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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Performance Before and After Irradiation of Pixelated 3D Silicon Sensors for the HL-LHC CMS Tracker

The Large Hadron Collider (LHC) particle accelerator at European Center for Nuclear Research (CERN) will be shut down starting in 2026 to achieve the High Luminosity Large Hadron Collider (HL-LHC) upgrade. The upgrade will allow for higher fluences, in order to increase the probability of detecting increasingly rare particles, and to obtain higher precision measurements of known particles. To accommodate the new accelerator conditions, many aspects of the Compact Muon Solenoid (CMS) detector will be upgraded; of particular interest for this thesis are the silicon pixel detectors located in the inner tracker. These will be replaced and upgraded to accommodate the higher fluences of the HL-LHC upgrade, as well as to replace existing sensors which have sustained radiation damage. In order for the new sensors to operate under high luminosity conditions, they must be increasingly radiation hard, and in order to detect rare particles, they must be increasingly more precise. The performance of one Centro Nacional de Microelectronica (CNM) 3D silicon sensor before and after undergoing irradiation at fluences similar to those which will be observed at the HL-LHC was investigated to determine radiation hardness and precision. Data was collected at Fermi National Laboratory (Fermilab), in the Fermi National Laboratory Test Beam Facility (FTBF) silicon tracker telescope, which can be used to determine the number of particles, and tracks made by high energy protons passing through. The sensor was also irradiated at Fermilab in the Irradiation Test Area (ITA). Prior to data collection a tuning procedure is carried out to determine ideal bias voltage operating conditions, mask noisy and dead pixels, adjust to the ideal threshold, and map sensor gain. Data is then collected at the FTBF, where the sensor is installed in the center of the FTBF silicon telescope. Variables, including angle and bias voltage, are varied throughout data collection. Data is then processed using an alignment software to determine the exact telescope geometry, along with the tracks which were observed passing through the sensor and telescope. Sensor performance was found to be comparable before and after irradiation, with irradiated results showing slightly lower efficiencies and cluster sizes. Position resolution is comparable both before and after irradiation, and similar distributions of cluster shape are observed. After irradiation, the sensor shows increasing collected charge with bias, an indication of increased width of the depletion region. Peak charge pre-irradiation is higher than post-irradiation peak charge, indicating the irradiated results are not taken under fully-depleted conditions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Smart-readout of the Skipper-CCD: Achieving Sub-electron Noise Levels in Regions of Interest

The skipper CCD is a special type of charge coupled device in which the readout noise can be reduced to sub-electron levels by averaging independent measurements of the same charge. Thus the charge in the pixels can be determined by counting the exact number of electrons. The total readout time is proportional to the number of measurements of the charge in each pixel. For some applications this time may be too long; however, researchers usually are interested only on certain region within the matrix of pixels. In this paper we present the development of a smart skipper readout technique that allows the user to specify regions of interest of the CCD matrix where an arbitrary (high) number of measurements of the same charge can taken to obtain the desired noise level, and far less measurements are performed in those regions that are less interesting to the researcher, therefore reducing the total readout time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1985

A high-speed, dual-CCD imaging photometer

The SNAPSHOT is a high-speed, dual-CCD imaging photometer, with special capability for occultation observations. It is capable of recording occultation light curves in the presence of bright, nonuniform background illumination, such as occultations of stars by Saturn's rings or by comets. Such events are difficult or impossible to observe with conventional photometers. The fundamental idea that makes high time-resolution observations possible is to reduce the data rate by digitizing only those pixels in subframes containing the objects of interest.

Dunham, E. W.↗
NASA NTRS1992

Interaction types and their like-polarization phase-angle difference signatures

The JPL Airborne Synthetic Aperture Radar (AIRSAR) measures the full polarimetric properties of scene objects. AIRSAR data contain a complete set of magnitudes (for all linearly-polarized combinations (viz., VV, HH, and CS (cross Polarization))) and phase-angle differences (for all pairs of linearly-polarized components) for each image pixel. Radar images users have been greatly interested in the like-polarization (LK) phase-angle difference parameter, delta phi(sub LK). Usually, it is associated with the type of interaction between microwaves and scene-object scattering-elements. One value of delta phi(sub LK) is said to be produced by a dominant single scattering (or reflection) event, and another value is said to be the result of a dominant double-scattering (or double reflection) event. these are often called 'single bounce' and 'double bounce' interaction signatures, respectively. There appears to be a significant amount of confusion about how the interaction processes produce the characteristic values of delta phi(sub LK) and about what value of delta phi(sub LK) should be associated with each specific type. This issue is addressed.

Paris, Jack F.↗
NASA NTRS2005

Method and structure for minimizing error sources in image and position sensing detectors

A method and structure for minimizing one or more non-uniformities in image and position sensing detectors are provided. The structure is directed to a focal plane processor for removing non-uniformities which distort the computation of a desired property of an object of interest in an image field. The focal plane processor is capable of selectively disconnecting one or more rows and/or columns from further processing in the imaging array for those rows and/or columns which contribute to the presence of at least one non-uniformity in a video image generated by the focal plane processor. In one embodiment, the disconnection means is embodied as pre-processing circuitry which includes row and column shift registers which provide control signals to area-of-interest (AOI) switches. In another embodiment, the pixels which comprise the focal plane array are constructed in a manner which facilitates their individual isolation.

Strohbehn, Kim↗
NASA NTRS2006

Nondestructive Evaluation of Foam Insulation on the Space Shuttle External Tank

Foam loss on the External Tank (ET) during launch can be caused by a number of factors. Voids are the best understood mechanism of foam loss, although it is known that delaminations, cracks and crushed foam can also lead to liberation of foam. Shortly after the Columbia accident, work began on non-destructive evaluation of foam targeted at finding voids and delaminations. After several months of searching for candidate methods capable of inspecting ET foam, the five most promising techniques were taken through a blind test and narrowed down to two methods to develop and use for inspection of the ET. These methods were backscatter radiography and terahertz imaging. The backscatter radiography system measures a test part by detecting Compton backscattered x-ray energy generated by a collimated beam of x-rays directed at the test subject. This collimated beam is scanned across the subject, recording scatter intensity data one pixel at a time until the area of interest is covered. The resulting data can be used to generate an image similar to a radiograph. Some depth information can be gathered utilizing apertures or collimation on the detectors. The detectors are located around the collimated source, making this a single sided inspection. The void detection limit with the currently utilized system is around 0.5 inches in diameter by 0.2 inches high. The terahertz imaging system inspects a test part by utilizing a transceiver to emit a pulse focused at the aluminum skin of the ET, which reflects it back to the transceiver where it is analyzed. The transceiver is scanned across the area of interest until a measurement has been taken at every location. Amplitude, time delay and frequency content are examined to note any discontinuities which may be the result of a void or other type of defect. The pulse currently utilized is in the millimeter wave regime. The void detection limit with this system is around 0.5 inches in diameter by 0.2 inches high. With increased interest in other causes of foam loss following the flight of Discovery in July 2005, laser shearography was added to the techniques used for inspecting ET foam. The shearography method records a sheared image of a laser speckle pattern projected on a test part before And after some sort of excitation. The resultant fringe pattern allows the slope of the out of plane displacement to be measured. For crushed and delaminated foam applications, a non-contact air coupled acoustic force is used to excite the surface of the foam. Regions without defects tend to respond differently to the sound energy than do regions with defects, generating a map of the foam integrity. Foam crushed to a depth of about 0.1 inches is detectable with shearography even after it has relaxed to its original shape.

Richter, Joel↗
NASA NTRS2012

Refinement of a Method for Identifying Probable Archaeological Sites from Remotely Sensed Data

To facilitate locating archaeological sites before they are compromised or destroyed, we are developing approaches for generating maps of probable archaeological sites, through detecting subtle anomalies in vegetative cover, soil chemistry, and soil moisture by analyzing remotely sensed data from multiple sources. We previously reported some success in this effort with a statistical analysis of slope, radar, and Ikonos data (including tasseled cap and NDVI transforms) with Student's t-test. We report here on new developments in our work, performing an analysis of 8-band multispectral Worldview-2 data. The Worldview-2 analysis begins by computing medians and median absolute deviations for the pixels in various annuli around each site of interest on the 28 band difference ratios. We then use principle components analysis followed by linear discriminant analysis to train a classifier which assigns a posterior probability that a location is an archaeological site. We tested the procedure using leave-one-out cross validation with a second leave-one-out step to choose parameters on a 9,859x23,000 subset of the WorldView-2 data over the western portion of Ft. Irwin, CA, USA. We used 100 known non-sites and trained one classifier for lithic sites (n=33) and one classifier for habitation sites (n=16). We then analyzed convex combinations of scores from the Archaeological Predictive Model (APM) and our scores. We found that that the combined scores had a higher area under the ROC curve than either individual method, indicating that including WorldView-2 data in analysis improved the predictive power of the provided APM.

Tilton, James C.↗
DOE OSTI2025

Dense Image Matching Uncertainty Estimation and Confidence Metrics

Dense stereo matching takes overlapping image pairs as input and outputs a disparity map which encodes pixel-by-pixel matches between the images. Recently, there has been an interest in ranking the quality, or even quantifying the accuracy, of disparity estimates. The proposed methods can be described as either uncertainty estimators or confidence metrics. Uncertainty estimators are a small minority of the research. However, they have the potential to be the most useful because they estimate disparity accuracy (in pixel units) that can be used to threshold matches or carried forward using error propagation. The majority of the research deals with confidence metrics which give an ordinal (or binary) ranking of a match’s quality relative to other matches. Confidence metrics do not have units and thus are useful primarily for thresholding matches from mismatches. The methods could also be described as handcrafted or deep-learning based. The majority of the research focused on outdoor driving scenes. Hence, our interest–application to a satellite semi-global matching pipeline–is a domain shift that may challenge deep-learning based methods. We conclude by recommending five handcrafted and two deep-learning based methods for evaluation in our pipeline.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

Algorithm for Detecting a Bright Spot in an Image

An algorithm processes the pixel intensities of a digitized image to detect and locate a circular bright spot, the approximate size of which is known in advance. The algorithm is used to find images of the Sun in cameras aboard the Mars Exploration Rovers. (The images are used in estimating orientations of the Rovers relative to the direction to the Sun.) The algorithm can also be adapted to tracking of circular shaped bright targets in other diverse applications. The first step in the algorithm is to calculate a dark-current ramp a correction necessitated by the scheme that governs the readout of pixel charges in the charge-coupled-device camera in the original Mars Exploration Rover application. In this scheme, the fraction of each frame period during which dark current is accumulated in a given pixel (and, hence, the dark-current contribution to the pixel image-intensity reading) is proportional to the pixel row number. For the purpose of the algorithm, the dark-current contribution to the intensity reading from each pixel is assumed to equal the average of intensity readings from all pixels in the same row, and the factor of proportionality is estimated on the basis of this assumption. Then the product of the row number and the factor of proportionality is subtracted from the reading from each pixel to obtain a dark-current-corrected intensity reading. The next step in the algorithm is to determine the best location, within the overall image, for a window of N N pixels (where N is an odd number) large enough to contain the bright spot of interest plus a small margin. (In the original application, the overall image contains 1,024 by 1,024 pixels, the image of the Sun is about 22 pixels in diameter, and N is chosen to be 29.)

Source record↗
DOE OSTI2025

Using Neural Networks to Identify Mixture Components in Hyperspectral Reflectance Data

Neural networks have been employed to identify materials of interest from hyperspectral data (generally imagery) based on their unique spectral signatures. This approach assumes that there is a single material that is standing out from the rest of the spectrum to be identified. However, pixels often contain more than one material, or a material of interest may itself be a mixture of multiple materials. Neural networks are only as good as the data used to train them, and it takes a great deal of work in the laboratory to identify, make, and measure all potential mixtures of interest. Thus, researchers often calculate synthetic spectra using algorithms with varying degrees of fidelity to the physics that govern the interactions between light and multiple materials. In this work, we have (1) adapted a neural network designed to identify mixture components from Raman spectroscopy to work with visible to near‐infrared reflectance data and (2) tested three common mixture algorithms to determine the most accurate and least computationally expensive method to build synthetic training datasets. With our initial test dataset, we have achieved accuracies of > 90% and found that the synthetic training dataset produced using the Hapke mixture model provides the best results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Separating Physically Distinct Mechanisms in Complex Infrared Plasmonic Nanostructures via Machine Learning Enhanced Electron Energy Loss Spectroscopy

Electron energy loss spectroscopy (EELS) enables direct exploration of plasmonic phenomena at the nanometer level. To isolate individual plasmon modes, linear unmixing methods can be used to separate different physical mechanisms, but in larger and more complex systems the interpretability of the components becomes uncertain. Here, infrared plasmonic resonances in self-assembled heterogeneous monolayer films of doped-semiconductor nanoparticles are examined beyond linear unmixing techniques, and both supervised and unsupervised machine-learning-based analyses of hyperspectral EELS datasets are demonstrated. Additionally, in the supervised approach, a human operator labels a small number of pixels in the hyperspectral dataset corresponding to features of interest which are then propagated across the entire dataset. In the unsupervised approach, non-linear autoencoders are used to create a highly-reduced latent-space representation of the dataset, within which insight into the relevant physics can be gleaned from straightforward distance metrics that do not depend on operator input and bias. The advantage of these approaches is that the labeling separates physical mechanisms without altering the data, enabling robust analyses of the influence of heterogeneities in mesoscale complex systems.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Real-Time X-ray Radiography Diagnostics of Components in Solid Rocket Motors

Solid rocket motors (SRMs) typically use nozzle materials which are required to maintain their shape as well as insulate the underlying support structure during the motor operation. In addition, SRMs need internal insulation materials to protect the motor case from the harsh environment resulting from the combustion of solid propellant. In the nozzle, typical materials consist of high density graphite, carbon-carbon composites and carbon phenolic composites. Internal insulation of the motor cases is typically a composite material with carbon, asbestos, Kevlar, or silica fibers in an ablative matrix such as EPDM or NBR. For both nozzle and internal insulation materials, the charring process occurs when the hot combustion products heat the material intensely. The pyrolysis of the matrix material takes away a portion of the thermal energy near the wall surface and leaves behind a char layer. The fiber reinforcement retains the porous char layer which provides continued thermal protection from the hot combustion products. It is of great interest to characterize both the total erosion rates of the material and the char layer thickness. By better understanding of the erosion process for a particular ablative material in a specific flow environment, the required insulation material thickness can be properly selected. The recession rates of internal insulation and nozzle materials of SRMs are typically determined by testing in some sort of simulated environment; either arc-jet testing, flame torch testing, or subscale SRMs of different size. Material recession rates are deduced by comparison of pre- and post-test measurements and then averaging over the duration of the test. However, these averaging techniques cannot be used to determine the instantaneous recession rates of the material. Knowledge of the variation in recession rates in response to the instantaneous flow conditions during the motor operation is of great importance. For example, in many SRM configurations the recession of the solid propellant grain can drastically alter the flow-field and effect the recession of internal insulation and nozzle materials. Simultaneous measurement of the overall erosion rate, the development of the char layer, and the recession of the char-virgin interface during the motor operation can be rather difficult. While invasive techniques have been used with limited success, they have serious drawbacks. Break wires or make wire sensors can be installed into a sufficient number of locations in the charring material from which a time history of the charring surface can be deduced. These sensors fundamentally alter the local structure of the material in which they are imbedded. Also, the location of these sensors within the material is not known precisely without the use of an X-ray. To determine instantaneous recession rates, real-time X-ray radiography (X-ray RTR) has been utilized in several SRM experiments at PSU. The X-ray RTR system discussed in this paper consists of an X-ray source, X-ray image intensifier, and CCD camera connected to a capture computer. The system has been used to examine the ablation process of internal insulation as well as nozzle material erosion in a subscale SRM. The X-ray source is rated to 320 kV at 10 mA and has both a large (5.5 mm) and small (3.0 mm) focal spot. The lead-lined cesium iodide X-ray image intensifier produces an image which is captured by a CCD camera with a 1,000 x 1,000 pixel resolution. To produce accurate imagery of the object of interest, the alignment of the X-ray source to the X-ray image intensifier is crucial. The image sequences captured during the operation of an SRM are then processed to enhance the quality of the images. This procedure allows for computer software to extract data on the total erosion rate and the char layer thickness. Figure 1 Error! Reference source not found.shows a sequence of images captured during the operation the subscale SRM with the X-ray RTR system. The X-rayTR system, alignment procedure, uncertainty determination, and image analysis process will be discussed in detail in the full manuscript.

Cortopassi, A. C.↗
DOE OSTI2022

The SiD Digital ECal Based on Monolithic Active Pixel Sensors

The SiD detector concept capitalizes on high granularity in its tracker and calorimeter to achieve the momentum resolution and particle flow calorimetry physics goals in a compact design. The collaboration has had a long interest in the potential for improved granularity in both the tracker and ECal with an application of monolithic active pixel sensors (MAPS) and a study of MAPS in the SiD ECal was described in the ILC TDR. Work is progressing on the MAPS application in an upgraded SiD design with a prototyping design effort for a common SiD tracker/ECal design based on stitched reticules to achieve 10 × 10 cm2 sensors with 25 × 100 micron2 pixels. Application of large area MAPS in these systems would limit delicate and expensive bump-bonding, provide possibilities for better timing, and should be significantly cheaper than the TDR concept due to being a more conventional CMOS foundry process. The small pixels significantly improve shower separation. Recent simulation studies confirm previous performance projections, indicating electromagnetic energy resolution based on digital hit cluster counting provides better performance than the SiD TDR analog design based on 13 mm2 pixels. Furthermore, the two shower separation is excellent down to the millimeter scale. Geant4 simulation results demonstrate these expectations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1998

Segmentation and tracking in echocardiographic sequences: active contours guided by optical flow estimates

This paper presents a method for segmentation and tracking of cardiac structures in ultrasound image sequences. The developed algorithm is based on the active contour framework. This approach requires initial placement of the contour close to the desired position in the image, usually an object outline. Best contour shape and position are then calculated, assuming that at this configuration a global energy function, associated with a contour, attains its minimum. Active contours can be used for tracking by selecting a solution from a previous frame as an initial position in a present frame. Such an approach, however, fails for large displacements of the object of interest. This paper presents a technique that incorporates the information on pixel velocities (optical flow) into the estimate of initial contour to enable tracking of fast-moving objects. The algorithm was tested on several ultrasound image sequences, each covering one complete cardiac cycle. The contour successfully tracked boundaries of mitral valve leaflets, aortic root and endocardial borders of the left ventricle. The algorithm-generated outlines were compared against manual tracings by expert physicians. The automated method resulted in contours that were within the boundaries of intraobserver variability.

Non-NASA Center↗
DOE OSTI2025

Application of automated iterative target detection for standoff hyperspectral imaging

The utility of hyperspectral imaging (HSI) has been well established for a wide array of applications but has generated a need for automated screening of high volumes of large HSI cubes. We report two important automated algorithms for more efficient standoff processing: atmospheric correction and target detection. The atmospheric correction method is based on a fast asymmetric least squares approach that is applied on a pixel-by-pixel basis. Here, the correction can be applied to entire images without manually identifying regions of interest and utilizes only in-scene information, no ancillary modeling of the atmosphere is required. An iterative target detection approach is also introduced which demonstrates faster speeds relative to moving window approaches. The target detection algorithm classifies each pixel as true target detections, near target detections, clutter, and no-calls. The algorithms were tested on forty images of twenty-two solid mineral targets placed at a 14-meter standoff distance allowing general observations on expected detection performance for a variety of minerals. In addition to identifying anomalous pixels, the inclusion of “no-calls” reduced the number of false detections significantly.

47 OTHER INSTRUMENTATION↗
NASA NTRS1996

Active-Pixel Image Sensors With Programmable Resolution

Active-pixel image sensors with programmable resolution proposed for use in applications in which speed and efficiency of processing of image data enhanced by providing those data at varying resolutions. Such applications include modeling of biological vision, stereoscopic range-finding, recognition of patterns, tracking targets, and progressive transmission of compressed images. In target-tracking application, sensor initially forms low-resolution image from which area of interest identified, then sensor set at high resolution for examination of identified area. Outputs of contiguous pixels combined. Sensor of this type made to act as though it comprised fewer and larger pixels.

Kemeny, Sabrina E.↗
NASA NTRS2015

An Upgrade of the Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Software

The Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) code is used at NASA Langley Research Center to analyze global aeroheating data on wind tunnel models tested in the Langley Aerothermodynamics Laboratory. One-dimensional, semi-infinite heating data derived from IHEAT are used to design thermal protection systems to mitigate the risks due to the aeroheating loads on hypersonic vehicles, such as re-entry vehicles during descent and landing procedures. This code was originally written in the PV-WAVE programming language to analyze phosphor thermography data from the two-color, relativeintensity system developed at Langley. To increase the efficiency, functionality, and reliability of IHEAT, the code was migrated to MATLAB syntax and compiled as a stand-alone executable file labeled version 4.0. New features of IHEAT 4.0 include the options to batch process all of the data from a wind tunnel run, to map the two-dimensional heating distribution to a three-dimensional computer-aided design model of the vehicle to be viewed in Tecplot, and to extract data from a segmented line that follows an interesting feature in the data. Results from IHEAT 4.0 were compared on a pixel level to the output images from the legacy code to validate the program. The differences between the two codes were on the order of 10-5 to 10-7. IHEAT 4.0 replaces the PV-WAVE version as the production code for aeroheating experiments conducted in the hypersonic facilities at NASA Langley.

Mason, Michelle L.↗
NASA NTRS2012

Nonlinear Estimation Approach to Real-Time Georegistration from Aerial Images

When taking aerial images, it is important to know locations of specific points of interest in an Earth-centered coordinate system (latitude, longitude, height). The correspondence between a pixel location in the image and its Earth coordinate is known as georegistration. There are two main technical challenges arising in the intended application. The first is that no known features are assumed to be available in any of the images. The second is that the intended applications are real time. Here, images are taken at regular intervals (i.e. once per second), and it is desired to make decisions in real time based on the geolocation of specific objects seen in the images as they arrive. This is in sharp contrast to most current methods for geolocation that operate "after-the-fact" by processing, on the ground, a database of stored images using computationally intensive methods. The solution is a nonlinear estimation algorithm that combines processed realtime camera images with vehicle position and attitude information ob tained from an onboard GPS receiver. This approach provides accurate georegistration estimates (latitude, longitude, height) of arbitrary features and/or points of interest seen in the camera images. This solves the georegistration problem at the modest cost of augmenting the camera information with a GPS receiver carried onboard the vehicle.

Bayard, David S.↗