Uncertainty Quantification in Computational Fluid Dynamics (2013) (Lecture Notes in Computational Science and Engineering #92)

By: Hester Bijl, Didier Lucor, Siddhartha Mishra and Christoph Schwab

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Synopsis: 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.

Book Quality:: Publisher Quality
ISBN-13:: 9783319008851
Related ISBNs:: 9783319008844
Publisher:: Springer International Publishing
Date of Addition:: 08/09/22
Copyrighted By:: Springer International Publishing Switzerland
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Computers and Internet, Technology, Earth Sciences, Mathematics and Statistics
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.
Edited by:: Hester Bijl
Edited by:: Didier Lucor
Edited by:: Siddhartha Mishra
Edited by:: Christoph Schwab

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