Lecture Notes in Computational Science and Engineering

Bijl, Hester; Lucor, Didier; Mishra, Siddhartha; Schwab, Christoph

Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches.

Details

Published by: Springer

Publication Date: 2013-10-07

Format: Hardcover

ISBN-13: 9783319008844

DOI: 10.1007/978-3-319-00885-1

Dimensions: 235cm x155cm

Pages: 333