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NASA NTRS1988

Neural networks with hierarchically correlated patterns

The Hopfield model of neural networks is extended to allow for the storage and retrieval of hierarchically correlated patterns. The overlaps between these patterns form an ultrametric tree. Intermediate states, which serve as ancestors for the following levels, are generated at each level of the tree. The states belonging to each level are stored, by a modified learning rule, in a series of identical networks, one for each level. The retrieval of a particular pattern is preceded and assisted by the successive retrieval of its ancestors. The performance of this scheme is studied analytically and numerically.

Gutfreund, H.↗
NASA NTRS2016

Investigation of Optimal Digital Image Correlation Patterns for Deformation Measurement

Digital image correlation (DIC) relies on the surface texture of a specimen to measure deformation. When the specimen itself has little or no texture, a pattern is applied to the surface which deforms with the specimen and acts as an artificial surface texture. Because the applied pattern has an effect on the accuracy of DIC, an ideal pattern is sought for which the error introduced into DIC measurements is minimal. In this work, a study is performed in which several DIC pattern quality metrics from the literature are correlated to DIC measurement error. The resulting correlations give insight on the optimality of DIC patterns in general. Optimizations are then performed to produce patterns which are well suited for DIC. These patterns are tested to show their relative benefits. Chief among these benefits are a reduction in error of approximately 30 with respect to a randomly generated pattern.

Bomarito, G. F.↗
NASA NTRS2011

Global Multi-Year O3-CO Correlation Patterns from Models and TES Satellite Observations

The correlation between measured tropospheric ozone (O3) and carbon monoxide (CO) has been used extensively in tropospheric chemistry studies to explore the photochemical characteristics of different regions and to evaluate the ability of models to capture these characteristics. Here, we present the first study that uses multi-year, global, vertically resolved, simultaneous and collocated O3 and CO satellite (Tropospheric Emission Spectrometer) measurements, to determine this correlation in the middle/lower free troposphere for two different seasons, and to evaluate two chemistry-climate models. We find results that are fairly robust across different years, altitudes and timescales considered, which indicates that the correlation maps presented here could be used in future model evaluations. The highest positive correlations (around 0.8) are found in the northern Pacific during summer, which is a common feature in the observations and the G-PUCCINI model. We make quantitative comparisons between the models using a single-figure metric (C), which we define as the correlation coefficient between the modeled and the observed O3-CO correlations for different regions of the globe. On a global scale, the G-PUCCINI model shows a good performance in the summer (C =0.71) and a satisfactory performance in the winter (C = 0.52). It captures midlatitude features very well, especially in the summer, whereas the performance in regions like South America or Central Africa is weaker. The UKCA model (C = 0.46/0.15 for July-August/December-January on a global scale) performs better in certain regions, such as the tropics in winter, and it captures some of the broad characteristics of summer extratropical correlations, but it systematically underestimates the O3-CO correlations over much of the globe. It is noteworthy that the correlations look very different in the two models, even though the ozone distributions are similar. This demonstrates that this technique provides a powerful global constraint for understanding modeled tropospheric chemical processes. We investigated the sources of the correlations by performing a series of sensitivity experiments. In these, the sign of the correlation is, in most cases, insensitive to removing different individual emissions, but its magnitude changes downwind of emission regions when applying such perturbations. Interestingly, we find that the O3-CO correlation does not solely reflect the strength of O3 photochemical production, as often assumed by earlier studies, but is more complicated and may reflect a mixture of different processes such as transport.

Voulgarakis, A.↗
NASA NTRS2016

Image Correlation Pattern Optimization for Micro-Scale In-Situ Strain Measurements

The accuracy and precision of digital image correlation (DIC) is a function of three primary ingredients: image acquisition, image analysis, and the subject of the image. Development of the first two (i.e. image acquisition techniques and image correlation algorithms) has led to widespread use of DIC; however, fewer developments have been focused on the third ingredient. Typically, subjects of DIC images are mechanical specimens with either a natural surface pattern or a pattern applied to the surface. Research in the area of DIC patterns has primarily been aimed at identifying which surface patterns are best suited for DIC, by comparing patterns to each other. Because the easiest and most widespread methods of applying patterns have a high degree of randomness associated with them (e.g., airbrush, spray paint, particle decoration, etc.), less effort has been spent on exact construction of ideal patterns. With the development of patterning techniques such as microstamping and lithography, patterns can be applied to a specimen pixel by pixel from a patterned image. In these cases, especially because the patterns are reused many times, an optimal pattern is sought such that error introduced into DIC from the pattern is minimized. DIC consists of tracking the motion of an array of nodes from a reference image to a deformed image. Every pixel in the images has an associated intensity (grayscale) value, with discretization depending on the bit depth of the image. Because individual pixel matching by intensity value yields a non-unique scale-dependent problem, subsets around each node are used for identification. A correlation criteria is used to find the best match of a particular subset of a reference image within a deformed image. The reader is referred to references for enumerations of typical correlation criteria. As illustrated by Schreier and Sutton and Lu and Cary systematic errors can be introduced by representing the underlying deformation with under-matched shape functions. An important implication, as discussed by Sutton et al., is that in the presence of highly localized deformations (e.g., crack fronts), error can be reduced by minimizing the subset size. In other words, smaller subsets allow the more accurate resolution of localized deformations. Contrarily, the choice of optimal subset size has been widely studied and a general consensus is that larger subsets with more information content are less prone to random error. Thus, an optimal subset size balances the systematic error from under matched deformations with random error from measurement noise. The alternative approach pursued in the current work is to choose a small subset size and optimize the information content within (i.e., optimizing an applied DIC pattern), rather than finding an optimal subset size. In the literature, many pattern quality metrics have been proposed, e.g., sum of square intensity gradient (SSSIG), mean subset fluctuation, gray level co-occurrence, autocorrelation-based metrics, and speckle-based metrics. The majority of these metrics were developed to quantify the quality of common pseudo-random patterns after they have been applied, and were not created with the intent of pattern generation. As such, it is found that none of the metrics examined in this study are fit to be the objective function of a pattern generation optimization. In some cases, such as with speckle-based metrics, application to pixel by pixel patterns is ill-conditioned and requires somewhat arbitrary extensions. In other cases, such as with the SSSIG, it is shown that trivial solutions exist for the optimum of the metric which are ill-suited for DIC (such as a checkerboard pattern). In the current work, a multi-metric optimization method is proposed whereby quality is viewed as a combination of individual quality metrics. Specifically, SSSIG and two auto-correlation metrics are used which have generally competitive objectives. Thus, each metric could be viewed as a constraint imposed upon the others, thereby precluding the achievement of their trivial solutions. In this way, optimization produces a pattern which balances the benefits of multiple quality metrics. The resulting pattern, along with randomly generated patterns, is subjected to numerical deformations and analyzed with DIC software. The optimal pattern is shown to outperform randomly generated patterns.

Bomarito, G. F.↗
NASA NTRS1973

Sediment pattern correlation with inflow and tidal action

The author has identified the following significant results. At the time the two scenes of the Chesapeake Bay Study Area were taken, ground truth data were taken at a number of stations within each of the test areas. Where local conditions permitted, either all or a part of the following parameters were measured: water temperature, spectral transmittance, conductivity, turbidity, dissolved oxygen, current velocity, and pH. In addition, a sample of water was taken at each location and the concentration of suspended material in each sample was determined. In the analysis the relationship of each measured parameter and the corresponding radiance values (reflectance spectrum) detected by the ERTS-1 were evaluated. Thus far, the analysis has shown a good correlation with concentrations of suspended material contained in the water.

Grabau, W. E.↗
NASA NTRS1985

Aerosol pattern correlation techniques of wind measurement

This paper reviews the current status of lidar image correlation techniques of remote wind measurement. It also examines the potential use of satellite borne lidar global wind measurements using this approach. Lidar systems can easily detect spatial variations in the volume scattering cross section of naturally occurring aerosols. Lidar derived RHI, PPI and range-time displays of aerosol backscatter have been extensively employed in the study of atmospheric structure. Descriptions of this type of data can be obtained in many references including Kunkel et al. (1977), Kunkel et al. (1980), Boers et al. (1984), Uthe et al. (1980), Melfi et al. (1985) and Browell et al. (1983). It is likely that the first space-borne lidars for atmospheric studies will observe aerosol backscatter to measure parameters such as boundary layer depth and cloud height. This paper examines the potential application of these relatively simple aerosol backscatter lidars to global wind measurements.

Eloranta, Edwin W.↗
NASA NTRS1986

Quasi-stationary states in the Southern Hemisphere

Pattern correlations between daily anomalies have been used to study the persistence of the Southern Hemisphere circulations. The dataset consists of daily Australian analyses of 500 mb heights and sea level pressure for the period from 1972 to 1983. Compared to the Northern Hemisphere, the pattern correlations are much lower and more variable in the Southern Hemisphere. The mean one-day lag autocorrelation is only 0.57, compared to 0.81 in the Northern Hemisphere. The correlations increase significantly for the filtered anomalies, which consist of the planetary wavenumbers from 0 to 4. Subjective criteria based on the pattern correlations are used to select quasi-stationary events. A series of 5 or more daily maps is defined to be quasi-stationary if the pattern correlations between all pairs of five consecutive maps in this time series are larger than or equal to 0.5. In winter, quasi-stationary events can be classified in terms of wavenumbers. Waves 3 and 4 are by far the dominant waves. More than half of the events have large wave 3 amplitude with geographically fixed orientations.

Mo, K. C.↗
NASA NTRS1985

Quasi Stationary States in the Southern Hemisphere

Pattern correlations between daily anomalies (Horel 1984) were used to study the persistency of the Southern Hemisphere circulations. The data set consists of the daily Australian analyses of 500 mb heights and sea level pressure for the period from 1972 and 1983. Compared to the Northern Hemisphere, the pattern correlations are much smaller and more variable in the Southern Hemisphere. The mean one day lag is only 0.57, (0.82 for the NH). The correlations increase significantly for the filtered anomalies which consist of the long planetary waves from 0 to 4. Subjective criteria based on the pattern correlations are used to select the quasi stationary events. A series of 5 or more daily maps is quasi stationary if the pattern correlations between all consecutive pairs of maps in this time series are larger or equal to 0.5.

Mo, K. C.↗
NASA NTRS1991

Optical Correlation

Pattern recognition may supplement or replace certain navigational aids on spacecraft in docking or landing activities. The need to correctly identify terrain features remains critical in preparation of autonomous planetary landing. One technique that may solve this problem is optical correlation. Correlation has been successfully demonstrated under ideal conditions; however, noise significantly affects the ability of the correlator to accurately identify input signals. Optical correlation in the presence of noise must be successfully demonstrated before this technology can be incorporated into system design. An optical correlator is designed and constructed using a modified 2f configuration. Liquid crystal televisions (LCTV) are used as the spatial light modulators (SLM) for both the input and filter devices. The filter LCTV is characterized and an operating curve is developed. Determination of this operating curve is critical for reduction of input noise. Correlation of live input with a programmable filter is demonstrated.

Cotariu, Steven S.↗
NASA NTRS1979

Programmable charge-coupled device /CCD/ correlator for pattern classification

The potential use of charge coupled device (CCD) programmable digital/analog correlators for multispectral data classification is discussed. CCD digital/analog correlator technology and the experimental evaluation of a 32-stage 4-bit test device are presented. The design of an IC for use in a multispectral classification system for 16 sensors and 8 bit accuracy is reviewed.

Mayer, D. J.↗
NASA NTRS1968

Predicted vibration responses of Apollo structure and effects of pressure correlation lengths on response

Progressive wove and reverberant acoustic fields ore often used in the laboratory for qualification testing of aerospace structures that are subjected to unsteady aerodynamic environments which occur during flight through the atmosphere. Acoustic simulation of these in-flight environments i s achieved i f the structural vibration response to acoustic excitation is equivalent, over the frequency range of interest, to the response caused by aerodynamic turbulence. To determine the degree of response simulation that could be expected for such qualification testing of the Apollo Spacecraft, responses of a segment of the Apollo structure were estimated theoretically for both acoustic and flight environments. The vibration analysis presented in this report was performed for the Spacecraft Lunar Module Adaptor; and the three environments treated are turbulence at Mach 1 and Mach 2, a reverberant acoustic field, and a modified acoustic progressive wave field. The progressive wave field is assumed to be generated within a specially designed shroud of sixteen axially oriented ducts which is constructed around and contoured to the external skin of the vehicle. Each duct is open on the side adjacent to the skin and is driven acoustically at one end by an independent noise source, thus allowing for different pressure correlation patterns around the circumference of the vehicle. The purpose of the analysis was to determine the effects of surface pressure correlation lengths on the response characteristics of representative Apollo structure, and to select on this basis, the optimum acoustic environment for structural vibration qualification tests of the Apollo in the Spacecraft Acoustic Laboratory at MSC. The method of analysis employed consists of determining, independently, the space average, mean-square acceleration spectral density for each of the significant modes of vibration of an equivalent cylindrical shell, and then expressing the total structural response as a linear summation of these modal responses. Approximately 570 classical modes of a pinned-end cylinder were used in order to find the spectral response characteristics of the structure throughout the frequency range of 10 - 1,000 Hz. The effective forcing functions or joint acceptances of the various modes of vibration were computed and are presented graphically for each of the pressure excitation environments. A brief development of the response equations used is presented in the report. Space average acceleration response spectra were computed for twelve different cases including aerodynamic turbulence at Mach 1 and Mach 2, reverberant acoustic field, five duct correlation patterns, two cases of an axially damped progressive wave field, and two cases in which the structural damping constant was varied from the expected value. The response spectra were computed and plotted by a high speed digital computer far a flat excitation pressure spectrum; and the response spectra were numerically integrated to give one-third octave bond average responses. A complete set of digital computer programs has been developed for both flat plate and cylindrical shell structures for the above environments, and each requires run times of three minutes or less. Thus, the work presented herein, along with the results, constitutes a practical advancement to the existing state-of-the-art of vibration prediction.

R W White↗