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At least 1,657 records · Page 92

Identification of vortex-induced clear-air turbulence using airline flight records

The nature and cause of clear-air turbulence is being investigated, in cooperation with the National Transportation Safety Board, using the flight records available from airline encounters with severe turbulence. This paper presents two case studies of severe turbulence which indicate that the airplanes involved encountered vortex arrays which were generated by destabilized wind-shear layers near the tropopause. In order to identify and analyze vortex patterns (i.e., vortex strength, size, and spacings), potential-flow models of vortex arrays were developed that describe reasonably well the wind patterns derived from the airliner flight records. The results of this analysis indicate that in the two cases studied, the vortex cores had diameters in the range of 900 to 1,200 ft with tangential velocities in the range of 70 to 85 ft/sec. This study presents the first identification and analysis of vortex arrays from airline flight data. The results are compared with theoretical predictions and previous observations.

Parks, E. K.↗

Identification of multivariable high performance turbofan engine dynamics from closed loop data

The multivariable instrumental variable/approximate maximum likelihood (IV/AML) method of recursive time-series analysis is used to identify the multivariable (four inputs-three outputs) dynamics of the Pratt and Whitney F100 engine. A detailed nonlinear engine simulation is used to determine linear engine model structures and parameters at an operating point using open loop data. Also, the IV/AML method is used in a direct identification made to identify models from actual closed loop engine test data. Models identified from simulated and test data are compared to determine a final model structure and parameterization that can predict engine response for a wide class of inputs. The ability of the IV/AML algorithm to identify useful dynamic models from engine test data is assessed. Previously announced in STAR as N82-20339

Merrill, W.↗

A bias identification and state estimation methodology for nonlinear systems

A computational algorithm for the identification of input and output biases in discrete-time nonlinear stochastic systems is derived by extending the separate bias estimation results for linear systems to the extended Kalman filter formulation. The merits of the approach are illustrated by identifying instrument biases using a terminal configured vehicle simulation.

Caglayan, A. K.↗

Identification of structural systems using naturally induced vibration data in the presence of measurement noise

The method of instrument variables for the identification of the parameters of structural systems excited by white noise in the presence of white measurement noise is applied. The requisite equations and the resulting consistent estimator are derived and simulation results for least squares and instrumental variables methods, for light and heavy damping, are compared. The present method gave better results than least squares when measurement noise was presented, and verified the fact that least squares yields an inconsistent estimator unless the measurement noise is zero.

Huan, S.-L.↗

Optical identification of 2S 1417-62

The 17 s X-ray pulsar 2S 1417-62 has been identified with a V of approximately 16.9 mag OB star on the basis of an X-ray position obtained with the Einstein X-Ray Observatory and spectrophotometry with the 4-m telescope at Cerro Tololo Inter-American Observatory. Strong H-alpha emission is observed as well as significant changes in X-ray luminosity. The optical counterpart may be either a Be or a B I star, but the H-alpha emission strength and galactic position suggest that a Be star is more likely. A Be star identification also further supports the limit of approximately 15 days or more on the system binary period obtained by Kelley et al. (1981) from pulse timing studies.

Grindlay, J. E.↗

Identification of oxygen-related midgap level in GaAs

An oxygen-related deep level ELO was identified in GaAs employing Bridgman-grown crystals with controlled oxygen doping. The activation energy of ELO is almost the same as that of the dominant midgap level: EL2. This fact impedes the identification of ELO by standard deep level transient spectroscopy. However, it was found that the electron capture cross section of ELO is about four times greater than that of EL2. This characteristic served as the basis for the separation and quantitative investigation of ELO employing detailed capacitance transient measurements in conjunction with reference measurements on crystals grown without oxygen doping and containing only EL2.

Lagowski, J.↗

Line identifications in the ultraviolet (2590-3230 A) spectrum of the hydrogen-deficient carbon star HD 182040

Identifications for absorption features detected in the ultraviolet spectrum of the hydrogen-deficient supergiant carbon star HD 182040 observed at high resolution with the IUE satellite are presented. The spectrum in this range is filled with blended lines of the iron-peak elements, with Fe I and Cr II dominating the spectrum. Spectra definitely and probably detected are given, as well as those searched for and not detected. In the investigated range, the spectrum resembles that of a middle-G supergiant. The absorption-line spectrum is similar to the spectra of the sun and other late-type stars, but neutral metal lines are weaker than in K and M giants. The level of ionization is significantly higher than in the sun, Zeta Cap, and Epsilon Gem.

Johnson, H. R.↗

Identification of dynamic coefficients of annular turbulent seals

An identification procedure to determine dynamic coefficients of annular turbulent seals in turbopumps is presented. Measurements were carried out at a built test rig with two symmetrical arranged seals. A rigid rotating shaft is surrounded by an elastically supported housing, which is excited by impact forces. The relative radial motion between the rotating parts and the housing, respectively between the seal surfaces, is measured by displacement pick-ups and from the time signals complex frequency response functions can be calculated. Finally an analytical model, depending on the seal parameters, is fitted to the measured data, to find the dynamic coefficients.

Nordmann, R.↗

Identification of dynamic systems, theory and formulation

The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

Maine, R. E.↗

Landform Identification on Radar Images

Polarized radar echo images of the Moon acquired using 3.8 and 70 cm wavelengths were examined to learn more about (1) the relationships between theoretical resolutions of the radars and the sizes of landforms that can be identified and (2) the factors that effect landform identification.

Moore, H. J.↗

On-orbit Systems Identification of Flexible Spacecraft Technol., 1984, Pt. 2 p 465-481

Future spacecraft include configurations which are too flexible to be adequately tested prior to flight and which will require on-orbit systems identification to ensure safe operation of the flight control system. The structural dynamics model will evolve and its accuracy will improve in stages as ground tests of full-scale components and replica-scale models are performed. State Space Modeling and Conditional Maximum Likelihood Parameter Estimation methodology can provide the formal probability-based framework for the process of upgrading a model as additional test results are obtained. Although the number of unknown parameters can be reduced by the use of canonical forms for the stability matrix, the number of unknown model parameters quickly becomes unmanageable unless advantage is taken of the relationship of a much fewer number of global model parameters. Distributed parameter systems or partial differential equation models are one way to take advantage of such global parameters to reduce the number of unknown model parameters.

Taylor, L.↗

A Nonlinear Dual-Adaptive Control Strategy for Identification and Control of Flexible Structures

A technique is presented for obtaining a control law to regulate the modal dynamics and identify the modal parameters of a flexible structure. The method is based on using a min-max performance index to derive a control law which may be considered to be a best compromise between optimum one step control and identification inputs. Features of the approach are demonstrated by a computer simulation of the controlled modal response of a flexible beam.

Thau, F. E.↗

Self-Tuning Adaptive-Controller Using Online Frequency Identification

A real time adaptive controller was designed and tested successfully on a fourth order laboratory dynamic system which features very low structural damping and a noncolocated actuator sensor pair. The controller, implemented in a digital minicomputer, consists of a state estimator, a set of state feedback gains, and a frequency locked loop (FLL) for real time parameter identification. The FLL can detect the closed loop natural frequency of the system being controlled, calculate the mismatch between a plant parameter and its counterpart in the state estimator, and correct the estimator parameter in real time. The adaptation algorithm can correct the controller error and stabilize the system for more than 50% variation in the plant natural frequency, compared with a 10% stability margin in frequency variation for a fixed gain controller having the same performance at the nominal plant condition. After it has locked to the correct plant frequency, the adaptive controller works as well as the fixed gain controller does when there is no parameter mismatch. The very rapid convergence of this adaptive system is demonstrated experimentally, and can also be proven with simple root locus methods.

Chiang, W. W.↗

A Residuals Approach to Filtering, Smoothing and Identification for Static Distributed Systems

An approach for state estimation and identification of spatially distributed parameters embedded in static distributed (elliptic) system models is advanced. The method of maximum likelihood is used to find parameter values that maximize a likelihood functional for the system model, or equivalently, that minimize the negative logarithm of this functional. To find the minimum, a Newton-Raphson search is conducted that from an initial estimate generates a convergent sequence of parameter estimates. For simplicity, a Gauss-Markov approach is used to approximate the Hessian in terms of products of first derivatives. The gradient and approximate Hessian are computed by first arranging the negative log likelihood functional into a form based on the square root factorization of the predicted covariance of the measurement process. The resulting data processing approach, referred to here by the new term of predicted data covariance square root filtering, makes the gradient and approximate Hessian calculations very simple. A closely related set of state estimates is also produced by the maximum likelihood method: smoothed estimates that are optimal in a conditional mean sense and filtered estimates that emerge from the predicted data covariance square root filter.

Rodriguez, G.↗

Identification of unsteady aerodynamics and aeroelastic integro-differential systems

The problem of estimating integro-differential models based on test or simulation data is dealt with. The identification techniques proposed for estimating parameters in models described by differential equations need to be considerably extended to deal with the integral terms. Conditions under which the integral terms may be approximated by algebraic values are discussed. The integro-differential models discussed are related to indicial models proposed by aerodynamicists to describe unsteady flow.

Gupta, N. K.↗

The Tidbinbilla-U.K. Schmidt radio quasar identification program

A program is under way at Tidbinbilla to measure accurate (up to 2 arcsec r.m.s) radio positions for compact sources in the Parkes 2.7 GHz survey south of declination -30 deg. Optical identifications are being made on the basis of radio-optical position coincidence alone, without regard to colour or morphology, using the U.K. Schmidt IIIa-J sky survey to a limiting magnitude of 22.5. This program is aimed at producing an evaluation of the radio quasar redshift distribution with particular emphasis on those objects with redshifts greater than 3.0.

Jauncey, D. L.↗

Cerenkov detectors for cosmic ray telescopes employing the Cerenkov x total energy technique of mass identification

Considerable progress has been made regarding the evolution of the 'Cerenkov x total energy technique' for mass identification of cosmic ray nuclei since the introduction of telescopes employing this technique by Webber et al. (1973). Thus, significant improvements in mass resolution have been made. These improvements are mainly related to the resolution of the Cerenkov counter. The present investigation is, therefore, concerned with the properties of various types of Cerenkov detectors. In addition, a description is provided of the characteristics of a large area (approximately 0.5 sq m-ster) cosmic ray isotope telescope, which is being developed for use on balloons or spacecraft.

Webber, W. R.↗

The application of Legendre-tau approximation to parameter identification for delay and partial differential equations

Approximation schemes based on Legendre-tau approximation are developed for application to parameter identification problem for delay and partial differential equations. The tau method is based on representing the approximate solution as a truncated series of orthonormal functions. The characteristic feature of the Legendre-tau approach is that when the solution to a problem is infinitely differentiable, the rate of convergence is faster than any finite power of 1/N; higher accuracy is thus achieved, making the approach suitable for small N.

Ito, K.↗