G. Rozza1, K. Veroy Grepl2
1EPFL/CH, 2RWTH Aachen/DE
This proposed minisymposium will consider a range of model reduction strategies with applications in real-time computing. The increasing complexity of mathematical models used to predict real-world systems, such as the climate or the human cardiovascular system, has lead to a need for model reduction techniques. Such techniques develop systematic algorithms for substituting complex models with ones that are far simpler but nevertheless accurately capture the most important aspects of the phenomena being modeled. Some subtopics include state space and parameter space reduction -- with a special emphasis on reduced basis methods and proper orthogonal decomposition. The minisymposium will emphasize model reduction topics in several themes:
A strong attention is on mathematical models based on parametrized ordinary and partial differential equations. We will emphasize engineering and life-sciences applications, including continuum mechanics, fluid dynamics, and transport problems. Other mathematical frameworks and application domains may also be considered to provide perspective and opportunity for "technology transfer" and interdisciplinary exchanges. However, even if the focus of the minisymposium is methodological, we expect a wide range of both academic and industrial problems of high complexity to motivate, stimulate, and ultimately demonstrate the meaningfulness and efficiency of the proposed approaches. The emphasis on real-time computing applications, and above all real-time visualization, can be seen as a new frontier in scientific computing to assist scientists and engineers during design, construction, manufacturing or production phases, and even medical doctors during surgery or diagnosis. Reduced order modelling has found a wide range of applications in several areas in science and computational engineering, and its increasing popularity is underscored by the many minisymposia at conferences such as ICOSAHOM, ECCOMAS CFD, SIAM CSE and ICIAM in the last few years.
The aim of this minisymposium is to discuss successful developments, to address current challenges, and to identify new directions. The objectives of the minisymposium are focused on a strong interaction and integration of several contributions on model order reduction developed in the last few years in diff erent fields and with different purposes.
The goals are: