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NASA NTRS1981

A stochastic-dynamic model for global atmospheric mass field statistics

A model that yields the spatial correlation structure of atmospheric mass field forecast errors was developed. The model is governed by the potential vorticity equation forced by random noise. Expansion in spherical harmonics and correlation function was computed analytically using the expansion coefficients. The finite difference equivalent was solved using a fast Poisson solver and the correlation function was computed using stratified sampling of the individual realization of F(omega) and hence of phi(omega). A higher order equation for gamma was derived and solved directly in finite differences by two successive applications of the fast Poisson solver. The methods were compared for accuracy and efficiency and the third method was chosen as clearly superior. The results agree well with the latitude dependence of observed atmospheric correlation data. The value of the parameter c sub o which gives the best fit to the data is close to the value expected from dynamical considerations.

Ghil, M.↗

NASA NTRS1984

Exploring the use of structural models to improve remote sensing agricultural estimates

Satellite estimates of agricultural characteristics often are not sufficiently precise for reliable use in small geographical regions. The precision of estimates of agricultural characteristics such as crop proportions and leaf area indexes can be increased by modeling ground observations as a function of satellite estimates. Linear regression models using least squares estimators of the model parameters are most often advocated as an appropriate methodology; however, least squares estimation requires that the predictor variables are measured without error, an unreasonable assumption for this application. An alternative estimation methodology which assumes that both the response variables (ground observations) and the predictor variables (satellite estimates) are measured with error involves the use of linear structural models. The application of linear structural models to the estimation of agricultural characteristics using satellite spectral measurements is examined.

Gunst, R. F.↗

NASA NTRS1990

On-orbit structural dynamic performance of a 15-meter microwave radiometer antenna

The on-orbit structural dynamic performance of a microwave radiometer antenna for Earth science applications is addressed. The radiometer is one of the Earth-observing instruments aboard a proposed geostationary platform as part of the Mission to the Planet Earth. A sequential approach is presented for assessing the ability of an antenna structure to retain its geometric shape subject to a representative onboard disturbance. This approach includes establishing the structural requirements of the antenna, developing the structural and disturbance models, performing modal and forced response analyses, and evaluating the resulting distortions in terms of the antenna's ability to meet stringent structural performance requirements. Two antenna configurations are discussed: free-flying and platform-mounted. These configurations are analyzed for a representative disturbance function which simulates rotation of the subreflector in order to perform a raster-type scan of the Earth disk. Results show that the scanning maneuver modeled would not induce antenna structural errors outside the specified limits.

Wahls, Deborah M.↗

NASA NTRS1997

Worst-Case Flutter Margins from F/A-18 Aircraft Aeroelastic Data

An approach for computing worst-case flutter margins has been formulated in a robust stability framework. Uncertainty operators are included with a linear model to describe modeling errors and flight variations. The structured singular value, micron, computes a stability margin which directly accounts for these uncertainties. This approach introduces a new method of computing flutter margins and an associated new parameter for describing these margins. The micron margins are robust margins which indicate worst-case stability estimates with respect to the defined uncertainty. Worst-case flutter margins are computed for the F/A-18 SRA using uncertainty sets generated by flight data analysis. The robust margins demonstrate flight conditions for flutter may lie closer to the flight envelope than previously estimated by p-k analysis.

Lind, Rick↗

NASA NTRS1998

Robust Flutter Margin Analysis that Incorporates Flight Data

An approach for computing worst-case flutter margins has been formulated in a robust stability framework. Uncertainty operators are included with a linear model to describe modeling errors and flight variations. The structured singular value, mu, computes a stability margin that directly accounts for these uncertainties. This approach introduces a new method of computing flutter margins and an associated new parameter for describing these margins. The mu margins are robust margins that indicate worst-case stability estimates with respect to the defined uncertainty. Worst-case flutter margins are computed for the F/A-18 Systems Research Aircraft using uncertainty sets generated by flight data analysis. The robust margins demonstrate flight conditions for flutter may lie closer to the flight envelope than previously estimated by p-k analysis.

Lind, Rick↗

NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here we apply an Ensemble Kalman Filter DA system as part of the Data Assimilation Research Testbed to a variety of land surface simulations. First, we describe the use of remotely sensed biomass observations to provide improved simulations of plant phenology, carbon and water cycling for regions highly sensitive to climate change (Western US, China, and Arctic). We discuss approaches to account for systemic biases between models and observations, including the use of spatially-varying adaptive ensemble inflation as an alternative approach to re-scaling soil moisture observations. Finally, we discuss a strategy to incorporate complementary observations (snow water equivalent, solar-induced fluorescence) to better constrain the representation of carbon and water cycling across complex terrain.

DART↗

NASA NTRS1990

Model reduction for flexible structures

Several conditions for a near-optimal reduction of general dynamic systems are presented focusing on the reduction in balanced and modal coordinates. It is shown that model and balanced reductions give very different results for the flexible structure with closely-spaced natural frequencies. In general, balanced reduction is found to give better results. A robust model reduction technique was developed to study the sensitivity of modeling error to variations in the damping of a structure. New concepts of grammians defined over a finite time and/or a frequency interval are proposed including computational procedures for evaluating them. Application of the model reduction technique to these grammians is considered to lead to a near-optimal reduced model which closely reproduces the full system output in the time and/or frequency interval.

Gawronski, Wodek↗

NASA NTRS1989

Reanalysis, compatibility and correlation in analysis of modified antenna structures

A simple computational procedure is synthesized to process changes in the microwave-antenna pathlength-error measure when there are changes in the antenna structure model. The procedure employs structural modification reanalysis methods combined with new extensions of correlation analysis to provide the revised rms pathlength error. Mainframe finite-element-method processing of the structure model is required only for the initial unmodified structure, and elementary postprocessor computations develop and deal with the effects of the changes. Several illustrative computational examples are included. The procedure adapts readily to processing spectra of changes for parameter studies or sensitivity analyses.

Levy, R.↗

NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes Using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here, we emphasize the implementation of tools and approaches to overcome challenges related to land DA to constrain carbon and water cycling. In particular, we discuss the implementation of adaptive inflation to modify ensemble spread in response to time-varying networks of gridded observations. We also discuss methods to generate ensemble spread through boundary condition (meteorology) forcing that can be applied to site-level applications. Next, we describe the application of vertical localization upon surface soil moisture observations, and forward operators specifically designed for the assimilation of snow and solar-induced fluorescence observations. Finally, we discuss the potential benefit of a quantile conserving filter used to update bounded quantities (state or parameter values).

Brett Raczka↗

NASA NTRS2013

Follow on Research for Multi-Utility Technology Test Bed Aircraft at NASA Dryden Flight Research Center (FY13 Progress Report)

Modern aircraft employ a significant fraction of their weight in composite materials to reduce weight and improve performance. Aircraft aeroservoelastic models are typically characterized by significant levels of model parameter uncertainty due to the composite manufacturing process. Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of Multi Utility Technology Test-bed (MUTT) aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of MUTT aircraft. The ground vibration test-validated structural dynamic finite element model of the MUTT aircraft is created in this study. The structural dynamic finite element model of MUTT aircraft is improved using the in-house Multi-disciplinary Design, Analysis, and Optimization tool. In this study, two different weight configurations of MUTT aircraft have been improved simultaneously in a single model tuning procedure.

multi-utility technology test bed aircraft↗

NASA NTRS1992

The effects of weighting function errors on spatial filters for structural control

Distributed-effect sensors, which respond to spatially distributed inputs over a significant gauge length, encompass piezoelectric laminate films, modal-domain optical fiber sensors, and holographic sensors; they can be fabricated with spatially varying sensitivity to a distributed measurand for spatial filtering. Such spatial filters are configurable to extract various structural parameters from distributed measurements that cannot be directly measured by sensors. A modeling is presently conducted for distributed-effect sensors' integration into state-space structural models, noting the effects of fabrication errors on sensor operation.

Lindner, Douglas K.↗

NASA NTRS1986

Parameter estimation and error analysis in environmental modeling and computation

A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.

Kalmaz, E. E.↗

NASA NTRS1985

Structural error and identifiability

In most identification problems, the possibility of identifying a model from the observation of input and output is approached by first assuming that the model is an exact representation of the process. Since models are only approximations to a real process, this paper presents a concrete way of taking into account the difference in structure between the model and the process it represents. The identifiability problem is reformulated on the basis of equivalence and near-equivalence between model and process. Necessary and sufficient conditions under which the differences between the outputs of the process and a model remains within a desired bound in the presence of modeling error are given. Necessary and sufficient conditions for the identifiability of parameters are presented.

Hadaegh, F. Y.↗

NASA NTRS2012

Follow on Researches for X-56A Aircraft at NASA Dryden Flight Research Center (Progress Report)

A lot of composite materials are used for the modern aircraft to reduce its weight. Aircraft aeroservoelastic models are typically characterized by significant levels of model parameter uncertainty due to composite manufacturing process. Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of X-56A aircraft is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes is based on the flutter analysis of X-56A aircraft. It should be noted that for all three Mach number cases rigid body modes and mode numbers seven and nine are participated 89.1 92.4 % of the first flutter mode. Modal participation of the rigid body mode and mode numbers seven and nine for the second flutter mode are 94.6 96.4%. Rigid body mode and the first two anti-symmetric modes, eighth and tenth modes, are participated 93.2 94.6% of the third flutter mode. Therefore, rigid body modes and the first four flexible modes of X-56A aircraft are the primary modes during the model tuning procedure. The ground vibration test-validated structural dynamic finite element model of the X-56A aircraft is to obtain in this study. The structural dynamics finite element model of X-56A aircraft is improved using the parallelized big-bang big-crunch algorithm together with a hybrid optimization technique.

Structural Dynamic Model Tuning↗

NASA NTRS1986

Variable structure control of nonlinear systems through simplified uncertain models

A variable structure control approach is presented for the robust stabilization of feedback equivalent nonlinear systems whose proposed model lies in the same structural orbit of a linear system in Brunovsky's canonical form. An attempt to linearize exactly the nonlinear plant on the basis of the feedback control law derived for the available model results in a nonlinearly perturbed canonical system for the expanded class of possible equivalent control functions. Conservatism tends to grow as modeling errors become larger. In order to preserve the internal controllability structure of the plant, it is proposed that model simplification be carried out on the open-loop-transformed system. As an example, a controller is developed for a single link manipulator with an elastic joint.

Sira-Ramirez, Hebertt↗

NASA NTRS1991

Attitude error response of structures to actuator/sensor noise

Explicit closed-form formulas are presented for the RMS attitude-error response to sensor and actuator noise for co-located actuators/sensors as a function of both control-gain parameters and structure parameters. The main point of departure is the use of continuum models. In particular the anisotropic Timoshenko model is used for lattice trusses typified by the NASA EPS Structure Model and the Evolutionary Model. One conclusion is that the maximum attainable improvement in the attitude error varying either structure parameters or control gains is 3 dB for the axial and torsion modes, the bending being essentially insensitive. The results are similar whether the Bernoulli model or the anisotropic Timoshenko model is used.

Balakrishnan, A. V.↗

NASA NTRS1975

Stochastic process approximation for recursive estimation with guaranteed bound on the error covariance

An approach, is proposed for the design of approximate, fixed order, discrete time realizations of stochastic processes from the output covariance over a finite time interval, was proposed. No restrictive assumptions are imposed on the process; it can be nonstationary and lead to a high dimension realization. Classes of fixed order models are defined, having the joint covariance matrix of the combined vector of the outputs in the interval of definition greater or equal than the process covariance; (the difference matrix is nonnegative definite). The design is achieved by minimizing, in one of those classes, a measure of the approximation between the model and the process evaluated by the trace of the difference of the respective covariance matrices. Models belonging to these classes have the notable property that, under the same measurement system and estimator structure, the output estimation error covariance matrix computed on the model is an upper bound of the corresponding covariance on the real process. An application of the approach is illustrated by the modeling of random meteorological wind profiles from the statistical analysis of historical data.

Menga, G.↗

NASA NTRS1983

Classification of journal surfaces using surface topography parameters and software methods to compensate for stylus geometry

Measurements made with a stylus surface tracer which provides a digitized representation of a surface profile are discussed. Parameters are defined to characterize the height (e.g., RMS roughness, skewness, and kurtosis) and length (e.g., autocorrelation) of the surface topography. These are applied to the characterization of crank shaft journals which were manufactured by different grinding and lopping procedures known to give significant differences in crank shaft bearing life. It was found that three parameters (RMS roughness, skewness, and kurtosis) are necessary to adequately distinguish the character of these surfaces. Every surface specimen has a set of values for these three parameters. They can be regarded as a set coordinate in a space constituted by three characteristics axes. The various journal surfaces can be classified along with the determination of a proper wavelength cutoff (0.25 mm) by using a method of separated subspace. The finite radius of the stylus used for profile tracing gives an inherent measurement error as it passes over the fine structure of the surface. A mathematical model is derived to compensate for this error.

Li, C. J.↗