Session: 10-03-02: Fundamental Issues and Perspectives in Fluid Mechanics - II

Paper Number: 70674

Start Time: Monday, 04:30 PM

70674 - Validation Study of Reynolds Stress Model Coupled With Gamma Transition for Uav Propellers 

The current study aims at demonstrating the capability of an in-house developed transition turbulence model, SSG/LRR-omega-gamma, in accurately predicting the transition phenomena and its influence on the aerodynamic characteristics of UAV propellers. The propeller used in the DJI Phantom 3 drone is chosen to perform the computational analyses and was chosen since it has been widely studied and is commercially very popular.

UAV propellers undergo laminar to turbulent transition as they predominantly operate in low Reynolds number regimes (O~10^4-10^5) and experience high pressure gradients. Transition phenomena like laminar separation bubbles are often observed in these lifting surfaces due to adverse pressure gradients in the boundary layer which tend to greatly alter the blade surface pressure distribution, in turn altering the aerodynamic characteristics. Hence, using a fully turbulent model to capture the flow would not suffice. It becomes pivotal to use a transition turbulence model that can capture these low-Re phenomena to obtain an accurate estimation of propeller performance. There has been extensive research in the recent years conducted on UAV propeller performance and characteristics. However, there is no study that investigates the near-wall behavior of the flow for UAV propellers and the current study aims to fill that gap.

The in-house developed RANS transition turbulence model: SSG/LRR-omega-gamma uses a second order closure Reynolds stress transport (RST) model, SSG/LRR-omega as the base turbulence formulation. This is then coupled with the intermittency equation (gamma), which governs the transition prediction. The transport equation for intermittency is formulated in such a way that it can be applied to stationary as well as moving wall boundaries, making it Galilean invariant. Therefore, by the virtue of its formulation, the model is capable of handling complex flow-fields with moving boundaries, making it an attractive transition turbulence model for a wide range of applications. To prove the credibility of this model, it is validated against existing experimental data on DJI Phantom 3. The computational analyses for this study were performed on an overset grid and solved using a compressible solver on OpenFOAM. Thrust and torque data at different RPMs available in the literature are compared against the model predictions. A qualitative analysis is also performed by comparing visualization of different flow characteristics.

Subsequently, the SSG/LRR-omega-gamma model is used to study the transition phenomena occurring at multiple sections of the Phantom propeller. This is done by looking at the surface pressure and wall-shear stress distributions along the chord at different radial sections of the propeller. The flow visualizations for velocity and vorticity are also studied to analyze the captured flow intricacies. These results are then compared against predictions made by widely used state-of-the art transition models like the Langtry Menter gamma-Re_theta model and the one-equation gamma transition model, both of which are based on the linear eddy viscosity turbulence model, k-omega SST. Linear eddy viscosity models use the Boussinesq approximation and hence, tend to be less accurate in complex flow-fields. This comparison study is carried out to demonstrate the capability of second-order models over linear eddy viscosity models in capturing these complex flow-fields. The impact of having a Galilean invariant formulation for transition is also studied by comparing the two Galilean invariant models, k-omega SST  gamma and SSG/LRR-omega-gamma, against the  k-omega SST gamma-Re_theta model. Finally, predictions made by fully turbulent models, k-omega SST and SSG/LRR-omega are also compared against the transition turbulence model predictions to demonstrate how the surface pressure and skin-friction coefficient distributions as well as the thrust predictions get impacted.

 

 

Presenting Author: Naina Pisharoti Virginia Tech

Authors:

Naina Pisharoti Virginia Tech
Stefano Brizzolara Virginia Tech