(Georgia Institute of Technology, 2018-04-10)
Schatzman, Natasha Lydia
Vehicles with coaxial, contra-rotating rotor systems (CACR) are being considered for a range of applications, including those requiring high speed and operations in urban environments. Community and environmental noise impact is likely to be a concern in these applications. Design parameters are identified that effect the fundamental aerodynamics and fluid dynamic features of a CACR in hover, vertical, and edgewise flight. Particular attention is paid to those features affecting thickness, loading, blade vortex interaction (BVI), and high speed impulsive (HSI) noise. Understanding the fluid dynamic features is a precursor to studying the aeroacoustics of a coaxial rotor. Rotor performance was computed initially using Navier-Stokes solver with prescribed blade section aerodynamic properties, the results validated against generic experimental test cases. The fluid dynamics of blade interactions was simplified and broken into a 2-D blade crossing problem, with crossing locations and velocity fields from the rotor results. Two trains of 8 airfoils passing were simulated to understand the effects due to shed vorticity. The airfoils are displaced vertically by a distance equivalent to the typical spacing between the upper and lower rotors of a coaxial system. A 2D potential flow code and 2D OVERFLOW compressible-flow Navier-Stokes solver were used to investigate the complex coaxial rotor system flow field. One challenge of analyzing the CACR is the difficulty in envisioning all the possible interactions and their possible locations as flight conditions and rotor designs change. A calculation tool has been developed to identify time and location of blade overlap. The tool was then integrated with a wake aerodynamics model to identify locations and instances of upper rotor tip vortex interaction with a lower rotor blade. This tool enables rapid identification of different types of BVI based on relative rotor orientation. Specific aerodynamic phenomena that occur for each noise source relevant to CACR are presented, along with computational tools to predict these occurrences.