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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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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

An Advanced Approach to Simultaneous Monitoring of Multiple Bacteria in Space

The utility of a novel microarray-based microbial analyzer was demonstrated by the rapid detection, imaging, and identification of a mixture of microorganisms found in a waste water sample from the Lunar-Mars Life Support Test Project through the synergistic combination of: (1) judicious RNA probe selection via algorithms developed by University of Houston scientists; (2) tuned surface chemistries developed by Baylor College of Medicine scientists to facilitate hybridization of rRNA targets to DNA probes under very low salt conditions, thereby minimizing secondary structure; and (3) integration of the microarray printing and detection/imaging instrumentation by Genometrix to complete the quantitative analysis of microorganism mixtures.

Eggers, M.↗
NASA NTRS1994

The Visibility of DCT Quantization Noise: Spatial Frequency Summation

Computational models of the ability to detect image compression artifacts facilitate the optimization of compression parameters, such as the JPEG quantization matrix. For simplicity, some models assume that the visibility of artifacts containing different spatial frequency components is determined by the most visible component, that is, no summation over components. Using the type of noise generated by quantization in the Discrete Cosine Transform (DCT) domain, we find a degree of summation between that of probability summation and contrast energy summation.

Peterson, H. A.↗
NASA NTRS2007

Imaging Spectrometer on a Chip

A proposed visible-light imaging spectrometer on a chip would be based on the concept of a heterostructure comprising multiple layers of silicon-based photodetectors interspersed with long-wavelength-pass optical filters. In a typical application, this heterostructure would be replicated in each pixel of an image-detecting integrated circuit of the active-pixel-sensor type (see figure). The design of the heterostructure would exploit the fact that within the visible portion of the spectrum, the characteristic depth of penetration of photons increases with wavelength. Proceeding from the front toward the back, each successive long-wavelength-pass filter would have a longer cutoff wavelength, and each successive photodetector would be made thicker to enable it to absorb a greater proportion of incident longer-wavelength photons. Incident light would pass through the first photodetector and encounter the first filter, which would reflect light having wavelengths shorter than its cutoff wavelength and pass light of longer wavelengths. A large portion of the incident and reflected shorter-wavelength light would be absorbed in the first photodetector. The light that had passed through the first photodetector/filter pair of layers would pass through the second photodetector and encounter the second filter, which would reflect light having wavelengths shorter than its cutoff wavelength while passing light of longer wavelengths. Thus, most of the light reflected by the second filter would lie in the wavelength band between the cutoff wavelengths of the first and second filters. Thus, further, most of the light absorbed in the second photodetector would lie in this wavelength band. In a similar manner, each successive photodetector would detect, predominantly, light in a successively longer wavelength band bounded by the shorter cutoff wavelength of the preceding filter and the longer cutoff wavelength of the following filter.

Wang, Yu↗
NASA NTRS2009

Amazing Science from NASA's Chandra X-Ray Observatory

NASA s Chandra X-ray Observatory made its first observations one decade ago. With unprecedented capability to detect, image, and measure the energy of X-rays from objects ranging from planets to distant quasars, Chandra has transformed 21st century astronomy. In this presentation we shall discuss how the Observatory accomplishes these observations, discuss the importance of X-Ray astronomy in understanding the Universe and share some of the most exciting results..

Weisskopf, Martin C.↗
NASA NTRS2010

Legacy of the Space Shuttle Program

This slide presentation reviews many of the innovations from Kennedy Space Center engineering for ground operations that were made during the shuttle program. The innovations are in the areas of detection, image analysis, protective equipment, software development and communications.

Sullivan, Steven J.↗
NASA NTRS2005

GaAs QWIP Array Containing More Than a Million Pixels

A 1,024 x 1,024-pixel array of quantum-well infrared photodetectors (QWIPs) has been built on a 1.8 x 1.8- cm GaAs chip. In tests, the array was found to perform well in detecting images at wavelengths from 8 to 9 m in operation at temperatures between 60 and 70 K. The largest-format QWIP prior array that performed successfully in tests contained 512 x 640 pixels. There is continuing development effort directed toward satisfying actual and anticipated demands to increase numbers of pixels and pixel sizes in order to increase the imaging resolution of infrared photodetector arrays. A 1,024 x 1,024-pixel and even larger formats have been achieved in the InSb and HgCdTe material systems, but photodetector arrays in these material systems are very expensive and manufactured by fewer than half a dozen large companies. In contrast, GaAs-photodetector-array technology is very mature, and photodetectors in the GaAs material system can be readily manufactured by a wide range of industrial technologists, by universities, and government laboratories. There is much similarity between processing in the GaAs industry and processing in the pervasive silicon industry. With respect to yield and cost, the performance of GaAs technology substantially exceeds that of InSb and HgCdTe technologies. In addition, GaAs detectors can be designed to respond to any portion of the wavelength range from 3 to about 16 micrometers - a feature that is very desirable for infrared imaging. GaAs QWIP arrays, like the present one, have potential for use as imaging sensors in infrared measuring instruments, infrared medical imaging systems, and infrared cameras.

Jhabvala, Murzy↗
NASA NTRS2015

Study of Static Microchannel Plate Saturation Effects for the Fast Plasma Investigation Dual Electron Spectrometers on NASA's Magnetospheric MultiScale Mission

Imaging detecting systems based on microchannel plates (MCPs) are the most common for low energy plasma measurements for both space borne and ground applications. One of the key parameters of these detection systems is the dynamic range of the MCP's response to the input fluxes of charged particles. For most applications the dynamic range of the linear response should be as wide as possible. This is especially true for the Dual Electron Spectrometers (DESs) of the Fast Plasma Investigation (FPI) on NASA's Magnetospheric MultiScale (MMS) mission because a wide range of input fluxes are expected. To make use of the full available dynamic range, it is important to understand the MCP response behavior beyond the linear regime where the MCPs start to saturate. We have performed extensive studies of this during the characterization and calibration of the DES instruments and have identified several saturation effects of the detection system. The MCP itself exhibits saturation when the channels lack the ability to replenish charge sufficiently rapidly. It is found and will be shown that the ground system can significantly impact the correct measurement of this effect. As the MCP starts to saturate, the resulting pulse height distribution (PHD) changes shape and location (with less pulse height values), which leads to truncation of the PHD by the threshold set on the detection system discriminator. Finally, the detection system pulse amplifier exhibits saturation as the input flux drives pulse rates greater than its linear response speed. All of these effects effectively change the dead time of the overall detection system and as a result can affect the quality and interpretation of the flight data. We present results of detection system saturation effects and their interaction with special emphasis on the MCP related effects.

detecting system↗
NASA NTRS2018

Video Distribution and Storage Unit

Disclosed is a satellite payload device, including a plurality of sensors configured to detect images of a satellite, a video distribution and storage unit configured to collect, compress, store, and transmit the images, and a control computer configured to request a portion of the plurality of sensors from which to receive sensor data that is routed to the video distribution and storage unit.

Kadari, Madhusudhan↗
NASA NTRSDate not supplied

Graph Convolutional Network-Strengthened Topic Modeling for Scientific Papers

Machine learning has been woven into statistics to modernize topic modeling over textual documents written in natural language, and scientific paper search and recommendation can consequently offer higher accuracy instead of counting on traditional keyword-based search. However, topic distribution of a paper resulted from existing topic modeling techniques only relies on the statistics of words contained in the paper itself. We argue that community users’ views of a paper may also provide insights at the time of recommendation. For example, if a paper on fake image detection has been cited heavily by machine learning papers, such a feature should be absorbed in the embedding of this paper, so that it can be recommended for future query on machine learning. In this paper, we present a Graph Convolutional Network-strengthened Topic Modeling (GCN-TM) method, which employs GCN technique to refine topic modeling of scientific papers. A citation-oriented knowledge graph is constructed, and topic modeling is mapped to feature embedding of the comprising papers. On top of its own topics carried in its content, each paper learns topics from its neighbors and revise its embedding accordingly. Our empirical studies over real-life scientific literature has proved the necessity and effectiveness of our proposed approach.

Jia Zhang↗
NASA NTRS2022

Nested Dust Shells Around the Wolf–Rayet Binary WR 140 Observed With JWST

Massive colliding-wind binaries that host a Wolf–Rayet (WR) star present a potentially important source of dust and chemical enrichment in the interstellar medium. However, the chemical composition and survival of dust formed from such systems is not well understood. The carbon-rich Wolf–Rayet binary WR 140 presents an ideal astrophysical laboratory for investigating these questions, given its well-defined orbital period and predictable dust-formation episodes every 7.93 years around periastron passage. We present observations from our Early Release Science programme (ERS 1349) with the James Webb Space Telescope Mid-Infrared Instrument (MIRI) Medium-Resolution Spectrometer and Imager that reveal the spectral and spatial signatures of nested circumstellar dust shells around WR 140. MIRI medium-resolution spectroscopy of the second dust shell and Imager detections of over 17 shells formed throughout approximately the past 130 years confirm the survival of carbonaceous dust grains from WR 140 that are probably carriers of ‘unidentified infrared’-band features at 6.4 and 7.7 μm. The observations indicate that dust-forming carbon-rich Wolf–Rayet binaries can enrich the interstellar medium with organic compounds and carbonaceous dust.

massive stars↗
NASA NTRS1994

Boundary-layer transition detection with infrared imaging emphasizing cryogenic applications

This paper reviews the technique of boundary-layer transition detection using infrared (IR) imaging, emphasizing cryogenic wind-tunnel testing. With the exception of the low-temperature effects on the IR radiation, the discussion is relevant to conventional wind-tunnel and flight testing as well. At low temperatures, IR imaging encounters a reduction in the radiated energy throughout the IR spectrum, combined with a shift to longer wavelengths of the bulk of the radiation. This radiation behavior affects the minimum resolvable temperature difference (MRTD) of the IR imaging system because of its fixed wave band sensitivity. In the absence of commercial long wavelength IR imaging systems, operating at wavelengths longer than 13 micron, some measures can be taken to alleviate the problem caused by the MRTD limitation. The thermal signature of transition can be enhanced by allowing a small and controlled temperature increase of the wind-tunnel flow that induces a transient heat transfer to the model. This action temporarily reveals the model area under the turbulent regime through its higher heating rate compared with the laminar regime. The contrast between the areas exposed to the two regimes can be enhanced by subtraction of thermograms (the equilibrium thermogram from the transient thermogram). Further visual improvement can be obtained through shade stretching or binary shading.

Gartenberg, Ehud↗
DOE OSTI2025

Optimizing Deep Learning Models for Climate-Related Natural Disaster Detection from UAV Images and Remote Sensing Data

This research study utilized artificial intelligence (AI) to detect natural disasters from aerial images. Flooding and desertification were two natural disasters taken into consideration. The Climate Change Dataset was created by compiling various open-access data sources. This dataset contains 6334 aerial images from UAV (unmanned aerial vehicles) images and satellite images. The Climate Change Dataset was then used to train Deep Learning (DL) models to identify natural disasters. Four different Machine Learning (ML) models were used: convolutional neural network (CNN), DenseNet201, VGG16, and ResNet50. These ML models were trained on our Climate Change Dataset so that their performance could be compared. DenseNet201 was chosen for optimization. All four ML models performed well. DenseNet201 and ResNet50 achieved the highest testing accuracies of 99.37% and 99.21%, respectively. This research project demonstrates the potential of AI to address environmental challenges, such as climate change-related natural disasters. This study’s approach is novel by creating a new dataset, optimizing an ML model, cross-validating, and presenting desertification as one of our natural disasters for DL detection. Three categories were used (Flooded, Desert, Neither). Our study relates to AI for Climate Change and Environmental Sustainability. Drone emergency response would be a practical application for our research project.

AI↗
NASA NTRS1992

Edge detection algorithm for SST images

An algorithm to detect fronts in satellite-derived sea surface temperature fields is presented. Although edge detection is the main focus, the problem of cloud detection is also addressed since unidentified clouds can lead to erroneous edge detection. The algorithm relies on a combination of methods and it operates at the picture, the window, and the local level. The resulting edge detection is not based on the absolute strength of the front, but on the relative strength depending on the context, thus, making the edge detection temperature-scale invariant. The performance of this algorithm is shown to be superior to that of simpler algorithms commonly used to locate edges in satellite-derived SST images. This evaluation was performed through a careful comparison between the location of the fronts obtained by applying the various methods to the SST images and the in situ measures of the Gulf Stream position.

Cayula, Jean-Francois↗
NASA NTRS1992

Digital image profilers for detecting faint sources which have bright companions

For this program, an image profiling system was developed which offers the potential for detecting extremely faint optical sources that are located in close proximity to bright companions. The approach employed is novel in three respects. First, it does not require an optical system wherein extraordinary measures must be taken to minimize diffraction and scatter. Second, it does not require detectors possessing either extreme uniformity in sensitivity or extreme temporal stability. Finally, the system can readily be calibrated, or nulled, in space by testing against an unresolved singular stellar source.

Morris, Elena↗
DOE OSTI2023

L-dwarf Detection from SDSS Images using Improved Faster R-CNN

We present a data-driven approach to automatically detect L dwarfs from Sloan Digital Sky Survey (SDSS) images using an improved Faster R-CNN framework based on deep learning. The established L-dwarf automatic detection (LDAD) model distinguishes L dwarfs from other celestial objects and backgrounds in SDSS field images by learning the features of 387 SDSS images containing L dwarfs. Applying the LDAD model to the SDSS images containing 93 labeled L dwarfs in the test set, we successfully detected 83 known L dwarfs with a recall rate of 89.25% for known L dwarfs. Several techniques are implemented in the LDAD model to improve its detection performance for L dwarfs, including the deep residual network and the feature pyramid network. As a result, the LDAD model outperforms the model of the original Faster R-CNN, whose recall rate of known L dwarfs is 80.65% for the same test set. The LDAD model was applied to detect L dwarfs from a larger validation set including 843 labeled L dwarfs, resulting in a recall rate of 94.42% for known L dwarfs. The newly identified candidates include L dwarfs, late M and T dwarfs, which were estimated from color (i – z) and spectral type relation. The contamination rates for the test candidates and validation candidates are 8.60% and 9.27%, respectively. The detection results indicate that our model is effective to search for L dwarfs from astronomical images.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

Space Shuttle Main Engine Propellant Path Leak Detection Using Sequential Image Processing

Initial research in this study using theoretical radiation transport models established that the occurrence of a leak is accompanies by a sudden but sustained change in intensity in a given region of an image. In this phase, temporal processing of video images on a frame-by-frame basis was used to detect leaks within a given field of view. The leak detection algorithm developed in this study consists of a digital highpass filter cascaded with a moving average filter. The absolute value of the resulting discrete sequence is then taken and compared to a threshold value to produce the binary leak/no leak decision at each point in the image. Alternatively, averaging over the full frame of the output image produces a single time-varying mean value estimate that is indicative of the intensity and extent of a leak. Laboratory experiments were conducted in which artificially created leaks on a simulated SSME background were produced and recorded from a visible wavelength video camera. This data was processed frame-by-frame over the time interval of interest using an image processor implementation of the leak detection algorithm. In addition, a 20 second video sequence of an actual SSME failure was analyzed using this technique. The resulting output image sequences and plots of the full frame mean value versus time verify the effectiveness of the system.

Smith, L. Montgomery↗