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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

X-ray phase contrast imaging of the breast: Analysis of tissue simulating materials

Purpose: Phase contrast imaging, particularly of the breast, is being actively investigated. The purpose of this work is to investigate the x-ray phase contrast properties of breast tissues and commonly used breast tissue substitutes or phantom materials with an aim of determining the phantom materials best representative of breast tissues. Methods: Elemental compositions of breast tissues including adipose, fibroglandular, and skin were used to determine the refractive index, n= 1 -{delta}+i {beta}. The real part of the refractive index, specifically the refractive index decrement ({delta}), over the energy range of 5-50 keV were determined using XOP software (version 2.3, European Synchrotron Radiation Facility, France). Calcium oxalate and calcium hydroxyapatite were considered to represent the material compositions of microcalcifications in vivo. Nineteen tissue substitutes were considered as possible candidates to represent adipose tissue, fibroglandular tissue and skin, and four phantom materials were considered as possible candidates to represent microcalcifications. For each material, either the molecular formula, if available, or the elemental composition based on weight fraction, was used to determine {delta}. At each x-ray photon energy, the absolute percent difference in {delta} between the breast tissue and the substitute material was determined, from which three candidates were selected. From these candidate tissue substitutes, the material that minimized the absolute percent difference in linear attenuation coefficient {mu}, and hence {beta}, was considered to be best representative of that breast tissue. Results: Over the energy range of 5-50 keV, while the {delta} of CB3 and fibroglandular tissue-equivalent material were within 1% of that of fibroglandular tissue, the {mu} of fibroglandular tissue-equivalent material better approximated the fibroglandular tissue. While the {delta} of BR10 and adipose tissue-equivalent material were within 1% of that of adipose tissue, the tissue-equivalent material better approximated the adipose tissue in terms of {mu}. Polymethyl methacrylate, a commonly used tissue substitute, exhibited {delta} greater than fibroglandular tissue by {approx}12%. The A-150 plastic closely approximated the skin. Several materials exhibited {delta} between that of adipose and fibroglandular tissue. However, there was an energy-dependent mismatch in terms of equivalent fibroglandular weight fraction between {delta} and {mu} for these materials. For microcalcifications, aluminum and calcium carbonate were observed to straddle the {delta} and {mu} of calcium oxalate and calcium hydroxyapatite. Aluminum oxide, commonly used to represent microcalcifications in the American College of Radiology recommended phantoms for accreditation exhibited {delta} greater than calcium hydroxyapatite by {approx}23%. Conclusions: A breast phantom comprising A-150 plastic to represent the skin, commercially available adipose and fibroglandular tissue-equivalent formulations to represent adipose and fibroglandular tissue, respectively, was found to be best suited for x-ray phase-sensitive imaging of the breast. Calcium carbonate or aluminum can be used to represent microcalcifications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Simulations of the STIS CCD clear imaging mode PSF

Detailed understanding of the properties of the point-spread function (PSF) of Space Telescope Imaging Spectrograph (STIS) imaging modes is necessary to separate real effects of geometrically complex astronomical sources, such as protoplanetary disks surrounding bright stars, from instrumental effects, such as scattering and diffraction. In order to investigate STIS imaging properties we have numerically simulated broadband stellar PSFs generated by STIS in CCD clear imaging mode, including the effects of the Lyot stop and the coronagraphic wedges. The input spectrum is a stellar model atmosphere of the appropriate spectral type, convolved with the pre-flight STIS CCD response function. The PSF modeler generates broadband PSFs by co-adding weighted monochromatic PSFs across the waveband.

Cornett, R. H.↗
DOE OSTI2022

Defect identification in simulated Bragg coherent diffraction imaging by automated AI

X-ray Bragg coherent diffraction imaging is a powerful technique for operando and in situ materials characterization and provides a unique means of quantifying the influence of one-dimensional (1D) and two-dimensional (2D) material defects on material response. However, obtaining full images from raw x-ray diffraction data is nontrivial and computationally intensive, precluding real-time experimental feedback. Here, we present a machine learning approach to identify the presence of crystalline line defects (edge and screw) in samples from the raw, 2D, coherent diffraction data without the need for image reconstruction through iterative phase retrieval. Further, we compare different approaches to designing neural networks for this application and demonstrate the potential of automated ML (autoML) approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-E-J-135: An Investigation of Ultrasound Imaging for 3D Intra-Fraction Prostate Motion Estimation

Purpose: This study investigates the use of a mechanically swept 3D ultrasound (US) probe to estimate intra-fraction motion of the prostate during radiation therapy using an US phantom and simulated transperineal imaging. Methods: A 3D motion platform was used to translate an US speckle phantom while simulating transperineal US imaging. Motion patterns for five representative types of prostate motion, generated from patient data previously acquired with a Calypso system, were using to move the phantom in 3D. The phantom was also implanted with fiducial markers and subsequently tracked using the CyberKnife kV x-ray system for comparison. A normalised cross correlation block matching algorithm was used to track speckle patterns in 3D and 2D US data. Motion estimation results were compared with known phantom translations. Results: Transperineal 3D US could track superior-inferior (axial) and anterior-posterior (lateral) motion to better than 0.8 mm root-mean-square error (RMSE) at a volume rate of 1.7 Hz (comparable with kV x-ray tracking RMSE). Motion estimation accuracy was poorest along the US probe's swept axis (right-left; RL; RMSE < 4.2 mm) but simple regularisation methods could be used to improve RMSE (< 2 mm). 2D US was found to be feasible for slowly varying motion (RMSE < 0.5 mm). 3D US could also allow accurate radiation beam gating with displacement thresholds of 2 mm and 5 mm exhibiting a RMSE of less than 0.5 mm. Conclusion: 2D and 3D US speckle tracking is feasible for prostate motion estimation during radiation delivery. Since RL prostate motion is small in magnitude and frequency, 2D or a hybrid (2D/3D) US imaging approach which also accounts for potential prostate rotations could be used. Regularisation methods could be used to ensure the accuracy of tracking data, making US a feasible approach for gating or tracking in standard or hypo-fractionated prostate treatments.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

Introduction The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗
NASA NTRS2018

Design and Development of Modules to Support Live Microscopic Imaging on Ground-Based Microgravity Simulators

In space, astronauts are exposed to environmental stressors that often result in physiological changes. One prominent stressor in spaceflight is microgravity, and research has shown that long term microgravity exposure causes muscle atrophy, bone loss, cardiovascular concerns, and vision impairment. It is critical to understand how altered gravity affects physiology on the cellular, molecular, and gene level in order to accurately assess health risks and to develop effective countermeasures. Ground-based microgravity simulators such as random positioning machines (RPMs) are used to produce some of the biological effects of altered gravity on different cell types and organisms. Real-time imaging during simulations are of particular interest as we can study how basic cell functions such as cell division, cell migration, and proliferation progress under microgravity conditions. However, design limitations of present microgravity simulators such as susceptibility to parasitic vibration and displacement of the sample from the center of rotation challenge the accuracy of experiment results and live images. We have developed a cell culture sample holder module suitable for live microscopic imaging on an RPM. CAD modeling and 3D printing technology were used to implement modifications to the sample holder and to install a digital microscope to perform live bright-field and fluorescent imaging. Vibration damping materials were also investigated to allow for stable imaging while the microgravity simulator was within a cell culture incubator. Novel methods and hardware modifications for improving live cell imaging on ground-based microgravity simulators were proposed and discussed.

3D printing↗
DOE OSTI2019

An Extended Catalog of Galaxy–Galaxy Strong Gravitational Lenses Discovered in DES Using Convolutional Neural Networks

We search Dark Energy Survey (DES) Year 3 imaging for galaxy–galaxy strong gravitational lenses using convolutional neural networks, extending previous work with new training sets and covering a wider range of redshifts and colors. We train two neural networks using images of simulated lenses, then use them to score postage-stamp images of 7.9 million sources from DES chosen to have plausible lens colors based on simulations. We examine 1175 of the highest-scored candidates and identify 152 probable or definite lenses. Examining an additional 20,000 images with lower scores, we identify a further 247 probable or definite candidates. After including 86 candidates discovered in earlier searches using neural networks and 26 candidates discovered through visual inspection of blue-near-red objects in the DES catalog, we present a catalog of 511 lens candidates.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Energy Minimization of Molecular Features Observed on the (110) Face of Lysozyme Crystals

Molecular dynamics and energy minimization have been carried out using the program XPLOR to check the plausibility of a model lysozyme crystal surface. The molecular features of the (110) face of lysozyme were observed using atomic force microscopy (AFM). A model of the crystal surface was constructed using the PDB file 193L, and was used to simulate an AFM image. Molecule translations, van der Waals radii, and assumed AFM tip shape were adjusted to maximize the correlation coefficient between the experimental and simulated images. The highest degree of 0 correlation (0.92) was obtained with the molecules displaced over 6 A from their positions within the bulk of the crystal. The quality of this starting model, the extent of energy minimization, and the correlation coefficient between the final model and the experimental data will be discussed.

Perozzo, Mary A.↗
DOE OSTI2025

End–to–End Metasurface Design for Temperature Imaging via Broadband Planck‐Radiation Regression

A theoretical framework is presented for temperature imaging from long-wavelength infrared (LWIR) thermal radiation (e.g., 8–12 µm) through the end-to-end design of a metasurface-optics frontend and a computational-reconstruction backend. A new nonlinear reconstruction algorithm, “Planck regression”, is introduced to reconstruct the temperature map from a gray scale sensor image, even in the presence of severe chromatic aberration, by exploiting black body and optical physics particular to thermal imaging. This algorithm is combined with an end-to-end approach that optimizes manufacturable, single-layer metasurfaces to yield the most accurate reconstruction. The designs demonstrate high-quality, noise-robust reconstructions of arbitrary temperature maps (including completely random images) in simulations of an ultra-compact thermal-imaging device. Here, it is also shown that Planck regression is much more generalizable to arbitrary images than a straightforward neural-network reconstruction, which requires a large training set of domain-specific images.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Micro-CT Imaging and Fluid Flow Simulations of Fractures in MSEEL Shale

micro-CT scans of a naturally fractured MSEEL shale sample as a shear fracture is generated and displaced in the center, intact region of the sample. Steady State laminar fluid flow simulations were then performed on each individual fracture during each experimental segment as effective stress and shear displacement changed. Released under LA-UR-21-24335.

Fractures,Fracturing Initiation,Marcellus Shale↗
NASA NTRS1984

Remote detection of geobotanical anomalies associated with hydrocarbon microseepage using thematic mapper simulator (TMS) and airborne imaging spectrometer (AIS) data

An interpretation of TMS and AIS data sets collected from Lost River, West Virginia, are presented, along with a brief review of the supervised vegetation classification approach to vegetation mapping used at Lost River. A preliminary study of AIS data suggests that contiguous high-spectral resolution data from a very limited portion of the spectrum (1.2-1.5 micron) provide a greater discriminatory capability than do broad-band sensors such as the TMS covering of wider spectral range (0.45-2.35 microns).

Rock, B. N.↗