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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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NASA NTRS1991

The dependence of wind stress on wave height and wind speed

Three near-neutral boundary layer data sets were investigated with the aim of finding a dependence of wind stress on both wind speed and significant wave height. The data set most representative of open-ocean wave height, wind speed, and momentum flux conditions, was selected and analyzed by means of the least-squares method to produce a new parameterization for the wind stress as a function of both wind speed and significant wave height. This study shows that the wind stress, and consequently the drag coefficient, decreases with increasing wave height for a fixed wind speed. The study also shows that the curvature of the wind profile decreases with increasing wave height and that the C(DN) = A + BU-bar(10) form for the drag coefficient parameterization is inadequate. A drag coefficient that applies to both smooth and rough flows is proposed. These results are more applicable for open-ocean deep-water conditions and less applicable for sheltered, closed, shallow water sites.

Blake, Reginald A.↗

NASA NTRS1994

Height and altitude distribution of large volcanoes on Venus

Magellan data reveal 156 large volcanoes on Venus (greater than 100 km in diameter) which range in height from 300 m to 5.55 km, with an average height of 1.42 km. On the basis of theory it has been predicted that the development of neutral buoyancy zones (NBZ) on Venus and thus the resulting volcanic deposits are strongly influenced by the altitude-controlled variations in surface pressure. The distribution and height of these large volcanoes as a function of altitude was examined to begin to test these predications. Although large volcanoes are relatively uniformly distributed in altitude, there may be a slight paucity of volcanoes at the lowest elevations and a slight surplus at mid-altitudes. In addition, it is observed that the volcanoes at the highest altitudes tend to be the tallest. The observed distributions at low-mid altitudes is consistent with the prediction of NBZ theory. The high altitude distribution and heights, however, emphasize the necessity of considering other factors, such as tectonic setting, edifice age, magma supply, and thermal gradient, in describing the location and development of large volcanoes on Venus.

Keddie, S. T.↗

NASA NTRS2017

Vertical Structure and Optical Properties of Titans Aerosols from Radiance Measurements Made Inside and Outside the Atmosphere

Prompted by the detection of stratospheric cloud layers by Cassini's Composite Infrared Spectrometer (CIRS; see Anderson, C.M., Samuelson, R.E. [2011]. Icarus 212, 762-778), we have re-examined the observations made by the Descent Imager/Spectral Radiometer (DISR) in the atmosphere of Titan together with two constraints from measurements made outside the atmosphere. No evidence of thin layers (<1 km) in the DISR image data sets is seen beyond the three previously reported layers at 21 km, 11 km, and 7 km by Karkoschka and Tomasko (Karkoschka, E., Tomasko, M.G. [2009]. Icarus 199, 442-448). On the other hand, there is evidence of a thicker layer centered at about 55 km. A rise in radiance gradients in the Downward-Looking Visible Spectrometer (DLVS) data below 55 km indicates an increase in the volume extinction coefficient near this altitude. To fit the geometric albedo measured from outside the atmosphere the decrease in the single scattering albedo of Titan's aerosols at high altitudes, noted in earlier studies of DISR data, must continue to much higher altitudes. The altitude of Titan's limb as a function of wavelength requires that the scale height of the aerosols decrease with altitude from the 65 km value seen in the DISR observations below 140 km to the 45 km value at higher altitudes. We compared the variation of radiance with nadir angle observed in the DISR images to improve our aerosol model. Our new aerosol model fits the altitude and wavelength variations of the observations at small and intermediate nadir angles but not for large nadir angles, indicating an effect that is not reproduced by our radiative transfer model. The volume extinction profiles are modeled by continuous functions except near the enhancement level near 55 km altitude. The wavelength dependence of the extinction optical depth is similar to earlier results at wavelengths from 500 to 700 nm, but is smaller at shorter wavelengths and larger toward longer wavelengths. A Hapke-like model is used for the ground reflectivity, and the variation of the Hapke single scattering albedo with wavelength is given. Fits to the visible spectrometers looking upward and downward are achieved except in the methane bands longward of 720 nm. This is possibly due to uncertainties in extrapolation of laboratory measurements from 1 km-am paths to much longer paths at lower pressures. It could also be due to changes in the single scattering phase functions at low altitudes, which strongly affect the path length through methane that the photons travel. We demonstrate the effects on the model fits by varying each model parameter individually in order to illustrate the sensitivity of our determination of each model parameter.

Titan↗

NASA NTRS1975

Comparison between reflectivity statistics at heights of 3 and 6 km and rain rate statistics at ground level

An experiment was conducted to study the relations between the empirical distribution functions of reflectivity at specified locations above the surface and the corresponding functions at the surface. A bistatic radar system was used to measure continuously the scattering cross section per unit volume at heights of 3 and 6 km. A frequency of 3.7 GHz was used in the tests. It was found that the distribution functions for reflectivity may significantly change with height at heights below the level of the melting layer.

Crane, R. K.↗

NASA NTRS2015

Signal Processing for Determining Water Height in Steam Pipes with Dynamic Surface Conditions

An enhanced signal processing method based on the filtered Hilbert envelope of the auto-correlation function of the wave signal has been developed to monitor the height of condensed water through the steel wall of steam pipes with dynamic surface conditions. The developed signal processing algorithm can also be used to estimate the thickness of the pipe to determine the cut-off frequency for the low pass filter frequency of the Hilbert Envelope. Testing and analysis results by using the developed technique for dynamic surface conditions are presented. A multiple array of transducers setup and methodology are proposed for both the pulse-echo and pitch-catch signals to monitor the fluctuation of the water height due to disturbance, water flow, and other anomaly conditions.

health monitoring↗

NASA NTRS1973

Virginia precipitation scatter experiment: Data analysis

Rain scatter and surface rain rate data were obtained from October 3, 1970 to October 2, 1971 using a bistatic radar system and tipping bucket rain gauges located in southeastern Virginia. The data showed that interference may occur between earth and terrestrial stations located within 80 km of each other either by mainlobe-to-mainlobe coupling or sidelobe-to-mainlobe coupling. The data further show that the distributions of scattering cross section per unit volume measured at several heights and estimated from surface rain gauge data were different. The density functions for the scattering cross section per unit volume values measured at a 3 km height and estimated from surface rain rate data were identical only for summer thundershowers. The data showed that the CCIR model used to estimate interference due to rain is inadequate because the cell size and change of scattering cross section per unit volume with height estimates of the model predict transmission loss values that are too low (more interference than will occur).

Crane, R. K.↗

NASA NTRS1979

Analysis of GEOS-3 altimeter data and extraction of ocean wave height and dominant wavelength

When the amplitude and timing biases are removed from the GEOS-3 Sample and Hold (S&H) gates, the mean return waveforms can be excellently fitted with a theoretical template which represents the convolution of: (1) the radar point target response; (2) the range noise (jitter) in the altimeter tracking loop; (3) the sea surface height distribution; and (4) the antenna pattern as a function of the range to mean sea level. Several techniques of varying complexity to remove the effect of the tracking loop jitter in computing the wave height are considered. They include: (1) realigning the S&H gates to their actual positions with respect to mean sea level before averaging; (2) using the observed standard deviation on the altitude measurement to remove the integrated effect of the tracking loop jitter, and (3) using a look-up table to correct for the expected value of range noise. Analysis of skewness in the GEOS return waveform demonstrates the potential of a satellite radar altimeter to determine the dominant wavelength of ocean waves.

Walsh, E. J.↗

DOE OSTI2021

FY21 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g., height, color and grayscale values; all as functions of a location in a plane projection). A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data, flag significant features, execute Machine Learning (ML) algorithms, output parameters for trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Features can be called out by user-specified thresholds, manual labeling or machine learning algorithms when they have been completed. The ability to rapidly label data is important because of the volume of data required for training machine learning algorithms. The GUI has the flexibility to allow addition of improved ML algorithms, methods for data visualization, and statistical computations. Statistical analyses via the GUI include areas of pits within a defined range of pit depths, correlations between Red-Green-Blue (RGB) or grayscale intensity and relative surface height, covariances between values associated with features, and feature histograms. The development of supervised machine learning algorithms, however, has been hindered by a lack of training data. The machine learning algorithms for crack identification are being refined but require improvements to the true positive rate for crack detection. This shortcoming is an artifact of the limited training data currently available, perhaps more so than the structure of the neural networks. At present, the best results are had from a consensus over an ensemble of randomly generated Deep Neural Network (DNN) or Convolutional Neural Network (CNN) algorithms. Although the consensus accuracy method has yielded optimum true positive and true negative rates in excess of 80%, additional validation testing is necessary. In addition to the suite of LCM data that was initially used, and which represents the majority of the work presented in this report, WAMS image data was also reviewed at a preliminary level. The review included a comparison between image resolution and dynamic range for each method. WAMS (ZON file) image data was found to have a pixel pitch of 3.69μm compared to 1 μm for the LCM (vk4 file) data, which implies a lower resolution for the WAMS images. Conversely, the ratio of dynamic range of the WAMS data to the LCM data was approximately 41:20 for height data, suggesting that information from WAMS should more accurately determine the depth of pits. At present, the significance of the greater dynamic range of the WAMS data relative to the LCM data has not yet been evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1986

Extended active space CASSCF/MRSD CI calculations of the barrier height for the reaction: O + H2 yields OH + H

The convergence of the barrier height for the O + H2 yields OH + H reaction was studied as a function of the size of the active space and basis set completeness. The barrier height is rapidly convergent with respect to expansion of the active space. Addition of 2p yields 2p' correlation terms to the active space lowers the barrier to the O + H2 reaction by about 2.0 kcal/mole, but addition of 3d and other terms has little additional effect. Multireference singles and doubles contracted CI plus Davidson's correction calculations using a (5s5p3d2f1g/4s3p2d1f) basis set with a 5 sigma 2 pi active space lead to a barrier height of 12.7 kcal/mole. Including an estimate of the CI contraction error and basis set superposition error leads to 12.4 kcal/mole as the best estimate of the barrier height.

Walch, Stephen P.↗

NASA NTRS1987

Intrinsic frequency spectra of short gravity-capillary waves obtained from temporal measurements of wave height on a lake

Intrinsic frequency spectra of water waves in the range of 6-17 Hz were obtained as a function of both wind speed and wind stress from point measurements of wave height. In a lake with a limited fetch, there are two types of surface motions causing Doppler shift in the frequencies of short waves: orbital velocity of long waves and surface wind drift. The former was estimated from long-wave amplitude by using a linear wave theory. The error in this estimate is of the order of the long-wave slope, and for this work it is typically 10 percent. The latter was approximated by the friction velocity. The friction velocity could be either taken as 3 percent of the mean wind speed measured at a height of 10 m or obtained from direct measurements of the wind stress. The surface drift velocities obtained by these two approaches were found to be in close agreement. Doppler frequency shift can be corrected in either the frequency or the equivalent spatial domain. The two techniques were found to produce comparable results. Experimental results showed that the spectral energy of short waves rapidly increased in response to increasing winds and jumped up by an order of magnitude when wave breaking occurred.

Atakturk, S. S.↗

NASA NTRS2020

Mapping tree canopy cover and canopy height with L-band SAR using LiDAR data and Random Forests

Light detection and ranging (LiDAR) data can provide direct measurements of vegetation structures but are limited by the sparse spatial coverage. Polarimetric synthetic aperture radar (SAR) can perform large-scale high-resolution mapping without weather constraints but the information about vegetation and ground subsurface are mixed in the backscatter data. In this paper, we adopted the Random Forests algorithm to train an upscaling function using tree canopy cover (TCC) and canopy height model (CHM) derived from Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) data. The regression model is then applied to the L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign to map the TCC and CHM over the Delta Junction area in interior Alaska.

Moghaddam, Mahta↗

DOE OSTI2021

An initial exploration of Bayesian model calibration for estimating the composition of rocks and soils on Mars

The Mars Curiosity rover carries an instrument, ChemCam, designed to measure the composition of surface rocks and soil using laser-induced breakdown spectroscopy (LIBS). The measured spectra from this instrument must be analyzed to identify the component elements in the target sample, as well as their relative proportions. This process, which we call disaggregation, is complicated by so-called matrix effects, which describe nonlinear changes in the relative heights of emission lines as an unknown function of composition due to atomic interactions within the LIBS plasma. In this work, we explore the use of the plasma physics code ATOMIC, developed at Los Alamos National Laboratory, for the disaggregation task. ATOMIC has recently been used to model LIBS spectra and can robustly reproduce matrix effects from first principles. The ability of ATOMIC to predict LIBS spectra presents an exciting opportunity to perform disaggregation in a manner not yet tried in the LIBS community, namely via Bayesian model calibration. However, using it directly to solve our inverse problem is computationally intractable due to the large parameter space and the computation time required to produce a single output. Therefore, we also explore the use of emulators as a fast solution for this analysis. We discuss a proof of concept Gaussian process emulator for disaggregating two-element compounds of sodium and copper. The training and test datasets were simulated with ATOMIC using a Latin hypercube design. After testing the performance of the emulator, we successfully recover the composition of 25 test spectra with Bayesian model calibration.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Process Image Analysis using Big Data, Machine Learning, and Computer Vision

The development of algorithms for machine learning and data analysis for the 3013 MIS corrosion surveillance program is a collaborative effort by SRNL, USC and GT. For corrosion detection, LCM image data is extracted from large binary files, with software written to convert the data to physical attributes (i.e. height, color and grayscale values; all as functions of a location in a plane projection). The user interface for the software permits selective downloading of binary data and interrogation of attributes. User input thresholds are used to flag attributes of interest. Machine learning algorithms, developed for this application, are used to determine whether the features are the result of corrosion. To address the fundamental mechanisms of corrosion, machine learning algorithms are being developed to derive interatomic potential force-fields from ab-initio DFT calculations. The goal is to apply molecular modeling on a large enough scale to guide the design of resistant materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking (FY2020 Progress Report)

3013 corrosion↗

DOE OSTI2022

FY22 Progress Report: SRNL Analysis of ICCWR LCM and WAMS Data for Corrosion and Cracking

Algorithms for machine learning and data analysis for the 3013 Surveillance Program are being developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). To detect the presence of corrosion and cracking, data is collected from large binary files generated by a Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS). Software is being developed to use the physical attributes in the data files (e.g., height, color, and grayscale values; all as functions of a location in a plane projection) to detect the presence of surface corrosion and cracking. A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data for training ML algorithms, flag significant features, execute Machine Learning (ML) algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Surface defects can be called out by setting user-specified thresholds, feature based analysis or machine learning algorithms. Enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the very large volume of data required to train ML algorithms.

3013 Corrosion↗

DOE OSTI2025

Experimental Study of a Novel Semi-Transparent Bi-Facial Agri-Voltaic System: Initial Results

Solar (photovoltaic)-agriculture practices have experienced notable progress across several countries over the past few decades, creating a field widely known as agrivoltaics. This co-location practice has proved effective for certain crops that prefer partial shade like tomatoes, lettuce, and peppers, although it is less effective for crops needing more sun. Availability of natural sunlight with a specific spectral signature is necessary for agricultural practices as many plant species require an optimum-level and quality of sunlight for photosynthesis. The goal of this work is to model and validate ground-level irradiance for a semi-transparent bifacial solar collector equipped with a custom spectral reflector. By introducing intentional gaps between opaque solar cells, we hope to allow 50% of visible light to pass through the module. Additionally, this technology could reduce the soil temperature by 2° C, improve moisture retention, and enhance yield by providing partial solar radiation. In our model, we can calculate the total solar irradiance for the plants as a function of the cell distribution, material absorption, height of the panel and time of year with a spatial resolution of 0.0625 m2. When comparing theoretical estimates to experimental measurements of photosynthetically active radiation (PAR), we find a discrepancy of 32-48%, and a discrepancy of 19-38% after correction with TMY data.

McGraw, Duncan (ORCID:0000000256388118)↗

NASA NTRS1972

A quadratic pulse height analyzer for space applications.

A flight-worthy pulse height analyzer that has a quadratic transfer function is described. This quadratic function permits optimum usage of the entire PHA dynamic range due to the quadratic nature of the gamma ray spectrometer's resolution vs energy. After the theoretical design discussion, the implementation of the design is examined and test results described. The analyzer is part of the University of New Hampshire gamma ray monitor for OSO-H.

Burtis, D. W.↗

NASA NTRS1973

A high frequency correction to the Kirchhoff approximation, with application to rough surface EM wave scattering

A high frequency correction to the Kirchhoff approximation is developed for application to rough surface scattering. An approximate solution to the magnetic field integral equation for perfect conductivity and plane wave excitation yields a perturbed surface current expressed as a linear function of the second derivatives of surface height. The corrected surface current vector is substituted into the far field Stratton-Chu integral and average backscattered powers for the four polarization combinations are computed on the assumption that the surface is describable as a stationary Gaussian random process. The strength of this scattering solution is that it can account for height curvature correlation without requiring small height and slope.

Jackson, F. C.↗