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This paper proposes a shape optimization algorithm based on the principles ofIsogeometric Analysis (IGA) in which the parameterization of the geometryenters the problem formulation as an additional PDE-constraint. Inspired by theisoparametric principle of IGA, the parameterization and the governing stateequation are treated using the same numerical technique. This leads to a schemethat is comparatively easy to differentiate, allowing for a fully symbolicderivation of the gradient and subsequent gradient-based optimization. Toimprove the efficiency and robustness of the scheme, the basis is re-selectedduring each optimization iteration and adjusted to the current needs. Thescheme is validated in two test cases.

The Role of PDE-Based Parameterization Techniques in Gradient-Based IGA Shape Optimization Applications