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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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NASA NTRS2016

Features of the Upgraded Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Software

The Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) software is used at the NASA Langley Research Center to analyze global aeroheating data on wind tunnel models tested in the Langley Aerothermodynamics Laboratory. One-dimensional, semi-infinite heating data derived from IHEAT are used in the design of thermal protection systems for hypersonic vehicles that are exposed to severe aeroheating loads, such as reentry vehicles during descent and landing procedures. This software program originally was written in the PV-WAVE(Registered Trademark) programming language to analyze phosphor thermography data from the two-color, relative-intensity system developed at Langley. To increase the efficiency, functionality, and reliability of IHEAT, the program was migrated to MATLAB(Registered Trademark) syntax and compiled as a stand-alone executable file labeled version 4.0. New features of IHEAT 4.0 include the options to perform diagnostic checks of the accuracy of the acquired data during a wind tunnel test, to extract data along a specified multi-segment line following a feature such as a leading edge or a streamline, and to batch process all of the temporal frame data from a wind tunnel run. Results from IHEAT 4.0 were compared on a pixel level to the output images from the legacy software to validate the program. The absolute differences between the heat transfer data output from the two programs were on the order of 10(exp -5) to 10(exp -7). IHEAT 4.0 replaces the PV-WAVE(Registered Trademark) version as the production software for aeroheating experiments conducted in the hypersonic facilities at NASA Langley.

Mason, Michelle L.↗

NASA NTRS1985

Polar transport of 45Ca2+ across the elongation zone of gravistimulated roots

The movement of calcium across the elongation zone of gravistimulated primary roots of maize (Zea mays L.) was measured using 45Ca2+. Radioactive calcium was applied to one side of the elongation zone about 4 mm back from the root tip and the distribution of radioactivity across the root in the region of application was determined using scintillation spectrometry. The movement of 45Ca2+ across the elongation zone was non-polar in vertically oriented roots. In gravistimulated roots the movement of label was polarized with about twice as much label moving from top to bottom as from bottom to top. A variety of treatments which interfere with gravitropism was found to eliminate the polar movement of 45Ca2+ across the elongation zone. In maize cultivars which require light for gravitropic competency, dark grown roots exhibited neither gravitropism nor polar movement of 45Ca2+ across the elongation zone. Upon illumination the roots developed but gravitropic competency and gravity-induced polar movement of 45Ca2+ across the elongation zone. Similarly, roots of light-grown seedlings lost both gravitropic competency and 45Ca2+ transport polarity upon transfer to the dark. The results indicate a close correlation between calcium movement and gravitropism in primary roots in maize.

NASA Discipline Number 40-10↗

NASA NTRS2013

Label-Free Detection of Cardiac Troponin-I Using Carbon Nanofiber Based Nanoelectrode Arrays

A sensor platform based on vertically aligned carbon nanofibers (CNFs) has been developed. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. A carbon nanofiber (CNF) multiplexed array has been fabricated with 9 sensing pads, each containing 40,000 carbon nanofibers as nanoelectrodes. Here, we report the use of vertically aligned CNF nanoelectrodes for the detection of cardiac Troponin-I for the early diagnosis of myocardial infarction. Antibody, antitroponin, probe immobilization and subsequent binding to human cardiac troponin-I were characterized using electrochemical impedance spectroscopy and cyclic voltammetry techniques. Each step of the modification process resulted in changes in electrical capacitance or resistance to charge transfer due to the changes at the electrode surface upon antibody immobilization and binding to the specific antigen. This sensor demonstrates high sensitivity, down to 0.2 ng/mL, and good selectivity making this platform a good candidate for early stage diagnosis of myocardial infarction.

cardiac output↗

NASA NTRS1984

Cosmic Ray Exposure & Linear-Energy-Transfer Evaluations for the COBE Mission

Magnetospherically attenuated, orbit integrated, surface incident cosmic ray fluxes of galactic origin were determined for the COBE mission. All heavy ions up to Nickel (z=28) were considered in this, evaluation. In order to provide worst case approximations, estimates were based on solar minimum conditions. Transport and material shielding calculations were then performed for these vehicle encountered particles, for a simple spherical 3-D aluminum geometry, and the materially attenuated cosmic ray distributions emerging behind selected shield thicknesses were obtained. Finally, Linear-Energy-Transfer (LET) spectra were evaluated for the energy spectra of each ion specie and these were, in turn, integrated into the sum-total LET distribution contained in this report. The results are presented in tabular and graphical form for eight (8) different shield thicknesses from.01 to 10.0 gm/cm2 of aluminum. They show most conclusively, and not unexpectedly, that material shielding has virtually no 'effect on the final LET spectrum, at least not for aluminum shields. This was predictable. Please note that in the LET graphs, two curves were plotted. Of these, please ignore the one labeled "grazing" and use only the one labeled "normal". Again, it should be remembered that the end results contain contributions from all elements up to Nickel (z=28).

Stassinopoulos, E. G.↗

NASA NTRS2024

3D Cloud Masking Across A Broad Swath Using Multi-Angle Polarimetry and Deep Learning

Understanding the 3-dimensional structure of clouds is of crucial importance to modeling our changing climate. Active sensors, such as radar and lidar, provide accurate vertical cloud profiles, but are mostly restricted to along-track sampling. Passive sensors can capture a wide swath, but struggle to see beneath cloud tops. In essence, both types of products are restricted to two dimensions: as a cross-section in the active case, and an image in the passive case. However, multi-angle sensor configurations contain implicit information about 3D structure, due to parallax and atmospheric path differences. Extracting that implicit information can be challenging, requiring computationally expensive radiative transfer techniques. Machine learning, as an alternative, may be able to capture some of the complexity of a full 3D radiative transfer solution with significantly less computational expense. In this work, we make three contributions towards understanding 3D cloud structure from multi-angle polarimetry. First, we introduce a large-scale, publicly available dataset that fuses existing cloud products into a format more amenable to machine learning. This dataset treats multi-angle polarimetry as an input, and radar-based vertical cloud profiles as an output. Second, we describe and evaluate strong baseline machine learning models based that predict these profiles from the passive imagery. Notably, these models are trained only on center-swath labels, but can predict cloud profiles over the entire passive imagery swath. Third, we leverage the information-theoretic nature of machine learning to draw conclusions about the relative utility of various sensor configurations, including spectral channels, viewing angles, and polarimetry. These findings have implications for Earth-observing missions such as NASA’s Plankton, Aerosol, Cloud-ocean Ecosystem (PACE) and Atmosphere Observing System (AOS) missions, as well as in informing future applications of computer vision to atmospheric remote sensing.

clouds↗

NASA NTRS2018

NASA Electronic Parts and Packaging (NEPP) Field Programmable Gate Array (FPGA) Single Event Effects (SEE) Test Guideline Update

The following are updated or new subjects added to the FPGA SEE Test Guidelines manual: academic versus mission specific device evaluation, single event latch-up (SEL) test and analysis, SEE response visibility enhancement during radiation testing, mitigation evaluation (embedded and user-implemented), unreliable design and its affects to SEE Data, testing flushable architectures versus non-flushable architectures, intellectual property core (IP Core) test and evaluation (addresses embedded and user-inserted), heavy-ion energy and linear energy transfer (LET) selection, proton versus heavy-ion testing, fault injection, mean fluence to failure analysis, and mission specific system-level single event upset (SEU) response prediction. Most sections within the guidelines manual provide information regarding best practices for test structure and test system development. The scope of this manual addresses academic versus mission specific device evaluation and visibility enhancement in IP Core testing.

Test guidelines↗

NASA NTRS2018

NASA Electronic Parts and Packaging Field Programmable Gate Array Single Event Effects Test Guideline Update

Field Programmable Gate Array (FPGA)↗

NASA NTRS2001

Classification Experiments on Real-World Texture

Many papers have been published concerning the analysis of visual texture and yet, very few application domains use texture for image classification. A possible reason for this low transfer of the technology is the lack of experience and testing in real-world imagery. In this paper, we assess the performance of texture-based classification methods on a number of real-world images relevant to autonomous navigation on cross-country terrain and to autonomous geology. Texture analysis will form part of the closed loop that allows a robotic system to navigate autonomously. We have implemented two different classifiers on features extracted by Gabor filter banks. The first classifier models feature distributions for each texture class using a mixture of Gaussians. Classification is performed using Maximum Likelihood. The second classifier represents local statistics using marginal histograms of the features over a region centered on the pixel to be classified. We measure system performance by comparison to ground truth image labels.

image segmentation↗

NASA NTRS2014

In-Situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori ground-truth labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and auxiliary (e.g. trajectory) data and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our misclassification rates as related to our ground-truth labels, and with multi-layered pollution plume cases. The next step in our analysis is to optimize parameter selection for a scheme that can be applied to space-borne aerosol and trace-gas observation platforms such as OMI, and future geostationary satellites such as TEMPO and GEO-CAPE.

Neural-network↗

NASA NTRS2003

Intracellular stress tomography reveals stress focusing and structural anisotropy in cytoskeleton of living cells

We describe a novel synchronous detection approach to map the transmission of mechanical stresses within the cytoplasm of an adherent cell. Using fluorescent protein-labeled mitochondria or cytoskeletal components as fiducial markers, we measured displacements and computed stresses in the cytoskeleton of a living cell plated on extracellular matrix molecules that arise in response to a small, external localized oscillatory load applied to transmembrane receptors on the apical cell surface. Induced synchronous displacements, stresses, and phase lags were found to be concentrated at sites quite remote from the localized load and were modulated by the preexisting tensile stress (prestress) in the cytoskeleton. Stresses applied at the apical surface also resulted in displacements of focal adhesion sites at the cell base. Cytoskeletal anisotropy was revealed by differential phase lags in X vs. Y directions. Displacements and stresses in the cytoskeleton of a cell plated on poly-L-lysine decayed quickly and were not concentrated at remote sites. These data indicate that mechanical forces are transferred across discrete cytoskeletal elements over long distances through the cytoplasm in the living adherent cell.

NASA Discipline Cell Biology↗

NASA NTRSDate not supplied

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or create more accurate transcripts of air traffic management conversations. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement (LOA) which is used as the evaluation case in this paper. These applications can benefit from the use of state-of-the-art Natural Language Processing (NLP) techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of transferring pre-trained large language models to the aviation domain by adapting transformer based models using aviation datasets. This paper utilized two datasets to adapt a ‘Robustly Optimized Bidirectional Encoder Representations from Transformers Approach’ (RoBERTa) model and two down-stream classification tasks to assess its performance. These datasets are all built upon Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. The first two datasets are used for the adaptation of RoBERTa to the aviation domain and were of different sizes to assess the number of documents needed to adapt to the aviation domain. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the unsupervised adaptation. The second dataset is a separate set of LOA documents with two sets of classification labels to be used for evaluation; one at the document level and one at the line level. These down-stream evaluations allowed the measurement of improvement by adapting RoBERTa. The accuracy increased by 4-6% on both tasks and the F1 score on the class of interest increased by 4-8% from the adaptation.

Air Traffic Management↗

NASA NTRSDate not supplied

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

Air Traffic Management↗

NASA NTRS1997

Elucidation of the Cross-Link Structure of Nadic-End-Capped Polyimides Using NMR of C-13-Labeled Polymers

Solid NMR of C-13 isotope-labeled samples of PMR-15 was used to follow the cross-linking reaction of the nadic end cap. Some samples were labeled on one of the carbon atoms of the nadic end cap, and others on the methylene carbon atom of the methylenedianiline portion of the polymer. NMR spectra were run on these samples both before and after cross-linking. In this way, direct evidence of the major products of cross-linking under normal cure conditions is provided. The majority (approximately 85%) of the cross-linking derives from olefin polymerization through the double bond of the end cap. Approximately 15% of the products could come from a pathway involving a retro-Diels-Alder reaction. However, all of the products could be explained by a biradical intermediate without a retro-Diels-Alder reaction. Evidence is also presented that the methylene moiety in the methylenedianiline part of the polymer chain also participates in the cross-linking, albeit to a small extent, by a radical transfer reaction. Different cure conditions (higher temperatures, longer times) could change the relative distribution of the products.

Meador, Mary Ann B.↗

NASA NTRS2017

Recent Radiation Test Results for Trench Power MOSFETs

Single-event effect (SEE) radiation test results are presented for various trench-gate power MOSFETs. The heavy-ion response of the first (and only) radiation-hardened trench-gate power MOSFET is evaluated: the manufacturer SEE response curve is verified and importantly, no localized dosing effects are measured, distinguishing it from other, non-hardened trench-gate power MOSFETs. Evaluations are made of n-type commercial and both n- and p-type automotive grade trench-gate device using ions comparable to of those on the low linear energy transfer (LET) side of the iron knee of the galactic cosmic ray spectrum, to explore suitability of these parts for missions with higher risk tolerance and shorter duration, such as CubeSats. Part-to-part variability of SEE threshold suggests testing with larger sample sizes and applying more aggressive derating to avoid on-orbit failures. The n-type devices yielded expected localized dosing effects including when irradiated in an unbiased (0-V) configuration, adding to the challenge of inserting these parts into space flight missions.

Schottky Diodes↗

NASA NTRS2011

Feature Acquisition with Imbalanced Training Data

This work considers cost-sensitive feature acquisition that attempts to classify a candidate datapoint from incomplete information. In this task, an agent acquires features of the datapoint using one or more costly diagnostic tests, and eventually ascribes a classification label. A cost function describes both the penalties for feature acquisition, as well as misclassification errors. A common solution is a Cost Sensitive Decision Tree (CSDT), a branching sequence of tests with features acquired at interior decision points and class assignment at the leaves. CSDT's can incorporate a wide range of diagnostic tests and can reflect arbitrary cost structures. They are particularly useful for online applications due to their low computational overhead. In this innovation, CSDT's are applied to cost-sensitive feature acquisition where the goal is to recognize very rare or unique phenomena in real time. Example applications from this domain include four areas. In stream processing, one seeks unique events in a real time data stream that is too large to store. In fault protection, a system must adapt quickly to react to anticipated errors by triggering repair activities or follow- up diagnostics. With real-time sensor networks, one seeks to classify unique, new events as they occur. With observational sciences, a new generation of instrumentation seeks unique events through online analysis of large observational datasets. This work presents a solution based on transfer learning principles that permits principled CSDT learning while exploiting any prior knowledge of the designer to correct both between-class and withinclass imbalance. Training examples are adaptively reweighted based on a decomposition of the data attributes. The result is a new, nonparametric representation that matches the anticipated attribute distribution for the target events.

Thompson, David R.↗

NASA NTRS1999

Fluorescence Studies of Protein Crystal Nucleation

Fluorescence can be used to study protein crystal nucleation through methods such as anisotropy, quenching, and resonance energy transfer (FRET), to follow pH and ionic strength changes, and follow events occurring at the growth interface. We have postulated, based upon a range of experimental evidence that the growth unit of tetragonal hen egg white lysozyme is an octamer. Several fluorescent derivatives of chicken egg white lysozyme have been prepared. The fluorescent probes lucifer yellow (LY), cascade blue, and 5-((2-aminoethyl)aminonapthalene-1-sulfonic acid (EDANS), have been covalently attached to ASP 101. All crystallize in the characteristic tetragonal form, indicating that the bound probes are likely laying within the active site cleft. Crystals of the LY and EDANS derivatives have been found to diffract to at least 1.7 A. A second group of derivatives is to the N-terminal amine group, and these do not crystallize as this site is part of the contact region between the adjacent 43 helix chains. However derivatives at these sites would not interfere with formation of the 43 helices in solution. Preliminary FRET studies have been carried out using N-terminal bound pyrene acetic acid (Ex 340 nm, Em 376 nm) lysozyme as a donor and LY (Ex -425 nm, Em 525 nm) labeled lysozyme as an acceptor. FRET data have been obtained at pH 4.6, 0.1 M NaAc buffer, at 5 and 7% NaCl, 4 C. The corresponding Csat values are 0.471 and 0.362 mg/ml (approximately 3.3 and approximately 2.5 x 10(exp -5) M respectively). The data at both salt concentrations show a consistent trend of decreasing fluorescence intensity of the donor species (PAA) with increasing total protein concentration. This decrease is more pronounced at 7% NaCl, consistent with the expected increased intermolecular interactions at higher salt concentrations reflected in the lower solubility. The calculated average distance between any two protein molecules at 5 x 10(exp -6) M is approximately 70nm, well beyond the range where any FRET can be expected. Results from these and ongoing studies will be presented.

Pusey, Marc L.↗

NASA NTRSDate not supplied

NASA GPM Status and Future Activities

The joint U.S.-Japan Global Precipitation Measurement (GPM) mission is approaching a decade of operations, and continues to pursue research, dataset production, and outreach related to precipitation. Key activities over the last year were the release of an improved “Version 07” of all GPM precipitation and latent heating products, boosting the orbit of the GPM Core Observatory (GPM CO) to 435 km, and improving quality control on precipitation retrievals from the GPM constellation of passive microwave satellites. This presentation summarizes key improvements to the GPM products and provides some examples of the changes between Versions 06 and 07 in algorithm performance. One important operational change that affected Version 07 is that the scanning strategy for the Ka-band radar channel changed in May 2018; all products that depend on Ka were revised to accommodate this change. For example, in Version 07 the Goddard Profiling (GPROF) algorithm has implemented improvements in regions where orographic enhancement and suppression take place and where the surface is snowy/icy, and again covers radiometers reaching back to 1987. The Combined Radar Radiometer Algorithm (CORRA) now incorporates modified drop-size distribution constraints that substantially reduce bias. Revisions to the Convective-Stratiform Heating (CSH) algorithm employ new radiative transfer retrievals as well as accounting for terrain in the vertical coordinates. Each algorithm was adjusted to ensure continuity for each product across the boundary in 2014 between the predecessor Tropical Rainfall Measuring Mission (TRMM) and the GPM CO. The U.S. Science Team’s Integrated Multi-satellitE Retrievals for GPM (IMERG) was upgraded to account for distortions in the probability density function of regional precipitation rates due to weighted averaging in the Kalman filter used for “morphing” the passive microwave data. Maintaining the GPM CO orbital altitude in the the current very active solar cycle has been forcing the use of more fuel than planned and consequently shortening the forecasted life of the mission from the early 2030's to the late 2020's. It was considered vital to regain some of this lifetime to ensure overlap with the upcoming Atmosphere Observing System mission to provide crosscalibration of instruments. To accomplish this, the orbital altitude was raised from 400 to 435 km on 7-8 November 2023. Thereafter, the primary GPM CO algorithms had to be revised to account for the change in observing parameters. By meeting time this action should be complete. Recently, a screening algorithm based on auto-encoding was developed that uncovered 162 orbits (out of the many thousands of orbits across all years and all satellites) of passive microwave retrievals that had highly anomalous values. Removing these defective retrievals has improved the integrity of both the GPROF and IMERG records. However, the nature of the IMERG processing interacted sufficiently badly with the now-discovered anomalous orbits that it was necessary to completely reprocess the IMERG Final Run record, now labeled Version 07B. The presentation also considers major issues that require continued attention, including the use of machine learning algorithms and the operational challenge of swarms of “small”, perhaps short-lived satellites.

GPM↗

NASA NTRS1996

Clusters of DNA damage induced by ionizing radiation: formation of short DNA fragments. II. Experimental detection

The basic 30-nm chromatin fiber in the mammalian cell consists of an unknown (possibly helical) arrangement of nucleosomes, with about 1.2 kb of DNA per 10-nm length of fiber. Track-structure considerations suggest that interactions of single delta rays or high-LET particles with the chromatin fiber might result in the formation of multiple lesions spread over a few kilobases of DNA (see the accompanying paper: W.R. Holley and A. Chatterjee, Radiat. Res. 145, 188-199, 1996). In particular, multiple DNA double-strand breaks and single-strand breaks may form. To test this experimentally, primary human fibroblasts were labeled with [3H]thymidine and exposed at 0 degrees C to X rays or accelerated nitrogen or iron ions in the LET range of 97-440 keV/microns. DNA was isolated inside agarose plugs and subjected to agarose gel electrophoresis under conditions that allowed good separation of 0.1-2 kb size DNA. The bulk of DNA remained in the well or migrated only a small distance into the gel. It was found that DNA fragments in the expected size range were formed linearly with dose with an efficiency that increased with LET. A comparison of the yield of such fragments with the yield of total DNA double-strand breaks suggests that for the high-LET ions a substantial proportion (20-90%) of DNA double-strand breaks are accompanied within 0.1-2 kb by at least one additional DNA double-strand break. It is shown that these results are in good agreement with theoretical calculations based on treating the 30-nm chromatin fiber as the target for ionizing particles. Theoretical considerations also predict that the clusters will contain numerous single-strand breaks and base damages. It is proposed that such clusters be designated "regionally multiply damaged sites." Postirradiation incubation at 37 degrees C resulted in a decline in the number of short DNA fragments, suggesting a repair activity. The biological significance of regionally multiply damaged sites is presently unknown.

Non-NASA Center↗