Multiscale Model Reduction

Zusatztext

This monograph is devoted to the study of multiscale model reduction methods from the point of view of multiscale finite element methods. <div> <div>Multiscale numerical methods have become popular tools for modeling processes with multiple scales. These methods allow reducing the degrees of freedom based on local offline computations. Moreover, these methods allow deriving rigorous macroscopic equations for multiscale problems without scale separation and high contrast. Multiscale methods are also used to design efficient solvers. </div><div> </div><div>This book offers a combination of analytical and numerical methods designed for solving multiscale problems. The book mostly focuses on methods that are based on multiscale finite element methods. Both applications and theoretical developments in this field are presented. The book is suitable for graduate students and researchers, who are interested in this topic.</div></div>

Autorenportrait

<b>¿Eric Chung</b> is a Professor in the Department of Mathematics and an Outstanding Fellow of the Faculty of Science at the Chinese University of Hong Kong. His research focuses on numerical discretizations of partial differential equations and the development of computational multiscale methods for challenging applications.<div> </div><div><b>Yalchin Efendiev </b>is a Professor in the Department of Mathematics at the Texas A&M University.<p></p><div> </div><div><b>Thomas Y. Hou</b> is the Charles Lee Powell Professor of Applied and Computational Mathematics at the California Institute of Technology. His research focuses on multiscale analysis and computation, fluid interface problems, and singularity formation of 3D Euler and Navier-Stokes equations. <p> </p> <p> </p></div></div>

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