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[资源]
2013CFD新书Uncertainty Quantification in Computational Fluid Dynamics
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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. Table of contents : Content: Front Matter....Pages i-xi Non-intrusive Uncertainty Propagation with Error Bounds for Conservation Laws Containing Discontinuities....Pages 1-57 Uncertainty Quantification in Aeroelasticity....Pages 59-103 Robust Uncertainty Propagation in Systems of Conservation Laws with the Entropy Closure Method....Pages 105-149 Adaptive Uncertainty Quantification for Computational Fluid Dynamics....Pages 151-191 Implementation of Intrusive Polynomial Chaos in CFD Codes and Application to 3D Navier-Stokes....Pages 193-223 Multi-level Monte Carlo Finite Volume Methods for Uncertainty Quantification in Nonlinear Systems of Balance Laws....Pages 225-294 Essentially Non-oscillatory Stencil Selection and Subcell Resolution in Uncertainty Quantification....Pages 295-333 Back Matter....Pages 335-341 |
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2014-11-02 10:22:49, 16.43 M
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