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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 NTRS2021

Surface Melting Over the Greenland Ice Sheet Derived From Enhanced Resolution Passive Microwave Brightness Temperatures (1979–2019)

Surface melting is a major component of the Greenland ice sheet surface mass balance, and it affects sea level rise through direct runoff and the modulation of ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting due to their long temporal coverage (1979–present) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, which has historically been of the order of tens of kilometers. Here, we use a newly released PMW dataset (37 GHz, horizontal polarization) made available through a NASA “Making Earth System Data Records for Use in Research Environments” (MeASUREs) program to study the spatiotemporal evolution of surface melting over the Greenland ice sheet at an enhanced spatial resolution of 3.125 km. We assess the outputs of different detection algorithms using data collected by automatic weather stations (AWSs) and the outputs of the Modèle Atmosphérique Régional (MAR) regional climate model. We found that sporadic melting is well captured using a dynamic algorithm based on the outputs of the Microwave Emission Model of Layered Snowpack (MEMLS), whereas a fixed threshold of 245 K is capable of detecting persistent melt. Our results indicate that, during the reference period from 1979 to 2019 (from 1988 to 2019), surface melting over the ice sheet increased in terms of both duration, up to 4.5 (2.9) d per decade, and extension, up to 6.9 % (3.6 %) of the entire ice sheet surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season started up to 4.0 (2.5) d earlier and ended 7.0 (3.9) d later per decade. We also explored the information content of the enhanced-resolution dataset with respect to the one at 25 km and MAR outputs using a semi-variogram approach. We found that the enhanced product is more sensitive to local-scale processes, thereby confirming the potential of this new enhanced product for monitoring surface melting over Greenland at a higher spatial resolution than the historical products and for monitoring its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modeled melt extent at high resolution and, potentially, to assimilate these data in climate models.

Surface melting↗
NASA NTRS1981

Rock type discrimination techniques using Landsat and Seasat image data

Results of a sedimentary rock type discrimination project using Seasat radar and Landsat multispectral image data of the San Rafael Swell, in eastern Utah, are presented, which has the goal of determining the potential contribution of radar image data to Landsat image data for rock type discrimination, particularly when the images are coregistered. The procedure employs several images processing techniques using the Landsat and Seasat data independently, and then both data sets are coregistered. The images are evaluated according to the ease with which contacts can be located and rock units (not just stratigraphically adjacent ones) separated. Results show that of the Landsat images evaluated, the image using a supervised classification scheme is the best for sedimentary rock type discrimination. Of less value, in decreasing order, are color ratio composites, principal components, and the standard color composite. In addition, for rock type discrimination, the black and white Seasat image is less useful than any of the Landsat color images by itself. However, it is found that the incorporation of the surface textural measures made from the Seasat image provides a considerable and worthwhile improvement in rock type discrimination.

Blom, R.↗
NASA NTRS1996

On the Capabilities of Using AIRSAR Data in Surface Energy/Water Balance Studies

The capabilities of using remote sensing data, and in particular multifrequency/multipolarization SAR data, like AIRSAR, for the retrieval of surface parameters, depend considerably on the specificity of each application. The potentials, and limitations, of SAR data in ecological investigations are well known. Because the chemistry is a major component in such studies and because of the almost lacking chemical information at the wavelengths of SAR data, the capabilities of using SAR-derived information in such studies are considerably limited. However, in the case of surface energy/water balance studies, the determination of the amount of water content, both in the soil and in the plants, is a major component in all modeling approaches. As the information about water content is present in the SAR signal, then the role of SAR data in studies where water content is to be determined becomes clearly predominant. Another situation where the role of SAR data becomes dominant over other remote sensing systems is the case of dense canopies. Because of the penetration capabilities of microwave data, which is especially superior as compared to optical data, information about the canopy as a whole and even the underlying soil is contained in the SAR data, while only the top canopy provides the information content in the case of optical data. In the case of relatively dense canopies, as has been demonstrated in this study, such different penetration capabilities provide very different results in terms of the derived total canopy water content, for instance. However, although all such capabilities are well known, unfortunately there are also well known limitations. Apart from calibration-related aspects (that we will not consider in this study), and apart from other intrinsic problems (like image noise, topographic corrections, etc.) which also significantly affect the derived results, we will concentrate on the problem of extracting information from the data. Even at this level, methods are still not fully well established, especially over vegetation-covered areas. In this paper, an algorithm is described which allows derivation of three fundamental parameters from SAR data: soil moisture, soil roughness and canopy water content, accounting for the effects of vegetation cover by using optical (Landsat) data as auxiliary. Capabilities and limitations of the data and algorithms are discussed, as well as possibilities to use these data in energy/water balance modeling studies. All the data used in this study were acquired as part of the Intensive Observation Period in June-July 1991 (European Multisensor Aircraft Campaign-91), as part of the European Field Experiment in a Desertification- threatened Area (EFEDA), a European contribution to the global-change research sponsored by the IGBP program (Bolle et al., 1993).

Moreno, Jose F.↗
NASA NTRS2010

Super Resolution Image Enhancement for a Flash Lidar: Back Projection Method

In this paper a new image processing technique for flash LIDAR data is presented as a potential tool to enable safe and precise spacecraft landings in future robotic or crewed lunar and planetary missions. Flash LIDARs can generate, in real-time, range data that can be interpreted as a 3-dimensional (3-D) image and transformed into a corresponding digital elevation map (DEM). The NASA Autonomous Landing and Hazard Avoidance (ALHAT) project is capitalizing on this new technology by developing, testing and analyzing flash LIDARs to detect hazardous terrain features such as craters, rocks, and slopes during the descent phase of spacecraft landings. Using a flash LIDAR for this application looks very promising, however through theoretical and simulation analysis the ALHAT team has determined that a single frame, or mosaic, of flash LIDAR data may not be sufficient to build a landing site DEM with acceptable spatial resolution, precision, size, or for a mosaic, in time, to meet current system requirements. One way to overcome this potential limitation is by enhancing the flash LIDAR output images. We propose a new super-resolution algorithm applicable to flash LIDAR range data that will create a DEM with sufficient accuracy, precision and size to meet current ALHAT requirements. The performance of our super-resolution algorithm is analyzed by processing data generated during a series of simulation runs by a high fidelity model of a flash LIDAR imaging a high resolution synthetic lunar elevation map. The flash LIDAR model is attached to a simulated spacecraft by a gimbal that points the LIDAR to a target landing site. For each simulation run, a sequence of flash LIDAR frames is recorded and processed as the spacecraft descends toward the landing site. Each run has a different trajectory profile with varying LIDAR look angles of the terrain. We process the output LIDAR frames using our SR algorithm and the results show that the achieved level of accuracy and precision of the SR generated landing site DEM is more than adequate for detecting hazardous terrain features and identifying safe areas.

Bulyshev, Alexander↗
DOE OSTI2024

The Role of Data Filtering in Open Source Software Ranking and Selection

Faced with more than 100M open source projects, a more manageable small subset is needed for most empirical investigations. More than half of the research papers in leading venues investigated filtering projects by some measure of popularity with explicit or implicit arguments that unpopular projects are not of interest, may not even represent "real" software projects, or that less popular projects are not worthy of study. However, such filtering may have enormous effects on the results of the studies if and precisely because the sought-out response or prediction is in any way related to the filtering criteria.This paper exemplifies the impact of this common practice on research outcomes, specifically how filtering of software projects on GitHub based on inherent characteristics affects the assessment of their popularity. Using a dataset of over 100,000 repositories, we used multiple regression to model the number of stars -a commonly used proxy for popularity- based on factors such as the number of commits, the duration of the project, the number of authors and the number of core developers. Our control model included the entire dataset, while a second filtered model considered only projects with ten or more authors. The results indicated that while certain characteristics of the repository consistently predict popularity, the filtering process significantly alters the relationships between these characteristics and the response. We found that the number of commits exhibited a positive correlation with popularity in the control sample but showed a negative correlation in the filtered sample. These findings highlight the potential biases introduced by data filtering and emphasize the need for careful sample selection in empirical research of mining software repositories. We recommend that empirical work should either analyze complete datasets such as World of Code, or employ stratified random sampling from a complete dataset to ensure that filtering is not biasing the results.

Malviya Thakur, Addi↗
DOE OSTI2025

On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling [SWR-25-20]

Code repository for the experiments performed in the paper: On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling (https://doi.org/10.1017/eds.2025.11) Overall, our work investigates the zero-shot downscaling potential of neural operators. To summarize, our contributions are: 1. We provide a comparative analysis based on two challenging weather downscaling problems, between various neural operator and non-neural-operator methods with large upsampling factors (e.g., 8x and 15x) and fine grid resolutions (e.g., 2 km × 2 km wind speed). 2. We examine whether neural operator layers provide unique advantages when testing downscaling models on upsampling factors higher than those seen during training, i.e., zero-shot downscaling. Our results instead show the surprising success of an approach that combines a powerful transformer-based model with a parameter-free interpolation step at zero-shot weather downscaling. 3. We find that this Swin-Transformer-based approach mostly outperforms all neural operator models in terms of average error metrics, whereas an enhanced super-resolution generative adversarial network (ESRGAN)-based approach is better than most models in capturing the physics of the system, and suggests their use in future work as strong baselines. However, these approaches still do not capture variations at smaller spatial scales well, including the physical characteristics of turbulence in the HR data. This suggests a potential for improvement in transformer or GAN-based methods and neural-operator-based methods for zero-shot weather downscaling.

Sinha, Saumya [National Renewable Energy Laborator↗
DOE OSTI2020

Intercropping kura clover with prairie cordgrass mitigates soil greenhouse gas fluxes

Prairie cordgrass (PCG) ( Spartina pectinata Link) has a high tolerance to soil salinity and waterlogging, therefore, it can thrive on marginal lands. Optimizing the nitrogen (N) input is crucial to achieving desirable biomass production of PCG without negatively impacting the environment. Thus, this study was based on the hypothesis that the use of legumes such as kura clover ( Trifolium ambiguum M. Bieb.) (KC) as an intercrop with PCG can provide extra N to the crop reducing the additional N fertilizer and mitigating soil surface greenhouse gas (GHG) emissions. Specific objective of the study was to assess the impact of PCG managed with different N rates [0 kg N ha -1 (PCG-0N), 75 kg N ha -1 (PCG-75N), 150 kg N ha -1 (PCG-150N), and 225 kg N ha -1 (PCG-255N)], and PCG intercropped with KC (PCG-KC) on GHG fluxes and biomass yield. The experimental site was established in 2010 in South Dakota under a marginally yielding cropland. The GHG fluxes were measured from 2014 through 2018 growing seasons using the static chamber. Net global warming potential (GWP) was calculated. Data showed that cumulative CH 4 and CO 2 fluxes were similar for all the treatments over the study period. However, the PCG-KC, PCG-0N, and PCG-75N recorded lower cumulative N 2 O fluxes (384, 402, and 499 g N ha -1 , respectively) than the PCG-150N (644 g N ha -1 ) and PCG-255N (697 g N ha -1 ). The PCG-KC produced 85% and 39% higher yield than the PCG-0N in 2016 and 2017, respectively, and similar yield to the other treatments (PCG-75N, PCG-150N, and PCG-255N) in these years. Net GWP was 52% lower for the PCG-KC (112.38 kg CO 2 -eq ha -1 ) compared to the PCG-225N (227.78 kg CO 2 -eq ha -1 ), but similar to other treatments. Soil total N was 15%% and 13% higher under PCG-KC (3.7 g kg -1 ) than that under PCG-0N (3.2 g kg -1 ) and PCG-75N (3.3 g kg -1 ), respectively. This study concludes that intercropping prairie cordgrass with kura clover can enhance biomass yield and reduce fertilizer-derived N 2 O emissions and net global warming potential.

09 BIOMASS FUELS↗
DOE OSTI2023

A common resequencing‐based genetic marker data set for global maize diversity

SUMMARY Maize ( Zea mays ssp. mays ) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole‐genome resequencing strategies, identifying millions of segregating single‐nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high‐confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering‐time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Creep Testing of Vectran Yarn

NASA and industry are developing inflatable space structures to provide deployable habitable volumes for future exploration missions in space and on the surface of the Moon and Mars. These structures must withstand the constant pressure loading of multi-year missions. These missions therefore require excellent creep resistance in the constituent cordage and webbings that provide the primary structure of the vessel, which is typically constructed using high-strength synthetic materials such as Vectran. Real-time and accelerated creep testing of Vectran webbings has been performed at NASA Langley Research Center (LaRC), however, acceptable correlation between the results of the two approaches has not yet been achieved. Given the additional complexity of the webbing architecture, creep testing at the yarn level is being studied to reduce the number of interacting properties and focus on the core creep behavior to see if better correlation can be achieved between real-time and accelerated tests. To achieve this objective a creep test stand that is able to support simultaneous testing of five Vectran yarns had been previously designed and built. The test stand utilizes two clamp-wrap grips to mount the yarn and has a 10:1 load ratio, via a lever-arm, henceforth, known as the lever-arm test stand. Real-time creep testing (without measuring the strain of the yarn) in this fixture produces yarn ruptures in the gauge section. However, a large scatter in the times to failure was seen in the results across multiple loading conditions. For example, a test at 70% of the ultimate tensile strength (UTS) was found to have specimens that failed within a matter of hours and others that took over 6 weeks to fail. Prior test data on Vectran webbings had indicated high variability in the material strength, leading to higher than average scatter in the creep testing of webbings, which could translate to the scatter in creep behavior at the yarn level as well. However, there was still the possibility that the lever-arm test stand was causing the high scatter in data; specifically, due to potential variability in the loading of each specimen. Therefore, an additional creep test setup was designed and built to attempt to determine if the large scatter in the results was due to inherent material properties, the lever-arm test stand, or both. The newly designed creep test stand, henceforth known as the conventional test stand, utilized the more typical method for creep testing which involved hanging a weight from the yarn with no additional load amplification. The conventional test stand was designed and fabricated in-house at LaRC. High speed cameras were used to validate that the specimens in the conventional test stand failed in the gauge section. Once it was determined that the conventional test stand would provide valid failures in the gauge section, creep tests on the Vectran yarns were run to compare to the lever-arm test stand results. Preliminary results for a 70% UTS creep test have some specimens failing within a number of hours and some failing in excess of 6 weeks. These results are similar to those seen on the lever-arm test stand, pointing towards a large variability inherent in the material. The poster/presentation will focus on the design, fabrication, and validation of the conventional test stand as well as present preliminary results comparing the creep data from the conventional and lever-arm test stands

creep testing↗
DOE OSTI2026

Meta-analysis of North American Arctic and boreal aboveground biomass datasets: assessing accuracy, dynamics, and similarities

The North American arctic and boreal regions (ABRs) are rapidly warming and experiencing intensifying disturbances. Accurately quantifying aboveground biomass (AGB) is critical for understanding the impacts of these changes on the carbon cycle and for designing climate change mitigation strategies. Several AGB maps have been developed for the North American ABRs, including recent contributions from National Aeronautics and Space Administration’s Arctic-Boreal Vulnerability Experiment (ABoVE) campaign. However, these maps differ widely in training data, methodology, and resulting AGB density estimates. Presently, a comprehensive comparative evaluation is lacking, making it difficult for users to select datasets suited to their research or management needs. Here, in this study, we conducted a comparative analysis of nine AGB density datasets across North American ABRs, specifically for Alaska and Canada. We (1) summarized AGB by ecoregion and Canadian provinces, (2) evaluated their accuracy against field-based measurements, (3) analyzed spatial and temporal similarities among datasets, and (4) assessed their ability to capture disturbance (fire and harvest) impacts on AGB. We found substantial variation in regional and local AGB estimates across datasets, with overall accuracy ranging from R 2 = 0.25–0.62 and Bias% from −47.8% to 69.9% when validated against field plots. Despite these differences, most datasets have comparatively consistent spatial patterns in AGB (r > 0.8 for most cases). In contrast, agreement on the temporal patterns of AGB change is generally low. We found datasets with spatial resolutions ⩽300 m are capable of capturing disturbance impacts on AGB dynamics, though sensitivity varies across products. Our findings and dataset summary provide guidance for selecting appropriate AGB datasets for different applications within our study area. Our analysis also highlights the need to decrease map bias and increase capability to detect temporal change to decrease uncertainty of AGB datasets potentially by using training data which is representative of major plant functional types within the mapped area.

ABoVE↗
NASA NTRS2020

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗
DOE OSTI2024

Teaching Freight Mode Choice Models New Tricks Using Interpretable Machine Learning Methods

Understanding and forecasting the intricate freight mode choice behavior under various industry, policy, and technology contexts is essential in freight planning and policymaking. Numerous models have been developed in prior studies to provide insights into freight mode selection, the majority of which use discrete choice models such as multinomial logit (MNL) models. However, logit models often rely on linear specifications of independent variables, despite potential nonlinear relationships in the data. Moreover, there often lacks a heuristic and efficient approach to identify such complex relationships to define the logit model specifications. To fill this gap, we developed an MNL model for freight mode choice using the insights from state-of-the- art machine learning (ML) models. ML models can capture the nonlinear nature of the complex decision-making process, and recent advances in 'explainable AI' have greatly improved their interpretability. The interpretable ML methods help enhance the performance of MNL models and advance knowledge of freight mode choice. Specifically, the influential factors and their relationship with individual modes are identified using SHapley Additive exPlanations (SHAP) to improve the MNL's performance. The workflow is demonstrated in a case study of Austin, Texas, and the SHAP results reveal multiple nonlinear relationships predicted by ML models. Incorporating those relationships into MNL model specifications improves the interpretability and accuracy of the MNL model compared to a conventional MNL model. Findings from this study can be used to guide freight planning and inform policymakers and practitioners on how key factors affect freight decision-making.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2019

Detection and Characterization of Intrusions to Network Parameter Data in Electric Power Systems

Combating cyberattacks is an emerging challenge in maintaining the reliable and economic operation of electric power systems. Possible cyberattacks include intrusions to the parameter data at a control center. In this class of attacks, algorithms at the control center are correctly executed, but the attacker's modification of the associated parameter data yields improper results. This paper proposes an algorithm for detecting and characterizing cyberattacks to network parameter data, with specific application to optimal power flow problems. The proposed algorithm evaluates whether historical operating point data are consistent with the network parameters. Inconsistencies indicating potential cyberattacks are characterized using historical operational data (power injections and voltage phasors) along with network parameter data. Simulated test cases illustrate the proposed algorithm's detection and characterization capabilities.

cybersecurity↗
NASA NTRS1980

Detection of heavy convective precipitation using rapid interval digital radar and satellite data

A study was carried out to investigate the evolution of thunderstorms with short-interval (5 min) geosynchronous digital satellite data and with digital radar data (12 min interval) in order to determine the potential and limitations of using the satellite data to detect regions of heavy convective precipitation. Initial results indicate that satellite-based estimates of thunderstorm updraft intensity are related to storm precipitation rate as indicated in the digital radar data. The conclusions give support to the effort to use satellite data for detection of heavy convective precipitation, but emphasize the need for high time resolution (5 min) data.

Negri, A. J.↗
NASA NTRS1994

Status of the Dobson total ozone data set

During deliberations of the International Ozone Trends Panel (IOTP) it became obvious that satellite determinations of global ozone amounts by themselves could not provide the necessary confidence in the measured trends. During the time of the deliberations of the IOTP, Bojkov re-examined the records of serveral North American Dobson stations and Degorska re-examined the records of the Belsk station. They were able to improve the quality of the data sets, thus improving the precision of their total ozone data sets. These improvements showed the greater potential of the world-wide Dobson total ozone data set in two primary areas. Firstly, the improvements showed that the existing data set when evaluated will become more valuable for comparisons with satellite determinations of total ozone. Secondly, the Dobson data set covers a greater period of time than the satellite data sets thus offering the possibility of extending improved information on ozone trends further back in time. An International Dobson Workshop was convened in September, 1991, under the auspices of the NOAA Climate and Global Change Program. It was part of the Information Management element of the C&GC Program. Further, it was considered as a 'data archaeology' project under the above. Clearly if the existing Dobson data set can be improved by re-evaluating all data records, we will be able to uncover the 'true' or 'best' data and fulfill the role of archaeologists.

Planet, Walter G.↗
DOE OSTI2017

Nanoscale Structure–Property Relationships of Polyacrylonitrile/CNT Composites as a Function of Polymer Crystallinity and CNT Diameter

Polyacrylonitrile (PAN)/carbon nanotube (CNT) composites are used as precursors for ultrastrong and lightweight carbon fibers. However, insights into the structure at the nanoscale and the relationships to mechanical and thermal properties have remained difficult to obtain. In this study, molecular dynamics simulation with accurate potentials and available experimental data were used to describe the influence of different degrees of PAN preorientation and CNT diameter on the atomic-scale structure and properties of the composites. The inclusion of CNTs in the polymer matrix is favored for an intermediate degree of PAN orientation and small CNT diameter whereas high PAN crystallinity and larger CNT diameter disfavor CNT inclusion. The glass transition at the CNT/PAN interface involves the release of rotational degrees of freedom of the polymer backbone and increased mobility of the protruding nitrile side groups in contact with the carbon nanotubes. The glass-transition temperature of the composite increases in correlation with the amount of CNT/polymer interfacial area per unit volume, i.e., in the presence of CNTs, for higher CNT volume fraction, and inversely with CNT diameter. The increase in glass-transition temperature upon CNT addition is larger for PAN of lower crystallinity than for PAN of higher crystallinity. Interfacial shear strengths of the composites are higher for CNTs of smaller diameter and for PAN with preorientation, in correlation with more favorable CNT inclusion energies. The lowest interfacial shear strength was observed in amorphous PAN for the same CNT diameter. PAN with ~75% crystallinity exhibited hexagonal patterns of nitrile groups near and far from the CNT interface which could influence carbonization into regular graphitic structures. The results illustrate the feasibility of near-quantitative insights into macroscale properties of polymer/CNT composites from simulations of nanometer-scale composite domains. Guidance is most effective when key assumptions in experiment and simulation are closely aligned, such as exfoliation versus bundling of CNTs, size, type, potential defects of CNTs, and precise measures for polymer crystallinity.

Materials Science↗
DOE OSTI2016

Hypoxia Potentiates the Radiation-Sensitizing Effect of Olaparib in Human Non-Small Cell Lung Cancer Xenografts by Contextual Synthetic Lethality

Purpose: Poly(ADP-ribose) polymerase (PARP) inhibitors potentiate radiation therapy in preclinical models of human non-small cell lung cancer (NSCLC) and other types of cancer. However, the mechanisms underlying radiosensitization in vivo are incompletely understood. Herein, we investigated the impact of hypoxia on radiosensitization by the PARP inhibitor olaparib in human NSCLC xenograft models. Methods and Materials: NSCLC Calu-6 and Calu-3 cells were irradiated in the presence of olaparib or vehicle under normoxic (21% O{sub 2}) or hypoxic (1% O{sub 2}) conditions. In vitro radiosensitivity was assessed by clonogenic survival assay and γH2AX foci assay. Established Calu-6 and Calu-3 subcutaneous xenografts were treated with olaparib (50 mg/kg, daily for 3 days), radiation (10 Gy), or both. Tumors (n=3/group) were collected 24 or 72 hours after the first treatment. Immunohistochemistry was performed to assess hypoxia (carbonic anhydrase IX [CA9]), vessels (CD31), DNA double strand breaks (DSB) (γH2AX), and apoptosis (cleaved caspase 3 [CC3]). The remaining xenografts (n=6/group) were monitored for tumor growth. Results: In vitro, olaparib showed a greater radiation-sensitizing effect in Calu-3 and Calu-6 cells in hypoxic conditions (1% O{sub 2}). In vivo, Calu-3 tumors were well-oxygenated, whereas Calu-6 tumors had extensive regions of hypoxia associated with down-regulation of the homologous recombination protein RAD51. Olaparib treatment increased unrepaired DNA DSB (P<.001) and apoptosis (P<.001) in hypoxic cells of Calu-6 tumors following radiation, whereas it had no significant effect on radiation-induced DNA damage response in nonhypoxic cells of Calu-6 tumors or in the tumor cells of well-oxygenated Calu-3 tumors. Consequently, olaparib significantly increased radiation-induced growth inhibition in Calu-6 tumors (P<.001) but not in Calu-3 tumors. Conclusions: Our data suggest that hypoxia potentiates the radiation-sensitizing effects of olaparib by contextual synthetic killing, and that tumor hypoxia may be a potential biomarker for selecting patients who may get the greatest benefit from the addition of olaparib to radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1998

SOHO Ultraviolet Coronagraph Spectrometer (UVCS) Mission Operations and Data Analysis

The scientific goal of UVCS is to obtain detailed empirical descriptions of the extended solar corona as it evolves from a period of minimum activity to maximum and to use these descriptions to identify and understand the physical processes responsible for coronal heating, solar wind acceleration, coronal mass ejections (CME's), and the phenomena that establish the plasma properties of the solar wind as measured by the CELIAS/SOHO experiment. We must observe a wide range of conditions (e.g., heating rate, impulsive mass ejections, magnetic field opening) in order to choose among competing theoretical explanations of the observed coronal structures and dynamics. During the first year of scientific observations (1 April 1996 through 31 March 1997), the LTVCS made the first extensive ultraviolet spectroscopic observations above the base of the solar corona. Those observations revealed extremely high most probable speeds along the line of sight for O(5+) in polar coronal holes above 2 solar radii from sun center and smaller such speeds for H(0) and protons. Doppler dimming and pumping diagnostics indicated that O(5+) and H(0) I reached supersonic outflow velocities within 2 solar radii. The observations appeared to be consistent with O95+) heating and direct momentum transfer by high frequency MHD waves through ion cyclotron resonance. Equatorial streamers were found to appear much different when observed in O VI, Fe XII and Mg X than when observed in H I Lyman-alpha or visible light. This led G. Noci to suggest that the elemental abundance of O, Fe, and Mg are lower in the dark center region of the O VI streamer image than it is in the brighter outer legs of the streamer. The O VI line ratio indicated a much smaller outflow speed in streamers than in the surrounding coronal holes. Spectroscopic observations of CME's in June and December 1996 showed large Doppler shifts indicating macroscopic flows of up to 200 km/s transverse to the apparent motion of the CME. The December event displayed factor of 500 intensity increases in H I Lyman lines and bright emissions in cool ion lines like C III 977 A indicating that the origin of some of the gas was a prominence. UVCS also observed two comets, several stars and interplanetary hydrogen. In the current reporting period, the initial results were published and detailed analyses including self consistent empirical models were developed. The research results were reported, published or submitted/accepted for publication. New observations were made to uncover additional information about the surprising results of the first year and other new observations revealed more surprises. A UVCS Tutorial was developed to familiarize potential users of UVCS data with the data products, analysis techniques and coronal models needed to analyze the data.

Kohl, John L.↗