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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

A Compton reflection model for the cosmic X-ray and gamma-ray backgrounds

The gamma-ray spectrum of an AGN in the Compton reflection model is calculated and the contribution of such sources to the cosmic gamma-ray background is considered. The spectrum is composed of three parts: an X-ray power law, a broad hump from roughly 10 to 120 keV due to reprocessing of the power-law X-ray spectrum by cold gas, and gamma rays which are due to the inverse-Compton scattering of X-rays. The contribution of such sources to the cosmic gamma-ray background is computed and it is found that they provide an excellent fit to the entire background spectrum from 3 keV to 10 MeV. Constraints on the physical conditions in these sources are derived based on these results and the possibility of observing such sources with GRO is considered.

Rogers, R. D.↗
NASA NTRS1991

Exocentric judgements in real environments and stereoscopic displays

Spatial direction errors during interpretation of perspective images, such as 3D map displays, may originate from misjudgment of the orientation of the viewing direction used to make the display. One source of these errors could be perceptual evidence of the display surface. Two experiments are reported in which the same judgment exocentric task was presented, but the cues to the picture surface were reduced or eliminated by presenting the task as a stereoscopic, virtual image or by a geometrically matched physical model. A theory developed to model exocentric direction errors on perspective displays has been fitted to the data from these two experiments. The parameters estimated from the fit in both experiments indicate that the subjects may be more correctly estimating the viewing direction than in ordinary perspective displays. Consequently, in some real world or stereo viewing conditions, errors in estimating the viewing direction are not likely to dominate exocentric direction errors.

Ellis, Stephen R.↗
NASA NTRS1997

Satellite Sensed Skin Sea Surface Temperature

Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data.

Donlon, Craig↗
NASA NTRS1961

A Method of Estimating Residuals in Orbital Theory

The degree of approximation used in determining the orbits of earth satellites is reflected in the residuals (differences between calculated and observed positions). The least-squares procedure generally used to fit theory to observation tends to obscure the significance of theoretical parameters, so that the physical sources of residuals cease to be apparent. A method is outlined herein for estimating the magnitude of the residuals to be expected from an approximate theory presumed to have one missing or incorrect term.

Lecar, Myron↗
NASA NTRS2003

Failure Criteria for FRP Laminates in Plane Stress

A new set of six failure criteria for fiber reinforced polymer laminates is described. Derived from Dvorak's fracture mechanics analyses of cracked plies and from Puck's action plane concept, the physically-based criteria, denoted LaRC03, predict matrix and fiber failure accurately without requiring curve-fitting parameters. For matrix failure under transverse compression, the fracture plane is calculated by maximizing the Mohr-Coulomb effective stresses. A criterion for fiber kinking is obtained by calculating the fiber misalignment under load, and applying the matrix failure criterion in the coordinate frame of the misalignment. Fracture mechanics models of matrix cracks are used to develop a criterion for matrix in tension and to calculate the associated in-situ strengths. The LaRC03 criteria are applied to a few examples to predict failure load envelopes and to predict the failure mode for each region of the envelope. The analysis results are compared to the predictions using other available failure criteria and with experimental results. Predictions obtained with LaRC03 correlate well with the experimental results.

Davila, Carlos G.↗
DOE OSTI2020

Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics

For multilayer materials in thin substrate systems, interfacial failure is one of the most challenges. The traction-separation relations (TSR) quantitatively describe the mechanical behavior of a material interface undergoing openings, which is critical to understand and predict interfacial failures under complex loadings. However, existing theoretical models have limitations on enough complexity and flexibility to well learn the real-world TSR from experimental observations. A neural network can fit well along with the loading paths but often fails to obey the laws of physics, due to a lack of experimental data and understanding of the hidden physical mechanism. In this paper, we propose a thermodynamic consistent neural network (TCNN) approach to build a data-driven model of the TSR with sparse experimental data. The TCNN leverages recent advances in physics-informed neural networks (PINN) that encode prior physical information into the loss function and efficiently train the neural networks using automatic differentiation. We investigate three thermodynamic consistent principles, i.e., positive energy dissipation, steepest energy dissipation gradient, and energy conservative loading path. All of them are mathematically formulated and embedded into a neural network model with a novel defined loss function. A real-world experiment demonstrates the superior performance of TCNN, and we find that TCNN provides an accurate prediction of the whole TSR surface and significantly reduces the violated prediction against the laws of physics.

Zhang, Jiaxin↗
DOE OSTI2021

Muon-neutrino disappearance with multiple liquid argon time projection chambers in the Fermilab Booster neutrino beam

The Short Baseline Neutrino (SBN) program consists of three liquid argon time projection chamber (LArTPC) experiments: SBND, MicroBooNE and ICARUS, with 110 m, 470 m and 600 m baselines respectively. The detectors are located in the Booster Neutrino Beam (BNB) at Fermilab which has a peak energy around 0.7 GeV and contains predominantly muon neutrinos. The baseline and energy range of the SBN program is conducive to measuring neutrino oscillation parameters under various sterile neutrino hypotheses. Sterile neutrinos have been proposed as a possible solution to the numerous short baseline anomalies. The proposed particles must be sterile in nature such that they do not interact via the weak force, however they may undergo oscillations with the active neutrino flavours. Their existence may consequently be confirmed through measurements of the appearance and disappearance of the active flavours. The analyses presented in this thesis aimed to calculate and understand the sensitivity of the SBN program to measuring the ?µ disappearance parameters under the (3+1) sterile neutrino oscillation hypothesis. The sensitivity of SBN to measuring the ?µ disappearance sterile oscillation parameters, sin2 2?µµ, ?m2 41, was calculated through semi-exclusive joint fits of the ?µ CC 0p and ?µ CC Other reconstructed neutrino energy spectra. The first iteration used truth-level Monte Carlo (MC) events, and determined that the 5s SBN sensitivity is comparable to the 90% MINOS/MINOS+ confidence level and supersedes the 90% MiniBooNE confidence level across entire phase space. Semi-exclusive joint fits of the aforementioned sample spectra were performed between the MC and multiple mock data sets in SBND. This analysis assessed the accuracy with which the near detector can disentangle systematic from physics effects in the oscillation analysis. The result was a 5.49% discrepancy between the ICARUS Monte Carlo and mock data event rates, when the systematic constraints from the near detector fit were extrapolated to the far detector. The second iteration of the SBN sensitivity analysis involved the application of an event selection procedure developed in SBND, following the full reconstruction chain. ?µ CC 0p events were selected from sample of neutrinos with 84.5% efficiency and 84.3% purity. The sterile neutrino sensitivity was determined once more at the near detector with these samples, and was shown to be consistent with the truth-level studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Solar neutrinos and ν 2 visible decays to ν 1

Experimental bounds on the neutrino lifetime depend on the nature of the neutrinos and the details of the potentially new physics responsible for neutrino decay. In the case where the decays involve active neutrinos in the final state, the neutrino masses also qualitatively impact how these manifest themselves experimentally. In order to further understand the impact of nonzero neutrino masses, we explore how observations of solar neutrinos constrain a very simple toy model. We assume that neutrinos are Dirac fermions and there is a new massless scalar that couples to neutrinos such that a heavy neutrino— ν 2 with mass m 2 —can decay into a lighter neutrino— ν 1 with mass m 1 —and a massless scalar. We find that the constraints on the new physics coupling depend, sometimes significantly, on the ratio of the daughter-to-parent neutrino masses and that, for large-enough values of the new physics coupling, the “dark side” of the solar neutrino parameter space— sin 2 θ 12 ∼ 0.7 —provides a reasonable fit to solar neutrino data, if only B 8 or Be 7 neutrino data alone are considered, but no allowed region is found in the combined analysis. Our results generalize to other neutrino-decay scenarios, including those that mediate ν 2 → ν 1 ν ¯ 3 ν 3 when the neutrino mass ordering is inverted mass and m 2 > m 1 ≫ m 3 , the mass of ν 3 . Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2021

Urban Green Spaces, Greenness Exposure and Species Richness in Residential Environments and Relations with Physical Activity and BMI in Portuguese Adolescents

Environmental factors play an important role in obesity-related behaviors. Evidence indicates significant associations between weight and urban green spaces in adults, but it is not clear whether this relationship applies to adolescents. Therefore, our aim was to determine the associations between urban green spaces, greenness exposure and species richness in residential environments with physical activity and body mass index. Sixty-two adolescents between 12 and 18 years of age answered a self-administered questionnaire, providing information on height, weight, age, sex and home address. Data on socioeconomic deprivation were obtained from the European Index of Deprivation for Small Portuguese Areas. Physical activity levels were assessed using accelerometers. Urban green space counts and the normalized difference vegetation index values were measured using buffers along the roads with distances of 300, 500, 1000 and 1500 m from each participant’s residence. To quantify the species richness, the species richness index was used. Linear regression models were fitted to analyze whether urban green spaces, exposure to green spaces and species richness counts for each distance were associated with physical activity and self-reported body mass index. We did not find significant associations between the independent variables and the probability of overweight or obesity. The relationship between environmental variables, adolescents’ physical activity and body weight seems to be complex and further studies may contribute to better understanding of the topic.

Melo, Juliana (ORCID:0000000301275340)↗
NASA NTRS1994

Investigation of physical parameters in stellar flares observed by GINGA

This program involves analysis and interpretation of results from GINGA Large Area Counter (LAC) observations from a group of large stellar x-ray flares. All LAC data are re-extracted using the standard Hayashida method of LAC background subtraction and analyzed using various models available with the XSPEC spectral fitting program. Temperature-emission measure histories are available for a total of 5 flares observed by GINGA. These will be used to compare physical parameters of these flares with solar and stellar flare models.

Stern, Robert A.↗
DOE OSTI2026

First nucleon gluon PDF from large momentum effective theory

We report the first nucleon gluon parton distribution function (PDF) using Large-Momentum Effective Theory (LaMET). We focus on the gluon operator which was demonstrated to have the best signal-to-noise in the previous attempt [1] in computing gluon PDFs using LaMET. We compute the corresponding Wilson coefficients needed for the hybrid-renormalized matrix elements and the matching kernel to convert the quasi-PDF to the lightcone one at the one-loop level. We demonstrate that with the proper Wilson coefficients in place, the counterterms for the renormalization are independent of the hadron and mass within statistical error. Using the resulting renormalization, we then compute the nucleon PDF using a HISQ ensemble generated by the MILC collaboration with N f = 2 + 1 +1, a ≈ 0.12 fm, with valence pion masses of 310 and 690 MeV and two gauge link smearing techniques. Despite the physics effects of the heavier than physical pion masses and gauge link smearing, this calculation provides excellent proof of principle and compares reasonably with selected global fit results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2009

Application of a Self-Similar Pressure Profile to Sunyaev-Zeldovich Effect Data from Galaxy Clusters

We investigate the utility of a new, self-similar pressure profile for fitting Sunyaev-Zel'dovich (SZ) effect observations of galaxy clusters. Current SZ imaging instruments-such as the Sunyaev-Zel'dovich Array (SZA)- are capable of probing clusters over a large range in a physical scale. A model is therefore required that can accurately describe a cluster's pressure profile over a broad range of radii from the core of the cluster out to a significant fraction of the virial radius. In the analysis presented here, we fit a radial pressure profile derived from simulations and detailed X-ray analysis of relaxed clusters to SZA observations of three clusters with exceptionally high-quality X-ray data: A1835, A1914, and CL J1226.9+3332. From the joint analysis of the SZ and X-ray data, we derive physical properties such as gas mass, total mass, gas fraction and the intrinsic, integrated Compton y-parameter. We find that parameters derived from the joint fit to the SZ and X-ray data agree well with a detailed, independent X-ray-only analysis of the same clusters. In particular, we find that, when combined with X-ray imaging data, this new pressure profile yields an independent electron radial temperature profile that is in good agreement with spectroscopic X-ray measurements.

Mroczkowski, Tony↗
NASA NTRS1994

HST eclipse mapping of dwarf nova OY Carinae in quiescence: An 'Fe II curtain' with Mach approx. = 6 velocity dispersion veils the white dwarf

Hubble Space Telescope (HST) observations of the eclipsing dwarf nova OY Car in its quiescent state are used to isolate the ultraviolet spectrum (1150-2500 A at 9.2 A Full Width at Half Maximum (FWHM) resolution) of the white dwarf, the accretion disk, and the bright spot. The white dwarf spectrum has a Stark-broadened photospheric L(alpha) absorption, but is veiled by a forest of blended Fe II features that we attribute to absorption by intervening disk material. A fit gives T(sub w) approx. = 16.5 x 10(exp 3) K for the white dwarf with a solar-abundance, log g = 8 model atmosphere, and T approx. = 10(exp 4) K, n(sub e) approx. = 10(exp 13)/cu cm, N(sub H) approx. = 10(exp 22) sq cm, and velocity dispersion delta V approx. = 60 km/s for the veil of homogeneous solar-abundance local thermodynamic equilibrium (LTE) gas. The veil parameters probably measure characteristic physical conditions in the quiescent accretion disk or its chromosphere. The large velocity dispersion is essential for a good fit; it lowers (chi square)/778 from 22 to 4. Keplerian shear can produce the velocity dispersion if the veiling gas is located at R approx. = 5 R(sub W) with (delta R)/R approx. = 0.3, but this model leaves an unobscured view to the upper hemisphere of the white dwarf, incompatible with absorptions that are up to 80% deep. The veiling gas may be in the upper atmosphere of the disk near its outer rim, but we then require supersonic (Mach approx. = 6) but sub-Keplerian (delta V/V(sub Kep) approx. = 0.07) velocity disturbances in this region to produce both the observed radial velocity dispersion and vertical motions sufficient to elevate the gas to z/R = cos i = 0.12. Such motions might be driven by the gas stream, since it may take several Kepler periods to reestablish the disk's vertical hydrostatic equilibrium. The temperature and column density of the gas we see as Fe II absorption in the ultraviolet are similar to what is required to produce the strong Balmer jump and line emissions seen in optical spectra of OY Car and similar quiescent dwarf novae. The outer accretion disk is detected at mid-eclipse with a spectrum that rises from 0.05 to 0.3 mJy between 2000 and 2500 A, consistent with combinations of cool blackbodies, blended Fe II emission lines, and Balmer continuum emission. The total disk flux density is 0.5 mJy at 2500 A, and this shallow disk eclipse implies a roughly flat surface brightness distribution. The bright spot, somewhat bluer than the disk, has a flux density rising from 0.05 to 0.15 mJy between 1600 and 2500 A. The C IV emission line has a broad shallow eclipse, but the radial velocity variations observed during the eclipse do not clearly distinguish between a disk or wind origin. The only possible indications of boundary layer emission are fast UV flares that appear to arise from near the central object -- not from the bright spot.

Horne, Keith↗
DOE OSTI2023

Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data

High-energy large-scale particle colliders produce data at high speed in the order of 1 terabytes per second in nuclear physics and petabytes per second in high energy physics. Developing real-time data compression algorithms to reduce such data at high throughput to fit permanent storage has drawn increasing attention. Specifically, at the newly constructed sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC), a time projection chamber is used as the main tracking detector, which records particle trajectories in a volume of three-dimensional (3D) cylinder. The resulting data are usually very sparse with occupancy around 10.8%. Such sparsity presents a challenge to conventional learning-free lossy compression algorithms, such as SZ, ZFP, and MGARD. The 3D convolutional neural network (CNN)-based approach, Bicephalous Convolutional Autoencoder (BCAE), outperforms traditional methods both in compression rate and reconstruction accuracy. BCAE can also utilize the computation power of graphical processing units suitable for deployment in a modern heterogeneous highperformance computing environment. This work introduces two BCAE variants: BCAE++ and BCAE-2D. BCAE++ achieves a 15% better compression ratio and a 77% better reconstruction accuracy measured in mean absolute error compared with BCAE. BCAE-2D treats the radial direction as the channel dimension of an image, resulting in a 3× speedup in compression throughput. In addition, we demonstrate an unbalanced autoencoder with a larger decoder can improve reconstruction accuracy without significantly sacrificing throughput. Lastly, we observe both the BCAE++ and BCAE-2D can benefit more from using half-precision mode in throughput (76 - 79% increase) without loss in reconstruction accuracy. The source code and links to data and pretrained models can be found at https://github.com/BNL-DAQ-LDRD/NeuralCompression_v2

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Accurate calculation of many-body energies in water clusters using a classical geometry-dependent induction model

We incorporate geometry-dependent distributed multipole and polarizability surfaces into an induction model that is used to describe the 3- and 4-body terms of the interaction between water molecules. The expansion is carried out up to hexadecapole with the multipoles distributed on the atom sites. Dipole-dipole, dipole-quadrupole, and quadrupole-quadrupole distributed polarizabilities are used to represent the response of the multipoles to an electric field. We compare the model against two large databases consisting of 43,844 3-body terms and 3,603 4-body terms obtained from high level ab initio calculations previously used to fit the MB-pol and q-AQUA interaction potentials. The classical induction model with no adjustable parameters reproduces the ab-initio 3- and 4-body terms contained in these teo Databases with a Root-Mean-Square-Error (RMSE) of 0.104/0.058 and a Mean-Absolute-Error (MAE) of 0.054/0.026 kcal/mol, respectively, results that are on a par with those obtained 1 by fitting the same data using tens of thousands of Permutationally Invariant Polynomials (PIPs). This demonstrates the accuracy of this physically motivated model in describing the 3- and 4-body terms in the interactions between water molecules with no adjustable parameters. The triple-dipole-dispersion energy was included in the 3-body energy and was found to be small but not quite negligible. The model represents a practical, efficient and transferable approach for obtaining accurate non-additive interactions for multi-component systems without the need of performing tens of thousands of high level electronic structure calculations and fitting them with tens of thousands of PIPs.

molecular analysis water, aqueous↗
DOE OSTI2024

Polyconvex neural network models of thermoelasticity

Machine-learning function representations such as neural networks have proven to be excellent constructs for constitutive modeling due to their flexibility to represent highly nonlinear data and their ability to incorporate constitutive constraints, which also allows them to generalize well to unseen data. Here, in this work, we extend a polyconvex hyperelastic neural network framework to (isotropic) thermo-hyperelasticity by specifying the thermodynamic and material theoretic requirements for an expansion of the Helmholtz free energy expressed in terms of deformation invariants and temperature. Different formulations which a priori ensure polyconvexity with respect to deformation and concavity with respect to temperature are proposed and discussed. The physics-augmented neural networks are furthermore calibrated with a recently proposed sparsification algorithm that not only aims to fit the training data but also penalizes the number of active parameters, which prevents overfitting in the low data regime and promotes generalization. The performance of the proposed framework is demonstrated on synthetic data, which illustrate the expected thermomechanical phenomena, and existing temperature-dependent uniaxial tension and tension-torsion experimental datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Uranium hydride corrosion. I New insights into the Condon-Kirkpatrick model of uranium hydride formation rate

An analytic solution to the uranium hydride formation rate equation of Condon and Kirkpatrick (CK) has been developed, which is directly solved via algebraic operations and requires only gaseous hydrogen (H 2 ) pressure and temperature as inputs. The solution does not depend on the specific functional forms of the hydriding and dehydriding rate constants, nor of key physical parameters. Furthermore, a modified form of the CK model has also been developed, where replacement of the hydrogen solubility function results in an improved fit to published experimental data as H 2 pressure decreases toward the corrosion threshold value.

36 MATERIALS SCIENCE↗
DOE OSTI2021

MB-Fit: Software infrastructure for data-driven many-body potential energy functions

Many-body potential energy functions (MB-PEFs), which integrate data-driven representations of many-body short-range quantum mechanical interactions with physics-based representations of many-body polarization and long-range interactions, have recently been shown to provide high accuracy in the description of molecular interactions from the gas to the condensed phase. Here, we present MB-Fit, a software infrastructure for the automated development of MB-PEFs for generic molecules within the TTM-nrg (Thole-type model energy) and MB-nrg (many-body energy) theoretical frameworks. Besides providing all the necessary computational tools for generating TTM-nrg and MB-nrg PEFs, MB-Fit provides a seamless interface with the MBX software, a many-body energy and force calculator for computer simulations. Given the demonstrated accuracy of the MB-PEFs, particularly within the MB-nrg framework, we believe that MB-Fit will enable routine predictive computer simulations of generic (small) molecules in the gas, liquid, and solid phases, including, but not limited to, the modeling of quantum isomeric equilibria in molecular clusters, solvation processes, molecular crystals, and phase diagrams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗