An LES CFD simulation is one of the most accurate methods used to study turbulent airflow. Large Eddy Simulation (LES) is a powerful model that can capture the small, chaotic, and swirling movements of air that simpler models often miss. This makes an LES Fluent simulation the ideal tool for a detailed airfoil CFD analysis, especially for complex conditions like high angles of attack.

However, the main goal of any advanced simulation is to prove its accuracy against the real world. This report details a high-fidelity LES simulation of an NACA 6409 airfoil. The primary purpose is to validate the simulation’s results by comparing its predictions for lift and drag coefficients directly against established experimental data from a reference study [1]. This validation process builds confidence that the CFD model can be trusted for future engineering designs.

For more aerodynamic CFD simulation tutorials and airfoil analysis projects, visit: https://cfdland.com/product-category/engineering/aerodynamics-aerospace-cfd-simulation/

• Reference [1]: Prajapati, Nirav, Umang Patdiwala, and Piyushkumar Surani. “Experimental validation of naca 6409 airfoil using cfd analysis.”  org(2021).

Simulation Process: Fluent-CFD Setup, RANS-to-LES Workflow with Adaptive Meshing

The simulation process for this airfoil was performed in two main stages to ensure the highest accuracy. The first stage was a steady-state simulation using a RANS turbulence model on a structured grid of 20 million cells. This initial step is a best practice that provides a stable and converged flow field, which serves as an excellent starting point for the more complex LES analysis.

In the second stage, the simulation was switched to transient mode, and the Large Eddy Simulation (LES) model was activated in ANSYS Fluent. To correctly capture the physics near the airfoil’s surface, a technique called mesh adaptation was used. This feature automatically refines the mesh to ensure the Y+ value is close to 1, which is a strict requirement for a high-quality LES simulation that can resolve the boundary layer.

A custom field function was created to control this adaptation process intelligently. This function calculated the ratio of the largest turbulent eddies to the size of the local mesh cell. Following guidelines from scientific literature, the mesh was automatically refined in any area where this ratio was greater than 5. This ensured the grid was always fine enough to capture the important turbulent structures. This smart adaptation process increased the final mesh size to approximately 45 million cells, creating the high-resolution grid needed for the final LES CFD analysis.

Figure 1: The initial structured computational grid of 20 million cells, used for the preliminary RANS simulation phase

Figure 2: The final computational grid after mesh refinement for the secondary LES simulation phase

Post-processing: LES Validation and Analysis of Lift Coefficient

The primary goal of this simulation was to validate the CFD model’s predictions. The results show a strong correlation between the numerical simulation and the real-world experimental data, especially for the lift coefficient. A direct comparison of the integrated aerodynamic forces is presented in the table below. The LES simulation predicted the lift coefficient with an error of only 7.4%, which is considered an excellent agreement for such a complex, separated flow.

The simulation results provide a powerful engineering analysis of a critical aerodynamic event: flow separation. The analysis goes beyond simply observing the flow, explaining how the turbulent structures directly cause a major loss in performance. The Q-criterion contours in Figures 3 and 4 are a standard CFD method used to visualize vortices. The results show a complex network of tube-like turbulent structures that form on the top surface of the airfoil and then break down into chaotic motion in the wake behind it. These structures are colored by vorticity magnitude, a measure of how fast the fluid is spinning. The red areas in Figure 2 show the most intense, rapidly spinning vortices, which are concentrated right where the flow pulls away from the airfoil’s surface.

From a skillful engineering viewpoint, these visualizations are showing a condition of massive flow separation. The smooth flow is unable to follow the curved upper surface of the airfoil. This separation creates the large, unstable, and energy-consuming turbulent wake seen in all the contours. This is not a minor effect; a wake of this size is directly linked to a catastrophic loss of lift and a very large increase in aerodynamic drag. In aviation, this condition is known as an aerodynamic stall, and it is extremely dangerous.

Figure 3: Contours of Vorticity Magnitude on xy plane from the LES Fluent simulation, clearly showing the point of flow separation and the formation of a large wake.

Figure 4: 3D visualization of vortical structures using the Q-criterion, revealing the complex breakdown of turbulence in the airfoil’s wake.

The most important achievement of this LES simulation is the successful and detailed capture of the physics of stall. Simpler models might only predict a small wake, but the LES Fluent simulation correctly shows the dynamic and chaotic process of vortices being formed, shed from the airfoil, and breaking down. This provides engineers with invaluable data to understand the unsteady forces acting on the wing during a stall. This high-fidelity information is essential for designing more efficient and, most importantly, safer airfoils that can resist stalling.

Figure 5: Top-down view of the Q-criterion contours, highlighting the three-dimensional and chaotic nature of the turbulent flow structures.