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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

An Advanced Approach to Simultaneous Monitoring of Multiple Bacteria in Space

The utility of a novel microarray-based microbial analyzer was demonstrated by the rapid detection, imaging, and identification of a mixture of microorganisms found in a waste water sample from the Lunar-Mars Life Support Test Project through the synergistic combination of: (1) judicious RNA probe selection via algorithms developed by University of Houston scientists; (2) tuned surface chemistries developed by Baylor College of Medicine scientists to facilitate hybridization of rRNA targets to DNA probes under very low salt conditions, thereby minimizing secondary structure; and (3) integration of the microarray printing and detection/imaging instrumentation by Genometrix to complete the quantitative analysis of microorganism mixtures.

Eggers, M.↗
NASA NTRS1998

Analysis of Daily, Seasonal, and Interannual Changes in Hofsjokull Ice Cap, Iceland, using Satellite Data

Analysis of a time series of European Remote Sensing Satellite (ERS)-1 and -2, RADARSAT ScanSAR synthetic aperture radar (SAR) and Landsat images from 1973 to 1998, shows daily to interannual changes in Hofsjokull, a 923 sq km ice cap in central Iceland. A digital elevation model of Hofsjokull was constructed using interferometry, and then SAR backscatter coefficient (d) was plotted with elevation, and air temperature along a transect across the ice cap. Most of the a' changes measured along the transect are caused by a change in the state (frozen or thawed) of the surficial snow or ice when air temperature rises above or below about -5 to O C. Seasonal (sigma)deg patterns are identified in a 4-year time series of 57 ERS-1 and -2 images. In addition, June 1997 ScanSAR images display rapid changes in brightness that are tied closely to daily meteorological events. SAR and Landsat data were also used to measure changes in the areal extent of Hofsjokull, from 1973 to 1997, and to locate (sigma)deg and reflectance boundaries that relate to the glacier facies. Late-summer 1997 (sigma)deg and reflectance boundaries agree and are coincident with the approximate location of the fim line, and the January 1998 position of the equilibrium line as determined from ERS-2 data.

Hall, D. K.↗
NASA NTRS2004

Optical Design of the RAISE Sounding Rocket Instrument

The Rapid Acquisition Imaging Spectrograph Experiment (RAISE) is a recently selected sounding rocket program to investigate the dynamics and heating of the outer solar atmosphere on time scales as short as looms. Its optical design represents the first in a new class of two-reflection W / E W imaging spectrometers with Toroidal Varied-Line Space (TVLS) gratings. Due to the remarkable imaging properties of such gratings, RAISE will measure spectra simultaneously over four different wavelength bands (1205-1243 & 1524-1559 A in first order, 602.5-621.5 & 762.0-779.5 A in second), with an unprecedented combination of spatial, spectral, and temporal resolutions. These spectral regions include many bright, well-resolved lines covering the temperature range from the low chromosphere up to the 2 MK Fe XI1 corona. The RAISE optical design features an extremely fast beam (f/7.0) and a minimum number of reflections, which together allow enough throughput to provide high quality spectral data even at its very short exposure times. Moreover, by operating with high magnification (x4.25), the RAISE spectrometer can most effectively utilize the full length and width available in the sounding rocket payload. First launch of this exciting new instrument is scheduled for 2006 June 21.

Thomas, Roger J.↗
NASA NTRS2016

Surgical Capabilities for Exploration and Colonization Space Flight - An Exploration Symposium

Surgical capabilities in human space flight, whether on a space-based platform in low Earth orbit or on a long duration planetary exploration mission, will be challenging to conduct for a variety of reasons, some of which will be ameliorated by training, technology, and pre-flight planning. Nevertheless, inherent risks and challenges remain. Early space missions did not have any surgical capability. It was not until NASA's Skylab mission that serious consideration was given to this fundamental medical care capability. Over the past 30 years, subject matter experts have been brought together for discussion on the myriad of challenges and opportunities in this endeavor. The last such meeting was held in 2005 at the NASA Johnson Space Center. As we continue to move forward with human space flight activities for the International Space Station and beyond, the capabilities of information technology, robotics, sensors and imaging have rapidly changed since the last gathering of expertise. In December 2015, through sponsorship of the National Space Biomedical Research Institute (NSBRI), a diverse group of individuals from government, academia, and industry representing three countries gathered at the NSBRI Space 4 Biomedicine facility in Houston, TX. This two day symposia included comprehensive sessions that addressed the challenges that we all face in developing, deploying, and utilizing surgical care capabilities in all human space missions, regardless of mission duration or profile. The symposium benefited from the knowledge and experience of three seasoned NASA physician astronauts, Drs. Jay Buckey, Thomas Marshburn, and Lee Morin. At the end of the first day, the assembled group heard from the crew members about their experiences and their ideas. It is clear that the discussion of surgical capabilities is part of the larger discussion of consideration of advanced healthcare, including critical care, on exploration space missions. This report represents the culmination of the symposium, capturing knowledge, experience, conceptual dialogue, and a narrative that can be used in supporting the development of future programs and potential policy. Each of the presentations that were provided by the guest speakers is included in the appendices. Those presentations that are not included were due to sensitivity of the material or at the request of the speaker. In addition, each speaker was offered an opportunity to provide comments in a 'lightning round' format. All of these comments and speaker abstracts also appear in the appendices. At the conclusion of the second day, a discussion was held that reviewed the priorities that perhaps add value to decision makers. These are also summarized. This report will serve as the final product of this symposium. Additional material may be produced for the peer-reviewed literature.

Doarn, Charles R.↗
DOE OSTI2023

Sidewall Breach During Lithium-Ion Battery Thermal Runaway Triggered by Cell-to-Cell Propagation Visualized Using High-Speed X-Ray Imaging

With the rapid deployment of Li-ion batteries (LiBs) in a range of applications, it is crucial to ensure their safe operation. Therefore, it is necessary to investigate the rapid thermal runaway failure that LiBs can undergo if improperly operated or subjected to abuse scenarios so that hazardous events can be avoided or mitigated. Sidewall breaches or ruptures of LiBs during thermal runaway are considered the most hazardous failure scenario, resulting in hot abrasive flare from the casing of the cell that can impinge on neighbouring cells and lead to the propagation of thermal runaway throughout a battery pack. Yet, the process leading up to the sidewall breach is not well understood due to the extreme difficulty in visualizing such a failure in commercially relevant cells. With the application of a newly developed chamber for remote-controlled abuse testing of batteries coupled with simultaneous X-ray imaging, we demonstrate here for the first time an in-situ visualization of a sidewall breach. By further applying spatiotemporal mapping techniques, the internal thermal runaway events leading up to the sidewall breach can be analyzed in detail. Subsequently, the speed of the electrode layer delamination could be calculated to a speed of 0.6 m/s. These new insights bring more clarity regarding this phenomenon, that in turn can help battery designers improve battery safety.

battery safety↗
DOE OSTI2022

Training calibration-based counterfactual explainers for deep learning models in medical image analysis

The rapid adoption of artificial intelligence methods in healthcare is coupled with the critical need for techniques to rigorously introspect models and thereby ensure that they behave reliably. This has led to the design of explainable AI techniques that uncover the relationships between discernible data signatures and model predictions. In this context, counterfactual explanations that synthesize small, interpretable changes to a given query while producing desired changes in model predictions have become popular. This under-constrained, inverse problem is vulnerable to introducing irrelevant feature manipulations, particularly when the model’s predictions are not well-calibrated. Hence, in this paper, we propose the TraCE (training calibration-based explainers) technique, which utilizes a novel uncertainty-based interval calibration strategy for reliably synthesizing counterfactuals. Given the wide-spread adoption of machine-learned solutions in radiology, our study focuses on deep models used for identifying anomalies in chest X-ray images. Using rigorous empirical studies, we demonstrate the superiority of TraCE explanations over several state-of-the-art baseline approaches, in terms of several widely adopted evaluation metrics. Our findings show that TraCE can be used to obtain a holistic understanding of deep models by enabling progressive exploration of decision boundaries, to detect shortcuts, and to infer relationships between patient attributes and disease severity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1999

Correlation Between Bulk Material Defects and Spectroscopic Response in Cadmium Zinc Telluride Detectors

One of the critical challenges for large area cadmium zinc telluride (CdZnTe) detector arrays is obtaining material capable of uniform imaging and spectroscopic response. Two complementary nondestructive techniques for characterizing bulk CdZnTe have been developed to identify material with a uniform response. The first technique, infrared transmission imaging, allows for rapid visualization of bulk defects. The second technique, x-ray spectral mapping, provides a map of the material spectroscopic response when it is configured as a planar detector. The two techniques have been used to develop a correlation between bulk defect type and detector performance. The correlation allows for the use of infrared imaging to rapidly develop wafer mining maps. The mining of material free of detrimental defects has the potential to dramatically increase the yield and quality of large area CdZnTe detector arrays.

Parker, Bradford H.↗
NASA NTRS2009

Particle-Image Velocimeter Having Large Depth of Field

An instrument that functions mainly as a particle-image velocimeter provides data on the sizes and velocities of flying opaque particles. The instrument is being developed as a means of characterizing fluxes of wind-borne dust particles in the Martian atmosphere. The instrument could also adapted to terrestrial use in measuring sizes and velocities of opaque particles carried by natural winds and industrial gases. Examples of potential terrestrial applications include monitoring of airborne industrial pollutants and airborne particles in mine shafts. The design of this instrument reflects an observation, made in field research, that airborne dust particles derived from soil and rock are opaque enough to be observable by use of bright field illumination with high contrast for highly accurate measurements of sizes and shapes. The instrument includes a source of collimated light coupled to an afocal beam expander and an imaging array of photodetectors. When dust particles travel through the collimated beam, they cast shadows. The shadows are magnified by the beam expander and relayed to the array of photodetectors. Inasmuch as the images captured by the array are of dust-particle shadows rather of the particles themselves, the depth of field of the instrument can be large: the instrument has a depth of field of about 11 mm, which is larger than the depths of field of prior particle-image velocimeters. The instrument can resolve, and measure the sizes and velocities of, particles having sizes in the approximate range of 1 to 300 m. For slowly moving particles, data from two image frames are used to calculate velocities. For rapidly moving particles, image smear lengths from a single frame are used in conjunction with particle- size measurement data to determine velocities.

Bos, Brent↗
DOE OSTI2020

Multi-beam X-ray ptychography for high-throughput coherent diffraction imaging

X-ray ptychography is a rapidly developing coherent diffraction imaging technique that provides nanoscale resolution on extended field-of-view. However, the requirement of coherence and the scanning mechanism limit the throughput of ptychographic imaging. Herein, we propose X-ray ptychography using multiple illuminations instead of single illumination in conventional ptychography. Multiple locations of the sample are simultaneously imaged by spatially separated X-ray beams, therefore, the obtained field-of-view in one scan can be enlarged by a factor equal to the number of illuminations. We have demonstrated this technique experimentally using two X-ray beams focused by a house-made Fresnel zone plate array. Two areas of the object and corresponding double illuminations were successfully reconstructed from diffraction patterns acquired in one scan, with image quality similar with those obtained by conventional single-beam ptychography in sequence. Multi-beam ptychography approach increases the imaging speed, providing an efficient way for high-resolution imaging of large extended specimens.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗
DOE OSTI2021

Reconstructing porous media using generative flow networks

One area of intense scientific interest for the study of sandstones, carbonates, and shale at the pore scale is the use of limited image and petrophysical data to generate multiple realizations of a rock’s pore structure. Such images aid efforts to quantify uncertainty in petrophysical properties, including porosity–permeability transforms. We develop and evaluate a deep learning-based method to synthesize porous media volumes using a so-called generative flow model trained on x-ray microscope images of rock texture and pore structure. These models are optimized on a log-likelihood objective and they synthesize large and realistic three-dimensional images. Further, we demonstrate the rapid generation of sandstone image volumes that display realism as gauged by quantitative comparison of topological features using Minkowski functionals of porosity, specific surface area, and the Euler–Poincaré characteristic (i.e., pore connectivity). We also evaluate the single-phase permeability using Navier–Stokes and lattice Boltzmann methods and show that transport properties of the generated samples match measured trends.

58 GEOSCIENCES↗
DOE OSTI2022

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory

X-ray micro-computed tomography (X-ray μCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray μCT images, using low-cost resources in Google’s Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2013

Synthetic Foveal Imaging Technology

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

Monacos, Steve P.↗
NASA NTRS2011

NASA Tech Briefs, May 2011

Topics covered include: 1) Method to Estimate the Dissolved Air Content in Hydraulic Fluid; 2) Method for Measuring Collimator-Pointing Sensitivity to Temperature Changes; 3) High-Temperature Thermometer Using Cr-Doped GdAlO3 Broadband Luminescence; 4)Metrology Arrangement for Measuring the Positions of Mirrors of a Submillimeter Telescope; 5) On-Wafer S-Parameter Measurements in the 325-508-GHz Band; 6) Reconfigurable Microwave Phase Delay Element for Frequency Reference and Phase-Shifter Applications; 7) High-Speed Isolation Board for Flight Hardware Testing; 8) High-Throughput, Adaptive FFT Architecture for FPGA-Based Spaceborne Data Processors; 9) 3D Orbit Visualization for Earth-Observing Missions; 10) MaROS: Web Visualization of Mars Orbiting and Landed Assets; 11) RAPID: Collaborative Commanding and Monitoring of Lunar Assets; 12) Image Segmentation, Registration, Compression, and Matching; 13) Image Calibration; 14) Rapid ISS Power Availability Simulator; 15) A Method of Strengthening Composite/Metal Joints; 16) Pre-Finishing of SiC for Optical Applications; 17) Optimization of Indium Bump Morphology for Improved Flip Chip Devices; 18) Measuring Moisture Levels in Graphite Epoxy Composite Sandwich Structures; 19) Marshall Convergent Spray Formulation Improvement for High Temperatures; 20) Real-Time Deposition Monitor for Ultrathin Conductive Films; 21) Optimized Li-Ion Electrolytes Containing Triphenyl Phosphate as a Flame-Retardant Additive; 22) Radiation-Resistant Hybrid Lotus Effect for Achieving Photoelectrocatalytic Self-Cleaning Anticontamination Coatings; 23) Improved, Low-Stress Economical Submerged Pipeline; 24) Optical Fiber Array Assemblies for Space Flight on the Lunar Reconnaissance Orbiter; 25) Local Leak Detection and Health Monitoring of Pressurized Tanks; 26) Dielectric Covered Planar Antennas at Submillimeter Wavelengths for Terahertz Imaging; 27) Automated Cryocooler Monitor and Control System; 28) Broadband Achromatic Phase Shifter for a Nulling Interferometer; 29) Super Dwarf Wheat for Growth in Confined Spaces; 30) Fine Guidance Sensing for Coronagraphic Observatories; 31) Single-Antenna Temperature- and Humidity-Sounding Microwave Receiver; 32) Multi-Wavelength, Multi-Beam, and Polarization-Sensitive Laser Transmitter for Surface Mapping; 33) Optical Communications Link to Airborne Transceiver; 34) Ascent Heating Thermal Analysis on Spacecraft Adaptor Fairings; 35) Entanglement in Self-Supervised Dynamics; 36) Prioritized LT Codes; 37) Fast Image Texture Classification Using Decision Trees; 38) Constraint Embedding Technique for Multibody System Dynamics; 39) Improved Systematic Pointing Error Model for the DSN Antennas; 40) Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks; 41) More-Accurate Model of Flows in Rocket Injectors; 42) In-Orbit Instrument-Pointing Calibration Using the Moon as a Target; 43) Reliability of Ceramic Column Grid Array Interconnect Packages Under Extreme Temperatures; 44) Six Degrees-of-Freedom Ascent Control for Small-Body Touch and Go; and 45) Optical-Path-Difference Linear Mechanism for the Panchromatic Fourier Transform Spectrometer.

Source record↗
DOE OSTI2021

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Abstract Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems. However, the present paradigm involves time-intensive manual analysis that is inherently biased, error-prone, and unable to accommodate the large volumes of data produced by modern instrumentation. While more automated approaches have been proposed, many are not robust to a high variety of data, and do not generalize well to diverse microstructural features and material systems. Here, we present a flexible, semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems: (1) epitaxial heterostructures of SrTiO 3 /Ge, (2) La 0.8 Sr 0.2 FeO 3 thin films, and (3) MoO 3 nanoparticles. We demonstrate that the few-shot learning method is more robust against noise, more reconfigurable, and requires less data than conventional image analysis methods. This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multimodal, Multidimensional, and Multiscale X-ray Imaging at the National Synchrotron Light Source II

Over the last couple of decades, the synchrotron radiation research community has witnessed tremendous advancement in the field of x-ray imaging and microscopy. Continuing enhancement of the light sources’ brightness, advances in x-ray focusing optics, incorporation of precision instruments, and development of innovative imaging techniques are some of the leading contributors for the rapid progress. New imaging and microscopy beamlines, such as the ones at the National Synchrotron Light Source II (NSLS-II), a Department of Energy (DOE) Office of Science user facility located at DOE’s Brookhaven National Laboratory, are capable of performing more sophisticated and complicated measurements than ever before, either on their own or used together as a suite of tools. These sophisticated and complex measurements exhibit attributes for multimodal, multidimensional, and multiscale imaging. Recent popularity of these methods is strongly driven by the current trends in materials characterizations, where researchers desire to map out hierarchical materials structure over a large range of length scales, to understand structure-property correlation, to quantify materials structures in 3D, and/or to perform operando or in situ experiments. It is important to emphasize that “materials” under investigation are not only synthesized materials but also the natural materials. In this article, we describe multimodal, multidimensional and multiscale x-ray imaging capabilities of the NSLS-II beamlines and how these methods are used to tackle complex scientific problems.

47 OTHER INSTRUMENTATION↗