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Reduced Basis Summer School 2014


The reduced basis summer school is an event made by young scientists for young scientists. It aims at master students and PhD students in the field of Model Order Reduction and especially, but no exclusively, Reduced Basis Methods. Topics:
  • Reduced Basis Methods
  • Model Reduction for Parametrized Systems
  • Balanced Truncation
  • POD Methods

As the main purpose of this event is to get to know each other, everyone is encouraged to give a talk, even if the talk just introduces the topic and no earthshaking results are available yet. It is the fourth event of this kind.

Date and Location

The Reduced Basis Summer School 2014 will take place August 18th to 22nd, 2014 in Münster, Germany. It will be held at Hotel Münnich, which is conveniently reachable from Münster Central Station: Google Maps Directions.

Registration and Fees

The conference fee, including accomodation in a two bed room, meals and WiFi is € 370. Single rooms are available on request. Registration deadline is June 7th. To register please send an email to andreas.buhr@uni-muenster.de containing the following information:
  • Name
  • Institute
  • University (with address)
  • Mail Address
  • Presentation Title
Registration can be cancelled without any cost until May 31st.

Contact

If you have any questions, feel free to contact the local organization team at any time:
Program

  • Participant Talks (Timetable) Updated!
  • Model Reduction Software Short Communications
  • MORwiki Presentation
  • Guided City Tour
  • Conference Dinner
  • All Slides

Participants

NameUniversityPresentation Title
Eduard BaderAICES, RWTH AachenOnline-Efficient Reduced Basis Methods for Contact
and Other Problems in Nonlinear Solid Mechanics
Andreas BarthlenFraunhofer ITWMStable Parametric Model Reduction using Matrix Interpolation
Olena BurkovskaTU MünchenReduced Basis Method to Option Pricing
Andreas BuhrUniversity of MünsterInteractive Simulations using the Localized Reduced Basis Method
Robert O'ConnorIGPM, RWTH AachenReduced-Basis Modelling for Optimal-Control Problems
Martin EllerTU DarmstadtReduced Basis Methods for Maxwell's equations
Dominik GarmatterUniversity of StuttgartReduced Basis Methods for Inverse Problems
Silke GlasUniversity of UlmReduced Basis Methods for Variational Inequalities
Pawan GoyalMPI MagdeburgInterpolatory Model Order Reduction for Bilinear Descriptor Systems
Martin GubischUniversity of KonstanzOptimality System Pod for State Constrained Optimal Control Problems
Christian HimpeUniversity of MünsterYet Another Talk About Empirical Gramians
Johanna KerlerUniversity of AugsburgModel order reduction and Dynamic Iteration for coupled systems
Adrian MaroniPolitecnico di TorinoMulti-scale Modelling of Heat Exchangers for Electronic Cooling Through RBM
Immanuel MartiniUniversity of StuttgartReduced basis methods for heterogeneous domain decomposition
Antonia MayerhoferUniversity of UlmRBM for parabolic PDEs with parameter functions and
application to option pricing
Falk MeyerUniversity of Münster--
Mladjan RadicUniversity of UlmReduced Basis Approximation of Coupled Problems
Andreas SchmidtUniversity of StuttgartFeedback Control of Parametric PDEs with RB-Surrogate Models
Jan Henrik SchmidtKIT Karlsruhe--
Rakesh SarmaDelft UniversitySystem identification based approach for reconstruction of
aeroelastic response
Jos Pedro SilvaUniversity of Wuppertal--
Sebastian SteckUniversity of UlmReduced Basis Method for Hamilton-Jacobi-Bellman equations
Johannes StemickRWTH AachenRB for a Multiscale Stokes Flow
Maximilian WaltherUniversity of
Erlangen-Nürnberg
Model reduction for partial differential equations on networks
Andrea WescheUniversity of KonstanzRBM on Battery
Oliver ZeebUniversity of UlmTowards automatic RBM
Zhenying ZhangAICES, RWTH AachenReduced Basis Approximation for Parametrized Contact Problems

Software Short Communications

ProjectNameWebsite
pyMOR Model Order Reduction with Pythonpymor.org
RBmatlab Reduced Basis Matlab Software@morepas.org
emgr Empirical Gramian Frameworkgramian.de
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