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At least 55 records · Page 3

On estimating gravity anomalies: A comparison of least squares collocation with least squares techniques

The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown to be an application of the well known regression equations which provide the mean and covariance of a random vector (gravity anomalies) given a realization of a correlated random vector (geodetic data). It is also shown that the collocation solution for gravity anomalies is equivalent to the conventional least-squares-Stokes' function solution when the conventional solution utilizes properly weighted zero a priori estimates. The mathematical and physical assumptions underlying the least squares collocation estimator are described, and its numerical properties are compared with the numerical properties of the conventional least squares estimator.

Argentiero, P.↗

On estimating gravity anomalies - A comparison of least squares collocation with conventional least squares techniques

The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown to be an application of the well known regression equations which provide the mean and covariance of a random vector (gravity anomalies) given a realization of a correlated random vector (geodetic data). It is also shown that the collocation solution for gravity anomalies is equivalent to the conventional least-squares-Stokes' function solution when the conventional solution utilizes properly weighted zero a priori estimates. The mathematical and physical assumptions underlying the least squares collocation estimator are described.

Argentiero, P.↗

Parameter estimation technique for boundary value problems by spline collocation method

A parameter-estimation technique for boundary-integral equations of the second kind is developed. The output least-squares identification technique using the spline collocation method is considered. The convergence analysis for the numerical method is discussed. The results are applied to boundary parameter estimations for two-dimensional Laplace and Helmholtz equations.

Kojima, Fumio↗

Analysis of chromatograph systems using orthogonal collocation

Research is generating fundamental engineering design techniques and concepts for the chromatographic separator of a chemical analysis system for an unmanned, Martian roving vehicle. A chromatograph model is developed which incorporates previously neglected transport mechanisms. The numerical technique of orthogonal collocation is studied. To establish the utility of the method, three models of increasing complexity are considered, the latter two being limiting cases of the derived model: (1) a simple, diffusion-convection model; (2) a rate of adsorption limited, inter-intraparticle model; and (3) an inter-intraparticle model with negligible mass transfer resistance.

Woodrow, P. T.↗

Least squares collocation applied to local gravimetric solutions from satellite gravity gradiometry data

An autonomous spaceborne gravity gradiometer mission is being considered as a post Geopotential Research Mission project. The introduction of satellite diometry data to geodesy is expected to improve solid earth gravity models. The possibility of utilizing gradiometer data for the determination of pertinent gravimetric quantities on a local basis is explored. The analytical technique of least squares collocation is investigated for its usefulness in local solutions of this type. It is assumed, in the error analysis, that the vertical gravity gradient component of the gradient tensor is used as the raw data signal from which the corresponding reference gradients are removed to create the centered observations required in the collocation solution. The reference gradients are computed from a high degree and order geopotential model. The solution can be made in terms of mean or point gravity anomalies, height anomalies, or other useful gravimetric quantities depending on the choice of covariance types. Selected for this study were 30 x 30 foot mean gravity and height anomalies. Existing software and new software are utilized to implement the collocation technique. It was determined that satellite gradiometry data at an altitude of 200 km can be used successfully for the determination of 30 x 30 foot mean gravity anomalies to an accuracy of 9.2 mgal from this algorithm. It is shown that the resulting accuracy estimates are sensitive to gravity model coefficient uncertainties, data reduction assumptions and satellite mission parameters.

Robbins, J. W.↗

An improved gravity model for Mars: Goddard Mars Model-1 (GMM-1)

Doppler tracking data of three orbiting spacecraft have been reanalyzed to develop a new gravitational field model for the planet Mars, GMM-1 (Goddard Mars Model-1). This model employs nearly all available data, consisting of approximately 1100 days of S-bank tracking data collected by NASA's Deep Space Network from the Mariner 9, and Viking 1 and Viking 2 spacecraft, in seven different orbits, between 1971 and 1979. GMM-1 is complete to spherical harmonic degree and order 50, which corresponds to a half-wavelength spatial resolution of 200-300 km where the data permit. GMM-1 represents satellite orbits with considerably better accuracy than previous Mars gravity models and shows greater resolution of identifiable geological structures. The notable improvement in GMM-1 over previous models is a consequence of several factors: improved computational capabilities, the use of optimum weighting and least-squares collocation solution techniques which stabilized the behavior of the solution at high degree and order, and the use of longer satellite arcs than employed in previous solutions that were made possible by improved force and measurement models. The inclusion of X-band tracking data from the 379-km altitude, near-polar orbiting Mars Observer spacecraft should provide a significant improvement over GMM-1, particularly at high latitudes where current data poorly resolves the gravitational signature of the planet.

Smith, D. E.↗

An improved gravity model for Mars: Goddard Mars Model 1

Doppler tracking data of three orbiting spacecraft have been reanalyzed to develop a new gravitational field model for the planet Mars, Goddard Mars Model 1 (GMM-1). This model employs nearly all available data, consisting of approximately 1100 days of S band tracking data collected by NASA's Deep Space Network from the Mariner 9 and Viking 1 and Viking 2 spacecraft, in seven different orbits, between 1971 and 1979. GMM-1 is complete to spherical harmonic degree and order 50, which corresponds to a half-wavelength spatial resolution of 200-300 km where the data permit. GMM-1 represents satellite orbits with considerably better accuracy than previous Mars gravity models and shows greater resolution of identifiable geological structures. The notable improvement in GMM-1 over previous models is a consequence of several factors: improved computational capabilities, the use of otpimum weighting and least squares collocation solution techniques which stabilized the behavior of the solution at high degree and order, and the use of longer satellite arcs than employed in previous solutions that were made possible by improved force and measurement models. The inclusion of X band tracking data from the 379-km altitude, nnear-polar orbiting Mars Observer spacecraft should provide a significant improvement over GMM-1, particularly at high latitudes where current data poorly resolve the gravitational signature of the planet.

Smith, D. E.↗

Radiation Transport in Random Media With Large Fluctuations

Strongly heterogeneous media arise in several applications that include radiation shields, nuclear fuel, BWR moderators, clouds, planetary and stellar atmospheres, turbulent gases and plasmas. Neutral and charged particle transport computations in such media have relied heavily on formulating transport equations with spatially random coefficients (physical data) and developing solution methods to deal with the additional stochastic dimensions. Attempts at developing approximate closures that yield only low order statistical information (e.g., mean and variance of the flux) have proved to be highly restrictive under real physics conditions or rely on techniques that require fluctuation amplitudes to be small for robustness. Recently, stochastic spectral methods such as polynomial chaos and stochastic collocation have been developed for aleatoric uncertainty quantification and sensitivity analysis, and successfully applied in radiation transport work. Advances in UQ techniques have tended to focus on efficiently handling large numbers of uncertain variables but the rigorous stochastic basis of the approach also promotes its use in situations where stochasticity is due to spatial heterogeneity and the associated uncertainty is large. Here we apply these techniques to radiation transport in media with spatially randomly varying cross sections without restriction on fluctuation amplitudes. Specifically, we represent the cross sections as a lognormal spatial random process with specified mean, variance and covariance function and use a Karhunen-Loeve (KL) decomposition to generate cross section realizations that are strictly positive. Woodcock Monte Carlo (WMC) is then used to simulate transport using random sampling of cross sections and deterministic sampling based on a stochastic collocation technique. Numerical results for the mean and variance in the scalar flux and leakage currents are obtained for weak and strong random variations. We focus in this work on demonstrating the approach and defer application to specific problems to a future investigation. We have demonstrated that a combination of stochastic spectral representation and Woodcock Monte Carlo simulation allows efficient computation of radiation transport in strongly random media. The use of a lognormal distribution to represent the fluctuations in medium properties facilitates enforcement of strict positivity of cross section realizations, a condition that has challenged standard approaches that assume Gaussian fluctuations. The fact that the lognormal random process is a memoryless nonlinear transformation of a Gaussian process further enables efficient and accurate reconstruction of the random cross section realizations using a Karhunen-Loeve representation of the cross section. Finally, the robustness of this model enables fluctuations of arbitrarily large amplitude to be studied, using both random sampling Monte Carlo and more efficient stochastic collocation techniques. The present work is being extended to allow reconstruction of probability density functions of output variables using polynomial chaos representation, and to accommodate general cross section covariance functions. Also, techniques are being explored to more judiciously select ceiling cross sections to enhance the efficiency of Woodcock Monte Carlo for transport in random media. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Higher modes of the Orr-Sommerfeld problem for boundary layer flows

The discrete spectrum of the Orr-Sommerfeld problem of hydrodynamic stability for boundary layer flows in semi-infinite regions is examined. Related questions concerning the continuous spectrum are also addressed. Emphasis is placed on the stability problem for the Blasius boundary layer profile. A general theoretical result is given which proves that the discrete spectrum of the Orr-Sommerfeld problem for boundary layer profiles (U(y), 0,0) has only a finite number of discrete modes when U(y) has derivatives of all orders. Details are given of a highly accurate numerical technique based on collocation with splines for the calculation of stability characteristics. The technique includes replacement of 'outer' boundary conditions by asymptotic forms based on the proper large parameter in the stability problem. Implementation of the asymptotic boundary conditions is such that there is no need to make apriori distinctions between subcases of the discrete spectrum or between the discrete and continuous spectrums. Typical calculations for the usual Blasius problem are presented.

Lakin, W. D.↗

On the Use of Deep Convective Clouds to Calibrate AVHRR Data

Remote sensing of cloud and radiation properties from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellites requires constant monitoring of the visible sensors. NOAA satellites do not have onboard visible calibration and need to be calibrated vicariously in order to determine the calibration and the degradation rate. Deep convective clouds are extremely bright and cold, are at the tropopause, have nearly a Lambertian reflectance, and provide predictable albedos. The use of deep convective clouds as calibration targets is developed into a calibration technique and applied to NOAA-16 and NOAA-17. The technique computes the relative gain drift over the life-span of the satellite. This technique is validated by comparing the gain drifts derived from inter-calibration of coincident AVHRR and Moderate-Resolution Imaging Spectroradiometer (MODIS) radiances. A ray-matched technique, which uses collocated, coincident, and co-angled pixel satellite radiance pairs is used to intercalibrate MODIS and AVHRR. The deep convective cloud calibration technique was found to be independent of solar zenith angle, by using well calibrated Visible Infrared Scanner (VIRS) radiances onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, which precesses through all solar zenith angles in 23 days.

Doelling, David R.↗

Application of implicit numerical techniques to the solution of the three-dimensional diffusion equation

Implicit techniques for calculating three-dimensional, time-dependent heat diffusion in a cube are tested with emphasis on storage efficiency, accuracy, and speed of calculation. For this purpose, a tensor product technique with both Chebyshev collocation and finite differences and a generalized conjugate gradient technique with finite differences are used in conjunction with Crank-Nicolson discretization. An Euler explicit finite difference calculation is performed for use as a benchmark. The implicit techniques are found to be competitive with the Euler explicit method in terms of storage efficiency and speed of calculation and offer advantages both in accuracy and stability. Mesh stretching in the finite difference calculations is shown to markedly improve the accuracy of the solution.

Peltier, Leonard Joel↗

A new aerodynamic integral equation based on an acoustic formula in the time domain

An aerodynamic integral equation for bodies moving at transonic and supersonic speeds is presented. Based on a time-dependent acoustic formula for calculating the noise emanating from the outer portion of a propeller blade travelling at high speed (the Ffowcs Williams-Hawking formulation), the loading terms and a conventional thickness source terms are retained. Two surface and three line integrals are employed to solve an equation for the loading noise. The near-field term is regularized using the collapsing sphere approach to obtain semiconvergence on the blade surface. A singular integral equation is thereby derived for the unknown surface pressure, and is amenable to numerical solutions using Galerkin or collocation methods. The technique is useful for studying the nonuniform inflow to the propeller.

Farassat, F.↗

Evaluation of convergence behavior of metamodeling techniques for bridging scales in multi-scale multimaterial simulation

The effectiveness of several metamodeling techniques, viz. the Polynomial Stochastic Collocation method, Adaptive Stochastic Collocation method, a Radial Basis Function Neural Network, a Kriging Method and a Dynamic Kriging Method is evaluated. This is done with the express purpose of using metamodels to bridge scales between micro- and macro-scale models in a multi-scale multimaterial simulation. The rate of convergence of the error when used to reconstruct hypersurfaces of known functions is studied. For sufficiently large number of training points, Stochastic Collocation methods generally converge faster than the other metamodeling techniques, while the DKG method converges faster when the number of input points is less than 100 in a two-dimensional parameter space. Because the input points correspond to computationally expensive micro/meso-scale computations, the DKG is favored for bridging scales in a multi-scale solver.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Wet-radome attenuation in ARM cloud radars and its utilization in radar calibration using disdrometer measurements

Abstract. A relative calibration technique has been developed for the US Department of Energy's (DOE's) Atmospheric Radiation Measurement (ARM) user facility Ka-band ARM Zenith Radars (KAZRs). This method uses the signal attenuation caused by water on the radome to estimate reflectivity factor (Ze) offsets. The wet-radome attenuation (WRA) is assumed to follow a log-linear relationship with rainfall rate during light and moderate rain, as measured by a collocated surface disdrometer. The technique has an uncertainty of approximately 3 dB, due to factors such as disdrometer measurement error, rain variability between radar and disdrometer sample volumes, and the fitting function's uncertainty for the WRA behavior. A practical advantage of this WRA-based approach to shorter-wavelength radar monitoring is that, while it requires a reference disdrometer, it proves feasible for a wider range of collocated disdrometer measurements compared to traditional direct disdrometer comparison at the onset of light rain. This technique thus offers a cost-effective monitoring tool for remote or long-term radar deployments. This calibration technique was applied during the ARM Tracking Aerosol Convection Interactions Experiment (TRACER) from October 2021 through September 2022. The estimated Ze offsets were compared against traditional radar calibration and monitoring methods using available datasets from this campaign. Results show that the WRA-based offsets align closely with mean offsets found between cloud radars and from direct disdrometer comparison near the onset of rain, while also reflecting similar offset and campaign-long trends when compared to collocated, independently calibrated radar wind profilers. Nevertheless, overall, the KAZR Ze offsets estimated during TRACER remained stable at approximately 2 dB lower than the disdrometer estimates from the campaign start until the end of June 2022; afterward, the offsets increased to around 7 dB by the campaign's end. This increase is linked to a drop of about 1 dB in transmitter power toward the end of the project.

54 ENVIRONMENTAL SCIENCES↗

Using Sounder Data to Improve Cirrus Cloud Height Estimation from Satellite Imagers

Modern polar-orbiting meteorological satellites provide both imaging and sounding observations simultaneously. Most imagers, however, do not have H2O and CO2 absorption bands and therefore struggle to accurately estimate the height of optically thin cirrus clouds. Sounders provide these needed observations, but at a spatial resolution that is too coarse to resolve many important cloud structures. This paper presents a technique to merge sounder and imager observations with the goal of maintaining the details offered by the imager’s high spatial resolution and the accuracy offered by the sounder’s spectral information. The technique involves deriving cloud temperatures from the sounder observations, interpolating the sounder temperatures to the imager pixels, and using the sounder temperatures as an additional constraint in the imager cloud height optimal estimation approach. This technique is demonstrated using collocated VIIRS and Cross-track Infrared Sounder (CrIS) observations with the impact of the sounder observations validated using coincident CALIPSO/CALIOP cloud heights These comparisons show significant improvement in the cloud heights for optically thin cirrus. The technique should be generally applicable to other imager/sounder pairs.

Sounder Data↗

Preconditioning for first-order spectral discretization

Efficient solution of the equations from spectral discretizations is essential if the high-order accuracy of these methods is to be realized. Direct solution of these equations is rarely feasible, thus iterative techniques are required. A preconditioning scheme for first-order Chebyshev collocation operators is proposed herein, in which the central finite difference mesh is finer than the collocation mesh. Details of the proper techniques for transferring information between the meshes are given here, and the scheme is analyzed by examination of the eigenvalue spectra of the preconditioned operators. The effect of artificial viscosity required in the inversion of the finite difference operator is examined. A second preconditioning scheme, involving a high-order upwind finite difference operator of the van Leer type is also analyzed to provide a comparison with the present scheme. Finally, the performance of the present scheme is verified by application to several test problems.

Streett, C. L.↗

Measurements of DSD Second Moment Based on Laser Extinction

Using a technique recently developed for estimating the density of surface dust dispersed during a rocket landing, measuring the extinction of a laser passing through rain (or dust in the rocket case) yields an estimate of the 2nd moment of the particle cloud, and rainfall drop size distribution (DSD) in the terrestrial meteorological case. With the exception of disdrometers, instruments that measure rainfall make in direct measurements of the DSD. Most common of these instruments are the rainfall rate gauge measuring the 1 1/3 th moment, (when using a D(exp 2/3) dependency on terminal velocity). Instruments that scatter microwaves off of hydrometeors, such as the WSR-880, vertical wind profilers, and microwave disdrometers, measure the 6th moment of the DSD. By projecting a laser onto a target, changes in brightness of the laser spot against the target background during rain, yield a measurement of the DSD 2nd moment, using the Beer-Lambert law. In order to detect the laser attenuation within the 8-bit resolution of most camera image arrays, a minimum path length is required, depending on the intensity of the rainfall rate. For moderate to heavy rainfall, a laser path length of 100 m is sufficient to measure variations in optical extinction using a digital camera. A photo-detector could replace the camera, for automated installations. In order to spatially correlate the 2nd moment measurements to a collocated disdrometer or tipping bucket, the laser's beam path can be reflected multiple times using mirrors to restrict the spatial extent of the measurement. In cases where a disdrometer is not available, complete DSD estimates can be produced by parametric fitting of DSD model to the 2nd moment data in conjunction with tipping bucket data. In cases where a disdrometer is collocated, the laser extinction technique may yield a significant improvement to insitu disdrometer validation and calibration strategies

Lane, John E.↗