Verification and Validation

This page documents major validation and verification cases for ADflow.

NASA Common Research Model (CRM)

Coder et al. [1] compares ADflow with OVERFLOW and elsA for the CRM Wing-Body and Wing-Body-Nacelle-Pylon configurations. Both overset and multiblock structured meshes were used in the comparison. The cases are run at a freestream Mach number of 0.85 and a Reynolds number of 5 million. Figure 8 in this paper details the grid convergence of each of the flow solvers.

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Figure 8 from Coder et al. [1]

ONERA M6

The MACH-Aero tutorial contains a comparison of ADflow with other flow solvers for the ONERA M6 wing here. The results section at the bottom of this page shows force and moment coefficient convergence of ADflow and other solvers.

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Hydrofoils

Garg et al. [2] couples hydrodynamic and structural analysis of hydrofoils and compares the results with experimental data. The CFD analysis uses a low-speed preconditioner to solve hydrodynamic problems that have nearly incompressible flow. A NACA 0009 hydrofoil is analyzed at a Reynolds number of 1 million and compared to experimental results. Figure 3 in this paper shows the comparison between the predicted force and moment coefficients and tip deflection with the experimental results.

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Figure 3 from Garg et al. [2]

Figure 4 shows a drag convergence study, and the results approach experimental values.

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Figure 4 from Garg et al. [2]

Wind Turbines

Analysis of wind turbines is conducted in Madsen et al. [3]. Appendix A compares ADflow to EllipSys3D at different flow conditions. Figure 21 shows the thrust and torque calculations from ADflow and EllipSys3D. These results show that ADflow consistently overshoots the EllipSys3D results at all wind speeds.

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Figure 21 from Madsen et al. [3]

1

James G. Coder, Thomas H. Pulliam, David Hue, Gaetan K. W. Kenway, and Anthony J. Sclafani. Contributions to the 6th AIAA CFD Drag Prediction Workshop using structured grid methods. In AIAA SciTech Forum. American Institute of Aeronautics and Astronautics, January 2017. doi:10.2514/6.2017-0960.

2

Nitin Garg, Gaetan K. W. Kenway, Joaquim R. R. A. Martins, and Yin Lu Young. High-fidelity multipoint hydrostructural optimization of a 3-D hydrofoil. Journal of Fluids and Structures, 71:15–39, May 2017. doi:10.1016/j.jfluidstructs.2017.02.001.

3

Mads H. Aa. Madsen, Frederik Zahle, Niels N. Sørensen, and Joaquim R. R. A. Martins. Multipoint high-fidelity CFD-based aerodynamic shape optimization of a 10 MW wind turbine. Wind Energy Science, 4:163–192, April 2019. doi:10.5194/wes-4-163-2019.