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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 NTRS1995

High angular resolution far-infrared and submillimeter mapping survey of the dust cores associated with ultracompact H II regions

The primary objective of the research funded under this grant has been to perform a high angular resolution mapping survey of the far-infrared and submillimeter continuum emission from the dust cocoons surrounding young, deeply embedded massive stars and the ultracompact H II regions they create. The high infrared, submillimeter, and radio luminosity makes the ultracompact H II regions ideal tracers of current high-mass star formation. Detailed investigations of their structure, evolution, and interaction with their parent molecular clouds are thus important for understanding the early evolutionary phases of massive main sequence stars, the nature of the dense molecular cores in which they form, and the relationship to coeval low-mass star formation.

Phillips, T. G.↗
NASA NTRS2000

Quantitative Estimation of Some Possible Errors Associated With TRMM GV Monthly Rain Maps and a Scheme for Spatial Averaging of Radar Accumulations

The Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) rain products are generated from ground-based radar observations using a bulk adjusted FACE radar reflectivity (Ze) - rain rate (R) relationship. Monthly Ze-R relationships are obtained by extracting the Ze data with a horizontal resolution of 2 km from an altitude of 1.5 km (from Constant Altitude PPIS, CAPPIS) over the locations of the gauges. The gauge and radar data are merged, and a quality control procedure is applied that eliminates poorly correlated gauge-radar data. Bulk adjusted Ze-R relations are then derived from this quality-controlled merged data base. These Z-R relations are applied to the base scan reflectivity to produce rain maps. The present study examines the effect of these different planes on the total accumulations from the radar and the associated effect on the bulk adjustment coefficient. In order to evaluate the credibility of these GV products, the effect of the different planes involved in the bulk adjustment method will be discussed, The gauge data will also be used to assess the impact of missing radar data (i.e., data gaps) upon the monthly radar-derived rainfall estimates. Experiments were also performed varying both the area of the radar data extracted over the gauges and the use of different weighting coefficients. Preliminary results from these sensitivity tests indicate improved agreement and consistency between the gauge and radar data.

Datta, Saswati↗
NASA NTRS1978

The prediction and mapping of geoidal undulations from GEOS-3 altimetry

From the adjusted altimeter data an approximation to the geoid height in ocean areas is obtained. Methods are developed to produce geoid maps in these areas. Geoid heights are obtained for grid points in the region to be mapped, and two of the parameters critical to the production of an accurate map are investigated. These are the spacing of the grid, which must be related to the half-wavelength of the altimeter signal whose amplitude is the desired accuracy of the contour; and the method adopted to predict the grid values. Least squares collocation was used to find geoid undulations on a 1 deg grid in the mapping area. Twenty maps, with their associated precisions, were produced and are included. These maps cover the Indian Ocean, Southwestern and Northeastern portions of the Pacific Ocean, and Southwest Atlantic and the U.S. Calibration Area.

Kearsley, W.↗
NASA NTRS1972

Effective use of ERTS multisensor data in the Great Plains

The author has identified the following significant results. One unique advantage of ERTS imagery for delineating soil associations is the large area that can be scanned with one photo. Although soil associations usually are published at scales of 1:500,000 or 1:1,000,000, the delineations are drawn on much larger scale maps covering small pieces of the scene and then pieced together. Alluvial areas are usually swollen out of proportion to other soil areas. ERTS imagery puts alluvial areas into their proper size. A second feature of ERTS imagery is that a soil association map constructed with its aid assures that the cartographic level of the associations is more nearly the same. Another advantage of ERTS imagery is that the actual shape and configuration of soil associations are apparent. Also with ERTS imagery significant new delineations may become apparent which were missed when constructing soil association maps from conventional large scale photos.

Myers, V. I.↗
NASA NTRS1999

Carbon Monoxide Distributions and Atmosphere Transports over Southern Africa

Sources and transports of CO as measured by the Measurement of Air Pollution from Space (MAPS) over a substantial sector of the southern hemisphere between South America and southern Africa are described by air parcel trajectories based upon European Center for Medium Range Weather Forecasts (ECMWF) model data fields. Observations, made by NASA Shuttle astronauts during the October 1994 mission, of vegetation fires suggest a direct relationship between in situ biomass burning, at least over South America and southern Africa, and coincident tropospheric measurements of CO. Results of this paper indicate that the transport of CO from the surface to the levels of maximum MAPS sensitivity (about 450 hPa) over these regions is not of a direct nature due largely to the well stratified atmospheric environment. The atmospheric transport of CO from biomass burning within this region is found to occur over intercontinental scales over numbers of days to more than a week. Three distinct synoptic circulation and transport classes are found to have occurred over southern Africa during the October 1994 MAPS experiment: (1) transport from South America and Africa to southern Africa associated with elevated MAPS measured CO (> 150 ppbv); (2) weakening anticyclonic transport from South America associated with moderate CO (< 150 ppbv and > 105 ppbv); and (3) transport from the high southern latitudes associated with low CO (<105 ppbv).

Garstang, Michael↗
DOE OSTI2020

Linkage mapping evidence for a syntenic QTL associated with flowering time in perennial C 4 rhizomatous grasses Miscanthus and switchgrass

Flowering in perennial species is directed via complex signalling pathways that adjust to developmental regulations and environmental cues. Synchronized flowering in certain environments is a prerequisite to commercial seed production, and so the elucidation of the genetic architecture of flowering time in Miscanthus and switchgrass could aid breeding in these underdeveloped species. In this context, we assessed a mapping population in Miscanthus and two ecologically diverse switchgrass mapping populations over 3 years from planting. Multiple flowering time quantitative trait loci (QTL) were identified in both species. Remarkably, the most significant Miscanthus and switchgrass QTL proved to be syntenic, located on linkage groups 4 and 2, with logarithm of odds scores of 17.05 and 21.8 respectively. These QTL regions contained three flowering time transcription factors: Squamosa Promoter-binding protein-Like, MADS-box SEPELLATA2 and gibberellin-responsive bHLH137. The former is emerging as a key component of the age-related flowering time pathway.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2026

Improvement in the Thermal-to-Structural Model Mapping Process for Integrated Modeling for the Roman Space Telescope

Integrated Modeling has been a key component of verifying optical requirements for the Nancy Grace Roman Space Telescope (RST) that are either impossible or impractical to verify exclusively through ground testing. Two major areas for integrated Modeling are Jitter and Thermal Distortion that require the exchanges of model performance predictions across disciplines. In both cases, distortions are impressed on optical models to evaluate the impact on boresight alignment and wave front error. In the case of Jitter, the disturbances are driven by reactions to motions most often from actuators; however, in the case of thermal distortion, the motions are driven by thermal expansion or contraction as a result of changing temperatures. This then requires a link further upstream to the thermal model, which is used to predict the thermal performance and temperature gradients and stability. The process for mapping temperatures from a thermal model to a corresponding structural model has been performed numerous times through the RST project lifecycle, with improvements in the accuracy, verification, and effort sought throughout. This paper describes some of the recent improvements to the process, including: capture of the visualization parameters, automatic generation of the mapped images for both the thermal and structural model groupings, and reduction in the effort to assemble the full set of mapped temperatures. These upgrades have greatly reduced the manual effort associated with thermal mapping and allowed for faster turn-around of Integrated Modeling predictions.

Thermal Mapping↗
NASA NTRS2023

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy Data Fusion to Map Global Surface Ozone Concentration and Associated Uncertainty

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R 2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m −3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Ozone↗
NASA NTRS1981

Fundamental procedures of geographic information analysis

Analytical procedures common to most computer-oriented geographic information systems are composed of fundamental map processing operations. A conceptual framework for such procedures is developed and basic operations common to a broad range of applications are described. Among the major classes of primitive operations identified are those associated with: reclassifying map categories as a function of the initial classification, the shape, the position, or the size of the spatial configuration associated with each category; overlaying maps on a point-by-point, a category-wide, or a map-wide basis; measuring distance; establishing visual or optimal path connectivity; and characterizing cartographic neighborhoods based on the thematic or spatial attributes of the data values within each neighborhood. By organizing such operations in a coherent manner, the basis for a generalized cartographic modeling structure can be developed which accommodates a variety of needs in a common, flexible and intuitive manner. The use of each is limited only by the general thematic and spatial nature of the data to which it is applied.

Berry, J. K.↗
DOE OSTI2026

MAL33 drives natural variation in maltose metabolism in Saccharomyces eubayanus

Maltose is one of the most abundant sugars in brewer’s wort, and its efficient utilization is critical for successful fermentation. However, maltose consumption varies naturally among Saccharomyces eubayanus strains isolated from different host trees, such as Quercus and Nothofagus. To identify the genetic determinants underlying these phenotypic differences, we performed bulk segregant analysis (BSA) and quantitative trait loci (QTL) mapping using an F 2 offspring derived from QC18 (Quercus-associated) and CL467.1 (Nothofagus-associated) strains. QTL mapping identified two significant genomic regions on subtelomeric loci of chromosomes V-R and XVI-L, each containing complete MAL loci composed of MAL32 (encoding maltase), MAL31 (transporter), and MAL33 (transcriptional activator) genes. Comparative polymorphism analyses identified mutations in MAL32 and MAL33 of QC18, including frameshift mutations resulting in premature stop codons. Functional validation demonstrated that the heterologous expression of MAL33 ChrV from CL467.1 fully restored maltose utilization in QC18, indicating the functional presence of MAL33 cis-regulatory sequences and MAL32 and MAL31 genes in QC18. While structural protein predictions identified truncation and impaired functionality in the maltose-responsive activation domain of Mal33p from QC18, overexpression of QC18’s own MAL33 ChrV allele also improved maltose metabolism, suggesting dosage-dependent transcriptional limitations rather than complete functional loss. These results indicate that allelic variations in the maltose-responsive activation domain of Mal33p result in differences in maltose consumption between strains. Here, we hypothesized that reduced maltose metabolism in QC18 is an adaptive response to the distinct sugar composition in Quercus robur bark, contrasting with the starch-rich environment of Nothofagus pumilio. These findings highlight subtelomeric MAL gene diversity as a reservoir of genetic variation, representing a key evolutionary mechanism that influences maltose adaptation among natural Saccharomyces isolates.

evolutionary plasticity↗
NASA NTRS1986

Detection and mapping of volcanic rock assemblages and associated hydrothermal alteration with Thermal Infrared Multiband Scanner (TIMS) data Comstock Lode Mining District, Virginia City, Nevada

Thermal Infrared Multispectral Scanner (TIMS) data were acquired over the Virginia City area on September 12, 1984. The data were acquired at approximately 1130 hours local time (1723 IRIG). The TIMS data were analyzed using both photointerpretation and digital processing techniques. Karhuen-Loeve transformations were utilized to display variations in radiant spectral emittance. The TIMS image data were compared with color infrared metric camera photography, LANDSAT Thematic Mapper (TM) data, and key areas were photographed in the field.

Taranik, James V.↗
DOE OSTI2023

exRNA-eCLIP intersection analysis reveals a map of extracellular RNA binding proteins and associated RNAs across major human biofluids and carriers

Although the role of RNA binding proteins (RBPs) in extracellular RNA (exRNA) biology is well established, their exRNA cargo and distribution across biofluids are largely unknown. To address this gap, we extend the exRNA Atlas resource by mapping exRNAs carried by extracellular RBPs (exRBPs). This map was developed through an integrative analysis of ENCODE enhanced crosslinking and immunoprecipitation (eCLIP) data (150 RBPs) and human exRNA profiles (6,930 samples). Computational analysis and experimental validation identified exRBPs in plasma, serum, saliva, urine, cerebrospinal fluid, and cell-culture-conditioned medium. exRBPs carry exRNA transcripts from small non-coding RNA biotypes, including microRNA (miRNA), piRNA, tRNA, small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), Y RNA, and lncRNA, as well as protein-coding mRNA fragments. Computational deconvolution of exRBP RNA cargo reveals associations of exRBPs with extracellular vesicles, lipoproteins, and ribonucleoproteins across human biofluids. Overall, we mapped the distribution of exRBPs across human biofluids, presenting a resource for the community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quantum Adiabatic Optimization with Rydberg Arrays: Localization Phenomena and Encoding Strategies

Quantum adiabatic optimization seeks to solve combinatorial problems using quantum dynamics, requiring the Hamiltonian of the system to align with the problem of interest. However, these Hamiltonians are often incompatible with the native constraints of quantum hardware, necessitating encoding strategies to map the original problem into a hardware-conformant form. While the classical overhead associated with such mappings is easily quantifiable and typically polynomial in problem size, it is much harder to quantify their overhead on the quantum algorithm, e.g., the transformation of the adiabatic timescale. In this work, we address this challenge on the concrete example of the encoding scheme proposed in [Nguyen , PRX Quantum , 010316 (2023)], which is designed to map optimization problems on arbitrarily connected graphs into Rydberg atom arrays. We consider the fundamental building blocks underlying this encoding scheme and determine the scaling of the minimum gap with system size along adiabatic protocols. Even when the original problem is trivially solvable, we find that the encoded problem can exhibit an exponentially closing minimum gap. We show that this originates from a quantum coherent effect, which gives rise to an unfavorable localization of the ground-state wave function. On the QuEra Aquila neutral atom machine, we observe such localization and its effect on the success probability of finding the correct solution to the encoded optimization problem. Finally, we propose quantum-aware modifications of the encoding scheme that avoid this quantum bottleneck and lead to an exponential improvement in the adiabatic performance. This highlights the crucial importance of accounting for quantum effects when designing strategies to encode classical problems onto quantum platforms. Published by the American Physical Society 2025

Bombieri, Lisa (ORCID:0009000950422897)↗
NASA NTRS1983

Forest Resource Information System (FRIS)

The technological and economical feasibility of using multispectral digital image data as acquired from the LANDSAT satellites in an ongoing operational forest information system was evaluated. Computer compatible multispectral scanner data secured from the LANDSAT satellites were demonstrated to be a significant contributor to ongoing information systems by providing the added dimensions of synoptic and repeat coverage of the Earth's surface. Major forest cover types of conifer, deciduous, mixed conifer-deciduous and non-forest, were classified well within the bounds of the statistical accuracy of the ground sample. Further, when overlayed with existing maps, the acreage of cover type retains a high level of positional integrity. Maps were digitized by a graphics design system, overlayed and registered onto LANDSAT imagery such that the map data with associated attributes were displayed on the image. Once classified, the analysis results were converted back to map form as a cover type of information. Existing tabular information as represented by inventory is registered geographically to the map base through a vendor provided data management system. The notion of a geographical reference base (map) providing the framework to which imagery and tabular data bases are registered and where each of the three functions of imagery, maps and inventory can be accessed singly or in combination is the very essence of the forest resource information system design.

Source record↗
DOE OSTI2024

Quantitative trait locus (QTL) mapping and transcriptome profiling identify QTLs and candidate genes associated with heat stress response during reproductive development in Camelina sativa

Camelina sativa (L.) Crantz is a low-input oilseed crop that has great potential in providing sustainable feedstock for biofuels and bioproducts. Climate change is threatening production of camelina with rising global temperatures. Elucidating the genetic response to high temperatures is essential for successful breeding of heat-tolerant camelina varieties. Here, we report a combinatorial approach to identifying candidate genes associated with heat stress by quantitative trait locus (QTL) mapping and comparative transcriptome profiling. A population of recombinant inbred lines (RILs) was grown in a controlled growth chamber under the high-temperature regimes for 14 days beginning at the onset of the reproductive stage. Several traits related to seed production were evaluated at maturity. The QTL analysis identified several regions with co-located traits on chromosomes 8, 10, and 12. Two RILs with contrasting phenotypic responses to heat stress were chosen for gene expression profiling via RNA sequencing. Multiple pathways and genes were found to be strongly affected by heat stress, and many genes expressed differently between the two RILs. Several genes identified within the QTL regions were considered strong candidates that may control heat tolerance during reproduction in camelina. These studies provide resources for future studies that may assist in improving the heat tolerance of camelina.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Predicting images for the dynamics of stellar clusters ( π-DOC ): a deep learning framework to predict mass, distance, and age of globular clusters

ABSTRACT Dynamical mass estimates of simple systems such as globular clusters (GCs) still suffer from up to a factor of 2 uncertainty. This is primarily due to the oversimplifications of standard dynamical models that often neglect the effects of the long-term evolution of GCs. Here, we introduce a new approach to measure the dynamical properties of GCs, based on the combination of a deep-learning framework and the large amount of data from direct N-body simulations. Our algorithm, π-DOC (Predicting Images for the Dynamics Of stellar Clusters) is composed of two convolutional networks, trained to learn the non-trivial transformation between an observed GC luminosity map and its associated mass distribution, age, and distance. The training set is made of V-band luminosity and mass maps constructed as mock observations from N-body simulations. The tests on π-DOC demonstrate that we can predict the mass distribution with a mean error per pixel of 27 per cent, and the age and distance with an accuracy of 1.5 Gyr and 6 kpc, respectively. In turn, we recover the shape of the mass-to-light profile and its global value with a mean error of 12 per cent, which implies that we efficiently trace mass segregation. A preliminary comparison with observations indicates that our algorithm is able to predict the dynamical properties of GCs within the limits of the training set. These encouraging results demonstrate that our deep-learning framework and its forward modelling approach can offer a rapid and adaptable tool competitive with standard dynamical models.

Chardin, Jonathan↗
DOE OSTI2021

Assessing and mapping extreme wave height along the Gulf of Mexico coast

The effect of extreme waves on the coastal community includes inundation, loss of habitats, increasing shoreline erosion, and increasing risks to coastal infrastructures (e.g., ports, breakwaters, oil and gas platforms), important for supporting coastal resilience. The coastal communities along the US Gulf of Mexico are very low-lying, which makes the region particularly vulnerable to impacts of extreme waves generated by storm events. We propose assessing and mapping the risks from extreme waves for the Gulf of Mexico coast to support coastal resiliency planning. The risks will be assessed by computing n-year recurring wave height (e.g., 1, 5, 50, 100-year) using 32-year wave hindcast data and various extreme value analysis techniques including Peak- Over-Threshold and Annual Maxima method. The characteristics of the extreme waves, e.g., relations between the mean and extreme wave climates, directions associated with extreme waves, will be investigated. Hazard maps associated with extreme wave heights at different return periods will be generated to help planners identify potential risks and envision places that are less susceptible to future storm damage.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Coronal synoptic temperature maps derived from the Fe XIV/Fe X intensity ratio

The large-scale temperature structure of the low corona is investigated using synoptic temperature maps, derived from the intensity ratio of the green (Fe XIV) and red (Fe X) coronal lines as observed at the National Solar Observatory/Sacramento Peak. This intensity ratio is sensitive to coronal plasma with temperatures in the range of 1-2 MK. The synoptic maps indicate an association between high coronal temperature and the large-scale magnetic field. A comparison with WSO 'source surface' synoptic maps shows that especially when the heliospheric current sheet is stable over several rotations, the large-scale high-temperature features follow the current sheet remarkably well. For recent Carrington rotations temperature maps have been constructed for various heights between 1.15 and 1.45 solar radii. For these maps the correspondence with the current sheet (calculated at 2.5 solar radii) improves with height. Deviations between temperature structure and magnetic structure appears to be largest when the magnetic structure changes rapidly from rotation to rotation.

Hick, P.↗