87 citations · 347 across the 20 of their papers we have counts for
21 papers
Data-Driven Model Order Reduction with pyMOR
Hendrik Kleikamp, Petar Mlinarić, Stephan Rave +1
pyMOR is a free and open-source software library of model order reduction algorithms for the Python programming language. Designed with classical model-based reduction methods for…
Local training and enrichment based on a residual localization strategy
Tim Keil, Mario Ohlberger, Felix Schindler +1
To efficiently tackle parametrized multi and/or large scale problems, we propose an adaptive localized model order reduction framework combining both local offline training and loc…
Adaptive Localized Reduced Basis Methods for Large Scale Parameterized Systems
Tim Keil, Mario Ohlberger, Felix Schindler
In this contribution, we introduce and numerically evaluate a certified and adaptive localized reduced basis method as a local model in a trust-region optimization method for param…
Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling
Tizian Wenzel, Bernard Haasdonk, Hendrik Kleikamp +2
In the framework of reduced basis methods, we recently introduced a new certified hierarchical and adaptive surrogate model, which can be used for efficient approximation of input-…
Collapse of Coherent Large Scale Flow in Strongly Turbulent Liquid Metal Convection
Felix Schindler, Sven Eckert, Till Zürner +2
The large-scale flow structure and the turbulent transfer of heat and momentum are directly measured in highly turbulent liquid metal convection experiments for Rayleigh numbers va…
An adaptive model hierarchy for data-augmented training of kernel models for reactive flow
Bernard Haasdonk, Mario Ohlberger, Felix Schindler
We consider machine-learning of time-dependent quantities of interest derived from solution trajectories of parabolic partial differential equations. For large-scale or long-time i…
Jump rope vortex flow in liquid metal Rayleigh-Bénard convection in a cuboid container of aspect ratio five
Megumi Akashi, Takatoshi Yanagisawa, Ataru Sakuraba +4
We study the topology and the temporal dynamics of turbulent Rayleigh-Benard convection in a liquid metal with a Prandtl number of 0.03 located inside a box with a square base area…
A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows
Pavel Gavrilenko, Bernard Haasdonk, Oleg Iliev +5
We present an integrated approach for the use of simulated data from full order discretization as well as projection-based Reduced Basis reduced order models for the training of ma…
An adaptive projected Newton non-conforming dual approach for trust-region reduced basis approximation of PDE-constrained parameter optimization
Stefan Banholzer, Tim Keil, Luca Mechelli +3
In this contribution we device and analyze improved variants of the non-conforming dual approach for trust-region reduced basis (TR-RB) approximation of PDE-constrained parameter o…
Free-fall velocities and heat transport enhancement in liquid metal magneto-convection
Tobias Vogt, Juancheng Yang, Felix Schindler +1
In geo- and astrophysics, low Prandtl number convective flows often interact with magnetic fields. Although a static magnetic field acts as a stabilizing force on such flow fields,…
A non-conforming dual approach for adaptive Trust-Region Reduced Basis approximation of PDE-constrained optimization
Tim Keil, Luca Mechelli, Mario Ohlberger +2
In this contribution we propose and rigorously analyze new variants of adaptive Trust-Region methods for parameter optimization with PDE constraints and bilateral parameter constra…
Generating a tide-like flow in a cylindrical vessel by electromagnetic forcing
Peter Jüstel, Sebastian Röhrborn, Peter Frick +6
We show and compare numerical and experimental results on the electromagnetic generation of a tide-like flow structure in a cylindrical vessel which is filled with the eutectic liq…
Flow regimes of Rayleigh-Bénard convection in a vertical magnetic field
Till Zürner, Felix Schindler, Tobias Vogt +2
The effects of a vertical static magnetic field on the flow structure and global transport properties of momentum and heat in liquid metal Rayleigh-Bénard convection are investigat…
A locally conservative reduced flux reconstruction for elliptic problems
Stephan Rave, Felix Schindler
In the context of model order reduction of parametric elliptic problems, we present a methodology to reconstruct a conforming flux from a given reduced solution, that is locally co…
Localized model reduction for parameterized problems
Andreas Buhr, Laura Iapichino, Mario Ohlberger +3
In this contribution we present a survey of concepts in localized model order reduction methods for parameterized partial differential equations. The key concept of localized model…
True Error Control for the Localized Reduced Basis Method for Parabolic Problems
Mario Ohlberger, Stephan Rave, Felix Schindler
We present an abstract framework for a posteriori error estimation for approximations of scalar parabolic evolution equations, based on elliptic reconstruction techniques [10, 9, 3…
Model Reduction for Multiscale Lithium-Ion Battery Simulation
Mario Ohlberger, Stephan Rave, Felix Schindler
In this contribution we are concerned with efficient model reduction for multiscale problems arising in lithium-ion battery modeling with spatially resolved porous electrodes. We p…
Extending DUNE: The dune-xt modules
Tobias Leibner, René Milk, Felix Schindler
We present our effort to extend and complement the core modules of the Distributed and Unified Numerics Environment DUNE (http://dune-project.org) by a well tested and structured c…
pyMOR - Generic Algorithms and Interfaces for Model Order Reduction
René Milk, Stephan Rave, Felix Schindler
Reduced basis methods are projection-based model order reduction techniques for reducing the computational complexity of solving parametrized partial differential equation problems…
Error control for the localized reduced basis multi-scale method with adaptive on-line enrichment
Mario Ohlberger, Felix Schindler
In this contribution we consider localized, robust and efficient a-posteriori error estimation of the localized reduced basis multi-scale (LRBMS) method for parametric elliptic pro…
A-posteriori error estimates for the localized reduced basis multi-scale method
Mario Ohlberger, Felix Schindler
We present a localized a-posteriori error estimate for the localized reduced basis multi-scale (LRBMS) method [Albrecht, Haasdonk, Kaulmann, Ohlberger (2012): The localized reduced…