RQ_7 UAV Dynamic Stability Derivatives: CFD Simulation by Ansys Fluent

Description

Dynamic Stability Derivatives: RQ_7 UAV CFD Simulation Training

Introduction

The determination of an UAV’s dynamic stability and control derivatives is vital for the development of accurate flight models and control system design. These coefficients, which relate aerodynamic moments to angular motion, are traditionally obtained through costly and time-consuming wind tunnel tests.

In RQ_7 UAV dynamic stability derivatives project, a numerical approach based on computational fluid dynamics (CFD) combined with the forced oscillation technique is proposed to efficiently extract the derivatives of the dynamic stability of an UAV in the subsonic flight regime.

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The smallest of AAI’s RQ_7 Shadow family of unmanned aircraft systems is the RQ_7 Shadow 200. Targets can be found, recognized, and identified using Shadow 200 up to 125 kilometers away from a tactical center. The device can identify tactical vehicles day or night from a height of 8,000 feet and at a distance of 3.5 kilometers on a slant.

A trailer-mounted pneumatic launcher helps with takeoffs and has the ability to accelerate a 170-kilogram aircraft to 130 km/h in 12 m.

The Tactical Automatic Landing System, which consists of an aircraft-mounted transponder and a ground-based micro-millimeter wavelength radar, directs landings.

An AAI RQ_7 Shadow UAV is modeled in this simulation using ANSYS Fluent software. The device moves at a speed of 36.1 m/s while the propeller rotates at an angular velocity of 3800 rev/min.

The geometry of the present model is two-dimensional and has been designed using Design Modeler software. We do the meshing of the present model with Fluent Meshing software. The mesh type is Tetrahedral, and the element number is 4,146,673.

The computational domain is specifically structured with three fluid regions to facilitate the motion: a rotating internal fluid region for the blade, an oscillating internal fluid region that completely encloses the drone, and an external fluid region that does not oscillate. This research focuses on applying a specific cosine oscillation to the drone and analyzing the resulting aerodynamic moments to quantify the dynamic stability derivatives.

Methodology

This study used a transient, pressure-based CFD simulation in ANSYS Fluent to analyze the incompressible flow around a UAV to derive dynamic derivatives. The flow physics was modeled using the k-ω SST turbulence model. The key method involved the oscillatory region technique, in which an inner fluid region, containing the UAV, was forced into a simple harmonic oscillation via a UDF, while the outer domain was set with inlet and outlet boundary conditions. This setup, with good time resolution, was designed to capture the aerodynamic response necessary to calculate dynamic stability derivatives.

Results and Conclusion

The most commonly used and important coefficients in the discussion of stability have been extracted after simulation and are given in the table below. Using these coefficients, it is possible to comment on whether a drone is stable or not in terms of static and dynamic. Also, using the extracted data, hysteresis diagrams have been drawn, which can be understood by considering the shape and direction of rotation of these rings, whether the drone is stable or not.