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At least 19 records

Structural damage assessment as an identification problem

Damage assessment of structural assemblies is treated as an identification problem. A brief review of identification methods is first presented with particular focus on the output error approach. The use of numerical optimization methods in identifying the location and extent of damage in structures is studied. The influence of damage on eigenmode shapes and static displacements is explored as a means of formulating a measure of damage in the structure. Preliminary results obtained in this study are presented and special attention is directed at the shortcomings associated with the nonlinear programming approach to solving the optimization problem.

Hajela, Prabhat↗

Boundary shape identification problems in two-dimensional domains related to thermal testing of materials

The identification of the geometrical structure of the system boundary for a two-dimensional diffusion system is reported. The domain identification problem treated here is converted into an optimization problem based on a fit-to-data criterion and theoretical convergence results for approximate identification techniques are discussed. Results of numerical experiments to demonstrate the efficacy of the theoretical ideas are reported.

Banks, H. T.↗

Boundary shape identification problems in two-dimensional domains related to thermal testing of materials

The identification of the geometrical structure of the system boundary for a two-dimensional diffusion system is reported. The domain identification problem treated here is converted into an optimization problem based on a fit-to-data criterion and theoretical convergence results for approximate identification techniques are discussed. Ressults of numerical experiments to demonstrate the efficacy of the theoretical ideas are reported.

Banks, H. T.↗

Optimal matrix approximants in structural identification

Problems of model correlation and system identification are central in the design, analysis, and control of large space structures. Of the numerous methods that have been proposed, many are based on finding minimal adjustments to a model matrix sufficient to introduce some desirable quality into that matrix. In this work, several of these methods are reviewed, placed in a modern framework, and linked to other previously known ideas in computational linear algebra and optimization. This new framework provides a point of departure for a number of new methods which are introduced here. Significant among these is a method for stiffness matrix adjustment which preserves the sparsity pattern of an original matrix, requires comparatively modest computational resources, and allows robust handling of noisy modal data. Numerical examples are included to illustrate the methods presented herein.

Beattie, C. A.↗

Relationships between digital signal processing and control and estimation theory

Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.

Willsky, A. S.↗

An operational approach to long-duration mission behavioral health and performance factors

NASA's participation in nearly 10 yr of long-duration mission (LDM) training and flight confirms that these missions remain a difficult challenge for astronauts and their medical care providers. The role of the astronaut's crew surgeon is to maximize the astronaut's health throughout all phases of the LDM: preflight, in flight, and postflight. In support of the crew surgeon, the NASA-Johnson Space Center Behavioral Health and Performance Group (JSC-BHPG) has focused on four key factors that can reduce the astronaut's behavioral health and performance. These factors are defined as: sleep and circadian factors; behavioral health factors; psychological adaptation factors; and human-to-system interface (the interface between the astronaut and the mission workplace) factors. Both the crew surgeon and the JSC-BHPG must earn the crewmember's trust preflight to encourage problem identification and problem solving in these four areas. Once on orbit, the crew medical officer becomes a valuable extension of the crew surgeon and BHPG on the ground due to the crew medical officer's constant interaction with crewmembers and preflight training in these four factors. However, the crew surgeon, BHPG, and the crew medical officer need tools that will help predict, prevent, monitor, and respond to developing problems. Objective data become essential when difficult mission termination decisions must be made. The need for behavioral health and performance tool development creates an environment rich for collaboration between operational healthcare providers and researchers. These tools are also a necessary step to safely complete future, more autonomous exploration-class space missions.

Review↗

Managing Risk on the Final Frontier

The National Aeronautics and Space Administration (NASA). Exploration Systems Mission Directorate (ESMD) has combined the Continuous Risk Management (CRM) discipline with innovative knowledge management (KM) practices to more effectively enable the accomplishment of work. CRM enables proactive problem identification and problem solving in the complex world of rocket science. while KM is used to improve this process.

Lengyel, David M.↗

Discrete approximation methods for parameter identification in delay systems

Approximation schemes for parameter identification problems in which the governing state equation is a linear functional differential equation of retarded type are constructed. The basis of the schemes is the replacement of the parameter identification problem having an infinite dimensional state equation by a sequence of approximating parameter identification problems in which the states are given by finite dimensional discrete difference equations. The difference equations are constructed using linear semigroup theory and rational function approximations to the exponential. Sufficient conditions are given for the convergence of solutions to the approximating problems, which can be obtained using conventional methods, to solutions to the original parameter identification problem. Finite difference and spline based schemes using Paderational function approximations to the exponential are constructed, and shown to satisfy the sufficient conditions for convergence. A discussion and analysis of numerical results obtained through the application of the schemes to several examples is included.

Rosen, I. G.↗

A numerical scheme for the identification of hybrid systems describing the vibration of flexible beams with tip bodies

A cubic spline based Galerkin-like method is developed for the identification of a class of hybrid systems which describe the transverse vibration to flexible beams with attached tip bodies. The identification problem is formulated as a least squares fit to data subject to the system dynamics given by a coupled system of ordnary and partial differential equations recast as an abstract evolution equation (AEE) in an appropriate infinite dimensional Hilbert space. Projecting the AEE into spline-based subspaces leads naturally to a sequence of approximating finite dimensional identification problems. The solutions to these problems are shown to exist, are relatively easily computed, and are shown to, in some sense, converge to solutions to the original identification problem. Numerical results for a variety of examples are discussed.

Rosen, I. G.↗

Aerodynamic parameter estimation via Fourier modulating function techniques

Parameter estimation algorithms are developed in the frequency domain for systems modeled by input/output ordinary differential equations. The approach is based on Shinbrot's method of moment functionals utilizing Fourier based modulating functions. Assuming white measurement noises for linear multivariable system models, an adaptive weighted least squares algorithm is developed which approximates a maximum likelihood estimate and cannot be biased by unknown initial or boundary conditions in the data owing to a special property attending Shinbrot-type modulating functions. Application is made to perturbation equation modeling of the longitudinal and lateral dynamics of a high performance aircraft using flight-test data. Comparative studies are included which demonstrate potential advantages of the algorithm relative to some well established techniques for parameter identification. Deterministic least squares extensions of the approach are made to the frequency transfer function identification problem for linear systems and to the parameter identification problem for a class of nonlinear-time-varying differential system models.

Pearson, A. E.↗

Results of piloted simulator studies of fighter aircraft at high angles of attack

The experience gained at the NASA Langley Research Center during the application of simulator techniques to high angle of attack flight conditions for several current fighters is discussed. The discussion includes (1) the simulator hardware, (2) requirements for static and dynamic aerodynamic data inputs, (3) evaluation procedures, (4) correlation with flight, and (5) the effects of dynamic stability parameters. Results obtained with the simulator technique have correlated well with flight test experience, resulting in early identification of potential problems, identification of critical flight conditions, and solutions to various deficiencies in stability and control characteristics. Dynamic stability parameters, results indicate that certain parameters can have a large influence on the flying qualities and tactical effectiveness of fighters at high angles of attack.

Chambers, J. R.↗

Galerkin approximation for inverse problems for nonautonomous nonlinear distributed systems

An abstract framework and convergence theory is developed for Galerkin approximation for inverse problems involving the identification of nonautonomous nonlinear distributed parameter systems. A set of relatively easily verified conditions is provided which are sufficient to guarantee the existence of optimal solutions and their approximation by a sequence of solutions to a sequence of approximating finite dimensional identification problems. The approach is based on the theory of monotone operators in Banach spaces and is applicable to a reasonably broad class of nonlinear distributed systems. Operator theoretic and variational techniques are used to establish a fundamental convergence result. An example involving evolution systems with dynamics described by nonstationary quasilinear elliptic operators along with some applications are presented and discussed.

Banks, H. T.↗

An Interactive MATLAB Program for Fitting Transfer Functions to Frequency Responses

A computer program called FRFit (Frequency Response Fitting) for matching single-input single-output (SISO) transfer function models to empirical frequency response data is described. The program was written in MATLAB and has a graphical user interface (GUI). It is interactive in that the user manually builds the transfer function model using ``elementary factors'' (gain, delay, differentiators and integrators, and first- and second-order poles and zeros) and adjusts their values with sliders or entry fields. A nonlinear optimization can also be used to determine maximum-likelihood estimates of the transfer function parameters and their associated uncertainties. The program has some usefulness as a teaching aid, and can be applied to model structure determination, reduced-order modeling, preliminary analysis, and other system identification problems. FRFit is demonstrated using example problems, including the identification of aircraft transfer functions and rational function approximations of Theodorsen's function.

Frequency response↗

Parameter identification methods for improving structural dynamic models

There is an increasing need to develop Parameter Identification methods for improving structural dynamic models, based on the inability of engineers to produce mathematical models which correlate with experimental data. This research explores the efficiency of combining Component Mode Synthesis (substructuring) methods with Parameter Identification procedures in order to improve analytical modeling of structural components and their connections. Improvements are computed in terms of physical stiffness and damping parameters in order that the physical characteristics of the model can be better understood. Connections involving both viscous and friction damping are investigated. Substructuring methods are utilized to reduce the complexity of the identification problem. Component and inter-component structural connection properties are evaluated and identified independently, thus simplifying the identification problem. It is shown that modal test data is effective for identifying modeling problems associated with structural components, and for determining the stiffness and damping properties of intercomponent connections. In general, Parameter Identification is improved when greater quantities of experimental data are available.

Lawrence, Charles↗

New approximation of frequency response for structural synthesis and parameter identification

This paper presents two approaches that will improve the accuracy of explicit approximations of frequency responses. They are important components of structural design optimization and system identification. The first is a product form approximation that improves approximated frequency responses near resonant conditions. This approach is applicable to both design optimization and system identification problems. The second is aimed at improving the computed sensitivity coefficients that are used to solve system identification problems.

Miura, Hirokazu↗