Nonintrusive model order reduction for cross-diffusion systems

Model Order Reduction of 1D Diffusion Systems Via Residue Grouping

A model order reduction method is developed and applied to 1D diffusion systems with negative real eigenvalues. Spatially distributed residues are found either analytically (from a transcendental transfer function) or numerically (from a finite element or finite difference state space model), and residues with similar eigenvalues are grouped together to reduce the model order. Two examples are ...

Model order reduction of parametrized nonlinear reaction-diffusion systems

We present a model order reduction technique for parametrized nonlinear reaction-diffusion systems. In our approach we combine the reduced basis method — a computational framework for rapid evaluation of functional outputs associated with the solution of parametrized partial differential equations — with the empirical interpolation method — a tool to construct “affine” coefficient-function appr...

Fast Model-order Reduction for Mechatronic Systems

We present recent advances in the mixed symbolic and numeric model reduction techniques for automatically extracting the dominant system behavior of multiphysical systems. A unique feature of our approach is to compute approximated symbolic formulas for linear and nonlinear system characteristics, rigorously reducing the complexity of symbolic expressions while controlling a user-given error bo...

Model reduction of second order systems

where the matrix M ∈ RN×N is assumed to be invertible. Models of mechanical systems are often of this type since (1.1) then represents the equation of motion of the system. For such a system M = MT , C = CT and K = KT are respectively the mass, damping and stiffness matrices, f(t) ∈ RN×1 is the vector of external forces, and x(t) ∈ RN×1 is the vector of internal generalized coordinates (see [4]...

6 Model Reduction of Second - Order Systems