Study of an instrument for sensing errors in a telescope wavefront

Focal plane sensors for determining the error in a telescope wavefront were investigated. The construction of three candidate test instruments and their evaluation in terms of small wavefront error aberration measurements are described. A laboratory wavefront simulator was designed and fabricated to evaluate the test instruments. The laboratory wavefront error simulator was used to evaluate three tests; a Hartmann test, a polarization shearing interferometer test, and an interferometric Zernike test

Extraction of the second-order nonlinear response from model test data in random seas and comparison of the Gaussian and non-Gaussian models

This study presents the results of an extraction of the 2nd-order nonlinear responses from model test data. Emphasis is given on the effects of assumptions made for the Gaussian and non-Gaussian input on the estimation of the 2nd-order response, employing the quadratic Volterra model. The effects of sea severity and data length on the estimation of response are also investigated at the same time. The data sets used in this study are surge forces on a fixed barge, a surge motion of a compliant mini TLP (Tension Leg Platform), and surge forces on a fixed and truncated column. Sea states are used from rough sea (Hs=3m) to high sea (Hs=9m) for a barge case, very rough sea (Hs=3.9m) for a mini TLP, and phenomenal sea (Hs=15m) for a truncated column. After the estimation of the response functions, the outputs are reconstructed and the 2nd order nonlinear responses are extracted with all the QTF distributed in the entire bifrequency domain. The reconstituted time series are compared with the experiment in both the time and frequency domains. For the effects of data length on the estimation of the response functions, 3, 15, and 40- hour data were investigated for a barge, but 3-hour data was used for a mini TLP and a fixed and truncated column due to lack of long data. The effects of sea severity on the estimation of the response functions are found in both methods. The non-Gaussian method for estimation is more affected by data length than the Gaussian method

Fault-Tolerant Flight Control Using One Aerodynamic Control Surface

University of Minnesota Ph.D. dissertation. June 2018. Major: Aerospace Engineering and Mechanics. Advisor: Peter Seiler. 1 computer file (PDF); xiii, 291 pages.Small unmanned aircraft systems (UAS) have recently found increasing civilian and commercial applications. On-board fault management is one of several technical challenges facing their widespread use. The aerodynamic control surfaces of a fixed-wing UAS perform the safety-critical functions of stabilizing and controlling the aircraft. Failures in one or more of these surfaces, or the actuators controlling them, may be managed by repurposing the other control surfaces and/or propulsive devices. A natural question arises in this context: What is the minimum number of control surfaces required to adequately control a handicapped aircraft? The answer, in general, depends on the control surface layout of the aircraft under consideration. For some aircraft, however, the answer is one. If the UAS is equipped with only two control surfaces, such as the one considered in this thesis, then this limiting case is reached with a single control surface failure. This thesis demonstrates, via multiple flight tests, the autonomous landing of a UAS using only one aerodynamic control surface and the throttle. In seeking to arrive at these demonstrations, this thesis makes advances in the areas of model-based fault diagnosis and fault-tolerant control. Specifically, a new convex method is developed for synthesizing robust output estimators for continuous-time, uncertain, gridded, linear parameter-varying systems. This method is subsequently used to design the fault diagnosis algorithm. The detection time requirement of this algorithm is established using concepts from loss-of-control. The fault-tolerant controller is designed to operate the single control surface for lateral control and the throttle for total energy control. The fault diagnosis algorithm and the fault-tolerant controller are both designed using a model of the aircraft. This model is first developed using physics-based first-principles and then updated using system identification experiments. Since this aircraft does not have a rudder, the identification of the lateral-directional dynamics requires some novelty

Applicability of Bispectral Analysis to Unstable Plasma Waves

A program to implement a spectral analysis technique called the bispectrum was written and tested with computer generated time series data. The application of the algorithm to the study of nonlinear interactions was demonstrated by a comparison of computed quantities with results from model equations found in the literature. Specifically determined were: the amplitude and phase of coupling coefficients, the power transfer function, the fraction of power associated with nonlinear coupling, and the identification of waves involved in a quadratic coupling interaction. A method of distinguishing the two parent waves from the daughter wave in this three-wave interaction is proposed as a new application of the technique. These results, as well as the values computed from a Monte Carlo simulation of plasma turbulence were found to be consistent with expectations. Two experimental systems were investigated with the bispectrum. One was the periodically pulled time series data of a driven van der Pol oscillator (unijunction transistor circuit) which contained significant bispectral features but no real evidence of quadratic coupling. The other was plasma fluctuation data from the WVU-Q Machine, where the inhomogeneous energy-density driven mode exhibited a degree of coupling to lower frequencies that was absent in the case of the current driven mode

Simulation of vertical ship responses in high seas

This research was done to study the effect of sea severity on the vertical ship responses like heave and pitch. Model testing of a 175m moored container ship with zero heading speed was done for different sea states varying from very rough to very high seas. Transfer functions were extracted using Volterra model which constitutes both linear and quadratic part. The experimental linear transfer functions were calculated using Volterra linear model and were compared with linear transfer function from the hydrodynamic theory. Experimental second order transfer functions were also extracted using Volterra quadratic model and their behavior was studied for different sea states. After the extraction of linear and second order transfer functions total responses were reconstructed and compared with the measured responses. This also helped to investigate the contribution of second order part to the total vertical ship responses. In the last stage of the research a new semi- empirical method was developed called as ‘UNIOM’ for the prediction of the responses. Laboratory input waves and theoretical LTFs were used for the simulation of ship response and these were compared with measured responses

Doctor of Philosophy

dissertationWith the ever-increasing amount of available computing resources and sensing devices, a wide variety of high-dimensional datasets are being produced in numerous fields. The complexity and increasing popularity of these data have led to new challenges and opportunities in visualization. Since most display devices are limited to communication through two-dimensional (2D) images, many visualization methods rely on 2D projections to express high-dimensional information. Such a reduction of dimension leads to an explosion in the number of 2D representations required to visualize high-dimensional spaces, each giving a glimpse of the high-dimensional information. As a result, one of the most important challenges in visualizing high-dimensional datasets is the automatic filtration and summarization of the large exploration space consisting of all 2D projections. In this dissertation, a new type of algorithm is introduced to reduce the exploration space that identifies a small set of projections that capture the intrinsic structure of high-dimensional data. In addition, a general framework for summarizing the structure of quality measures in the space of all linear 2D projections is presented. However, identifying the representative or informative projections is only part of the challenge. Due to the high-dimensional nature of these datasets, obtaining insights and arriving at conclusions based solely on 2D representations are limited and prone to error. How to interpret the inaccuracies and resolve the ambiguity in the 2D projections is the other half of the puzzle. This dissertation introduces projection distortion error measures and interactive manipulation schemes that allow the understanding of high-dimensional structures via data manipulation in 2D projections

Solving inverse problems for medical applications

It is essential to have an accurate feedback system to improve the navigation of surgical tools. This thesis investigates how to solve inverse problems using the example of two medical prototypes. The first aims to detect the Sentinel Lymph Node (SLN) during the biopsy. This will allow the surgeon to remove the SLN with a small incision, reducing trauma to the patient. The second investigates how to extract depth and tissue characteristic information during bone ablation using the emitted acoustic wave. We solved inverse problems to find our desired solution. For this purpose, we investigated three approaches: In Chapter 3, we had a good simulation of the forward problem; namely, we used a fingerprinting algorithm. Therefore, we compared the measurement with the simulations of the forward problem, and the simulation that was most similar to the measurement was a good approximation. To do so, we used a dictionary of solutions, which has a high computational speed. However, depending on how fine the grid is, it takes a long time to simulate all the solutions of the forward problem. Therefore, a lot of memory is needed to access the dictionary. In Chapter 4, we examined the Adaptive Eigenspace method for solving the Helmholtz equation (Fourier transformed wave equation). Here we used a Conjugate quasi-Newton (CqN) algorithm. We solved the Helmholtz equation and reconstructed the source shape and the medium velocity by using the acoustic wave at the boundary of the area of interest. We accomplished this in a 2D model. We note, that the computation for the 3D model was very long and expensive. In addition, we simplified some conditions and could not confirm the results of our simulations in an ex-vivo experiment. In Chapter 5, we developed a different approach. We conducted multiple experiments and acquired many acoustic measurements during the ablation process. Then we trained a Neural Network (NN) to predict the ablation depth in an end-to-end model. The computational cost of predicting the depth is relatively low once the training is complete. An end-to-end network requires almost no pre-processing. However, there were some drawbacks, e.g., it is cumbersome to obtain the ground truth. This thesis has investigated several approaches to solving inverse problems in medical applications. From Chapter 3 we conclude that if the forward problem is well known, we can drastically improve the speed of the algorithm by using the fingerprinting algorithm. This is ideal for reconstructing a position or using it as a first guess for more complex reconstructions. The conclusion of Chapter 4 is that we can drastically reduce the number of unknown parameters using Adaptive Eigenspace method. In addition, we were able to reconstruct the medium velocity and the acoustic wave generator. However, the model is expensive for 3D simulations. Also, the number of transducers required for the setup was not applicable to our intended setup. In Chapter 5 we found a correlation between the depth of the laser cut and the acoustic wave using only a single air-coupled transducer. This encourages further investigation to characterize the tissue during the ablation process