1.

Record Nr.

UNINA9910299987603321

Titolo

Reduced Order Methods for Modeling and Computational Reduction / / edited by Alfio Quarteroni, Gianluigi Rozza

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014

ISBN

3-319-02090-0

Edizione

[1st ed. 2014.]

Descrizione fisica

1 online resource (338 p.)

Collana

MS&A, Modeling, Simulation and Applications, , 2037-5263 ; ; 9

Disciplina

004.0151

Soggetti

Mathematics - Data processing

Numerical analysis

Engineering mathematics

Engineering - Data processing

Mathematical models

Mechanics, Applied

Solids

Mathematical physics

Computational Mathematics and Numerical Analysis

Numerical Analysis

Mathematical and Computational Engineering Applications

Mathematical Modeling and Industrial Mathematics

Solid Mechanics

Theoretical, Mathematical and Computational Physics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

1 W. H. A. Schilders, A. Lutowska: A novel approach to model order reduction for coupled multiphysics problems -- 2 A. C. Ionita, A. C. Antoulas: Case study. Parametrized Reduction using Reduced-Basis and the Loewner Framework -- 3 M. Bebendorf, Y. Maday, B. Stamm: Comparison of some reduced representation approximations -- 4 H. Antil, M. Heinkenschloss, D. C. Sorensen: Application of the Discrete Empirical Interpolation Method to Reduced Order Modeling of Nonlinear and Parametric System -- 5 K. Urban, S. Volkwein, O. Zeeb: Greedy



Sampling using Nonlinear Optimization -- 6 P. Benner, L. Feng: A Robust Algorithm for Parametric Model Order Reduction based on Implicit Moment Matching -- 7 F. Chen, J. S. Hesthaven, X. Zhu: On the use of reduced basis methods to accelerate and stabilize the Parareal method -- 8 C. Farhat, D. Amsallem: On the stability of reduced-order linearized computational fluid dynamics models based on POD and Galerkin projection: descriptor vs non-descriptor forms -- 9 T. Lassila, A. Manzoni, A. Quarteroni, G. Rozza: Model Order Reduction in Fluid Dynamics: Challenges and Perspectives -- 10 L. Grinberg, M. Deng, A. Yakhot, G. Karniadakis: Window Proper Orthogonal Decomposition. Application to Continuum and Atomistic Data -- 11 M. Bergmann, T. Colin, A. Iollo, D. Lombardi, O. Saut, H. Telib: Reduced order models at work in Aeronautics and Medicine.

Sommario/riassunto

This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics.  Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This book is primarily addressed to computational scientists interested in computational reduction techniques for large scale differential problems.