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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

The Auroral Particles experiment

An instrument for the detection of particles in the energy range of 0.1 ev to 80 Kev was designed, built, tested, calibrated, and flown onboard the spacecraft ATS-6. Data from this instrument generated the following research: intensive studies of the plasma in the vicinity of the spacecraft; global variations of plasmas; correlative studies using either other spacecraft or ground based measurements; and studies of spacecraft interactions with ambient plasmas including charging, local electric fields due to differential charging, and active control of spacecraft potential. Results from this research are presented.

Source record↗
NASA NTRS1982

Conference on Complex Turbulent Flows: Comparison of Computation and Experiment, Stanford University, Stanford, CA, September 14-18, 1981, Proceedings. Volume 2 - Taxonomies, reporters' summaries, evaluation, and conclusions

Computational techniques for simulating turbulent flows were explored, together with the results of experimental investigations. Particular attention was devoted to the possibility of defining a universal closure model, applicable for all turbulence situations; however, conclusions were drawn that zonal models, describing localized structures, were the most promising techniques to date. The taxonomy of turbulent flows was summarized, as were algebraic, differential, integral, and partial differential methods for numerical depiction of turbulent flows. Numerous comparisons of theoretically predicted and experimentally obtained data for wall pressure distributions, velocity profiles, turbulent kinetic energy profiles, Reynolds shear stress profiles, and flows around transonic airfoils were presented. Simplifying techniques for reducing the necessary computational time for modeling complex flowfields were surveyed, together with the industrial requirements and applications of computational fluid dynamics techniques.

Kline, S. J.↗
DOE OSTI2020

Measurement of top quark pair production in association with a Z boson in proton-proton collisions at s$$ \sqrt{\mathrm{s}} $$ = 13 TeV

A measurement of the inclusive cross section of top quark pair production in association with a Z boson using proton-proton collisions at a center-of-mass energy of 13 TeV at the LHC is performed. The data sample corresponds to an integrated luminosity of 77.5 fb$^{-1}$, collected by the CMS experiment during 2016 and 2017. The measurement is performed using final states containing three or four charged leptons (electrons or muons), and the Z boson is detected through its decay to an oppositely charged lepton pair. The production cross section is measured to be σ($ \mathrm{t}\overline{\mathrm{t}}\mathrm{Z} $) = 0.95 ± 0.05 (stat) ± 0.06 (syst) pb. For the first time, differential cross sections are measured as functions of the transverse momentum of the Z boson and the angular distribution of the negatively charged lepton from the Z boson decay. The most stringent direct limits to date on the anomalous couplings of the top quark to the Z boson are presented, including constraints on the Wilson coefficients in the framework of the standard model effective field theory.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Effect of Pressure and Oxidation State on Pnictogen Metal-Silicate Partitioning

The partitioning of trace elements between metal and silicate melts serves as the foundation for understanding the differentiation of a planetary body into a metallic core and silicate mantle. Element activity influences metal-silicate partitioning behavior. Activity coefficients are directly dependent on composition and temperature, and can be indirectly dependent on oxygen fugacity and pressure. Distinguishing the effect of pressure from other variables on the activity coefficients and partitioning is important for understanding the chemical evolution of different planetary bodies during differentiation. In this study, we investigated the influence of pressure on the activity coefficients of Cu, Mo, Pd, Pt, As, Sb, and Bi in Fe-Si metallic liquids. All of these elements exhibit moderate to high activity coefficients in Fe-Si liquids at low pressure, which significantly controls their metal-silicate partitioning behavior. Identifying whether this strong dependence persists at higher pressures is critical to modeling and understanding the chemical consequences of core formation. New experiments at 10 GPa were used to derive activity coefficients for these metals which can be compared to activity coefficients determined at 1 GPa. Experiments were conducted at 10 GPa and 2373K using a 10/5 assembly in the 880-ton multi anvil press at NASA Johnson Space Center. The standard 10/5 COMPRES assembly was slightly modified to accommodate a sample capsule machined from single-crystal MgO that minimizes melt percolation out of the sample volume during the experiment. Experiment starting materials were comprised of 70 wt.% Knippa basalt and 30 wt.% metal. The metal mixture (~85 wt.% Fe) was created by adding the elements of interest (Cu, Mo, Pd, Pt, As, Sb, Bi) to Fe metal powder. Varied amounts of Si metal (0-10 wt.% Si) were added to the metal-silicate mixtures to generate a systematic series of starting materials. For each element, an epsilon interaction parameter in Fe-Si liquid was derived from the results of our 0-10 wt.% Si metal series. To investigate whether pressure influences the trace element activity coefficients in the 1-10 GPa pressure range, we compared our results at 10 GPa to those at 1-4 GPa [1-3]. Our results can also be directly compared to interaction parameters for Au, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb previously determined at 10 GPa and 2373K following the same methods [4]. Combined, this suite of interaction parameters will directly inform metal- silicate partitioning between 1 and 10 GPa, and assess whether these values can be extrapolated to modeling differentiation processes at pressures >10 GPa. [1] Righter et al. (2018) GCA 232, 101-123 [2] Righter et al. (2019) MaPS 54, 1379-1394 [3] Steenstra et al. (2020) Icarus, 335, 113391 [4] Righter et al. (2020) Geochem. Persp. Let. 15, 44-49

Kelsey Prissel↗
NASA NTRSDate not supplied

Effect of Pressure on Trace Element Activity Coefficients in Metal-Silicate Systems

The partitioning of trace elements between metal and silicate melts serves as the foundation for understanding the differentiation of a planetary body into a metallic core and silicate mantle. Element activity influences metal-silicate partitioning behavior. Activity coefficients are directly dependent on composition and temperature, and can be indirectly dependent on oxygen fugacity and pressure. Distinguishing the effect of pressure from other variables on the activity coefficients and partitioning is important for understanding the chemical evolution of different planetary bodies during differentiation. In this study, we investigated the influence of pressure on the activity coefficients of Cu, Mo, Pd, Pt, As, Sb, and Bi in Fe-Si metallic liquids. All of these elements exhibit moderate to high activity coefficients in Fe-Si liquids at low pressure, which significantly controls their metal-silicate partitioning behavior. Identifying whether this strong dependence persists at higher pressures is critical to modeling and understanding the chemical consequences of core formation. New experiments at 10 GPa were used to derive activity coefficients for these metals which can be compared to activity coefficients determined at 1 GPa. Experiments were conducted at 10 GPa and 2373K using a 10/5 assembly in the 880-ton multi-anvil press at NASA Johnson Space Center. The standard 10/5 COMPRES assembly was slightly modified to accommodate a sample capsule machined from single-crystal MgO that minimizes melt percolation out of the sample volume during the experiment. Experiment starting materials were comprised of 70 wt.% Knippa basalt and 30 wt.% metal. The metal mixture (~85 wt.% Fe) was created by adding the elements of interest (Cu, Mo, Pd, Pt, As, Sb, Bi) to Fe metal powder. Varied amounts of Si metal (0-10 wt.% Si) were added to the metal-silicate mixtures to generate a systematic series of starting materials. For each element, an epsilon interaction parameter in Fe-Si liquid was derived from the results of our 0-10 wt.% Si metal series. To investigate whether pressure influences the trace element activity coefficients in the 1-10 GPa pressure range, we compared our results at 10 GPa to those at 1-4 GPa [1-3]. Our results can also be directly compared to interaction parameters for Au, P, V, Mn, Ga, Zn, Cd, Sn, W, Pb, and Nb previously determined at 10 GPa and 2373K following the same methods [4]. Combined, this suite of interaction parameters will directly inform metal-silicate partitioning between 1 and 10 GPa, and assess whether these values can be extrapolated to modeling differentiation processes at pressures >10 GPa.

Kelsey Prissel↗
DOE OSTI2024

Speeding up and reducing memory usage for scientific machine learning via mixed precision

Scientific machine learning (SciML) has emerged as a versatile approach to address complex computational science and engineering problems. Within this field, physics-informed neural networks (PINNs) and deep operator networks (DeepONets) stand out as the leading techniques for solving partial differential equations by incorporating both physical equations and experimental data. However, training PINNs and DeepONets require significant computational resources, including long computational times and large amounts of memory. In search of computational efficiency, training neural networks using half precision (float16) rather than the conventional single (float32) or double (float64) precision has gained substantial interest, given the inherent benefits of reduced computational time and memory consumed. However, we find that float16 cannot be applied to SciML methods, because of gradient divergence at the start of training, weight updates going to zero, and the inability to converge to a local minima. To overcome these limitations, we explore mixed precision, which is an approach that combines the float16 and float32 numerical formats to reduce memory usage and increase computational speed. Our experiments showcase that mixed precision training not only substantially decreases training times and memory demands but also maintains model accuracy. Here, we also reinforce our empirical observations with a theoretical analysis. The research has broad implications for SciML in various computational applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Measurement of $Z\gamma \gamma$ production in pp collisions at $\sqrt{s}= 13$ TeV with the ATLAS detector

Cross-sections for the production of a $Z$ boson in association with two photons are measured in proton–proton collisions at a centre-of-mass energy of 13 TeV. The data used correspond to an integrated luminosity of 139 fb -1 recorded by the ATLAS experiment during Run 2 of the LHC. The measurements use the electron and muon decay channels of the $Z$ boson, and a fiducial phase-space region where the photons are not radiated from the leptons. The integrated $Z$($\rightarrow$ $\ell$$\ell$)$\gamma \gamma$ cross-section is measured with a precision of 12% and differential cross-sections are measured as a function of six kinematic variables of the $Z\gamma \gamma$ system. The data are compared with predictions from MC event generators which are accurate to up to next-to-leading order in QCD. The cross-section measurements are used to set limits on the coupling strengths of dimension-8 operators in the framework of an effective field theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Update on NNL TSL Evaluations and Validation [Slides]

12 new/revised TSL evaluations were contributed to ENDF/B-VIII.1. The thermal diffusion length $L$ is an integral property of a single material’s absorption and scattering cross sections (both differential and integral). No other neutron reactions or materials are involved. The MC21-calculated $L$ for water is consistent with the spread of experimental data and is sufficiently sensitive to different H-H 2 O TSL physics models to use the method as a TSL integral performance benchmark. Modern high-quality diffusion experiments at elevated $T$ would allow direct low-cost physics benchmarking of water TSLs when public elevated-$T$ critical benchmarks are limited. NNL is working with LLNL and RPI to develop experimental PNDA capability. An ICSBEP Fundamental Physics benchmark of the Nassar and Murphy PNDA experiment is being developed to provide an example of how to evaluate these type of benchmarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Measurement of Low-$Q^2$ Protons from Neutral Current Events in Argon with MicroBooNE

The MicroBooNE experiment is an 85 ton active mass liquid-argon time projection chamber located at the Fermilab Booster Neutrino Beamline. MicroBooNE’s ability to detect low-energy protons allows us to study single-proton events with a four-momentum transfer squared Q 2 as low as 0.10 GeV 2 . We present a differential cross-section measurement of a signal with one proton and no other particles (NC1p) in the final state. We report the flux-averaged NC1p differential cross section dσ/dT for neutrinos scattering on argon as a function of proton kinetic energy T using a subset of MicroBooNE’s data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1991

A study of high alpha dynamics and flow visualization for a 2.5-percent model of the F-18 HARV undergoing wing rock

Free-to-roll experiments and flow visualization studies have been conducted for a 2.5-percent model of the F-18 undergoing unsteady wing rock oscillations. Data have been acquired in the form of roll angle time histories as well as video recordings and 35 mm photography of the forebody and leading edge extension vortices. The time histories were differentiated to produce angular velocity and angular acceleration. From this the roll moment as a function of time and/or roll angle could be estimated. A thorough analysis of the data has revealed a genuine wing-rock phenomenon. Off-surface flow visualization was used to identiify the forebody and LEX vortex core positions and their interaction in both static and dynamic configurations. A direct correlation between the dynamic data and visualized vortex activity during the wing-rock motion has been made.

Quast, Thomas↗
NASA NTRS1992

Venturi air-jet vacuum ejectors for high-volume atmospheric sampling on aircraft platforms

Documentation of the installation and use of venturi air-jet vacuum ejectors for high-volume atmospheric sampling on aircraft platforms is presented. Information on the types of venturis that are useful for meeting the pumping requirements of atmospheric-sampling experiments is also presented. A description of the configuration and installation of the venturi system vacuum line is included with details on the modifications that were made to adapt a venturi to the NASA Electra aircraft at GSFC, Wallops Flight Facility. Flight test results are given for several venturis with emphasis on applications to the Differential Absorption Carbon Monoxide Measurement (DACOM) system at LaRC. This is a source document for atmospheric scientists interested in using the venturi systems installed on the NASA Electra or adapting the technology to other aircraft.

Hill, Gerald F.↗
NASA NTRS1994

Packet radio data link applications in the NASA Langley Research Center Transport Systems Research Vehicle

An amateur packet radio system operating in the very high frequency (VHF) range has been implemented in the Transport Systems Research Vehicle at the NASA Langley Research Center to provide an economical, bidirectional, real-time, ground-to-air data link. The packet system has been used to support flight research involving air traffic control (ATC), differential global positioning systems (DGPS), and windshear terminal doppler weather radar (TDWR). A data maximum rate of 2400 baud was used. Operational reliability of the packet system has been very good. Also, its versatility permits numerous specific configurations. These features, plus its low cost, have rendered it very satisfactory for support of data link flight experiments that do not require high data transfer rates.

Easley, Wesley C.↗
NASA NTRS2000

Cell and Particle Interactions and Aggregation During Electrophoretic Motion

The objectives of this research were (i) to perform experiments for observing and quantifying electrophoretic aggregation, (ii) to develop a theoretical description to appropriately analyze and compare with the experimental results, (iii) to study the combined effects of electrophoretic and gravitational aggregation of large particles, and the combined effects of electrophoretic and Brownian aggregation of small particles, and (iv) to perform a preliminary design of a potential future flight experiment involving electrophoretic aggregation. Electrophoresis refers to the motion of charged particles, droplets or molecules in response to an applied electric field. Electrophoresis is commonly used for analysis and separation of biological particles or molecules. When particles have different surface charge densities or potentials, they will migrate at different velocities in an electric field. This differential migration leads to the possibility that they will collide and aggregate, thereby preventing separation.

Davis, Robert H.↗
DOE OSTI2021

B-PINNs: Bayesian Physics-informal Neural Networks for Forward and Inverse PDE Problems with Noisy Data

We propose a Bayesian physics-informed neural network (B-PINN) to solve both forward and inverse nonlinear problems described by partial differential equations (PDEs) and noisy data. In this Bayesian framework, the Bayesian neural network (BNN) combined with a PINN for PDEs serves as the prior while the Hamiltonian Monte Carlo (HMC) or the variational inference (VI) could serve as an estimator of the posterior. B-PINNs make use of both physical laws and scattered noisy measurements to provide predictions and quantify the aleatoric uncertainty arising from the noisy data in the Bayesian framework. Compared with PINNs, in addition to uncertainty quantification, B-PINNs obtain more accurate predictions in scenarios with large noise due to their capability of avoiding overfitting. We conduct a systematic comparison between the two different approaches for the B-PINNs posterior estimation (i.e., HMC or VI), along with dropout used for quantifying uncertainty in deep neural networks. Our experiments show that HMC is more suitable than VI with mean field Gaussian approximation for the B-PINNs posterior estimation, while dropout employed in PINNs can hardly provide accurate predictions with reasonable uncertainty. Finally, we replace the BNN in the prior with a truncated Karhunen-Loève (KL) expansion combined with HMC or a deep normalizing flow (DNF) model as posterior estimators. The KL is as accurate as BNN and much faster but this framework cannot be easily extended to high-dimensional problems unlike the BNN based framework.

Non linear PDEs, Noisy data, Bysian physics inform↗
NASA NTRSDate not supplied

Operational Experience with the Electromagnetic Position Sensor (EPS) for the NASA 6-inch MSBS

A Magnetic Suspension and Balance System (MSBS), originally developed in 1969, has been recommissioned at NASA Langley and is being used to explore dynamic test techniques for planetary entry capsules. A critical component of this system is the Electromagnetic Position Sensor (EPS) which provides non-contact position measurement for control of the actively suspended model. The sensor’s operation is similar to a Linear Variable Differential Transformer (LVDT). However the EPS has a much larger gap and smaller core than traditional LVDTs and therefore it requires specialized driving and processing circuitry. This paper describes the history of this sensor system, its mechanical and electrical design, and the efforts to improve signal conditioning circuitry.

T. D. Schott↗
DOE OSTI2024

62°S Witnesses the Transition of Boundary Layer Marine Aerosol Pattern Over the Southern Ocean (50°S–68°S, 63°E– 150°E) During the Spring and Summer: Results From MARCUS (I)

The Atmospheric Radiation Measurement Mobile Facility-2 was installed onboard the research vessel Aurora Australis to measure aerosol properties during the 2017-2018 Measurement of Aerosols, Radiation, and CloUds over the pristine Southern ocean (MARCUS) Experiment, providing unique data on aerosols latitudinal and seasonal variation, including south of 60 degrees S where previous observations are scarce. Data from a Cloud Condensation Nuclei (CCN) counter and Ultra-High-Sensitivity Aerosol Spectrometer show that both the number concentration (N-CCN) and size distribution of CCN-active aerosols, with diameters (D) between 60 nm < D < 1,000 nm are different over the North Southern Ocean (NSO) (50 degrees S-60 degrees S) and the South Southern Ocean (SSO) (62 degrees S-68 degrees S). The average NSO N-CCN at 0.2% and 0.5% supersaturation were 28% and 49% less than that over the SSO. This increase of CCN over the SSO is caused by the increase of aerosols with 60 nm < D < 200 nm, consistent with calculations of Aerosol Scattering Angstrom Exponents derived from a nephelometer. Aerosol hygroscopicity growth factor measured by the Hygroscopic Tandem Differential Mobility Analyzer stayed close to 1.41 for aerosols with 50 nm < D < 250 nm over the SSO, but increased from 1.30 to 1.67 over the NSO, indicating different chemical compositions. Both CCN and Ice Nucleating Particles (INPs) showed a stronger variation with season than with latitude. The variation of heat-labile and presumably proteinacous INPs suggests an increase of ice nucleating-active microbes in summer.

Niu, Qing↗
DOE OSTI2026

Active operator learning with predictive uncertainty quantification for partial differential equations

With the increased prevalence of neural operators being used to provide rapid solutions to partial differential equations (PDEs), understanding the accuracy of model predictions and the associated error levels is necessary for deploying reliable surrogate models in scientific applications. Existing uncertainty quantification (UQ) frameworks employ ensembles or Bayesian methods, which can incur substantial computational costs during both training and inference. Here, we propose a lightweight predictive UQ method tailored for Deep operator networks (DeepONets) that also generalizes to other operator networks. Numerical experiments on linear and nonlinear PDEs demonstrate that the framework’s uncertainty estimates are unbiased and provide accurate out-of-distribution uncertainty predictions with a sufficiently large training dataset. Our framework provides fast inference and uncertainty estimates that can efficiently drive outer-loop analyses that would be prohibitively expensive with conventional solvers. We demonstrate how predictive uncertainties can be used in the context of Bayesian optimization and active learning problems to yield improvements in accuracy and data-efficiency for outer-loop optimization procedures. In the active learning setup, we extend the framework to Fourier Neural Operators (FNO) and describe a generalized method for other operator networks. To enable real-time deployment, we introduce an inference strategy based on precomputed trunk outputs and a sparse placement matrix, reducing evaluation time by more than a factor of five. Our method provides a practical route to uncertainty-aware operator learning in time-sensitive settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Free energy difference to create the M-OH* intermediate of the oxygen evolution reaction by time-resolved optical spectroscopy

Theoretical descriptors differentiate the catalytic activity of materials for the oxygen evolution reaction by the strength of oxygen binding in the reactive intermediate created upon electron transfer. Recently, time-resolved spectroscopy of a photo-electrochemically driven oxygen evolution reaction followed the vibrational and optical spectra of this intermediate, denoted M-OH*. However, these inherently kinetic experiments have not been connected to the relevant thermodynamic quantities. Here we discover that picosecond optical spectra of the Ti-OH* population on lightly doped SrTiO 3 are ordered by the surface hydroxylation. A Langmuir isotherm as a function of pH extracts an effective equilibrium constant relatable to the free energy difference of the first oxygen evolution reaction step. Thus, time-resolved spectroscopy of the catalytic surface reveals both kinetic and energetic information of elementary reaction steps, which provides a critical new connection between theory and experiment by which to tailor the pathway of water oxidation and other surface reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗