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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Accurate temperature model for absorptance determination of optical components with laser calorimetry

In the international standard (International Organization for Standardization 11551) for measuring the absorptance of optical components (i.e., laser calorimetry), the absorptance is obtained by fitting the temporal behavior of laser irradiation-induced temperature rise to a homogeneous temperature model in which the infinite thermal conductivity of the sample is assumed. In this paper, an accurate temperature model, in which both the finite thermal conductivity and size of the sample are taken into account, is developed to fit the experimental temperature data for a more precise determination of the absorptance. The difference and repeatability of the results fitted with the two theoretical models for the same experimental data are compared. The optimum detection position when the homogeneous model is employed in the data-fitting procedure is also analyzed with the accurate temperature model. The results show that the optimum detection location optimized for a wide thermal conductivity range of 0.2-50W/m{center_dot}K moves toward the center of the sample as the sample thickness increases and deviates from the center as the radius and irradiation time increase. However, if the detection position is optimized for an individual sample with known sample size and thermal conductivity by applying the accurate temperature model, the influence of the finite thermal conductivity and sample size on the absorptance determination can be fully compensated for by fitting the temperature data recorded at the optimum detection position to the homogeneous temperature model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

A comparison of small-field tissue phantom ratio data generation methods for an Elekta Agility 6 MV photon beam

Tissue-phantom ratios (TPRs) are a common dosimetric quantity used to describe the change in dose with depth in tissue. These can be challenging and time consuming to measure. The conversion of percentage depth dose (PDD) data using standard formulae is widely employed as an alternative method in generating TPR. However, the applicability of these formulae for small fields has been questioned in the literature. Functional representation has also been proposed for small-field TPR production. This article compares measured TPR data for small 6 MV photon fields against that generated by conversion of PDD using standard formulae to assess the efficacy of the conversion data. By functionally fitting the measured TPR data for square fields greater than 4 cm in length, the TPR curves for smaller fields are generated and compared with measurements. TPRs and PDDs were measured in a water tank for a range of square field sizes. The PDDs were converted to TPRs using standard formulae. TPRs for fields of 4 × 4 cm{sup 2} and larger were used to create functional fits. The parameterization coefficients were used to construct extrapolated TPR curves for 1 × 1 cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields. The TPR data generated using standard formulae were in excellent agreement with direct TPR measurements. The TPR data for 1 × 1-cm{sup 2}, 2 × 2-cm{sup 2}, and 3 × 3-cm{sup 2} fields created by extrapolation of the larger field functional fits gave inaccurate initial results. The corresponding mean differences for the 3 fields were 4.0%, 2.0%, and 0.9%. Generation of TPR data using a standard PDD-conversion methodology has been shown to give good agreement with our directly measured data for small fields. However, extrapolation of TPR data using the functional fit to fields of 4 × 4 cm{sup 2} or larger resulted in generation of TPR curves that did not compare well with the measured data.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Exploring new physics with O(keV) electron recoils in direct detection experiments

Motivated by the recent XENON 1T results, we explore various new physics models that can be discovered through searches for electron recoils in O(keV)-threshold direct-detection experiments. First, we consider the absorption of axion-like particles, dark photons, and scalars, either as dark matter relics or being produced directly in the Sun. In the latter case, we find that keV mass bosons produced in the Sun provide an adequate fit to the data but are excluded by stellar cooling constraints. We address this tension by introducing a novel Chameleon-like axion model, which can explain the excess while evading the stellar bounds. We find that absorption of bosonic dark matter provides a viable explanation for the excess only if the dark matter is a dark photon or an axion. In the latter case, photophobic axion couplings are necessary to avoid X-ray constraints. Second, we analyze models of dark matter-electron scattering to determine which models might explain the excess. Standard scattering of dark matter with electrons is generically in conflict with data from lower-threshold experiments. Momentum-dependent interactions with a heavy mediator can fit the data with dark matter mass heavier than a GeV but are generically in tension with collider constraints. Next, we consider dark matter consisting of two (or more) states that have a small mass splitting. The exothermic (down)scattering of the heavier state to the lighter state can fit the data for keV mass splittings. Finally, we consider a subcomponent of dark matter that is accelerated by scattering off cosmic rays, finding that dark matter interacting though an O(100 keV)-mass mediator can fit the data. The cross sections required in this scenario are, however, typically challenged by complementary probes of the light mediator. Throughout our study, we implement an unbinned Monte Carlo analysis and use an improved energy reconstruction of the XENON 1T events.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1989

Rapid fitting of particle cascade development data from X-ray film densitometry measurements

A semiautomatic method of fitting transition curves to X-ray film optical density measurements of electromagnetic particle cascades is described. Several hundred singly and multiple interacting cosmic ray events from the JACEE 8 balloon flights were analyzed using this procedure. In addition to greatly increased speed compared to the previous manual method, the semiautomatic method offers increased accuracy through maximum likelihood fitting.

Roberts, E.↗
NASA NTRS2019

Kepler Data Validation II–Transit Model Fitting and Multiple-Planet Search

This paper discusses the transit model-fitting and multiple-planet search algorithms and performance of the Kepler Science Data Processing Pipeline, developed by the Kepler Science Operations Center (SOC). Threshold crossing events (TCEs), which are transit candidate events, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the data validation (DV) component. The transit model is used in DV to fit TCEs to characterize planetary candidates and to derive parameters that are used in various diagnostic tests to classify them. After the signature associated with the TCE is removed from the light curve of the target star, the residual light curve goes through TPS again to search for additional TCEs. The iterative process of transit model fitting and multiple-planet search continues until no TCE is generated from the residual light curve or an upper limit is reached. The transit model-fitting and multiple-planet search performance of the final release (9.3, 2016January) of the pipeline is demonstrated with the results of the processing of four years (17 quarters) of flight data from the primary Kepler Mission. The transit model-fitting results are accessible from the NASA Exoplanet Archive. The final version of the SOC codebase is available through GitHub.

Threshold crossing events (TCEs↗
NASA NTRS1981

Polarization of the cosmic background radiation

The technique and results of a measurement of the linear polarization of the cosmic background radiation at a wavelength of 9 mm are discussed. Data taken between 1978 May and 1980 February from both the Northern Hemisphere (Berkeley latitude 38 deg N) and the Southern Hemisphere (Lima latitude 12 deg S) over 11 declinations from -37 to +63 deg show the radiation to be essentially unpolarized over all areas surveyed. Fitting all data gives the 95% confidence level limit on a linearly polarized component of 0.3 mK for spherical harmonics through third order. A fit of all data to the anisotropic axisymmetric model of Rees (1968) yields a 95% confidence level limit of 0.15 mK for the magnitude of the polarized component. Constraints on various cosmological models are discussed in light of these limits.

Lubin, P. M.↗
NASA NTRS1996

X-ray spectroscopy of the super soft source RXJ0925.7-475

The super soft source (SSS) RXJ 0925.7-475 was observed with the Advanced Satellite for Cosmology and Astrophysics (ASCA) solid state spectrometer and its energy spectrum was analyzed. A simple black body model does not fit the data, and several absorption edges of ionized heavy elements are required. Without the addition of absorption edges, the best-fit black body radius and the estimated bolometric luminosity are 6800 (d/1 kpc) km and 1.2 x 10(exp 37) (d/1 kps)(exp 2) erg/s, respectively. The introduction of absorption edges significantly reduces the best-fit radius and luminosity to 140 (d/1 KPS) km and 6 x 10(exp 34) (d/1 kpc)(exp 2) erg/s, respectively. This suggests that the estimation of the emission region size and luminosity of SSS based on the black body model fit to the observed data is not reliable.

Ebisawa, Ken↗
DOE OSTI2011

INFORMATION ON THE MILKY WAY FROM THE TWO MICRON ALL SKY SURVEY WHOLE SKY STAR COUNT: THE STRUCTURE PARAMETERS

The K{sub s} -band differential star count of the Two Micron All Sky Survey (2MASS) is used to derive the global structure parameters of the smooth components of the Milky Way. To avoid complication introduced by other fine structures and significant extinction near and at the Galactic plane, we only consider Galactic latitude |b| > 30{sup 0} data. The star count data are fitted with a three-component model: double exponential thin disk and thick disk, and a power-law decay oblate halo. Using maximum likelihood, the best-fit local density of the thin disk is n{sub 0} = 0.030 {+-} 0.002 stars pc{sup -3}. The best-fit scale height and length of the thin disk are H{sub z1} = 360 {+-} 10 pc and H{sub r1} = 3.7 {+-} 1.0 kpc, and those of the thick disk are H{sub z2} = 1020 {+-} 30 pc and H{sub r2} = 5.0 {+-} 1.0 kpc, the local thick-to-thin disk density ratio is f{sub 2} = 7% {+-} 1%. The best-fit axis ratio, power-law index, and local density ratio of the oblate halo are {kappa} = 0.55 {+-} 0.15, p = 2.6 {+-} 0.6, and f{sub h} = 0.20% {+-} 0.10%, respectively. Moreover, we find some degeneracy among the key parameters (e.g., n{sub 0}, H{sub z1}, f{sub 2}, and H{sub z2}). Any pair of these parameters are anti-correlated to each other. The 2MASS data can be well fitted by several possible combinations of these parameters. This is probably the reason why there is a wide range of values for the structure parameters in literature similar to this study. Since only medium and high Galactic latitude data are analyzed, the fitting is insensitive to the scale lengths of the disks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Evolving radon diffusion through earthen barriers at uranium waste disposal sites

Field measurements of Rn-222 fluxes from the tops and bottoms of compacted clay radon barriers were used to calculate effective Rn diffusion coefficients (D Rn ) at four uranium waste disposal sites in the western United States to assess cover performance after more than 20 years of service. Values of D Rn ranged from 7.4 × 10 -7 to 6.0 × 10 -9 m 2 /s, averaging 1.42 × 10 -7 . Water saturation (S W ) from soil cores indicated that there was relatively little control of D Rn by S W , especially at higher moisture levels, in contrast to estimates from most steady-state diffusion models. Further, this is attributed to preferential pathways intrinsic to construction of the barriers or to natural process that have developed over time including desiccation cracks, root channels, and insect burrows in the engineered earthen barriers. A modification to some models in which fast and slow pathway D Rn values are partitioned appears to give a good representation of the data; 4% of the fast pathway was needed to fit the data regression. For locations with high S w and highest D Rn (and fluxes) at each site, the proportion of fast pathway ranged from 1.7% to 34%, but for many locations with lower fluxes, little if any fast pathway was needed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

A comparison of model validation approaches for echo state networks using climate model replicates

As global temperatures continue to rise, climate mitigation strategies such as stratospheric aerosol injections (SAI) are increasingly discussed, but the downstream effects of these strategies are not well understood. As such, there is interest in developing statistical methods to quantify the evolution of climate variable relationships during the time period surrounding an SAI. Feature importance applied to echo state network (ESN) models has been proposed as a way to understand the effects of SAI using a data-driven model. This approach depends on the ESN fitting the data well. If not, the feature importance may place importance on features that are not representative of the underlying relationships. Typically, time series prediction models such as ESNs are assessed using out-of-sample performance metrics that divide the times series into separate training and testing sets. However, this model assessment approach is geared towards forecasting applications and not scenarios such as the motivating SAI example where the objective is using a data driven model to capture variable relationships. Here, in this paper, we demonstrate a novel use of climate model replicates to investigate the applicability of the commonly used repeated hold-out model assessment approach for the SAI application. Simulations of an SAI are generated using a simplified climate model, and different initialization conditions are used to provide independent training and testing sets containing the same SAI event. The climate model replicates enable out-of-sample measures of model performance, which are compared to the single time series hold-out validation approach. For our case study, it is found that the repeated hold-out sample performance is comparable, but conservative, to the replicate out-of-sample performance when the training set contains enough time after the aerosol injection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Impact of Precipitation Parameters on the Specific Surface Area of PuO 2

Controlling the properties of PuO 2 through processing is of vital importance to environmental transport and fate, production of nuclear fuels, nuclear forensic analyses, stockpile stewardship, and storage of nuclear wastes applications. A number of processing conditions have been identified to control final product properties, including specific surface area (SSA), residual carbon content, adsorption of volatile species, morphology, and particle size. In this paper, a novel approach is developed for the prediction of PuO 2 SSA via the synthetic route of Pu(IV) oxalate precipitation followed by calcination. The proposed model utilizes multivariate regression methodology and leave one out formalism to link Savannah River Site (SRS) precipitation and calcination production data to the SSA of the final product. A comparison among the models provides insight into the accuracy and ability to identify variations amongst the processing data. Additionally, the models may also be used to fit new data outside of the parameters explored in a production facility. Finally, the trained model was compared to a similarly trained conventional model form to illustrate the influence of precipitation parameters on the prediction of the final SSA. The models presented here attempt to provide new methods for more accurate prediction of the PuO 2 product properties in a production scale environment for key environmental and nuclear applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2016

Comment on “Temperature dependence of atomic vibrations in mono-layer graphene” [J. Appl. Phys. 118, 074302 (2015)]

In an interesting recent study [Allen et al., J. Appl. Phys. 118, 074302 (2015)] (see also their Erratum [Allen et al., J. Appl. Phys. 118, 159902 (2015)]), Allen and co-workers measured the mean square amplitudes of graphene lattice vibrations between 100 and 1300 K and used a simplified theoretical approximation for the acoustic phonon modes to evaluate the maximum phonon wavelengths supported by the lattice. By fitting their data using the smallest wave-vector as the fitting parameter, they found this to be significantly smaller than the physical size of the graphene crystallites.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

$N$=5, 6, 7, 8: Nested hypothesis tests and truncation dependence of $|V_{cb}|$ |Vcb|

The determination of | V c b | from exclusive semileptonic B → D * ℓ ν decays is sensitive to the choice of form factor parametrization. Larger | V c b | values are obtained by fitting the Boyd-Grinstein-Lebed (BGL) versus the Caprini-Lellouch-Neubert (CLN) parametrization to recent Belle measurements. For the BGL parametrization, published fits use different numbers of parameters. We propose a method based on nested hypothesis tests to determine the optimal number of BGL parameters to fit the data, and find that six parameters are optimal to fit the Belle tagged and unfolded measurement. We further explore the differences between fits that use different numbers of parameters. The fits which yield | V c b | values in better agreement with determinations from inclusive semileptonic decays tend to exhibit tensions with heavy quark symmetry expectations. These have to be resolved before the determinations of | V c b | from exclusive and inclusive decays can be considered understood.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

When more data hurts: Optimizing data coverage while mitigating diversity-induced underfitting in an ultrafast machine-learned potential

Machine-learned interatomic potentials (MLIPs) are becoming an essential tool in materials modeling. However, optimizing the generation of training data used to parametrize the MLIPs remains a significant challenge. This is because MLIPs can fail when encountering local environments too different from those present in the training data. The difficulty of determining a priori the environments that will be encountered during molecular dynamics simulation necessitates diverse, high-quality training data. Here, this study investigates how training data diversity affects the performance of MLIPs using the Ultra-Fast force field (UF 3 ) to model amorphous silicon nitride. We employ expert and autonomously generated data to create the training data and fit four force field variants to subsets of the data. Our findings reveal a critical balance in training data diversity: insufficient diversity hinders generalization, while excessive diversity can exceed the MLIP's learning capacity, reducing simulation accuracy. Specifically, we found that the UF 3 variant trained on a subset of the training data, in which nitrogen-rich structures were removed, offered vastly better prediction and simulation accuracy than any other variant. By comparing these UF 3 variants, we highlight the nuanced requirements for creating accurate MLIPs, emphasizing the importance of application-specific training data to achieve optimal performance in modeling complex material behaviors.

ab initio molecular dynamics↗
DOE OSTI2022

Thermoelastic properties of zircon: Implications for geothermobarometry

Abstract A thermal-pressure equation of state has been determined for zircon (ZrSiO4) that characterizes its thermoelastic behavior at metamorphic conditions. New pressure-volume (P-V) data from a “Mud Tank” zircon have been collected from 1 bar to 8.47(1) GPa using X-ray diffraction, and elastic moduli were measured from room temperature up to 1172 K by resonance ultrasound spectroscopy. These data were fitted simultaneously with temperature-volume (T-V) data from the literature in EosFit7c using a new scaling technique. The parameters of a third-order Birch-Murnaghan EoS with a Mie-Grüneisen-Debye model for thermal pressure have compressional EoS parameters K0T = 224.5(1.2) GPa, K0T' = 4.90(31) with a fixed initial molar volume V0 = 39.26 cm3/mol and thermal parameters γ0 = 0.868(15), q = 2.37(80), and ΘD = 848(38) K. EoS parameters that describe the variation of unit-cell parameters with pressure and temperature were determined using an isothermal-type EoS. This new EoS confirms that zircons are stiffer than garnets and exhibit a much lower thermal expansion. This results in steep isomekes between zircon and garnets, which makes zircon trapped as inclusions in garnets at metamorphic conditions a good piezothermometer.

Geochemistry & Geophysics↗
DOE OSTI2021

Critical and Subcritical Californium Source Driven Noise Analysis Experiments with Fresh PWR Fuels Pins

These experiments were performed in 1983 between August 1 and September 16 and used 35 operational days of critical facility time at the Babcock & Wilcox critical facility in Lynchburg, Va. These measurements were to assess the capability of the Cf source driven noise analysis method to measure the subcriticality of light water reactor fresh fuel configurations. This report documents the experiments of 1983 that were not reported at that time. These measurement with 2.459 wt. % 235 U enriched uranium oxide fresh fuel pins started at the delayed critical configuration of the fully assembled pressurized water reactor (PWR) core configuration with 1511 parts per million (ppm) natural boron (19.8 wt. % 10 B) in the water. This was a cylindrical configuration of 4961 fuel pins. After the initial measurements at delayed criticality, subcritical measurements by the Cf source driven noise analysis method were performed in which the number of detectors and Cf source locations were varied. Additional boron was added to the water moderator and reflector to reduce the neutron multiplication factor, with resulting boron concentrations of 1561, 1613, 1765, 1880, 2104, 2384, 2975, 3606, and 4303 ppm. After the completion of these measurements the increased, the boron concentration was returned to that at delayed critical (1511 ppm) and the reactivity was decreased by reducing the number of fuel pins in steps to 3713, 2553, 1281, 749, and 333 fuel pins and then to that (289) of a s ingle square 17 x 17 pin array, corresponding to a single PW fuel element. For all measurement that started at delayed criticality and then reduced the neutron multiplication factor to various subcritical states, inverse kinetics rod drop measurements at the higher reactivities were also performed but not reported here. At all subcritical states the break frequency noise analysis data was fitted to obtain the prompt neutron decay constant. Some data presented in this report are from notes not in the logbook. The purpose of this report is to document the experimental information for the measurements performed so that a later date someone could perform the required uncertainty and calculational analyses and documentation to use these data for an International Nuclear Criticality Safety Benchmark Program (INCSBEP) or Nuclear Energy Agency (NEA) benchmark. The data from these measurements is available from the Laboratory Records Department of Oak Ridge National Laboratory and the logbook is available from INCSBEP at Idaho National Laboratory.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Exploring the Whole Set of Accurate Sparse Interpretable Models

In data science applications, there are often many models that fit the data well. This phenomenon was called the Rashomon Effect by Leo Breiman. The set of good models is called the Rashomon Set, and the goal of this project is to locate, store, and study the Rashomon sets for classes of interpretable models, including decision trees and generalized additive models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Perspective on Traditional and Data Driven Electrochemical Modeling and Analysis

To understand the behavior of electrochemical systems, we need to reduce the dimensionality of the measured current-voltage-time (I-V-t) data by fitting models, thus enabling us to analyze and compare the governing physics. Traditionally, the process for this is an 'expert first' approach: defining the model and its explicit assumptions based on inductive reasoning or empirical observation, fitting small portions of the I-V-t data where assumptions are most valid or carefully designing experiments to enforce key assumptions, and then interpreting the model parameters. However, modern data-driven methods enable a new paradigm: a 'data first' approach, where the latent behaviors governing the system's measured response are identified directly using machine-learning models that optimize both model structure and parameters from the I-V-t data, guaranteeing that the learned model explains as much of the observed system response as possible. After model identification, the model can then be interrogated by an expert to connect observed behaviors with underlying physics. This talk will review several different types of electrochemical analysis (electrochemical impedance, differential voltage-capacity, electrochemical kinetics) and compare the traditional and data-driven methods for analyzing the data.

42 ENGINEERING↗