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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Atomic oxygen undercutting of LDEF aluminized Kapton multilayer insulation

Atomic oxygen undercutting is a potential threat to vulnerable spacecraft materials which have been shielded with an atomic oxygen protective coating. This is due to atomic oxygen attack of oxidizable materials at the point of microscopic defects in the protective coatings which occur during fabrication and handling, or from micrometeoroid and debris bombardment in space. An aluminized Kapton multilayer insulation sample which was flown on the leading edge of the Long Duration Exposure Facility (LDEF) was used to study low Earth orbit (LEO) directed ram oxygen undercutting. Cracks in the aluminized coatings around the vent holes provided excellent locations for evaluation of atomic oxygen undercutting. The undercutting profiles were compared to Monte Carlo models which predict LEO ram atomic oxygen attack. The shape of the undercurrent profile was found to vary with crack width, which is proportional to the number of atomic oxygen atoms entering the crack. The resulting atomic oxygen undercut profiles which occurred on LDEF indicated wide undercut cavities in spite of the fixed ram orientation. Potential causes of the observed undercutting profiles will be presented. Implications of the undercutting profiles relevant to Space Station Freedom will also be discussed.

Degroh, Kim K.↗
NASA NTRS2002

A geostatistical analysis of small-scale spatial variability in bacterial abundance and community structure in salt marsh creek bank sediments

Small-scale variations in bacterial abundance and community structure were examined in salt marsh sediments from Virginia's eastern shore. Samples were collected at 5 cm intervals (horizontally) along a 50 cm elevation gradient, over a 215 cm horizontal transect. For each sample, bacterial abundance was determined using acridine orange direct counts and community structure was analyzed using randomly amplified polymorphic DNA fingerprinting of whole-community DNA extracts. A geostatistical analysis was used to determine the degree of spatial autocorrelation among the samples, for each variable and each direction (horizontal and vertical). The proportion of variance in bacterial abundance that could be accounted for by the spatial model was quite high (vertical: 60%, horizontal: 73%); significant autocorrelation was found among samples separated by 25 cm in the vertical direction and up to 115 cm horizontally. In contrast, most of the variability in community structure was not accounted for by simply considering the spatial separation of samples (vertical: 11%, horizontal: 22%), and must reflect variability from other parameters (e.g., variation at other spatial scales, experimental error, or environmental heterogeneity). Microbial community patch size based upon overall similarity in community structure varied between 17 cm (vertical) and 35 cm (horizontal). Overall, variability due to horizontal position (distance from the creek bank) was much smaller than that due to vertical position (elevation) for both community properties assayed. This suggests that processes more correlated with elevation (e.g., drainage and redox potential) vary at a smaller scale (therefore producing smaller patch sizes) than processes controlled by distance from the creek bank. c2002 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Non-NASA Center↗
NASA NTRS2013

Soft Decision Analyzer

The Soft Decision Analyzer (SDA) is an instrument that combines hardware, firmware, and software to perform realtime closed-loop end-to-end statistical analysis of single- or dual- channel serial digital RF communications systems operating in very low signal-to-noise conditions. As an innovation, the unique SDA capabilities allow it to perform analysis of situations where the receiving communication system slips bits due to low signal-to-noise conditions or experiences constellation rotations resulting in channel polarity in versions or channel assignment swaps. SDA s closed-loop detection allows it to instrument a live system and correlate observations with frame, codeword, and packet losses, as well as Quality of Service (QoS) and Quality of Experience (QoE) events. The SDA s abilities are not confined to performing analysis in low signal-to-noise conditions. Its analysis provides in-depth insight of a communication system s receiver performance in a variety of operating conditions. The SDA incorporates two techniques for identifying slips. The first is an examination of content of the received data stream s relation to the transmitted data content and the second is a direct examination of the receiver s recovered clock signals relative to a reference. Both techniques provide benefits in different ways and allow the communication engineer evaluating test results increased confidence and understanding of receiver performance. Direct examination of data contents is performed by two different data techniques, power correlation or a modified Massey correlation, and can be applied to soft decision data widths 1 to 12 bits wide over a correlation depth ranging from 16 to 512 samples. The SDA detects receiver bit slips within a 4 bits window and can handle systems with up to four quadrants (QPSK, SQPSK, and BPSK systems). The SDA continuously monitors correlation results to characterize slips and quadrant change and is capable of performing analysis even when the receiver under test is subjected to conditions where its performance degrades to high error rates (30 percent or beyond). The design incorporates a number of features, such as watchdog triggers that permit the SDA system to recover from large receiver upsets automatically and continue accumulating performance analysis unaided by operator intervention. This accommodates tests that can last in the order of days in order to gain statistical confidence in results and is also useful for capturing snapshots of rare events.

Steele, Glen↗
NASA NTRS2012

Measurement of Clathrate Hydrate Thermodynamic Stability in the Presence of Ammonia

There is a lack of data available for the stability of clathrate hydrates in the presence of ammonia for low-to-moderate pressures in the 0-10 MPa range. Providing such data will allow for a better understanding of natural mass transfer processes on celestial bodies like Titan and Enceladus, on which destabilization of clathrates may be responsible for replenishment of gases in the atmosphere. The experimental process utilizes a custom-built gas handling system (GHS) and a cryogenic calorimeter to allow for the efficient testing of samples under varying pressures and gas species.

clathrate hyudrates↗
NASA NTRS2016

Cryo-Temp Data Logger

Biological experiments on the ISS are frequently frozen at ultra-low temperatures on orbit prior to return to Earth for analysis. Recording temperatures during the freezing process, and subsequent handling to the point of post-flight processing, can provide important information of sample integrity to the scientist. The MadgeTech Cryo-Temp Data Logger has been modified for space flight applications by the Payload Development Team at Kennedy Space Center. This ultra-low temperature data logger is rated for temperatures from -86 C to +35 C with 0.1 C resolution and +/-1 C accuracy, but has been successfully tested at Kennedy Space Centers Cryogenic Lab down to -100 C. The logger provides date and time stamped temperature recordings and can be set with logging intervals from 5 seconds up to 30 minutes using the MadgeTech Data Logger Software. Data can be recorded, depending on logging interval, for greater than 90 days. The Cryo-Temp Data logger will first be flown on Space X-12 in the BRIC-Petri Dish Fixation Unit (PDFU) canister hardware, recording temperature data for a Space Life and Physical Sciences (SLPS) flight experiment. The modified Cryo-Temp Data Logger is small in size (Figure 1) and is the ideal temperature monitoring solution for any application involving independent temperature data logging.

Logger↗
NASA NTRS2011

Droplet actuator analyzer with cartridge

A droplet actuator with cartridge is provided. According to one embodiment, a sample analyzer is provided and includes an analyzer unit comprising electronic or optical receiving means, a cartridge comprising self-contained droplet handling capabilities, and a wherein the cartridge is coupled to the analyzer unit by a means which aligns electronic and/or optical outputs from the cartridge with electronic or optical receiving means on the analyzer unit. According to another embodiment, a sample analyzer is provided and includes a sample analyzer comprising a cartridge coupled thereto and a means of electrical interface and/or optical interface between the cartridge and the analyzer, whereby electrical signals and/or optical signals may be transmitted from the cartridge to the analyzer.

Smith, Gregory F.↗
DOE OSTI2024

D2NO: Efficient handling of heterogeneous input function spaces with distributed deep neural operators

Neural operators have been applied in various scientific fields, such as solving parametric partial differential equations, dynamical systems with control, and inverse problems. However, challenges arise when dealing with input functions that exhibit heterogeneous properties, requiring multiple sensors to handle functions with minimal regularity. To address this issue, discretization-invariant neural operators have been used, allowing the sampling of diverse input functions with different sensor locations. However, existing frameworks still require an equal number of sensors for all functions. We propose a novel distributed approach to further relax the discretization requirements and solve the heterogeneous dataset challenges. Our method involves partitioning the input function space and processing individual input functions using independent and separate neural networks. A centralized neural network is used to handle shared information across all output functions. This distributed methodology reduces the number of gradient descent back-propagation steps, improving efficiency while maintaining accuracy. Here, we demonstrate that the corresponding neural network is a universal approximator of continuous nonlinear operators and present three numerical examples to validate its performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Uncertainty-aware particle segmentation for electron microscopy at varied length scales

Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder samples that are widely used in materials development, scanning electron microscopes (SEMs) are increasingly used at the laboratory scale to generate large datasets with hundreds of images. Parsing these images to identify distinct particles and determine their morphology requires careful analysis, and automating this process remains challenging. In this work, we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM images. We address several challenges inherent to measurements, such as image blur and particle agglomeration. Moreover, our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a particle. Recognizing that disparate length scales are often present in large datasets, we use this framework to create two models that are separately trained to handle images obtained at low or high magnification. By testing these models on a variety of inorganic samples, our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts, revealing comparable accuracy while requiring a fraction of the time. These findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Innovative Video Diagnostic Equipment for Material Science

Materials science experiments under microgravity increasingly rely on advanced optical systems to determine the physical properties of the samples under investigation. This includes video systems with high spatial and temporal resolution. The acquisition, handling, storage and transmission to ground of the resulting video data are very challenging. Since the available downlink data rate is limited, the capability to compress the video data significantly without compromising the data quality is essential. We report on the development of a Digital Video System (DVS) for EML (Electro Magnetic Levitator) which provides real-time video acquisition, high compression using advanced Wavelet algorithms, storage and transmission of a continuous flow of video with different characteristics in terms of image dimensions and frame rates. The DVS is able to operate with the latest generation of high-performance cameras acquiring high resolution video images up to 4Mpixels@60 fps or high frame rate video images up to about 1000 fps@512x512pixels.

Capuano, G.↗
NASA NTRSDate not supplied

Assessing the Oxygen Permeability of Candidate Asteroid Sample Containers With Optochemical Sensors

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center currently curates 500 mg (10%) of carbonaceous asteroid Ryugu regolith collected by the Japan Aerospace and Exploration Agency’s Hayabusa II spacecraft and returned to Earth in 2021. In September 2023, NASA’s OSIRIS-REx spacecraft returned at least 70 grams of regolith collected from the surface of Carbonaceous Asteroid Bennu. These new astromaterials collections are stored and handled in gloveboxes and desiccators that are continuously purged with ultrapure nitrogen in order to minimize contamination and alteration of extraterrestrial samples from terrestrial environments, e.g., reaction with terrestrial oxygen and water. Ito et al. have previously reported on the development of containers to transport samples between facilities in inert, sealed environments; Hayabusa2 samples allocated to investigators by JAXA’s Extraterrestrial Sample Curation Center (ESCuC) are shipped in these Facility-to-Facility Transfer Containers (FFTCs). NASA curation has also been investigating sealed containers for storage, transportation, and allocation of Bennu and Ryugu regolith in sealed anoxic environments. In order to assess the ability of candidate sample containers to maintain nitrogen environments, we have utilized optochemical sensors to measure trace oxygen levels within sealed volumes.

C J Snead↗
NASA NTRS1995

Carbon isotopic analysis of atmospheric methane by isotope-ratio-monitoring gas chromatography-mass spectrometry

Less than 15 min are required for the determination of delta C(sub PDB)-13 with a precision of 0.2 ppt(1 sigma, single measurement) in 5-mL samples of air containing CH4 at natural levels (1.7 ppm). An analytical system including a sample-introduction unit incorporating a preparative gas chromatograph (GC) column for separation of CH4 from N2, O2, and Ar is described. The 15-min procedure includes time for operation of that system, high-resolution chromatographic separation of the CH4, on-line combustion and purification of the products, and isotopic calibration. Analyses of standards demonstrate that systematic errors are absent and that there is no dependence of observed values of delta on sample size. For samples containing 100 ppm or more CH4, preconcentration is not required and the analysis time is less than 5 min. The system utilizes a commercially available, high-sensitivity isotope-ratio mass spectrometer. For optimal conditions of smaple handling and combustion, performance of the system is within a factor of 2 of the shot-noise limit. The potential exists therefore for analysis of samples as small as 15 pmol CH4 with a standard deviation of less than 1 ppt.

Merritt, Dawn A.↗
NASA NTRS1969

Apollo 7 to 11 - Medical Concerns and Results

The goal of the Apollo Program is to land men on the moon and safely return them to earth. The medical task thus outlined required confirmation of the Gemini findings and definition and solution of any problems encountered in the four Apollo flights prior to the Apollo 11 lunar landing. The medical concerns included the following: 1. The effect of decreased red blood cell mass and decreased exercise capacity and of cardiovascular de conditioning on the ability of the crew to do lunar-surface activity; 2. The capability to work effectively in one-sixth the force of gravity and the energy cost of such work; 3. The ability to get adequate rest and sleep in flight and on the lunar surface; 4. The prevention of preflight, inflight, and post-flight illness by proper preventive medicine; 5. The possible development of motion sickness of vestibular origin; 6. The conduct of a post-flight quarantine of crew and lunar samples. The results of the Apollo 7 to 11 missions, demonstrating the ability of man to handle this difficult task and the environment successfully, are discussed in detail and are related to the future of manned flight.

Berry, C. A.↗
NASA NTRS1976

Viking Mars encounter

Various phases of planetary operations related to the Viking mission to Mars are described. Topics discussed include: approach phase, Mars orbit insertion, prelanding orbital activities, separation, descent and landing, surface operations, surface sampling and operations starting, orbiter science and radio science, Viking 2, Deep Space Network and data handling.

Source record↗
NASA NTRS1992

Atomic oxygen undercutting of LDEF aluminized-Kapton multilayer insulation

Atomic oxygen undercutting is a potential threat to vulnerable spacecraft materials which have atomic oxygen protective coatings. Such undercutting is due to atomic oxygen attack of oxidizable materials at microscopic defects in the protective coatings. These defects occur during fabrication and handling, or from micrometeoroid and debris bombardment in space. An aluminized-polyimide Kapton multilayer insulation sample that was located on the leading edge of the Long Duration Exposure Facility (LDEF) was used to study low Earth orbit directed ram atomic oxygen undercutting. Cracks in the aluminized coatings located around vent holes provided excellent defect sites for evaluation of atomic oxygen undercutting. The experimentally observed undercutting profiles were compared to predictions from Monte Carlo models for normal incident ram atomic oxygen attack. The shape of the undercut profile was found to vary with crack width, which is proportional to the number of oxygen atoms entering the crack. The resulting profiles of atomic oxygen which occurred on LDEF indicated wide undercut cavities in spite of the fixed ram orientation. Potential causes of the observed undercutting are presented. Implications of the undercutting profiles relevant to the Space Station Freedom are also discussed.

Degroh, Kim K.↗
NASA NTRS1993

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Lure, Y. M. Fleming↗
NASA NTRS2009

New Measurements of the Particle Size Distribution of Apollo 11 Lunar Soil 10084

We have initiated a major new program to determine the grain size distribution of nearly all lunar soils collected in the Apollo program. Following the return of Apollo soil and core samples, a number of investigators including our own group performed grain size distribution studies and published the results [1-11]. Nearly all of these studies were done by sieving the samples, usually with a working fluid such as Freon(TradeMark) or water. We have measured the particle size distribution of lunar soil 10084,2005 in water, using a Microtrac(TradeMark) laser diffraction instrument. Details of our own sieving technique and protocol (also used in [11]). are given in [4]. While sieving usually produces accurate and reproducible results, it has disadvantages. It is very labor intensive and requires hours to days to perform properly. Even using automated sieve shaking devices, four or five days may be needed to sieve each sample, although multiple sieve stacks increases productivity. Second, sieving is subject to loss of grains through handling and weighing operations, and these losses are concentrated in the finest grain sizes. Loss from handling becomes a more acute problem when smaller amounts of material are used. While we were able to quantitatively sieve into 6 or 8 size fractions using starting soil masses as low as 50mg, attrition and handling problems limit the practicality of sieving smaller amounts. Third, sieving below 10 or 20microns is not practical because of the problems of grain loss, and smaller grains sticking to coarser grains. Sieving is completely impractical below about 5- 10microns. Consequently, sieving gives no information on the size distribution below approx.10 microns which includes the important submicrometer and nanoparticle size ranges. Finally, sieving creates a limited number of size bins and may therefore miss fine structure of the distribution which would be revealed by other methods that produce many smaller size bins.

McKay, D.S.↗
NASA NTRS2015

Mineralogy, Petrology, Chronology, and Exposure History of the Chelyabinsk Meteorite and Parent Body

The Chelyabinsk meteorite fall on February 15, 2013 attracted much more attention worldwide than do most falls. A consortium led by JSC received 3 masses of Chelyabinsk (Chel-101, -102, -103) that were collected shortly after the fall and handled with care to minimize contamination. Initial studies were reported in 2013; we have studied these samples with a wide range of analytical techniques to better understand the mineralogy, petrology, chronology and exposure history of the Chelyabinsk parent body.

Righter, K.↗