Date of Award

June 2021

Degree Type


Degree Name

Doctor of Philosophy



First Advisor

Ryoichi S Amano

Committee Members

John R Reisel, Deyang Qu, Wilkistar A Otieno, Istvan G Lauko


Cavitation, Hybrid optimization of multiple energy resources, Hydrofoil, Renewables, Solar Power, Wind Energy


The optimization of turbines hydrofoils is to improve the efficiency and lifetime of the hydro turbines. Air treatment is one of the methods to reduce the cavitation effect and improve hydro turbines performance. It is necessary to utilize Computational Fluid Dynamics (CFD) analysis and to generate cavitation at different Angle of Attack (AoA) for the hydrofoil and test a variety of designs of air injection slots through the hydrofoil to optimize the best design. StarCCM+ software is used for CFD simulations. The hydrofoil is tested in a square water tunnel with water entering the tunnel at different velocities for each AoA ranges from 9.1 m/s to 12.2 m/s. While the cavitation can be identified by a unique number (Averaged Vapor Volume Fraction), the work done created an inverse correlation between this number and the cavitation number at the same AoA. The validation and comparison were accomplished through three steps: visual validation, CFD simulation results, and image processing. The VVF scenes and high-speed camera images were compared and validated, visually, the cavitation behavior and pattern. The image processing confirmed the percentages of the cavitation area, numerically and experimentally, with almost matching values.

The cavitation behavior was observed first without aeration, then followed by air injection simulations to investigate the effect of aeration. The air was introduced at 101.3 kPa (0 psig) at AoA of 0, 6, 9, and 12 degrees. The Vapor Volume Fraction (VVF) and the output mechanical power were monitored throughout the simulations. The data acquired from the simulations were compared for both 6 and 3 air slots over the hydrofoil. It was observed that the cavitation was mitigated in the computer simulations reaching up to 97.9% as an average reduction for the 6 air slots, while the 3 air slots case was reduced by 93%.Using fossil fuels as the primary way to generate electricity causes a significant effect on the environment. In 2019 more than 64% of the electricity in the United States of America was generated using fossil fuel resources, while renewable energy (RE) resources contributed to only 17% of the U.S. electricity generation for the same year. Due to the complex terrain distribution of many states in the U.S., a massive opportunity of utilizing RE resources in rural and remote areas can reduce the cost of electrical grid installation for such areas. In this study, a typical residential building with an average energy utilization of 30.25 kWh/day with a demand peak of 5.34 kW was considered a case study in each state to optimize a hybrid RE system and find the best alternative electrical grid system. This study presents the best configuration between Solar and Wind energy with different types of energy storage. It was discovered that the photovoltaic (PV) solar panels - diesel generator with battery best services in all states. The daily radiation and diesel prices substantially affect the Levelized Cost of Energy (COE) values in each state. A remote residential building, commercial building, and industrial facility having different load profiles were considered as the case studies’ loads. The load profile for each case was found to have a substantial effect on how the system’s power produced a scheme. For the residential building, PV panels contributed more than 75% of the total power production for some cases, the contribution reduced for the commercial building case study to 65% and dropped for the industrial facility case to almost 35%. Different fuel source (natural gas) for the generator was considered in the third-round simulations. It was found that the natural gas generator which has a lower installation and running cost than the diesel generator, reduces the net present cost, the COE, PV size, and the number of batteries at all states.