Recent Work
Velocity fields of common FSI problem. Bottom three are recreated via machine learning.
Pressure POD mode reconstruction using machine learning.
Computer simulations have captivated me ever since I was a child. The predictive capabilities of
simulations allow for humans to better understand the world we live in, as well as the many
scenarios of what the future could hold. Like many kids born in the 90's, we grew up in a world
where the evidence for climate change and it's repercussion were becoming increasingly apparent. By
high school, the majority opinion was that the renewable energy takeover was imminent. Soon, the
world's nations would come together to solve the most pressing catastrophe.
Fast forward to 2023, renewables now account for roughly 18\% of energy generation globally. In undergrad I learned the hard truth; most countries energy grids are not setup to accommodate the transition to renewable energy. Even with heavy investment in wind and solar technologies, if hydropower energy storage is not made more cost effective and small hydropower expanded, the entire world could struggle with the transition. My goal is to change that with the power of predictive computer simulations.
The first time I was introduced to the hydropower industry was the time I spent as a summer
engineering intern in 2013 at a custom machine parts shop called `East Tech Company' in Chattanooga,
TN. Here I learned how custom industrial equipment machine parts are made using mills and lathes. My
responsibilities included directly dealing with customer orders, estimating material costs,
preparing and ordering raw materials needed for the parts, sending cost estimates, negotiating with
customers, completing order paperwork, and finally ensuring that the part drawings made their way to
the correct machinist who all had their specialities. Although I was barely a sophomore in undergrad
at the time and was put in a role I did not originally expect to be in, I was able to gain a depth
of practical, hands-on knowledge in material and mechanical engineering.
Despite the challenges, I managed to complete several large tasks for noteworthy companies such as
Voith Hydro, Roadtec, and for Watts Bar Dam (TVA). From this experience, I not only gained an
intimate understanding of how machine parts are made, but also an interest in the different metals
used, what their uses were, their costs, and what made parts expensive to create. I believe my
understanding of practical material science was greatly impacted by this job, as well as an
understanding that I could go into a job not knowing anything about it but quickly adapt and thrive.
This experience was invaluable as I at first was unsure if engineering was the right fit me. After
my internship, I had little doubt that I had what it took to one day be a great engineer.
Since completing undergrad I have focused my attention towards a Ph.D. degree. With the completion
of the needed classes, my effort has been concentrated on performing research into the reduced-order
modeling of complex hydro turbine simulations. Utilizing both open-source and in-house code
developed by my department, I have performed several incompressible fluid simulations. Such research
has already resulted in a scientific paper that was presented at an aerospace engineering conference
called SciTech. This research has been conducted in part with the guidance of the Standard Modular
Hydropower Research Team at the Water Power Program in the ORNL Environmental Sciences Division.
This collaboration has allowed me to tailor many aspects of my research towards practical and
industry needed applications.
Both my interning and Ph.D. experiences have given me the unique position of understanding both the
complex, math-orientated field of fluid-dynamics and the practical, hands-on nature of material
science. Both of which are needed to develop state-of-the-art composite hydro turbines.