<p> In this study the researcher provides a behavioral framework for managing massive airline flight disruptions (MAFD) in the United States. Under conditions of MAFD, multiple flights are disrupted throughout the airline's route network, customer service is negatively affected, additional costs are created for airlines, and governments intervene. This study is different from other studies relating to MAFD that have focused on the operational, technical, economic, financial, and customer service impacts. The researcher argues that airlines could improve the management of events that led to MAFD by applying the principles of crisis management where the entire organization is mobilized, rather than one department, adapting organization development (OD) interventions to implement change and organization learning (OL) processes to create culture of innovation, resulting in sustainable improvement in customer service, cost reductions, and mitigation of government intervention. At the intersection of crisis management, OD, and OL, the researcher has developed a new conceptual framework that enhances the resiliency of individuals and organizations in responding to unexpected-yet-recurring crises (e.g., MAFD) that impact operations. The researcher has adapted and augmented Lalonde's framework for managing crises through OD interventions by including OL processes. The OD interventions, coupled with OL, provide a framework for airline leaders to manage more effectively events that result in MAFD with the goal of improving passenger satisfaction, reducing costs, and preventing further government intervention. Further research is warranted to apply this conceptual framework to unexpected-yet-recurring crises that affect operations in other industries.</p>

The increasing use of artificial neural networks and other connectionist systems in engineering, and the advantages obtained from that use, motivated the development of an approach wherein a single or multiple input feedforward artificial neural network with piecewise linear hard limit transfer functions could be directly "constructed." By viewing the network as a function approximator, algebraic constraint equations for the input and bias weights were derived which transformed the mathematical character of the net into one amenable to rigorous analysis without changing the architecture. Further application of the method of weighted residuals allowed direct solution for the output weights without any training. Ordinary and partial differential equations were solved using this method and the resulting accuracy and reliability verified. Further extension of this research will hopefully lead to the creation of adaptive engineering systems able to incorporate both governing equations and experimental data.

A multi-segment robot is developed as a concept for use in space based construction operations. The multi-segment robot is envisioned as a member of a class of large space robots, or space cranes, used in the assembly of advanced spacecraft. The problems that arise when the requisite robot size becomes large are explored. The unique capabilities of the multi-segment robot are discussed. The multi-segment robot involves a collection of common bodies, or segments, that are pinned together to form a snake-like, or train, configuration. A degree of freedom representing rotation is retained at each pinned connection. Reaction flywheels are suspended within each segment and provide the control necessary to position each body segment. Algorithms are developed to position this serpentine robot to a prescribed location and orientation. The first algorithm is used to compute a general shape, based on a constrained polynomial function, that locates the robot tip at the proper position. Next, an algorithm is developed that is used to position the discrete bodies along the shape function and determines their relative positions. This information is used as the target values in a control system that uses the reaction flywheels to position each body into the desired relative position. An n-body simulation program is developed based on Newton-Euler equations of motion for the robot. The simulation is used to develop the robot control strategy, to verify its performance, and to size prototype hardware. Two cases are analyzed to investigate the dexterity of the proposed configuration. Robot design issues are explored as they relate to the multi-segment robot. A prototype system is designed, fabricated, and tested. Motion tests are included that compare experimental results with pertinent analytical predictions. Collectively, the present study demonstrates the viability of the proposed concept for addressing the unique problems associated with large robotic operations in space.

This dissertation introduces a novel method of teleoperation of complex anthropomorphic robotic hands: converting the myoelectric signal generated by an operator's muscles during movement into robot commands replicating the motion. This teleoperation scenario is, in a sense, the limiting case of myoelectric prosthetic hand control. This project contributes to implementation of a practical myoelectric teleoperation system and improved prosthetic hand control by analyzing the myoelectric spectrum's variation during thumb motions. The investigation applies a new spectral estimation approach, Thomson's multiple window method (MWM), to the myoelectric signal. The MWM estimate has much lower bias and variance than traditional periodogram estimates, making it a better candidate to compute motion classification features. The MWM is also less sensitive to motion artifact than autoregressive methods. Extending Thomson's MWM into a time-frequency analysis tool analogous to the short-time Fourier transform, here called the short-time Thomson transform, shows that the myoelectric signal may be more stationary than previously thought. This project includes development of a unique myoelectric data collection system (MDCS) and a myoelectric teleoperation demonstration system (MTDS). The MDCS allows simultaneous measurement of 16 hand joint motions and 8 myoelectric signals. This capability enables close alignment of myoelectric signatures in time based on the hand motions and a search for motion-specific temporal characteristics in the myoelectric signal. While this study yields little evidence of motion-specific temporal consistency, it shows promising motion-specific spectral consistency. Spectral analysis proves less sensitive to alignment uncertainties than temporal analysis. An evaluation of five techniques for finding a motion's starting point in the myoelectric signal, a major implementation concern, suggests that we not pursue alignment-sensitive myoelectric control algorithms. Finally, the MTDS is used to demonstrate myoelectric control of chuck and key grasp motions of NASA/JSC's Utah/MIT Dextrous Hand, realtime, with 90% accuracy. The demonstration uses the time-varying myoelectric spectrum estimated with short-time Fourier transforms; however, this project lays the foundation for using the superior short-time Thomson transforms in this application.

Piloting and many related control activities, especially remote manipulation via teleoperations and robotics, stand to benefit substantially from better means of communication between controller and controlled. We have investigated one such approach: the use of augmented displays on a cathode ray terminal (CRT) for controlling simulated motion in microgravity. Such displays, which have been shown to be highly effective in a variety of applications, provide information to the operator which goes beyond that which is found in nature, and thereby emphasize important aspects of a task and minimize irrelevant ones. Using this approach, we attempted to develop stylized graphical displays, incorporating augmented feedback by distorting the background of the scene under display, for purposes of flight control and/or control of a robotic arm. Besides attempting to utilize transformations of the scene itself for informational purposes, the displays we developed represent significant departures from previous methods in two notable respects. First we have attempted to design our instrumentation to make use of peripheral rather than exclusively foveal vision, thus broadening the bandwidth of perception by vision. Second, we attempted to incorporate optical illusions intended to enhance the perception of depth and apparent motion to provide better and more compelling feedback for the operator performing the task. Data from a small group of subjects suggest that the illusion of depth produced significantly better performance in that this was faster, had fewer errors, and interfered less with a secondary task (all correlations were significant, with p $<$.0001), while the main effect for peripheral vision was not significant but other evidence suggests it improved performance nonetheless. A second experiment indicated that while pilots' acquisition of task skills differed significantly from nonpilots' (p =.00078), optical illusions augmenting the effect of depth and of motion induced profound differences in performance (p =.000006), although masked by practice effects, etc., and in control motion (p =.000006) where this augmented feedback eliminated any tendency to overcontrol in pilots and nonpilots both.

This thesis provides first an introduction to an area of continuum mechanics the author terms multibody mechanics. Therein, a continuum is separated into a finite number of bodies. By merging ideas from classical and multibody dynamics with contemporary rational mechanics, approximate methods such as the finite element method and substructuring techniques are presented as natural approximation schemes of the differential equations generated. When such approximations are done for each body, which are in turn connected to form a system, differential-algebraic equations with index three result. The difficulty in solving index three differential-algebraic equations is demonstrated with a simple example and alternative strategies are discussed. In most situations, the alternatives either destroy the natural sparse structure of the matrices or employ artificial techniques to control constraint drift. For flexible bodies, the benefits of using the residual flexibility method are demonstrated. The method naturally retains the sparse (mostly diagonal) matrix structures while also resulting in differential-algebraic equations with index one. As is well-known, the numerical solution of index one equations is more easily accomplished than that of equations with a higher index. Therefore, the residual flexibility method represents a remarkable approach for not only modeling the flexibility but also reducing the index of the governing differential-algebraic equations.

A stochastic model for predicting the lifetime of composite laminates subjected to multiaxial fatigue loading is proposed. The model is based on the application of Markov chains to the well known "critical element" model for the fatigue of composite laminates. The model considers the accumulation of fatigue damage as an evolutionary random process characterized by changes in the global compliance of a laminate. These changes are modeled as nonstationary, discrete time, discrete state Markov processes (Markov chains) utilizing stationary Markov chains and polynomial transformations of their indexing parameters. The stationary Markov chains are developed on the assumption of "equivalent damage". Their parameters are determined from experimental data. The Markov chain models yield full cycle dependent probability distributions for the changes in laminate compliance. These changes and their respective distributions are used as input into a mechanical analysis to determine the stresses on the life controlling critical elements of a laminate. The stresses on the critical elements and their derived probability distributions are used in turn to predict the lifetime of a laminate based on Markov chain models of the fatigue behavior of the critical elements. The predictive capability of the proposed model is demonstrated by comparison with experimental results.

Equations of motion for flexible multibody systems with model uncertainty are developed using the Lagrangian formulation. The dynamic model developed serves to exemplify systems which possess undesirable flexibility by representing it as a stochastic process. Further, a novel methodology for treating uncertainties in flexible systems is proposed. The method uses concepts from stochastic finite elements to address the problem of uncertain parameters in flexible mechanical systems. In particular, the problem of random bending rigidity of a flexible beam is studied. The spatial random process is represented using the Karhunen-Loeve expansion. The response process of the beam, comprising of large rotation and elastic vibration is expressed as a projection on the Homogeneous Chaos. Expressions for the response statistics, including the coupling between the elastic vibration and the large displacements are derived. Comparison of the results obtained with those from Monte-Carlo simulation shows a fair amount of agreement.

A simulation technique is described which directly synthesizes the extrema of a random process and is more efficient than the Gaussian simulation method. Such a technique is particularly useful in stochastic fatigue analysis because the required stress range moment, E(R$\sp{\rm m}$), is a function only of the extrema of the random stress process. The family of autoregressive moving average (ARMA) models is reviewed and an autoregressive model is presented for modeling the extrema of any random process which has a unimodal power spectral density (psd). The proposed autoregressive technique is found to produce rainflow stress range moments which compare favorably with those computed by the Gaussian technique and to average 11.7 times faster than the Gaussian technique. The autoregressive technique is also adapted for processes having bimodal psd's. The adaptation involves using two autoregressive processes to simulate the extrema due to each mode and the superposition of these two extrema sequences. The proposed autoregressive superposition technique is found to be 9 to 13 times faster than the Gaussian technique and to produce comparable values for E(R$\sp{\rm m}$) for bimodal psd's having the frequency of one mode at least 2.5 times that of the other mode. A key parameter in the autoregressive model is the correlation coefficient $\rho\sb1$ between adjacent extrema. A linear regression of $\rho\sb1$ on Vanmarcke's bandwidth parameter is presented as a practical description of $\rho\sb1$'s dependence on bandwidth for both unimodal and bimodal psd's. The effect of psd shape on the expected fatigue damage rate is also investigated. For bimodal psd's, the contribution of the two frequency components to the damage rate is determined for frequency ratios from 1.5 to 15. The relative contribution of the two modes is measured by a parameter b which is the ratio of the mean squared value of the high frequency component to that of the other component. It is found that both components must be considered for b values from 0.01 to 10. The effect of high frequency truncation of the psd on the expected damage rate is also studied for two unimodal psd's.

A reduced-order modal energy (ROME) technique for spectrum estimation is introduced. In this technique the transfer function of a higher-order autoregressive (AR) model of a power spectrum is decomposed into partial fractions. These individual fractions are examined from the perspective of relative significance to the total energy of the system. First, the technique is formulated for a scalar random process (the univariate case). In the derivation, two solution procedures are discussed. In one procedure, a system of equations is solved to determine the unknown numerator coefficients of the partial fraction expansion. In the second procedure, a unique approach is used which yields each numerator coefficient directly, avoids solving a system of equations, and greatly reduces the requisite computation time. Next, the reduced-order modal energy technique is formulated for a vector random process (the multivariate case); it provides a parsimonious estimate of the power spectral density by capturing frequencies associated with significant spectral values. Numerical examples involving short data sequences, Space Shuttle acceleration data, and sunspot and temperature measurements are presented which demonstrate the usefulness of the technique.