Computer Methods in Applied Mechanics and Engineering
GPBi-CG: Generalized Product-type Methods Based on Bi-CG for Solving Nonsymmetric Linear Systems
SIAM Journal on Scientific Computing
Shape optimization towards stability in constrained hydrodynamic systems
Journal of Computational Physics
Shapes and Geometries: Metrics, Analysis, Differential Calculus, and Optimization
Shapes and Geometries: Metrics, Analysis, Differential Calculus, and Optimization
3D Shape Optimization in Viscous Incompressible Fluid under Oseen Approximation
SIAM Journal on Control and Optimization
Forward-and-backward diffusion processes for adaptive image enhancement and denoising
IEEE Transactions on Image Processing
Numerical Methods in Sensitivity Analysis and Shape Optimization
Numerical Methods in Sensitivity Analysis and Shape Optimization
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To obtain the maximum drag profiles for the surface of an object located in unsteady flow, a shape optimization algorithm based on an adjoint method is presented. The adjoint method is based on the Lagrange multiplier method. Using a first variation of the Lagrange function, stationary conditions can be derived. These conditions consist of state equations, adjoint equations, and sensitivity equations with boundary conditions. The sensitivity equations are derived based on the shape derivative and the material derivative. To achieve the optimal shape based on these stationary conditions, a smoothing technique, a constant volume technique, a node relocation technique, the SUPG/PSPG stabilized method, and the GPBi-CG solver are implemented in the shape optimization algorithm. Using this algorithm, under Stokes flow, we can obtain the Pironneau's result found in the literature where the optimal shape is of the rugby ball type. Under unsteady flow i.e. for a Reynolds number of 1000, this algorithm can also construct an optimal shape. Compared an initial cylindrical shape, the drag of the optimal shape under constant volume can be increased by about 218% in the case of a Reynolds number of 1000.