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Inguva, R.

Publications and source records attributed to Inguva, R..

Evolution of Local Microstructures: Spatial and Temporal Correlation in Clusters Undergoing 2-Dimensional Diffusion

Diffusion-limited, capillarity-driven, coarsening of precipitates is an important and intensively studied phenomenon. Coarsening can occur among several microstructural constituents ranging from the primary phases to widely dispersed precipitates. Moreover, coarsening of three-dimensional (3-D) phase domains, occurring via mass transport through a two-dimensional (2-D) diffusion field (called mixed-dimensional phase coarsening) is a cooperative phenomenon that is of practical importance, especially in thin film technologies and catalysis. A primary objective of our current work is to focus on the details of evolving microstructures through a study of 'island' formation in heteroepitaxial film/substrate systems. Whereas this work has been designed for space-based coarsening studies, which require long-duration quality microgravity to observe 3-D Ostwald ripening, a significant amount of work has been performed during ground-based studies to observe diffusional coarsening in a liquid-liquid two-phase system. We have performed the experiment at an isopycnic point to maximize exclusion of gravity-based system disturbance. This has allowed observations of 3-D droplets, immobilized by container wall contact, undergoing coarsening by 2-D diffusion for the required long times (approximately 4 months) using a holographic imaging technique. Although such systems may not be as reliant on long-duration microgravity processing as 3-D systems are, they are of direct relevance to so-called mixed-dimensional coarsening and to the study of heterostructures grown by thin-film technique

Curreri, Peter A.↗

Modeling the Effect of Vegetation on Passive Microwave Remote Sensing of Soil Moisture

The effect of vegetation on passive microwave remote sensing of soil moisture is studied. The radiative transfer modeling work of Njoku and Kong is applied to a stratified medium of which the upper layer is treated as a layer of vegetation. An effective dielectric constant for this vegetation layer is computed using estimates of the dielectric constant of individual components of the vegetation layer. The horizontally-polarized brightness temperature is then computed as a function of the incidence angle. Model predictions are used to compare with the data obtained in the Huntsville '96, remote sensing of soil moisture experiment, and with predictions obtained using a correction procedure of Jackson and Schmugge.

Liu, Y. P.↗

A statistical inference approach for the retrieval of the atmospheric ozone profile from simulated satellite measurements of solar backscattered ultraviolet radiation

NASA's Mission to Planet Earth (MTPE) will address important interdisciplinary and environmental issues such as global warming, ozone depletion, deforestation, acid rain, and the like with its long term satellite observations of the Earth and with its comprehensive Data and Information System. Extensive sets of satellite observations supporting MTPE will be provided by the Earth Observing System (EOS), while more specific process related observations will be provided by smaller Earth Probes. MTPE will use data from ground and airborne scientific investigations to supplement and validate the global observations obtained from satellite imagery, while the EOS satellites will support interdisciplinary research and model development. This is important for understanding the processes that control the global environment and for improving the prediction of events. In this paper we illustrate the potential for powerful artificial intelligence (AI) techniques when used in the analysis of the formidable problems that exist in the NASA Earth Science programs and of those to be encountered in the future MTPE and EOS programs. These techniques, based on the logical and probabilistic reasoning aspects of plausible inference, strongly emphasize the synergetic relation between data and information. As such, they are ideally suited for the analysis of the massive data streams to be provided by both MTPE and EOS. To demonstrate this, we address both the satellite imagery and model enhancement issues for the problem of ozone profile retrieval through a method based on plausible scientific inferencing. Since in the retrieval problem, the atmospheric ozone profile that is consistent with a given set of measured radiances may not be unique, an optimum statistical method is used to estimate a 'best' profile solution from the radiances and from additional a priori information.

Bonavito, N. L.↗

High spatial resolution restoration of IRAS images

A general technique to improve the spatial resolution of the IRAS AO data was developed at The Aerospace Corporation using the Maximum Entropy algorithm of Skilling and Gull. The technique has been applied to a variety of fields and several individual AO MACROS. With this general technique, resolutions of 15 arcsec were achieved in 12 and 25 micron images and 30 arcsec in 60 and 100 micron images. Results on galactic plane fields show that both photometric and positional accuracy achieved in the general IRAS survey are also achieved in the reconstructed images.

Grasdalen, Gary L.↗

Propane spectral resolution enhancement by the maximum entropy method

The Burg algorithm for maximum entropy power spectral density estimation is applied to a time series of data obtained from a Michelson interferometer and compared with a standard FFT estimate for resolution capability. The propane transmittance spectrum was estimated by use of the FFT with a 2 to the 18th data sample interferogram, giving a maximum unapodized resolution of 0.06/cm. This estimate was then interpolated by zero filling an additional 2 to the 18th points, and the final resolution was taken to be 0.06/cm. Comparison of the maximum entropy method (MEM) estimate with the FFT was made over a 45/cm region of the spectrum for several increasing record lengths of interferogram data beginning at 2 to the 10th. It is found that over this region the MEM estimate with 2 to the 16th data samples is in close agreement with the FFT estimate using 2 to the 18th samples.

Bonavito, N. L.↗