TY - BOOK ID - 8285547 TI - Uncertainty quantification in computational fluid dynamics PY - 2013 VL - 92 SN - 3319008846 3319008854 PB - Heidelberg [Germany] : Springer, DB - UniCat KW - Computational fluid dynamics. KW - Mathematics KW - Physical Sciences & Mathematics KW - Mathematics - General KW - Aeroelasticity. KW - Fluid dynamics. KW - Mathematics. KW - Computer mathematics. KW - Physics. KW - Applied mathematics. KW - Engineering mathematics. KW - Aerospace engineering. KW - Astronautics. KW - Computational Mathematics and Numerical Analysis. KW - Computational Science and Engineering. KW - Appl.Mathematics/Computational Methods of Engineering. KW - Aerospace Technology and Astronautics. KW - Numerical and Computational Physics. KW - Dynamics KW - Fluid mechanics KW - Aerodynamics KW - Elastic waves KW - Elasticity KW - Computer science KW - Computer science. KW - Mathematical and Computational Engineering. KW - Numerical and Computational Physics, Simulation. KW - Space sciences KW - Aeronautics KW - Astrodynamics KW - Space flight KW - Space vehicles KW - Engineering KW - Engineering analysis KW - Mathematical analysis KW - Informatics KW - Science KW - Computer mathematics KW - Discrete mathematics KW - Electronic data processing KW - Natural philosophy KW - Philosophy, Natural KW - Physical sciences KW - Aeronautical engineering KW - Astronautics KW - Uncertainty KW - Mathematical models. UR - https://www.unicat.be/uniCat?func=search&query=sysid:8285547 AB - 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. ER -