Dr. Stephan Rave
Postdoc
Group Numerical Analysis and Scientific ComputingTel: +49 251 83 35061
Fax: +49 251 83 32729
stephan.rave@uni-muenster.de
Fax: +49 251 83 32729
stephan.rave@uni-muenster.de
Main Research Interests
- Model Order Reduction
- Transport dominated conservation laws
- A-posteriori Error Estimates
- Functional Analysis
- Li-Ion Batteries
- Design of Scientific Computing Software
Projects
MULTIBAT: Multiscale Models and Model Order Reduction Methods for Predicting the Life-Time of Lithium-Ion Batteries
Co-operative research project in BMBF programme "Mathematics for innovations in industry and services"Publications
- . . ‘MULTIBAT: Unified workflow for fast electrochemical 3D simulations of lithium-ion cells combining virtual stochastic microstructures, electrochemical degradation models and model order reduction.’ Journal of Computational Science 2018. doi: 10.1016/j.jocs.2018.03.006. [In Press]
- . . ‘Mass Conservative Reduced Order Modeling of a Free Boundary Osmotic Cell Swelling Problem.’ arXiv e-prints 1805.01812. [Submitted]
- . . ‘Hierarchical Approximate Proper Orthogonal Decomposition.’ SIAM J. Sci. Comput. 2018. [Accepted]
- . . ‘True Error Control for the Localized Reduced Basis Method for Parabolic Problems.’ In Model Reduction of Parametrized Systems, edited by , 169-182. Cham: Springer International Publishing. doi: 10.1007/978-3-319-58786-8_11.
- . . ‘Localized Reduced Basis Approximation of a Nonlinear Finite Volume Battery Model with Resolved Electrode Geometry.’ In Model Reduction of Parametrized Systems, edited by , 201-212. Cham: Springer International Publishing. doi: 10.1007/978-3-319-58786-8_13.
- . . ‘ArbiLoMod: Local Solution Spaces by Random Training in Electrodynamics.’ In Model Reduction of Parametrized Systems, edited by , 137-148. Cham: Springer International Publishing. doi: 10.1007/978-3-319-58786-8_9.
- . . ‘Fast Low-Rank Empirical Cross Gramians.’ PAMM 17, No. 1: 841-842. doi: 10.1002/pamm.201710388.
- . . ‘ArbiLoMod, a Simulation Technique Designed for Arbitrary Local Modifications.’ SIAM J. Sci. Comput. 39, No. 4: A1435–A1465. doi: 10.1137/15M1054213.
- . . ‘pyMOR - Generic algorithms and interfaces for model order reduction.’ SIAM Journal on Scientific Computing 38, No. 5: 194-216. doi: 10.1137/15M1026614.
- . . ‘Reduced Basis Methods: Success, Limitations and Future Challenges.’ In roceedings of ALGORITMY 2016, 20th Conference on Scientific Computing, Vysoke Tatry, Podbanske, Slovakia, March 13-18, 2016, edited by , 1-12. Bratislava: Publishing House of Slovak University of Technology in Bratislava.
- . . ‘Adaptive Localized Model Reduction.’ Oberwolfach Reports 13, No. 3: 2406-2409. doi: 10.4171/OWR/2016/42.
- . . ‘Model Reduction for Multiscale Lithium-Ion Battery Simulation.’ In Numerical Mathematics and Advanced Applications ENUMATH 2015, edited by , 317-331.: Springer. doi: 10.1007/978-3-319-39929-4_31.
- . . ‘A Numerically Stable A Posteriori Error Estimator for Reduced Basis Approximations of Elliptic Equations.’ In 11th World Congress on Computational Mechanics, WCCM 2014, 5th European Conference on Computational Mechanics, ECCM 2014 and 6th European Conference on Computational Fluid Dynamics, ECFD 2014, edited by , 4094-4102.: CIMNE, Barcelona.
- . . ‘A Model Reduction Framework for Efficient Simulation of Li-Ion Batteries.’ In Finite Volumes for Complex Applications VII-Elliptic, Parabolic and Hyperbolic Problems, edited by , 695-702.: Springer. doi: 10.1007/978-3-319-05591-6_69.
- . . ‘Nonlinear reduced basis approximation of parameterized evolution equations via the method of freezing.’ C. R. Acad. Sci. Paris, Ser. I 351: 901-906. doi: 10.1016/j.crma.2013.10.028.
- . . On Finitely Summable K-Homology Doctoral Thesis, Universität Münster.
Talks
2018-
Efficient Reduced Order Simulation of Pore-Scale Lithium-Ion Battery Models (talk)
ECMI 2018 - 20th European Conference on Mathematics for Industry – June 2018 -
Online-Adaptive Localized Reduced Basis Approximation of Parameterized Parabolic Problems (talk)
MORCOS 2018 - IUTAM Symposium on Model Order Reduction of Coupled Systems – May 2018 -
A Globally Mass Conservative Nonlinear Reduced Basis Method for Parabolic Free Boundary Problems (talk)
MoRePaS 2018 - Model Reduction of Parametrized Systems IV – April 2018 -
Hierarchical Approximate Proper Orthogonal Decomposition (talk)
CSC Seminar, MPI Magdeburg – March 2018 -
HAPOD - Fast, Simple and Reliable Distributed POD Computation (talk)
MATHMOD 2018 - 9th Vienna International Conference on Mathematical Modelling – February 2018 -
Nonlinear Model Order Reduction for Problems with Moving Discontinuities (talk)
CASA Colloquium, TU Eindhoven – January 2018
2017-
MULTIBAT - Reduced Order Modelling of Lithium-Ion Battery Models with Resolved Electrode Geometry (talk)
ACOMEN 2017 - 7th International Conference on Advanced COmputational Methods in ENgineering – September 2017 -
Hierarchical Approximate POD (talk)
LMS-EPSRC Durham Symposium – August 2017 -
Model Reduction for Transport Problems via Nonlinear State Space Transformation (talk)
14th U.S. National Congress on Computational Mechanics – July 2017 -
Model Order Reduction with pyMOR and NGSolve (talk) (Jupyter notebook)
NGSolve User Meeting – June 2017 -
HAPOD – Fast and Simple Distributed POD Computation (talk)
GAMM Jahrestagung – March 2017 -
Nonlinear Model Order Reduction with pyMOR (talk)
SIAM CSE17 - Conference on Computational Science and Engineering – February 2017
2016-
Reduced Basis Approximation of Lithium-Ion Battery Models (talk)
RWTH Aachen – December 2016 -
Nonlinear Model Order Reduction for Parametric Time Evolution Problems using the Method of Freezing (talk) (code)
7th European Congress of Mathematics – July 2016 -
pyMOR - Generic Model Order Reduction Algorithms for MPI Distributed PDE Solvers (talk)
PDE Software Frameworks 2016 – July 2016 -
Model Order Reduction for Electrochemistry Simulations (talk)
Absolventen-Seminar Numerische Mathematik, TU Berlin – June 2016 -
Hierarchical Approximate POD (poster) (code)
MORML 2016 - Workshop on Data-driven Model Order Reduction and Machine Learning – March 2016 -
Reduced Basis Methods - Success, Limitations and Future Challenges (talk)
ALGORITMY 2016 - Conference on Scientific Computing – March 2016
2015-
Reduced Basis Approximation of Microscale Lithium-Ion Battery Models - From Theory to Implementation (talk)
SimTech MOR-Seminar, Stuttgart – December 2015 -
A Modularized Modeling, Discretization and Model Order Reduction Workflow (talk)
MoRePaS 2015 - Model Reduction of Parametrized Systems III – October 2015 -
Reduction of Microscale Li-Ion Battery Models (talk)
ECCOMAS COUPLED PROBLEMS 2015 – May 2015 -
pyMOR - A New Model Order Reduction Software Framework (talk)
SIAM CSE15 - Conference on Computational Science and Engineering – March 2015 -
Reduced Basis Methods - From Theory to Implementation (talk)
KIT, Karlsruhe – January 2015
2014-
A Model Reduction Framework for Efficient Simulation of Li-Ion Batteries (poster)
FVCA7 - The International Symposium of Finite Volumes for Complex Applications VII – June 2014 -
Model Reduction of Microscale Li-Ion Battery Models (talk)
CeNoS Workshop: Complexity Meets Energy – March 2014
2013-
DUNE-pyMOR: Model Order Reduction with Python and Dune (talk)
Dune User Meeting 2013 – September 2013 -
Nonlinear Reduced Basis Approximation of Parameterized Evolution Equations Using the Method of Freezing (talk)
Model Reduction and Approximation for Complex Systems – June 2013
2012-
Freezing of Evolution Equations for Improved Reduced Basis Approximation (poster)
MoRePaS II - Second International Workshop on Model Reduction for Parametrized Systems – October 2012 -
Freezing Solutions of Time Evolution Problems for Reduced Basis Approximation (talk)
Reduced Basis Methods Workshop 2012 – August 2012
-
Efficient Reduced Order Simulation of Pore-Scale Lithium-Ion Battery Models (talk)
Teaching
- Praktikum: Introduction to Numerical Programming with Python [100434]
(in cooperation with Dr. Felix Tobias Schindler, Prof. Dr. Mario Ohlberger)
[ - | | Blockveranstaltung (Mo-Fr) | Prof. Dr. Mario Ohlberger] - Seminar: Bachelor Seminar: A posteriori Error Estimations and their Applications [104438]
(in cooperation with Dr. Felix Tobias Schindler, Andreas Buhr)
[ | wöchentlich | Do. | SRZ 117 | Dr. Stephan Rave] - Seminar: Master Seminar Applied Mathematics [104435]
(in cooperation with Andreas Buhr, Dr. Felix Tobias Schindler, Jun.-Prof. Mira Schedensack, Barbara Verfürth)
[ | wöchentlich | Do. | SRZ 117 | Barbara Verfürth]
- Seminar: Master Seminar Applied Mathematics [102385]
(in cooperation with Dr. Felix Tobias Schindler, Andreas Buhr, Prof. Dr. Mario Ohlberger, Jun.-Prof. Mira Schedensack, Barbara Verfürth)
[ - | SRZ 115 | Dr. Stephan Rave]
[Dr. Stephan Rave] - Seminar: Bachelor Seminar: A posteriori Error Estimations and their Applications [102383]
(in cooperation with Dr. Felix Tobias Schindler, Prof. Dr. Mario Ohlberger)
[ - | Prof. Dr. Mario Ohlberger]
[M A 109 (SR 1B) | Prof. Dr. Mario Ohlberger]
- Praktikum: Introduction to Numerical Programming with Python [100872]
(in cooperation with Prof. Dr. Mario Ohlberger) - Seminar: Master Seminar Applied Mathematics [100386]
(in cooperation with Dr. Felix Tobias Schindler, Prof. Dr. Mario Ohlberger) - Seminar: Bachelor Seminar: A posteriori Error Estimations and their Applications [100385]
(in cooperation with Dr. Felix Tobias Schindler, Prof. Dr. Mario Ohlberger)
- Übung: Tutorial Numerical multiscale methods and model reduction [108038]
(in cooperation with Prof. Dr. Mario Ohlberger) - Praktikum: Introduction to Numerical Programming with Python [108048]
(in cooperation with Dr. Felix Tobias Schindler, Prof. Dr. Mario Ohlberger) - Praktikum: Introduction to Numerical Programming with Python [108012]
(in cooperation with Dr. Felix Tobias Schindler, Prof. Dr. Mario Ohlberger)
- Übung: Tutorial Scientific Computing [106233]
(in cooperation with Julia Brunken, Dr. Felix Tobias Schindler) - Praktikum: Introduction to Numerical Programming with Python [106227]
- Vorlesung: Scientific Computing [106232]
(in cooperation with Dr. Felix Tobias Schindler)
- Praktikum: Scientific Computing [103870]
(in cooperation with Dr. Felix Tobias Schindler, Prof. Dr. Mario Ohlberger)
- Praktikum: Practical Course: Model Reduction for Partial Differential Equations [102957]
(in cooperation with René Milk, Prof. Dr. Mario Ohlberger) - V/Ü: Model Order Reduction for Partial Differential Equations [102938]
(in cooperation with Prof. Dr. Mario Ohlberger)
- V/Ü: Model Reduction for Parametrised Partial Differential Equations [100952]
(in cooperation with Dr. Felix Tobias Schindler)
- Praktikum: Introduction to Programming with MATLab [101297]
(in cooperation with Dr. Kathrin Smetana, Prof. Dr. Mario Ohlberger)
- Übung: Module 7: Analytical Chemistry [100450]
(in cooperation with , apl. Prof. Wend Werner)
- Praktikum: Introduction to Numerical Programming with Python [100434]
Software
pyMOR
A modern Python-based model reduction library which can be easily integrated with external PDE solvers Project Page
simdb
A simple Python module for the management of simulation datasets Project Page