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Results for “Nuclear data uncertainties”

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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Differential analysis of incompressibility in neutron-rich nuclei

Both the incompressibility K A of a finite nucleus of mass A and that (K ∞ ) of infinite nuclear matter are fundamentally important for many critical issues in nuclear physics and astrophysics. While some consensus has been reached about K ∞ , accurate theoretical predictions and experimental extractions of K τ characterizing the isospin dependence of K A have been very difficult. We propose a differential approach to extract K τ and K ∞ independently from the K A data of any two nuclei in a given isotope chain. Applying this method to the K A data from isoscalar giant monopole resonances (ISGMR) in even-even Pb, Sn, Cd, and Ca isotopes taken by Garg et al. at the Research Center for Nuclear Physics (RCNP), Osaka University, Japan, we find that the 106 Cd– 116 Cd and 112 Sn– 124 Sn pairs having the largest differences in isospin asymmetries in their respective isotope chains measured so far provide consistently the most accurate up-to-date K τ value of K τ = –616 ± 59 MeV and K τ =–623 ± 86 MeV, respectively, largely independent of the remaining uncertainties of the surface and Coulomb terms in expanding K A , while the K ∞ values extracted from different isotopes chains are all well within the current uncertainty range of the community consensus for K ∞ . Moreover, the size and origin of the “soft Sn puzzle” is studied with respect to the “stiff Pb phenomenon.” Furthermore, it is found that the latter is favored due to a much larger (by ≈ 380 MeV) K τ for Pb isotopes than for Sn isotopes, while K ∞ from analyzing the K A data of Sn isotopes is only about 5 MeV less than that from analyzing the Pb data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Nuclear masses learned from a probabilistic neural network

Machine learning methods and uncertainty quantification have been gaining interest throughout the last several years in low-energy nuclear physics. In particular, Gaussian processes and Bayesian neural networks have increasingly been applied to improve mass model predictions while providing well-quantified uncertainties. In this work, we use the probabilistic Mixture Density Network (MDN) to directly predict the mass excess of the 2016 Atomic Mass Evaluation within the range of measured data, and we extrapolate the inferred models beyond available experimental data. The MDN provides not only mean values but also full posterior distributions both within the training set and extrapolated testing set. We show that the addition of physical information to the feature space increases the accuracy of the match to the training data as well as provides for more physically meaningful extrapolations beyond the the limits of experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Flow boiling transient critical heat flux tests with stainless steel and FeCrAl: Transient correlation implementation, model calibration, and sensitivity analysis

In this study, steady-state and transient internal-flow critical heat flux (CHF) experiments were carried out under two flow conditions, at atmospheric pressure, on 316 stainless steel (316-SS) and iron-chromium-aluminum (FeCrAl) tubes. Slow power transients at a low mass flow (300 kg/m 2 - s) with very low subcooling (X e =-0.0054) generated premature CHFs, which were prevented by faster power transients and high mass flow (1000 kg/m 2 - s). The measured transient CHFs increased linearly with increasing power transients, compared with the steady-state CHF. Yet, the wall superheat at the CHFs decreased with faster power transients. Transient CHF correlations highlighting heterogeneous spontaneous nucleation were calibrated to the measured CHFs and compared with other existing correlations. Transient CHF multipliers were acquired from pool and flow boiling empirical CHF correlations that were generated. The multipliers were applied to the RELAP5-3D nuclear system code to analyze the discrepancies between the measured data and the predicted CHF and post-CHF behavior, which improved peak cladding temperature predictions by 24.6%. A variance-based global sensitivity study perturbing the experimental uncertainties and cladding material thermal properties showed the diminishing influence of flow boiling heat transfer with increasing power transients, highlighting the significance of the volumetric heat capacity for the cladding integrity during transients. Transient CHF correlations were applied to the most limiting design basis accident: a hot-zero-power reactivity-initiated accident on a generic pressurized water reactor RELAP5-3D model.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mobility assessment of the BCC and carbide phases in the C-Nb, C-U and Nb-U systems

Uranium carbides with refractory metal additions are considered for Gen IV nuclear reactors and nuclear thermal propulsion as fuels for their high-temperature and corrosion resistant properties. Understanding kinetic effects that dictate microstructural evolution during fabrication and operating conditions is essential to advance technological development of these fuels. This work presents the development of an atomic mobility database for C-Nb-U systems based off available experimental data supported with ab-initio methods. The mobility assessments and uncertainty quantification (using Markov chain Monte Carlo) were conducted in the Kawin software. Carbon diffusion is considered dominant, as metal diffusion is much slower, with niobium diffusion being even slower and rate limiting than uranium metal. We provide a comprehensive and self-consistent thermo-kinetic database that is validated by diffusion couple simulations through Kawin. In conclusion, this enables prediction of microstructural and phase evolution critical for the development and lifetime assessment of next generation nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Industry Requirements for Geomagnetic Disturbance Models

This research project will address the most pressing uncertainties in modeling and measuring the electric power grid effects of geomagnetic disturbances (GMDs) and the E3 portion of nuclear electromagnetic pulse (EMP). The primary goal is to help decision-makers in the electric power sector have the knowledge and tools they need to most effectively mitigate GMD effects on our nation’s electric grid, with a secondary focus on EMP. Comprehensive modeling, model assessment through sensitivity analysis, and validation with field measurement data will be the primary tasks undertaken. The goal will be a more widespread adoption of these modeling approaches, namely characterizing the uncertainty associated with these models and how that uncertainty will affect decision-making by industry. This document summarizes industry requirements for better decision-making tools, informed by feedback from an industry advisory board. These requirements help guide planning and execution of the project's remaining tasks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Benchmark Evaluation of one Dimensional Array of HEU Moderated and Reflected by Lucite [Poster]

Two critical experiments with HEU-Lucite were performed using the Planet Universal Critical Assembly Machine at Los Alamos National Laboratory in 2019. HEU foils were interleaved with Lucite in a column stack for moderation and reflection from the square Lucite plates. The evaluation of the experiments is presented. A Monte-Carlo (MCNP6) calculation model was developed for the determination of uncertainties and their effect on the multiplication factor. Experimental uncertainties were found to be low with the overall uncertainty in k eff approximately 240 pcm. The comparison of calculations with experimental data is presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

SAS4A/SASSYS-1 Validation with EBR-II Tests Performed During the SHRT Testing Program (Rev. 2)

The EBR-II sodium-cooled fast reactor supported a wide range of fast reactor research activities. The final fifteen years of operations at EBR-II were used for experiments and tests to demonstrate the importance of passive safety in liquid metal reactors and the capability of such systems to provide strong passive responses during off-normal conditions. The Shutdown Heat Removal Test program at EBR-II provided test data supporting the validation of computer codes for design, licensing, and operation of LMRs, among other objectives. The program included nearly sixty tests, most of which were protected and unprotected loss of flow and loss of heat sink tests run at various initial powers and flow rates. This report documents the results of modeling and simulation of tests from the Shutdown Heat Removal Test program to support validation of Argonne’s SAS4A/SASSYS-1 fast reactor safety analysis code. SHRT-17 and SHRT-6 were protected loss of flow tests where a loss of electrical power to all sodium coolant pumps was simulated to demonstrate the effectiveness of natural circulation cooling characteristics. SHRT-45R, SHRT-39, and SHRT-43R were unprotected loss of flow tests where the control rod scram function of the plant protection system was disabled to demonstrate the effectiveness of EBR-II’s passive reactivity feedbacks. BOP-301 and BOP-302R were unprotected loss of heat sink tests that demonstrated how reactivity feedback effects driven by changes to the core inlet temperature can shut down the fission process. PICT-5/6 demonstrated how core power could be increased and decreased via changes in the intermediate sodium and feedwater flow rates. This validation activity leverages modeling and simulation efforts that originated under an International Atomic Energy Agency Coordinated Research Project for benchmark analysis of the EBR-II Shutdown Heat Removal Tests. The SAS4A/SASSYS-1 models originally developed for the CRP have been modernized to utilize new code features and modeling practices. Differences between the predicted and measured test data were explored and the causes of these differences were identified as being due to modeling approximations, uncertainty in transient component behavior, and instrumentation uncertainties. Overall, it was concluded that for all tests simulated there was good agreement between the flow, power, and temperature predictions and the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

The muon g-2 experiment at Fermilab

The E989 collaboration has recently published the most precise measurement of the muon anomalous magnetic moment $a_\mu$ with an uncertainty of $0.46\,\mathrm{ppm}$. The new experimental world average of $a_\mu$ deviates by 4.2 standard deviations from the Standard Model prediction provided by the Muon g-2 Theory Initiative. Emerging results from ab-initio lattice QCD calculations for hadron-physics contributions allow to scrutinize this tantalizing hint for physics beyond the Standard Model for the first time in a three way comparison. To extract the value of $a_\mu$ a frequency comparison experiment is performed with spin-polarized muons confined in a superbly controlled electric and magnetic field environment. A measurement of the difference between the Larmor and the cyclotron frequency, the so-called anomalous spin precession frequency, is combined with a high-precision measurement of the magnetic field environment which is performed using nuclear magnetic resonance techniques. I discussed the most recent result of the Fermilab Muon g-2 experiment's first physics data run performed in 2018. I reported on the experimental improvements implemented for the subsequent science runs that will allow the collaboration to achieve the ultimate goal of $0.14\,\mathrm{ppm}$ uncertainty on $a_\mu$.

Fertl, Martin↗
DOE OSTI2023

First Direct Measurement Constraining the Ar 34 ( α , p ) K 37 Reaction Cross Section for Mixed Hydrogen and Helium Burning in Accreting Neutron Stars

The rate of the final step in the astrophysical αp process, the 34 Ar(α,p) 37 K reaction, suffers from large uncertainties due to a lack of experimental data, despite having a considerable impact on the observable light curves of x-ray bursts and the composition of the ashes of hydrogen and helium burning on accreting neutron stars. Here, we present the first direct measurement constraining the 34Ar(α,p)37K reaction cross section, using the Jet Experiments in Nuclear Structure and Astrophysics gas jet target. The combined cross section for the 34 Ar,Cl(α,p) 37 K,Ar reaction is found to agree well with Hauser-Feshbach predictions. The 34 Ar(α,2p) 36 Ar cross section, which can be exclusively attributed to the 34 Ar beam component, also agrees to within the typical uncertainties quoted for statistical models. This indicates the applicability of the statistical model for predicting astrophysical (α,p) reaction rates in this part of the αp process, in contrast to earlier findings from indirect reaction studies indicating orders-of-magnitude discrepancies. This removes a significant uncertainty in models of hydrogen and helium burning on accreting neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Hierarchical Bayesian Thermonuclear Rate for the 7 Be(n,p) 7 Li Big Bang Nucleosynthesis Reaction

Big Bang nucleosynthesis provides the earliest probe of standard model physics, at a time when the universe was less than 1000 seconds old. It determines the abundances of the lightest nuclides, which give rise to the subsequent history of the visible matter in the universe. This work derives new 7 Be(n,p) 7 Li thermonuclear reaction rates based on all available experimental information. This reaction sensitively impacts the primordial abundances of 7 Be and 7 Li during big bang nucleosynthesis. We critically evaluate all available data and disregard experimental results that are questionable. For the nuclear model, we adopt an incoherent sum of single-level, two-channel, R -matrix approximation expressions, which are implemented into a hierarchical Bayesian model, to analyze the remaining six data sets we deem most reliable. In the fitting of the data, we consistently model all known sources of uncertainty, including discrepant absolute normalizations of different data sets, and also take the variation of the neutron and proton channel radii into account, hence providing less biased estimates of the 7 Be(n,p) 7 Li thermonuclear rates. From the resulting posteriors, we extract R -matrix parameters ($E_r, γ^2_n, γ^2_p$) and derive excitation energies and partial and total widths. Our fit is sensitive to the contributions of the first three levels above the neutron threshold. Reaction rates were computed by integrating 10,000 samples of the reduced cross section. Our 7 Be(n,p) 7 Li thermonuclear rates have uncertainties between 1.5% and 2.0% at temperatures of ≤1 GK. Finally, we compare our rates to previous results and find that the 7 Be(n,p) 7 Li rates most commonly used in big bang simulations have uncertainties that are too optimistic.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Measurement uncertainty of rossi-alpha neutron experiments

Rossi-alpha neutron experiments are used to estimate the prompt neutron decay constant of a fissile assembly, a quantity of widespread interest in applications including in nuclear nonproliferation and criticality safety. This work develops a mathematical model to efficiently estimate measurement uncertainty of Rossi-alpha neutron experiments inferred from a two-exponential fit model with histogram binning. The derived uncertainty estimates were validated using repeated Rossi-alpha measurements of a subcritical, 4.5-kg sphere of weapons-grade, alpha-phase plutonium with nickel, copper, tungsten, and polyethylene reflectors. The estimates of uncertainty for the histogram data produced by the model were conservative and agree with the reference uncertainties within noise. The estimates of the prompt neutron decay constant uncertainty agreed with the reference uncertainties within one standard deviation. In conclusion, the proposed model will reduce total measurement times, ultimately reducing operational and procedural costs in application.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Quantifying uncertainty in physics-based predictions of rare-isotope production cross sections via Bayesian-inspired model averaging across nuclear mass tables

Accurate prediction of fragmentation cross sections is essential for rare-isotope beam production, planning new-isotope searches, and designing experiments to study the most exotic regions of the nuclear chart. However, existing reaction models and phenomenological cross-section parametrizations often exhibit significant deviations over broad regions of mass and charge. In this work, a Bayesian-inspired model-averaging framework is developed to combine abrasion-ablation (AA) calculations based on multiple nuclear mass tables into a single statistically weighted estimate. For the calibrated systems, the model weights are assigned empirically according to the relative quality of fit to measured cross sections, thereby reducing systematic model bias while preserving the underlying physics content of the AA description. The weights are constrained using proton-rich fragmentation data for the 78 Kr and 124 Xe projectiles. The resulting parameter trends are then propagated to the 92 Mo and 144 Sm systems through a controlled scaling procedure. In the present implementation, the excitation-energy prescription is fixed, while the averaging is performed across nuclear-mass inputs; the framework provides both weighted cross sections and associated uncertainty estimates. Applied to proton-rich fragmentation, the present approach provides a practical basis for interpolation and limited extrapolation in regions relevant to rare-isotope production. The resulting predictions are used to assess the production of very proton-rich nuclei, and candidate new isotopes are discussed.

Bayesian methods↗
DOE OSTI2022

Quality Ranking System for Molten Salt Thermal Property Data

A simple ranking system for use with data and property values compiled in the Molten Salt Thermal Database-Thermophysical Properties (MSTDB-TP) is presented. The approach includes assessments of five features of data collection: the method used to measure the property value, calibration of devices used to make the measurements, the quantified uncertainty of the results, control of the environmental conditions, and determination of the salt composition. The verifiability of how the property value was determined is also assessed based on information provided or cited within the data set. The quality of each facet is ranked as High, Moderate, or Incomplete based on objective metrics. The overall quality of the dataset is ranked based on rankings of the five data features and the reported property value, with rankings of A and B indicating the data and property value are deemed suitable for quantitative use and U indicating uncertainties that restrict the recommended use to qualitative purposes. The system is suitable for assessing data already in the MSTDB-TP and screening new entries.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Progress in Constraining Nuclear Symmetry Energy Using Neutron Star Observables Since GW170817

The density dependence of nuclear symmetry energy is among the most uncertain parts of the Equation of State (EOS) of dense neutron-rich nuclear matter. It is currently poorly known especially at suprasaturation densities partially because of our poor knowledge about isovector nuclear interactions at short distances. Because of its broad impacts on many interesting issues, pinning down the density dependence of nuclear symmetry energy has been a longstanding and shared goal of both astrophysics and nuclear physics. New observational data of neutron stars including their masses, radii, and tidal deformations since GW170817 have helped improve our knowledge about nuclear symmetry energy, especially at high densities. Based on various model analyses of these new data by many people in the nuclear astrophysics community, while our brief review might be incomplete and biased unintentionally, we learned in particular the following: (1) The slope parameter L of nuclear symmetry energy at saturation density ρ0 of nuclear matter from 24 new analyses of neutron star observables was about L≈57.7±19 MeV at a 68% confidence level, consistent with its fiducial value from surveys of over 50 earlier analyses of both terrestrial and astrophysical data within error bars. (2) The curvature Ksym of nuclear symmetry energy at ρ0 from 16 new analyses of neutron star observables was about Ksym≈−107±88 MeV at a 68% confidence level, in very good agreement with the systematics of earlier analyses. (3) The magnitude of nuclear symmetry energy at 2ρ0, i.e., Esym(2ρ0)≈51±13 MeV at a 68% confidence level, was extracted from nine new analyses of neutron star observables, consistent with the results from earlier analyses of heavy-ion reactions and the latest predictions of the state-of-the-art nuclear many-body theories. (4) While the available data from canonical neutron stars did not provide tight constraints on nuclear symmetry energy at densities above about 2ρ0, the lower radius boundary R2.01=12.2 km from NICER’s very recent observation of PSR J0740+6620 of mass 2.08±0.07M⊙ and radius R=12.2–16.3 km at a 68% confidence level set a tight lower limit for nuclear symmetry energy at densities above 2ρ0. (5) Bayesian inferences of nuclear symmetry energy using models encapsulating a first-order hadron–quark phase transition from observables of canonical neutron stars indicated that the phase transition shifted appreciably both L and Ksym to higher values, but with larger uncertainties compared to analyses assuming no such phase transition. (6) The high-density behavior of nuclear symmetry energy significantly affected the minimum frequency necessary to rotationally support GW190814’s secondary component of mass (2.50–2.67) M⊙ as the fastest and most massive pulsar discovered so far. Overall, thanks to the hard work of many people in the astrophysics and nuclear physics community, new data of neutron star observations since the discovery of GW170817 have significantly enriched our knowledge about the symmetry energy of dense neutron-rich nuclear matter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Contextually aware roadside radiation measurement testbed

Here we demonstrate a contextually aware multimodal roadside radiation measurement detection testbed for traffic monitoring applications in nuclear nonproliferation. Many variables in traffic such as vehicle or cargo size, mass, speed, shape, and distance of closest approach can have significant impacts on the radiation measured from a vehicle-transported radiation source. These factors can lead to uncertainties in the analysis of the radiation source, especially for lower-strength radiation sources of interest. Our testbed, known as the Multimodal Measurement System (MMS) uses non-radiation sensors including magnetometers, geophones, radiofrequency receivers, cameras, and LiDAR to extract contextual information about vehicles passing by the system. These contextual data can then be fused with data from radiation measurements to increase the system’s sensitivity and accuracy in nuclear threat detection applications. This work describes the instrumentation of the MMS and its data acquisition pipeline. Furthermore, we describe the pre-analysis performed on the raw multimodal data streams for data fusion, and the high-level machine learning analyses for detection and characterization. The variety of sensors within the MMS provides a valuable testbed that can be used to identify the combinations of contextual sensors that provide the greatest improvements to radiation source detection and characterization within the restrictions for various proliferation detection applications. The MMS is also modular so that additional combinations of sensors can be explored in the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Coupling RELAP5-3D to BISON

This report details two approaches for coupling the BISON nuclear fuel performance code with RELAP5-3D. Both approaches are shown to work well. The first is a Python-based approach, and the second combines the two applications into one executable with data passed in memory from one library to the other. This second coupling approach forms the basis for analysis of complex loss of coolant scenarios and enables future calculations of modeling uncertainties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Bayesian averaging for ground state masses of atomic nuclei in a Machine Learning approach

We present global predictions of the ground state mass of atomic nuclei based on a novel Machine Learning algorithm. We combine precision nuclear experimental measurements together with theoretical predictions of unmeasured nuclei. This hybrid data set is used to train a probabilistic neural network. In addition to training on this data, a physics-based loss function is employed to help refine the solutions. The resultant Bayesian averaged predictions have excellent performance compared to the testing set and come with well-quantified uncertainties which are critical for contemporary scientific applications. We assess extrapolations of the model’s predictions and estimate the growth of uncertainties in the region far from measurements.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Validation of Recent Changes in Actinide Evaluations U-235, U-233, Pu-239 [Slides]

This presentation discusses U-235 updates, including fluctuations in the fission cross section in the URR range that were refined to represent measured data following the Paradela et al. evaluation. There were small changes to the low-energy resonances to improve the fit to measured capture data from RPI (capture reduced by 5% from 0.06-7.8 eV, by 7.7% from 7.8-11 eV) and there was a very small change to the thermal nu-bar within uncertainties. Discrete level data are stored in MF=6 (format requirement, no impact on calculations) and issues leading to negative eigenvalues in cross-covariances in the RR have been sorted out. In conclusion, many improvements were made to evaluated nuclear data of actinides in the resonance region and above, such as minor changes to U-235 including assessment of changes that depend on the finalization of the O-16 evaluation. U-233 improvements show significant progress in performance and some further improvement might be needed at intermediate energies. Pu-239 ORNL/IAEA evaluation is promising; however, more work is needed.

07 ISOTOPE AND RADIATION SOURCES↗