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Prediction of Wake Flows Induced by an Offshore Wind Turbine Foundation: Understanding its Environmental Impact - Phase 2: Floating Platforms
(2026) Shendokar, Yash Vijay
The deployment of Floating Offshore Wind Turbine(s) (FOWTs) requires methods to evaluate their hydrodynamic response and wake characteristics. This thesis ap plies the Immersed Boundary Method (IBM), implemented as the Virtual Body Method (VBM) in Simcenter STAR-CCM+, to simulate the UMaine VolturnUS-S semi-submersible platform. The methodology was validated against the dynamic Fluid-Body Interaction (DFBI) with overset meshing technique. For a 2D floating box in waves, the VBM reproduced heave and pitch natural periods with differences of 0.65% and 0.24%, respectively, while surge exhibited a 12% deviation. In 3D free-decay simulations of the UMaine VolturnUS-S foundation, the platform’s heave natural period agreed within 0.73%, whereas the pitch period deviated by 0.22% . Even with noticeable deviations, this VBM notably reduced computational costs by nearly 40% in core-hours per million elements for free decay case, when com pared to the DFBI cases with overset meshing. Applying the validated framework to full-scale conditions, multiphase simulations of the platform in a thermally strat ified environment were conducted. The results demonstrated that the multi-column structure generates a complex near-wake recirculation zone with persistent flow re versal. Thermal mixing was predominantly observed near the surface, resulting in a maximum mean temperature increase by 5.82K at a depth of 3.83m below the free surface, with mixing effects decaying rapidly in deeper waters. The findings validate the VBM as a functional fixed-grid alternative for simulating platform kinemat ics and provide a baseline for future environmental wake investigations involving FOWTs.
Static Complex-Response Characterization of Selected ZCU216 RFSoC Loopback Paths at 3 GHz
(2026) Mashayekhi, Nick
Modern wireless communication systems, particularly 5G networks and radar applications, demand exceptional hardware performance to meet increasing data-rate requirements and to support complex modulation schemes. Practical implementations inevitably suffer from hardware imperfections, including non-linear characteristics in digital-to-analog converters (DACs) and analog-to-digital converters (ADCs), which degrade signal fidelity. While advanced spatial processing techniques such as digital beamforming provide the overarching motivation for understanding these impairments, the fundamental prerequisite is a rigorous static characterization of the data converters themselves. This thesis characterizes the static complex-response of selected loopback paths on the AMD Xilinx Zynq UltraScale+ ZCU216 RFSoC development board operating at a single-tone frequency of 3 GHz. The completed work comprises single-tone end-to-end loopback measurements of seven distinct DAC-to-ADC paths, the generation of a 28 × 16 two-dimensional full LHS map for a single selected path, and the development of a forward GPR interpolation model using MATLAB programming language. It is explicitly noted that the measurements represent the complete uncalibrated DAC-to-ADC loopback cascade, encapsulating analog interfaces, cables, timing, and software processing. The thesis establishes a forward interpolation model and provides quantifiable metrics on amplitude and phase response deviations. No inverse digital pre-distortion was implemented, nor was beamforming or communication-link performance evaluated. This work provides the foundational mathematical forward-modeling framework necessary for future hardware imperfection mitigation.
Developing and testing a palm-sized shaking energy harvesting device
(2026) Dinh, Duc Thinh
In the development of technology today, the energy problem remains one of the most challenging issues that electrical engineers must carefully consider. Although people use electricity daily, generating it is a relatively unfamiliar concept to those outside the engineering field. To raise awareness of this issue, the idea of creating a simple, compact power generator has emerged. One objective was to make the principle sufficiently accessible to be demonstrated and understood by younger students, while also investigating its potential for small-scale energy generation and storage. Improving understanding of energy generators for the next generation could open another potential for energy technology. The project investigated the feasibility of converting human-generated mechanical motion into electrical energy using a compact vibration-based electromagnetic energy harvester. The system was based on Faraday's law of electromagnetic induction, in which a permanent magnet moved axially inside a copper coil during manual shaking. A numerical model was developed in MATLAB to calculate the magnetic field, magnetic flux linkage, induced voltage, and generated current. Electromagnetic behavior was also simulated using COMSOL Multiphysics and ANSYS Electronics Desktop, while LTspice was used to investigate the Schottky bridge rectifier and capacitor-smoothing circuit. A physical bench prototype consisting of the magnet-coil generator, rectification and filtering circuit, TP4056 charging module, and 18650 lithium-ion battery were constructed and experimentally tested. The constructed system remained a bench prototype and was not developed into a complete enclosed palm-sized product suitable for use by children. Experimental measurements showed that the electrical output was intermittent and strongly dependent on the speed and consistency of manual shaking. The TP4056 charging indication and the measured positive battery-side current showed that current was transferred toward the battery during operation. However, a complete battery charge or a controlled long-term increase in battery state of charge was not quantitatively demonstrated. At the measured mean battery-side current of 0.2625 mA, the ideal constant-current equivalent charging time for a nominal 2600 mAh battery is approximately 9905 hours. This is not an experimentally demonstrated charging time and excludes the intermittency of manual shaking, conversion losses, and the battery-charging profile. The developed prototype demonstrated the feasibility and educational value of shaking-based energy harvesting, while the limited output power remained an important area for future improvement.
Structural Evaluation of Defects in Bolt Hole Threads
(2026) Mohamed Habibullah, Abdul Basit
Threaded bolted joints are a critical fastening method in aerospace engineering, used to connect structural components under demanding mechanical and thermal conditions. In many of the assemblies manufactured at GKN Aerospace, bolts are installed directly into tapped holes machined into large, high-value components — without the use of nuts. This thesis focuses on a component called the Intermediate Case (IMC), produced from cast titanium alloy Ti-6Al-4V (Ti-64). The bolts are fabricated from Inconel 718 (IN-718), with a thread specification of .3125-24 UNJF-3A (Unified National Joint Fine). Because the threaded holes are integral to the parent components, any damage or defect renders replacement extremely difficult and costly. Thread defects can arise at various stages of a component's lifecycle, including manufacturing, installation, maintenance, and handling. Currently, GKN Aerospace evaluates such defects using a conservative approach in which the defect is assumed to behave as a pre-existing crack. Crack propagation and fatigue life analyses are subsequently performed using linear elastic fracture mechanics. While this method ensures structural safety, it frequently leads to the rejection of components that may still be structurally serviceable, resulting in unnecessary material waste, increased costs, and extended maintenance downtime. This thesis aims to develop a more realistic and less conservative methodology for evaluating defects in bolt hole threads. The approach involves explicitly incorporating defect geometry into finite element models rather than relying on simplified stress concentration factors and crack assumptions. Numerical simulations are carried out using software tools including Siemens NX and ANSYS. The study encompasses a systematic classification of defects, followed by targeted simulation and evaluation for each defect. The findings are intended to support more informed maintenance decision-making at GKN Aerospace, helping to distinguish between components that require removal from service and those that can safely continue in operation. The outcomes of this work are expected to contribute to improved safety assessment practices while reducing unnecessary conservatism in defect evaluation, thereby minimising operational costs and material waste in aerospace maintenance.
Defect-aware 3D Geometry Reconstruction from 2D Annotations and 3D Scan Data
(2026) Halwai, Abhishek; Ponkshe, Durvesh
Components produced through additive manufacturing require particular methods of inspection to locate and characterize surface defects on those components. Although 2D image-based defect detection is an accepted method, linking that 2D defect information to the 3D geometry of the part by reconstructing the location and severity of the defect-induced deformation of the 3D surface is challenging with limited 3D scan data and the absence of certified 3D reference geometry. This gap between 2D defect annotation and 3D defect geometry motivates this thesis. This master’s thesis develops and analyzes a pipeline that projects 2D defect annotations onto a nominal 3D CAD model to reconstruct defect-aware 3D geometry with the help of structured-light scan data from the 3D-ADAM dataset. The pipeline projects 2D defect masks to 3D nominal surface points through the sensor’s organized point cloud, registers each PLY scan to the nominal CAD, computes the signed deviation between defective and nominal scans, and finally reconstructs the defect on the CAD model in the form of a point cloud, a mesh, and a deviation map. The thesis also explores the possibility of predicting defect deviation directly on the nominal CAD using a PointNet++ model. A geometry-only formulation shows significant limitations in predicting deviation magnitude and sign as this information is unavailable in the nominal geometry. After additionally providing a coarse 2D heatmap of the deviation as input, the magnitude prediction error was reduced by around 28% relative to the geometry-only model and 36% relative to the class-average baseline, and the direction of deviation was also recovered. The accuracy of defect placement onto the 3D surface is bounded by single-view registration and partially unresolved mirror ambiguity. This thesis validates the scan-based defect mapping and reconstruction pipeline, and describes the information required to predict defect deviation. Furthermore, this thesis identifies RGB-based defect prediction to reduce reliance on the 3D scan at inference as the key direction for future research.