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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Design and performance of an in-vacuum, magnetic field mapping system for the Muon g-2 experiment

The E989 Muon g-2 experiment at Fermilab aims to measure the anomalous magnetic moment, a$_\mu$, of the muon with a precision of 140 parts-per-billion. This requires a precise measurement of both the anomalous spin precession frequency, $\omega_a$, and the average magnetic field in terms of the equivalent, free proton Larmor frequency, $\omega_p$. The measurement of $\omega_p$ with a total systematic uncertainty of 70 parts-per-billion involves a combination of various NMR probes. There are 378 probes in fixed locations constantly monitoring field drifts. A water-based probe provides the calibration in terms of $\omega_p$. A crucial element for the multi-step measurement of $\omega_p$ is the regular mapping of the magnetic field over the muon storage region. The former E821 experiment at Brookhaven employed an in-vacuum field mapping system equipped with 17 NMR probes, which was developed by the University of Heidelberg. We have refurbished and upgraded this system with new probes and electronics. The upgrades include a new communication scheme incorporating time-division multiplexing to separate the important NMR reference clock from the data communication. The addition digitization of the NMR signals replaced the hardware-implemented zero-crossing counting of the E821 system. The digitized signals offer new capabilities in the NMR frequency analysis and its related systematic uncertainties. While the mechanical systems that move the field mapper around the ring have been mostly refurbished, the motion control system was completely replaced with a custom-built electronics centered around a commercial Galil motion controller. Both the field mapping NMR system and its motion control were successfully commissioned at Fermilab and have been in reliable operation during the first data taking periods. This article provides details of the upgrades of the field mapper and its performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Fuel Fabrication Specification Impact Analysis for NBSR LEU Conversion

As part of a national initiative to enhance nuclear security and reduce proliferation risks, significant efforts have been undertaken by the National Nuclear Security Administration Material Management and Minimization Office of Reactor Conversion Program to convert U.S. high performance research reactors (USHPRRs) from the use of highly enriched uranium (HEU) to low-enriched uranium (LEU), including the National Bureau of Standards Reactor (NBSR). The current plan is to procure LEU fuel assemblies from commercial fabricators according to fuel specifications tailored for each USHPRR. The analysis conducted at Brookhaven National Laboratory was part of an effort to identify the sources of uncertainty in the fuel specifications that may impact the performance of the NBSR core after its conversion and, in particular, to assess the range of acceptable tolerance limits from the perspective of core safety and reactor performance. Using the stochastic neutronics code MCNP 6.2, the variations in important NBSR neutronics characteristics were analyzed as a function of the specification parameters independently and in combination. The important NBSR specification parameters analyzed were the fuel isotopic composition, the amount of impurity content in cladding, the fuel plate thickness, and the fuel element 235U mass loading. The range of variation of each specification parameter was based on the technical specification limit or available as-fabricated assay data and uncertainties. The NBSR neutronics characteristics selected for analysis were the reactor reactivity characteristics at equilibrium and the equilibrium fuel cycle length. Results show that with variations in the fabrication parameters of the as-fabricated U-10Mo fuel within the specification limitations, the excess reactivity of the NBSR LEU core remains well below the 15% Δk/k technical specification limit, and the shutdown margin is always significantly greater than the required 0.68% Δk/k. This ensures that the NBSR can be operated safely and reliably shut down for all analyzed cases within the specified fabrication limits after the LEU conversion. In the prototypic case, the fuel cycle length was 1.5 days longer than the targeted 38.5 days. In a credible worst-case scenario, where all low-reactivity parameters were combined, the fuel cycle length was reduced to 35.5 days, which is still considered manageable for reactor operations. Variations in cycle length are primarily driven by changes in 235U loading, with other parameters having secondary effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Direct sensitivity analysis on the parameterization of crystal plasticity models

Various methods for calibrating crystal plasticity finite element (CPFE) models lead to non-unique input parameter values, which subsequently introduce uncertainty in the predicted mechanical response. Sensitivity analysis (SA) conducted on crystal plasticity models is used to identify how variability in these parameters contribute to output uncertainty. Traditional SA on CPFE parameters uses simplified surrogate models to save computational time. However, the accuracy of the surrogate models depends on the quantity of training data used, and any modeling error can propagate into the SA results, potentially affecting their reliability. In this work, the elementary effects test (EET) method, a global SA technique using direct CPFE simulations was employed, and the results obtained were compared with the First Order Second Moment (FOSM) method. ExaConstit, an open-source GPU-enabled CPFE code, was used to perform the simulations and direct SA. The EET method was accurately able to capture the non-linear effects of all the input parameters on the output and is a valuable approach for reliably attributing parameter sensitivities in CPFE models. Based on the results, efficient strategies to perform future parameter calibration and SA are discussed. Additionally, the SA trends observed in different single crystal orientations closely mirrored the activity of the slip systems.

Elementary Effects Test↗
DOE OSTI2023

Measurement of Rayleigh Scattering in Liquid Argon at Vacuum Ultraviolet Wavelengths

Liquid argon based experiments are limited in scintillation light analysis capabilities due to inconsistent measured values of fundamental constants essential for reconstructing scintillation events. This experiment measures the Rayleigh scattering length of vacuum ultraviolet light propagating in liquid argon to support liquid argon experiments by expanding the scope of scintillation signal analysis. Preliminary results are presented for the Rayleigh scattering length in arange of vacuum ultraviolet wavelengths, including the liquid argon scintillation peak wavelength. Currently, further data collection and analysis is required to reduce measurement uncertainty as well as quantify and correct for other effects such as the photon detector temperature dependence. Results will contribute to the development of new photon detector system analysis methods for liquid argon experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Validation of SAS4A/SASSYS-1 for predicting steady-state single-phase natural circulation

The validation of system analysis codes for nuclear reactor systems is required for the development and application of these computational tools. Designed as a comprehensive system analysis code for advanced nuclear reactors, SAS4A/SASSYS-1 requires validation of its physics model for capturing single-phase natural circulation behavior. To support the validation of SAS4A/SASSYS-1, high-precision experiments are performed capturing steady-state single-phase natural circulation on a scaled facility with comprehensive instrumentation. In this work, dedicated tests are performed quantifying the critical modeling parameters, and a single-phase natural circulation benchmark dataset is obtained with well-documented uncertainty and comprehensive facility description. The validation is then performed against the dataset examining the capability of SAS4A/SASSYS-1 in simulating steady-state single-phase natural circulation. The experimental facility is modeled in the candidate code. Solution verification is performed using Richardson-extrapolation-based estimators which quantify and restrict numerical errors from discretization. Input uncertainty provided by the benchmark dataset is forward propagated through the candidate code, quantifying the output uncertainty in a Monte Carlo approach. The composition of the output uncertainty is also quantified through a variance-based sensitivity analysis. With the uncertainty quantified for each individual condition, a detailed comparison between the simulation results and experimental data is performed covering the whole dataset. The results show consistent agreement for all primary parameters. The current validation activity provides a valuable benchmark dataset for the validation of system analysis codes in capturing single-phase natural circulation and demonstrates satisfactory prediction capability of SAS4A/SASSYS1 for steady-state single-phase natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Uncertainty quantification for inverse problems with application to ptychographic reconstruction

Inverse problems in imaging are commonly solved by optimization or learned surrogates that return a single reconstruction, while uncertainty information is often unavailable. In many experimental settings, however, uncertainty is required to assess reliability, guide downstream analysis, and prioritize additional measurements. In this note, we present a compact uncertainty-quantification framework based on local objective curvature, and then specialize it to ptychographic reconstruction. We further show how repeated reconstructions can be aggregated in a statistically principled way, including a practical implementation path for PtychoNN.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Probabilistic modeling and prediction of out-of-plane unidirectional composite lamina properties

Computational simulation provides an efficient means to predict the behavior of customized hybrid material configurations using validated, physics-based models. One limitation to this approach is the quality and quantity of available data to characterize the many constituent input properties. Therefore, a systematic approach to identify the most influential parameters on the hybrid behavior and quantify the corresponding uncertainty in predictive capabilities is required. Here, an approach using Bayesian multimodel inference and imprecise global sensitivity analysis is presented to investigate the effects of sparse constituent data on the prediction of composite material properties. The methodology allows the identification, using quantified uncertainties, of the most influential constituent material parameters for specified homogenized properties. This sensitivity analysis further enables a dimension reduction when assessing the influence of uncertainties on material properties and can be used to inform testing programs of the constituent properties that require additional testing/data collection in order to minimize uncertainty in macro-scale composite properties. The methodology is specifically demonstrated on the prediction and sensitivity analysis of out-of-plane mechanical properties of a unidirectional lamina.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unbalanced Nested Random Effects Estimation of Variance Components

To investigate the contributing factors of variance in the measurement of an iodine 127 (127I) sample, we implement a nested random effects analysis of variance (ANOVA). Historically, the reported uncertainty on a measurement of 127I has been obtained by methods of forward uncertainty propagation because there is typically only one replicate of a given sample for which to estimate the uncertainty. When samples are processed there are several types of quality control (QC) standards analyzed along-side the unknown samples with two to five replicates for each. Assuming the variance observed in these replicate QC standards is representative of that of the unknown samples, we use these data in a nested random effects ANOVA to estimate the total uncertainty of a measurement. We demonstrate this approach with two sets of measurements from Idaho National Laboratory and compare the results with the forward uncertainty propagation approach. Variance component estimates for the coarsest level of the nesting structure were most imprecise because replicates were most limited at these levels. We find that the results largely agree between forward propagation and ANOVA, and the greatest contributors of variance are due to instrument variation and chemical processing, with human processing being among the smallest contributors. This analysis provides reassurance that the reported uncertainties using forward propagation are reasonable and the process is well controlled. We propose a future designed experiment to increase replicates at the coarsest level of the hierarchy to improve estimates of these variance components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Inadequacy of current approaches for characterizing membrane transport properties at high salinities

Cost optimal design of osmotic membrane processes requires an accurate estimate of membrane transport parameters across their full operational range. However, standard approaches for estimating these parameters rely on empirical methods, the accuracy of which remains unquantified as a function of temperature, salinity, and measurement error. Herein, we present a systematic accuracy analysis of previously developed methods for estimation of membrane transport properties in reverse osmosis, high-pressure reverse osmosis, forward osmosis, pressure retarded reverse osmosis, and osmotically assisted reverse osmosis. We use a Monte Carlo approach to sample the full range of feasible membrane water permeabilities, salt permeabilities, structural parameters, and operating conditions for these processes. These material and process parameters are then incorporated into a physical transport model for each process. Our analysis shows that the statistical uncertainty of current empirical methods for estimating membrane parameters increases by 5 times from low-salinity to high-salinity conditions. Here, the result of this work demonstrates that empirical methods are inadequate for precisely estimating membrane transport properties at high salinity and highlight a critical need for the development of statistically validated higher accuracy methods.

42 ENGINEERING↗
DOE OSTI2020

Quantifying heavy quark transport coefficients with an improved transport model

We report that the heavy-flavor transport coefficients contain important information on the strong interaction at finite temperatures. The extraction of these numbers from experimental data requires dynamical modeling of heavy-flavor transport that is coupled to realistic medium evolution. Furthermore, meaningful extractions necessitate both a faithful implementation of the physical inputs to be tested and the quantification of model uncertainty. For these purposes, we have developed a partonic transport model LIDO. It has an improved treatment of in-medium parton bremsstrahlung, which has been calibrated to theoretical calculations in a simple medium to reduce modeling uncertainty. Regarding the interaction between heavy quark and the medium, few-body perturbative scatterings are applied to large-momentum transfer (q) processes, while a diffusion equation models the dynamics of small-q processes. Such a separation restricts the explicit use of medium quasi-particles to large-q processes only. Another advantage is that deviations from the leading-order probe-medium coupling can be parametrized as an additional contribution to the diffusion constant. The heavy quark transport coefficients are then extracted with uncertainty estimation from a Bayesian analysis including both the RHIC and the LHC data. The results are found to be consistent with earlier extraction of the light-quark transport coefficients at high momentum and be comparable with lattice calculations of the heavy-flavor diffusion constant in the static limit at low momentum.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Effect of void positioning on the detonation sensitivity of a heterogeneous energetic material

We show although it is well-established that voids profoundly influence the initiation and reaction behaviors of heterogeneous energetic materials such as polymer-bonded explosives (PBX) and propellants, there has been little study of how void location in different constituents in the microstructures of such materials affect the macroscale behavior. Here, we use three-dimensional (3D) mesoscale simulations to study how void placement within the reactive grains versus the polymer binder influences the shock-to-detonation transition (SDT) in a polymer-bonded explosive. The material studied here has a microstructure comprised of 75% PETN (pentaerythritol tetranitrate) grains and 25% HTPB (hydroxyl-terminated polybutadiene) polymer binder by volume. Porosities up to 10% in the form of spherical voids distributed in both the grains and polymer are considered. An Arrhenius reactive burn relation is used to model the chemical kinetics of the PETN grains under shock loading, thereby resolving the heterogeneous detonation behavior of the PBX. The influence of void location on the shock initiation sensitivity of the material is quantitatively ranked by comparing the predicted run distance to detonation (RDD) for each sample. The analysis includes inherent quantification of uncertainties arising from the stochastic variations in the microstructure morphologies and void distributions by using statistically equivalent microstructure sample sets (SEMSS), leading to probabilistic formulations for the RDD as a function of shock pressure. The calculations reveal that the location of voids in the composite microstructure significantly affects the RDD. Specifically, voids exclusively within the grains cause the PBX to be more sensitive (having shorter RDD) than voids in the polymer binder. Unique probabilistic relationships are derived to map the probability of observing RDD for each void location material case, allowing for prediction of initiation behavior anywhere in the shock pressure – RDD space. These findings agree with trends reported in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Density reconstruction in convergent high-energy-density systems using x-ray radiography and Bayesian inference

X-ray radiography is a technique frequently used to diagnose convergent high-energy-density (HED) systems, such as inertial confinement fusion implosion, and provides unique information that is not available through self-emission measurements. In this work, we investigate the scope and limits of that information using a radiography simulation combined with the Bayesian inference workflow. The accuracy of density reconstruction from simulated radiographs of spherical implosions driven with 27 kJ laser energy is assessed, including the increase or decrease in accuracy due to the addition of Lagrangian marker layers, Poisson noise, and improved prior information. This work is the first to present the full uncertainty distributions inferred from radiography analysis in HED systems and demonstrates the importance of constructing the full posterior probability density, as opposed to a point estimate, due to the modal structure of the likelihood surface introduced by typical experimental noise sources. This general methodology can be used both for robust analysis of radiographic data and for an improved design of radiography experiments by modeling the full experimental system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Inclusive Search for Anomalous Single-Photon Production in MicroBooNE

We present an inclusive search for anomalous production of single-photon events from neutrino interactions in the MicroBooNE experiment. The search and its signal definition are motivated by the previous observation of a low-energy excess of electromagnetic shower events from the MiniBooNE experiment. We use the Wire-Cell reconstruction framework to select a sample of inclusive single-photon final-state interactions with a final efficiency and purity of 7.0% and 40.2%, respectively. We leverage simultaneous measurements of sidebands of charged current 𝜈 𝜇 interactions and neutral current interactions producing 𝜋 0 mesons to constrain signal and background predictions and reduce uncertainties. We perform a blind analysis using a dataset collected from February 2016 to July 2018, corresponding to an exposure of 6.34 × 10 20 protons on target from the Booster Neutrino Beam at Fermilab. In the full signal region, we observe agreement between the data and the prediction, with a goodness-of-fit 𝑝 value of 0.11. We then isolate a subsample of these events containing no visible protons, and observe 93 ± 22⁢(stat) ±35⁢(syst) data events above prediction, corresponding to just above 2⁢𝜎 local significance, concentrated at shower energies below 600 MeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Nuclear mass measurements map the structure of atomic nuclei and accreting neutron stars

We introduce here mass excesses (ME) of neutron-rich isotopes of Ar through Fe, obtained via time of flight B ρ mass spectrometry at the National Superconducting Cyclotron Laboratory. Our new results have significantly reduced systematic uncertainties relative to a prior analysis, enabling the first determination of ME for Ti 58 , 59 , V 62 , Cr 65 , Mn 67 , 68 , and Fe 69 , 70 . Our results show the N = 34 subshell weaken at Sc and vanish at Ti, along with the absence of an N = 40 subshell at Mn. This further leads to a cooler accreted neutron star crust, highlighting the connection between the structure of nuclei and neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Sensitivity of Au + Au collisions to the symmetric nuclear matter equation of state at 2–5 nuclear saturation densities

We demonstrate that proton and pion flow measurements in heavy-ion collisions at incident energies ranging from 1 to 20 GeV per nucleon in the fixed target frame can be used for an accurate determination of the symmetric nuclear matter equation of state at baryon densities equal 2–4 times nuclear saturation density n 0 . We simulate Au + Au collisions at these energies using a hadronic transport model with an adjustable vector mean-field potential dependent on baryon density n B . Here, we show that the mean field can be parametrized to reproduce a given density dependence of the speed of sound at zero temperature $c$$^{2}_{s}$ (n B , T = 0), which we vary independently in multiple density intervals to probe the differential sensitivity of heavy-ion observables to the equation of state at these specific densities. Recent flow data from the STAR experiment at the center-of-mass energies √ s NN = {3.0, 4.5} GeV can be described by our model, and a Bayesian analysis of these data indicates a hard equation of state at n B ϵ (2, 3)n 0 and a possible phase transition at n B ϵ (3, 4)n 0 . More data at √ s NN = 2–5 GeV, as well as a more thorough analysis of the model systematic uncertainties will be necessary for a more precise conclusion.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Model independent comparison of supernova and strong lensing cosmography: Implications for the Hubble constant tension

We use supernovae measurements, calibrated by the local determination of the Hubble constant $H_0$ by SH0ES, to interpolate the distance-redshift relation using Gaussian process regression. We then predict, independent of the cosmological model, the distances that are measured with strong lensing time delays to test their mutual agreement. In this work we find excellent agreement between these predictions and the measurements. The agreement holds when we consider only the redshift dependence of the distance-redshift relation, independent of the value of $H_0$. Our results disfavor the possibility that lens mass modeling contributes a 10% bias or uncertainty in the strong lensing analysis, as suggested recently in the literature. In general our analysis strengthens the case that residual systematic errors in both measurements are below the level of the current discrepancy with the CMB determination of $H_0$, and supports the possibility of new physical phenomena on cosmological scales. With additional data our methodology can provide more stringent tests of unaccounted for systematics in the determinations of the distance-redshift relation in the late universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Calibration of reactive burn and Jones-Wilkins-Lee parameters for simulations of a detonation-driven flow experiment with uncertainty quantification

Here, uncertainties in the explosive-specific parameters of the Jones-Wilkins-Lee (JWL) equation of state (EOS) are carefully considered in hydrodynamic simulations of an explosive experiment to minimize the error in the flow prediction. Experimental data of the leading shock position in the transverse direction over time serves as the prediction metric for quantifying simulation prediction error. The uncertainty quantification technique, global sensitivity analysis, is utilized to determine the JWL parameters to which the transverse shock propagation is most sensitive. A polynomial response surface (PRS) is constructed in the space of the most influential JWL parameters, and the point of minimum error between the experimental data and the PRS yields calibrated JWL parameters for the experimental flow. The simulation results following the parameter calibration show good agreement with the experimental data. It was found that two significant parameters, the heat release per unit mass of reactant Q and JWL model exponent R 1 are strongly related, which makes it difficult to identify accurate values.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncer- tainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗