Analysis-Aware Defeaturing of Dirichlet Features in Poisson Problems
13th International Conference on Isogeometric Analysis (IGA 2025), Eindhoven, Netherlands
Talk on certified a posteriori defeaturing error estimation, including goal-oriented estimates and features subject to Dirichlet boundary conditions.
Defeaturing Error Estimates for Poisson Problems with Dirichlet Features
14th European Conference on Numerical Mathematics and Advanced Applications (ENUMATH), Heidelberg, Germany
Geometry simplification, also known as defeaturing, is crucial for industrial simulations. It not only simplifies the meshing process but also reduces the computational costs of subsequent simulations by decreasing the number of degrees of freedom. Traditional defeaturing methods often rely on geometric criteria alone, overlooking the underlying physics of the problem. In contrast, analysis-aware defeaturing employs a posteriori error estimation, combining the defeatured simulation outputs with the exact geometry information to better inform the defeaturing process.
Analysis-Aware Defeaturing of Dirichlet Features in Poisson Problems
Schweizer Numerik Kolloquium, Basel, Switzerland
Talk on analysis-aware defeaturing of Dirichlet features in Poisson problems, including goal-oriented estimates. The abstract of the talk can be found here.
Galerkin Neural Network-POD for Acoustic and Electromagnetic Wave Propagation
16th International Conference on Mathematical and Numerical Aspects of Wave Propagation, Berlin, Germany
Talk on the POD-NN method for wave propagation in parameterized domains based on this preprint. The abstract of the talk can be found here.