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EN
A general framework for calculating shape derivatives for domain optimization problems with partial differential equations as constraints is presented. The first order approximation of the cost with respect to the geometry perturbation is arranged in an efficient manner that allows the computation of the shape derivative of the cost without the necessity to involve the shape derivative of the state variable. In doing so, the state variable is only required to be Lipschitz continuous with respect to geometry perturbations. Application to shape optimization with the Navier-Stokes equations as PDE constraint is given.
2
Content available remote Optimal control of partial differential equations with affine control constraints
EN
Numerical solution of PDE optimal control problems involving affine pointwise control constraints is investigated. Optimality conditions are derived and a semi-smooth Newton method is presented. Global and local superlinear convergence of the method are obtained for linear problems. Differently from box constraints, in the case of general affine constraints a proper weighting of the control costs is essential for superlinear convergence of semi-smooth Newton methods. This is also demonstrated numerically by controlling the two-dimensional Stokes equations with different kinds of affine constraints.
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