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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 109 records · Page 6

Improved reconstruction stability for chemical shift encoded hyperpolarized 13 C magnetic resonance spectroscopic imaging using k‐t spiral acquisitions

Purpose A multiecho, field of view (FOV)‐oversampled k‐t spiral acquisition and direct iterative decomposition of water and fat with echo asymmetry and least‐squares estimation reconstruction is demonstrated to improve the stability of hyperpolarized 13 C magnetic resonance spectroscopic imaging (MRSI) in the presence of signal ambiguities attributed to low‐SNR (signal‐to‐noise‐ratio) species, local uncertainties in metabolite peaks, and echo‐to‐echo signal inconsistencies. Theory k‐t spiral acquisitions redistribute readout points to be more densely spaced radially in k‐space by acquiring an FOV and matrix that are oversampled by η . These more densely spaced spiral turns constitute effective intraspiral echoes and can supplement conventional interspiral echoes to improve spectral separation and reduce spectral cross‐talk to better resolve 13 C‐labeled species for spectroscopic imaging. Methods Digital simulations and imaging phantom experiments were performed for a range of interspiral echo spacings and η using multiecho, k‐t spiral acquisitions. Image spectral cross‐talk artifacts were evaluated both qualitatively and quantitatively as the percent error in measured metabolite ratios. In vivo murine experiments evaluated the feasibility of multiecho, k‐t spiral [1‐ 13 C]pyruvate MRSI to reduce spectral cross‐talk for 3 scenarios of different expected reconstruction stability. Results Digital simulations and imaging phantom experiments both demonstrated reduced or comparable image spectral cross‐talk and percent errors in measured metabolite ratios with increasing η and better choices of echo spacings. In vivo images displayed markedly reduced spectral cross‐talk in lactate images acquired with η = 7 versus η = 1. Conclusion The precision of hyperpolarized 13 C metabolic imaging and quantification in the presence of low‐SNR species, local uncertainties in metabolite resonances, and echo‐to‐echo signal inconsistencies can be improved with the use of FOV‐oversampled k‐t spiral acquisitions.

Macdonald, Erin B.↗

Effects of Postmortem Decomposition on Face Recognition

Although viable tools are available for the identification of unknown deceased individuals, recognition rates with these methods are greatly impacted by the degree to which decomposition has occurred. Therefore, identifying highly decomposed remains poses a major challenge. This paper analyzes the effect of facial decomposition on the recognition rates of several facial recognition commercial-off-theshelf systems and research-grade systems, as well as algorithms contained in a custom recognition library. The custom dataset of facial images used in the experiment is composed of 42 subjects at stages of decomposition rangingfrom recently deceased to later stages where the soft tissues are severely decomposed and facial features are deformed. It is shown that an algorithm’s ability to correctly detect a decomposing face is a crucial first step that not all face models can accurately handle. However, some of the evaluated Convolution Neural Network (CNN)–inspired methods provide promising results even in cases of severely decomposed faces.

Cornett, David↗

Three-Dimensional Instantaneous Flow-field Reconstruction Using Planar Spectral Proper Orthogonal Decomposition

A novel method for three-dimensional flowfield reconstruction is presented that utilizes spectral proper orthogonal decomposition (SPOD). The time-resolved PIV data are acquired in multiple two-dimensional spanwise planes, with adequate streamwise spacing to resolve the out-of-plane wavelength. Knowledge of the out-of-plane phase speed is also required, and for the present case this value was obtained using instantaneous hot-wire measurements. The method is validated by comparing phase-averaged results acquired with a forcing signal to the SPOD reconstructed results using the same data. The method is also applied to data with no forcing applied, and the results are shown to be similar to the forced case. This method is particularly useful for cases in which there are multiple frequencies of interest, or cases in which the phenomena occur over a broad range of frequencies. This method allows reconstruction of the frequencies of interest without the need for a forcing signal, so the flow can be studied in its natural (undisturbed) state.

boundary-layer transition↗

Verification of diesel spray ignition phenomenon in dual-fuel diesel-piloted premixed natural gas engine

Dual-fuel (DF) engines, in which premixed natural gas and air in an open-type combustion chamber is ignited by diesel-fuel pilot sprays, have been more popular for marine use than pre-chamber spark ignition (PCSI) engines because of their superior durability. However, control of ignition and combustion in DF engines is more difficult than in PCSI engines. In this context, here we focus on the ignition stability of n-heptane pilot-fuel jets injected into a compressed premixed charge of natural gas and air at low-load conditions. To aid understanding of the experimental data, chemical-kinetics simulations were carried out in a simplified engine-environment that provided insight into the chemical effects of methane (CH4) on pilot-fuel ignition. The simulations reveal that CH4 has an effect on both stages of n-heptane autoignition: the small, first-stage, cool-flame-type, low-temperature ignition (LTI) and the larger, second-stage, high-temperature ignition (HTI). As the ratio of pilot-fuel to CH4 entrained into the spray decreases, the initial oxidization of CH4 consumes the OH radicals produced by pilot-fuel decomposition during LTI, thereby inhibiting its progression to HTI. Using imaging diagnostics, the spatial and temporal progression of LTI and HTI in DF combustion are measured in a heavy-duty optical engine, and the imaging data are analyzed to understand the cause of severe fluctuations in ignition timing and combustion completeness at low-load conditions. Images of cool-flame and hydroxyl radical (OH*) chemiluminescence serve as indicators of LTI and HTI, respectively. The cycle-to-cycle and spatial variation in ignition extracted from the imaging data are used as key metrics of comparison. The imaging data indicate that the local concentration of the pilot-fuel and the richness of the surrounding natural-gas air mixture are important for LTI and HTI, but in different ways. In particular, higher injection pressures and shorter injection durations increase the mixing rate, leading to lower concentrations of pilot-fuel more quickly, which can inhibit HTI even as LTI remains relatively robust. Decreasing the injection pressure from 80 MPa to 40 MPa and increasing the injection duration from 500 µs to 760 µs maintained constant pilot-fuel mass, while promoting robust transition from LTI to HTI by effectively slowing the mixing rate. This allows enough residence time for the OH radicals, produced by the two-stage ignition chemistry of the pilot-fuel, to accelerate the transition from LTI to HTI before being consumed by CH4 oxidation. Thus from a practical perspective, for a premixed natural gas fuel–air equivalence-ratio, it is possible to improve the “stability” of the combustion process by solely manipulating the pilot-fuel injection parameters while maintaining constant mass of injected pilot-fuel. This allows for tailoring mixing trajectories to offset changes in fuel ignition chemistry, so as to promote a robust transition from LTI to HTI by changing the balance between the local concentration of the pilot-fuel and richness of the premixed natural gas and air. This could prove to be a valuable tool for combustion design to improve fuel efficiency or reduce noise or perhaps even reduce heat-transfer losses by locating early combustion away from in-cylinder walls.

42 ENGINEERING↗

Robot Acting on Moving Bodies (RAMBO): Interaction with tumbling objects

Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Davis, Larry S.↗

Robot acting on moving bodies (RAMBO): Preliminary results

A robot system called RAMBO is being developed. It is equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a moving object. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations nearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enchancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows the use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using parametric cubic splines between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Davis, Larry S.↗

Context Modeler for Wavelet Compression of Spectral Hyperspectral Images

A context-modeling sub-algorithm has been developed as part of an algorithm that effects three-dimensional (3D) wavelet-based compression of hyperspectral image data. The context-modeling subalgorithm, hereafter denoted the context modeler, provides estimates of probability distributions of wavelet-transformed data being encoded. These estimates are utilized by an entropy coding subalgorithm that is another major component of the compression algorithm. The estimates make it possible to compress the image data more effectively than would otherwise be possible. The following background discussion is prerequisite to a meaningful summary of the context modeler. This discussion is presented relative to ICER-3D, which is the name attached to a particular compression algorithm and the software that implements it. The ICER-3D software is summarized briefly in the preceding article, ICER-3D Hyperspectral Image Compression Software (NPO-43238). Some aspects of this algorithm were previously described, in a slightly more general context than the ICER-3D software, in "Improving 3D Wavelet-Based Compression of Hyperspectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. In turn, ICER-3D is a product of generalization of ICER, another previously reported algorithm and computer program that can perform both lossless and lossy wavelet-based compression and decompression of gray-scale-image data. In ICER-3D, hyperspectral image data are decomposed using a 3D discrete wavelet transform (DWT). Following wavelet decomposition, mean values are subtracted from spatial planes of spatially low-pass subbands prior to encoding. The resulting data are converted to sign-magnitude form and compressed. In ICER-3D, compression is progressive, in that compressed information is ordered so that as more of the compressed data stream is received, successive reconstructions of the hyperspectral image data are of successively higher overall fidelity.

Kiely, Aaron↗

Effects of Ionizing Radiation on the Thermodynamic Stability of Boehmite and Gibbsite

Here, in this study, we examined the effect of gamma radiation on the stabilities of aluminum hydroxide (gibbsite) and aluminum oxyhydroxide (boehmite) nanoparticles in relation to their thermal decomposition. X-ray diffraction (XRD) patterns and scanning electron microscopy (SEM) images revealed no significant differences in mineral components or morphology before and after radiation. However, thermogravimetric and differential scanning calorimetry (TGA/DSC) analyses showed that both boehmite and gibbsite nanoparticles experienced decreased mass loss following irradiation. Raman and attenuated total reflection-Fourier transfer infrared (ATR-FTIR) spectra indicated that a fraction of the hydroxyl content in both cases was selectively cleaved by radiation, primarily at the particle surfaces. Quantitative analyses of thermal mass loss behavior demonstrated that irradiated boehmite and gibbsite nanoparticles had higher activation energies than their pristine counterparts, with the extent of the increase dependent on the total dose. Taken together, these findings suggest that exposure to a sufficient dose of ionizing radiation alters these materials such that they are less prone to decomposition by dehydration. This increased stability may be due to the decreased hydrous nature of the samples after radiation exposure, which was supported by further high temperature drop calorimetry. Additionally, a radiation-induced amorphous phase on the nanoparticle surfaces appears to have a permanent and positive influence on their thermodynamic stabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low level image processing techniques using the pipeline image processing engine in the flight telerobotic servicer

The sensory processing system for the NASA/NBS Standard Reference Model (NASREM) for telerobotic control is described. This control system architecture was adopted by NASA of the Flight Telerobotic Servicer. The control system is hierarchically designed and consists of three parallel systems: task decomposition, world modeling, and sensory processing. The Sensory Processing System is examined, and in particular the image processing hardware and software used to extract features at low levels of sensory processing for tasks representative of those envisioned for the Space Station such as assembly and maintenance are described.

Nashman, Marilyn↗

Turbulent flow characteristics in an 84-pin rod bundle for typical and damaged spacer grids

Hexagonal rod bundles arranged in a tightly packed triangular lattice are extensively used for heat transfer and energy generation applications. Staggered spacer grids are used to maintain the structural integrity of gas-cooled fast reactor (GFR) fuel assemblies, while inducing localized turbulence in flow. Damage to these spacer grids results in a disruption of flow fields within these hexagonal fuel bundles. Experimental flow visualizations are critical to identify the differences in local flow properties that the structural damage may cause. This experimental research investigates the flow-field characteristics at a near-wall and center plane in a prototypical 84-pin GFR fuel assembly. Newly installed typical spacers and spacers subject to naturally occurring damage due to material degradation over prolonged experimentation were investigated. Velocity fields were acquired by utilizing the matched-index-of-refraction method to obtain time-resolved particle image velocimetry measurements for a Reynolds number of 12 000. Reynolds decomposition statistical results divulged differences in the time-averaged velocity, velocity fluctuations, flow anisotropy, and Reynolds stress distributions. Galilean decomposition demarcated the influence of spacer grid damage on the velocity fields. To extract turbulent structures and elucidate mechanisms of flow instabilities, proper orthogonal decomposition analysis was employed. Reduced order flow reconstructions enabled the application of vortex identification algorithms to determine the spatial and statistical characteristics of vortices generated. This research work provides unique experimental data on the spacer grid condition-dependent flow. The results offer a deeper understanding of fluid dynamics behavior to support GFR rod bundle design efforts and computational fluid dynamics model validation.

36 MATERIALS SCIENCE↗

Unveiling the Nature of Polar-ring Galaxies from Deep Imaging

Abstract General structural properties and low surface brightness tidal features hold important clues to the formation of galaxies. In this paper, we study a sample of polar-ring galaxies (PRGs) based on optical imaging from the Sloan Digital Sky Survey Stripe 82 and other deep surveys. We investigate the deepest images of candidates for PRGs to date. We carry out photometric decomposition on the host galaxies and associated polar structures that allows us to derive the structural properties of both components. We are able to detect very faint tidal structures around most PRGs in our sample. For several galaxies, we can directly observe the formation of the polar ring due to merging, which is manifested in debris of the victim galaxy and an arc-like polar structure made up of its material. In a few cases, we can discern signs of tidal accretion. The results obtained indicate that the gravitational interaction and merging of galaxies are the most plausible mechanisms for the formation of PRGs.

Astronomy & Astrophysics↗

21 cm Power Spectrum Analysis of North Celestial Pole Observations with the Tianlai Dish Pathfinder Array

The Tianlai Dish Pathfinder Array (TDPA) is a radio interferometer designed to test techniques for 21 cm intensity mapping in the post-reionization Universe as a means of measuring large-scale cosmic structure. Using nine nights of observations targeting the North Celestial Pole field, totaling approximately 107 hr of integration time, we analyze data in the frequency range 700–800 MHz (corresponding to redshift z ∼ 0.9). We do the data format conversion, radio frequency interference flagging, calibration, imaging and point source subtraction, and foreground removal via Singular Value Decomposition. The spherically averaged power spectrum Δ 2 (k) is obtained. Furthermore, this work successfully establishes and validates a comprehensive data analysis framework for the TDPA. We identify key improvements including sky model refinement, increased integration time, and pipeline optimization that will enable future detection of the 21 cm signal through auto-correlation and cross-correlation with optical galaxy surveys.

cosmology: large-scale structure of universe↗

Transverse mode analysis for free-space laser beams using Bayesian analysis

Reliable and rapid assessment of the transverse mode quality of a free-space laser beam has a wide range of applications in laser development, research, and utilization. It has become even more important with recent advances in developing orbital angular momentum photon beams across a broad spectral region. In this work, a general modal analysis method for a free-space multimode laser beam has been developed based on Bayesian analysis. After transforming mode decomposition into a linear system problem, a Gaussian probabilistic model is used to find a closed-form solution. The method is found to be robust with the presence of Gaussian noise. Prior knowledge about the mode content can be incorporated into the method to improve the solution for situations when coherent disturbances or contamination are present in the laser beam. This method can be used to analyze the mode content for laser beams in different bases, such as Hermite–Gaussian (HG) modes and Laguerre–Gaussian (LG) modes. Three applications of this method are presented: a detailed modal analysis of the beam image from the incoherent intensity addition of HG modes and two examples of mode decomposition using the complex wavefront from the coherent superposition of HG and LG modes. The feasibility of this method is demonstrated using various simulation results. Based on digital images of a laser beam recorded without complex wavelength-limiting optics, in principle, this method can be used in a wide wavelength range from infrared to ultraviolet, and possibly x ray.

Liu, Peifan (ORCID:0000000273816153)↗

Microwave Imaging on Metal Objects

This final report for the project discusses the attempts to model, using different methods, microwave image reconstruction. Maximum Entropy Method was not successful. Attempts to use Singular Value Decomposition (SVD) got some good results after initial failure. SVD is based upon a theory of linear algebra, to the effect that any M X N Matrix A whose number of rows M is greater than or equal to its number of columns, N can be written as the product of an M X N column-orthogonal matrix U, an N X N diagonal Matrix, W, with m positive or zero elements (the singular values) and the transposition of an N X N orthogonal matrix V. In microwave imaging, the scattered fields can be expressed by the induced current distribution. The SVD method required more contiguous computer memory than was available. Work was also done on the Conjugate Gradient Method (CGM), which didn't work well when tried earlier. It was found that separation of the imaginary part and the real part during calculation may work. This work was considered incomplete as of the end of the grant period.

Tolliver, C. L.↗

HRTEM Imaging and Mechanistic Insights Into Carbon Nanotube Nucleation and Growth on Fe Nanocatalysts in a Thermal Plasma

Thermal plasma decomposition of natural gas is a scalable pathway for the production of hydrogen alongside high-value carbon nanotubes (CNTs). Metals evaporate from an electrode and condense to form seed nanoparticles that nucleate and grow CNTs. However, the lack of mechanistic understanding of the CNT nucleation and growth processes in thermal plasma makes control over CNT diameter, chirality, length, and yield difficult. We debundled and separated CNTs from soots produced using iron (Fe) nanocatalysts, and distributed them on monolayer graphene for high-resolution transmission electron microscopy (HRTEM) imaging to gain mechanistic insights. Full graphene encapsulation was found for relatively small Fe nanoparticles that were molten at high temperatures. Zigzag single-wall or double-wall CNTs (SWCNTs or DWCNTs) appeared to have grown out directly from the graphene covering on the conical or cylindrical bodies of small molten Fe nanodroplets with high curvature. Also, SWCNTs likely grew out from H- or O-atom etched single-wall carbon nanocones observed on conical Fe nanoparticles. A SWCNT/DWCNT could also be generated from the cracked opening of the graphene covering on a face-centered cubic (FCC) Fe nanoparticle. A simple, plausible pathway is proposed for the growth of an open, H-passivated, zigzag SWCNT involving reaction of CH 2 and CH radicals at high temperatures.

Fe nanocatalysts↗

Morphological Feature Extraction for Automatic Registration of Multispectral Images

The task of image registration can be divided into two major components, i.e., the extraction of control points or features from images, and the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual extraction of control features can be subjective and extremely time consuming, and often results in few usable points. On the other hand, automated feature extraction allows using invariant target features such as edges, corners, and line intersections as relevant landmarks for registration purposes. In this paper, we present an extension of a recently developed morphological approach for automatic extraction of landmark chips and corresponding windows in a fully unsupervised manner for the registration of multispectral images. Once a set of chip-window pairs is obtained, a (hierarchical) robust feature matching procedure, based on a multiresolution overcomplete wavelet decomposition scheme, is used for registration purposes. The proposed method is validated on a pair of remotely sensed scenes acquired by the Advanced Land Imager (ALI) multispectral instrument and the Hyperion hyperspectral instrument aboard NASA's Earth Observing-1 satellite.

Plaza, Antonio↗

Gaussian Decomposition of Laser Altimeter Waveforms

We develop a method to decompose a laser altimeter return waveform into its Gaussian components assuming that the position of each Gaussian within the waveform can be used to calculate the mean elevation of a specific reflecting surface within the laser footprint. We estimate the number of Gaussian components from the number of inflection points of a smoothed copy of the laser waveform, and obtain initial estimates of the Gaussian half-widths and positions from the positions of its consecutive inflection points. Initial amplitude estimates are obtained using a non-negative least-squares method. To reduce the likelihood of fitting the background noise within the waveform and to minimize the number of Gaussians needed in the approximation, we rank the "importance" of each Gaussian in the decomposition using its initial half-width and amplitude estimates. The initial parameter estimates of all Gaussians ranked "important" are optimized using the Levenburg-Marquardt method. If the sum of the Gaussians does not approximate the return waveform to a prescribed accuracy, then additional Gaussians are included in the optimization procedure. The Gaussian decomposition method is demonstrated on data collected by the airborne Laser Vegetation Imaging Sensor (LVIS) in October 1997 over the Sequoia National Forest, California.

Hofton, Michelle A.↗

Three-Dimensional Stereoscopic Tracking Velocimetry and Experimental/Numerical Comparison of Directional Solidification

Measurement of three-dimensional (3-D) three-component velocity fields is of great importance in both ground and space experiments for understanding materials processing and fluid physics. The experiments in these fields most likely inhibit the application of conventional planar probes for observing 3-D phenomena. Here, we present the investigation results of stereoscopic tracking velocimetry (STV) for measuring 3-D velocity fields, which include diagnostic technology development, experimental velocity measurement, and comparison with analytical and numerical computation. STV is advantageous in system simplicity for building compact hardware and in software efficiency for continual near-real-time monitoring. It has great freedom in illuminating and observing volumetric fields from arbitrary directions. STV is based on stereoscopic observation of particles-Seeded in a flow by CCD sensors. In the approach, part of the individual particle images that provide data points is likely to be lost or cause errors when their images overlap and crisscross each other especially under a high particle density. In order to maximize the valid recovery of data points, neural networks are implemented for these two important processes. For the step of particle overlap decomposition, the back propagation neural network is utilized because of its ability in pattern recognition with pertinent particle image feature parameters. For the step of particle tracking, the Hopfield neural network is employed to find appropriate particle tracks based on global optimization. Our investigation indicates that the neural networks are very efficient and useful for stereoscopically tracking particles. As an initial assessment of the diagnostic technology performance, laminar water jets with and without pulsation are measured. The jet tip velocity profiles are in good agreement with analytical predictions. Finally, for testing in material processing applications, a simple directional solidification apparatus is built for experimenting with a metal analog of succinonitrile. Its 3-D velocity field at the liquid phase is then measured to be compared with those from numerical computation. Our theoretical, numerical, and experimental investigations have proven STV to be a viable candidate for reliably measuring 3-D flow velocities. With current activities are focused on further improving the processing efficiency, overall accuracy, and automation, the eventual efforts of broad experimental applications and concurrent numerical modeling validation will be vital to many areas in fluid flow and materials processing.

Lee, David↗