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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

The impact of Doppler lidar wind observations on a single-level meteorological analysis

Through the use of observation operators, modern data assimilation systems have the capability to ingest observations of quantities that are not themselves model variables, but are mathematically related to those variables. An example of this are the so-called LOS (line of sight) winds that a Doppler wind Lidar can provide. The model - or data assimilation system - needs information about both components of the horizontal wind vectors, whereas the observations in this case only provide the projection of the wind vector onto a given direction. The analyzed value is then calculated essentially based on a comparison between the observation itself and the model-simulated value of the observed quantity. However, in order to assess the expected impact of such an observing system, it is important to examine the extent to which a meteorological analysis can be constrained by the LOS winds. The answer to this question depends on the fundamental character of the atmospheric flow fields that are analyzed, but more importantly it also depends on the real and assumed error covariance characteristics of these fields. A single-level wind analysis system designed to explore these issues has been built at the NASA Data Assimilation Office. In this system, simulated wind observations can be evaluated in terms of their impact on the analysis quality under various assumptions about their spatial distribution and error characteristics and about the error covariance of the background fields. The basic design of the system will be presented along with experimental results obtained with it. In particular, the value of simultaneously measuring LOS winds along two different directions for a given location will be discussed.

Riishojgaard, L. P.↗
NASA NTRS2007

Water Droplet Impingement on Simulated Glaze, Mixed, and Rime Ice Accretions

Water droplet impingement data were obtained at the NASA Glenn Icing Research Tunnel (IRT) for a 36-in. chord NACA 23012 airfoil with and without simulated ice using a dye-tracer method. The simulated ice shapes were defined with the NASA Glenn LEWICE 2.2 ice accretion program and including one rime, four mixed and five glaze ice shapes. The impingement experiments were performed with spray clouds having median volumetric diameters of 20, 52, 111, 154, and 236 micron. Comparisons to the experimental data were generated which showed good agreement for the rime and mixed shapes at lower drop sizes. For larger drops sizes LEWICE 2.2 over predicted the collection efficiencies due to droplet splashing effects which were not modeled in the program. Also for the more complex glaze ice shapes interpolation errors resulted in the over prediction of collection efficiencies in cove or shadow regions of ice shapes.

Papadakis, Michael↗
NASA NTRS2018

Performance Analysis of Airborne Photon-Counting Lidar Data in Preparation for the ICESat-2 Mission

Two airborne photon-counting laser altimeters have been deployed in direct support of National Aeronautics and Space Adminsitration (NASA's) upcoming Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. Multiple Altimeter Beam Experimental Lidar (MABEL) was developed specifically for ICESat-2 testing and development. MABEL data are used to simulate key aspects of the ICESat-2 measurement strategy and are critical to the development of the algorithms for geophysical data-product generation. Slope Imaging Multipolarization Photon-counting Lidar (SIMPL) is a NASA Goddard Space Flight Center instrument that has also been deployed in support of ICESat-2 performance discovery. Both instruments are photon-counting, small footprint laser altimeters that sample in both the 532- and 1064-nm wavelengths. And both instruments serve as a proxy for ICESat-2 operational performance and error assessment and a basis for the development of potential validation strategies. This paper provides an overview of how data from MABEL and SIMPL overflights have specifically provided the foundation for understanding the quality of ICESat-2 data and how we can plan to evaluate ICESat-2 products through comparison with other modalities of lidar data and/or groundtruth locations using ground fiducials.

MABEL↗
DOE OSTI2024

Evaluation of Uncertainties of Pressure Gain Measurements in Rotating Detonation Combustor

Experimentally measuring the pressure gain of a rotating detonation combustor through the method of equivalent available pressure is prone to many experimental uncertainties. A detailed analysis of sources of random and systematic uncertainties in the thrust and pressure gain is performed using data from a hydrogen/air-operated rotating detonation combustor. The combustor had an axial air inlet and a 50% exit constriction. The measured (negative) pressure gain values agree with the results in the literature for similar inlet-to-exit area ratios. The base drag correction on the centerbody was found to be the greatest source of uncertainty for the thrust. While thrust is the predominant source of random uncertainty in the pressure gain calculation, significant systematic errors can be committed due to the assumed exit Mach number. The impact of this assumption becomes more detrimental the closer to positive the measured pressure gain is. By experimentally evaluating the exit Mach number, the random and systematic uncertainty in pressure gain both decreased, indicating that this should be an essential step. A definitive demonstration of gain is challenging, given the assessed uncertainties, and recommendations are provided to increase the precision of the equivalent available pressure methodology.

Engineering↗
NASA NTRS1998

Optical Channelizer Evaluation Using Empirical Data and Simulation

Westinghouse Electric Corporation Division under NASA contract NAS3-25865 developed a proof-of-concept (POC) multichannel demultiplexer implemented as an acousto-optic radiofrequency (RF) with a spectrum analyzer. A detailed analysis of the experimental results indicate that the expected degradation caused by the acousto-optical channelizer is approximately 2.0 dB degradation at 10(exp -5) bit-error rate (BER) and 3.0 dB degradation at 10(exp -8) BER. This degradation may be quite acceptable when considering the excellent volume, mass, and power characteristics of acousto-optical channelizing relative to other technologies. In addition, system performance can be greatly improved by using digital pulse shaping in the modem and increasing the channel spacing from 40 to 45 kHz for 64 kbps quadrature phase-shift keying (QPSK) modulation.

Ivancic,William D.↗
DOE OSTI2024

Critical Assessment of Electronic Structure Descriptors for Predicting Perovskite Catalytic Properties

The discovery and design of materials which can efficiently catalyze the oxygen reduction and evolution reactions at reduced temperatures is important for facilitating the widespread adoption of fuel cell and electrolyzer technologies. Numerous studies have produced correlations between catalytic properties, such as oxygen surface exchange or electrode area specific resistance (ASR), and properties of the catalyst material. However, correlations have historically been limited in scope (e.g., using only a few materials or at a single temperature) and it has been difficult to provide detailed assessments of their robustness. Here, in this study, we assess the ability of the O p-band center electronic structure descriptor, obtained from density functional theory (DFT) calculations, to correlate with oxygen surface exchange rates, diffusivities, and area specific resistances for a large database of perovskite oxide catalytic properties. By data mining the literature, we obtain 747 catalytic property value data points spanning 299 unique perovskite compositions from 313 studies. We assess linear correlations of each property with the O p-band center and find generally modest correlations that are qualitatively useful (prediction mean absolute errors of about 0.5 log units are typical), where the correlations are improved at higher temperatures (e.g., 800 °C vs. 500 °C) and significantly improve when considering fits to the subset of materials which have multiple independent measurements. These findings suggest that the spread of property data is significantly influenced by experimental uncertainty, and subsequent measurements of additional materials will likely improve the O p-band center correlations.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Simulations of tokamak edge plasma turbulent fluctuations based on a minimal 3D model

In this study, a new simulation model for tokamak boundary plasma, SOLT3D, is implemented in the BOUT++ framework. The simulation model includes a set of dynamic equations describing collisional boundary plasma and neutral gas in the tokamak scrape-off layer and divertor region. The model is verified against standard linear plasma instabilities and available nonlinear results. For L-mode like conditions, SOLT3D reproduces characteristics of boundary plasma turbulent fluctuations that are similar to published experimental data, in terms of the amplitude and spatial dependence of the fluctuations. It also reproduces realistic plasma fluxes on material surfaces and expected Bohm-like effective radial transport. Plasma fluctuations inferred from the simulations imply inevitably a significant level of intrinsic 'noise' for axisymmetric tokamak plasma transport modeling, introducing errors on the order of unity. In particular, the toroidally averaged atomic rates below 5–10 eV are strongly modified by turbulent plasma fluctuations, which should significantly affect the standard axisymmetric modeling of the tokamak edge plasma and divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Studying electroweak few-body observables in chiral effective field theory

The use of nuclei to study electroweak probes is becoming increasingly relevant experimentally. The success of dark matter and neutrino experiments strongly depends on the ability to control nuclear effects in order to extract the fundamental parameters associated with external probes. Therefore, reliable theoretical calculations of nuclear structure and reactions, with well-controlled errors, are crucial for the success of experimental efforts. Currently, chiral effective field theory ($\chi$EFT) coupled with {\it ab-initio} methods represents one of the best approaches that fulfills these requirements. To use this approach as a tool for studying fundamental physics, it is essential to validate it against experimental data for which the calculations are well under control, such as the elastic scattering of electrons on nuclei. In this proceeding, I will present recent developments in the fitting of electromagnetic currents derived using $\chi$EFT and the calculation of electromagnetic form factors of light nuclei. The results of these calculations demonstrate the strength of the theory in describing the interaction of nuclei with electromagnetic probes over a broad range of momentum transfers and highlight the robustness of $\chi$EFT for analyzing future experimental data aimed at extracting fundamental parameters.

Gnech, Alex [Old Dominion Univ., Norfolk, VA (Unit↗
NASA NTRS1975

Equalization of data transmission cable

The paper describes an equalization approach utilizing a simple RLC network which can obtain a maximum slope of -12dB/octave for reshaping the frequency characteristics of a data transmission cable, so that data may be generated and detected at the receiver. An experimental procedure for determining equalizer design specifications using distortion analysis is presented. It was found that for lengths of 16 PEV-L cable of up to 5 miles and data transmission rates of up to 1 Mbs, the equalization scheme proposed here is sufficient for generation of the data with acceptable error rates.

Zobrist, G. W.↗
NASA NTRS1975

Drogue performance evaluation. Part 1: Data acquisition

Surface buoy/subsurface drogue drag coupling was investigated. Data acquisition methods and techniques derived from several experimental cruises on the Chesapeake Bay are presented. Four buoys were utilized: three coupled to steel plates rigidly attached to each other at right angles and at various depths; and one spar type that did not require drag plates. Data from these surface floats and the drogue depth combinations were processed. Errors in tracking the surface buoys are discussed.

Johnson, R. E.↗
NASA NTRS1979

A structural model of the adaptive human pilot

A compensatory tracking model of the human pilot is offered which attempts to provide a more realistic representation of the human's signal processing structure than that which is exhibited by pilot models currently in use. Two features of the model distinguish it from other representations of the human pilot. First, proprioceptive information from the control stick or manipulator constitutes one of the major feedback paths in the model, providing feedback of vehicle output rate due to control activity. Implicit in this feedback loop is a model of the vehicle dynamics which is valid in and beyond the region of crossover. Second, error-rate information is continuously derived and independently but intermittently controlled. An output injected remnant model is offered and qualitatively justified on the basis of providing a measure of the effect of inaccuracies such as time variations in the pilot's internal model of the controlled element dynamics. The data from experimental tracking tasks involving five different controlled element dynamics and one nonideal viewing condition were matched with model generated describing functions and remnant power spectral densities.

Hess, R. A.↗
NASA NTRS1988

Fiber optic sensors with internal referencing

The main problem with amplitude modulating type sensors is that any variation in the intensity of the optical signal which occurs throughout the sensing system is interpreted by the photodetector as resulting from the sensor itself and is reflected as an error in the sensed parameter. To account for these errors, a referencing technique with the signal and reference channels separated in the time domain over the same fiber link can be used. Selected sensing and signal processing techniques involving temporally separated signal and referencing channels are described. A transition from the time into the frequency domain is also discussed. Experimental data are presented.

Adamovsky, Grigory↗
NASA NTRS1989

Transient fault behavior in a microprocessor: A case study

An experimental analysis is described which studies the susceptibility of a microprocessor based jet engine controller to upsets caused by current and voltage transients. A design automation environment which allows the run time injection of transients and the tracing from their impact device to the pin level is described. The resulting error data are categorized by the charge levels of the injected transients by location and by their potential to cause logic upsets, latched errors, and pin errors. The results show a 3 picoCouloumb threshold, below which the transients have little impact. An Arithmetic and Logic Unit transient is most likely to result in logic upsets and pin errors (i.e., impact the external environment). The transients in the countdown unit are potentially serious since they can result in latched errors, thus causing latent faults. Suggestions to protect the processor against these errors, by incorporating internal error detection and transient suppression techniques, are also made.

Duba, Patrick↗
NASA NTRS2002

Characterizing Thermal Properties of Melting Te Semiconductor: Thermal Diffusivity Measurements and Simulation

Tellurium is an element for many II-VI and I-III-VI(sub 2) compounds that are useful materials for fabricating many devices. In the melt growth techniques, the thermal properties of the molten phase are important parameter for controlling growth process to improve semiconducting crystal quality. In this study, thermal diffusivity of molten tellurium has been measured by a laser flash method in the temperature range from 500 C to 900 C. A pulsed laser with 1064 nm wavelength is focused on one side of the measured sample. The thermal diffusivity can be estimated from the temperature transient at the other side of the sample. A numerical simulation based on the thermal transport process has been also performed. By numerically fitting the experimental results, both the thermal conductivity and heat capacity can be derived. A relaxation phenomenon, which shows a slow drift of the measured thermal conductivity toward the equilibrium value after cooling of the sample, was observed for the first time. The error analysis and the comparison of the results to published data measured by other techniques will be discussed.

Zhu, Shen↗
NASA NTRS2002

Characterizing Thermal Properties of Melting Te Semiconductor: Thermal Diffusivity Measurements and Simulation

Tellurium is an element for many II-VI and I-III-VI(sub 2) compounds that are useful materials for fabricating many devises. In the melt growth techniques, the thermal properties of the molten phase are important parameter for controlling growth process to improve semiconducting crystal quality. In this study, thermal diffusivity of molten tellurium has been measured by a laser flash method in the temperature range from 500 C to 900 C. A pulsed laser with 1064 nm wavelength is focused on one side of the measured sample. The thermal diffusivity can be estimated from the temperature transient at the other side of the sample. A numerical simulation based on the thermal transport process has been also performed. By numerically fitting the experimental results, both the thermal conductivity and heat capacity can be derived. A relaxation phenomenon, which shows a slow drift of the measured thermal conductivity toward the equilibrium value after cooling of the sample, was observed for the first time. The error analysis and the comparison of the results to published data measured by other techniques will be discussed in the presentation.

Zhu, Shen↗
NASA NTRS2007

Large and Small Droplet Impingement Data on Airfoils and Two Simulated Ice Shapes

Water droplet impingement data were obtained at the NASA Glenn Icing Research Tunnel (IRT) for four wings and one wing with two simulated ice shapes. The wings tested include three 36-in. chord wings (MS(1)-317, GLC-305, and a NACA 652-415) and a 57-in. chord Twin Otter horizontal tail section. The simulated ice shapes were 22.5- and 45-min glaze ice shapes for the Twin Otter horizontal tail section generated using the LEWICE 2.2 ice accretion program. The impingement experiments were performed with spray clouds having median volumetric diameters of 11, 21, 79, 137, and 168 mm. Comparisons to the experimental data were generated which showed good agreement for the clean wings and ice shapes at lower drop sizes. For larger drop sizes LEWICE 2.2 over predicted the collection efficiencies due to droplet splashing effects which were not modeled in the program. Also for the more complex glaze ice shapes interpolation errors resulted in the over prediction of collection efficiencies in cove and shadow regions of ice shapes.

Papadakis, Michael↗
DOE OSTI2021

Toward Guided Mutagenesis: Gaussian Process Regression Predicts MHC Class II Antigen Mutant Binding

Antigen-specific immunotherapies (ASI) require successful loading and presentation of antigen peptides into the major histocompatibility complex (MHC) binding cleft. One route of ASI design is to mutate native antigens for either stronger or weaker binding interaction to MHC. Exploring all possible mutations is costly both experimentally and computationally. To reduce experimental and computational expense, here we investigate the minimal amount of prior data required to accurately predict the relative binding affinity of point mutations for peptide-MHC class II (pMHCII) binding. Using data from different residue subsets, we interpolate pMHCII mutant binding affinities by Gaussian process (GP) regression of residue volume and hydrophobicity. We apply GP regression to an experimental data set from the Immune Epitope Database, and theoretical data sets from NetMHCIIpan and Free Energy Perturbation calculations. We find that GP regression can predict binding affinities of nine neutral residues from a six-residue subset with an average R 2 coefficient of determination value of 0.62 ± 0.04 (±95% CI), average error of 0.09 ± 0.01 kcal/mol (±95% CI), and with an receiver operating characteristic (ROC) AUC value of 0.92 for binary classification of enhanced or diminished binding affinity. Similarly, metrics increase to an R2 value of 0.69 ± 0.04, average error of 0.07 ± 0.01 kcal/mol, and an ROC AUC value of 0.94 for predicting seven neutral residues from an eight-residue subset. Our work finds that prediction is most accurate for neutral residues at anchor residue sites without register shift. This work holds relevance to predicting pMHCII binding and accelerating ASI design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Winetrout, Jordan J.↗