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Results for “nonlinear least squares”

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 19 records

Stratospheric NO2 and H2O mixing ratio profiles from high resolution infrared solar spectra using nonlinear least squares

Nonlinear least squares spectral curve fitting has been used to derive vertical mixing ratio profiles for NO2 and H2O above 16 km from high resolution (0.2/cm) solar spectra collected during sunset with a balloon borne interferometer. The NO2 profile shows a sharp peak of 8 ppbv at 32 km falling rapidly to less than 0.5 ppbv at 17 km. The H2O profile shows a broad peak of 6.5 ppmv at 30 km falling to less than 4 ppmv at 17 km.

Niple, E.↗

Nonlinear least squares - An aid to thermal property determination

Nonlinear least squares techniques can be used to determine effective thermal conductivity values from experimental data. Comparisons between measured and predicted conductivity values indicate that the analytically determined values can be used with confidence in performing thermal protection system analyses. A study was performed to compare the relative efficiencies of different minimizing techniques; techniques; the method of Peckham was the most efficient.

Curry, D. M.↗

Nonlinear least squares - An aid to thermal property determination.

Nonlinear least squares techniques can be used to determine effective thermal conductivity values from experimental data. Comparisons between measured and predicted conductivity values indicate that the analytically determined values can be used with confidence in performing thermal protection system analyses. A study was performed to compare the relative efficiencies of different minimizing techniques; the method of Peckham was the most efficient.

Curry, D. M.↗

Constrained hierarchical least square nonlinear equation solvers

The current paper develops a constrained hierarchical least square nonlinear equation solver. The procedure can handle the response behavior of systems which possess indefinite tangent stiffness characteristics. Due to the generality of the scheme, this can be achieved at various hierarchical application levels. For instance, in the case of finite element simulations, various combinations of either degree of freedom, nodal, elemental, substructural, and global level iterations are possible. Overall, this enables a solution methodology which is highly stable and storage efficient. To demonstrate the capability of the constrained hierarchical least square methodology, benchmarking examples are presented which treat structure exhibiting highly nonlinear pre- and postbuckling behavior wherein several indefinite stiffness transitions occur.

Padovan, J.↗

A study of various methods for calculating locations of lightning events

This article reports on the results of numerical experiments on finding the location of lightning events using different numerical methods. The methods include linear least squares, nonlinear least squares, statistical estimations, cluster analysis and angular filters and combinations of such techniques. The experiments involved investigations of methods for excluding fake solutions which are solutions that appear to be reasonable but are in fact several kilometers distant from the actual location. Some of the conclusions derived from the study are that bad data produces fakes, that no fool-proof method of excluding fakes was found, that a short base-line interferometer under development at Kennedy Space Center to measure the direction cosines of an event shows promise as a filter for excluding fakes. The experiments generated a number of open questions, some of which are discussed at the end of the report.

Cannon, John R.↗

A Nonlinear Least Squares Phasor Estimation Algorithm with a Trust Metric

The paper presents a separable nonlinear least squares (NLLS)-based approach for estimation of fundamental-frequency phasors from sampled point-on-wave measurements. An analytical connection is established between the NLLS cost function and the discrete Fourier transform (DFT)-based periodogram of the input signal. This periodogram-based interpretation of the cost function offers an intuitive and easy-to-implement solution for the frequency estimate. Using the residual error of the NLLS-fit, the paper also presents an insightful measure for ascertaining the quality of the phasor estimates and their validity, especially for data windows containing signal transients.

Chatterjee, Kaustav↗

Application of nonlinear least squares methods to the analysis of solar spectra

A fast method of retrieving vertical temperature profiles in the atmosphere and of determining the paths of the rays producing the ATMOS occultation spectra has been developed. The results from one set of occultation data appear to be consistent with other available data. A study of sources of error, a search for other suitable features for measurement in the spectra, and modification of the program to obtain mixing ratio profiles have been initiated.

Shaw, J. H.↗

A quadratic-tensor model algorithm for nonlinear least-squares problems with linear constraints

A new algorithm for solving nonlinear least-squares and nonlinear equation problems is proposed which is based on approximating the nonlinear functions using the quadratic-tensor model by Schnabel and Frank. The algorithm uses a trust region defined by a box containing the current values of the unknowns. The algorithm is found to be effective for problems with linear constraints and dense Jacobian matrices.

Hanson, R. J.↗

A new algorithm for constrained nonlinear least-squares problems, part 1

A Gauss-Newton algorithm is presented for solving nonlinear least squares problems. The problem statement may include simple bounds or more general constraints on the unknowns. The algorithm uses a trust region that allows the objective function to increase with logic for retreating to best values. The computations for the linear problem are done using a least squares system solver that allows for simple bounds and linear constraints. The trust region limits are defined by a box around the current point. In its current form the algorithm is effective only for problems with small residuals, linear constraints and dense Jacobian matrices. Results on a set of test problems are encouraging.

Hanson, R. J.↗

A nonlinear least-squares inverse analysis of strike-slip faulting with application to the San Andreas fault

A nonlinear weighted least-squares analysis was performed for a synthetic elastic layer over a viscoelastic half-space model of strike-slip faulting. Also, an inversion of strain rate data was attempted for the locked portions of the San Andreas fault in California. Based on an eigenvector analysis of synthetic data, it is found that the only parameter which can be resolved is the average shear modulus of the elastic layer and viscoelastic half-space. The other parameters were obtained by performing a suite of inversions for the fault. The inversions on data from the northern San Andreas resulted in predicted parameter ranges similar to those produced by inversions on data from the whole fault.

Williams, Charles A.↗

Kernel Partial Least Squares for Nonlinear Regression and Discrimination

This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.

Rosipal, Roman↗

Improvement of structural models using covariance analysis and nonlinear generalized least squares

The next generation of large, flexible space structures will be too light to support their own weight, requiring a system of structural supports for ground testing. The authors have proposed multiple boundary-condition testing (MBCT), using more than one support condition to reduce uncertainties associated with the supports. MBCT would revise the mass and stiffness matrix, analytically qualifying the structure for operation in space. The same procedure is applicable to other common test conditions, such as empty/loaded tanks and subsystem/system level tests. This paper examines three techniques for constructing the covariance matrix required by nonlinear generalized least squares (NGLS) to update structural models based on modal test data. The methods range from a complicated approach used to generate the simulation data (i.e., the correct answer) to a diagonal matrix based on only two constants. The results show that NGLS is very insensitive to assumptions about the covariance matrix, suggesting that a workable NGLS procedure is possible. The examples also indicate that the multiple boundary condition procedure more accurately reduces errors than individual boundary condition tests alone.

Glaser, R. J.↗