Matthew Zahr, University of Notre Dame
Youngsoo Choi, Lawrence Livermore National Laboratory
Masayuki Yano, University of Toronto
While physical simulation has become an indispensable tool in engineering design and analysis, a number of real-time and many-query applications remains out of reach for classical high-fidelity analysis techniques. Model reduction is one approach to reduce the computational cost in these applications while minimizing the error introduced in the reduction process. In this mini-symposium, we discuss recent developments in model reduction techniques. Topics include, but not limited to: model-reduction techniques for flow control, poroelastic media, coupled flow-geomechanics, contact problems, design optimization, inverse problems, uncertainty quantification, advection-dominated problems, Lagrangian coherent structure, and turbulence modeling problems; treatment of the parameter space with a large dimension; efficient reduction of nonlinear operators; (Petrov–)Galerkin schemes; residual and goal-oriented error estimation and adaptivity; and demonstration of model-reduction techniques for large-scale industry-relevant problems. The minisymposium will bring together researchers working on both fundamental and applied aspects of model reduction to provide a forum for discussion, interaction, and assessment of techniques.