Reduced-Order Modeling (Rom) for Simulation and Optimization: Powerful Algorithms as Key Enablers for Scientific Computing

ISBN-13: 9783319753188 / Angielski / Twarda / 2018 / 179 str.

Winfried Keiper; Anja Milde; Stefan Volkwein

Opis

This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control.

Spis treści

​Greedy Kernel Approximation for Sparse Surrogate Modelling.- Set-Oriented Multiobjective Optimal Control of

PDEs using Proper Orthogonal Decomposition.- A Direct Index 1 DAE Model of Gas Networks.- Model Order Reduction for Rotating Electrical Machines.- Morembs – a Model Order Reduction Package for Elastic Multibody Systems and Beyond.- An Iterative Model Reduction Scheme for Quadratic-Bilinear Descriptor Systems with an Application to Navier-Stokes Equations.- Sequential Reduced Order Modeling for Time-Dependent Optimization Problems with Initial Value Controls.

Blurb

This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box algorithmic solutions for scientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for electrochemical processes. The target audience comprises research experts and practitioners in the field of simulation, optimization and control, but the book may also be beneficial for graduate students alike.