Model Reduction for Parametrized Systems
Modern discretization techniques for differential equations yield high dimensional simulation models, which require high computational effort for determining approximate solutions. This even gets more problematic, if many of such simulations are required, e.g. for parametrized problems. Such settings can be parameter studies, interactive simulations, parameter identification problems, statistical investigations, etc.
For such problems, efficient techniques for dimensionality reduction are desirable. In addition to fast algorithms, also error quantification is crucial. Methods for this can be found and are developed in the fields of Reduced Basis (RB) techniques for parametrized partial differential equations and Model Order Reduction (MOR) for parametrized dynamical systems. On the present website, we present our collaborative work on these questions.
- 05.09.2016: A new postdoctoral research position in
Numerical Analysis and Scientific Computing (with applications) is
open at SISSA, International School for Advanced Studies, Mathematics
Area, mathLab division, Trieste, Italy. This position is in the
framework of the ERC (European Research Council) Consolidator Grant
AROMA-CFD, Advanced Reduced Order Methods with Applications in
Computational Fluid Dynamics, PI Prof. Gianluigi Rozza (Project
681447). Applications info, details and requirements are available at
The announcement is in Italian and in English. Application deadline is September 8, 2016 at 1pm (CET).
Fields of the research activity: Mathematical modeling, numerical analysis and simulation for the complex systems held by parametrized PDEs, computational fluid dynamics for optimization, control, inverse problems, uncertainty quantification, data assimilation; scientific computing programming, high performance computing and/or large scale computing competences. Additional requirements, competencies and abilities: Good knowledge of high level programming languages, e.g., C/C++/Python; Scientific Computing software libraries, Reduced Order modeling techniques (reduced basis methods, POD, PGD), efficient geometrical parametrization techniques, spectral methods, stability and bifurcations. For more info and details you can contact Gianluigi Rozza (website).
- 28.06.2016: Version 4.0 of emgr (empirical gramian framework) has been released. See http://gramian.de for more information.
- 12.04.2016: The 6th Reduced Basis Summer School is organized by the AG Benner from the MPI Magdeburg. It will take place from the 4th to the 7th of October 2016; registration deadline: 17th of June 2016.
- 12.04.2016: A postdoctoral research position in Numerical Analysis and Scientific Computing (with applications) is open at SISSA, International School for Advanced Studies, Mathematics Area, mathLab division, Trieste, Italy. Further information are given in this document.