Optimal local approximation spaces for parabolic problems
J Schleuß, K Smetana - Multiscale Modeling & Simulation, 2022 - SIAM
We propose local space-time approximation spaces for parabolic problems that are optimal
in the sense of Kolmogorov and may be employed in multiscale and domain decomposition …
in the sense of Kolmogorov and may be employed in multiscale and domain decomposition …
A priori error bounds for model reduction of interconnected linear systems using robust performance analysis
L Janssen, B Besselink, R Fey… - 2022 American …, 2022 - ieeexplore.ieee.org
Subsystem reduction of interconnected systems provides a computationally cheap and
structure-preserving alternative to direct model order reduction techniques of large-scale …
structure-preserving alternative to direct model order reduction techniques of large-scale …
Optimal local approximation spaces for parabolic problems
J Schleuß, K Smetana - arXiv preprint arXiv:2012.02759, 2020 - arxiv.org
We propose local space-time approximation spaces for parabolic problems that are optimal
in the sense of Kolmogorov and may be employed in multiscale and domain decomposition …
in the sense of Kolmogorov and may be employed in multiscale and domain decomposition …
Multiscale Methods for High Performance Uncertainty Quantification
L Seelinger - 2022 - archiv.ub.uni-heidelberg.de
Mathematical models of complex real-world phenomena result in computational challenges,
often necessitating the use of modern High Performance Computing (HPC) systems and …
often necessitating the use of modern High Performance Computing (HPC) systems and …