SEARCH · Engineering Papers

Results for “directional data”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

All sources NASA NTRS DOE OSTI

DOE OSTI2024

On the accuracy of compressibility transformations

This study highlights the importance of satisfying the eddy viscosity equivalence below the logarithmic layer, to deriving accurate compressibility transformations. First, we analyze the ability of known transformations to satisfy the eddy viscosity equivalence and show that the accuracy of these transformations is strongly dependent on this ability. Second, in a step-by-step manner, we devise new transformations that satisfy this hypothesis. An approach based on curve fitting of the incompressible Direct Numerical Simulation data for eddy viscosity profiles below the logarithmic layer provides an extremely accurate transformation, which motivates self-contained methods, making use of mixing length formulas in the inner region. It is shown that the accuracy of existing transformations can be significantly improved by applying these ideas, below the logarithmic layer. Motivated by the effectiveness of the formulations derived from eddy viscosity equivalence, we introduce a new integral transformation based on Reynolds number equivalence between compressible and incompressible flows. This approach is based on defining a new compressible velocity scale, which affects the accuracy of transformations. Several choices for the velocity scale are tested, and in each attempt, it is shown that the eddy viscosity equivalence plays a very important role for the accuracy of compressibility transformations.

42 ENGINEERING↗

DOE OSTI2026

AI-supported mini-labs: combining smartphone-based experiments and multimodal AI

Multimedia learning has always been a topic in physics education—whether through specialized digital data acquisition systems, simulations, or animations. Due to increasing digitalization, more and more media from our everyday lives have also found their way into education in recent decades. This contribution introduces a conceptual framework and illustrative examples for AI-supported experimentation in physics education. It does not yet present empirical data but outlines directions for forthcoming classroom studies evaluating learning outcomes and engagement.

generative AI↗

DOE OSTI2024

Machine learning aided line intensity ratio method for helium–hydrogen mixed recombining plasmas

The helium line intensity ratio (LIR) with the help of a collisional radiative (CR) model has long been used to measure the electron density, n e , and temperature, T e , and its potential and limitations for fusion applications have been discussed. However, it has been reported that the CR model approach leads to deviations in helium–hydrogen mixed plasmas and/or recombining plasmas. In this study, a machine learning (ML) aided LIR method is used to measure n e and T e from spectroscopic data of helium–hydrogen mixed recombining plasmas in the divertor simulator Magnum-PSI. To analyze mixed plasmas, which have more complex spectral shapes, the spectroscopy data were used directly for training instead of separating the intensities of each line. Finally, it is shown that the ML approach can provide a robust and simpler analysis method to deduce n e and T e from the visible emissions in helium–hydrogen mixed plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Applying simulation-based inference to spectral and spatial information from the Galactic Center gamma-ray excess

Abstract The two most favored explanations of theFermiGalactic Center gamma-ray excess (GCE) are millisecond pulsars and self annihilation of the smooth dark matter halo of the galaxy. In order to distinguish between these possibilities, we would like to optimally use all information in the available data, including photon direction and energy information.To date, analyses of the GCE have generally treated directional and energy information separately, or have ignored one or the other completely.Here, we develop a method for analyzing the GCE that relies on simulation-basedinference with neural posterior models to jointly analyze photon directional and spectral information while correctly accounting for the spatial and energy resolution of the telescope, here assumed to be theFermiLarge Area Telescope (LAT).Our results also have implications for analyses of the diffuse gamma-ray background, which we discuss.

Astronomy & Astrophysics↗

DOE OSTI2020

Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques

Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The identification performances of a variety of algorithms are characterized in simulated events and directly compared with data. The algorithms are validated using proton-proton collision data at $\sqrt{s}$ = 13TeV, corresponding to an integrated luminosity of 35.9 fb -1 . Systematic uncertainties are assessed by comparing the results obtained using simulation and collision data. The new techniques studied in this paper provide significant performance improvements over non-ML techniques, reducing the background rate by up to an order of magnitude at the same signal efficiency.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Is tokenization needed for masked particle modeling?

In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets relevant to developing foundation models for high-energy physics. In MPM, a model is trained to recover the missing elements of a set, a learning objective that requires no labels and can be applied directly to experimental data. We achieve significant performance improvements over previous work on MPM by addressing inefficiencies in the implementation and incorporating a more powerful decoder. We compare several pre-training tasks and introduce new reconstruction methods that utilize conditional generative models without data tokenization or discretization. We show that these new methods outperform the tokenized learning objective from the original MPM on a new test bed for foundation models for jets, which includes using a wide variety of downstream tasks relevant to jet physics, such as classification, secondary vertex finding, and track identification.

conditional generative models↗

DOE OSTI2021

Probing the hadronic nature of the gamma-ray emission associated with Westerlund 2

ABSTRACT Star-forming regions have been proposed as potential Galactic cosmic ray accelerators for decades. Cosmic ray acceleration can be probed through observations of gamma-rays produced in inelastic proton–proton collisions at GeV and TeV energies. In this paper, we analyse more than 11 yr of Fermi–LAT data from the direction of Westerlund 2, one of the most massive and best-studied star-forming regions in our Galaxy. In particular, we investigate the characteristics of the bright pulsar PSR J1023–5746 that dominates the gamma-ray emission below a few GeV at the position of Westerlund 2 and the underlying extended source FGES J1023.3–5747. The analysis results in a clear identification of FGES J1023.3–5747 as the GeV counterpart of the TeV source HESS J1023-575, through its morphological and spectral properties. This identification provides new clues about the origin of the HESS J1023-575 gamma-ray emission, favouring a hadronic origin of the emission, powered by Westerlund 2, rather than a leptonic origin related to either the pulsar wind nebula associated with PSR J1023–5746 or the cluster itself. This result indirectly supports the hypothesis that star-forming regions can contribute to the cosmic ray sea observed in our Galaxy.

Mestre, Enrique↗

DOE OSTI2021

Evidence for a high-energy tail in the gamma-ray spectra of globular clusters

Millisecond pulsars are very likely the main source of gamma-ray emission from globular clusters. However, the relative contributions of two separate emission processes – curvature radiation from millisecond pulsar magnetospheres versus inverse Compton emission from relativistic pairs launched into the globular cluster environment by millisecond pulsars – have long been unclear. To address this, we search for evidence of inverse Compton emission in 8-yr Fermi–LAT data from the directions of 157 Milky Way globular clusters. We find a mildly statistically significant (3.8σ) correlation between the measured globular cluster gamma-ray luminosities and their photon field energy densities. However, this may also be explained by a hidden correlation between the photon field densities and the stellar encounter rates of globular clusters. Analysed in toto, we demonstrate that the gamma-ray emission of globular clusters can be resolved spectrally into two components: (i) an exponentially cut-off power law and (ii) a pure power law. The latter component – which we uncover at a significance of 8.2σ – has a power index of 2.79 ± 0.25. It is most naturally interpreted as inverse Compton emission by cosmic-ray electrons and positrons injected by millisecond pulsars. Here, we find the luminosity of this power-law component is comparable to, or slightly smaller than, the luminosity of the curved component, suggesting the fraction of millisecond pulsar spin-down luminosity into relativistic leptons is similar to the fraction of the spin-down luminosity into prompt magnetospheric radiation.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Cold gas mass measurements for the era of large optical spectroscopic surveys

ABSTRACT Gas plays an important role in many processes in galaxy formation and evolution, but quantifying the importance of gas has been hindered by the challenge to measure gas masses for large samples of galaxies. Data sets of direct atomic and molecular gas measurements are sufficient to establish simple scaling relations, but often not large enough to quantify three-parameter relations, or second-order dependences. As an alternative approach, we derive here indirect cold gas measurements from optical emission lines using photoionization models for galaxies in the Sloan Digital Sky Survey (SDSS) main galaxy sample and the PHANGS-MUSE survey. We calibrate the gas surface density measurements using xCOLD GASS and PHANGS-ALMA molecular gas measurements to ensure that our measurements are reliable. We demonstrate the importance of taking into account the scale dependence of the relation between optical depth (τ V ) and gas surface density (Σ gas ) and provide a general prescription to estimate Σ gas from τ V , metallicity, and the dust-to-metal ratio, at any arbitrary physical resolution. To demonstrate that the indirect cold gas masses are accurate enough to quantify the role of gas in galaxy evolution, we study the mass–metallicity relation of SDSS galaxies and show that as a third parameter gas mass is better than star formation rate at reducing the scatter of the relation, as predicted by models and simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Lattice calculation of short-range contributions to neutrinoless double-beta decay 𝜋 − → 𝜋 + ⁢𝑒⁢𝑒 at physical pion mass

Neutrinoless double-beta (0⁢𝜈⁢𝛽⁢𝛽) decays provide an excellent probe for determining whether neutrinos are Dirac or Majorana fermions. The short-range matrix elements associated with the 𝜋 − → 𝜋 + ⁢𝑒⁢𝑒 process contribute at leading order in the 0⁢𝜈⁢𝛽⁢𝛽 decay channel 𝑛⁢𝑛 → 𝑝⁢𝑝⁢𝑒⁢𝑒 through pion exchange between nucleons. However, current lattice calculations show notable discrepancies in predicting these short-range contributions. To address this issue, we perform a lattice QCD calculation of the 𝜋 − → 𝜋 + ⁢𝑒⁢𝑒 matrix elements using domain wall fermion ensembles at the physical pion mass generated by the RBC/UKQCD Collaboration. To mitigate contamination from around-the-world effects, we develop a new method to reconstruct and subtract them directly from lattice data. We then perform nonperturbative renormalization in the regularization-independent symmetric momentum-subtraction scheme (RI/SMOM), using the (𝛾 𝜇 , 𝛾 𝜇 ) and ($\not{𝑞}$, $\not{𝑞}$) projectors. Compared with previous studies, this work reduces the uncertainties in the matrix elements and provides an independent cross-check that helps to reconcile the discrepancies among previous lattice calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Fluorescence-mediated postcollision interaction in x-ray photoionization of the Xe 𝐾 edge

Postcollision interaction (PCI) in near-threshold photoionization of the K shell of atomic Xe is investigated with hard-x-ray synchrotron radiation. Applying Auger electron spectroscopy, line-shape distortion is monitored in the K-L 2 → L 2 M 4,5 M 4,5 decay channel, where the initial K-L 2 (Kα 2 ) x-ray-emission step mediates the emission of the two continuum electrons. The K-edge result is compared to similar data obtained on direct L 2 M 4,5 M 4,5 decay at the L 2 edge without x-ray-emission. In conclusion, it is found that the evolution of the PCI shift with excess photon energy is very similar at both edges, but a subtle decrease in the PCI shift is observable at the K edge due to the effect of the ultrafast x-ray emission step delaying the PCI energy exchange by a few attoseconds.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

Machine learning the electronic structure of matter across temperatures

Here, we introduce machine learning (ML) models that predict the electronic structure of materials across a wide temperature range. Our models employ neural networks and are trained on density functional theory (DFT) data. Unlike most other ML models that use DFT data, our models directly predict the local density of states (LDOS) of the electronic structure. This provides several advantages, including access to multiple observables such as the electronic density and electronic total free energy. Moreover, our models account for both the electronic and ionic temperatures independently, making them ideal for applications like laser heating of matter. We validate the efficacy of our LDOS-based models on a metallic test system. They accurately capture energetic effects induced by variations in ionic and electronic temperatures over a broad temperature range, even when trained on a subset of these temperatures. These findings open up exciting opportunities for investigating the electronic structure of materials under both ambient and extreme conditions.

Fiedler, Lenz↗

DOE OSTI2024

Fractionalized excitations probed by ultrasound

In this work, we study magnetoelastic interactions by means of ultrasound experiments in 𝛼−RuCl 3 —a prototypical material for the Kitaev spin model on the honeycomb lattice, with a possible spin-liquid state featuring Majorana fermions and ℤ 2 -flux excitations. We present results of the temperature and in-plane magnetic-field dependence of the sound velocity and sound attenuation for several longitudinal and transverse phonon modes propagating along high-symmetry crystallographic directions. A comprehensive data analysis above the magnetically ordered state provides strong evidence of phonon scattering by Majorana fermions. This scattering depends sensitively on the value of the phonon velocities relative to the characteristic velocity of the low-energy fermionic excitations describing the spin dynamics of the underlying Kitaev magnet. Moreover, our data displays a distinct reduction of anisotropy of the sound attenuation, consistent with the presence of thermally excited ℤ 2 visons. Here, we demonstrate the potential of phonon dynamics as a promising probe for uncovering fractionalized excitations in 𝛼−RuCl 3 and provide new insights into the 𝐻−𝑇 phase diagram of this material.

Kitaev magnet↗

DOE OSTI2021

Reconstructing quintessence

We present an Effective Field Theory based reconstruction of quintessence models of dark energy directly from cosmological data. We show that current cosmological data possess enough constraining power to test several quintessence model properties for redshifts z ϵ [0, 1.5] with no assumptions about the behavior of the scalar field potential. We use measurements of the cosmic microwave background, supernovae distances, and the clustering and lensing of galaxies to constrain the evolution of the dark energy equation of state, Swampland Conjectures, the shape of the scalar field reconstructed potential, and the structure of its phase space. The standard cosmological model still remains favored by data and, within quintessence models, deviations from its expansion history are bounded to be below the 10% level at 95% confidence at any redshift below z = 1.5.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Internal energy balance and aerodynamic heating predictions for hypersonic turbulent boundary layers

The elemental equation governing heat transfer in aerodynamic flows is the internal energy equation. For a boundary layer flow, a double integration of the Reynolds-averaged form of this equation provides an expression of the wall heat flux in terms of the integrated effects, over the boundary layer, of various physical processes: turbulent dissipation, mean dissipation, turbulent heat flux, etc. Recently available direct numerical simulation data for a Mach 11 cold-wall turbulent boundary layer allows a comparison of the exact contributions of these terms in the energy equation to the wall heat flux with their counterparts modeled in the Reynolds-averaged Navier-Stokes (RANS) framework. Various approximations involved in RANS, both closure models as well as approximations involved in adapting incompressible RANS models to a compressible form, are assessed through examination of the internal energy balance. There are a number of potentially problematic assumptions and terms identified through this analysis. Here, the effect of compressibility corrections of the dilatational dissipation type is explored, as is the role of the modeled turbulent dissipation, in the context of wall heat flux predictions. The results indicate several potential avenues for RANS model improvement for hypersonic cold-wall boundary-layer flows.

42 ENGINEERING↗

DOE OSTI2025

Neutrino and gamma-ray emissions from NGC 1068

IceCube has recently reported the detection of ∼1–10 TeV neutrinos from the nearby active galaxy, NGC 1068. The lack of TeV-scale emission from this source suggests that these neutrinos are generated in the dense corona that surrounds NGC 1068’s supermassive black hole. In this paper, we present a physical model for this source, including the processes of pair production, pion production, synchrotron, and inverse Compton scattering. We have also performed a new analysis of Fermi-LAT data from the direction of NGC 1068, finding that the gamma-ray emission from this source is very soft but bright at energies below ∼1 GeV . Our model can predict a gamma-ray spectrum that is consistent with Fermi-LAT observations when the magnetic field within the corona of this active galactic nucleus (AGN) is quite high, namely 𝐵 ≳6 kG . To explain the observed neutrino emission, this source must accelerate protons with a total power that is comparable to its intrinsic x-ray luminosity. In this context, we consider two additional nearby active galaxies, NGC 4151 and NGC 3079, which have been identified as promising targets for IceCube.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources

Applications which fuse machine learning and simulation are rarely best served by a single computing resource. Highly parallel simulation codes are best deployed on super- computers, while AI tasks used to decide which simulations to perform may be best suited to specialized accelerators. Here we present a Function-as-a-Service (FaaS) system for executing complex, distributed computational campaigns that achieves performance parity with conventional workflow systems without the complexities of secure network connections between compute providers. One innovation enabling high performance is a subsystem that directly moves task data between sites, separate from the cloud-hosted FaaS system used to distribute task instructions. We also introduce a flexible scheduling system that allows us access factor of 2 trade offs between the amount of resources required to solve a problem at each compute site. We anticipate that this system will upgrade multi-site applications from demonstration projects to routine practice in computational science.

Ward, Logan↗

DOE OSTI2023

Glass Additive and Subtractive Manufacturing of a Fiber Optic Rotary Encoder for Downhole Pressure Sensing

This article presents a fiber optic rotary encoder-based pressure sensor for downhole applications. The rotary encoder, which is composed of an encoding pad and an all-glass optical fiber sensing head, converts the rotation angles of a pressure transducer to digital codes. The optical fiber only serves as the telemetry channel to directly transmit the data in digital format such that the environmental temperature influence and the long-time drift are minimized. The glass additive and subtractive manufacturing (ASM) techniques are used to embed the multichannel optical fibers into a bulk-fused silica glass substrate. Because the fused silica glass shares a similar material property to the optical fiber (e.g., thermal expansion coefficient), the optical fiber sensing head is well sealed and fixed even at an elevated temperature. The picosecond laser blackening technique is used to fabricate the high reflectivity contrast encoding pad with high accuracy. Here, the proposed pressure sensor was manufactured and experimentally verified to have a signal-to-noise ratio (SNR) of 23 dB and a linear pressure response with a root-mean-square error (RMSE) of 0.37. During the 400-h 250 °C long-term stability test, there was no digital code variation. In addition, a mathematical model to study the relationships between the sensor’s performances and design parameters was established. According to the model, a 12-bit encoder (0.02% pressure sensitivity) can be achieved with a radius of 20 mm.

02 PETROLEUM↗