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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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25 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

The Host Galaxies of X-Ray Selected Active Galactic Nuclei to z - 2.5: Structure, Star-Formation and Their Relationships from CANDELS and Herschel/Pacs

We study the relationship between the structure and star-formation rate (SFR) of X-ray selected low and moderate luminosity active galactic nuclei (AGNs) in the two Chandra Deep Fields, using Hubble Space Telescope imaging from the Cosmic Assembly Near Infrared Extragalactic Legacy Survey (CANDELS) and deep far-infrared maps from the PEP+GOODS-Herschel survey. We derive detailed distributions of structural parameters and FIR luminosities from carefully constructed control samples of galaxies, which we then compare to those of the AGNs. At z is approximately 1, AGNs show slightly diskier light profiles than massive inactive (non-AGN) galaxies, as well as modestly higher levels of gross galaxy disturbance (as measured by visual signatures of interactions and clumpy structure). In contrast, at z ∼ 2, AGNs show similar levels of galaxy disturbance as inactive galaxies, but display a red central light enhancement, which may arise due to a more pronounced bulge in AGN hosts or due to extinguished nuclear light. We undertake a number of tests of both these alternatives, but our results do not strongly favour one interpretation over the other. The mean SFR and its distribution among AGNs and inactive galaxies are similar at z greater than 1.5. At z less than 1, however, clear and significant enhancements are seen in the SFRs of AGNs with bulge-dominated light profiles. These trends suggest an evolution in the relation between nuclear activity and host properties with redshift towards a minor role for mergers and interactions at z greater than 15

host↗
NASA NTRS2017

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS-national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91 percent was achieved, which is a 6 percent improvement in unmixing based classification relative to per-pixel-based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

Subpixel↗
NASA NTRS2013

Candels Multi-Wavelength Catalogs: Source Detection and Photometry in the Goods-South Field

We present a UV to mid-infrared multi-wavelength catalog in the CANDELS/GOODS-S field, combining the newly obtained CANDELS HST/WFC3 F105W, F125W, and F160W data with existing public data. The catalog is based on source detection in the WFC3 F160W band. The F160W mosaic includes the data from CANDELS deep and wide observations as well as previous ERS and HUDF09 programs. The mosaic reaches a 5σ limiting depth (within an aperture of radius 0farcs17) of 27.4, 28.2, and 29.7 AB for CANDELS wide, deep, and HUDF regions, respectively. The catalog contains 34,930 sources with the representative 50% completeness reaching 25.9, 26.6, and 28.1 AB in the F160W band for the three regions. In addition to WFC3 bands, the catalog also includes data from UV (U band from both CTIO/MOSAIC and VLT/VIMOS), optical (HST/ACS F435W, F606W, F775W, F814W, and F850LP), and infrared (HST/WFC3 F098M, VLT/ISAAC Ks, VLT/HAWK-I Ks, and Spitzer/IRAC 3.6, 4.5, 5.8, 8.0 μm) observations. The catalog is validated via stellar colors, comparison with other published catalogs, zero-point offsets determined from the best-fit templates of the spectral energy distribution of spectroscopically observed objects, and the accuracy of photometric redshifts. The catalog is able to detect unreddened star-forming (passive) galaxies with stellar mass of 10(exp 10) M(sub ☉) at a 50% completeness level to z ~ 3.4 (2.8), 4.6 (3.2), and 7.0 (4.2) in the three regions. As an example of application, the catalog is used to select both star-forming and passive galaxies at z ~ 2-4 via the Balmer break. It is also used to study the color-magnitude diagram of galaxies at 0 < z < 4.

CATALOGS↗
NASA NTRSDate not supplied

Aeroacoustic Measurements from the Aerodynamic and Acoustic Rotorprop Test (AART) in the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel

Unmanned Aerial Vehicle (UAV) designs typically have aerodynamic configurations that result in complex aerodynamic and acoustic conditions, such as wing and propeller interaction. In response, the Aerodynamic and Acoustic Rotorprop Test (AART) Program was implemented, a primary objective of which was to determine the aerodynamics and acoustics related to an auxiliary propulsor mounted behind an isolated wing in the National Full-Scale Aerodynamics Complex (NFAC) 40-by 80-Foot Wind Tunnel. Three configurations (no wing, half wing, and full wing) were tested, with conditions including variation of the propeller speed, wind tunnel Mach number, and Yaw. The acoustic set up, processing, and analysis are discussed along with the known issues for this complex data set. The interaction of upstream bodies and the resulting substantial increase in acoustic emissions are discussed in detail.

Propeller↗
NASA NTRS2019

The CANDELS/SHARDS Multi-Wavelength Catalog in GOODS-N: Photometry, Photometric Redshifts, Stellar Masses, Emission Line Fluxes and Star Formation Rates

We present a WFC3 F160W (H-band) selected catalog in the CANDELS/GOODS-N field containing photometry from the ultraviolet (UV) to the far-infrared (IR), photometric redshifts and stellar pa-rameters derived from the analysis of the multi-wavelength data. The catalog contains 35,445 sourcesover the 171 arcmin2of the CANDELS F160W mosaic. The 5σdetection limits (within an aperture ofradius 0.′′17) of the mosaic range betweenH= 27.8, 28.2 and 28.7 in the wide, intermediate and deepregions, that span approximately 50%, 15% and 35% of the total area. The multi-wavelength photom-etry includes broad-band data from UV (U band from KPNO and LBC), optical (HST/ACS F435W,F606W, F775W, F814W, and F850LP), near-to-mid IR (HST/WFC3 F105W, F125W, F140W andF160W, Subaru/MOIRCS Ks, CFHT/Megacam K, andSpitzer/IRAC 3.6, 4.5, 5.8, 8.0μm) and far IR(Spitzer/MIPS 24μm, HERSCHEL/PACS 100 and 160μm, SPIRE 250, 350 and 500μm) observations.In addition, the catalog also includes, optical medium-band data (R∼50) in 25 consecutive bands,λ= 500 to 950 nm, from the SHARDS survey and WFC3 IR spectroscopic observations with theG102 and G141 grisms (R∼210 and 130). The use of higher spectral resolution data to estimate pho-tometric redshifts provides very high, and nearly uniform, precision fromz= 0−2.5. The comparisonto 1,485 good quality spectroscopic redshifts up toz∼3 yields ∆z/(1+zspec)=0.0032 and an outlierfraction ofη=4.3%. In addition to the multi-band photometry, we release added-value catalogs withemission line fluxes, stellar masses, dust attenuations, UV- and IR-based star formation rates andrest-frame colors.

Guillermo Barro↗
NASA NTRS2024

Climate Extremes and Risks: Links Between Climate Science and Decision-Making

The World Climate Research Programme (WCRP) envisions a future where actionable climate information is universally accessible, supporting decision makers in preparing for and responding to climate change. In this perspective, we advocate for enhancing links between climate science and decision-making through a better and more decision-relevant understanding of climate impacts. The proposed framework comprises three pillars: climate science, impact science, and decision-making, focusing on generating seamless climate information from sub-seasonal, seasonal, decadal to century timescales informed by observed climate events and their impacts. The link between climate science and decision-making has strengthened in recent years, partly owing to undeniable impacts arising from disastrous weather extremes. Enhancing decision-relevant understanding involves utilizing lessons from past extreme events and implementing impact-based early warning systems to improve resilience. Integrated risk assessment and management require a comprehensive approach that encompasses good knowledge about possible impacts, hazard identification, monitoring, and communication of risks while acknowledging uncertainties inherent in climate predictions and projections, but not letting the uncertainty lead to decision paralysis. The importance of data accessibility, especially in the Global South, underscores the need for better coordination and resource allocation. Strategic frameworks should aim to enhance impact-related and open-access climate services around the world. Continuous improvements in predictive modeling and observational data are critical, as is ensuring that climate science remains relevant to decision makers locally and globally. Ultimately, fostering stronger collaborations and dedicated investments to process and tailor climate data will enhance societal preparedness, enabling communities to navigate the complexities of a changing climate effectively.

climate extremes↗