Least squares estimation of regression coeffi- cients in a special class of polynomial models
Least squares estimation of regression coefficients of balanced polynomials
LEAST SQUARES METHOD↗
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A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models
Two methods of creating approximation models are compared through the calculation of the modeling accuracy on test problems involving one, five, and ten independent variables. Here, the test problems are representative of the modeling challenges typically encountered in realistic engineering optimization problems. The first approximation model is a quadratic polynomial created using the method of least squares. This type of polynomial model has seen considerable use in recent engineering optimization studies due to its computational simplicity and ease of use. However, quadratic polynomial models may be of limited accuracy when the response data to be modeled have multiple local extrema. The second approximation model employs an interpolation scheme known as kriging developed in the fields of spatial statistics and geostatistics. This class of interpolating model has the flexibility to model response data with multiple local extrema. However, this flexibility is obtained at an increase in computational expense and a decrease in ease of use. The intent of this study is to provide an initial exploration of the accuracy and modeling capabilities of these two approximation methods.
Giunta, Anthony A.↗
An analysis of LANDSAT MSS scene-to-scene registration accuracy
Measurements were made for 12 registrations done by ERL for 8 registrations done by SRS. The results indicate that the ERL method is significantly more accurate in five of the eight comparison. The difference between the two methods are not significant in the other three cases. There are two possible reasons for the differences. First, the ERL model is a piecewise linear model and the EDITOR model is a cubic polynomial model. Second, the ERL program resamples using bilinear interpolation while the EDITOR software uses a nearest neighbor resampling. This study did not indicate how much of the difference is attributable to each factor. The average of all merged scene error values for ERL was 31.6 meters and the average for the eight common areas was 32.6 meters. The average of the eight merged scene error values for SRS was 40.1 meters.
Seyfarth, B. R.↗
Comparison of Response Surface and Kriging Models in the Multidisciplinary Design of an Aerospike Nozzle
The use of response surface models and kriging models are compared for approximating non-random, deterministic computer analyses. After discussing the traditional response surface approach for constructing polynomial models for approximation, kriging is presented as an alternative statistical-based approximation method for the design and analysis of computer experiments. Both approximation methods are applied to the multidisciplinary design and analysis of an aerospike nozzle which consists of a computational fluid dynamics model and a finite element analysis model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations. Four optimization problems are formulated and solved using both approximation models. While neither approximation technique consistently outperforms the other in this example, the kriging models using only a constant for the underlying global model and a Gaussian correlation function perform as well as the second order polynomial response surface models.
Simpson, Timothy W.↗
Rectification of single and multiple frames of satellite scanner imagery using points and edges as control
Rectification of single and overlapping multiple scanner frames produced by such satellite-borne scanners as the LANDSAT MSS was carried out using a newly developed comprehensive parametric model. Tests with both simulated and real image data demonstrate conclusively that this model in general is superior to the widely used polynomial model, and that the simultaneous rectification of overlapping frames using least squares techniques yields a high accuracy than sngle frame rectification due to the inclusion of tie points between the image frames. Used to control, edges or lines, whic are much more likely to be found in images, can replace conventional control points and can easily be implemented into the least squares approach. An efficient algorithm for findng corresponding points in image paris was developed which can be used for determining tie points between image frames and thus increase the ecnomy of the whole rectification procedure.
Paderes, F. C., Jr.↗
Full-envelope aerodynamic modeling of the Harrier aircraft
A project to identify a full-envelope model of the YAV-8B Harrier using flight-test and parameter identification techniques is described. As part of the research in advanced control and display concepts for V/STOL aircraft, a full-envelope aerodynamic model of the Harrier is identified, using mathematical model structures and parameter identification methods. A global-polynomial model structure is also used as a basis for the identification of the YAV-8B aerodynamic model. State estimation methods are used to ensure flight data consistency prior to parameter identification.Equation-error methods are used to identify model parameters. A fixed-base simulator is used extensively to develop flight test procedures and to validate parameter identification software. Using simple flight maneuvers, a simulated data set was created covering the YAV-8B flight envelope from about 0.3 to 0.7 Mach and about -5 to 15 deg angle of attack. A singular value decomposition implementation of the equation-error approach produced good parameter estimates based on this simulated data set.
Mcnally, B. David↗
An Exponential Luminous Efficiency Model for Hypervelocity Impact into Regolith
The flash of thermal radiation produced as part of the impact-crater forming process can be used to determine the energy of the impact if the luminous efficiency is known. From this energy the mass and, ultimately, the mass flux of similar impactors can be deduced. The luminous efficiency, Eta is a unique function of velocity with an extremely large variation in the laboratory range of under 8 km/s but a necessarily small variation with velocity in the meteoric range of 20 to 70 km/s. Impacts into granular or powdery regolith, such as that on the moon, differ from impacts into solid materials in that the energy is deposited via a serial impact process which affects the rate of deposition of internal (thermal) energy. An exponential model of the process is developed which differs from the usual polynomial models of crater formation. The model is valid for the early time portion of the process and focuses on the deposition of internal energy into the regolith. The model is successfully compared with experimental luminous efficiency data from laboratory impacts and from astronomical determinations and scaling factors are estimated. Further work is proposed to clarify the effects of mass and density upon the luminous efficiency scaling factors
Swift, Wesley R.↗
An Exponential Luminous Efficiency Model for Hypervelocity Impact into Regolith
The flash of thermal radiation produced as part of the impact-crater forming process can be used to determine the energy of the impact if the luminous efficiency is known. From this energy the mass and, ultimately, the mass flux of similar impactors can be deduced. The luminous efficiency, eta, is a unique function of velocity with an extremely large variation in the laboratory range of under 6 km/s but a necessarily small variation with velocity in the meteoric range of 20 to 70 km/s. Impacts into granular or powdery regolith, such as that on the moon, differ from impacts into solid materials in that the energy is deposited via a serial impact process which affects the rate of deposition of internal (thermal) energy. An exponential model of the process is developed which differs from the usual polynomial models of crater formation. The model is valid for the early time portion of the process and focuses on the deposition of internal energy into the regolith. The model is successfully compared with experimental luminous efficiency data from both laboratory impacts and from lunar impact observations. Further work is proposed to clarify the effects of mass and density upon the luminous efficiency scaling factors. Keywords hypervelocity impact impact flash luminous efficiency lunar impact meteoroid 1
Swift, W. R.↗
Modeling the High Speed Research Cycle 2B Longitudinal Aerodynamic Database Using Multivariate Orthogonal Functions
The data for longitudinal non-dimensional, aerodynamic coefficients in the High Speed Research Cycle 2B aerodynamic database were modeled using polynomial expressions identified with an orthogonal function modeling technique. The discrepancy between the tabular aerodynamic data and the polynomial models was tested and shown to be less than 15 percent for drag, lift, and pitching moment coefficients over the entire flight envelope. Most of this discrepancy was traced to smoothing local measurement noise and to the omission of mass case 5 data in the modeling process. A simulation check case showed that the polynomial models provided a compact and accurate representation of the nonlinear aerodynamic dependencies contained in the HSR Cycle 2B tabular aerodynamic database.
Morelli, E. A.↗
A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION
Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system which may afford greater insight into the functionality of the system or a simpler controller design. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. The LASSO minimises the residual sum of squares by the addition of a 1 penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. The performance of this LASSO structure detection method was evaluated by using it to estimate the structure of a nonlinear polynomial model. Applicability of the method to more complex systems such as those encountered in aerospace applications was shown by identifying a parsimonious system description of the F/A-18 Active Aeroelastic Wing using flight test data.
Kukreja, Sunil L.↗
Passive Magnetic Bearing With Ferrofluid Stabilization
A new class of magnetic bearings is shown to exist analytically and is demonstrated experimentally. The class of magnetic bearings utilize a ferrofluid/solid magnet interaction to stabilize the axial degree of freedom of a permanent magnet radial bearing. Twenty six permanent magnet bearing designs and twenty two ferrofluid stabilizer designs are evaluated. Two types of radial bearing designs are tested to determine their force and stiffness utilizing two methods. The first method is based on the use of frequency measurements to determine stiffness by utilizing an analytical model. The second method consisted of loading the system and measuring displacement in order to measure stiffness. Two ferrofluid stabilizers are tested and force displacement curves are measured. Two experimental test fixtures are designed and constructed in order to conduct the stiffness testing. Polynomial models of the data are generated and used to design the bearing prototype. The prototype was constructed and tested and shown to be stable. Further testing shows the possibility of using this technology for vibration isolation. The project successfully demonstrated the viability of the passive magnetic bearing with ferrofluid stabilization both experimentally and analytically.
Jansen, Ralph↗
Development of Response Surface Models for Rapid Analysis & Multidisciplinary Optimization of Launch Vehicle Design Concepts
Multdisciplinary design optimization (MDO) is an important step in the design and evaluation of launch vehicles, since it has a significant impact on performance and lifecycle cost. The objective in MDO is to search the design space to determine the values of design parameters that optimize the performance characteristics subject to system constraints. Vehicle Analysis Branch (VAB) at NASA Langley Research Center has computerized analysis tools in many of the disciplines required for the design and analysis of launch vehicles. Vehicle performance characteristics can be determined by the use of these computerized analysis tools. The next step is to optimize the system performance characteristics subject to multidisciplinary constraints. However, most of the complex sizing and performance evaluation codes used for launch vehicle design are stand-alone tools, operated by disciplinary experts. They are, in general, difficult to integrate and use directly for MDO. An alternative has been to utilize response surface methodology (RSM) to obtain polynomial models that approximate the functional relationships between performance characteristics and design variables. These approximation models, called response surface models, are then used to integrate the disciplines using mathematical programming methods for efficient system level design analysis, MDO and fast sensitivity simulations. A second-order response surface model of the form given has been commonly used in RSM since in many cases it can provide an adequate approximation especially if the region of interest is sufficiently limited.
Unal, Resit↗
Criteria for the optimal design of experimental tests
Some of the basic concepts are unified that were developed for the problem of finding optimal approximating functions which relate a set of controlled variables to a measurable response. The techniques have the potential for reducing the amount of testing required in experimental investigations. Specifically, two low-order polynomial models are considered as approximations to unknown functionships. For each model, optimal means of designing experimental tests are presented which, for a modest number of measurements, yield prediction equations that minimize the error of an estimated response anywhere inside a selected region of experimentation. Moreover, examples are provided for both models to illustrate their use. Finally, an analysis of a second-order prediction equation is given to illustrate ways of determining maximum or minimum responses inside the experimentation region.
Canavos, G. C.↗
Comparison of reflectance with backscatter and absorption parameters for turbid waters
The relation of reflectance to backscatter and absorption parameters is investigated for waters more turbid than those of previous investigations. Experimental data are examined for river waters in which beam attenuation values range from 8.9 to 18.9 per m at 550 nm. Attenuation, absorption, backscatter, and irradiance reflectance spectral properties are presented for wavelengths between 450 and 800 nm. Comparisons of reflectance with backscatter to absorption ratio and backscatter with absorption plus backscatter ratio indicate that data for turbid waters do not fit linear or polynomial models which are presently available in the literature.
Whitlock, C. H.↗
Subset Regression
Backward elimination procedure minimizes prediction errors of equations fitted to factorial experiments. Problem of minimizing prediction error solved for two-level full- or fractional-factorial experiment with 16 factorial points and 0 to 6 center points. Such experiment provides 16 orthogonal coefficient estimates for empirical polynomial model. Each coefficient estimated with low variance error estimated from 16 observations.
Holms, A. G.↗
Terrain effects on backscattering coefficients derived from multifrequency, polarimetric SAR data
A set of multidate, multilook angle polarimetric SAR data, acquired in Pennsylvania during July 1990 was recorded to determine the effect of local incidence angle. Cosine-based and polynomial models are found to be equally good for correcting SAR data for local incidence angle effects. A modified approach, considering the correction factor as additive rather than multiplicative, gave better results. The standard error in the estimation of soil moisture improves from 8.1 to 5.8 after applying corrections to incidence angle effects.
Rao, K. S.↗
On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems
Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.
Belcastro, Christine M.↗
Survey and comparative analysis of current geophysical models
Legendre polynomials for gravitational field and orbit perturbation
Von Puttkamer, J.↗