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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fiber and bundle orientations, matrix rich regions, and mechanical properties of fiber reinforced composites using thermal digital image correlation

Methods for assessing fiber and bundle orientations and mechanical properties of fiber reinforced composite materials using Thermal Digital Image Correlation (TDIC) are disclosed. In some examples, the method comprises exposing the composite material to a temperature change; imaging the composite material at a plurality of time points before, during and/or after the temperature change; and assessing the characteristic of the composite material based on the imaging. In others, temperature changes naturally occur during the cooling process after manufacturing can be employed for this method such as compression molding process, injection molding process, resin transfer molding processes and its variants.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Scalable Track Detection in SAR CCD Images

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988, up fr om 0.907 obtained by the current state-of-the-art method.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

TH-EF-207A-05: Feasibility of Applying SMEIR Method On Small Animal 4D Cone Beam CT Imaging

Purpose: Small animal cone beam CT imaging has been widely used in preclinical research. Due to the higher respiratory rate and heat beats of small animals, motion blurring is inevitable and needs to be corrected in the reconstruction. Simultaneous motion estimation and image reconstruction (SMEIR) method, which uses projection images of all phases, proved to be effective in motion model estimation and able to reconstruct motion-compensated images. We demonstrate the application of SMEIR for small animal 4D cone beam CT imaging by computer simulations on a digital rat model. Methods: The small animal CBCT imaging system was simulated with the source-to-detector distance of 300 mm and the source-to-object distance of 200 mm. A sequence of rat phantom were generated with 0.4 mm{sup 3} voxel size. The respiratory cycle was taken as 1.0 second and the motions were simulated with a diaphragm motion of 2.4mm and an anterior-posterior expansion of 1.6 mm. The projection images were calculated using a ray-tracing method, and 4D-CBCT were reconstructed using SMEIR and FDK methods. The SMEIR method iterates over two alternating steps: 1) motion-compensated iterative image reconstruction by using projections from all respiration phases and 2) motion model estimation from projections directly through a 2D-3D deformable registration of the image obtained in the first step to projection images of other phases. Results: The images reconstructed using SMEIR method reproduced the features in the original phantom. Projections from the same phase were also reconstructed using FDK method. Compared with the FDK results, the images from SMEIR method substantially improve the image quality with minimum artifacts. Conclusion: We demonstrate that it is viable to apply SMEIR method to reconstruct small animal 4D-CBCT images.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Limited Angle Reconstruction Method for Reconstructing Terrestrial Plasmaspheric Densities from EUV Images

A new method for reconstructing the global 3D distribution of plasma densities in the plasmasphere from a limited number of 2D views is presented. The method is aimed at using data from the Extreme Ultra Violet (EUV) sensor on NASA s Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) satellite. Physical properties of the plasmasphere are exploited by the method to reduce the level of inaccuracy imposed by the limited number of views. The utility of the method is demonstrated on synthetic data.

Newman, Timothy↗
NASA NTRS1999

Method and System for Producing Images of an Object

A method and system are provided to produce images of an object. A receiving station is positioned in view of a range-coded signal emitting satellite and the object. The receiving station is sensitive to direct transmission of the range-coded signal and reflections of the range-coded signal from the object. Both range from the receiving station to the object and a Doppler frequency shift history between the receiving station and the object is determined using the direct transmission and reflections of the range-coded signal. An image is formed using the two-dimensional record provided by the range and the Doppler frequency shift history.

Katzberg, Stephen J.↗
NASA NTRS1991

Radiometric rectification - Toward a common radiometric response among multidate, multisensor images

A method is developed for relating scene digital counts among several images of the same scene by identifying radiometric control sets with mean reflectances that are basically constant. The average digital-count values of the control sets are utilized to compute linear transforms that relate digital count values between images. Two Landsat TM images are studied by means of the technique using simulations of a wide range of atmospheric conditions. In the visible and near-IR bands the algorithm effectively adjusts the surface reflectance for the effects of relative atmospheric differences to within 1 percent. The proposed method is found to be an effective relative correction procedure that can be used when atmospheric optical-depth data and calibration coefficients are not available.

Hall, F. G.↗
DOE OSTI2016

TH-CD-207A-09: Stay On Target: Dynamic, Patient-Specific Templates of Fiducial Marker Clusters for IGRT

Purpose: Pancreatic SBRT relies on extremely accurate delivery of ablative radiation doses to the target, and intra-fractional tracking of fiducial markers can facilitate improvements in dose delivery. However, this requires algorithms that are able to find fiducial markers with high speed and accuracy. The purpose of this study was to develop a novel marker tracking algorithm that is robust against many of the common errors seen with traditional template matching techniques. Methods: Using CBCT projection images, a method was developed to create detailed template images of fiducial marker clusters without prior knowledge of the number of markers, their positions, or their orientations. Briefly, the method (i) enhances markers in projection images, (ii) stabilizes the cluster’s position, (iii) reconstructs the cluster in 3D, and (iv) precomputes a set of static template images dependent on gantry angle. Furthermore, breathing data were used to produce 4D reconstructions of clusters, yielding dynamic template images dependent on gantry angle and breathing amplitude. To test these two approaches, static and dynamic templates were used to track the motion of marker clusters in more than 66,000 projection images from 75 CBCT scans of 15 pancreatic SBRT patients. Results: For both static and dynamic templates, the new technique was able to locate marker clusters present in projection images 100% of the time. The algorithm was also able to correctly locate markers in several instances where only some of the markers were visible due to insufficient field-of-view. In cases where clusters exhibited deformation and/or rotation during breathing, dynamic templates resulted in cross-correlation scores up to 70% higher than static templates. Conclusion: Patient-specific templates provided complete tracking of fiducial marker clusters in CBCT scans, and dynamic templates helped to provide higher cross-correlation scores for deforming/rotating clusters. This novel algorithm provides an extremely accurate method to detect fiducial markers during treatment. Research funding provided by Varian Medical Systems to Miften and Jones.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Three-Dimensional Evaluation of Sand Particle Fracture Using Discrete-Element Method and Synchrotron Microcomputed Tomography Images

Recent research showed that fracture of sand particles plays a significant role in determining the plastic bulk volumetric changes of granular materials under different loading conditions. One of the major tools used to better understand the influence of particle fracture on the behavior of granular materials is discrete-element modeling (DEM). This paper employed the bonded block model (BBM) to simulate the fracture behavior of sand. Each sand particle is modeled as an agglomerate of rigid blocks bonded at their contacts using the linear-parallel contact model, which can transmit both moment and force. DEM simulated particles closely matched the actual three-dimensional (3D) shape of sand particles acquired using high-resolution 3D synchrotron microcomputed tomography (SMT). Results from unconfined one-dimensional (1D) compression of a single synthetic silica cube were used to calibrate the model parameters. Particle fracture was investigated for specimens composed of three sand particles that were loaded under confined 1D compression. Breakage energy measured from DEM models matched well with that measured experimentally. The paper studied the effects of contact loading condition and particle interaction on the fracture mode of particles using BBM that can closely capture the 3D shape of real sand particles.

58 GEOSCIENCES↗
DOE OSTI2016

Characterization of encapsulated quantum dots via electron channeling contrast imaging

A method for characterization of encapsulated epitaxial quantum dots (QD) in plan-view geometry using electron channeling contrast imaging (ECCI) is presented. The efficacy of the method, which requires minimal sample preparation, is demonstrated with proof-of-concept data from encapsulated (sub-surface) epitaxial InAs QDs within a GaAs matrix. Imaging of the QDs under multiple diffraction conditions is presented, establishing that ECCI can provide effectively identical visualization capabilities as conventional two-beam transmission electron microscopy. This method facilitates rapid, non-destructive characterization of sub-surface QDs giving immediate access to valuable nanostructural information.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

MO-FG-204-01: Improved Noise Suppression for Dual-Energy CT Through Entropy Minimization

Purpose: In dual energy CT (DECT), noise amplification during signal decomposition significantly limits the utility of basis material images. Since clinically relevant objects contain a limited number of materials, we propose to suppress noise for DECT based on image entropy minimization. An adaptive weighting scheme is employed during noise suppression to improve decomposition accuracy with limited effect on spatial resolution and image texture preservation. Methods: From decomposed images, we first generate a 2D plot of scattered data points, using basis material densities as coordinates. Data points representing the same material generate a highly asymmetric cluster. We orient an axis by minimizing the entropy in a 1D histogram of these points projected onto the axis. To suppress noise, we replace pixel values of decomposed images with center-of-mass values in the direction perpendicular to the optimal axis. To limit errors due to cluster overlap, we weight each data point’s contribution based on its high and low energy CT values and location within the image. The proposed method’s performance is assessed on physical phantom studies. Electron density is used as the quality metric for decomposition accuracy. Our results are compared to those without noise suppression and with a recently developed iterative method. Results: The proposed method reduces noise standard deviations of the decomposed images by at least one order of magnitude. On the Catphan phantom, this method greatly preserves the spatial resolution and texture of the CT images and limits induced error in measured electron density to below 1.2%. In the head phantom study, the proposed method performs the best in retaining fine, intricate structures. Conclusion: The entropy minimization based algorithm with adaptive weighting substantially reduces DECT noise while preserving image spatial resolution and texture. Future investigations will include extensive investigations on material decomposition accuracy that go beyond the current electron density calculations. This work was supported in part by the National Institutes of Health (NIH) under Grant Number R21 EB012700.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Systems and methods for detecting an image of an object using multi-beam imaging from an X-ray beam having a polychromatic distribution

Systems and methods for detecting an image of an object using a multi-beam imaging system from an x-ray beam having a polychromatic energy distribution are disclosed. According to one aspect, a method can include generating a first X-ray beam having a polychromatic energy distribution. Further, the method can include positioning a plurality of monochromator crystals in a predetermined position to directly intercept the first X-ray beam such that a plurality of second X-ray beams having predetermined energy levels are produced. Further, an object can be positioned in the path of the second X-ray beams for transmission of the second X-ray beams through the object and emission from the object as transmitted X-ray beams. The transmitted X-ray beams can each be directed at an angle of incidence upon one or more crystal analyzers. Further, an image of the object can be detected from the beams diffracted from the analyzer crystals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1994

Image-adapted visually weighted quantization matrices for digital image compression

A method for performing image compression that eliminates redundant and invisible image components is presented. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Watson, Andrew B.↗
DOE OSTI2025

Robust measurement of microbial reduction of graphene oxide nanoparticles using image analysis

ABSTRACT Shewanella oneidensis ( S. oneidensis ) has the capacity to reduce electron acceptors within a medium and is thus used frequently in microbial fuel generation, pollutant breakdown, and nanoparticle fabrication. Microbial fuel setups, however, often require costly or labor-intensive components, thus making optimization of their performance onerous. For rapid optimization of setup conditions, a model reduction assay can be employed to allow simultaneous, large-scale experiments at lower cost and effort. Since S. oneidensis uses different extracellular electron transfer pathways depending on the electron acceptor, it is essential to use a reduction assay that mirrors the pathways employed in the microbial fuel system. For microbial fuel setups that use nanoparticles to stimulate electron transfer, reduction of graphene oxide provides a more accurate model than other commonly used assays as it is a bulk material that forms flocculates in solutions with a large ionic component. However, graphene oxide flocculates can interfere with traditional absorbance-based measurement techniques. This study introduces a novel image analysis method for quantifying graphene oxide reduction, showing improved performance and statistical accuracy over traditional methods. A comparative analysis shows that the image analysis method produces smaller errors between replicates and reveals more statistically significant differences between samples than traditional plate reader measurements under conditions causing graphene oxide flocculation. Image analysis can also detect reduction activity at earlier time points due to its use of larger solution volumes, enhancing color detection. These improvements in accuracy make image analysis a promising method for optimizing microbial fuel cells that use nanoparticles or bulk substrates. IMPORTANCE Shewanella oneidensis ( S. oneidensis ) is widely used in reduction processes such as microbial fuel generation due to its capacity to reduce electron acceptors. Often, these setups are labor-intensive to operate and require days to produce results, so use of a model assay would reduce the time and expenses needed for optimization. Our research developed a novel digital analysis method for analysis of graphene oxide flocculates that may be utilized as a model assay for reduction platforms featuring nanoparticles. Use of this model reduction assay will enable rapid optimization and drive improvements in the microbial fuel generation sector.

Bennett, Danielle T. (ORCID:0009000188748827)↗
NASA NTRS2013

Method and Apparatus for Computed Imaging Backscatter Radiography

Systems and methods of x-ray backscatter radiography are provided. A single-sided, non-destructive imaging technique utilizing x-ray radiation to image subsurface features is disclosed, capable of scanning a region using a fan beam aperture and gathering data using rotational motion.

Shedlock, Daniel↗
DOE OSTI2020

Topological analysis of X-ray CT data for the recognition and trending of subtle changes in microstructure under material aging

X-ray computed tomography (CT) is an established non-destructive tool for 3D imaging of multiphasic composites. Numerous applications of X-ray CT in medical diagnosis and materials characterization have been reported, many involving field-specific innovations in the imaging technology itself. Yet, quantitative summarization to link image features to properties of interest has been rare. Here we address this issue by employing state-of-the-art technics in scalar field topology for the summarization of X-ray CT images of an example biphasic system. By varying processing-parameters we create different microstructures, evolve them through accelerated thermal aging, CT-image them pre- and post-aged, and demonstrate the ability of our image summarization method to systematically track process- and age-related changes, which can often be very subtle. A novel aspect of the algorithm involves recognition over multiple resolution levels, which provides deeper insight into the pattern relationship between grain-like features and their neighbors. The method is general, adaptable to diverse image reconstruction methods and materials systems, and particularly useful in applications where practical constraints on the sample-size limits the reliable use of more complex models, e.g., convolutional neural networks.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Compositions for binding sphingosine-1-phosphate receptor 1 (S1P1), imaging of S1P1, and methods of use thereof

Among the various aspects of the present disclosure is the provision of a compositions for binding sphingosine-1-phosphate receptor 1 (S1P1), imaging of S1P1, and methods of use thereof. Provided are imaging agents for imaging S1P1 and S1P1 associated diseases, disorders, and conditions. Also provided are therapeutic compositions and methods for the treatment of S1P1 associated diseases, disorders, and conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

MO-DE-207A-07: Filtered Iterative Reconstruction (FIR) Via Proximal Forward-Backward Splitting: A Synergy of Analytical and Iterative Reconstruction Method for CT

Purpose: This work is to develop a general framework, namely filtered iterative reconstruction (FIR) method, to incorporate analytical reconstruction (AR) method into iterative reconstruction (IR) method, for enhanced CT image quality. Methods: FIR is formulated as a combination of filtered data fidelity and sparsity regularization, and then solved by proximal forward-backward splitting (PFBS) algorithm. As a result, the image reconstruction decouples data fidelity and image regularization with a two-step iterative scheme, during which an AR-projection step updates the filtered data fidelity term, while a denoising solver updates the sparsity regularization term. During the AR-projection step, the image is projected to the data domain to form the data residual, and then reconstructed by certain AR to a residual image which is in turn weighted together with previous image iterate to form next image iterate. Since the eigenvalues of AR-projection operator are close to the unity, PFBS based FIR has a fast convergence. Results: The proposed FIR method is validated in the setting of circular cone-beam CT with AR being FDK and total-variation sparsity regularization, and has improved image quality from both AR and IR. For example, AIR has improved visual assessment and quantitative measurement in terms of both contrast and resolution, and reduced axial and half-fan artifacts. Conclusion: FIR is proposed to incorporate AR into IR, with an efficient image reconstruction algorithm based on PFBS. The CBCT results suggest that FIR synergizes AR and IR with improved image quality and reduced axial and half-fan artifacts. The authors was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).

60 APPLIED LIFE SCIENCES↗
NASA NTRS2018

Mapping Mangrove Extent and Change: A Globally Applicable Approach

This study demonstrates a globally applicable method for monitoring mangrove forest extent at high spatial resolution. A 2010 mangrove baseline was classified for 16 study areas using a combination of ALOS PALSAR and Landsat composite imagery within a random forests classifier. A novel map-to-image change method was used to detect annual and decadal changes in extent using ALOS PALSAR/JERS-1 imagery. The map-to-image method presented makes fewer assumptions of the data than existing methods, is less sensitive to variation between scenes due to environmental factors (e.g., tide or soil moisture) and is able to automatically identify a change threshold. Change maps were derived from the 2010 baseline to 1996 using JERS-1 SAR and to 2007, 2008 and 2009 using ALOS PALSAR. This study demonstrated results for 16 known hotspots of mangrove change distributed globally, with a total mangrove area of 2,529,760 ha. The method was demonstrated to have accuracies consistently in excess of 90% (overall accuracy: 92.2–93.3%, kappa: 0.86) for mapping baseline extent. The accuracies of the change maps were more variable and were dependent upon the time period between images and number of change features. Total change from 1996 to 2010 was 204,850 ha (127,990 ha gain, 76,860 ha loss), with the highest gains observed in French Guiana (15,570 ha) and the highest losses observed in East Kalimantan, Indonesia (23,003 ha). Changes in mangrove extent were the consequence of both natural and anthropogenic drivers, yielding net increases or decreases in extent dependent upon the study site. These updated maps are of importance to the mangrove research community, particularly as the continual updating of the baseline with currently available and anticipated spaceborne sensors. It is recommended that mangrove baselines are updated on at least a 5-year interval to suit the requirements of policy makers.

Thomas, Nathan↗