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NASA NTRSDate not supplied

Bond Line Thickness Estimation in Composite Structures Using Multiple Inspection Techniques

Imaging and other nondestructive evaluation techniques are commonly used for material characterization and defect recognition in safety critical aerospace applications, with data fusion providing the framework for uncertainty quantification in these contexts. Most commonly, forward physics-based modeling predicts the response conditioned on material properties and defect assumptions, and probabilistic methods are used to infer the hidden state of subject of the inspection from a combination of prior information, likelihoods, and inspection data. In this paper Bayesian methods are used to estimate bond thickness in lap joints comprised of aluminum adherends using a combination of infrared thermography, digital radiography, and ultrasound. The accuracy of the fused estimates are validated against data generated from synthetic specimens, and by comparison against high resolution X-ray computed tomography inspections of built specimens.

thermal nondestructive evaluation↗
NASA NTRS2013

Validation of Forested Inundation Extent Revealed by L-Band Polarimetric and Interferometric SAR Data

UAVSAR, NASA's airborne Synthetic Aperture Radar (SAR), conducted an extended observational campaign in Central and South America in March 2013, primarily related to volcanic deformations along the Andean Mountain Range but also including a large number of flights studying other scientific phenomena. During this campaign, the L-Band SAR collected data over the Napo River in Ecuador. The objectives of this experiment were to acquire polarimetric and interferometric L-Band SAR data over an inundated tropical forest in Ecuador simultaneously with on-the-ground field work ascertaining the extent of inundation, and to then derive from this data a quantitative estimate for the error in the SAR-derived inundation extent. In this paper, we will first describe the processing and preliminary analysis of the SAR data. The polarimetric SAR data will be classified by land cover and inundation state. The interferometric SAR data will be used to identify those areas where change in inundation extent occurred, and to measure the change in water level between two observations separated by a week. Second, we will describe the collection of the field estimates of inundation, and have preliminary comparisons of inundation extent measured in the field field versus that estimated from the SAR data.

Synthetic Aperture Radar (SAR),↗
NASA NTRS2010

Relating Convective and Stratiform Rain to Latent Heating

The relationship among surface rainfall, its intensity, and its associated stratiform amount is established by examining observed precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The results show that for moderate-high stratiform fractions, rain probabilities are strongly skewed toward light rain intensities. For convective-type rain, the peak probability of occurrence shifts to higher intensities but is still significantly skewed toward weaker rain rates. The main differences between the distributions for oceanic and continental rain are for heavily convective rain. The peak occurrence, as well as the tail of the distribution containing the extreme events, is shifted to higher intensities for continental rain. For rainy areas sampled at 0.58 horizontal resolution, the occurrence of conditional rain rates over 100 mm/day is significantly higher over land. Distributions of rain intensity versus stratiform fraction for simulated precipitation data obtained from cloud-resolving model (CRM) simulations are quite similar to those from the satellite, providing a basis for mapping simulated cloud quantities to the satellite observations. An improved convective-stratiform heating (CSH) algorithm is developed based on two sources of information: gridded rainfall quantities (i.e., the conditional intensity and the stratiform fraction) observed from the TRMM PR and synthetic cloud process data (i.e., latent heating, eddy heat flux convergence, and radiative heating/cooling) obtained from CRM simulations of convective cloud systems. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. Major differences between the new and old algorithms include a significant increase in the amount of low- and midlevel heating, a downward emphasis in the level of maximum cloud heating by about 1 km, and a larger variance between land and ocean in the new CSH algorithm.

Tao, Wei-Kuo↗
NASA NTRS2019

Cluster Analysis of Spectroscopic Line Profiles and EUV Emission in RMHD Simulations and Observations of the Solar Atmosphere

Spatially-resolved observations from the IRIS, SDO/AIA, and other space mission and ground-based telescopes, coupled with realistic 3D RMHD simulations, are a powerful tool for analysis of processes in the solar atmosphere. To better understand the dynamical and thermodynamic properties in the simulation data and their connection to observations, it is essential to determine similarities in the behaviors of the synthesized and observed emission. However, the complexity of observational data and physical processes makes comparison of observations and modeling results difficult. In this work, we show the initial results of application of K-Means clustering (unsupervised machine learning) algorithm to two different problems: 1) recognition of the typical spectroscopic line profiles observed by IRIS during solar flares and their typical dynamic behavior; 2) recognition of shocks and heating events in synthetic AIA emission data obtained from StellarBox quiet-Sun simulations. The average silhouette width technique for the KMeans algorithm is utilized in different ways to obtain optimal numbers of clusters. We discuss application of the emission clustering to visualizations of the computational volume, understanding its evolutionary trends and behavior patterns, and inversion (reconstruction) of physical properties of the solar atmosphere from synthesizes emission data.

Sadykov, Viacheslav↗
NASA NTRS1988

A nonlinear least-squares inverse analysis of strike-slip faulting with application to the San Andreas fault

A nonlinear weighted least-squares analysis was performed for a synthetic elastic layer over a viscoelastic half-space model of strike-slip faulting. Also, an inversion of strain rate data was attempted for the locked portions of the San Andreas fault in California. Based on an eigenvector analysis of synthetic data, it is found that the only parameter which can be resolved is the average shear modulus of the elastic layer and viscoelastic half-space. The other parameters were obtained by performing a suite of inversions for the fault. The inversions on data from the northern San Andreas resulted in predicted parameter ranges similar to those produced by inversions on data from the whole fault.

Williams, Charles A.↗
NASA NTRS1981

Continuation of potential field data to a common altitude

It is noted that the distorsions introduced by the variation of distance between the sources and the measurement points can be important enough to create fake anomalies. The average amplitude of the anomalies at MAGSAT altitude is of the order of a few nT. Thus it is necessary to be careful in reducing MAGSAT data to a common elevation. The achievement of the corresponding anomaly map is of primary importance for the study of regional and long wave length anomalies. A method for the continuation of potential fields is described which consists in representing any harmonic function (in particular the anomaly is function of space coordinates) as a sum of elementary harmonic functions; the continuation being achieved by an inverse technique. Tests, made on a synthetic set of data, evaluate the method.

Lemouel, J. L.↗
NASA NTRS1978

Focusing effects in the synthetic aperture radar imaging of ocean waves

The paper derives the properties of the image obtained for an ocean wave whose cross section and surface profile are functions, representing the wave phenomena, whose exact properties are determined by the ocean wave surface properties, for ocean wavelength, height, and orbital frequency. The effect of defocusing of the wave image due to its temporal motion is calculated, and both the resolution of the radar system if no focus compensation is provided in the processor and the necessary distance the azimuth telescope has to be moved to provide diffraction-limited imaging are derived. These results are illustrated for data obtained by synthetic aperture radar during Hurricane Gloria on September 30, 1976, and by ERIM radar over Marineland, Florida, on December 15, 1975.

Jain, A.↗
NASA NTRS2019

Measured and Simulated Acoustic Signature of a Full-Scale Aircraft with Airframe Noise Reduction Technology Installed

Microphone phased-array and pole-mounted microphone data gathered during the NASA Acoustics Research Measurements flight tests were used to benchmark results from companion full-scale aeroacoustics simulations. Conducted with the lattice Boltzmann solver PowerFLOW®, the simulations predicted the acoustic behavior of various tested aircraft configurations. Emphasis was placed on those flown during the third flight test - a Fowler flap-equipped Gulfstream G-III with and without noise abatement technology on the main landing gear. Direct comparisons between experimental and synthetic microphone phasedarray data were achieved by applying the same processing and deconvolution technique to both sets of data. To extend the validation of the computations to the metric used for noise certification, the Effective Perceived Noise Level, a high-fidelity digital model of the nose landing gear, which was excluded from earlier computations, was developed and integrated into the G-III aircraft geometry. The acoustic study presented here demonstrates that the simulated beamform maps and corresponding integrated farfield spectra accurately predict the locations and strengths of the prominent airframe noise sources present on the G-III aircraft.

Khorrami, Mehdi R.↗
NASA NTRS1985

Multipolarization SAR data for surface feature delineation

This paper presents the techniques and the utility of multipolarization Synthetic Aperture Radar (SAR) data for surface feature delineation. Three channels of ratioed data (VV/HH, VH/HH, and VH/VV) are generated from the HH, VV, and VH polarization data (V = vertical, H = horizontal). The technique assumes redundancy of the VH and HV polarization and only VH polarization is used. The ratioed data are linearly stretched to yield a digital number within a range of 0 to 255. Based on the separability measure for two-class delineation, it was found that (1) the ratioed data resulted in a better delineation of surface features with high like (HH or VV) polarization digital number, and (2) the use of ratioed data provided further information not available from the original three-polarization data. The results suggest an advantage in using the ratioed data and the original three-polarization data for surface feature delineation.

Wu, S. T.↗
NASA NTRS1995

Bayes classification of interferometric TOPSAR data

We report the Bayes classification of terrain types at different sites using airborne interferometric synthetic aperture radar (INSAR) data. A Gaussian maximum likelihood classifier was applied on multidimensional observations derived from the SAR intensity, the terrain elevation model, and the magnitude of the interferometric correlation. Training sets for forested, urban, agricultural, or bare areas were obtained either by selecting samples with known ground truth, or by k-means clustering of random sets of samples uniformly distributed across all sites, and subsequent assignments of these clusters using ground truth. The accuracy of the classifier was used to optimize the discriminating efficiency of the set of features that was chosen. The most important features include the SAR intensity, a canopy penetration depth model, and the terrain slope. We demonstrate the classifier's performance across sites using a unique set of training classes for the four main terrain categories. The scenes examined include San Francisco (CA) (predominantly urban and water), Mount Adams (WA) (forested with clear cuts), Pasadena (CA) (urban with mountains), and Antioch Hills (CA) (water, swamps, fields). Issues related to the effects of image calibration and the robustness of the classification to calibration errors are explored. The relative performance of single polarization Interferometric data classification is contrasted against classification schemes based on polarimetric SAR data.

Michel, T. R.↗
NASA NTRS2011

Distributed Monitoring of the R(sup 2) Statistic for Linear Regression

The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more dependent target variables. This problem becomes challenging for large scale data in a distributed computing environment when only a subset of instances is available at individual nodes and the local data changes frequently. Data centralization and periodic model recomputation can add high overhead to tasks like anomaly detection in such dynamic settings. Therefore, the goal is to develop techniques for monitoring and updating the model over the union of all nodes data in a communication-efficient fashion. Correctness guarantees on such techniques are also often highly desirable, especially in safety-critical application scenarios. In this paper we develop DReMo a distributed algorithm with very low resource overhead, for monitoring the quality of a regression model in terms of its coefficient of determination (R2 statistic). When the nodes collectively determine that R2 has dropped below a fixed threshold, the linear regression model is recomputed via a network-wide convergecast and the updated model is broadcast back to all nodes. We show empirically, using both synthetic and real data, that our proposed method is highly communication-efficient and scalable, and also provide theoretical guarantees on correctness.

Bhaduri, Kanishka↗
NASA NTRS1978

Seasat-A opens new phase in earth observations

The data output of the Seasat-A, the first satellite designed specifically for oceanographic observation, is described. Wave height and direction, ice distribution, surface wind speed and direction, ocean-surface temperature, and atmospheric water content will be monitored by the satellite. Imaging radar, microwave scatterometer, microwave radiometer and visual and infrared radiometer experiments are included in the Seasat-A observing program. Two types of orbits have been developed: a near-repeat cycle of three days, and a near-repeat cycle of 25 days. Both orbit types offer fine coverage (18.5 km crossing separations) of the earth. Synthetic aperture radar data on computer-compatible tapes and geophysical data records available through the Seasat-A mission are described.

Cutting, E.↗
NASA NTRS2002

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated using both simulated and airborne data. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) satellite multi-frequency active and passive observations. These observations are characterized by various spatial and sampling resolutions. This makes the retrieval problem mathematically more difficult and ill-determined because the quality of information decreases with decreasing resolution. A model that, given reflectivity profiles and a small set of parameters (including the cloud water content, the intercept drop size distribution, and a variable describing the frozen hydrometeor properties), simulates high-resolution brightness temperatures is used. The high-resolution simulated brightness temperatures are convolved at the real sensor resolution. An optimal estimation procedure is used to minimize the differences between simulated and observed brightness temperatures. The retrieval technique is investigated using cloud model synthetic and airborne data from the Fourth Convection And Moisture Experiment. Simulated high-resolution brightness temperatures and reflectivities and airborne observation strong are convolved at the resolution of the TRMM instruments and retrievals are performed and analyzed relative to the reference data used in observations synthesis. An illustration of the possible use of the technique in satellite rainfall estimation is presented through an application to TRMM data. The study suggests improvements in combined active and passive retrievals even when the instruments resolutions are significantly different. Future work needs to better quantify the retrievals performance, especially in connection with satellite applications, and the uncertainty of the models used in retrieval.

Grecu, Mircea↗
NASA NTRS1992

The constitution of the atmospheric layers and the extreme ultraviolet spectrum of hot hydrogen-rich white dwarfs

An analysis is presented of the atmospheric properties of hot, H-rich, DA white dwarfs that is based on optical, UV, and X-ray observations aimed at predicting detailed spectral properties of these stars in the range 80-800 A. The divergences between observations from a sample of 15 hot DA white dwarfs emitting in the EUV/soft X-ray range and pure H synthetic spectra calculated from a grid of model atmospheres characterized by Teff and g are examined. Seven out of 15 DA stars are found to consistently exhibit pure hydrogen atmospheres, the remaining seven stars showing inconsistency between FUV and EUV/soft X-ray data that can be explained by the presence of trace EUV/soft X-ray absorbers. Synthetic data are computed assuming two other possible chemical structures: photospheric traces of radiatively levitated heavy elements and a stratified hydrogen/helium distribution. Predictions about forthcoming medium-resolution observations of the EUV spectrum of selected hot H-rich white dwarfs are made.

Vennes, Stephane↗
NASA NTRS2012

Study of Movement and Seepage Along Levees Using DINSAR and the Airborne UAVSAR Instrument

We have studied the utility of high resolution SAR (synthetic aperture radar) for levee monitoring using UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) data collected along the dikes and levees in California's Sacramento-San Joaquin Delta and along the lower Mississippi River. Our study has focused on detecting and tracking changes that are indicative of potential problem spots, namely deformation of the levees, subsidence along the levee toe, and seepage through the levees, making use of polarimetric and interferometric SAR techniques. Here was present some results of those studies, which show that high resolution, low noise SAR imaging could supplement more traditional ground-based monitoring methods by providing early indicators of seepage and deformation.

levee health↗
NASA NTRS1982

Automated preprocessing of spaceborne SAR data

An efficient algorithm has been developed for estimation of the echo phase delay in spaceborne synthetic aperture radar (SAR) data. This algorithm utilizes the spacecraft ephemeris data and the radar echo data to produce estimates of two parameters: (1) the centroid of the Doppler frequency spectrum f(d) and (2) the Doppler frequency rate. Results are presented from tests conducted with Seasat SAR data. The test data indicates that estimation accuracies of 3 Hz for f(d) and 0.3 Hz/sec for the Doppler frequency rate are attainable. The clutterlock and autofocus techniques used for estimation of f(d) and the Doppler frequency rate, respectively are discussed and the algorithm developed for optimal implementation of these techniques is presented.

Curlander, J. C.↗
NASA NTRS1986

Analysis of multiple incidence angle SIR-B data for determining forest stand characteristics

For the first time in the U.S. space program, digital synthetic aperture radar (SR) data were obtained from different incidence angles during Space Shuttle Mission 41-G. Shuttle Imaging Radar-B (SIR-B) data were obtained at incidence angles of 58 deg., 45 deg., and 28 deg., on October 9, 10, and 11, 1984, respectively, for a predominantly forested study area in northern Florida. Cloud-free LANDSAT Thematic Mapper (T.M.) data were obtained over the same area on October 12. The SIR-B data were processed and then digitally registered to the LANDSAT T.M. data by scientists at the Jet Propulsion Laboratory. This is the only known digitally registered SIR-B and T.M. data set for which the data were obtained nearly simultaneously. The data analysis of this information is discussed.

Hoffer, R. M.↗
NASA NTRS1987

Multipolarization SAR data for surface feature delineation and forest vegetation characterization

This paper presents the utility of multipolarization Synthetic Aperture Radar (SAR) data for surface feature delineation and forest vegetation characterization. Three channels of radioed data (VV/HH, VH/HH, and VH/VV) are generated from the HH, VV, and VH polarization data (V = vertical, H = horizontal). The radioed data are linearly stretched to yield a digital number within a range of 0 to 255. The techniques for reducing SAR speckle noise and for measuring the degree of separation are discussed. For surface feature delineation, the results indicate that cross polarization as well as cross polarization radioed data better delineate those surface features that are difficult to separate by like polarization data. The results suggest using a median value filtering technique to reduce within-plot data fluctuation to increase the separability measure. For forest vegetation characterization, the results indicate that multipolarization SAR data may be used to estimate forest properties such as total-tree biomass, basal area, and tree height.

Wu, Shih-Tseng↗