Reduced-order modeling of transonic flows around an airfoil submitted to small deformations

A reduced-order model (ROM) is developed for the prediction of unsteady transonic flows past an airfoil submitted to small deformations, at moderate Reynolds number. Considering a suitable state formulation as well as a consistent inner product, the Galerkin projection of the compressible flow Navier–Stokes equations, the high-fidelity (HF) model, onto a low-dimensional basis determined by Proper Orthogonal Decomposition (POD), leads to a polynomial quadratic ODE system relevant to the prediction of main flow features. A fictitious domain deformation technique is yielded by the Hadamard formulation of HF model and validated at HF level. This approach captures airfoil profile deformation by a modification of the boundary conditions whereas the spatial domain remains unchanged. A mixed POD gathering information from snapshot series associated with several airfoil profiles can be defined. The temporal coefficients in POD expansion are shape-dependent while spatial POD modes are not. In the ROM, airfoil deformation is introduced by a steady forcing term. ROM reliability towards airfoil deformation is demonstrated for the prediction of HF-resolved as well as unknown intermediate configurations

Shape deformations based on vector fields

This thesis explores applications of vector field processing to shape deformations. We present a novel method to construct divergence-free vector fields which are used to deform shapes by vector field integration (Chapter 2). The resulting deformation is volume-preserving and no self-intersections occur. We add more controllability to this approach by introducing implicit boundaries (Chapter 3), a shape editing method which resembles the well-known boundary constraint modeling metaphor. While the vector fields are originally defined in space, we also present a surface-based version of this approach which allows for more exact boundary selection and deformation control (Chapter 4). We show that vectorfield- based shape deformations can be used to animate elastic motions without complex physical simulations (Chapter 5). We also introduce an alternative approach to exactly preserve the volume of skinned triangle meshes (Chapter 6). This is accomplished by constructing a displacement field on the mesh surface which restores the original volume after deformation. Finally, we demonstrate that shape deformation by vector field integration can also be used to visualize smoke-like streak surfaces in dynamic flow fields (Chapter 7).In dieser Dissertation werden verschiedene Anwendungen der Vektorfeldverarbeitung im Bereich Objektdeformation untersucht. Wir präsentieren eine neuartige Methode zur Konstruktion von divergenzfreien Vektorfeldern, welche mittels Integration zum Deformieren von Objekten verwendet werden (Kapitel 2). Die so entstehende Deformation ist volumenerhaltend und keine Selbstüberschneidungen treten auf. Inspiriert von etablierten, auf Randbedingungen beruhenden Methoden, erweitern wir diese Idee hinsichtlich Kontrollierbarkeit mittels impliziten Abgrenzungen (Kapitel 3). Während die ursprüngliche Konstruktion im Raum definiert ist, präsentieren wir auch eine oberflächenbasierte Version, welche ein genaueres Festlegen der Abgrenzungen und bessere Kontrolle ermöglicht (Kapitel 4). Wir zeigen, dass vektorfeldbasierte Deformationen auch zur Animation von elastischen Bewegungen benutzt werden können, ohne dass komplexe Simulationen nötig sind (Kapitel 5). Des weiteren zeigen wir eine alternative Möglichkeit, mit der man das Volumen von Dreiecksnetzen erhalten kann, welche mittels Skelett-Animation deformiert werden (Kapitel 6). Dies erreichen wir durch ein Deformationsfeld auf der Oberfläche, das das ursprüngliche Volumen wieder hergestellt. Wir zeigen außerdem, dass Deformierungen mittels Vektorfeld-Integration auch zur Visualisierung von Rauch in dynamischen Flüssen genutzt werden können(Kapitel 7)

Towards a Lagrange-Newton approach for PDE constrained shape optimization

The novel Riemannian view on shape optimization developed in [Schulz, FoCM, 2014] is extended to a Lagrange-Newton approach for PDE constrained shape optimization problems. The extension is based on optimization on Riemannian vector space bundles and exemplified for a simple numerical example.Comment: 16 pages, 4 figures, 1 tabl