Aeroelasticity is one of the key points when designing any aerospace system. It allows the detection of the structure and aerodynamic safety limits and the improvement of the system performance when operating. The goal of this master thesis is to develop a partitioned fluid-structure-interaction (FSI) workflow for the study of aeroelastic phenomena at early stages of aircraft design. Requirements are thus accuracy, robustness and low computational cost. The workflow is implemented in python using Kratos Multi-Physics. To select an appropriate fluid solver, a comparison between a high fidelity variational multi-scale solver and a low fidelity potential solver is presented. The potential solver is selected due to its low computational cost and the possibility to implicitly define the wake in the mesh using an embedded approach. This avoids to remesh within each fluid-structure-interaction iteration. The potential solver limits the application of the FSI workflow to the study of static aeroelasticity of streamlined bodies flying at high Reynold numbers and small angles of attack. Verification and validation are performed for a heaving and pitching NACA 0012. The bending and torsion stiffness of the wing are modelled as a linear and rotational springs respectively. Using this model, the FSI workflow is used to study: the limits of the mesh motion and the dependency of the solution and the number of iterations on the iterative method (fix point iteration versus Newton Raphson) and the relaxation coefficient (constant versus Aitken). Finally, it is shown that the developed workflow is suitable for shown that the workflow is capable of trimming.     «

Aeroelasticity is one of the key points when designing any aerospace system. It allows the detection of the structure and aerodynamic safety limits and the improvement of the system performance when operating. The goal of this master thesis is to develop a partitioned fluid-structure-interaction (FSI) workflow for the study of aeroelastic phenomena at early stages of aircraft design. Requirements are thus accuracy, robustness and low computational cost. The workflow is implemented in pyt...     »