Moving Mesh (Mesh Motion): Switchblade 300 Drone

Introduction

This report presents the computational fluid dynamics (CFD) simulation of the Switchblade 300 drone using ANSYS Fluent. The primary objective was to analyze the fluid dynamics around the geometry under the specified conditions of motion and environmental parameters.

The geometry of the Switchblade 300 was created in SpaceClaim. Using ANSYS Meshing, a non-conformal mesh of approximately 40 million tetrahedral cells was initially generated. This dense mesh provided high resolution of the flow features around the geometry and was well suited to capturing the intricate details of the flow.

However, the initial 40,000,000-element mesh presented significant computational challenges. To optimize the simulation, the mesh type was converted to polyhedral, which dramatically reduced the element count from 40,000,000 to 7,000,000 while preserving the necessary resolution. Figure 2 shows the mesh configuration, highlighting the non-conformal mesh regions essential for accurately capturing the fluid interactions.

Methodology

The simulation was performed in ANSYS Fluent, making use of its Mesh Motion capability to analyze the flow characteristics of the rotating geometry. The setup specified a velocity inlet of 28.05 m/s, an angle of attack of 5 degrees, and a rotational speed of 5000 RPM. The k-ω SST turbulence model was selected for its effectiveness in predicting boundary layer separation and handling complex flow dynamics. For the numerical methods, the SIMPLE algorithm was used for pressure-velocity coupling, and standard initialization was applied to set the initial flow conditions within the solution domain.

Results

Velocity Contour — Presented in Figure 3, the velocity contour depicts the flow around the Switchblade 300, identifying the regions of high- and low-speed flow that arise from the angle of attack and the rotation of the geometry.

Pressure Contour — Shown in Figure 4, the pressure contour illustrates the varying pressure distribution across the geometry, which is critical for identifying the aerodynamic forces — such as lift and drag — acting on the drone.

Conclusion

The simulation results provide a detailed understanding of the aerodynamic performance of the Switchblade 300, offering significant insight into how rotational speed, inlet velocity, and angle of attack influence the overall flow behavior. These findings support the optimization of the design and operating parameters to enhance performance. Further simulations under varied conditions are recommended to explore additional operational scenarios and improve predictive accuracy.