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An Empirical Prediction Model Of The Performance Impacts Of Material Tolerances In Frequency Selective Surfaces Using The Monte Carlo Method, Matthew D. Craig
An Empirical Prediction Model Of The Performance Impacts Of Material Tolerances In Frequency Selective Surfaces Using The Monte Carlo Method, Matthew D. Craig
Theses and Dissertations
Standard computational tools predicting frequency selective surface (FSS) performance model periodic structures as an infinite-by-infinite array of perfectly placed elements with perfect, identical dimensions, and with dielectric layers of uniform thickness and material composition. These models do not address perturbations caused by manufacturing tolerances of elements and dielectric layers, nor do they address edge effects caused by finite-by-finite dimensional arrays. The Monte Carlo Method was used to determine the effects of random variations in element dimension, placement, dielectric thickness, and dielectric material on FSS performance. A full-factorial experimental design was applied, and eight hundred twenty-five unique finite arrays of elements …
A Statistical Analysis Of Space Structure Mode Localization, Amy M. Cox
A Statistical Analysis Of Space Structure Mode Localization, Amy M. Cox
Theses and Dissertations
Cyclic structures, such as antenna arrays, multi-bay trusses, and compressor blades, are significantly impacted by slight changes to system periodicity. Manufacturing errors of 5% or less can result in drastic changes to a structure's modal behavior. This change in modal behavior is significant, since it may result in the focusing of modal energy to individual substructures of the system. Poor modal identification can result in poorly designed control systems, resulting in shape control and pointing issues for space antennae. Additionally, modal energy localization may damage individual system components due to unanticipated levels of cyclic loading, leading to high cycle fatigue.
Loop Gain Estimation For Adaptive Control, Jamey P. Sillence
Loop Gain Estimation For Adaptive Control, Jamey P. Sillence
Theses and Dissertations
The identification of a linear discrete-time control system's loop gain is addressed. The classical Kalman filter theory for state estimation in linear control systems is extended, and the control system's loop gain and state are jointly estimated. A rigorous analysis of the measurement situation under consideration yields explicit formulae for the loop gain's unbiased estimate and estimation error's covariance.