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At least 631 records · Page 35

Scaling from Jupiter to pulsars and mass spectrum of pulsars

Following the principle of similitude, the energy loss of Jupiter was scaled through the acceleration of high energy particles to that of Crab pulsar. The agreement suggests a classification scheme for all pulsars in which the pulsar angular velocity and its decrease with time are related to the pulsar moment of inertia divided by its radius and its mass is determined according to neutron star models. The mass spectrum of 194 pulsars is found to be approximately 1/sq m.

Fan, C. Y.↗

20th JANNAF Propulsion Systems Hazards Subcommittee Meeting

This volume, the first of two volumes, is a collection of 24 unclassified/unlimited-distribution papers which were presented at the Joint Army-Navy-NASA-Air Force (JANNAF) 20th Propulsion Systems Hazards Subcommittee (PSHS), 38th Combustion Subcommittee (CS), 26th Airbreathing Propulsion Subcommittee (APS), and 21 Modeling and Simulation Subcommittee meeting. The meeting was held 8-12 April 2002 at the Bayside Inn at The Sandestin Golf & Beach Resort and Eglin Air Force Base, Destin, Florida. Topics covered include: insensitive munitions and hazard classification testing of solid rocket motors and other munitions; vulnerability of gun propellants to impact stimuli; thermal decomposition and cookoff properties of energetic materials; burn-to-violent reaction phenomena in energetic materials; and shock-to-detonation properties of solid propellants and energetic materials.

Cocchiaro, James E.↗

Bayesian classification in a time-varying environment

The problem of classifying a pattern based on multiple observation made in a time-varying environment is analyzed. The identity of the pattern may itself change. A Bayesian solution is derived, after which the conditions of the physical situation are invoked to produce a cascade classifier model. Experimental results based on remote sensing data demonstrate the effectiveness of the classifier.

Swain, P. H.↗

Spatiotemporal Methane Emissions from Global Lakes and Reservoirs

Inland aquatic systems, such as lakes and reservoirs, contribute substantially to global methane (CH4) emissions; yet are among the most uncertain components of the total CH4 budget. Lakes and reservoirs have received recent attention as they may generate high CH4 fluxes. Improved quantification of these CH4 fluxes, particularly their spatiotemporal distribution, is key to realistically incorporating them in CH4 modeling and budget studies. Here we report on a new global, gridded (0.25° lat × 0.25° lon) study of lake and reservoir CH4 emissions, accounting for new knowledge regarding lake and reservoir areal extent and distribution, and spatiotemporal emission patterns influenced by diurnal variability, temperature-dependent seasonality, satellite-derived freeze-thaw dynamics, and eco-climatic and physical CH4-centric type classification. The results of this new data set comprise daily CH4 emissions from lake and reservoirs throughout the full annual cycle and are tightly anchored to field observations, in situ measurements, and remote-sensing observations. Results show that reservoirs cover 297 × 103 km2 globally and emit 10.1 Tg CH4 yr-1 from diffusive (1.2 Tg CH4 yr-1) and ebullitive (8.9 Tg CH4 yr-1) emission pathways. On a global scale, CH4 emitting areas of lakes cover 1853 × 103 km2 and emit 37.1 Tg CH4 yr-1 from diffusive (17.1 Tg CH4 yr-1) and ebullitive (23.0 Tg CH4 yr-1) emission pathways and an additional ebullition flux of 5.2 Tg CH4 yr-1 upon ice-melt due to the accumulation of bubbles during the freeze period. This analysis of lakes and reservoir CH4 emission addresses multiple gaps and uncertainties in previous studies and represents an important contribution to studies of the global CH4 budget. The new data sets and methodologies from this study provide a framework to better understand and model the current and future role of lakes and reservoirs in the global CH4 budget and to guide efforts to mitigate inland aquatic system CH4 emissions. This presentation will describe the methodologies applied and the major results of this study focusing on the spatiotemporal distribution of lake and reservoir type classification, processes driving lake and reservoir emission seasonality, and the contribution of individual lake and reservoir types to the annual cycle of inland aquatic CH4 emissions.

Spatiotemporal↗

The relative importance of aerosol scattering and absorption in remote sensing

Previous attempts to explain the effect of aerosols on satellite measurements of surface properties for the visible and near-infrared spectrum have emphasized the amount of aerosols without consideration of their absorption properties. In order to estimate the importance of absorption, the radiances of the sunlight scattered from models of the earth-atmosphere system are computed as functions of the aerosol optical thickness and absorption. The absorption effect is small where the surface reflectance is weak, but is important for strong reflectance. These effects on classification of surface features, measuring vegetation index, and measuring surface reflectance are presented.

Fraser, R. S.↗

Gamma-Ray Burst Class Properties

Guided by the supervised pattern recognition algorithm C4.5 developed by Quinlan in 1986, we examine the three gamma-ray burst classes identified by Mukherjee et al. in 1998. C4.5 provides strong statistical support for this classification. However, with C4.5 and our knowledge of the Burst and Transient Source Experiment (BATSE) instrument, we demonstrate that class 3 (intermediate fluence, intermediate duration, soft) does not have to be a distinct source population: statistical/systematic errors in measuring burst attributes combined with the well-known hardness/intensity correlation can cause low peak flux class 1 (high fluence, long, intermediate hardness) bursts to take on class 3 characteristics naturally. Based on our hypothesis that the third class is not a distinct one, we provide rules so that future events can be placed in either class 1 or class 2 (low fluence, short, hard). We find that the two classes are relatively distinct on the basis of Band's work in 1993 on spectral parameters alpha, beta, and E (sub peak) alone. Although this does not indicate a better basis for classification, it does suggest that different physical conditions exist for class 1 and class 2 bursts. In the process of studying burst class characteristics, we identify a new bias affecting burst fluence and duration measurements. Using a simple model of how burst duration can be underestimated, we show how this fluence duration bias can affect BATSE measurements and demonstrate the type of effect it can have on the BATSE fluence versus peak flux diagram.

Hakkila, Jon↗

Defining Handling Qualities of Unmanned Aerial Systems: Phase II Final Report

Unmanned Air Systems (UAS) are no longer coming, they are here, and operators from first responders to Google and Amazon are demanding access to the National Airspace System (NAS) for a wide variety of missions. This includes a proliferation of small UAS or sUAS that will operate beyond line of sight at altitudes of 500 ft and below. A myriad of issues continues to slow the development of verification, validation, and certification methods that will enable the safe introduction of UAS to the NAS. These issues include the lack of both a consensus in UAS categorization process and quantitative certification requirements, including the definition of handling qualities. Because of the wide variety of UAS types (fixed wing, rotary wing from traditional helicopters to multirotor configurations, ducted fans, airships, etc.) and vehicle size from micro vehicles to the Global Hawk with a wing span similar to that of a Boeing 737, there cannot be a one-size-fits-all set of requirements. To address these issues, Systems Technology Inc. (STI) has developed the UAS Handling Qualities Assessment (UAS-HQ) process and corresponding draft specification that will guide UAS stakeholders through a systematic evaluation process. The work described herein builds on the existing, highly successful, military rotorcraft handling qualities specifications that features a mission-oriented approach, a concept that originated at STI. The vehicle is first identified by a simple weight-based classification and then the associated vehicle mission task elements are considered. These missions have specific tasks inclusive to them that then dictate the criteria and demonstration maneuvers necessary to evaluate the UAS handling qualities. An assessment of both modeled responses and flight test data can then be conducted to examine the predicted versus actual handling qualities and, if required, design modifications can then be made. Mr. David Klyde, Vice President and Technical Director, Engineering Services, served as Principal Investigator, while Dr. Natalia Alexandrov served as the NASA LaRC technical representative. In the Phase II program, STI was joined by David Mitchell of Mitchell Aerospace Research and the University of Minnesota. Mr. Mitchell led the draft specification development effort, while the University of Minnesota UAV Lab conducted sUAS flight tests under the direction of Dr. Peter Seiler.

Klyde, David H.↗

Remote sensing of agricultural crops and soils

Research in the correlative and noncorrelative approaches to image registration and the spectral estimation of corn canopy phytomass and water content is reported. Scene radiation research results discussed include: corn and soybean LANDSAT MSS classification performance as a function of scene characteristics; estimating crop development stages from MSS data; the interception of photosynthetically active radiation in corn and soybean canopies; costs of measuring leaf area index of corn; LANDSAT spectral inputs to crop models including the use of the greenness index to assess crop stress and the evaluation of MSS data for estimating corn and soybean development stages; field research experiment design data acquisition and preprocessing; and Sun-view angles studies of corn and soybean canopies in support of vegetation canopy reflection modeling.

Bauer, M. E.↗

Ice Shape Classification for Swept Wings

An important consideration for swept-wing ice shapes is the level of geometric fidelity required to accurately capture the aerodynamics. One way to help make the task of addressing this more manageable is to organize the ice shapes into a small number of classifications. These classifications are done by grouping similar ice shape geometries that also have similar iced wing aerodynamics. Ice shape classifications for airfoils are more mature and are reviewed as an example. Swept wing ice shape classifications are based on the well-established airfoil classifications and here five classifications are proposed: leading-edge roughness, streamwise ice, 3D leading-edge horn, highly 3D leading-edge horn and spanwise ridge. Recent data on swept wing icing aerodynamics is used to develop and support this classification. The development, or suppression, of the leading-edge separation vortex on swept wings without a leading-edge device is seen to be key in the classification of the highly 3D leading-edge horn.

Aircraft icing↗

Brief summary of the evolution of high-temperature creep-fatigue life prediction models for crack initiation

The evolution of high-temperature, creep-fatigue, life-prediction methods used for cyclic crack initiation is traced from inception in the late 1940's. The methods reviewed are material models as opposed to structural life prediction models. Material life models are used by both structural durability analysts and by material scientists. The latter use micromechanistic models as guidance to improve a material's crack initiation resistance. Nearly one hundred approaches and their variations have been proposed to date. This proliferation poses a problem in deciding which method is most appropriate for a given application. Approaches were identified as being combinations of thirteen different classifications. This review is intended to aid both developers and users of high-temperature fatigue life prediction methods by providing a background from which choices can be made. The need for high-temperature, fatigue-life prediction methods followed immediately on the heels of the development of large, costly, high-technology industrial and aerospace equipment immediately following the second world war. Major advances were made in the design and manufacture of high-temperature, high-pressure boilers and steam turbines, nuclear reactors, high-temperature forming dies, high-performance poppet valves, aeronautical gas turbine engines, reusable rocket engines, etc. These advances could no longer be accomplished simply by trial and error using the 'build-em and bust-em' approach. Development lead times were too great and costs too prohibitive to retain such an approach. Analytic assessments of anticipated performance, cost, and durability were introduced to cut costs and shorten lead times. The analytic tools were quite primitive at first and out of necessity evolved in parallel with hardware development. After forty years more descriptive, more accurate, and more efficient analytic tools are being developed. These include thermal-structural finite element and boundary element analyses, advanced constitutive stress-strain-temperature-time relations, and creep-fatigue-environmental models for crack initiation and propagation. The high-temperature durability methods that have evolved for calculating high-temperature fatigue crack initiation lives of structural engineering materials are addressed. Only a few of the methods were refined to the point of being directly useable in design. Recently, two of the methods were transcribed into computer software for use with personal computers.

Halford, Gary R.↗

Gamma-Ray Burst Class Properties

Guided by the Supervised pattern recognition algorithm C4.5, we examine the three gamma-ray burst classes identified by Mukherjee et al. C4.5 provides strong statistical support for this classification. However, with C4.5 and our knowledge of the BATSE instrument, we demonstrate that Class 3 (intermediate fluence, intermediate duration, soft) does not have to be a distinct source population: statistical/systematic errors in measuring burst attributes combined with the well-known hardness/intensity correlation can cause low peak flux Class I (high fluence, long, intermediate hardness) bursts to take on Class 3 characteristics naturally. Based on our hypothesis that the third class is not a distinct one, we provide rules so that future events can be placed in either Class I or Class 2 (low fluence, short, hard). Using classified bursts from the BATSE 4B Catalog, we plot log(N>P) vs. log(P) curves and study spectral features of each class. We find that the two classes are relatively distinct on the basis of spectral parameters, alpha, Beta, and E(sub peak) alone. Although this does not indicate a better basis for classification, it does suggest that different physical conditions exist for Class I and Class 2 bursts. In the process of studying burst class characteristics, we identify a new bias that affects measurement of burst fluences and durations. Using a simple model of how burst duration can be underestimated, we generally characterize how this fluence duration bias affects BATSE measurements, and demonstrate the type of effect it can have on the BATSE fluence vs. peak flux diagram.

Hakkila, Jon↗

Revolutionizing Earth Science with Generalized AI Models

Foundation Models (FM) are generalized Artificial Intelligence (AI) models that are designed to replace a task or an application-specific model and can be used for many downstream applications. These FM can be built on any sequence data and are trained utilizing self-supervised approaches. The obstacle of creating a sizable labeled dataset for training is removed by using self-supervised learning. Most FM employ transformer design that takes advantage of the idea of self-attention, allowing the network to represent the impact of distant data points on one another in space and time. The FM models show emergent qualities that are induced from the data. FM can become a valuable tool for Earth science researchers. Due to the size of these models, downstream applications built fine-tuning these FM perform better and exhibit greater accuracy than models created from scratch. FM significantly lowers the entry barrier in terms of both the time and effort required to develop various downstream applications. For some scientific datasets, such as optical remote sensing data, FM can speed up processes like classification, object detection and prediction. By eliminating the training data bottleneck and maximizing the usage of science data, FM can make it simpler to integrate AI into scientific research. Initial results for three different FMs will be presented.

Rahul Ramachandran↗

The pressure and energy balance of the cool corona over sunspots

The 22 largest sunspots observed with the Skylab SO55 spectrometer are studied for a relation between their EUV radiation and their umbral size or magnetic classification. The ultimate goal is to determine why the coronal plasma is so cool over a sunspot and how this cool plasma manages to support itself against gravity. Based on the time behavior of the EUV emission, a steady-state model is developed for the pressure and energy balance of the cool coronal-plasma loops over the spots. Analysis of the temperature structure in a typical loop indicates that the loop is exceedingly well insulated from the outside corona, that its energy balance is determined purely by internal heating and cooling processes, and that a heat input of about 0.0001 erg/cu cm per sec is required along the full length of the loop. It is proposed that: (1) coronal material flows steadily across the field lines at the tops of the loops and falls downward along both sides under gravity; (2) the corona is heated by mechanical-energy transport across the very thin transition region immediately over network-cell interiors; and (3) strong magnetic fields tend to inhibit mechanical-energy dissipation in the corona.

Foukal, P. V.↗

Error detection process - Model, design, and its impact on computer performance

An analytical model is developed for computer error detection processes and applied to estimate their influence on system performance. Faults in the hardware, not in the design, are assumed to be the potential cause of transition to erroneous states during normal operations. The classification properties and associated recovery methods of error detection are discussed. The probability of obtaining an unreliable result is evaluated, along with the resulting computational loss. Error detection during design is considered and a feasible design space is outlined. Extension of the methods to account for the effects of extant multiple faults is indicated.

Shin, K. G.↗

IRAC Observations of Taurus Pre-Main-Sequence Stars

We presented infrared photometry obtained with the IRAC camera on the Spitzer Space Telescope of a sample of 82 pre-main-sequence stars and brown dwarfs in the Taurus starforming region. We find a clear separation in some IRAC color-color diagrams between objects with and without disks. A few "transition" objects are noted, which correspond to systems in which the inner disk has been evacuated of small dust. Separating pure disk systems from objects with remnant protostellar envelopes is more difficult at IRAC wavelengths, especially for objects with infall at low rates and large angular momenta. Our results generally confirm the IRAC color classification scheme used in previous papers by Allen et al. and Megeath et al. to distinguish between protostars, T Tauri stars with disks, and young stars without (inner) disks. The observed IRAC colors are in good agreement with recent improved disk models, and in general accord with models for protostellar envelopes derived from analyzing a larger wavelength region. We also comment on a few Taurus objects of special interest. Our results should be useful for interpreting IRAC results in other, less well studied star-forming regions.

Hartmann, L.↗

Applications of remote sensing to hydrologic planning

The transfer of LANDSAT remote sensing technology from the research sector to user operational applications requires demonstration of the utility and accuracy of LANDSAT data in solving real problems. This report describes such a demonstration project in the area of water resources, specifically the estimation of non-point source pollutant loads. Non-point source pollutants were estimated from land cover data from LANDSAT images. Classification accuracies for three small watersheds were above 95%. Land cover was converted to pollutant loads for a fourth watershed through the use of coefficients relating significant pollutants to land use and storm runoff volume. These data were input into a simulator model which simulated runoff from average rainfall. The result was the estimation of monthly expected pollutant loads for the 17 subbasins comprising the Magothy watershed.

Loats, H., Jr.↗

An evaluation of a SIRA image to determine forest density under conditions of moderate topographical variation

Many studies have shown that radar images have increased classification accuracy over spectral classifications using only LANDSAT Multispectral Band Scanner (MSS) images. It was the objective to determine if a SIRA image taken over Hayfork when used alone or inconjuction with LANDSAT MSS data would increase separation of units not identified by LANSAT spectral mixture models. Areas in the LANDSAT model of varying vegetation density (0 to 50%) that had proven to be accurate by field surveys were compared. It was found in the Hayfork area that SIRA did not increase or help delineation of vegetation or ultramific units over LANDSAT MSS.

Smith, M.↗

Navier-Stokes and Euler solutions for lee-side flows over supersonic delta wings. A correlation with experiment

An Euler flow solver and a thin layer Navier-Stokes flow solver were used to numerically simulate the supersonic leeside flow fields over delta wings which were observed experimentally. Three delta wings with 75, 67.5, and 60 deg leading edge sweeps were computed over an angle-of-attack range of 4 to 20 deg at a Mach number 2.8. The Euler code and Navier-Stokes code predict equally well the primary flow structure where the flow is expected to be separated or attached at the leading edge based on the Stanbrook-Squire boundary. The Navier-Stokes code is capable of predicting both the primary and the secondary flow features for the parameter range investigated. For those flow conditions where the Euler code did not predict the correct type of primary flow structure, the Navier-Stokes code illustrated that the flow structure is sensitive to boundary layer model. In general, the laminar Navier-Stokes solutions agreed better with the experimental data, especially for the lower sweep delta wings. The computational results and a detailed re-examination of the experimental data resulted in a refinement of the flow classifications. This refinement in the flow classification results in the separation bubble with the shock flow type as the intermediate flow pattern between separated and attached flows.

Mcmillin, S. Naomi↗