Uncertainty Quantification in Computational Fluid Dynamics (Paperback, Softcover reprint of the original 1st ed. 2013)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Lecture Notes in Computational Science and Engineering, 92
Release date:	August 2016
First published:	2013
Editors:	Hester Bijl • Didier Lucor • Siddhartha Mishra • Christoph Schwab
Dimensions:	235 x 155 x 19mm (L x W x T)
Format:	Paperback
Pages:	333
Edition:	Softcover reprint of the original 1st ed. 2013
ISBN-13:	978-3-319-34666-3
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Science & Mathematics > Physics > General Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Professional & Technical > Transport technology > Aerospace & aviation technology > General
LSN:	3-319-34666-0
Barcode:	9783319346663

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