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At least 109 records · Page 6

Flutter and Divergence Analysis using the Generalized Aeroelastic Analysis Method

The Generalized Aeroelastic Analysis Method (GAAM) is applied to the analysis of three well-studied checkcases: restrained and unrestrained airfoil models, and a wing model. An eigenvalue iteration procedure is used for converging upon roots of the complex stability matrix. For the airfoil models, exact root loci are given which clearly illustrate the nature of the flutter and divergence instabilities. The singularities involved are enumerated, including an additional pole at the origin for the unrestrained airfoil case and the emergence of an additional pole on the positive real axis at the divergence speed for the restrained airfoil case. Inconsistencies and differences among published aeroelastic root loci and the new, exact results are discussed and resolved. The generalization of a Doublet Lattice Method computer code is described and the code is applied to the calculation of root loci for the wing model for incompressible and for subsonic flow conditions. The error introduced in the reduction of the singular integral equation underlying the unsteady lifting surface theory to a linear algebraic equation is discussed. Acknowledging this inherent error, the solutions of the algebraic equation by GAAM are termed 'exact.' The singularities of the problem are discussed and exponential series approximations used in the evaluation of the kernel function shown to introduce a dense collection of poles and zeroes on the negative real axis. Again, inconsistencies and differences among published aeroelastic root loci and the new 'exact' results are discussed and resolved. In all cases, aeroelastic flutter and divergence speeds and frequencies are in good agreement with published results. The GAAM solution procedure allows complete control over Mach number, velocity, density, and complex frequency. Thus all points on the computed root loci can be matched-point, consistent solutions without recourse to complex mode tracking logic or dataset interpolation, as in the k and p-k solution methods.

Edwards, John W.↗

Time-Distance Analysis of Deep Solar Convection

Recently it was shown by Hanasoge, Duvall, and DeRosa (2010) that the upper limit to convective flows for spherical harmonic degrees l<? is considerably smaller than the flows predicted by the ASH simulations (Miesch et a7. ref) at the depth r/R=0.95 ' The deep-focusing Lime-distance technique used to develop the upper limit was applied to linear acoustic simulations of a solar interior perturbed by convective flows in order to calibrate the technique. This technique has been applied to other depths in the convection zone and the results will be presented. The deep-focusing technique has considerable sensitivity to the flow ' signals at the desired subsurface location ' However, as shown by Birch {ref}, there is remaining much sensitivity to near-surface signals. Modifications to the technique using multiple bounce signals have been examined in a search for a more refined sensitivity, or kernel function. Initial results are encouraging and results will be presented'

Duvall, T. L., Jr.↗

Two-Dimensional Ffowcs Williams/Hawkings Equation Solver

FWH2D is a Fortran 90 computer program that solves a two-dimensional (2D) version of the equation, derived by J. E. Ffowcs Williams and D. L. Hawkings, for sound generated by turbulent flow. FWH2D was developed especially for estimating noise generated by airflows around such approximately 2D airframe components as slats. The user provides input data on fluctuations of pressure, density, and velocity on some surface. These data are combined with information about the geometry of the surface to calculate histories of thickness and loading terms. These histories are fast-Fourier-transformed into the frequency domain. For each frequency of interest and each observer position specified by the user, kernel functions are integrated over the surface by use of the trapezoidal rule to calculate a pressure signal. The resulting frequency-domain signals are inverse-fast-Fourier-transformed back into the time domain. The output of the code consists of the time- and frequency-domain representations of the pressure signals at the observer positions. Because of its approximate nature, FWH2D overpredicts the noise from a finite-length (3D) component. The advantage of FWH2D is that it requires a fraction of the computation time of a 3D Ffowcs Williams/Hawkings solver.

Lockard, David P.↗

Using Machine-Learning Methods and Expert Prediction Probabilities to Forecast Solar Flares

It has long been known that studying connection between solar flares and properties of magnetic field in active regions is very important for understanding the flare physics and developing space weather forecasts. The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) obtains tremendous amounts of magnetic field data products. However the operational NOAA Space Weather Prediction Center (SWPC) forecasts of solar flares still represent prediction probabilities issued by the experts. In this research we investigate the possibilities to enhance the daily operational flare forecasts performed at the SWPC by developing a synergy of the expert predictions and physics-based criteria, and by employing machine-learning methods. Among the physics-based criteria we consider the descriptors of the Polarity Inversion Line (PIL) and Space weather HMI Active Region Patches (SHARP), and derive from them daily characteristics of the entire Sun. We also consider the daily descriptors of the GOES Soft X-Ray (SXR) 1-8 Angstroms flux such as the flare history of the previous days and averaged X-Ray flux. We estimate the effectiveness in separation of flaring and non-flaring cases for each characteristic, as well as for the expert prediction probabilities, and find that some PIL, SHARP and SXR descriptors are as effective as the expert prediction probabilities and should be considered to issue the flare forecast. Finally, we train and test several Machine-Learning classification algorithms (Support Vector Classifiers with various kernel functions, k-Nearest Neighbor Classifier, Random Forest Classifier, and Neural Networks) using the most effective descriptors and expert prediction probabilities, and compare the obtained predictions with the current SWPC forecasts.

Machine-Learning↗

Solar Flare Heating with Turbulent Suppression of Thermal Conduction

During solar flares plasma is typically heated to very high temperatures, and the resulting redistribution of energy via thermal conduction is a primary mechanism transporting energy throughout the flaring solar atmosphere. The thermal flux is usually modeled using Spitzer’s theory, which is based on local Coulomb collisions between the electrons carrying the thermal flux and those in the background. However, often during flares, temperature gradients become sufficiently steep that the collisional mean free path exceeds the temperature gradient scale size, so that thermal conduction becomes inherently non-local. Further, turbulent angular scattering, which is detectable in nonthermal widths of atomic emission lines, can also act to increase the collision frequency and so suppress the heat flux. Recent work by Emslie & Bian (2018) extended Spitzer’s theory of thermal conduction to account for both non-locality and turbulent suppression. We have implemented their theoretical expression for the heat flux (which is a convolution of the Spitzer flux with a kernel function) into the RADYN flare-modeling code and performed a parameter study to understand how the resulting changes in thermal conduction affect flare dynamics and hence the radiation produced. We find that models with reduced heat fluxes predict slower bulk flows, less intense line emission, and longer cooling times. By comparing features of atomic emission lines predicted by the models with Doppler velocities and nonthermal line widths deduced from a particular flare observation, we find that models with suppression factors between 0.3 to 0.5 relative to the Spitzer value best reproduce observed Doppmission lines forming over a wide range of temperatures. Interestingly, the model that best matches observed nonthermal line widths has a kappa-type velocity distribution function.

Joel C. Allred↗

Solar Flare Heating with Turbulent Suppression of Thermal Conduction

During solar flares plasma is typically heated to very high temperatures, and the resulting redistribution of energy via thermal conduction is a primary mechanism transporting energy throughout the flaring solar atmosphere. The thermal flux is usually modeled using Spitzer’s theory, which is based on local Coulomb collisions between the electrons carrying the thermal flux and those in the background. However, often during flares, temperature gradients become sufficiently steep that the collisional mean free path exceeds the temperature gradient scale size, so that thermal conduction becomes inherently non-local. Further, turbulent angular scattering, which is detectable in nonthermal widths of atomic emission lines, can also act to increase the collision frequency and so suppress the heat flux. Recent work by Emslie & Bian (2018) extended Spitzer’s theory of thermal conduction to account for both non-locality and turbulent suppression. We have implemented their theoretical expression for the heat flux (which is a convolution of the Spitzer flux with a kernel function) into the RADYN flare-modeling code and performed a parameter study to understand how the resulting changes in thermal conduction affect flare dynamics and hence the radiation produced. We find that models with reduced heat fluxes predict slower bulk flows, less intense line emission, and longer cooling times. By comparing features of atomic emission lines predicted by the models with Doppler velocities and nonthermal line widths deduced from a particular flare observation, we find that models with suppression factors between 0.3 to 0.5 relative to the Spitzer value best reproduce observed Doppler velocities across emission lines forming over a wide range of temperatures. Interestingly, the model that best matches observed nonthermal line widths has a kappa-type velocity distribution function

Solar flares↗

Multiangle Implementation of Atmospheric Correction (MAIAC):: Radiative Transfer Basis and Look-up Tables - 1

This paper describes a radiative transfer basis of the algorithm MAIAC which performs simultaneous retrievals of atmospheric aerosol and bidirectional surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). The retrievals are based on an accurate semianalytical solution for the top-of-atmosphere reflectance expressed as an explicit function of three parameters of the Ross-Thick Li-Sparse model of surface bidirectional reflectance. This solution depends on certain functions of atmospheric properties and geometry which are precomputed in the look-up table (LUT). This paper further considers correction of the LUT functions for variations of surface pressure/height and of atmospheric water vapor, which is a common task in the operational remote sensing. It introduces a new analytical method for the water vapor correction of the multiple ]scattering path radiance. It also summarizes the few basic principles that provide a high efficiency and accuracy of the LUT ]based radiative transfer for the aerosol/surface retrievals and optimize the size of LUT. For example, the single-scattering path radiance is calculated analytically for a given surface pressure and atmospheric water vapor. The same is true for the direct surface-reflected radiance, which along with the single-scattering path radiance largely defines the angular dependence of measurements. For these calculations, the aerosol phase functions and kernels of the surface bidirectional reflectance model are precalculated at a high angular resolution. The other radiative transfer functions depend rather smoothly on angles because of multiple scattering and can be calculated at coarser angular resolution to reduce the LUT size. At the same time, this resolution should be high enough to use the nearest neighbor geometry angles to avoid costly three ]dimensional interpolation. The pressure correction is implemented via linear interpolation between two LUTs computed for the standard and reduced pressure levels. A linear mixture and a modified linear mixture methods are used to represent different aerosol types in the aerosol/surface retrievals from several base models of the fine and coarse aerosol fractions. In summary, the developed LUT algorithm allows fast high-accuracy simulations of the outgoing radiance with full variability of the atmospheric and surface bidirectional reflectance properties for the aerosol/surface remote sensing.

Lyapustin, Alexei↗

Use of speckle for determining the response characteristics of Doppler imaging radars

An optical model is developed for imaging optical radars such as the SAR on Seasat and the Shuttle Imaging Radar (SIR-B) by analyzing the Doppler shift of individual speckles in the image. The signal received at the spacecraft is treated in terms of a Fresnel-Kirchhoff integration over all backscattered radiation within a Huygen aperture at the earth. Account is taken of the movement of the spacecraft along the orbital path between emission and reception. The individual points are described by integration of the point source amplitude with a Green's function scattering kernel. Doppler data at each point furnishes the coordinates for visual representations. A Rayleigh-Poisson model of the surface scattering characteristics is used with Monte Carlo methods to generate simulations of Doppler radar speckle that compare well with Seasat SAR data SIR-B data.

Tilley, D. G.↗

Radiometric Characterization of IKONOS Multispectral Imagery

A radiometric characterization of Space Imaging's IKONOS 4-m multispectral imagery has been performed by a NASA funded team from the John C. Stennis Space Center (SSC), the University of Arizona Remote Sensing Group (UARSG), and South Dakota State University (SDSU). Both intrinsic radiometry and the effects of Space Imaging processing on radiometry were investigated. Relative radiometry was examined with uniform Antarctic and Saharan sites. Absolute radiometric calibration was performed using reflectance-based vicarious calibration methods on several uniform sites imaged by IKONOS, coincident with ground-based surface and atmospheric measurements. Ground-based data and the IKONOS spectral response function served as input to radiative transfer codes to generate a Top-of-Atmosphere radiance estimate. Calibration coefficients derived from each vicarious calibration were combined to generate an IKONOS radiometric gain coefficient for each multispectral band assuming a linear response over the full dynamic range of the instrument. These calibration coefficients were made available to Space Imaging, which subsequently adopted them by updating its initial set of calibration coefficients. IKONOS imagery procured through the NASA Scientific Data Purchase program is processed with or without a Modulation Transfer Function Compensation kernel. The radiometric effects of this kernel on various scene types was also investigated. All imagery characterized was procured through the NASA Scientific Data Purchase program.

Pagnutti, Mary↗

Dynamical Chaos in the Wisdom-Holman Integrator: Origins and Solutions

We examine the nonlinear stability of the Wisdom-Holman (WH) symplectic mapping applied to the integration of perturbed, highly eccentric (e-0.9) two-body orbits. We find that the method is unstable and introduces artificial chaos into the computed trajectories for this class of problems, unless the step size chosen 1s small enough that PeriaPse is always resolved, in which case the method is generically stable. This 'radial orbit instability' persists even for weakly perturbed systems. Using the Stark problem as a fiducial test case, we investigate the dynamical origin of this instability and argue that the numerical chaos results from the overlap of step-size resonances; interestingly, for the Stark-problem many of these resonances appear to be absolutely stable. We similarly examine the robustness of several alternative integration methods: a time-regularized version of the WH mapping suggested by Mikkola; the potential-splitting (PS) method of Duncan, Levison, Lee; and two original methods incorporating approximations based on Stark motion instead of Keplerian motion. The two fixed point problem and a related, more general problem are used to conduct a comparative test of the various methods for several types of motion. Among the algorithms tested, the time-transformed WH mapping is clearly the most efficient and stable method of integrating eccentric, nearly Keplerian orbits in the absence of close encounters. For test particles subject to both high eccentricities and very close encounters, we find an enhanced version of the PS method-incorporating time regularization, force-center switching, and an improved kernel function-to be both economical and highly versatile. We conclude that Stark-based methods are of marginal utility in N-body type integrations. Additional implications for the symplectic integration of N-body systems are discussed.

Rauch, Kevin P.↗

Virtual Sensors: Using Data Mining Techniques to Efficiently Estimate Remote Sensing Spectra

Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. These instruments are sometimes built in a phased approach, with some measurement capabilities being added in later phases. In other cases, there may not be a planned increase in measurement capability, but technology may mature to the point that it offers new measurement capabilities that were not available before. In still other cases, detailed spectral measurements may be too costly to perform on a large sample. Thus, lower resolution instruments with lower associated cost may be used to take the majority of measurements. Higher resolution instruments, with a higher associated cost may be used to take only a small fraction of the measurements in a given area. Many applied science questions that are relevant to the remote sensing community need to be addressed by analyzing enormous amounts of data that were generated from instruments with disparate measurement capability. This paper addresses this problem by demonstrating methods to produce high accuracy estimates of spectra with an associated measure of uncertainty from data that is perhaps nonlinearly correlated with the spectra. In particular, we demonstrate multi-layer perceptrons (MLPs), Support Vector Machines (SVMs) with Radial Basis Function (RBF) kernels, and SVMs with Mixture Density Mercer Kernels (MDMK). We call this type of an estimator a Virtual Sensor because it predicts, with a measure of uncertainty, unmeasured spectral phenomena.

Srivastava, Ashok N.↗

TADPLOT program, version 2.0: User's guide

The TADPLOT Program, Version 2.0 is described. The TADPLOT program is a software package coordinated by a single, easy-to-use interface, enabling the researcher to access several standard file formats, selectively collect specific subsets of data, and create full-featured publication and viewgraph quality plots. The user-interface was designed to be independent from any file format, yet provide capabilities to accommodate highly specialized data queries. Integrated with an applications software network, data can be assessed, collected, and viewed quickly and easily. Since the commands are data independent, subsequent modifications to the file format will be transparent, while additional file formats can be integrated with minimal impact on the user-interface. The graphical capabilities are independent of the method of data collection; thus, the data specification and subsequent plotting can be modified and upgraded as separate functional components. The graphics kernel selected adheres to the full functional specifications of the CORE standard. Both interface and postprocessing capabilities are fully integrated into TADPLOT.

Hammond, Dana P.↗

The Plasma Environment at Mercury

Mercury is the least explored terrestrial planet, and the one subjected to the highest flux of solar radiation in the heliosphere. Its highly dynamic, miniature magnetosphere contains ions from the exosphere and solar wind, and at times may allow solar wind ions to directly impact the planet's surface. Together these features create a plasma environment that shares many features with, but is nonetheless very different from, that of Earth. The first in situ measurements of plasma ions in the Mercury space environment were made only recently, by the Fast Imaging Plasma Spectrometer (FIPS) during the MESSENGER spacecraft's three flybys of the planet in 2008-2009 as the probe was en route to insertion into orbit about Mercury earlier this year. Here. we present analysis of flyby and early orbital mission data with novel techniques that address the particular challenges inherent in these measurements. First. spacecraft structures and sensor orientation limit the FIPS field of view and allow only partial sampling of velocity distribution functions. We use a software model of FIPS sampling in velocity space to explore these effects and recover bulk parameters under certain assumptions. Second, the low densities found in the Mercury magnetosphere result in a relatively low signal-to-noise ratio for many ions. To address this issue, we apply a kernel density spread function to guide removal of background counts according to a background-signature probability map. We then assign individual counts to particular ion species with a time-of-flight forward model, taking into account energy losses in the carbon foil and other physical behavior of ions within the instrument. Using these methods, we have derived bulk plasma properties and heavy ion composition and evaluated them in the context of the Mercury magnetosphere.

Raines, James M.↗