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New preprint

Published:

New preprint: A Certified Goal-Oriented A Posteriori Defeaturing Error Estimator for Elliptic PDEs

IGA 2025

Published:

Excited to give a talk on analysis-aware defeaturing at IGA 2025 in Eindhoven.

ENUMATH 2025

Published:

Happy to give a talk on analysis-aware defeaturing at ENUMATH 2025 in Heidelberg.

New preprint

Published:

New preprint: Extension Operators for Fractional Sobolev Spaces on Lipschitz Submanifolds

Swiss Numerics Day 2025

Published:

Looking forward to give a talk on analysis-aware defeaturing at the Swiss Numerics Day 2025 in Basel.

FIMH 2025

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Happy to contribute to the 13th Functional Imaging and Modeling of the Heart International Conference, June 1 - 5, Dallas USA, together with HernĂ¡n G. Morales.

New preprint

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New preprint: Nonlinear model reduction with Neural Galerkin schemes on quadratic manifolds

Creator School

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Looking forward to participating in the IGA Autumn School organized by the CREATOR team at TU Darmstadt

IGA School

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Happy to participate in the Lake Como Summer School on Isogeometric Analysis

WAVES conference

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Happy to give a talk at the 16th International Conference on Mathematical and Numerical Aspects of Wave Propagation in Berlin

New preprint

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New preprint: Galerkin Neural Network-POD for Acoustic and Electromagnetic Wave Propagation

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Defeaturing Error Estimates for Poisson Problems with Dirichlet Features

Published:

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.

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