Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “model parameter estimation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Wake Vortex Inverse Model User's Guide

NorthWest Research Associates (NWRA) has developed an inverse model for inverting landing aircraft vortex data. The data used for the inversion are the time evolution of the lateral transport position and vertical position of both the port and starboard vortices. The inverse model performs iterative forward model runs using various estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Forward model predictions of lateral transport and altitude are then compared with the observed data. Differences between the data and model predictions guide the choice of vortex parameter values, crosswind profile and circulation evolution in the next iteration. Iterations are performed until a user-defined criterion is satisfied. Currently, the inverse model is set to stop when the improvement in the rms deviation between the data and model predictions is less than 1 percent for two consecutive iterations. The forward model used in this inverse model is a modified version of the Shear-APA model. A detailed description of this forward model, the inverse model, and its validation are presented in a different report (Lai, Mellman, Robins, and Delisi, 2007). This document is a User's Guide for the Wake Vortex Inverse Model. Section 2 presents an overview of the inverse model program. Execution of the inverse model is described in Section 3. When executing the inverse model, a user is requested to provide the name of an input file which contains the inverse model parameters, the various datasets, and directories needed for the inversion. A detailed description of the list of parameters in the inversion input file is presented in Section 4. A user has an option to save the inversion results of each lidar track in a mat-file (a condensed data file in Matlab format). These saved mat-files can be used for post-inversion analysis. A description of the contents of the saved files is given in Section 5. An example of an inversion input file, with preferred parameters values, is given in Appendix A. An example of the plot generated at a normal completion of the inversion is shown in Appendix B.

Lai, David↗
NASA NTRS2014

Initial Evaluations of LoC Prediction Algorithms Using the NASA Vertical Motion Simulator

Flying near the edge of the safe operating envelope is an inherently unsafe proposition. Edge of the envelope here implies that small changes or disturbances in system state or system dynamics can take the system out of the safe envelope in a short time and could result in loss-of-control events. This study evaluated approaches to predicting loss-of-control safety margins as the aircraft gets closer to the edge of the safe operating envelope. The goal of the approach is to provide the pilot aural, visual, and tactile cues focused on maintaining the pilot's control action within predicted loss-of-control boundaries. Our predictive architecture combines quantitative loss-of-control boundaries, an adaptive prediction method to estimate in real-time Markov model parameters and associated stability margins, and a real-time data-based predictive control margins estimation algorithm. The combined architecture is applied to a nonlinear transport class aircraft. Evaluations of various feedback cues using both test and commercial pilots in the NASA Ames Vertical Motion-base Simulator (VMS) were conducted in the summer of 2013. The paper presents results of this evaluation focused on effectiveness of these approaches and the cues in preventing the pilots from entering a loss-of-control event.

Pilot Cue↗
NASA NTRS1990

Estimating short-period dynamics using an extended Kalman filter

An extended Kalman filter is used to estimate the parameters of a low-order model from aircraft transient response data. The low-order model is a state-space model derived from the short-period approximation of the longitudinal aircraft dynamics. The model corresponds to the pitch rate to stick force transfer function currently used in flying qualities analysis. The parameters are estimated from flight data as well as from a 6-DOF nonlinear simulation of the aircraft. These two estimates are then compared, and the discrepancies noted. The low-order model is able to satisfactorily match both flight data and simulation data from a high-order computer simulation.

Bauer, Jeffrey E.↗
NASA NTRS1983

System identification of large flexible structures by using simple continuum models

Simple continuum models for the representation of large truss beams and truss platforms are constructed and employed in the solution of system identification problems permitting the significant reduction of the number of structural parameters. Two simple and easily computer-implemented algorithms are presented for the estimation of a simple model's equivalent structural parameters, and analytical and numerical solutions are given for the truss beam and truss platform cases in order to illustrate the basic concepts. It is found that model simplicity, in conjunction with the principle of least square erors, yields a feasible integration of structural and identification problems.

Juang, J. N.↗
NASA NTRS2007

Stress Rupture Life Reliability Measures for Composite Overwrapped Pressure Vessels

Composite Overwrapped Pressure Vessels (COPVs) are often used for storing pressurant gases onboard spacecraft. Kevlar (DuPont), glass, carbon and other more recent fibers have all been used as overwraps. Due to the fact that overwraps are subjected to sustained loads for an extended period during a mission, stress rupture failure is a major concern. It is therefore important to ascertain the reliability of these vessels by analysis, since the testing of each flight design cannot be completed on a practical time scale. The present paper examines specifically a Weibull statistics based stress rupture model and considers the various uncertainties associated with the model parameters. The paper also examines several reliability estimate measures that would be of use for the purpose of recertification and for qualifying flight worthiness of these vessels. Specifically, deterministic values for a point estimate, mean estimate and 90/95 percent confidence estimates of the reliability are all examined for a typical flight quality vessel under constant stress. The mean and the 90/95 percent confidence estimates are computed using Monte-Carlo simulation techniques by assuming distribution statistics of model parameters based also on simulation and on the available data, especially the sample sizes represented in the data. The data for the stress rupture model are obtained from the Lawrence Livermore National Laboratories (LLNL) stress rupture testing program, carried out for the past 35 years. Deterministic as well as probabilistic sensitivities are examined.

Murthy, Pappu L. N.↗
NASA NTRS1997

Large Volcanic Rises on Venus

Large volcanic rises on Venus have been interpreted as hotspots, or the surface manifestation of mantle upwelling, on the basis of their broad topographic rises, abundant volcanism, and large positive gravity anomalies. Hotspots offer an important opportunity to study the behavior of the lithosphere in response to mantle forces. In addition to the four previously known hotspots, Atla, Bell, Beta, and western Eistla Regiones, five new probable hotspots, Dione, central Eistla, eastern Eistla, Imdr, and Themis, have been identified in the Magellan radar, gravity and topography data. These nine regions exhibit a wider range of volcano-tectonic characteristics than previously recognized for venusian hotspots, and have been classified as rift-dominated (Atla, Beta), coronae-dominated (central and eastern Eistla, Themis), or volcano-dominated (Bell, Dione, western Eistla, Imdr). The apparent depths of compensation for these regions ranges from 65 to 260 km. New estimates of the elastic thickness, using the 90 deg and order spherical harmonic field, are 15-40 km at Bell Regio, and 25 km at western Eistla Regio. Phillips et al. find a value of 30 km at Atla Regio. Numerous models of lithospheric and mantle behavior have been proposed to interpret the gravity and topography signature of the hotspots, with most studies focusing on Atla or Beta Regiones. Convective models with Earth-like parameters result in estimates of the thickness of the thermal lithosphere of approximately 100 km. Models of stagnant lid convection or thermal thinning infer the thickness of the thermal lithosphere to be 300 km or more. Without additional constraints, any of the model fits are equally valid. The thinner thermal lithosphere estimates are most consistent with the volcanic and tectonic characteristics of the hotspots. Estimates of the thermal gradient based on estimates of the elastic thickness also support a relatively thin lithosphere (Phillips et al.). The advantage of larger estimates of the thermal lithospheric thickness is that they provide an explanation for the apparently modest levels of geologic activity on Venus over the last half billion years.

Smrekar, Suzanne E.↗
NASA NTRS1993

Rain-rate data base development and rain-rate climate analysis

The single-year rain-rate distribution data available within the archives of Consultative Committee for International Radio (CCIR) Study Group 5 were compiled into a data base for use in rain-rate climate modeling and for the preparation of predictions of attenuation statistics. The four year set of tip-time sequences provided by J. Goldhirsh for locations near Wallops Island were processed to compile monthly and annual distributions of rain rate and of event durations for intervals above and below preset thresholds. A four-year data set of tropical rain-rate tip-time sequences were acquired from the NASA TRMM program for 30 gauges near Darwin, Australia. They were also processed for inclusion in the CCIR data base and the expanded data base for monthly observations at the University of Oklahoma. The empirical rain-rate distributions (edfs) accepted for inclusion in the CCIR data base were used to estimate parameters for several rain-rate distribution models: the lognormal model, the Crane two-component model, and the three parameter model proposed by Moupfuma. The intent of this segment of the study is to obtain a limited set of parameters that can be mapped globally for use in rain attenuation predictions. If the form of the distribution can be established, then perhaps available climatological data can be used to estimate the parameters rather than requiring years of rain-rate observations to set the parameters. The two-component model provided the best fit to the Wallops Island data but the Moupfuma model provided the best fit to the Darwin data.

Crane, Robert K.↗
NASA NTRS1972

Experiments with program locality.

Attempt to validate experimentally several intrinsic models for the concept of program locality. The models considered are a two-parameter simple locality model, a simple least recently used stack model, and an independent reference model. The first two models appear to produce good approximations to real world behavior, while the independent reference model, because of its static concept of locality, does very poorly. The working set is shown to be a good estimator of the simple two-parameters model's locality, provided that the locality does not change too rapidly. The working set exactly measures the locality in the case of the least recently used stack model and is thus nearly optimal for programs whose behavior can be closely approximated by this model.

Spirn, J. R.↗
NASA NTRS1990

Distributed parameter modeling for the control of flexible spacecraft

The use of FEMs of spacecraft structural dynamics is a common practice, but it has a number of shortcomings. Distributed-parameter models offer an alternative, but present both advantages and difficulties. First, the model order does not have to be reduced prior to the inclusion of control system dynamics. This advantage eliminates the risk involved with model 'order reduction'. Second, distributed parameter models inherently involve fewer parameters, thereby enabling more accurate parameter estimation using experimental data. Third, it is possible to include the damping in the basic model, thereby increasing the accuracy of the structural damping. The difficulty in generating distributed parameter models of complex spacecraft configurations has been greatly alleviated by the use of PDEMOD, BUNVIS-RG, or DISTEL. PDEMOD is being developed for simultaneously modeling structural dynamics and control system dynamics.

Taylor, Lawrence W., Jr.↗
NASA NTRS2022

Comparison of U.S. and Russian Slow Crack Growth Data and Models

Both the US and Russian space programs use similar predictive models for design of fused silica windows on the International space station. The Russian model can be derived from the power expression for slow crack growth (SCG) or “static fatigue.” The US uses both power and exponential models. Despite the similarity of models and data fitting approach (linear regression and right censoring), different SCG parameters have been derived by US and Russian parties for the same material (Russian fused silica) tested in a similar manner. The difference appears to be related to the use of short-term strength data along with the longer-term static fatigue data, with the power law parameter n being very sensitive to the conversion of strength data into equivalent static data. This hybrid approach is feasible if strength data is measured with a constant stress rate and is appropriately converted to a static equivalent. More research into the approach is needed. However, because of the nonlinear behavior of fused silica in log(v) – log(K(I) ) space and the sensitivity of parameter estimation to fit range, the exponential model is a better choice regardless of test method. Functions are given to convert parameters from the Russian model to those in the US model. However, accurate conversion is hampered by the lack of inert strength data. When the same test technique is used, US and Russian materials exhibit very similar parameters.

Silica, strength, impact, crack growth, windows, I↗
NASA NTRS1986

Estimation of aerodynamic parameters from flight data of a high incidence research model

A procedure for the determination of an aerodynamic model structure and aerodynamic parameters is applied to flight data from a high-incidence research model (HIRM) within an angle of attack range of 18 to 40 degrees. The HIRM is a three-surface unpowered model with a swept wing, an all-moving canard and stabilator, and a vertical tail with rudder. The motion of the HIRM was excited first by its release from the helicopter and then by the activation of control surfaces. This paper briefly describes the model, flight and wind tunnel data available, equations of motion and techniques for data analysis. The results presented contain an example of a measured data compatibility and the variation of some important stability derivatives with the angle of attack and canard setting. The derivatives were obtained from various maneuvers and subsets of joined data from several maneuvers by using a stepwise-regression technique. These derivatives agreed, in general, with the results of wind-tunnel measurements. The resulting lateral aerodynamic model equations could predict the motion of the HIRM reasonably well.

Klein, V.↗
NASA NTRS2012

Identification of Time-Varying Pilot Control Behavior in Multi-Axis Control Tasks

Recent developments in fly-by-wire control architectures for rotorcraft have introduced new interest in the identification of time-varying pilot control behavior in multi-axis control tasks. In this paper a maximum likelihood estimation method is used to estimate the parameters of a pilot model with time-dependent sigmoid functions to characterize time-varying human control behavior. An experiment was performed by 9 general aviation pilots who had to perform a simultaneous roll and pitch control task with time-varying aircraft dynamics. In 8 different conditions, the axis containing the time-varying dynamics and the growth factor of the dynamics were varied, allowing for an analysis of the performance of the estimation method when estimating time-dependent parameter functions. In addition, a detailed analysis of pilots adaptation to the time-varying aircraft dynamics in both the roll and pitch axes could be performed. Pilot control behavior in both axes was significantly affected by the time-varying aircraft dynamics in roll and pitch, and by the growth factor. The main effect was found in the axis that contained the time-varying dynamics. However, pilot control behavior also changed over time in the axis not containing the time-varying aircraft dynamics. This indicates that some cross coupling exists in the perception and control processes between the roll and pitch axes.

Zaal, Peter M. T.↗
NASA NTRS2009

Model Calibration in Watershed Hydrology

Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

Yilmaz, Koray K.↗
NASA NTRS2000

Systems Engineering Programmatic Estimation Using Technology Variance

Unique and innovative system programmatic estimation is conducted using the variance of the packaged technologies. Covariance analysis is performed on the subsystems and components comprising the system of interest. Technological "return" and "variation" parameters are estimated. These parameters are combined with the model error to arrive at a measure of system development stability. The resulting estimates provide valuable information concerning the potential cost growth of the system under development.

Mog, Robert A.↗
NASA NTRS2000

Systems Engineering Programmatic Estimation Using Technology Variance

Unique and innovative system programmatic estimation is conducted using the variance of the packaged technologies. Covariance analysis is performed oil the subsystems and components comprising the system of interest. Technological "returns" and "variation" parameters, are estimated. These parameters are combined with the model error to arrive at a measure of system development stability. The resulting estimates provide valuable information concerning the potential cost growth of the system under development.

Mog, Robert A.↗
NASA NTRS2002

A model for interphase chromosomes and evaluation of radiation-induced aberrations

We have developed a theoretical model for evaluating radiation-induced chromosomal exchanges by explicitly taking into account interphase (G(0)/G(1)) chromosome structure, nuclear organization of chromosomes, the production of double-strand breaks (DSBs), and the subsequent rejoinings in a faithful or unfaithful manner. Each of the 46 chromosomes for human lymphocytes (40 chromosomes for mouse lymphocytes) is modeled as a random polymer inside a spherical volume. The chromosome spheres are packed randomly inside a spherical nucleus with an allowed overlap controlled by a parameter Omega. The rejoining of DSBs is determined by a Monte Carlo procedure using a Gaussian proximity function with an interaction range parameter sigma. Values of Omega and sigma have been found which yield calculated results of interchromosomal aberration frequencies that agree with a wide range of experimental data. Our preferred solution is one with an interaction range of 0.5 microm coupled with a relatively small overlap parameter of 0.675 microm, which more or less confirms previous estimates. We have used our model with these parameter values and with resolution or detectability limits to calculate yields of translocations and dicentrics for human lymphocytes exposed to low-LET radiation that agree with experiments in the dose range 0.09 to 4 Gy. Five different experimental data sets have been compared with the theoretical results. Essentially all of the experimental data fall between theoretical curves corresponding to resolution limits of 1 Mbp and 20 Mbp, which may reflect the fact that different investigators use different limits for sensitivity or detectability. Translocation yields for mouse lymphocytes have also been calculated and are in good agreement with experimental data from 1 cGy to 10 cGy. There is also good agreement with recent data on complex aberrations. Our model is expected to be applicable to both low- and high-LET radiation, and we include a sample prediction of the yield of interchromosomal rejoining in the dose range 0.22 Gy to 2 Gy of 1000 MeV/nucleon iron particles. This dose range corresponds to average particle traversals per nucleus ranging from 1.0 to 9.12.

Non-NASA Center↗
NASA NTRS2009

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

Simon, Donald L.↗