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At least 271 records · Page 15

A study of parameter identification

A set of definitions for deterministic parameter identification ability were proposed. Deterministic parameter identificability properties are presented based on four system characteristics: direct parameter recoverability, properties of the system transfer function, properties of output distinguishability, and uniqueness properties of a quadratic cost functional. Stochastic parameter identifiability was defined in terms of the existence of an estimation sequence for the unknown parameters which is consistent in probability. Stochastic parameter identifiability properties are presented based on the following characteristics: convergence properties of the maximum likelihood estimate, properties of the joint probability density functions of the observations, and properties of the information matrix.

Herget, C. J.↗

Relationship between sea ice freeboard and draft in the Arctic Basin, and implications for ice thickness monitoring

This study confirms the finding of Comiso et al. (1991) that the probability density function (pdf) of the ice freeboard in the Arctic Ocean can be converted to a pdf of ice draft by applying a simple coordinate factor. The coordinate factor, R, which is the ratio of mean draft to mean freeboard pdf is related to the mean material (ice plus snow) density, rho(m), and the near-surface water density rho(w) by the relationship R = rho(m)/(rho(w) - rho(m)). The measured value of R was applied to each of six 50-km sections north of Greenland of a joint airborne laser and submarine sonar profile obtained along nearly coincident tracks from the Arctic Basin north of Greenland and was found to be consistent over all sections tested, despite differences in the ice regime. This indicates that a single value of R might be used for measurements done in this season of the year. The mean value R from all six sections was found to be 7.89.

Wadhams, P.↗

A Simple Stochastic Model for Generating Broken Cloud Optical Depth and Top Height Fields

A simple and fast algorithm for generating two correlated stochastic twodimensional (2D) cloud fields is described. The algorithm is illustrated with two broken cumulus cloud fields: cloud optical depth and cloud top height retrieved from Moderate Resolution Imaging Spectrometer (MODIS). Only two 2D fields are required as an input. The algorithm output is statistical realizations of these two fields with approximately the same correlation and joint distribution functions as the original ones. The major assumption of the algorithm is statistical isotropy of the fields. In contrast to fractals and the Fourier filtering methods frequently used for stochastic cloud modeling, the proposed method is based on spectral models of homogeneous random fields. For keeping the same probability density function as the (first) original field, the method of inverse distribution function is used. When the spatial distribution of the first field has been generated, a realization of the correlated second field is simulated using a conditional distribution matrix. This paper is served as a theoretical justification to the publicly available software that has been recently released by the authors and can be freely downloaded from http://i3rc.gsfc.nasa.gov/Public codes clouds.htm. Though 2D rather than full 3D, stochastic realizations of two correlated cloud fields that mimic statistics of given fields have proved to be very useful to study 3D radiative transfer features of broken cumulus clouds for better understanding of shortwave radiation and interpretation of the remote sensing retrievals.

Prigarin, Sergei M.↗

Use of Probability Distribution Functions for Discriminating Between Cloud and Aerosol in Lidar Backscatter Data

In this paper we describe the algorithm hat will be used during the upcoming Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission for discriminating between clouds and aerosols detected in two wavelength backscatter lidar profiles. We first analyze single-test and multiple-test classification approaches based on one-dimensional and multiple-dimensional probability density functions (PDFs) in the context of a two-class feature identification scheme. From these studies we derive an operational algorithm based on a set of 3-dimensional probability distribution functions characteristic of clouds and aerosols. A dataset acquired by the Cloud Physics Lidar (CPL) is used to test the algorithm. Comparisons are conducted between the CALIPSO algorithm results and the CPL data product. The results obtained show generally good agreement between the two methods. However, of a total of 228,264 layers analyzed, approximately 5.7% are classified as different types by the CALIPSO and CPL algorithm. This disparity is shown to be due largely to the misclassification of clouds as aerosols by the CPL algorithm. The use of 3-dimensional PDFs in the CALIPSO algorithm is found to significantly reduce this type of error. Dust presents a special case. Because the intrinsic scattering properties of dust layers can be very similar to those of clouds, additional algorithm testing was performed using an optically dense layer of Saharan dust measured during the Lidar In-space Technology Experiment (LITE). In general, the method is shown to distinguish reliably between dust layers and clouds. The relatively few erroneous classifications occurred most often in the LITE data, in those regions of the Saharan dust layer where the optical thickness was the highest.

Liu, Zhaoyan↗

Thermodynamics of the Lu2O3 – SiO2 system and comparison to other Rare Earth Silicates

Environmental barrier coatings are necessary to protect SiC based ceramics and composites from water vapor degradation in harsh engine environments. Currently, rare earth (RE) silicates are the most promising systems to protect SiC based ceramics and composites. This protection is largely based on reduced silica activity in these rare earth silicates which results in a lowered reactivity with water vapor. To that end, previous Knudsen effusion mass spectrometry (KEMS) studies have explored RE = Yb, Y silicates to measure the reduced silica activity and subsequent water vapor reactivity. Similarly, this work employs the KEMS technique to measure the SiO(g) vapor pressure in Lu containing RE silicates to calculate the activity of silica within the monosilicate [log(a(SiO2)) = -2351.1*1/T-1.6731] and the disilicate (log(a(SiO2)) = -4884.0*1/T + 2.2208) as a function of temperature. The enthalpies of formation for Lu monosilicate from the oxides and the elements were calculated to be -45±3 kJ/mol at 1550 K and -2831.1±12 kJ/mol at 298 K, respectively. The measured enthalpy of formation and those found in literature are compared to modeled values from density functional theory and those estimated using electronegativity.

Knudesen Effusion Mass Spectrometry↗

Reward and uncertainty in exploration programs

A set of variables which are crucial to the economic outcome of petroleum exploration are discussed. These are treated as random variables; the values they assume indicate the number of successes that occur in a drilling program and determine, for a particular discovery, the unit production cost and net economic return if that reservoir is developed. In specifying the joint probability law for those variables, extreme and probably unrealistic assumptions are made. In particular, the different random variables are assumed to be independently distributed. Using postulated probability functions and specified parameters, values are generated for selected random variables, such as reservoir size. From this set of values the economic magnitudes of interest, net return and unit production cost are computed. This constitutes a single trial, and the procedure is repeated many times. The resulting histograms approximate the probability density functions of the variables which describe the economic outcomes of an exploratory drilling program.

Kaufman, G. M.↗

Structure of the star field in the direction of the cluster NGC 6913. 2: Spatial distribution of stars

The space density function for the stars was determined in the Mikly Way field around NGC 6913 in the direction l = 76.9 deg, b = + 0.6 deg (along the local spiral arm toward Cygnus) by means of BV-photometry and spectral classification. O-B3 stars are concentrated at distances of 1 - 2 kpc, the density shows maximum at a distance of 1.6 kpc. There are also concentrations of O-B3 stars at distances of 1.9 and 2.5 kpc. The density for classes AV - FV shows maximum between 400 and 500 pc.

Kolesnik, L. N.↗

Modeling of turbulent supersonic H2-air combustion with a multivariate beta PDF

Recent calculations of turbulent supersonic reacting shear flows using an assumed multivariate beta PDF (probability density function) resulted in reduced production rates and a delay in the onset of combustion. This result is not consistent with available measurements. The present research explores two possible reasons for this behavior: use of PDF's that do not yield Favre averaged quantities, and the gradient diffusion assumption. A new multivariate beta PDF involving species densities is introduced which makes it possible to compute Favre averaged mass fractions. However, using this PDF did not improve comparisons with experiment. A countergradient diffusion model is then introduced. Preliminary calculations suggest this to be the cause of the discrepancy.

Baurle, R. A.↗

Theory of dense hydrogen

Equations of state for molecular and metallic hydrogen are calculated in an accurate and comparable manner by using the density-functional method applied to static lattices. By isolating the electronic energies in this way, attention can be drawn to the relative importance of the protonic degrees of freedom. From the equation-of-state results it can be concluded that a remnant molecular pairing is preferred in a band-overlap metallic state, complete dissociation occurring only at very high densities. An accurate determination of the pressure needed to achieve complete dissociation is shown to require a self-consistent treatment of electron and proton degrees of freedom.

Chakravarty, S.↗

The distribution of hot spots

Statistical analyses are compared for two published hot spot data sets, one minimal set of 42 and another larger set of 117, using three different approaches. First, the earths surface is divided into 16 equal-area fractions and the observed distribution of hot spots among them is analyzed using chi-square tests. Second, cumulative distributions about the principal axes of the hot spot inertia tensor are used to describe hot spot distribution. Finally, a hot spot density function is constructed for each of the two hot spot data sets. The methods all indicate that hot spots have a nonuniform distribution, even when statistical fluctuations are considered. To the first order, hot spots are concentrated on one half of of the earth's surface area; within that portion, the distribution is consistent with a uniform distribution. The observed hot spot densities for neither data set are explained solely by plate speed.

Stefanick, M.↗

Unoccupied electronic resonances of Sc adsorbed on W(001) by k-resolved inverse photoemission

Scandium adsorbed on the (001) face of tungsten has been studied using Auger-electron spectroscopy, low-energy electron diffraction, k-resolved inverse photoelectron spectroscopy, work-function measurements, and relativistic-electronic-structure calculations. We find that the work function of W(001) does not decrease monotonically as a function of scandium adsorption but reaches a minimum value of Phi = 3.25 eV at 50% coverage. For a complete monolayer, an order 1 X 1 Sc overlayer is formed. Inverse photoemission in the isochromat mode was used to map the unoccupied energy levels of this overlayer along the bar-Gamma(bar-Mu) symmetry direction of the surface Brillouin zone. Local-density-functional calculations using the muffin-tin orbital method were performed for a 1 X 1 Sc overlayer on W and are compared with the experimental two-dimensional band structure.

Lamouri, A.↗

AutoClass: A Bayesian Approach to Classification

We describe a Bayesian approach to the untutored discovery of classes in a set of cases, sometimes called finite mixture separation or clustering. The main difference between clustering and our approach is that we search for the "best" set of class descriptions rather than grouping the cases themselves. We describe our classes in terms of a probability distribution or density function, and the locally maximal posterior probability valued function parameters. We rate our classifications with an approximate joint probability of the data and functional form, marginalizing over the parameters. Approximation is necessitated by the computational complexity of the joint probability. Thus, we marginalize w.r.t. local maxima in the parameter space. We discuss the rationale behind our approach to classification. We give the mathematical development for the basic mixture model and describe the approximations needed for computational tractability. We instantiate the basic model with the discrete Dirichlet distribution and multivariant Gaussian density likelihoods. Then we show some results for both constructed and actual data.

Stutz, John↗

Going through a quantum phase

Phase measurements on a single-mode radiation field are examined from a system-theoretic viewpoint. Quantum estimation theory is used to establish the primacy of the Susskind-Glogower (SG) phase operator; its phase eigenkets generate the probability operator measure (POM) for maximum likelihood phase estimation. A commuting observables description for the SG-POM on a signal x apparatus state space is derived. It is analogous to the signal-band x image-band formulation for optical heterodyne detection. Because heterodyning realizes the annihilation operator POM, this analogy may help realize the SG-POM. The wave function representation associated with the SG POM is then used to prove the duality between the phase measurement and the number operator measurement, from which a number-phase uncertainty principle is obtained, via Fourier theory, without recourse to linearization. Fourier theory is also employed to establish the principle of number-ket causality, leading to a Paley-Wiener condition that must be satisfied by the phase-measurement probability density function (PDF) for a single-mode field in an arbitrary quantum state. Finally, a two-mode phase measurement is shown to afford phase-conjugate quantum communication at zero error probability with finite average photon number. Application of this construct to interferometric precision measurements is briefly discussed.

Shapiro, Jeffrey H.↗

Computer Code for Nanostructure Simulation

Due to their small size, nanostructures can have stress and thermal gradients that are larger than any macroscopic analogue. These gradients can lead to specific regions that are susceptible to failure via processes such as plastic deformation by dislocation emission, chemical debonding, and interfacial alloying. A program has been developed that rigorously simulates and predicts optoelectronic properties of nanostructures of virtually any geometrical complexity and material composition. It can be used in simulations of energy level structure, wave functions, density of states of spatially configured phonon-coupled electrons, excitons in quantum dots, quantum rings, quantum ring complexes, and more. The code can be used to calculate stress distributions and thermal transport properties for a variety of nanostructures and interfaces, transport and scattering at nanoscale interfaces and surfaces under various stress states, and alloy compositional gradients. The code allows users to perform modeling of charge transport processes through quantum-dot (QD) arrays as functions of inter-dot distance, array order versus disorder, QD orientation, shape, size, and chemical composition for applications in photovoltaics and physical properties of QD-based biochemical sensors. The code can be used to study the hot exciton formation/relation dynamics in arrays of QDs of different shapes and sizes at different temperatures. It also can be used to understand the relation among the deposition parameters and inherent stresses, strain deformation, heat flow, and failure of nanostructures.

Filikhin, Igor↗

A Low-Memory Spectral-Correlation Analyzer for Digital QAM-SRRC Waveforms

Cyclostationary signal processing (CSP) provides the ability to estimate received waveforms' statistical features blindly. Quadrature amplitude modulated (QAM) waveforms, when filtered by the square-root-raised cosine (SRRC) pulse shape function, have cyclic features that CSP can exploit to detect waveform parameters such as symbol rate (SR) and center frequency (CF). The estimation of these SR-CF pairs enables a cognitive radio (CR) to perform spectrum sensing techniques such as spectrum sharing and interference mitigation. Here, we investigate a field-programmable gate array (FPGA) application of a blind symbol rate-center frequency estimator. First, this study provides a background on the theory behind the cyclic spectral density function (CSD), spectral correlation analyzers (SCA), and spectrum sensing. Following this is a discussion on the motivation for CubeSat spectrum sensing. An SCA implementation for low-memory devices, such as FPGA-based CubeSat, is then describes. The paper concludes by reporting the performance characteristics of the newly developed streaming-based SCA.

FPGA↗

Equilibrium wave spectrum and sea state bias in satellite altimetry

For a well-developed sea at equilibrium with a constant wind, the energy-containing range of the wavenumber spectrum for wind-generated gravity waves is approximated by a generalized power law involving the angular spread function and mu, interpreted as a fractal codimension of a small surface patch. Dependence of mu on the wave age is estimated, and the 'Phillips constant', beta, along with the low-wavenumber boundary, k0, of the inertial subrange are analyzed on the basis of the wave action and energy conservation principles. The resulting expressions are employed to evaluate various non-Gaussian statistics of a weakly nonlinear sea surface, which determine the sea state bias in satellite altimetry. The locally accelerated decay of the spectral density function in a high-wavenumber dissipation subrange is pointed out as an important factor of wave dynamics and the geometrical optics treatment of the sea state bias. The analysis is carried out in the approximation of a unidirectional wave field and confined to the case of a well-developed sea.

Glazman, Roman E.↗