000 04035nam a22005655i 4500
001 978-3-319-00885-1
003 DE-He213
005 20140220082839.0
007 cr nn 008mamaa
008 130920s2013 gw | s |||| 0|eng d
020 _a9783319008851
_9978-3-319-00885-1
024 7 _a10.1007/978-3-319-00885-1
_2doi
050 4 _aQA71-90
072 7 _aPBKS
_2bicssc
072 7 _aMAT006000
_2bisacsh
082 0 4 _a518
_223
082 0 4 _a518
_223
100 1 _aBijl, Hester.
_eeditor.
245 1 0 _aUncertainty Quantification in Computational Fluid Dynamics
_h[electronic resource] /
_cedited by Hester Bijl, Didier Lucor, Siddhartha Mishra, Christoph Schwab.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2013.
300 _aXI, 333 p. 188 illus., 115 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computational Science and Engineering,
_x1439-7358 ;
_v92
505 0 _aTimothy Barth: Non-Intrusive Uncertainty Propagation with Error Bounds for Conservation Laws Containing Discontinuities -- Philip Beran and Bret Stanford: Uncertainty Quantification in Aeroelasticity -- Bruno Després, Gaël Poëtte and Didier Lucor: Robust uncertainty propagation in systems of conservation laws with the entropy closure method -- Richard P. Dwight, Jeroen A.S. Witteveen and Hester Bijl: Adaptive Uncertainty Quantification for Computational Fluid Dynamics -- Chris Lacor, Cristian Dinescu, Charles Hirsch and Sergey Smirnov: Implementation of intrusive Polynomial Chaos in CFD codes and application to 3D Navier-Stokes -- Siddhartha Mishra, Christoph Schwab and Jonas Šukys: Multi-level Monte Carlo Finite Volume Methods for Uncertainty Quantification in nonlinear systems of balance laws -- Jeroen A.S. Witteveen and Gianluca Iaccarino: Essentially Non-Oscillatory Stencil Selection and Subcell Resolution in Uncertainty Quantification.
520 _aFluid 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.
650 0 _aMathematics.
650 0 _aComputer science
_xMathematics.
650 0 _aComputer science.
650 0 _aEngineering mathematics.
650 0 _aAstronautics.
650 1 4 _aMathematics.
650 2 4 _aComputational Mathematics and Numerical Analysis.
650 2 4 _aComputational Science and Engineering.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aAerospace Technology and Astronautics.
650 2 4 _aNumerical and Computational Physics.
700 1 _aLucor, Didier.
_eeditor.
700 1 _aMishra, Siddhartha.
_eeditor.
700 1 _aSchwab, Christoph.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319008844
830 0 _aLecture Notes in Computational Science and Engineering,
_x1439-7358 ;
_v92
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-00885-1
912 _aZDB-2-SMA
999 _c96489
_d96489