Calendar

MechE PhD Prospectus Defense: Adam Rozman

Starts:
10:00 am on Wednesday, October 1, 2025
Ends:
12:00 pm on Wednesday, October 1, 2025
Location:
EMA 205, 730 Commonwealth Ave
TITLE: ADVANCING COMPUTATIONAL METHODS FOR ROTORCRAFT AERODYNAMICS AND ACOUSTICS

ABSTRACT: Multirotor drones or electric Vertical Take-Off and Landing (eVTOL) vehicles have versatile applications including photography, delivery, and soon, passenger-carrying air taxis. Because these vehicles service highly populated areas, controlling noise is an important factor for their continued adoption and acceptance. eVTOL vehicle noise is affected by the same mechanisms of helicopters; however, they spread thrust across multiple propellers, reducing disk loading and Reynolds number. The complex wakes produced by these vehicles create nonuniform inflow to propellers and introduce turbulence which impinges on blades and creates noise at a wide range of frequencies, known as broadband noise. Because of the small propellers and multirotor configuration of eVTOL vehicles, nondeterministic disturbances and the resulting broadband noise are major contributors to their overall noise. Different components of noise can be predicted accurately with approaches ranging from basic blade-element momentum theory using airfoil loads calculated by a low-order tool like XFOIL, to Vortex Particle Methods, to high accuracy modeling with Computational Fluid Dynamics (CFD). This work explores the modeling of propellers in various inflow conditions and installation configurations that produce unsteady interactions and noise. The effect of turbulence and transition modeling is investigated on the outcome of the CFD models by comparing to experiments. The application of CFD to accurately predict broadband noise is critiqued, and an analytical model for turbulence ingestion noise is proposed which can be combined with mid-fidelity approaches to comprehensively predict eVTOL noise.

COMMITTEE: ADVISOR/CHAIR Professor Sheryl Grace, ME; Professor Dan Li, Earth & Environment; Professor Shabnam Raayai, ME