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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Estimating Lunar Pyroclastic Deposit Depth from Imaging Radar Data: Applications to Lunar Resource Assessment

Lunar pyroclastic deposits represent one of the primary anticipated sources of raw materials for future human settlements. These deposits are fine-grained volcanic debris layers produced by explosive volcanism contemporaneous with the early stage of mare infilling. There are several large regional pyroclastic units on the Moon (for example, the Aristarchus Plateau, Rima Bode, and Sulpicius Gallus formations), and numerous localized examples, which often occur as dark-halo deposits around endogenic craters (such as in the floor of Alphonsus Crater). Several regional pyroclastic deposits were studied with spectral reflectance techniques: the Aristarchus Plateau materials were found to be a relatively homogeneous blanket of iron-rich glasses. One such deposit was sampled at the Apollo 17 landing site, and was found to have ferrous oxide and titanium dioxide contents of 12 percent and 5 percent, respectively. While the areal extent of these deposits is relatively well defined from orbital photographs, their depths have been constrained only by a few studies of partially filled impact craters and by imaging radar data. A model for radar backscatter from mantled units applicable to both 70-cm and 12.6-cm wavelength radar data is presented. Depth estimates from such radar observations may be useful in planning future utilization of lunar pyroclastic deposits.

Campbell, B. A.↗
DOE OSTI2018

System and method for controlling depth of imaging in tissues using fluorescence microscopy under ultraviolet excitation following staining with fluorescing agents

A method is disclosed for analyzing a thin tissue sample and adapted to be supported on a slide. The tissue sample may be placed on a slide and exposed to one or more different exogenous fluorophores excitable in a range of about 300 nm-200 nm, and having a useful emission band from about 350 nm-900 nm, and including one or more fluorescent dyes or fluorescently labeled molecular probes that accumulate in tissue or cellular components. The fluorophores may be excited with a first wavelength of UV light between about 200 nm-290 nm. An optical system collects emissions from the fluorophores at a second wavelength, different from the first wavelength, which are generated in response to the first wavelength of UV light, to produce an image for analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

THE SLOAN DIGITAL SKY SURVEY STRIPE 82 IMAGING DATA: DEPTH-OPTIMIZED CO-ADDS OVER 300 deg{sup 2} IN FIVE FILTERS

We present and release co-added images of the Sloan Digital Sky Survey (SDSS) Stripe 82. Stripe 82 covers an area of ∼300 deg{sup 2} on the celestial equator, and has been repeatedly scanned 70-90 times in the ugriz bands by the SDSS imaging survey. By making use of all available data in the SDSS archive, our co-added images are optimized for depth. Input single-epoch frames were properly processed and weighted based on seeing, sky transparency, and background noise before co-addition. The resultant products are co-added science images and their associated weight images that record relative weights at individual pixels. The depths of the co-adds, measured as the 5σ detection limits of the aperture (3.''2 diameter) magnitudes for point sources, are roughly 23.9, 25.1, 24.6, 24.1, and 22.8 AB magnitudes in the five bands, respectively. They are 1.9-2.2 mag deeper than the best SDSS single-epoch data. The co-added images have good image quality, with an average point-spread function FWHM of ∼1'' in the r, i, and z bands. We also release object catalogs that were made with SExtractor. These co-added products have many potential uses for studies of galaxies, quasars, and Galactic structure. We further present and release near-IR J-band images that cover ∼90 deg{sup 2} of Stripe 82. These images were obtained using the NEWFIRM camera on the NOAO 4 m Mayall telescope, and have a depth of about 20.0-20.5 Vega magnitudes (also 5σ detection limits for point sources)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Quantum ghost imaging microscopy depth-of-field study

Quantum ghost imaging approaches have been proposed to enhance biological microscopy, for example, using 2D visible detectors to provide IR images or providing additional dimensions of spatial or spectral information. Toward the goal of making such imaging schemes practical, we compare image quality and depth-of-field between traditional images and ghost images at the same excitation levels. We measure how image quality and depth-of-field depend on the parameters of the entangled light produced using type-I spontaneous parametric down-conversion (SPDC). We use a pair of time-synchronized, photon-timing single-photon avalanche diode (SPAD) array detectors to capture two distinct microscope imaging paths simultaneously on a photon-pair-by-photon-pair basis: one in a traditional imaging pathway and the other a quantum ghost imaging pathway. We calculate the depth-of-field, resolution, contrast, and signal-to-noise ratio (SNR) through the parameter space of a β-Barium Borate (BBO) type-I bulk non-linear crystal length and angle. Our results provide a basis for choosing parameters for quantum ghost imaging with type-I SPDC sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

SU-F-J-206: Systematic Evaluation of the Minimum Detectable Shift Using a Range- Finding Camera

Purpose: The robotic table used for patient alignment in proton therapy is calibrated only at commissioning under well-defined conditions and table shifts may vary over time and with differing conditions. The purpose of this study is to systematically investigate minimum detectable shifts using a time-of-flight (TOF) range-finding camera for table position feedback. Methods: A TOF camera was used to acquire one hundred 424 × 512 range images from a flat surface before and after known shifts. Range was assigned by averaging central regions of the image across multiple images. Depth resolution was determined by evaluating the difference between the actual shift of the surface and the measured shift. Depth resolution was evaluated for number of images averaged, area of sensor over which depth was averaged, distance from camera to surface, central versus peripheral image regions, and angle of surface relative to camera. Results: For one to one thousand images with a shift of one millimeter the range in error was 0.852 ± 0.27 mm to 0.004 ± 0.01 mm (95% C.I.). For varying regions of the camera sensor the range in error was 0.02 ± 0.05 mm to 0.47 ± 0.04 mm. The following results are for 10 image averages. For areas ranging from one pixel to 9 × 9 pixels the range in error was 0.15 ± 0.09 to 0.29 ± 0.15 mm (1σ). For distances ranging from two to four meters the range in error was 0.15 ± 0.09 to 0.28 ± 0.15 mm. For an angle of incidence between thirty degrees and ninety degrees the average range in error was 0.11 ± 0.08 to 0.17 ± 0.09 mm. Conclusion: It is feasible to use a TOF camera for measuring shifts in flat surfaces under clinically relevant conditions with submillimeter precision.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗
DOE OSTI2016

SPITZER ULTRA FAINT SURVEY PROGRAM (SURFS UP). II. IRAC-DETECTED LYMAN-BREAK GALAXIES AT 6 ≲ z ≲ 10 BEHIND STRONG-LENSING CLUSTERS

We study the stellar population properties of the IRAC-detected 6 ≲ z ≲ 10 galaxy candidates from the Spitzer UltRa Faint SUrvey Program. Using the Lyman Break selection technique, we find a total of 17 galaxy candidates at 6 ≲ z ≲ 10 from Hubble Space Telescope images (including the full-depth images from the Hubble Frontier Fields program for MACS 1149 and MACS 0717) that have detections at signal-to-noise ratios ≥ 3 in at least one of the IRAC 3.6 and 4.5 μm channels. According to the best mass models available for the surveyed galaxy clusters, these IRAC-detected galaxy candidates are magnified by factors of ∼1.2–5.5. Due to the magnification of the foreground galaxy clusters, the rest-frame UV absolute magnitudes M{sub 1600} are between −21.2 and −18.9 mag, while their intrinsic stellar masses are between 2 × 10{sup 8}M{sub ⊙} and 2.9 × 10{sup 9}M{sub ⊙}. We identify two Lyα emitters in our sample from the Keck DEIMOS spectra, one at z{sub Lyα} = 6.76 (in RXJ 1347) and one at z{sub Lyα} = 6.32 (in MACS 0454). We find that 4 out of 17 z ≳ 6 galaxy candidates are favored by z ≲ 1 solutions when IRAC fluxes are included in photometric redshift fitting. We also show that IRAC [3.6]–[4.5] color, when combined with photometric redshift, can be used to identify galaxies which likely have strong nebular emission lines or obscured active galactic nucleus contributions within certain redshift windows.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Robust Spectral Unmixing of Sparse Multispectral Lidar Waveforms using Gamma Markov Random Fields

Here, this paper presents a new Bayesian spectral un-mixing algorithm to analyse remote scenes sensed via sparse multispectral Lidar measurements. To a first approximation, in the presence of a target, each Lidar waveform consists of a main peak, whose position depends on the target distance and whose amplitude depends on the wavelength of the laser source considered (i.e, on the target reflectivity). Besides, these temporal responses are usually assumed to be corrupted by Poisson noise in the low photon count regime. When considering multiple wavelengths, it becomes possible to use spectral information in order to identify and quantify the main materials in the scene, in addition to estimation of the Lidar-based range profiles. Due to its anomaly detection capability, the proposed hierarchical Bayesian model, coupled with an efficient Markov chain Monte Carlo algorithm, allows robust estimation of depth images together with abundance and outlier maps associated with the observed 3D scene. The proposed methodology is illustrated via experiments conducted with real multispectral Lidar data acquired in a controlled environment. The results demonstrate the possibility to unmix spectral responses constructed from extremely sparse photon counts (less than 10 photons per pixel and band).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Extended depth of field imaging for high speed object analysis

A high speed, high-resolution flow imaging system is modified to achieve extended depth of field imaging. An optical distortion element is introduced into the flow imaging system. Light from an object, such as a cell, is distorted by the distortion element, such that a point spread function (PSF) of the imaging system is invariant across an extended depth of field. The distorted light is spectrally dispersed, and the dispersed light is used to simultaneously generate a plurality of images. The images are detected, and image processing is used to enhance the detected images by compensating for the distortion, to achieve extended depth of field images of the object. The post image processing preferably involves de-convolution, and requires knowledge of the PSF of the imaging system, as modified by the optical distortion element.

Ortyn, William↗
NASA NTRS2011

Extended depth of field imaging for high speed object analysis

A high speed, high-resolution flow imaging system is modified to achieve extended depth of field imaging. An optical distortion element is introduced into the flow imaging system. Light from an object, such as a cell, is distorted by the distortion element, such that a point spread function (PSF) of the imaging system is invariant across an extended depth of field. The distorted light is spectrally dispersed, and the dispersed light is used to simultaneously generate a plurality of images. The images are detected, and image processing is used to enhance the detected images by compensating for the distortion, to achieve extended depth of field images of the object. The post image processing preferably involves de-convolution, and requires knowledge of the PSF of the imaging system, as modified by the optical distortion element.

Ortyn, William↗
DOE OSTI2017

Full-Depth Coadds of the WISE and First-Year NEOWISE-Reactivation Images

The Near Earth Object Wide-field Infrared Survey Explorer (NEOWISE) Reactivation mission released data from its first full year of observations in 2015. This data set includes ~2.5 million exposures in each of W1 and W2, effectively doubling the amount of WISE imaging available at 3.4 μm and 4.6 μm relative to the AllWISE release. In this paper, we have created the first ever full-sky set of coadds combining all publicly available W1 and W2 exposures from both the AllWISE and NEOWISE-Reactivation (NEOWISER) mission phases. We employ an adaptation of the unWISE image coaddition framework, which preserves the native WISE angular resolution and is optimized for forced photometry. By incorporating two additional scans of the entire sky, we not only improve the W1/W2 depths, but also largely eliminate time-dependent artifacts such as off-axis scattered moonlight. We anticipate that our new coadds will have a broad range of applications, including target selection for upcoming spectroscopic cosmology surveys, identification of distant/massive galaxy clusters, and discovery of high-redshift quasars. In particular, our full-depth AllWISE+NEOWISER coadds will be an important input for the Dark Energy Spectroscopic Instrument selection of luminous red galaxy and quasar targets. Our full-depth W1/W2 coadds are already in use within the DECam Legacy Survey (DECaLS) and Mayall z-band Legacy Survey (MzLS) reduction pipelines. Finally, much more work still remains in order to fully leverage NEOWISER imaging for astrophysical applications beyond the solar system.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1989

Television monitor field shifter and an opto-electronic method for obtaining a stereo image of optimal depth resolution and reduced depth distortion on a single screen

A method and apparatus for obtaining a stereo image with reduced depth distortion and optimum depth resolution. Static and dynamic depth distortion and depth resolution trade-off is provided. Cameras obtaining the images for a stereo view are converged at a convergence point behind the object to be presented in the image, and (a) the collection-surface-to-object distance, (b) the camera separation distance, and (c) the focal lengths of zoom lenses for the camera are all increased. Doubling the distances cuts the static depth distortion in half while maintaining image size and depth resolution. Dynamic depth distortion is minimized by panning a stereo view-collecting camera system about a circle which passes through the convergence point and the cameras' first nodal points. Horizontal field shifting of the television fields on a television monitor brings both the monitor and the stereo views within the viewer's limit of binocular fusion.

Daniel B Diner↗
DOE OSTI2019

Complementary bimodal approach to monitoring of photodynamic therapy with targeted nanoconstructs: numerical simulations

We propose a new approach to monitoring photodynamic therapy (PDT) of glioblastoma with the use of targeted nanoconstructs containing a photosensitiser (PS) [benzoporphyrin derivative (BPD)] and IRDye800 dye, antibodies for efficient accumulation of the drug in a tumour, and a chemotherapeutic agent for combined effect on tumour cells. Application of IRDye800 is determined by the shift of its absorption and fluorescence spectra to the near-IR range with respect to BPD that ensures a higher imaging depth. Monitoring of PDT is based on the simultaneous fluorescence and optoacoustic (OA) imaging. Fluorescence imaging provides visualisation of fluorescence agents with high molecular sensitivity and monitoring of the effectiveness of PDT by PS photobleaching. OA allows one to examine the vascular pattern of the tumour environment, as well as assess the depth of the tumour. IRDye800 is a better contrast agent in comparison to BPD due to red-shifted spectral characteristics and a higher fluorescence quantum yield. Monte Carlo simulations combined for OA simulations with K-wave modelling allowed the feasibility of the complementary approach to be studied and demonstrated that this combination allows one to localise a tumour with a size of 2 mm at depths from 100 μm to 2 mm. (paper)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Prestack reverse time migration for 3D marine reflection seismic data

Prestack reverse time migration (RTM) is a method for imaging the subsurface using the inner product of wavefield extrapolation in shot domain and in receiver domain. It is well known that RTM is better for preserving amplitudes and phases than other prestack migrations. Since 3D seismic data is huge data volume and it needs heavy computing works, it requires parallel computing in order to have a meaningful depth image of the 3D subsurface. We implemented a parallelized version of 3D RTM for prestack depth migration. The results of numerical example for 3D SEG/EAGE salt model showed good agreement with the original geological model. We applied RTM to offshore 3D seismic reflection data. The study area is 12 × 25 km with 120 survey lines. Shot and receiver spacing is 25 m and 12.5 m. The line spacing is 100 m. Shot gathers were preprocessed to enhance signal to noise ratio and velocity model was calculated from conventional stack velocity. Both of them were used to obtain 3D image using RTM. The results show reasonable subsurface image.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2015

A Tool for the Automated Collection of Space Utilization Data: Three Dimensional Space Utilization Monitor

Space Human Factors and Habitability (SHFH) Element within the Human Research Program (HRP), in collaboration with the Behavioral Health and Performance (BHP) Element, is conducting research regarding Net Habitable Volume (NHV), the internal volume within a spacecraft or habitat that is available to crew for required activities, as well as layout and accommodations within that volume. NASA is looking for innovative methods to unobtrusively collect NHV data without impacting crew time. Data required includes metrics such as location and orientation of crew, volume used to complete tasks, internal translation paths, flow of work, and task completion times. In less constrained environments methods for collecting such data exist yet many are obtrusive and require significant post‐processing. Example technologies used in terrestrial settings include infrared (IR) retro‐reflective marker based motion capture, GPS sensor tracking, inertial tracking, and multiple camera filmography. However due to constraints of space operations many such methods are infeasible, such as inertial tracking systems which typically rely upon a gravity vector to normalize sensor readings, and traditional IR systems which are large and require extensive calibration. However multiple technologies have not yet been applied to space operations for these explicit purposes. Two of these include 3‐Dimensional Radio Frequency Identification Real‐Time Localization Systems (3D RFID‐RTLS) and depth imaging systems which allow for 3D motion capture and volumetric scanning (such as those using IR‐depth cameras like the Microsoft Kinect or Light Detection and Ranging / Light‐Radar systems, referred to as LIDAR).

Vos, Gordon A.↗
NASA NTRS2017

A Tool for the Automated Collection of Space Utilization Data: Three Dimensional Space Utilization Monitor

Space Human Factors and Habitability (SHFH) Element within the Human Research Program (HRP) and the Behavioral Health and Performance (BHP) Element are conducting research regarding Net Habitable Volume (NHV), the internal volume within a spacecraft or habitat that is available to crew for required activities, as well as layout and accommodations within the volume. NASA needs methods to unobtrusively collect NHV data without impacting crew time. Data required includes metrics such as location and orientation of crew, volume used to complete tasks, internal translation paths, flow of work, and task completion times. In less constrained environments methods exist yet many are obtrusive and require significant post-processing. Examplesused in terrestrial settings include infrared (IR) retro-reflective marker based motion capture, GPS sensor tracking, inertial tracking, and multi-camera methods Due to constraints of space operations many such methods are infeasible. Inertial tracking systems typically rely upon a gravity vector to normalize sensor readings,and traditional IR systems are large and require extensive calibration. However, multiple technologies have not been applied to space operations for these purposes. Two of these include: 3D Radio Frequency Identification Real-Time Localization Systems (3D RFID-RTLS) Depth imaging systems which allow for 3D motion capture and volumetric scanning (such as those using IR-depth cameras like the Microsoft Kinect or Light Detection and Ranging / Light-Radar systems, referred to as LIDAR)

Vos, Gordon A.↗