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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11

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NASA NTRS1993

A numerical technique for the calculation of cloud optical extinction from lidar

A simple numerical algorithm which calculates optical extinction from cloud lidar data is presented. The method assumes a two-component atmosphere consisting of 'clear air' and cloud particulates. 'Clear air' may consist of either molecules only or a mix of molecules and atmospheric aerosols. For certain clouds, the method may be utilized to provide an estimate of the cloud-atmospheric parameter defined as the ratio of the cloud volume backscatter coefficient to the cloud extinction coefficient divided by the atmospheric volume backscatter coefficient at a given altitude. The cloud-atmospheric parameter may be estimated only from cloud data from which the optical thickness may reliably be used as a constraint on the numerical solution. This constraint provides the additional information necessary to obtain the cloud-atmospheric parameter. Conversely, the method may be applied to obtain cloud extinction and optical thickness from lidar cloud soundings if an estimate of the cloud-atmospheric parameter is available.

Alvarez, J. M.↗

NASA NTRS1975

Kalman filter estimation of human pilot-model parameters

The parameters of a human pilot-model transfer function are estimated by applying the extended Kalman filter to the corresponding retarded differential-difference equations in the time domain. Use of computer-generated data indicates that most of the parameters, including the implicit time delay, may be reasonably estimated in this way. When applied to two sets of experimental data obtained from a closed-loop tracking task performed by a human, the Kalman filter generated diverging residuals for one of the measurement types, apparently because of model assumption errors. Application of a modified adaptive technique was found to overcome the divergence and to produce reasonable estimates of most of the parameters.

Schiess, J. R.↗

NASA NTRS2006

Small-Scale Gravity Waves in ER-2 MMS/MTP Wind and Temperature Measurements during CRYSTAL-FACE

Lower stratospheric wind and temperature measurements made from NASA's high-altitude ER-2 research aircraft during the CRYSTAL-FACE campaign in July 2002 were analyzed to retrieve information on small scale gravity waves (GWs) at the aircraft's flight level (typically approximately 20 km altitude). For a given flight segment, the S-transform (a Gaussian wavelet transform) was used to search for and identify small horizontal scale GW events, and to estimate their apparent horizontal wavelengths. The horizontal propagation directions of the events were determined using the Stokes parameter method combined with the cross S-transform analysis. The vertical temperature gradient was used to determine the vertical wavelengths of the events. GW momentum fluxes were calculated from the cross S-transform. Other wave parameters such as intrinsic frequencies were calculated using the GW dispersion relation. More than 100GW events were identified. They were generally high frequency waves with vertical wavelength of approximately 5 km and horizontal wavelength generally shorter than 20 km. Their intrinsic propagation directions were predominantly toward the east, whereas their ground-based propagation directions were primarily toward the west. Among the events, approximately 20% of them had very short horizontal wavelength, very high intrinsic frequency, and relatively small momentum fluxes, and thus they were likely trapped in the lower stratosphere. Using the estimated GW parameters and the background winds and stabilities from the NCAR/NCEP reanalysis data, we were able to trace the sources of the events using a simple reverse ray-tracing. More than 70% of the events were traced back to convective sources in the troposphere, and the sources were generally located upstream of the locations of the events observed at the aircraft level. Finally, a probability density function of the reversible cooling rate due to GWs was obtained in this study, which may be useful for cirrus cloud models.

Wang, L.↗

NASA NTRS1976

The use of LANDSAT-1 imagery in mapping and managing soil and range resources in the Sand Hills region of Nebraska

The author has identified the following significant results. Evaluation of ERTS-1 imagery for the Sand Hills region of Nebraska has shown that the data can be used to effectively measure several parameters of inventory needs. (1) Vegetative biomass can be estimated with a high degree of confidence using computer compatable tape data. (2) Soils can be mapped to the subgroup level with high altitude aircraft color infrared photography and to the association level with multitemporal ERTS-1 imagery. (3) Water quality in Sand Hills lakes can be estimated utilizing computer compatable tape data. (4) Center pivot irrigation can be inventoried from satellite data and can be monitored regarding site selection and relative success of establishment from high altitude aircraft color infrared photography. (5) ERTS-1 data is of exceptional value in wide-area inventory of natural resource data in the Sand Hills region of Nebraska.

Seevers, P. M.↗

NASA NTRS1977

A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

The paper presents a method for retrieving single field of view tropospheric temperature profiles directly from cloud-contaminated radiance data through the use of auxiliary data such as observed shelter temperatures and estimated cloud-top height. A model was formulated to calculate cloud parameters for use with the radiative transport equation at an estimated cloud-top level. The cloud and temperature data are used in conjunction with real and simulated radiance data from NOAA satellites.

Hodges, D. B.↗

NASA NTRS1990

Estimation of synoptic fields of middle atmosphere parameters from Nimbus-7 LIMS profile data

The most widely used version of the Nimbus-7 middle atmosphere dataset is the set of high quality, daily, and zonal Fourier coefficients that resolve information out to six wavenumbers at 12 UTC. A Kalman filter algorithm was applied to the original profile data in order to generate those fields for the data archive or LAMAT product. The characteristics and implementation of the algorithm are described in some detail, along with examples of the output for each of the LIMS parameters.

Remsberg, Ellis E.↗

NASA NTRS2021

Determining Aircraft Moments of Inertia from Flight Test Data

Flight test maneuvers and dynamic modeling techniques were developed for determining aircraft moments of inertia from flight test data. Full nonlinear rigid-body rotational equations of motion were used in the analysis, with aerodynamic moment dependencies modeled by linear expansions in the aircraft states and controls. Aerodynamic parameters were estimated simultaneously with inertia parameters using equation-error modeling applied to flight test data from maneuvers designed specifically for this problem. The approach was demonstrated using a nonlinear F 16 simulation, then applied to a remotely-piloted subscale aircraft flight test. Errors in the aircraft moment of inertia parameters determined from simulated F-16 flight test data were less than 6 percent compared to the true values in the simulation. Flight test results for the subscale aircraft were within 6 percent of ground-test values obtained using the same aircraft.

Parameter estimation↗

NASA NTRS2005

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Goetz, Scott J.↗

NASA NTRS1979

Comparison of stability and control parameters for a light, single-engine, high-winged aircraft using different flight test and parameter estimation techniques

The longitudinal and lateral stability and control parameters for a high wing, general aviation, airplane are examined. Estimations using flight data obtained at various flight conditions within the normal range of the aircraft are presented. The estimations techniques, an output error technique (maximum likelihood) and an equation error technique (linear regression), are presented. The longitudinal static parameters are estimated from climbing, descending, and quasi steady state flight data. The lateral excitations involve a combination of rudder and ailerons. The sensitivity of the aircraft modes of motion to variations in the parameter estimates are discussed.

Suit, W. T.↗

NASA NTRS1987

Projection filters for modal parameter estimate for flexible structures

Single-mode projection filters are developed for eigensystem parameter estimates from both analytical results and test data. Explicit formulations of these projection filters are derived using the pseudoinverse matrices of the controllability and observability matrices in general use. A global minimum optimization algorithm is developed to update the filter parameters by using interval analysis method. Modal parameters can be attracted and updated in the global sense within a specific region by passing the experimental data through the projection filters. For illustration of this method, a numerical example is shown by using a one-dimensional global optimization algorithm to estimate model frequencies and dampings.

Huang, Jen-Kuang↗

NASA NTRS1981

Maximum likelihood clustering with dependent feature trees

The decomposition of mixture density of the data into its normal component densities is considered. The densities are approximated with first order dependent feature trees using criteria of mutual information and distance measures. Expressions are presented for the criteria when the densities are Gaussian. By defining different typs of nodes in a general dependent feature tree, maximum likelihood equations are developed for the estimation of parameters using fixed point iterations. The field structure of the data is also taken into account in developing maximum likelihood equations. Experimental results from the processing of remotely sensed multispectral scanner imagery data are included.

Chittineni, C. B.↗

NASA NTRS1978

Estimation of longitudinal aircraft characteristics using parameter identification techniques

This study compares the results from different parameter identification methods used to determine longitudinal aircraft characteristics from flight data. In general, these comparisons have found that the estimated short-period dynamics (natural frequency, damping, transfer functions) are only weakly affected by the type of identification method, however, the estimated aerodynamic coefficients may be strongly affected by the type of identification method. The estimated values for aerodynamic coefficients were found to depend upon the type of math model and type of test data used with each of the identification methods. The use of fairly complete math models and the use of long data lengths, combining both steady and nonsteady motion, are shown to provide aerodynamic coefficient values that compare favorably with the results from other testing methods such as steady-state flight and full-scale wind-tunnel experiments.

Wingrove, R. C.↗

NASA NTRS1997

Can the Topex/Poseidon Altimetry Data be Used to Estimate Air Sea Heat Flux in the North Atlantic?

We propose a novel approach to directly invert large-scale anomalous annual net air-sea heat flux from the Topex/Poseidon altimetry data in the North Atlantic. The major advantage of this new approach over the conventional bulk formula approach is that it does not need those climate parameters used in the conventional bulk formula calculation in estimating the large-scale anomalous annual net air-sea heat flux. Comparison with expendable bathythermograph data demonstrates that it is a feasible approach.

Wang, Liping↗

NASA NTRS2016

Aircraft Fault Detection Using Real-Time Frequency Response Estimation

A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.

Grauer, Jared A.↗

NASA NTRSDate not supplied

Determining Aircraft Moments of Inertia from Flight Test Data

Flight test maneuver design and dynamic modeling techniques were developed for determining aircraft moments of inertia from flight test data. Full nonlinear rigid-body rotational equations of motion were used in the analysis, with aerodynamic moment dependencies modeled by linear expansions in the aircraft states and controls. Aerodynamic parameters were estimated simultaneously with inertia parameters using equation-error modeling applied to flight test data from maneuvers designed specifically for this problem. The approach was demonstrated using a nonlinear F-16 simulation, then applied to a remotely-piloted subscale aircraft flight test. Errors in the aircraft moment of inertia parameters determined from simulated F-16 flight test maneuver data were less than 6 percent compared to the true values in the simulation. Flight test results for the subscale aircraft were within 6 percent of ground-test values obtained using the same aircraft.

moments of inertia↗

NASA NTRSDate not supplied

Determining Aircraft Moments of Inertia from Flight Test Data

Flight test maneuver design and dynamic modeling techniques were developed for determining aircraft moments of inertia from flight test data. Full nonlinear rigid-body rotational equations of motion were used in the analysis, with aerodynamic moment dependencies modeled by linear expansions in the aircraft states and controls. Aerodynamic parameters were estimated simultaneously with inertia parameters using equation-error modeling applied to flight test data from maneuvers designed specifically for this problem. The approach was demonstrated using a nonlinear F 16 simulation, then applied to a remotely piloted subscale aircraft flight test. Errors in the aircraft moment of inertia parameters determined from simulated F-16 flight test maneuver data were less than 6 percent compared to the true values in the simulation. Flight test results for the subscale aircraft were within 6 percent of ground-test values obtained using the same aircraft.

Aircraft Moments of Inertia↗

NASA NTRS1975

Monte Carlo analysis of inaccuracies in estimated aircraft parameters caused by unmodeled flight instrumentation errors

An output error estimation algorithm was used to evaluate the effects of both static and dynamic instrumentation errors on the estimation of aircraft stability and control parameters. A Monte Carlo error analysis, using simulated cruise flight data, was performed for a high-performance military aircraft, a large commercial transport, and a small general aviation aircraft. The results indicate that unmodeled instrumentation errors can cause inaccuracies in the estimated parameters which are comparable to their nominal values. However, the corresponding perturbations to the estimated output response trajectories and characteristics equation pole locations appear to be relatively small. Control input errors and dynamic lags were found to be in the most significant of the error sources evaluated.

Hodge, W. F.↗

NASA NTRS1989

Adaptation of the ISCCP cloud detection algorithm to combined AVHRR and SMMR arctic data

The International Satellite Cloud Climatology Project (ISCCP) cloud detection algorithm is applied to artic data, and modifications are suggested. Both Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data are examined. Synthetic AVHRR and SMMR data are also generated. Modifications suggested include the use of snow and ice data sets for the estimation of surface parameters, additional AVHRR channels, and surface class characteristic values when clear sky values cannot be obtained. Greatest improvement in computed cloud fraction is realized over snow and ice surfaces; over other surfaces all versions perform similarly. Since the use of SMMR for surface analysis increases the computational burden, its use may be justified only over snow and ice-covered regions.

Key, J.↗