2 citations · 6 across the 23 of their papers we have counts for
5 papers · 1 filter
Distributed model order reduction of a model for microtubule-based cell polarization using HAPOD
Tobias Leibner, Maja Matis, Mario Ohlberger +1
In this contribution we investigate in mathematical modeling and efficient simulation of biological cells with a particular emphasis on effective modeling of structural properties…
A Modeling Framework for Efficient Reduced Order Simulations of Parametrized Lithium-Ion Battery Cells
M. Landstorfer, M. Ohlberger, S. Rave +1
In this contribution we present a new modeling and simulation framework for parametrized Lithium-ion battery cells. We first derive a new continuum model for a rather general inter…
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…
Model Reduction for Large Scale Systems
Tim Keil, Mario Ohlberger
Projection based model order reduction has become a mature technique for simulation of large classes of parameterized systems. However, several challenges remain for problems where…
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…