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At least 667 records · Page 37

Minimum High Fire Temperatures Detected in AVIRIS Spectral Measurements from Brazil in 1995

In August and September of 1995 the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) was deployed to Brazil as part of the NASA Smoke Cloud Aerosol and Radiation experiment in Brazil (SCAR-B). AVIRIS measures spectra from 400 to 2500 nm at 10-nm intervals. These spectra are acquired as images with dimensions of 11 by up to 800 km with 20-m spatial resolution. Spectral images measured by AVIRIS are spectrally, radiometrically, and spatially calibrated. During the SCAR-B deployment, AVIRIS measured more than 300 million spectra of regions of Brazil. A portion of these spectra were acquired over areas of actively burning fires. Actively burning fires emit radiance in the AVIRIS spectral range as a function of temperature. This emitted radiance is expressed from the 2500-nm end of the AVIRIS spectrum to shorter wavelengths as a function of intensity and modeled by the Planck function. The objective of this research and analysis was to use spectroscopic methods to determine the minimum high temperature of the most intense fires measured in the SCAR-B AVIRIS data set. Spectra measured by AVIRIS with hot sources have been previously examined for volcanic lava.

Green, Robert O.↗

Minimum High Fire Temperatures Detected in AVIRIS Spectral Measurements from Brazil in 1995

In August and September of 1995 the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) was deployed to Brazil as part of the NASA Smoke Cloud Aerosol and Radiation experiment in Brazil (SCAR-B). AVIRIS measures spectra from 400 to 2500 nm at 10-nm intervals. These spectra are acquired as images with dimensions of 11 by up to 800 km with 20-m spatial resolution. Spectral images measured by AVIRIS are spectrally, radiometrically, and spatially calibrated. During the SCAR-B deployment, AVIRIS measured more than 300 million spectra of regions of Brazil. A portion of these spectra were acquired over areas of actively burning fires. Actively burning fires emit radiance in the AVIRIS spectral range as a function of temperature. This emitted radiance is expressed from the 2500-nm end of the AVIRIS spectrum to shorter wavelengths as a function of intensity and modeled by the Planck function.. The objective of this research and analysis was to use spectroscopic methods to determine the minimum high temperature of the most intense fires measured in the SCAR-B AVIRIS data set. Spectra measured by AVIRIS with hot sources have been previously examined for volcanic lava and fires in Brazil.

Green, Robert O.↗

Development of New Open-Shell Perturbation and Coupled-Cluster Theories Based on Symmetric Spin Orbitals

A new spin orbital basis is employed in the development of efficient open-shell coupled-cluster and perturbation theories that are based on a restricted Hartree-Fock (RHF) reference function. The spin orbital basis differs from the standard one in the spin functions that are associated with the singly occupied spatial orbital. The occupied orbital (in the spin orbital basis) is assigned the delta(+) = 1/square root of 2(alpha+Beta) spin function while the unoccupied orbital is assigned the delta(-) = 1/square root of 2(alpha-Beta) spin function. The doubly occupied and unoccupied orbitals (in the reference function) are assigned the standard alpha and Beta spin functions. The coupled-cluster and perturbation theory wave functions based on this set of "symmetric spin orbitals" exhibit much more symmetry than those based on the standard spin orbital basis. This, together with interacting space arguments, leads to a dramatic reduction in the computational cost for both coupled-cluster and perturbation theory. Additionally, perturbation theory based on "symmetric spin orbitals" obeys Brillouin's theorem provided that spin and spatial excitations are both considered. Other properties of the coupled-cluster and perturbation theory wave functions and models will be discussed.

Lee, Timothy J.↗

Infrared Communications for Small Spacecraft: From a Wireless Bus to Cluster Concepts

Nanosatellites operating singly or in clusters are anticipated for future space science missions. To implement this new communications paradigm, we are approaching cluster communications by first developing an infrared (IR) intra-craft wireless bus capability, following initially the MIL-STD-1553B protocol. Benefits of an IR wireless bus are low mass, size, power, and cost, simplicity of implementation, ease of use, minimum EMI, and efficient and reliable data transfer. Our goals are to maximize the reliable link margin in order to afford greater flexibility in receiver placement, which will ease technology insertion. We have developed a concept demonstration using a high-speed visible-band silicon PIN photodiode and a high-efficiency visible LED operating at a data rate up to 4 Mb/sec. In designing an internal IR wireless bus, we have characterized various candidate materials, emitters, and geometries, assuming a single reflection. Thus, we have measured the bidirectional reflectance distribution function (BRDF) for five different materials characteristic of typical spacecraft structures, which range from nearly Lambertian to highly specular. We have fit our data to empirical BRDF functions and modeled the detected irradiance anywhere in the plane of incidence for a divergent (LED) emitter. We have also determined the angular limits on the link geometry to remain within the required bit error rate by determining the received signal-to-noise ratio (SNR) for minimum values of irradiance received at the detector.

Webb, Suzanne C.↗

A Rapid Aerodynamic Design Procedure Based on Artificial Neural Networks

An aerodynamic design procedure that uses neural networks to model the functional behavior of the objective function in design space has been developed. This method incorporates several improvements to an earlier method that employed a strategy called parameter-based partitioning of the design space in order to reduce the computational costs associated with design optimization. As with the earlier method, the current method uses a sequence of response surfaces to traverse the design space in search of the optimal solution. The new method yields significant reductions in computational costs by using composite response surfaces with better generalization capabilities and by exploiting synergies between the optimization method and the simulation codes used to generate the training data. These reductions in design optimization costs are demonstrated for a turbine airfoil design study where a generic shape is evolved into an optimal airfoil.

Rai, Man Mohan↗

Large Eddy Simulation of Gravitational Effects on Transitional and Turbulent Gas-Jet Diffusion Flames

The basic objective of this work is to assess the influence of gravity on "the compositional and the spatial structures" of transitional and turbulent diffusion flames via large eddy simulation (LES), and direct numerical simulation (DNS). The DNS is conducted for appraisal of the various closures employed in LES, and to study the effect of buoyancy on the small scale flow features. The LES is based on our "filtered mass density function"' (FMDF) model. The novelty of the methodology is that it allows for reliable simulations with inclusion of "realistic physics." It also allows for detailed analysis of the unsteady large scale flow evolution and compositional flame structure which is not usually possible via Reynolds averaged simulations.

Givi, Peyman↗

Prediction of Aerodynamic Coefficients using Neural Networks for Sparse Data

Basic aerodynamic coefficients are modeled as functions of angles of attack and sideslip with vehicle lateral symmetry and compressibility effects. Most of the aerodynamic parameters can be well-fitted using polynomial functions. In this paper a fast, reliable way of predicting aerodynamic coefficients is produced using a neural network. The training data for the neural network is derived from wind tunnel test and numerical simulations. The coefficients of lift, drag, pitching moment are expressed as a function of alpha (angle of attack) and Mach number. The results produced from preliminary neural network analysis are very good.

Rajkumar, T.↗

A Systems Approach to the Solid Lubrication of Foil Air Bearings for Oil-Free Turbomachinery

Foil air bearings are self-acting hydrodynamic bearings which rely upon solid lubricants to reduce friction and minimize wear during sliding which occurs at start-up and shut-down when surface speeds are too low to allow the formation of a hydrodynamic air film. This solid lubrication is typically accomplished by coating the non-moving foil surface with a thin, soft polymeric film. The following paper introduces a systems approach in which the solid lubrication is provided by a combination of self lubricating shaft coatings coupled with various wear resistant and lubricating foil coatings. The use of multiple materials, each providing different functions is modeled after oil-lubricated hydrodynamic sleeve bearing technology which utilizes various coatings and surface treatments in conjunction with oil lubricants to achieve optimum performance. In this study, room temperature load capacity tests are performed on journal foil air bearings operating at 14,000 rpm. Different shaft and foil coating technologies such as plasma sprayed composites, ceramic, polymer and inorganic lubricant coatings are evaluated as foil bearing lubricants. The results indicate that bearing performance is improved through the individual use of the lubricants and treatments tested. Further, combining several solid lubricants together yielded synergistically better results than any material alone.

DellaCorte, Christopher↗

Training Data Requirement for a Neural Network to Predict Aerodynamic Coefficients

Basic aerodynamic coefficients are modeled as functions of angle of attack, speed brake deflection angle, Mach number, and side slip angle. Most of the aerodynamic parameters can be well-fitted using polynomial functions. We previously demonstrated that a neural network is a fast, reliable way of predicting aerodynamic coefficients. We encountered few under fitted and/or over fitted results during prediction. The training data for the neural network are derived from wind tunnel test measurements and numerical simulations. The basic questions that arise are: how many training data points are required to produce an efficient neural network prediction, and which type of transfer functions should be used between the input-hidden layer and hidden-output layer. In this paper, a comparative study of the efficiency of neural network prediction based on different transfer functions and training dataset sizes is presented. The results of the neural network prediction reflect the sensitivity of the architecture, transfer functions, and training dataset size.

Korsmeyer, David↗

Low-Energy Study of Gamma-Ray Bursts Having Spectral Line Features

Gamma-ray bursts (GRBs) are energetic, short-duration emissions of gamma-rays. The Burst and Transient Source Experiment (BATSE) that was onboard NASA s Compton Gamma-Ray Observatory has done much to advance our understanding of GRBs. Perhaps foremost is to establish that GRBs originate from astronomical sources that exist well beyond our galaxy. Another area in which BATSE has been instrumental is to provide high-resolution data that can be used in spectral studies. Before BATSE, there were many reports of GRB spectra containing what appeared to be spectral absorption lines, whereas Briggs, after an extensive computer search of 117 bright BATSE GRBs, reported finding only one case that might be an absorption line and ten cases that might be emission lines. None of the eleven BATSE cases were definitively identified as spectral lines, and Briggs indicated reasons as to why the pre-BATSE reports should not be taken as conclusive. It remains an open question as to what these spectral-like features are, or if they are even real. The purpose of this work is, for the subset of the eleven BATSE GRBs for which low-energy data are available from two BATSE's Spectroscopy Detectors (SDs), to include these data in the spectral analysis. Such a study will provide additional constraints on the model spectral functions to better ascertain the reality of the line features. The spectral analysis program used was RMFIT. Of the six GRBs that met the selection criteria, the analysis was performed on only three of them due to a lack of time.

Pangia, Michael J.↗

Characteristics and Global Impact of Aerosols from Southern Africa and Eastern Asia

Supported mainly by the NASA GACP and ACMAP, we have made significant progress in the global modeling of tropospheric aerosols and their precursors in the past few years, especially in the development of the GOCART model, simulation of anthropogenic and natural aerosols, data analysis of field observations and satellite retrievals, assessment of global and regional budgets, estimate of aerosol direct radiative forcing, and aerosol forecasting and data analysis for the ACE-Asia field experiment. Our results and findings are summarized in Chin et al. Model calculated multiple-year optical thickness for individual and total aerosols are at internet. These results have been frequently used by other groups, for example, to impose initial conditions for regional models, provide dust source functions for other global models, supply aerosol fields for chemistry and climate models, help data group interpret their measurements, select monitoring sites for ground observation network, and assist satellite retrievals.

Chin, Mian↗

Accuracy of Pressure Sensitive Paint

Uncertainty in pressure sensitive paint (PSP) measurement is investigated from a standpoint of system modeling. A functional relation between the imaging system output and luminescent emission from PSP is obtained based on studies of radiative energy transports in PSP and photodetector response to luminescence. This relation provides insights into physical origins of various elemental error sources and allows estimate of the total PSP measurement uncertainty contributed by the elemental errors. The elemental errors and their sensitivity coefficients in the error propagation equation are evaluated. Useful formulas are given for the minimum pressure uncertainty that PSP can possibly achieve and the upper bounds of the elemental errors to meet required pressure accuracy. An instructive example of a Joukowsky airfoil in subsonic flows is given to illustrate uncertainty estimates in PSP measurements.

Liu, Tianshu↗

SODA: Smart Objects, Dumb Archives

We present the Smart Object, Dumb Archive (SODA) model for digital libraries (DLs). The SODA model transfers functionality traditionally associated with archives to the archived objects themselves. We are exploiting this shift of responsibility to facilitate other DL goals, such as interoperability, object intelligence and mobility, and heterogeneity. Objects in a SODA DL negotiate presentation of content and handle their own terms and conditions. In this paper we present implementations of our smart objects, buckets, and our dumb archive (DA). We discuss the status of buckets and DA and how they are used in a variety of DL projects.

Nelson, Michael L.↗

Controls Considerations for Turbine Active Clearance Control

This presentation discusses active control of turbine tip clearance from a control systems perspective. It is a subset of charts that were presented at the 2003 meeting of the International Society of Air Breathing Engines which was held August 31 through September 5 in Cleveland, Ohio. The associated reference paper is cited at the end of the presentation. The presentation describes active tip clearance control research being conducted by NASA to improve turbine engine systems. The target application for this effort is commercial aircraft engines. However, it is believed that the technologies developed as part of this research will benefit a broad spectrum of current and future turbomachinery. The first part of the presentation discusses the concept of tip clearance, problems associated with it, and the benefits of controlling it. It lays out a framework for implementing tip clearance controls that enables the implementation to progress from purely analytical to hardware-in-the-loop to fully experimental. And it briefly discusses how the technologies developed will be married to the previously described ACC Test Rig for hardware-in-the-loop demonstrations. The final portion of the presentation, describes one of the key technologies in some detail by presenting equations and results for a functional dynamic model of the tip clearance phenomena. As shown, the model exhibits many of the clearance dynamics found in commercial gas turbine engines. However, initial attempts to validate the model identified limitations that are being addressed to make the model more realistic.

Melcher, Kevin J.↗

Molecular evidence for a terrestrial origin of snakes

Biologists have debated the origin of snakes since the nineteenth century. One hypothesis suggests that snakes are most closely related to terrestrial lizards, and reduced their limbs on land. An alternative hypothesis proposes that snakes are most closely related to Cretaceous marine lizards, such as mosasaurs, and reduced their limbs in water. A presumed close relationship between living monitor lizards, believed to be close relatives of the extinct mosasaurs, and snakes has bolstered the marine origin hypothesis. Here, we show that DNA sequence evidence does not support a close relationship between snakes and monitor lizards, and thus supports a terrestrial origin of snakes.

Environment↗

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗

Testing for Software Safety

This research focuses on testing whether or not the hazardous conditions identified by design-level fault tree analysis will occur in the target implementation. Part 1: Integrate fault tree models into functional specifications so as to identify testable interactions between intended behaviors and hazardous conditions. Part 2: Develop a test generator that produces not only functional tests but also safety tests for a target implementation in a cost-effective way. Part 3: Develop a testing environment for executing generated functional and safety tests and evaluating test results against expected behaviors or hazardous conditions. It includes a test harness as well as an environment simulation of external events and conditions.

Chen, Ken↗