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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 NTRS1978

Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery

The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.

Williams, D. L.↗

DOE OSTI2025

Image-Driven Hybrid Structural Analysis Based on Continuum Point Cloud Method with Boundary Capturing Technique

Conventional approaches for the structural health monitoring of infrastructures often rely on physical sensors or targets attached to structural members, which require considerable preparation, maintenance, and operational effort, including continuous on-site adjustments. This paper presents an image-driven hybrid structural analysis technique that combines digital image processing (DIP) and regression analysis with a continuum point cloud method (CPCM) built on a particle-based strong formulation. Polynomial regressions capture the boundary shape change due to the structural loading and precisely identify the edge and corner coordinates of the deformed structure. The captured edge profiles are transformed into essential boundary conditions. This allows the construction of a strongly formulated boundary value problem (BVP), classified as the Dirichlet problem. Capturing boundary conditions from the digital image is novel, although a similar approach was applied to the point cloud data. It was shown that the CPCM is more efficient in this hybrid simulation framework than the weak-form-based numerical schemes. Unlike the finite element method (FEM), it can avoid aligning boundary nodes with regression points. A three-point bending test of a rubber beam was simulated to validate the developed technique. The simulation results were benchmarked against numerical results by ANSYS and various relevant numerical schemes. The technique can effectively solve the Dirichlet-type BVP, yielding accurate deformation, stress, and strain values across the entire problem domain when employing a linear strain model and increasing the number of CPCM nodes. In addition, comparative analysis with conventional displacement tracking techniques verifies the developed technique’s robustness. The proposed technique effectively circumvents the inherent limitations of traditional monitoring methods resulting from the reliance on physical gauges or target markers so that a robust and non-contact solution for remote structural health monitoring in real-scale infrastructures can be provided, even in unfavorable experimental environments.

Chemistry↗

NASA NTRS1994

Stereo imaging velocimetry for microgravity applications

Stereo imaging velocimetry is the quantitative measurement of three-dimensional flow fields using two sensors recording data from different vantage points. The system described in this paper, under development at NASA Lewis Research Center in Cleveland, Ohio, uses two CCD cameras placed perpendicular to one another, laser disk recorders, an image processing substation, and a 586-based computer to record data at standard NTSC video rates (30 Hertz) and reduce it offline. The flow itself is marked with seed particles, hence the fluid must be transparent. The velocimeter tracks the motion of the particles, and from these we deduce a multipoint (500 or more), quantitative map of the flow. Conceptually, the software portion of the velocimeter can be divided into distinct modules. These modules are: camera calibration, particle finding (image segmentation) and centroid location, particle overlap decomposition, particle tracking, and stereo matching. We discuss our approach to each module, and give our currently achieved speed and accuracy for each where available.

Miller, Brian B.↗

NASA NTRS1997

Optical Verification Laboratory Demonstration System for High Security Identification Cards

Document fraud including unauthorized duplication of identification cards and credit cards is a serious problem facing the government, banks, businesses, and consumers. In addition, counterfeit products such as computer chips, and compact discs, are arriving on our shores in great numbers. With the rapid advances in computers, CCD technology, image processing hardware and software, printers, scanners, and copiers, it is becoming increasingly easy to reproduce pictures, logos, symbols, paper currency, or patterns. These problems have stimulated an interest in research, development and publications in security technology. Some ID cards, credit cards and passports currently use holograms as a security measure to thwart copying. The holograms are inspected by the human eye. In theory, the hologram cannot be reproduced by an unauthorized person using commercially-available optical components; in practice, however, technology has advanced to the point where the holographic image can be acquired from a credit card-photographed or captured with by a CCD camera-and a new hologram synthesized using commercially-available optical components or hologram-producing equipment. Therefore, a pattern that can be read by a conventional light source and a CCD camera can be reproduced. An optical security and anti-copying device that provides significant security improvements over existing security technology was demonstrated. The system can be applied for security verification of credit cards, passports, and other IDs so that they cannot easily be reproduced. We have used a new scheme of complex phase/amplitude patterns that cannot be seen and cannot be copied by an intensity-sensitive detector such as a CCD camera. A random phase mask is bonded to a primary identification pattern which could also be phase encoded. The pattern could be a fingerprint, a picture of a face, or a signature. The proposed optical processing device is designed to identify both the random phase mask and the primary pattern [1-3]. We have demonstrated experimentally an optical processor for security verification of objects, products, and persons. This demonstration is very important to encourage industries to consider the proposed system for research and development.

Javidi, Bahram↗

NASA NTRS2003

Processing Digital Imagery to Enhance Perceptions of Realism

Multi-scale retinex with color restoration (MSRCR) is a method of processing digital image data based on Edwin Land s retinex (retina + cortex) theory of human color vision. An outgrowth of basic scientific research and its application to NASA s remote-sensing mission, MSRCR is embodied in a general-purpose algorithm that greatly improves the perception of visual realism and the quantity and quality of perceived information in a digitized image. In addition, the MSRCR algorithm includes provisions for automatic corrections to accelerate and facilitate what could otherwise be a tedious image-editing process. The MSRCR algorithm has been, and is expected to continue to be, the basis for development of commercial image-enhancement software designed to extend and refine its capabilities for diverse applications.

Woodell, Glenn A.↗

NASA NTRS2022

A Dynamic Landslide Hazard Monitoring Framework for the Lower Mekong Region

The Lower Mekong region is one of the most landslide-prone areas of the world. Despite the need for dynamic characterization of landslide hazard zones within the region, it is largely understudied for several reasons. Dynamic and integrated understanding of landslide processes requires landslide inventories across the region, which have not been available previously. Computational limitations also hamper regional landslide hazard assessment, including accessing and processing remotely sensed information. Finally, open-source software and modelling packages are required to address regional landslide hazard analysis. Leveraging an open-source data-driven global Landslide Hazard Assessment for Situational Awareness model framework, this study develops a region-specific dynamic landslide hazard system leveraging satellite-based Earth observation data to assess landslide hazards across the lower Mekong region. A set of landslide inventories were prepared from high-resolution optical imagery using advanced image-processing techniques. Several static and dynamic explanatory variables (i.e., rainfall, soil moisture, slope, relief, distance to roads, distance to faults, distance to rivers) were considered during the model development phase. An extreme gradient boosting decision tree model was trained for the monsoon period of 2015–2019 and the model was evaluated with independent inventory information for the 2020 monsoon period. The model performance demonstrated considerable skill using receiver operating characteristic curve statistics, with Area Under the Curve values exceeding 0.95. The model architecture was designed to use near-real-time data, and it can be implemented in a cloud computing environment (i.e., Google Cloud Platform) for the routine assessment of landslide hazards in the Lower Mekong region. This work was developed in collaboration with scientists at the Asian Disaster Preparedness Center as part of the NASA SERVIR Program’s Mekong hub. The goal of this work is to develop a suite of tools and services on accessible open-source platforms that support and enable stakeholder communities to better assess landslide hazard and exposure at local to regional scales for decision making and planning.

Nishan Kumar Biswas↗

NASA NTRS1989

An imaging vector magnetograph for the next solar maximum

Researchers describe the conceptual design of a new imaging vector magnetograph currently being constructed at the University of Hawaii. The instrument combines a modest solar telescope with a rotating quarter-wave plate, an acousto-optical tunable prefilter as a blocker for a servo-controlled Fabry-Perot etalon, CCD cameras, and on-line digital image processing. Its high spatial resolution (1/2 arcsec pixel size) over a large field of view (5 by 5 arcmin) will be sufficient to significantly measure, for the first time, the magnetic energy dissipated in major solar flares. Its millisecond tunability and wide spectral range (5000 to 7000 A) enable nearly simultaneous vector magnetic field measurements in the gas-pressure-dominated photosphere and magnetically-dominated chromosphere, as well as effective co-alignment with Solar-A's X ray images. Researchers expect to have the instrument in operation at Mees Solar Observatory (Haleakala) in early 1991. They have chosen to use tunable filters as wavelength-selection elements in order to emphasize the spatial relationships between magnetic field elements, and to permit construction of a compact, efficient instrument. This means that spectral information must be obtained from sequences of images, which can cause line profile distortions due to effects of atmospheric seeing.

Mickey, D. L.↗

NASA NTRS1992

Thermographic characterization of stress during crack growth

A full-field-thermographic technique for imaging stress patterns in dynamically loaded structures using general purpose IR imaging and image processing hardware is described. The inspection technique is based on the thermoelastic effect. A simple geometry is examined, and the experimentally determined values for the stress invariant are shown to be consistent with theoretical and numerical calculations. The application of full-field-thermographic measurement would ensure that the observed stress field has a common sampling period, thus allowing the observation of rapidly occurring stress anomalies such as the propagation of a fatigue crack. Fatigue crack propagation in two consecutive thermoelastic stress images from an aluminum sample is shown.

Cramer, K. E.↗

NASA NTRS2012

Mechanism of Water Droplet Breakup Near the Leading Edge of an Airfoil

This work presents results of an experimental study on droplet deformation and breakup near the leading edge of an airfoil. The experiment was conducted in the rotating rig test cell at the Instituto Nacional de Tecnica Aeroespacial (INTA) in Madrid, Spain. The airfoil model was placed at the end of the rotating arm and a monosize droplet generator produced droplets that fell from above, perpendicular to the path of the airfoil. The interaction between the droplets and the airfoil was captured with high speed imaging and allowed observation of droplet deformation and breakup as the droplet approached the airfoil near the stagnation line. Image processing software was used to measure the position of the droplet centroid, equivalent diameter, perimeter, area, and the major and minor axes of an ellipse superimposed over the deforming droplet. The horizontal and vertical displacement of each droplet against time was also measured, and the velocity, acceleration, Weber number, Bond number, Reynolds number, and the drag coefficients were calculated along the path of the droplet to the beginning of breakup. Droplet deformation is defined and studied against main parameters. The high speed imaging allowed observation of the actual mechanism of breakup and identification of the sequence of configurations from the initiation of the breakup to the disintegration of the droplet. Results and comparisons are presented for droplets of diameters in the range of 500 to 1800 microns, and airfoil velocities of 70 and 90 m/sec.

Vargas, Mario↗

NASA NTRS2012

Mechanism of Water Droplet Breakup near the Leading Edge of an Airfoil

This work presents results of an experimental study on droplet deformation and breakup near the leading edge of an airfoil. The experiment was conducted in the rotating rig test cell at the Instituto Nacional de T cnica Aeroespacial (INTA) in Madrid, Spain. The airfoil model was placed at the end of the rotating arm and a monosize droplet generator produced droplets that fell from above, perpendicular to the path of the airfoil. The interaction between the droplets and the airfoil was captured with high speed imaging and allowed observation of droplet deformation and breakup as the droplet approached the airfoil near the stagnation line. Image processing software was used to measure the position of the droplet centroid, equivalent diameter, perimeter, area, and the major and minor axes of an ellipse superimposed over the deforming droplet. The horizontal and vertical displacement of each droplet against time was also measured, and the velocity, acceleration, Weber number, Bond number, Reynolds number, and the drag coefficients were calculated along the path of the droplet to the beginning of breakup. Droplet deformation is defined and studied against main parameters. The high speed imaging allowed observation of the actual mechanism of breakup and identification of the sequence of configurations from the initiation of the breakup to the disintegration of the droplet. Results and comparisons are presented for droplets of diameters in the range of 500 to 1800 micrometers, and airfoil velocities of 70 and 90 meters/second.

Vargas, Mario↗

NASA NTRS1975

Mission operations and data systems

A communications system for performing the basic functions of mission operations, orbit and attitude determination, and data processing is described. A block diagram is provided to show the relationships of these functions with the spacecraft in orbit and the experiments to be conducted on board the spacecraft. Specific areas of application are discussed as follows: (1) software operating systems for the ATS-F satellite testing and ground support, (2) inversion of the RAE-1 satellite (Explorer 38 satellite) in orbit, (3) ALSEP differential Doppler tracking, (4) minitrack calibration using satellite data, (5) angles-only orbit extraction, and (6) image processing system performance prediction and product quality evaluation techniques. Block diagrams of the various systems are provided to show the steps involved in the operations.

Source record↗

NASA NTRS1982

Antimisting kerosene atomization and flammability

Various parameters found to affect the flammability of antimisting kerosene (Jet A + polymer additive) are investigated. Digital image processing was integrated into a technique for measurement of fuel spray characteristics. This technique was developed to avoid many of the error sources inherent to other spray assessment techniques and was applied to the study of engine fuel nozzle atomization performance with Jet A and antimisting fuel. Aircraft accident fuel spill and ignition dynamics were modeled in a steady state simulator allowing flammability to be measured as a function of airspeed, fuel flow rate, fuel jet Reynolds number and polymer concentration. The digital imaging technique was employed to measure spray characteristics in this simulation and these results were related to flammability test results. Scaling relationships were investigated through correlation of experimental results with characteristic dimensions spanning more than two orders of magnitude.

Fleeter, R.↗

NASA NTRS1993

Geographic information system for fusion and analysis of high-resolution remote sensing and ground data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System (GIS), integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a boreal forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case 1) calibrated DC-8 SAR (Synthetic Aperture Radar) data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case 2) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗

NASA NTRS1997

A quantitative assay for intercellular aggregation

In an earlier communication (Munn et al., J Immunol. Methods 166: 11-25, 1993), we presented the initial development of a quantitative assay for monitoring the rates of cellular aggregation based on digital image processing and video microscopy. This study describes some important enhancements and modifications to the procedure. A new index is introduced to characterize the three-dimensional morphology of the aggregates. This index is based on temporal changes in the projected area of the cells and cell aggregates during the course of the experiment. By drawing an analogy with the kinetic theory of gases, we have also introduced a procedure to normalize for variations in cell seeding density among different experiments. In addition, the image analysis technique has been improved by introducing a background subtraction algorithm to remove illumination defects and an adaptive segmentation procedure. These improvements allowed us to completely automate the image analysis procedure, thus minimizing user intervention and improving the reproducibility of the measurements. The enhanced visual assay is evaluated using some recent results from our studies on homotypic lymphocyte aggregation.

Non-NASA Center↗

NASA NTRS1992

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System, integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a bore Al forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case I) calibrated DC-8 SAR data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case II) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗

NASA NTRS1993

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Lure, Y. M. Fleming↗

DOE OSTI2020

Deep Learning for Intelligent Bubble Size Detection in the Spallation Neutron Source Visual Target

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) will undergo proton power upgrade (PPU), increasing the proton beam power from 1.4 MW to 2.8 MW. From 2.8 MW, 2.0 MW will go to the current First Target Station and the rest will go to the future Second Target Station (STS). The First Target Station uses a liquid mercury target that is contained in a 316L stainless steel vessel. The proton beam is pulsed at 60 Hz, with a pulse of about 0.7μs. When the proton beam hits the target, the intense energy deposition leads to a rapid rise in temperature in the mercury. This temperature rise creates pressure waves that propagate through the mercury and cause cavitation erosion. The power upgrade will cause stronger pressure waves that will further increase damage because of cavitation. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at 1.4 MW. However, at higher power, additional mitigation is necessary. Therefore, the 2 MW target vessel will be equipped with swirl bubblers and an additional gas injection port near the nose to inject more gas in the target. To develop a gas injection strategy and design, flow visualization in water with a transparent prototypical target (“visual target”) was performed. Bubble sizes and their spatial distribution in the flow loop are crucial to understanding the effectiveness of the bubbles in mitigating pressure waves. Bubbles were generated in the visual target under varied conditions of input pressures with helium and air. Images were captured using a high-speed camera at varied frame rates at different positions away from the swirl bubbler and different depths in the flow loop under varying lighting conditions. Initially, methods such as circular Hough transforms were applied after a series of images processing to obtain a general distribution of bubble sizes. Bubbles smaller than 500 μm are preferred to effectively mitigate the effect of pressure waves, which demands an accurate bubble detection and sizing system. Intelligent detection and identification of bubble sizes alleviate misdetection and improves accuracies. Employing neural networks, intelligent detection of bubble sizes and their distribution was developed and provides a robust alternative to traditional techniques. Human intervention was employed to label in-focus and out-of-focus bubbles in the set of training images. An object detection network using a pretrained convolutional neural network was created that extracted the features from the training images. Data augmentation was used to improve network accuracy through a random transformation of the original data.

Rasheed, Fayaz↗

NASA NTRS1985

Observations of E and F region Mg(+) from Spacelab 1

Images of airglow at 2800 A were taken on the Spacelab 1 Shuttle mission and have been interpreted to be solar resonant emission of magnesium ions. On two orbital passes, observations were made near the magnetic equator while observing in the 2800-A channel. The observations were made near the sunset terminator (approximately 1800 LT), in winter (1983, day 335). Three separate emission clouds were observed, all of which extended well into the F region. The location of the clouds in horizontal space is shown. The processed images have been pseudocolored to highlight the intensity distribution in the clouds. Observations included clouds with apparent magnetic-field aligned striations. Bright emissions were observed at the magnetic equator, at 12-deg north magnetic latitude, and at 12-deg south magnentic latitude. Cloud-center brightnesses varied between 680 rayleighs and 1700 rayleighs.

Mende, S. B.↗