Search NASA⌕ Search

SEARCH · Search NASA

Results for “Massive Data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

UH cosmic rays - Possible origin in massive stars

The origin of the Z greater than 28, ultraheavy (UH) cosmic rays in supernova explosions of massive stars, at least about 10 solar masses, is considered. For Z greater than 70, the UH data are dominated by an r-process source distribution, but for the elements just beyond iron, Z from 29 to 36, the data cannot be explained by any single process of nucleosynthesis. This problem is solved naturally in a massive-star model by secondary neutron-capture reactions occurring during core helium burning (a limited s-process) and during explosive carbon burning. Interstellar-propagation calculations have been performed with these episodes of synthesis as source distributions, and the results offer an explanation for the current UH cosmic-ray data. Further, the heavy-element synthesis during explosive carbon burning is re-examined by using more realistic initial conditions given by the post-helium-burning configuration of the star. These results are compared with earlier work and the UH cosmic-ray data. Some effects of preferential acceleration, based upon ionization potential, are considered, and experimental tests for this model are discussed.

Wefel, J. P.↗
NASA NTRS2016

DeepSAT: A Deep Learning Approach to Tree-Cover Delineation in 1-m NAIP Imagery for the Continental United States

High resolution tree cover classification maps are needed to increase the accuracy of current land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) tree cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agriculture Imagery Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~65 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. Using the NASA Earth Exchange (NEX) initiative, we have developed an end-to-end architecture by integrating a segmentation module based on Statistical Region Merging, a classification algorithm using Deep Belief Network and a structured prediction algorithm using Conditional Random Fields to integrate the results from the segmentation and classification modules to create per-pixel class labels. The training process is scaled up using the power of GPUs and the prediction is scaled to quarter million NAIP tiles spanning the whole of Continental United States using the NEX HPC supercomputing cluster. An initial pilot over the state of California spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles has produced true positive rates of around 88 percent for fragmented forests and 74 percent for urban tree cover areas, with false positive rates lower than 2 percent for both landscapes.

Imagery↗
NASA NTRSDate not supplied

NASA’s Prototype Spectral Water Inversion Processor and Emulator (SWIPE): Towards Global Coastal and Inland Water Quality and Algal Biodiversity Monitoring

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will provide updates on NASA’s prototype open-source aquatic modeling platform, Spectral Water Inversion Processor and Emulator (SWIPE), which is a comprehensive, multi-faceted modeling platform for both forward and inverse modeling of diverse aquatic ecosystems from the benthos to top-of-atmosphere (TOA). SWIPE provides a cohesive application which leverages recent advancements in particle modeling, Big Data analytics, and machine learning to develop a high-fidelity synthetic training ground for sensitivity studies and algorithm development for multispectral or upcoming hyperspectral missions. Some of the prominent features of SWIPE to be discussed include: 1. Advanced hyperspectral modeling of globally diverse algal and non-algal particles using a novel two-layer coated sphere scattering model and radiative transfer modeling, 2. Massive, highly detailed synthetic spectral libraries of Analysis-Ready-Data (ARD) which include spectral libraries of particle microphysics, water biogeophysical and optical properties, as well as surface and TOA reflectances at 1 nm resolution, 3. An ensemble of pre-built analytic, machine learning, and deep learning inversion algorithms for various water quality and biodiversity related retrieval parameters and uncertainty quantification, 4. Sensor-agnostic water quality inversion at wide ranging spatial and spectral resolutions including a codebase for seamless application in the Google Earth Engine and NASA Earth Exchange (NEX) for planetary scale analysis. SWIPE will be a fully open-source platform based in python with comprehensive documentation, tutorials, and options for distributed computing on high performance computing clusters or on single, local machines. Further, we will discuss how we envision SWIPE contributing towards a global analysis of coastal and inland water quality dynamics.

top-of-atmosphere (TOA)↗
NASA NTRS2020

Development of a Non-Iterative Balance Load Prediction Algorithm for the NASA Ames Unitary Plan Wind Tunnel

A non-iterative load prediction algorithm for strain-gage balances was developed for the NASA Ames Unitary Plan Wind Tunnels that computes balance loads from the electrical outputs of the balance bridges and a set of state variables. A state variable could be, for example, a balance temperature difference or the bellows pressure of a flow-through balance. The algorithm directly uses regression models of the balance loads for the load prediction that were obtained by applying global regression analysis to balance calibration data. This choice greatly simplifies both implementation and use of the load prediction process for complex balance configurations as no load iteration needs to be performed. The regression model of a balance load is constructed by using terms from a total of nine term groups. Four term groups are derived from a Taylor Series expansion of the relationship between the load, gage outputs, and state variables. The remaining five term groups are defined by using absolute values of the gage outputs and state variables. Terms from these groups should only be included in the regression model if calibration data from a balance with known bi-directional outputs is analyzed. It is illustrated in detail how global regression analysis may be applied to obtain the coefficients of the chosen regression model of a load component assuming that no linear or massive near-linear dependencies between the regression model terms exist. Data from the machine calibration of a six-component force balance is used to illustrate both application and accuracy of the non-iterative load prediction process.

Ulbrich, Norbert M.↗
NASA NTRS1983

The nature of R136a, the superluminous central object of the 30 Doradus nebula

UV data show R136a to be an extremely luminous object having spectral characteristics similar to that of O3 stars. It is suggested that the bright component of R136a is either a single, supermassive hydrogen-burning star, or a compact multiple system of supermassive stars. In the former case, the observational data imply a mass exceeding that of the most massive stars known by a factor of 20 and raise important theoretical problems concerning stellar formation and stability. Formation may occur through ordinary collapse in a region with peculiar dust properties, or through coalescence in the core of a compact cluster.

Cassinelli, J. P.↗
NASA NTRS1987

The architecture of tomorrow's massively parallel computer

Goodyear Aerospace delivered the Massively Parallel Processor (MPP) to NASA/Goddard in May 1983, over three years ago. Ever since then, Goodyear has tried to look in a forward direction. There is always some debate as to which way is forward when it comes to supercomputer architecture. Improvements to the MPP's massively parallel architecture are discussed in the areas of data I/O, memory capacity, connectivity, and indirect (or local) addressing. In I/O, transfer rates up to 640 megabytes per second can be achieved. There are devices that can supply the data and accept it at this rate. The memory capacity can be increased up to 128 megabytes in the ARU and over a gigabyte in the staging memory. For connectivity, there are several different kinds of multistage networks that should be considered.

Batcher, Ken↗
NASA NTRS1999

Airborne Radar Observations of Hurricane Georges during Landfall over the Dominican Republic

On 22 September 1998 hurricane Georges made landfall on the Dominican Republic (DR). Georges cost the DR at least 500 lives, made more than 155,000 people homeless and caused extensive damage to the country's main industries, tourism and agriculture. There was considerable wind damage, with wind gusts up to 58 m/s in Santa Domingo on the south coast, but most of the damage and deaths resulted from mudslides and the flooding of rivers. While this may have been the worst natural disaster to strike the DR, the sustained rapid storm movement saved the island from worse damage. Georges had previously affected several islands in the Lesser Antilles and Puerto Rico, but it had retained much of its circulation strength. Forty raingauge stations across the DR measured rainfall totals from Georges between 0.7 and 41 cm, the latter at the capital Santo Domingo, located on the south coast. At Herrera the maximum 1 h rainfall rate was 72 mm/h. It is suspected that much higher rain rates occurred in DR's mountainous interior. Before landfall the eye was clearly evident in satellite imagery. When the eye moved over southeastern DR, it filled rapidly, and the cloud top height decreased in all storm sectors except in the southern inflow sector, where a long-lived MCS, with a diameter larger than that of the eyewall, slowly became enwrapped in the hurricane circulation. The eye closure was most rapid between 16-18 UTC, when the eyewall circulation felt the mountainous terrain of the Cordillera Central, which rises up to 3,093 m. The estimated central pressure increased from 962 hPa at 15 UTC to 986 hPa at 03Z on 23 Sept, and the maximum sustained surface wind speed decreased from 54 to 36 in s-1 during the same period. The island of Hispaniola has a cross-track width of about 250 km, much wider than the diameter of the eyewall anvil (about 100 km before landfall). So the event can truly be considered to be a landfalling case, even though Georges recovered after crossing Hispaniola, albeit never to the same strength. This talk will summarize satellite and ground observations of Georges, as it passed the DR, and it will focus on EDOP data. In particular, we will try to estimate the rainfall rate over the mountainous terrain of the DR. And we will use detailed sounding data to explain the presence and characteristics of the massive MCS to the south, as well as the upper-level updrafts apparent over this MCS and over the mountains of the DR.

Geerts, B.↗
NASA NTRS2013

Towards Efficient Scientific Data Management Using Cloud Storage

A software prototype allows users to backup and restore data to/from both public and private cloud storage such as Amazon's S3 and NASA's Nebula. Unlike other off-the-shelf tools, this software ensures user data security in the cloud (through encryption), and minimizes users operating costs by using space- and bandwidth-efficient compression and incremental backup. Parallel data processing utilities have also been developed by using massively scalable cloud computing in conjunction with cloud storage. One of the innovations in this software is using modified open source components to work with a private cloud like NASA Nebula. Another innovation is porting the complex backup to- cloud software to embedded Linux, running on the home networking devices, in order to benefit more users.

He, Qiming↗
NASA NTRSDate not supplied

Relating Changing Aerosols to Changing Clouds: Two Decades of Terra and Aqua Observations

The global aerosol system of today is not the same as it was two decades ago when Terra and Aqua were launched. As a result of a changing climate (natural and anthropogenic) convolved with changes in human activity (deliberate and accidental), some regions have experienced significant changes to their total aerosol burden (increases or decreases of total loading) or their aerosol composition (as defined by relative size or source type). Other regions have had less or no significant changes. At the same time, changes in aerosol amount and composition affect clouds through direct and indirect microphysical and radiative processes. We can theoretically predict what might happen to clouds when you add aerosol to an otherwise pristine environment. Conversely, there is the situation of removing aerosol from a polluted environment. Over the past two decades, sensors on both Earth Observing Satellites (Terra and Aqua) have observed the radiative signatures of aerosols and clouds, as well as their changes. Via massive efforts by their respective characterization teams, the resulting data records appear to have a minimum of artificial drifts. Therefore, we are trying to assess, region by region, our 20-year records of aerosols and clouds, along with meteorological variables. Where have been the most significant changes of aerosols and/or clouds? Where do the changes in clouds conform with expectations based on changes of aerosols and meteorology and where do they not? In addition to separate ‘aerosol’ and ‘cloud’ retrievals from the Moderate Resolution Imaging Spectrometer (MODIS), there is a ‘twilight zone’ that is not accounted for in either product. What are these regions, and have they changed over the past two decades? We will present our early efforts at characterizing the MODIS view of aerosol and cloud changes, while also relating to changes in radiative fluxes at the top-of-atmosphere (TOA) from corresponding observations by the Clouds and the Earth's Radiant Energy System (CERES).

aerosols↗
NASA NTRS2019

Evidence for Late-stage Eruptive Mass Loss in the Progenitor to SN2018gep, a Broad-lined Ic Supernova: Pre-explosion Emission and a Rapidly Rising Luminous Transient

We present detailed observations of ZTF18abukavn (SN2018gep), discovered in high-cadence data from the Zwicky Transient Facility as a rapidly rising (1.4 ± 0.1 mag/hr) and luminous (M(g,peak) = -20 mag) transient. It is spectroscopically classified as a broad-lined stripped-envelope supernova (Ic-BL SN). The high peak luminosity (L(bol) ≳ 3 x 10^(44) erg/s), the short rise time (t = 3 days rise in g band), and the blue colors at peak (g–r ~ -0.4) all resemble the high-redshift Ic-BL iPTF16asu, as well as several other unclassified fast transients. The early discovery of SN2018gep (within an hour of shock breakout) enabled an intensive spectroscopic campaign, including the highest-temperature (T(eff) ≳ 40,000 K) spectra of a stripped-envelope SN. A retrospective search revealed luminous (M(g) ~ M(r) ≈ -14 mag) emission in the days to weeks before explosion, the first definitive detection of precursor emission for a Ic-BL. We find a limit on the isotropic gamma-ray energy release E(γ,iso) < 4.9 x 10^(48) erg, a limit on X-ray emission L(X) < 10^(40) erg/s, and a limit on radio emission vL(v) ≲ 10^(37) erg/s. Taken together, we find that the early (<10 days) data are best explained by shock breakout in a massive shell of dense circumstellar material (0.02 Mꙩ) at large radii (3 x 10^(14) cm) that was ejected in eruptive pre-explosion mass-loss episodes. The late-time (>10 days) light curve requires an additional energy source, which could be the radioactive decay of Ni-56.

Anna Y. Q. Ho↗
NASA NTRS1986

CO mapping of the Orion molecular cloud: The influence of star formation on cloud structure

Regions of massive star formation have long been believed to have a profound influence on the structure of their surrounding molecular clouds. The ways in which massive star formation has altered the structure and kinematics of the Orion Molecular Cloud are discussed. The data to be discussed consists of a large scale map of the CO J=1-0 emission from approximately 3 square degrees of OMC-1. During 1985, the Five College Radio Astronomy Observatory 14M antenna was used to map a 2 deg x 1 deg region centered on alpha(1950) = 5(h)33(m)00(s) delta(1950) = -5 deg 30 min. The region mapped in 1985 covers the well known HII regions M42, M43, and NGC1977, and the CO map contains abundant evidence of the interaction between these regions and the molecular cloud. Indeed, the global structure of the cloud appears to have been strongly influenced by the continuous formation of massive stars within the cloud. Individual instances of some of these features are discussed. There appear to be two classes of features which are indicative of this interaction: CO bright rims and CO holes. During 1986, we have undertaken further mapping of OMC-1 to the south of the region covered by the 1985 map. This portion of the cloud contains significant regions of star formation, but O star formation has not occured and large HII regions have not developed to alter the appearance of the cloud. A detailed map of this region is thus an opportunity to view the structure of the molecular cloud before it has been altered by massive star formation. Preliminary analysis of data obtained in this region suggests that the structure and kinematics of the southern portion of the Orion cloud are indeed dramatically different from those of the region previously mapped. Comparison of the two regions thus supports models of the development of structure in molecular clouds through interaction with the HII regions formed within them.

Schloerb, F. P.↗
NASA NTRS1987

Contextual classification on the massively parallel processor

Classifiers are often used to produce land cover maps from multispectral Earth observation imagery. Conventionally, these classifiers have been designed to exploit the spectral information contained in the imagery. Very few classifiers exploit the spatial information content of the imagery, and the few that do rarely exploit spatial information content in conjunction with spectral and/or temporal information. A contextual classifier that exploits spatial and spectral information in combination through a general statistical approach was studied. Early test results obtained from an implementation of the classifier on a VAX-11/780 minicomputer were encouraging, but they are of limited meaning because they were produced from small data sets. An implementation of the contextual classifier is presented on the Massively Parallel Processor (MPP) at Goddard that for the first time makes feasible the testing of the classifier on large data sets.

Tilton, James C.↗
NASA NTRS1995

SAVS: A Space and Atmospheric Visualization Science system

The research environment faced by space and atmospheric scientists in the 1990s is characterized by unprecedented volumes of new data, by ever-increasing repositories of unexploited mission files, and by the widespread use of empirical and large-scale computational models needed for the synthesis of understanding across data sets and discipline boundaries. The effective analysis and interpretation of such massive amounts of information have become the subjects of legitimate concern. With SAVS (a Space and Atmospheric Visualization Science System), we address these issues by creating a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, and analysis without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. SAVS provides (1) a customizable framework for accessing a powerful set of visualization tools based on the popular AVS visualization software with hooks to PV-Wave and access to Khoros modules, (2) a set of mathematical and statistical tools, (3) an extensible library of discipline-specific functions and models (e.g., MSIS, IRI, Feldstein Oval, IGRF, satellite tracking with CADRE-3, etc.), and (4) capabilities for local and remote data base access. The system treats scalar, vector, and image data, and runs on most common Unix workstations. We present a description of SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the Earth's thermospheric, ionospheric, and mesospheric domains (TIMED).

Szuszczewicz, E. P.↗
NASA NTRS2009

Eta Carinae in the Context of the Most Massive Stars

Eta Car, with its historical outbursts, visible ejecta and massive, variable winds, continues to challenge both observers and modelers. In just the past five years over 100 papers have been published on this fascinating object. We now know it to be a massive binary system with a 5.54-year period. In January 2009, Car underwent one of its periodic low-states, associated with periastron passage of the two massive stars. This event was monitored by an intensive multi-wavelength campaign ranging from -rays to radio. A large amount of data was collected to test a number of evolving models including 3-D models of the massive interacting winds. August 2009 was an excellent time for observers and theorists to come together and review the accumulated studies, as have occurred in four meetings since 1998 devoted to Eta Car. Indeed, Car behaved both predictably and unpredictably during this most recent periastron, spurring timely discussions. Coincidently, WR140 also passed through periastron in early 2009. It, too, is a intensively studied massive interacting binary. Comparison of its properties, as well as the properties of other massive stars, with those of Eta Car is very instructive. These well-known examples of evolved massive binary systems provide many clues as to the fate of the most massive stars. What are the effects of the interacting winds, of individual stellar rotation, and of the circumstellar material on what we see as hypernovae/supernovae? We hope to learn. Topics discussed in this 1.5 day Joint Discussion were: Car: the 2009.0 event: Monitoring campaigns in X-rays, optical, radio, interferometry WR140 and HD5980: similarities and differences to Car LBVs and Eta Carinae: What is the relationship? Massive binary systems, wind interactions and 3-D modeling Shapes of the Homunculus & Little Homunculus: what do we learn about mass ejection? Massive stars: the connection to supernovae, hypernovae and gamma ray bursters Where do we go from here? (future directions) The Science Organizing Committee: Co-chairs: Augusto Damineli (Brazil) & Theodore R. Gull (USA). Members: D. John Hillier (USA), Gloria Koenigsberger (Mexico), Georges Meynet (Switzerland), Nidia Morrell (Chile), Atsuo T. Okazaki (Japan), Stanley P. Owocki (USA), Andy M.T. Pol- lock (Spain), Nathan Smith (USA), Christiaan L. Sterken (Belgium), Nicole St Louis (Canada), Karel A. van der Hucht (Netherlands), Roberto Viotti (Italy) and GerdWeigelt (Germany)

Gull, Theodore R.↗
NASA NTRS1987

A simple two-component model for the far-infrared emission from galaxies

A simple model was constructed to calculate the far-infrared emission of galaxies made up of a disk component containing cool dust heated by the general interstellar radiation field and of a molecular cloud component containing warm dust heated by recently formed massive stars. This model is fitted to the optical and far-infrared data of 120 Shapley-Ames galaxies and of 20 optically studied mini-survey galaxies, resulting in the determination of blue face-on extinctions and of the total luminosities of recently born massive stars and disk stars. The ratio of these two luminosities is a more reliable star formation activity index than the previously used ratio L sub IR/L sub B. The results show that infrared selected galaxies are on the average almost three times more dusty than optically selected ones. Only about 10% of the mini-survey galaxies exhibits strongly enhanced star formation.

Dejong, T.↗
NASA NTRS1991

Massive star evolution and SN 1987A

The evolution of massive stars through hydrogen and helium burning is addressed. A set of stellar evolutionary sequences for mass/solar mass of 15, 20, and 25, and metallicity of 0.002, 0.005, 0.007, 0.010, and 0.20 are presented; semiconvection is restricted to operating slower than the local thermal time scale. Using these sequences, simple models of the massive star content of the LMC are found to agree moderately well with the new observational data of Fitzpatrick and Garmany (1990). LMC supergiants were detected only in their postmain-sequence phases, so that 5-10 times more massive stars are there but not identified as such. It is argued that SN 1987A exhibits the normal evolution of a single star of about 20 solar mases having LMC abundances. Despite the variety of envelope behavior, the structure of the core at collapse is rather similar for the stars of a given mass. Variations due to different rates of mass loss are likely to be larger than those due to composition.

Arnett, David↗
NASA NTRS1997

The Contribution of Ionizing Stars to the Far-Infrared and Radio Emission in the Galaxy

This is the first report of a new contract. However, this project represents ongoing work, so there are completed tasks as well as newly started tasks to report. The project involves the completion of the IRAS Galaxy Atlas (IGA), a large image database produced using data from the Infrared Astronomical Satellite (IRAS). In this phase, the project switches from the production and characterization of the IGA to its use in astronomical research studies of massive star formation. The research utilizes the IGA as well as two other large data sets being produced by research partners.

Cao, Yu↗
NASA NTRS2021

The NANOGrav 11yr Data Set: Limits on Supermassive Black Hole Binaries in Galaxies within 500 Mpc

Supermassive black hole binaries (SMBHBs) should form frequently in galactic nuclei as a result of galaxy mergers. At subparsec separations, binaries become strong sources of low-frequency gravitational waves (GWs), targeted by Pulsar Timing Arrays. We used recent upper limits on continuous GWs from the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) 11 yr data set to place constraints on putative SMBHBs in nearby massive galaxies. We compiled a comprehensive catalog of ∼44,000 galaxies in the local universe (up to redshift ∼0.05) and populated them with hypothetical binaries, assuming that the total mass of the binary is equal to the SMBH mass derived from global scaling relations. Assuming circular equal-mass binaries emitting at NANOGrav's most sensitive frequency of 8 nHz, we found that 216 galaxies are within NANOGrav's sensitivity volume. We ranked the potential SMBHBs based on GW detectability by calculating the total signal-to-noise ratio such binaries would induce within the NANOGrav array. We placed constraints on the chirp mass and mass ratio of the 216 hypothetical binaries. For 19 galaxies, only very unequal-mass binaries are allowed, with the mass of the secondary less than 10% that of the primary, roughly comparable to constraints on an SMBHB in the Milky Way. However, we demonstrated that the (typically large) uncertainties in the mass measurements can weaken the upper limits on the chirp mass. Additionally, we were able to exclude binaries delivered by major mergers (mass ratio of at least 1/4) for several of these galaxies. We also derived the first limit on the density of binaries delivered by major mergers purely based on GW data.

Zaven Arzoumanian↗