predicted particles from elementary quark models (CQMs) are expansive, accurate for the low-lying spectra, but incomplete. The GlueX experiment at Jefferson Lab is a vehicle to study medium energy photoproduction of hadronic states. The primary goal of the GlueX collaboration is to study Quantum Chromodynamics (QCD, also known as the strong nuclear force) and the nature of quark confinement. The GlueX collaboration uses a polarized photon beam incident on a liquid hydrogen target (LH 2 ) to investigate the aftermath of photon-proton interactions. The cascade baryons, denoted by Ξ, are defined by having two, second-generation, strange quarks with an additional first-generation light quark (u or d). Experimentally, few cascades have been discovered, which is the antithesis of what most models expect. The cascades have some favorable attributes but are difficult to detect because the production cross sections are small and direct production is unlikely. Fortunately, in the 12 GeV era of the GlueX experiment, there is sufficient energy, beam time and data analysis tools for the detection of excited cascade states and their properties. From the reaction γ p →Κ + Κ + Ξ - π 0 , the invariant mass spectra of Ξ - π 0 system was surveyed for new possible resonances. The invariant mass spectrum has a strong Ξ(1530) signal with other smaller resonances throughout the spectrum. Preliminary cross sections for the Ξ(1530) that was photoproduced from the proton are presented at energies never before explored. While the Ξ(1530) couples almost exclusively to the Ξπ channel, there is an easily identifiable Ξ(1690) signal decaying Ξπ. Through the use of a simultaneous fitting routing of the Ξ*- mass spectra, I was able to observe the Ξ(1690) decaying to the KΛ, as well as to the Ξ - π 0 branch. With additional statistics, a measurement of the branching ratio should be possible. Lastly, a partial wave analysis (PWA) was completed to verify that the total angular momentum of Ξ(1530) is J = 3/2 and consistent with having positive parity. Additionally, there is evidence of a potentially interesting feature slightly above the mass of the Ξ(1530) that should be more fully explored as new GlueX data becomes available.

Sumner, Brandon↗
DOE OSTI2025

Criticality Safety S/U based USL Calculation for UCl3-NaCl Fuel Salt Operations

Recent experimental data has shown inconsistencies with the 35Cl(n,p) cross-section. The cross-section uncertainty data does not account for the recent data. The 1s relative uncertainty is assumed to be 100% for the 35Cl(n,p) cross section over all energies above 0.017 MeV TerraPower and LANL have recently done cross-section measurements and developed new cross-sections for 35Cl.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

(U) SENSMG: First-Order Sensitivities of Neutron Reaction Rates, Reaction-Rate Ratios, Leakage, k eff , α , and Subcritical Multiplication Using PARTISN

SENSMG is a tool for computing first-order sensitivities of neutron reaction rates, reaction-rate ratios, leakage, k eff , α, and subcritical multiplication using the PARTISN multigroup discrete-ordinates code. SENSMG computes sensitivities to all of the transport cross sections and data (total, fission, a nu, chi, and all scattering moments), two edit cross sections (absorption and capture), and the density for every nuclide and energy group. It also computes sensitivities to the mass density for every material and derivatives with respect to all interface locations and outer boundaries. It computes sensitivities to user specified reactions whose cross sections are available in a user-supplied NJOY output file. The tool can be used for one-dimensional spherical and slab (r) and two-dimensional cylindrical (r-z) geometries. The tool can be used for fixed-source and eigenvalue problems. For most responses, the tool implements Generalized Perturbation Theory (GPT) as discussed by Williams and Stacey. The tool is thus limited to computing sensitivities only for GPT-allowable responses. For subcritical multiplication, the tool implements sensitivities derived by O’Brien and Clark. SENSMG has a similar role as the old SWANLAKE (Ref. 8), FORSS (Ref. 9), and SENSIT (Ref. 10) codes. It has capabilities similar to those of SUSD3D (Refs. 11 and 12), which also uses PARTISN. Section II of this report describes the theory behind adjoint-based sensitivities, gives the equations that SENSMG solves, and defines the sensitivities that are output. Section III describes the user interface, including the input file and command line options. Section IV describes the output. Section V gives some notes about the coding that may be of interest. Section VI presents some sample problems and discusses verification, which is ongoing. Section VII lists needs and ideas for future work. Appendix A lists most of the input files whose results are presented in Sec. VI. Appendix B provides some useful details on one of the cross-section libraries that SENSMG supports.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Erratum: Monoenergetic photon-induced fission cross-section ratio measurements for U 235 , U 238 , and Pu 239 from 9.0 to 17.0 MeV

In this erratum we report a correction to the previously published photofission cross-section ratio data. The actinide fission-chamber foils utilized in this work were extensively characterized during a new campaign using α- and γ-ray spectroscopy, and 2π alpha counting. These three techniques agreed, resulting in an improved accuracy of the fission-chamber foil masses used in the original experiment. The foil masses measured by α spectroscopy are detailed in Table I. All foils were counted on the same α spectrometer, using an identical geometry, which reduces the systematic uncertainty in the calculated mass ratios since the α spectrometer efficiency cancels out in the ratio. This results in a relative uncertainty on the mass ratio of 1.0% for 235 U/ 238 U, 0.62% for 239 Pu/ 235 U, and 1.1% for 239 Pu/ 238 U. The published cross-section ratio data are re-calculated to reflect the updated target masses and uncertainties. The new mass values cause a 2.40% decrease for the σ( 235 U(γ, f)/ 238 U(γ, f)) ratio, a 5.10% decrease for the σ( 235 U(γ, f)/ 239 Pu(γ, f)) ratio, and a 2.77% decrease for the σ( 238 U(γ, f)/ 239 Pu(γ, f)) ratio. The updated cross-section ratios are presented in Tables II, III, and IV, which are corrected versions of Tables III, IV, and V in Ref. [1]

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Applying a Template of Expected Uncertainties to Updating 239 Pu(n,f) Cross-section Covariances in the Neutron Data Standards Database

Templates of uncertainties expected in specific measurement types were recently developed. One aim of these templates is to help evaluators in identifying (1) missing or suspiciously low uncertainties and (2) missing correlations between uncertainties of the same and different experiments, when estimating covariances for experimental data employed in their evaluations. These templates also provide realistic estimates of standard deviations and correlations for a particular uncertainty source and measurement type that can be used by evaluators in situations where they are not supplied by the experimenters. This information allows for a more comprehensive uncertainty analysis across all measurements considered in an evaluation and, thus, more realistic evaluated covariances. Here, in this work, we extend a template that is applicable to uncertainties expected in neutron-induced fission, (n,f), cross-section measurements. It is applied to improving covariances of 239 Pu(n,f) cross-section measurements in the database underlying the Neutron Data Standards evaluations. This particular example was chosen since this evaluation is primarily based on experimental information. Also, some uncertainties of individual 239 Pu(n,f) cross-section experiments in this database were suspected to be underestimated. The evaluated uncertainties obtained after updating the covariances in the database by means of the template indeed do increase compared to their original values. Even more importantly, the evaluated mean values change noticeably. These modified cross sections impact application calculations significantly, as is demonstrated by employing them in simulations of the effective neutron multiplication factor for a few selected critical assemblies. However, this updated evaluated 239 Pu(n,f) cross section should not be interpreted as the final one that should replace values of the current Neutron Data Standards project. Evaluations for the Neutron Data Standards of the 239 Pu(n,f) cross section must be linked to many other observables included in the associated database, most notably to cross sections for 235 U(n,f), but also to those for 10 B(n, α ), 6 Li(n,t), 238 U(n,f), and 238 U(n, γ ), because of included measurements of the 239 Pu(n,f) cross section that appear as ratios to these reactions. Some of these other reactions are correlated to further observables in the database. Hence, updating uncertainties of data sets of any of these observables can potentially impact the 239 Pu(n,f) cross section. Uncertainties for all measurements of these linked physical observables have to be updated before a comprehensive evaluation of the 239 Pu(n,f) cross section and its corresponding uncertainties can be provided.

239Pu Neutron-induced fission cross-section↗
DOE OSTI2021

Fission TPC FY2020 Report (Mid Q2 FY2021): Preliminary 235 U(n,f)/ 6 Li(n,t)α Cross Section Ratio Analysis & Update on the 239 Pu(n,f) Data Collection

Fission TPC L2 Milestone Description: The fission TPC experimental campaign is in its final stages of collecting high precision (n,f) cross section data aimed at improving our understanding of the 239 Pu fission process. During FY 2019 235 U(n,f)/ 6 Li(n,t) ratio data collection began at WNR/LANSCE. This data is the first step in demonstrating the efficacy of 6 Li(n,t) as a diagnostic standard for a 239 Pu(n,f) ratio measurement. In FY 2020 and FY2021, the NIFFTE Collaboration will analyze 235 U(n,f)/ 6 Li(n,t) data already collected to establish this technique in preparation for 239 Pu(n,f)/ 6 Li(n,t) ratio data. Additionally, the ability to vapor deposit 239 Pu was developed in 2019, greatly improving target quality. As access to experimental facilities allows, 239 Pu/ 235 U and 239 Pu/ 6 Li data will be collected to provide new inputs for evaluation of the 239 Pu(n,f) cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Evaluating 239 Pu(n,f) cross sections via machine learning using experimental data, covariances, and measurement features

In this paper, the neutron-induced 239 Pu fission cross section, 239 Pu(n,f), is evaluated from 1–20 MeV using experimental data and associated covariances while also considering information on the measurement, termed features here. For instance, methods to determine the background, sample backing material, or impurities in the sample, are explicitly taken into account in the evaluation process. To this end, outliers in the experimental data are identified with a modified version of the Hybrid Robust Support Vector Machine. In a second step, two machine learning methods (logistic regression with elastic net regularization and random forest regression with SHAP feature importance metric) are used to highlight measurement features that are common among many of the outlying data points. Based on this analysis, penalty uncertainties are added to the experimental covariances of outlying data points that have outlier measurement features and are put through the generalized-least-squares evaluation. The resulting evaluated mean values and covariances differ distinctly from those data evaluated without the penalty uncertainties. These results highlight that certain measurement features should be more closely examined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

An uncertainty quantification method relevant to material test reactors

Within material test reactor calculations, energy dependent flux and reaction rate uncertainties are typically not quantified when performing as-run analyses to determine the neutron field experienced by the experiment. When high fidelity Monte-Carlo codes are used in such analyses, straight forward methods to calculate output uncertainties are not available, instead expert opinion is used to postulate computational uncertainties. New methods to propagate uncertainties through these high fidelity simulations are available when sufficient computational power is available. A tool is developed here for sampling any part of an MCNP input from random distributions to determine output uncertainties based on those inputs. Another tool is developed to sample nuclear data cross-section in ACE format using multi-group nuclear data covariances. The Total Monte-Carlo Method and Gesellschaft für Anlagen-und Reaktorsicherheit method (GRS) are implemented and compared to one another as well as MCNP sensitivity and uncertainty calculations. The methods were applied to the Godiva critical sphere k-eigenvalue, the UAM pin-cell benchmark energy dependent flux and reaction rates, and the Advanced Test Reactor energy dependent flux within an experimental location. Furthermore, the two methods agree well, with GRS allowing for an order of magnitude speedup for reaction rate uncertainty calculations and several orders of magnitude for eigenvalue uncertainty calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Demonstration of TOFFEE: A Response Uncertainty Quantification Tool

A key characteristic in neutron transport is nuclear data. Cross-section uncertainty is not used in MCNP6.3 to propagate response uncertainty without external analysis. Here, the TOol For Fast Error Estimation (TOFFEE) is a Python-based code developed to automate the propagation of cross-section uncertainty for MCNP evaluations. TOFFEE implements the sandwich rule to calculate the uncertainty from cross sections with sensitivity coefficients from MCNP6.3 and ENDF/B covariance data. In this paper, TOFFEE has been tested with benchmark experiments, and it has been compared to the uncertainty quantification capabilities of Sampler and TSUNAMI, within SCALE, to verify the application’s capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Application of research reactor environments for validation of the IRDFF-II dosimetry cross section library

Activation data from seven different reactor-based reference neutron fields are examined to provide enhanced validation evidence for the newly released IRDFF-II library. A least-squares based spectrum adjustment methodology is used and rigorous statistical metrics demonstrate the consistency of the set of IRDFF-II dosimetry cross sections. The use of these reactor-based neutron fields provides validation evidence for nine more reactions than have been addressed in the 252 Cf(sf) and 235 U(th) benchmark validation testing. The use of covers to shift their energy response increases the power of the response validation but makes it challenging to properly capture response correlations.

Griffin, Patrick↗
DOE OSTI2023

Bayesian inference of in-medium baryon-baryon scattering cross sections from HADES proton flow data

Within a Bayesian statistical framework using a Gaussian Process emulator for an isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model simulator of heavy-ion reactions at intermediate energies, we infer from the HADES proton flow data the posterior probability distribution functions of in-medium baryon-baryon scattering cross section modification factor X with respect to free-space and the corresponding incompressibility K of nuclear matter as well as their correlation function. In conclusion, the mean value of X is found to be $X$ = $1.32_ {+0.28} ^ {-0.40} $ at 68% confidence level assuming the nuclear incompressibility K will not exceed 400 MeV, providing circumstantial evidence for enhanced baryon-braryon scattering cross sections in hot and dense nuclear matter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Integrating ORNL’s HPC and Neutron Facilities with a Performance-Portable CPU/GPU Ecosystem

We explore the development of a performance-portable CPU/GPU ecosystem to integrate two of the US Department of Energy’s (DOE’s) largest scientific instruments, the Oak Ridge Leadership Computing facility and the Spallation Neutron Source (SNS), both of which are housed at Oak Ridge National Laboratory. We select a relevant data reduction workflow use-case to obtain the differential scattering cross-section from data collected by SNS’s CORELLI and TOPAZ instruments. We compare the current CPU-only production implementation using the Garnet Python multiprocess package based on the Mantid C++ framework against our proposed CPU/GPU implementation that uses the LLVM-based, just-in-time Julia scientific language and the JACC.jl performance-portable package. Two proxy apps were developed: (i) an app for extracting relevant Mantid kernels (MDNorm) in C++ and (ii) the Julia MiniVATES.jl miniapp. We present performance results for NVIDIA A100 and AMD MI100 GPUs and AMD EPYC 7513 and 7662 CPUs. The results provide insights for future generations of data reduction software that can embrace performance portability for an integrated research infrastructure across DOE’s experimental and computational facilities.

Hahn, Steven↗
DOE OSTI2023

A Study of the Covariance Data in ENDF/B VIII.0 for Low Z Isotopes

Thirty group covariance data have been produced from ENDF/B VIII.0 MF 33 for H1, H2, He4, Li6, Li7, Be9, B10, B11, C12, C13, N15, O16, the JENDL O16 and F19. Multi-group cross section covariance data was produced by NJOY routine ERRORR. Negative eigenvalues were found only for F19, but the covariance constraints required for the condition of the sum of partial cross sections being equal to the resultant total cross section were found to be incorrect for H2, Li6, B10, C12, C13, and O16. An easy correction is suggested for Li6 and C13. In closing, an expansion of the ENDF-6 formats manual is suggested for the MF 33 chapter and a new proposed covariance normalization scheme is proposed.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Modernization efforts for the R -Matrix code SAMMY [Abstract]

The R-Matrix code SAMMY is a widely used nuclear data evaluation code focused on the resolved range, which includes corrections for experimental effects. The code is still mostly written in Fortran 77, and uses a memory management system suitable for the time of its initial writing (1984). A modernization effort is under way to bring the code in-line with modern software development practices. A continuous-integration testing framework was added, automating the large existing set of test cases. It is run on every commit. The memory management was updated to current standard practices suitable for modern software analysis tools. The code can be obtained from https://code.ornl.gov/RNSD/SAMMY. The resonance parameters and covariance information are now stored in C++ objects shared by SAMMY and AMPX, the processing code that generates nuclear data libraries for SCALE. This allows for easier maintenance and access to the resonance parameters inside and outside of SAMMY. This feature is already used by accessing and changing parameters in memory in the Bayesian Monte Carlo Evaluation Framework for Cross Sections Nuclear Data and Integral Benchmark Experiments project, Further plans include the switch to the ENDF reading and writing routines in AMPX, as these routines are more robust, easier to maintain, and support more features. Of note here is support for the new GNDS format. Previously it wasn’t easy to share the full covariance matrix for evaluations containing more than one isotope due to limitations on the ENDF format; this is now supported in GNDS. The data are currently available in a binary SAMMY format and can be exported to GNDS to make them more widely available and sharable. The next step will be to use the same resonance processing code at 0K in AMPX and SAMMY as one of the available Reich-Moore R-Matrix formalism. The first step toward this goal is to isolate the reconstruction into a module that takes resonance parameters as its input and does not depend on SAMMY global parameters. This goal has been achieved and it should now be possible to more easily change the resonance formalism and add enhancements as the Phenomenological R-Matrix parameterization of direct, doorway, and compound nuclear reactions discussed elsewhere on this conference. This concerted modernization and enhancement effort provides multiple advantages to the nuclear data community. It will allow parameter optimization using enhanced formalisms, including experimental effects, that better match complex experimental data. Then those evaluated parameters can immediately be passed off to AMPX to be reconstructed with the exact same cross section model and be put into a data library for subsequent testing using SCALE and the Valid Benchmark suite or other suitable benchmark suites.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Study of a Proposed fissionTPC Measurement of 233 U(n,f)/ 235 U(n,f) Cross Section Ratio

A review of the available 233 U( n, f )/ 235 U( n, f ) cross section ratio data compared to the ENDF evaluation in the fast neutron energy range, 0.1–20 MeV, shows that discrepancies exist between some of the various measurements and the evaluation. The discrepancies vary and a function of incident neutron energy and range between 1–5%. In this document we review two potential options for performing new measurements of the cross section ratio to potentially resolve these discrepancies. The two options are compared and contrasted in terms of measurement accuracy and cost. The first option would utilize the fissionTPC, which was designed specifically to achieve measurement uncertainties of better than 1% to resolve a similar data–evaluation discrepancy in the 239 Pu( n, f ) cross section. While this would seem to be an ideal option in this case also, there are challenges. The fissionTPC is a complex instrument and the cost of maintenance and operations are significant. Furthermore, some of the fissionTPC equipment is nearing the end of its useful life which presents a risk to completion of a measurement campaign. The second option is to use a dual-fission chamber, which is the more traditional approach to these types of measurements. The cost is estimated to be about half that of a fissionTPC measurement, while the much simpler design of the detector reduces overall risk. The trade-off is the measurement uncertainty, which would be on order of 1–3% with a careful measurement and analysis. This uncertainty however may not be good enough to fully resolve the discrepancies. The objective of a new measurement would be the improvement in the ENDF evaluation with the end goal of improving the accuracy of models and simulations at the end of the nuclear data pipeline. An understanding of the sensitivity of these models to the data uncertainties would help guide the choice of measurement techniques.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Machine learning neutrino-nucleus cross sections

Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries—can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Machine Learning Neutrino-Nucleus Cross Sections

Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries— can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.

Tame-Narvaez, Karla [Fermilab] (ORCID:000000022249↗