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Articles 1 - 5 of 5
Full-Text Articles in Engineering
Two-Photon 3-Dimensional Photoelectrochemical Etching Of Single Crystal Silicon Carbide, Peter Robert Nyholm
Two-Photon 3-Dimensional Photoelectrochemical Etching Of Single Crystal Silicon Carbide, Peter Robert Nyholm
Theses and Dissertations
This thesis presents the first use of a novel direct-write, non-line-of-sight, two-photon photoelectrochemical etching technique for etching of single crystal silicon carbide substrates. The use of this technique has resulted in structuring of 3-dimensional structures in high quality single crystal silicon carbide wafers. The 3-dimensional structures demonstrated cannot be formed by any single or combination of traditional silicon carbide machining techniques. This thesis outlines the development of the optical, electrical, and diagnostic components required to achieve two-photon photoelectrochemical etching in silicon carbide. The diagnostic sub-assemblies --a single pixel confocal detector assembly and an in-situ optical microscope assembly-- and their design …
Inter-Core Interference Mitigation In A Mixed Criticality System, Michael Glenn Hinton
Inter-Core Interference Mitigation In A Mixed Criticality System, Michael Glenn Hinton
Theses and Dissertations
In this thesis, we evaluate how well isolation can be achieved between two virtual machines within a mixed criticality system on a multi-core processor. We achieve this isolation with Jailhouse, an open-source, minimalist hypervisor. We then enhance Jailhouse with core throttling, a technique we use to minimize inter-core interference between VMs. Then, we run workloads with and without core throttling to determine the effect throttling has on interference between a non-real time VM and a real-time VM. We find that Jailhouse provides excellent isolation between VMs even without throttling, and that core throttling suppresses the remaining inter-core interference to a …
Pitch And Thrust Allocation For Full-Flight-Regime Control Of Winged Evtol Uavs, Jacob B. Willis, Randal W. Beard
Pitch And Thrust Allocation For Full-Flight-Regime Control Of Winged Evtol Uavs, Jacob B. Willis, Randal W. Beard
Faculty Publications
Trajectory tracking control for winged eVTOL aircraft is complicated by the high-angle-of-attack aerodynamics experienced during navigational flight occurring immediately after takeoff and immediately before landing. The total energy use of the vehicle can be reduced and the control performance can be improved by appropriately considering the pitch angle of the vehicle in varying flight conditions. We present a review of high-angle-of-attack aerodynamic models as well as an algorithm for finding the optimal pitch and thrust of a winged eVTOL throughout its flight regime. We show simulation results demonstrating a 75% reduction in tracking error over our previous work while maintaining …
Increasing Isolation Between Closely Spaced X-Band Planar Transmit/Receive Antennas, Jacob Bartschi
Increasing Isolation Between Closely Spaced X-Band Planar Transmit/Receive Antennas, Jacob Bartschi
Undergraduate Honors Theses
Coupling between Tx/Rx antennas is a common and much-researched problem that is especially difficult when the antennas both placed close together and on the same plane. New systems with smaller footprints require this kind of placement while still maintaining the same levels of isolation as before. Traditional solutions for coupling involve large and heavy machined parts that are unsuited to compact systems. Many techniques have been proposed over the decades, but few have been applied to X-band antennas in closely spaced configurations. This thesis investigates those techniques, applies them to closely spaced X-band antennas, and compares them to conventional methods …
Analysis Of Feature Extraction In Knee Cartilage Semantic Segmentation Convolutional Neural Networks, Logan Thorneloe
Analysis Of Feature Extraction In Knee Cartilage Semantic Segmentation Convolutional Neural Networks, Logan Thorneloe
Undergraduate Honors Theses
Recent advances in deep learning and convolutional neural networks (CNNs) have shown promise for automatic segmentation in magnetic resonance images. However, because of the stochastic nature of the training process, it is difficult to interpret what information networks learn to represent. This study explores multiple difference metrics between networks to determine semantic relationships between knee cartilage tissues. It explores how differences in learned weights and output activations between networks can be used to express these relationships. These findings are further supported by training multi-class networks to segment multiple tissues to compare network accuracy across different tissue combinations. This study shows …