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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

SDSS-IV MaStar: Data-driven Parameter Derivation for the MaStar Stellar Library

The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) Stellar Library (MaStar) is a large collection of high-quality empirical stellar spectra designed to cover all spectral types and ideal for use in the stellar population analysis of galaxies observed in the MaNGA survey. The library contains 59,266 spectra of 24,130 unique stars with spectral resolution R ~ 1800 and covering a wavelength range of 3622–10,354 Å. In this work, we derive five physical parameters for each spectrum in the library: effective temperature (T eff ), surface gravity ($\mathrm{log} g$), metallicity ([Fe/H]), microturbulent velocity ($\mathrm{log}({v}_{\mathrm{micro}})$), and alpha-element abundance ([α/Fe]). These parameters are derived with a flexible data-driven algorithm that uses a neural network model. We train a neural network using the subset of 1675 MaStar targets that have also been observed in the Apache Point Observatory Galactic Evolution Experiment (APOGEE), adopting the independently-derived APOGEE Stellar Parameter and Chemical Abundance Pipeline parameters for this reference set. For the regions of parameter space not well represented by the APOGEE training set (7000 ≤ T ≤ 30,000 K), we supplement with theoretical model spectra. We present our derived parameters along with an analysis of the uncertainties and comparisons to other analyses from the literature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Tunneling away the relic neutrino asymmetry

The Earth acts as a matter potential for relic neutrinos which modifies their index of refraction from vacuum by δ ∼ 10 − 8 . It has been argued that the refractive effects from this potential should lead to a large O ( δ ) neutrino-antineutrino asymmetry at the surface of the Earth. This result was computed by treating the Earth as flat. In this work, we revisit this calculation in the context of a perfectly spherical Earth. We demonstrate, both numerically and through analytic arguments, that the flat-Earth result is only recovered under the condition δ 3 / 2 k R ≫ 1 , where k is the typical momentum of the relic neutrinos and R is the radius of the Earth. This condition is required to prevent antineutrinos from tunneling into classically inaccessible trajectories below the Earth’s surface and washing away the large asymmetry. As the physical parameters of the Earth do not satisfy this condition, we find that the asymmetry at the surface should only be O ( δ ) . While the asphericity of the Earth may serve as a loophole to our conclusions, we argue that it is still difficult to generate a large asymmetry even in the presence of local terrain. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Quantifying motion blur by imaging shock front propagation with broadband and narrowband X-ray sources

Time-integrated radiography using MeV Bremsstrahlung X-ray sources is the norm for imaging during system-level testing of components and structures under dynamic condition. One source of error in the analysis of the time-integrated radiography data sets stems from motion blur which smears out sharp interfaces to a greater degree with longer exposure times, which become necessary to provide sufficient signal-to-noise with low X-ray penetration of objects of interest. To quantify motion blur, a 1D shock wave through PMMA was investigated experimentally at The Dynamic Compression Sector at The Advanced Photon Source (DCS@APS) with tapered broadband and 25.46 ± 1.06 keV narrowband X-rays. Four cameras with different exposure times were used for each experiment to compare the effect that exposure time has on motion blur. In addition, our methodology to accurately simulate motion blur in terms of transmission and shape is presented and compared to our experimental results and quantified. There is a high level of agreement between the experimental and simulation results across the range of data sets investigated in this study with a percent difference range of 0.29–1.31% for the four shots. The methodology of this work serves as a steppingstone towards a physically validated model that could be used in conjunction with experimental results to deconvolve physical parameters, densities, and interfaces of interest in a way that would not be possible with experimental results alone.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

The role of toroidal rotation in the very high energy confinement quality observed in super H-mode experiments on DIII-D

In this paper, we report the key role that toroidal rotation and the related ExB shear physics played in the very high energy confinement quality (H98y2>1.5) of super H-mode experiments on DIII-D. Experiments show that the energy confinement quality decreases when toroidal rotation decreases due to the decreased externally controlled torque per particle. Meanwhile, the total pedestal pressure in the experiments remains very high during the rotation and confinement quality change. TGYRO transport modeling suggests the contribution from rotation in the ExB shear is responsible for the confinement quality in excess of standard H-mode (H98y2~1). CGYRO gyrokinetic simulations reveal the governing physics in the core plasma of super H-modes: significant up-shift of nonlinear the ITG critical gradient is observed when applying ExB shear physics in the modeling based on experimental data. The effects of other physical parameters and contribution from pedestal height, which may play minor roles in this study, are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Topologically protected Grover's oracle for the partition problem

The number partitioning problem (NPP) is one of the NP-complete (nondeterministic polynomial-time complete) computational problems. Its definite exact solution generally requires a check of all $N$ solution candidates, which is exponentially large. Here we describe a path to the fast solution of this problem in $\sqrt{N}$ quasi-adiabatic quantum annealing steps. We argue that the errors due to the finite duration of the quantum annealing can be suppressed if the annealing time scales with $N$ only logarithmically. Moreover, our adiabatic oracle is topologically protected, in the sense that it is robust against small uncertainty and slow time dependence of the physical parameters or the choice of the annealing protocol. In conclusion, we also argue that our approach can solve many other famous NP-complete computational problems in $\sqrt{N}$ steps.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A statistical analysis of the COHERENT data and applications to new physics

The observation of coherent elastic neutrino nucleus scattering (CEvNS) by the COHERENT collaboration in 2017 has opened a new window to both test Standard Model predictions at relatively low energies and probe new physics scenarios. Our investigations show, however, that a careful treatment of the statistical methods used to analyze the data is essential to derive correct constraints and bounds on new physics parameters. In this manuscript we perform a detailed analysis of the publicly available COHERENT CsI data making use of all available background data. We point out that Wilks’ theorem is not fulfilled in general and a calculation of the confidence regions via Monte Carlo simulations following a Feldman-Cousins procedure is necessary. As an example for the necessity of this approach to test new physics scenarios we quantify the allowed ranges for several scenarios with neutrino non-standard interactions. Furthermore, we provide accompanying code to enable an easy implementation of other new physics scenarios as well as data files of our results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Physical discovery in representation learning via conditioning on prior knowledge

Recent advances in electron, scanning probe, optical, and chemical imaging and spectroscopy yield bespoke data sets containing the information of structure and functionality of complex systems. In many cases, the resulting data sets are underpinned by low-dimensional simple representations encoding the factors of variability within the data. The representation learning methods seek to discover these factors of variability, ideally further connecting them with relevant physical mechanisms. However, generally, the task of identifying the latent variables corresponding to actual physical mechanisms is extremely complex. Here, we present an empirical study of an approach based on conditioning the data on the known (continuous) physical parameters and systematically compare it with the previously introduced approach based on the invariant variational autoencoders. The conditional variational autoencoder (cVAE) approach does not rely on the existence of the invariant transforms and hence allows for much greater flexibility and applicability. Interestingly, cVAE allows for limited extrapolation outside of the original domain of the conditional variable. However, this extrapolation is limited compared to the cases when true physical mechanisms are known, and the physical factor of variability can be disentangled in full. We further show that introducing the known conditioning results in the simplification of the latent distribution if the conditioning vector is correlated with the factor of variability in the data, thus allowing us to separate relevant physical factors. We initially demonstrate this approach using 1D and 2D examples on a synthetic data set and then extend it to the analysis of experimental data on ferroelectric domain dynamics visualized via piezoresponse force microscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Plausible indication of gamma-ray absorption by dark matter in NGC 1068

NGC 1068 is the brightest extragalactic source in high-energy neutrinos as seen by IceCube, yet the accompanying gamma-ray flux is orders of magnitude weaker. It has been argued that this indicates that the bulk of neutrinos and gamma rays are emitted in the innermost vicinity of the central supermassive black hole, which is transparent to neutrinos, but opaque to gamma rays. Even in such extreme scenarios for the acceleration of cosmic rays, astrophysical models typically overestimate the low-energy gamma-ray flux and/or require some fine-tuning in the physical parameters. Here, in this work, we suggest instead that the dark matter surrounding the supermassive black hole may absorb the gamma rays, inducing the observed deficit. We show that for a dark matter–photon scattering cross section in the range σ DM−γ /m DM ≃ 10 −28 −10 −30 cm 2 /GeV, Fermi-LAT measurements can be well reconciled with IceCube data. We also present some simple particle physics examples that achieve the correct spectral energy dependence while respecting complementary constraints.

Active Galactic Nuclei↗
DOE OSTI2025

Tables of Neutron Thermal Cross Sections, Westcott Factors, Resonance Integrals, Maxwellian Averaged Cross Sections, Astrophysical Reaction Rates, and r-process Abundances Calculated from the ENDF/B-VIII.1, JEFF-3.3, JENDL-5.0, BROND-3.1, and CENDL-3.2 Evaluated Data Libraries

We present calculations of neutron thermal cross sections, Westcott factors, resonance integrals, Maxwellian-averaged cross sections, astrophysical reaction rates, and solar system r-process abundances using the latest data from the major evaluated nuclear libraries for 849 ENDF target materials. The recent release of ENDF/B-VIII.1 library, progress in 252 Cf(SF) evaluation, extensive analysis of newly-evaluated neutron reaction cross sections, neutron covariances, and improvements in data processing techniques motivated us to calculate the nuclear industry and neutron physics parameters, produce s-process Maxwellian-averaged cross sections and astrophysical reaction rates, extract r-process abundances, systematically calculate uncertainties, and provide additional insights on currently available neutron-induced reaction data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Constraining high-energy neutrinos from tidal disruption events with IceCube high-energy starting events

Tidal disruption events (TDEs) have been proposed as candidate sources of high-energy neutrinos. Successful and choked jets, as well as the accretion disk, corona, wind, and outflow regions in a TDE have been examined and shown to produce TeV - PeV neutrinos. In this work, we use the IceCube 12.5 year high energy starting events (HESE) dataset and perform a maximum likelihood analysis to investigate the spatial and temporal correlations between HESE dataset and a selected sample of 89 TDEs. Our results indicate that the currently observed data do not show any significant correlation and hence is consistent with the background only hypothesis. Using this result, we place constraints on the fraction of TDEs harboring intrinsic jets ($f_{\rm jet}$) and the corresponding isotropic-equivalent cosmic ray (CR) energy ($\mathcal{E}_{\rm CR}$). We note that even with limited statistics, we can constrain the parameter space as $\mathcal{E}_{\rm CR} \lesssim 3 \times 10^{53}$ erg for $f_{\rm jet} \gtrsim 0.6$ at more than 90% C.L. Finally, we discuss the theoretical implications of our results and the limits on the all-sky diffuse neutrino flux from TDEs. With more observational data in the electromagnetic band for TDEs and neutrino observations from IceCube and KM3NeT, our analysis can be used to place stringent constraints on physical parameters associated with TDEs.

Mukhopadhyay, Mainak [Fermilab; Chicago U., KICP; ↗
DOE OSTI2023

Eco-PiNN: A Physics-informed Neural Network for Eco-toll Estimation

The eco-toll estimation problem quantifies the expected environmental cost (e.g., energy consumption, exhaust emissions) for a vehicle to travel along a path. This problem is important for societal applications such as eco-routing, which aims to find paths with the lowest exhaust emissions or energy need. The challenges of this problem are threefold: (1) the dependence of a vehicle's eco-toll on its physical parameters; (2) the lack of access to data with eco-toll information; and (3) the influence of contextual information (i.e. the connections of adjacent segments in the path) on the eco-toll of road segments. Prior work on eco-toll estimation has mostly relied on pure data-driven approaches and has high estimation errors given the limited training data. To address these limitations, we propose a novel Eco-toll estimation Physics-informed Neural Network framework (Eco-PiNN) using three novel ideas, namely, (1) a physics-informed decoder that integrates the physical laws governing vehicle dynamics into the network, (2) an attention-based contextual information encoder, and (3) a physics-informed regularization to reduce overfitting. Experiments on real-world heavy-duty truck data show that the proposed method can greatly improve the accuracy of eco-toll estimation compared with state-of-the-art methods.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2026

Evidence for $CP$ violation and measurement of $CP$-violating parameters in B$^0_\mathrm{s}$ $\to$ J/$\psi\,\phi$(1020) decays in pp collisions at $\sqrt{s} =$ 13 TeV

A pioneering machine-learning-based flavor-tagging algorithm combining same-side and opposite-side tagging is used to obtain the equivalent of 27$\,$000 tagged B$^0_\mathrm{s}$$\to$ J/$\psi\, \phi$(1020) decays from pp collisions at $\sqrt{s} =$ 13 TeV, collected by the CMS experiment and corresponding to an integrated luminosity of 96.5 fb$^{-1}$. A time- and flavor-dependent angular analysis of the $\mu^+\mu^-$K$^+$K$^-$ final state is used to measure parameters of the $\mathrm{B}^0_\mathrm{s}$-$\overline{\mathrm{B}}^0_\mathrm{s}$ system. The weak phase is measured to be $\phi_\mathrm{s}$ = $-$73 $\pm$ 23 (stat) $\pm$ 7 (syst) mrad, which, combined with a $\sqrt{s}$ = 8 TeV CMS result, gives $\phi_\mathrm{s}$ = $-$74 $\pm$ 23 mrad. This value differs from zero by 3.2 standard deviations, providing evidence for $CP$ violation in B$^0_\mathrm{s}$$\to$ J/$\psi\,\phi$(1020) decays. All measured physics parameters are found to agree with standard model predictions where available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Bayesian estimation of the $S$ factor and thermonuclear reaction rate for 16 O(p, γ) 17 F

The 16 O(p, γ) 17 F reaction is the slowest hydrogen-burning process in the CNO mass region. Its thermonuclear rate sensitively impacts predictions of oxygen isotopic ratios in a number of astrophysical sites, including AGB stars. The reaction has been measured several times at low bombarding energies using a variety of techniques. The most recent evaluated experimental rates have a reported uncertainty of about 7.5% below 1 GK. However, the previous rate estimate represents a best guess only and was not based on rigorous statistical methods. We apply a Bayesian model to fit all reliable 16 O(p, γ) 17 F cross section data, and take into account independent contributions of statistical and systematic uncertainties. The nuclear reaction model employed is a single-particle potential model involving a Woods-Saxon potential for generating the radial bound state wave function. The model has three physical parameters, the radius and diffuseness of the Woods-Saxon potential, and the asymptotic normalization coefficients (ANCs) of the final bound state in 17 F. Here, we find that performing the Bayesian S -factor fit using ANCs as scaling parameters has a distinct advantage over adopting spectroscopic factors instead. Based on these results, we present the first statistically rigorous estimation of experimental 16 O(p, γ) 17 F reaction rates, with uncertainties (±4.2%) of about half the previously reported values.

6 ≤ A ≤ 19↗
DOE OSTI2023

High-redshift quasars along the main sequence

The 4D Eigenvector 1 empirical formalism (4DE1) and its main sequence (MS) for quasars has emerged as a powerful tool for organising the diversity among quasar populations, as several key observational measures and physical parameters are systematically changing along it. Trends revealed by 4DE1 are very well established to explain all the diverse characteristics seen in low-redshift quasar samples. Nevertheless, the situation is far less clear when dealing with high-luminosity and high-redshift sources. Here, we aim to evaluate the behaviour of our sample of 22 quasars at high redshift (2.2 ≤ z ≤ 3.7) and high luminosity (47.39 ≤ L bol ≤ 48.36) in the context of the 4DE1. Our approach involves studying quasar physics through a spectroscopic exploration of UV and optical emission line diagnostics. We used new observations from the ISAAC instrument at ESO-VLT and primarily from the SDSS to cover the optical and the UV rest-frames, respectively. The emission lines were characterised both via a quantitative parametrisation of the line profiles and a decomposition of the emission line profiles using multicomponent fitting routines. We provide spectrophotometric properties and line profile measurements for Hβ+[O III]λλ4959,5007, as well as Si IVλ1397+O IV]λ1402, C IVλ1549+He IIλ1640, and the 1900 Å blend (including Al IIIλ1860, Si III]λ1892, and C III]λ1909). For six out of the 22 objects, a significantly blueshifted component on the Hβ profile is present. In 14 out of 22 cases, an Hβ outflowing component associated with [O III] is detected. The majority of [O III]λλ4959,5007 emission line profiles show blueshifted velocities higher than 250 km s -1 . We find extremely broad [O III]λλ4959,5007 emission that is comparable to the width of Hβ broad profile in some highly accreting quasars. The [O III]λλ4959,5007 and C IVλ1549 blueshifts show very high amplitudes and a high degree of correlation. The line widths and shifts are correlated for both [O III]λλ4959,5007 and C IVλ1549, suggesting that emission from outflowing gas is providing a substantial broadening effect to both lines. Otherwise, the links between C IVλ1549 centroid velocity at half intensity (c(1/2)), Eddington ratio (L/L Edd ), and bolometric luminosity are found to be in agreement with previous studies of high-luminosity quasars. Our analysis suggests that the behaviour of quasars of very high luminosity all along the main sequence is strongly affected by powerful outflows involving a broad range of spatial scales. The main sequence correlations remain valid at high redshift and high luminosity even if a systematic increase in line width is observed. Scaling laws based on UV Al IIIλ1860 and Hβ emission lines are equally reliable estimators of M BH .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Atomic Diffusivities of Yttrium, Titanium and Oxygen Calculated by Ab Initio Molecular Dynamics in Molten 316L Oxide-Dispersion-Strengthened Steel Fabricated via Additive Manufacturing

Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing steps required. Additive manufacturing (AM) can directly incorporate dispersion elements (e.g., Y, Ti and O) during component fabrication, thus bypassing the need for an ODS steel supply chain, the scale-up challenges of powder processing routes, the buoyancy challenges associated with casting ODS steels, and the joining issues for net-shape component fabrication. In the AM process, the diffusion of the dispersion elements in the molten steel plays a key role in the precipitation of the oxide particles, thereby influencing the microstructure, thermal stability and high-temperature mechanical properties of the resulting ODS steels. In this work, the atomic diffusivities of Y, Ti, and O in molten 316L stainless steel (SS) as functions of temperature are determined by ab initio molecular dynamics simulations. The latest Vienna Ab initio Simulation Package (VASP) package that incorporates an on-the-fly machine learning force field for accelerated computation is used. At a constant temperature, the time-dependent coordinates of the target atoms in the molten 316L SS were analyzed in the form of mean square displacement in order to obtain diffusivity. The values of the diffusivity at multiple temperatures are then fitted to the Arrhenius form to determine the activation energy and the pre-exponential factor. Given the challenges in experimental measurement of atomic diffusivity at such high temperatures and correspondingly the lack of experimental data, this study provides important physical parameters for future modeling of the oxide precipitation kinetics during AM process.

Chemistry↗
DOE OSTI2025

Are light curve classification metrics good proxies for SN Ia cosmological constraining power?

Context. When selecting a light curve classifier for use as part of a photometric supernova Ia (SN Ia) cosmological analysis, it is common to make decisions based on metrics of classification performance, such as the contamination within the photometrically classified SN Ia sample, rather than a measure of cosmological constraining power. If the former is an appropriate proxy for the latter, this practice would eliminate the computational expense of a full cosmology forecast in the analysis pipeline design process. Aims. This study tests the assumption that light curve classification metrics are an appropriate proxy for cosmology metrics. Methods. We emulated photometric SN Ia cosmology light curve samples with controlled contamination rates of individual contaminant classes and evaluated each of them under a set of classification metrics. We then derived cosmological parameter constraints from all samples under two common analysis approaches and quantified the impact of contamination by each contaminant class on the resulting cosmological parameter estimates. Results. We observe that cosmology metrics are sensitive to both the contamination rate and the class of the contaminating population, whereas the classification metrics are shown to be insensitive to the latter. Conclusions. Based on these findings, we discourage any exclusive reliance on light curve classification-based metrics for analysis design decisions, which (counterintuitively) include but are not limited to the classifier choice. Instead, we recommend optimising science analysis pipeline design choices using a metric of the information gained about the physical parameters of interest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Derivation of physical equations for high-speed laser welding using large language models

It is challenging to formulate complex physical phenomena that occur in a manufacturing process, particularly when the available data are limited, rendering conventional data-driven approaches ineffective. This study aims to predict humping onset in high-speed laser welding by introducing a novel framework, namely text-to-equations generative pre-trained transformer (T2EGPT). This method leverages the capabilities of large language models (LLMs), in combination with sparse experimental data and enriched literature data, to derive an interpretable and generalizable equation for predicting humping initiation. By capturing key correlations among physical parameters, T2EGPT generates a compact and dimensionless expression that accurately predicts hump formation. The equation reveals that humping arises from the interplay between inertia-driven backward melt flow and capillary-driven surface stabilization, where inertial forces drive molten metal backward and capillary forces resist surface deformation. Furthermore, compared to traditional data-driven models, T2EGPT demonstrates enhanced predictive accuracy and cross-material transferability. More broadly, this study highlights the potential of LLMs to integrate textual information with data-driven discovery, enabling the extraction of physical laws in data-scarce scientific domains.

36 MATERIALS SCIENCE↗