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At least 847 records · Page 47

On the Response of the Special Sensor Microwave/Imager to the Marine Environment: Implications for Atmospheric Parameter Retrievals

A reasonably rigorous basis for understanding and extracting the physical information content of Special Sensor Microwave/Imager (SSM/I) satellite images of the marine environment is provided. To this end, a comprehensive algebraic parameterization is developed for the response of the SSM/I to a set of nine atmospheric and ocean surface parameters. The brightness temperature model includes a closed-form approximation to microwave radiative transfer in a non-scattering atmosphere and fitted models for surface emission and scattering based on geometric optics calculations for the roughened sea surface. The combined model is empirically tuned using suitable sets of SSM/I data and coincident surface observations. The brightness temperature model is then used to examine the sensitivity of the SSM/I to realistic variations in the scene being observed and to evaluate the theoretical maximum precision of global SSM/I retrievals of integrated water vapor, integrated cloud liquid water, and surface wind speed. A general minimum-variance method for optimally retrieving geophysical parameters from multichannel brightness temperature measurements is outlined, and several global statistical constraints of the type required by this method are computed. Finally, a unified set of efficient statistical and semi-physical algorithms is presented for obtaining fields of surface wind speed, integrated water vapor, cloud liquid water, and precipitation from SSM/I brightness temperature data. Features include: a semi-physical method for retrieving integrated cloud liquid water at 15 km resolution and with rms errors as small as approximately 0.02 kg/sq m; a 3-channel statistical algorithm for integrated water vapor which was constructed so as to have improved linear response to water vapor and reduced sensitivity to precipitation; and two complementary indices of precipitation activity (based on 37 GHz attenuation and 85 GHz scattering, respectively), each of which are relatively insensitive to variations in other environmental parameters.

Petty, Grant W.↗

Towards Aerodynamic Shape Optimization Using an Immersed Boundary Overset Grid Method

Traditional Reynolds-averaged Navier-Stokes grid methods applied to aerodynamic shapeoptimization can struggle with the deformation of surface and volume grids at componentintersections, such as at wing-fuselage junctions. To overcome this, we propose an approachwhich utilizes curvilinear overset grids for the discretization of the domain, with the presenceof the body modeled using an immersed boundary method. This approach handles complexgeometries without the need for their explicit integration into the grid. The goal of this approachis to reduce grid generation time and allow for greater geometric freedom for component-basedaerodynamic shape optimization. Two different methods are presented: a source-term-basedand a ghost-node-based immersed boundary method. Flow analyses and adjoint solutionsobtained using the proposed methods show promising comparisons with standard body-fittedgrid methods. Preliminary aerodynamic shape optimization results obtained using one of theimmersed boundary methods are also presented.

TTT↗

Climatology tuned reflectivity-rain rate relations

The climatologically-tuned relationships between reflectivity, Z, and rain rate, R, are examined. A method is presented which selects the Z-R relation that assures that the values of R are weighted according to their climatological frequency of occurrence. The method is an extension of the approach suggested by Calheiros and Zawadski (1987). Also, consideration is given to the method of optimizing Z-R relations by matching hourly gage and radar-deduced rain amounts proposed by Smith et al. (1975). These two methods are described and applied to data from Germany and from the GARP Atlantic Tropical Experiment. The differences in the Z-R relations obtained using the two approaches are discussed.

Short, David A.↗

Traveling-Wave Tube Cold-Test Circuit Optimization Using CST MICROWAVE STUDIO

The internal optimizer of CST MICROWAVE STUDIO (MWS) was used along with an application-specific Visual Basic for Applications (VBA) script to develop a method to optimize traveling-wave tube (TWT) cold-test circuit performance. The optimization procedure allows simultaneous optimization of circuit specifications including on-axis interaction impedance, bandwidth or geometric limitations. The application of Microwave Studio to TWT cold-test circuit optimization is described.

Chevalier, Christine T.↗

New Technology-Large-Area Three- Dimensional Surface Profiling Using Only Focused Air-Coupled Ultrasound-Given 1999 R&D 100 Award

Surface topography, which significantly affects the performance of many industrial components, is normally measured with diamond-tip profilometry over small areas or with optical scattering methods over larger areas. To develop air-coupled surface profilometry, the NASA Glenn Research Center at Lewis Field initiated a Space Act Agreement with Sonix, Inc., through two Glenn programs, the Advanced High Temperature Engine Materials Program (HITEMP) and COMMTECH. The work resulted in quantitative surface topography profiles obtained using only high-frequency, focused ultrasonic pulses in air. The method is nondestructive, noninvasive, and noncontact, and it does not require light-reflective surfaces. Air surface profiling may be desirable when diamond-tip or laserbased methods are impractical, such as over large areas, when a significant depth range is required, or for curved surfaces. When the configuration is optimized, the method is reasonably rapid and all the quantitative analysis facilities are online, including two- and three-dimensional visualization, extreme value filtering (for faulty data), and leveling.

Roth, Don J.↗

Resonant power processors. II - Methods of control

The nature of resonant converter control is discussed. Employing the state-portrait, different control methods for series resonant converter are identified and their performance evaluated based on their stability, response to control and load changes and range of operation. A new control method, optimal-trajectory control, is proposed which, by utilizing the state trajectories as control laws, continuously monitors the energy level of the resonant tank. The method is shown to have superior control properties especially under transient operation.

Oruganti, R.↗

Optimization and analysis of large chemical kinetic mechanisms using the solution mapping method - Combustion of methane

A method of systematic optimization, solution mapping, as applied to a large-scale dynamic model is presented. The basis of the technique is parameterization of model responses in terms of model parameters by simple algebraic expressions. These expressions are obtained by computer experiments arranged in a factorial design. The developed parameterized responses are then used in a joint multiparameter multidata-set optimization. A brief review of the mathematical background of the technique is given. The concept of active parameters is discussed. The technique is applied to determine an optimum set of parameters for a methane combustion mechanism. Five independent responses - comprising ignition delay times, pre-ignition methyl radical concentration profiles, and laminar premixed flame velocities - were optimized with respect to thirteen reaction rate parameters. The numerical predictions of the optimized model are compared to those computed with several recent literature mechanisms. The utility of the solution mapping technique in situations where the optimum is not unique is also demonstrated.

Frenklach, Michael↗

Robust Trajectory Optimization for Guided Powered Descent and Landing

A robust trajectory optimization approach for guidance algorithm gain selection for powered descent and landing is developed. This approach uses a genetic algorithm to determine optimal guidance algorithm parameters while incorporating uncertainty information from linear covariance analysis. The optimal guidance algorithm parameters are determined while accounting for environment, navigation, and vehicle property uncertainty and sensor suite fidelity. As a demonstration of this method, the optimal gains for the fractional polynomial powered descent guidance are found for the braking phase of a robotic lunar landing mission. Scenarios with differing sensor suites and sensor qualities are considered, with objective functions to minimize variability in propellant usage or terminal position. Results show that the optimal guidance algorithm gains for a given trajectory differ based on the sensor suite, and optimal guidance algorithm gains may result in up to 20% performance improvements over the baseline in propellant usage and landed accuracy.

Grace E Calkins↗

Multidisciplinary Aerospace Systems Optimization: Computational AeroSciences (CAS) Project

The report describes a method for performing optimization of a system whose analysis is so expensive that it is impractical to let the optimization code invoke it directly because excessive computational cost and elapsed time might result. In such situation it is imperative to have user control the number of times the analysis is invoked. The reported method achieves that by two techniques in the Design of Experiment category: a uniform dispersal of the trial design points over a n-dimensional hypersphere and a response surface fitting, and the technique of krigging. Analyses of all the trial designs whose number may be set by the user are performed before activation of the optimization code and the results are stored as a data base. That code is then executed and referred to the above data base. Two applications, one of the airborne laser system, and one of an aircraft optimization illustrate the method application.

Kodiyalam, S.↗

Theory and design of interferometric synthetic aperture radars

A derivation of the signal statistics, an optimal estimator of the interferometric phase, and the expression necessary to calculate the height-error budget are presented. These expressions are used to derive methods of optimizing the parameters of the interferometric synthetic aperture radar system (InSAR), and are then employed in a specific design example for a system to perform high-resolution global topographic mapping with a one-year mission lifetime, subject to current technological constraints. A Monte Carlo simulation of this InSAR system is performed to evaluate its performance for realistic topography. The results indicate that this system has the potential to satisfy the stringent accuracy and resolution requirements for geophysical use of global topographic data.

Rodriguez, E.↗

AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement and Transition to MODIS

Study of the environment has historically been done with observations and measurements in relatively few local areas. While some of these have been done over long time spans, most have not. The NOAA/NASA Pathfinder project was initiated to complement these data sets with satellite data that can provide information over larger spatial areas and longer time spans. The AVHRR Polar Pathfinder (APR) program was part of this project. The APR was to supply data from the NOAA AVHRR instruments that was consistently generated in a format usable to a wide range of scientific investigators. A grant was obtained from the NASA Research Announcement 97-MTPE-03 to evaluate the APP products, to provide any enhancements, and to compare with products from the new MODIS instrument. There was about a two year overlap between the projects, and this validation effort had several impacts on the APP products. The APP products are derived from the instruments aboard 4 NOAA satellites, NOAA-7, 9, 11, and 14. Initial validation efforts compared the thermal calibrations of these instruments, and differences are found. Calibration has undergone many revisions and techniques have changed since the satellites were launched. The first calibration methods were optimized for global ocean temperatures, as this was one of the primary and important uses of the AVHRR instruments. As the APP program started, newer methods that provided more accurate temperature retrievals over a wider range of temperatures were being developed. The calibration of a wider range of temperatures were necessary because of the extremely low values in the polar regions. These methods were also designed so that calibrated data was also consistent between all the NOAA satellites. These newer calibration methods were then adopted primarily because of the initial finding of this validation effort.

Fowler, Charles↗

Robust Airfoil Optimization in High Resolution Design Space

The robust airfoil shape optimization is a direct method for drag reduction over a given range of operating conditions and has three advantages: (1) it prevents severe degradation in the off-design performance by using a smart descent direction in each optimization iteration, (2) it uses a large number of B-spline control points as design variables yet the resulting airfoil shape is fairly smooth, and (3) it allows the user to make a trade-off between the level of optimization and the amount of computing time consumed. The robust optimization method is demonstrated by solving a lift-constrained drag minimization problem for a two-dimensional airfoil in viscous flow with a large number of geometric design variables. Our experience with robust optimization indicates that our strategy produces reasonable airfoil shapes that are similar to the original airfoils, but these new shapes provide drag reduction over the specified range of Mach numbers. We have tested this strategy on a number of advanced airfoil models produced by knowledgeable aerodynamic design team members and found that our strategy produces airfoils better or equal to any designs produced by traditional design methods.

Li, Wu↗

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗

Methods of the Galerkin type

Optimal approximations, weighted residuals method, and linear and nonlinear applications of methods of Galerkin type with proof of convergence

Source record↗