23 citations · 62 across the 12 of their papers we have counts for
4 papers · 1 filter
Adaptive Reduced Basis Methods for Multiscale Problems and Large-scale PDE-constrained Optimization
Tim Keil
This thesis presents recent advances in model order reduction methods with the primary aim to construct online-efficient reduced surrogate models for parameterized multiscale pheno…
A Super-Localized Generalized Finite Element Method
Philip Freese, Moritz Hauck, Tim Keil +1
This paper presents a novel multi-scale method for elliptic partial differential equations with arbitrarily rough coefficients. In the spirit of numerical homogenization, the metho…
Adaptive machine learning based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery
Tim Keil, Hendrik Kleikamp, Rolf J Lorentzen +2
In this contribution, we develop an efficient surrogate modeling framework for simulation-based optimization of enhanced oil recovery, where we particularly focus on polymer floodi…
A Relaxed Localized Trust-Region Reduced Basis Approach for Optimization of Multiscale Problems
Tim Keil, Mario Ohlberger
In this contribution, we are concerned with parameter optimization problems that are constrained by multiscale PDE state equations. As an efficient numerical solution approach for…