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Uncertainty Quantification in Computational Fluid Dynamics

LNCSE: UNCRTNTY QNTFCTN IN COMPUTATIONAL FLUID DYNAMICS

Information Technology

Computing & Information Technology

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B2B GT

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B2B & B2C

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.

POST SECONDARY FOUR YEAR

COLFR

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COLSR

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Preface.
Contents.
1: Non-Intrusive Uncertainty Propagation with Error Bounds for Conservation Laws Containing Discontinuities.
2: Uncertainty Quantification in Aeroelasticity.
3: Robust Uncertainty Propagation in Systems of Conservation Laws with the Entropy Closure Method.
4: Adaptive Uncertainty Quantification for Computational Fluid Dynamics.
5: Implementation of Intrusive Polynomial Chaos in CFD Codes and Application to 3D Navier-Stokes.
6: Multi-Level Monte Carlo Finite Volume Methods for Uncertainty Quantification in Nonlinear Systems of Balance Laws.
7: Essentially Non-Oscillatory Stencil Selection and Subcell Resolution in Uncertainty Quantification.
Editorial Policy.
Lecture Notes in Computational Science and Engineering.
Monographs in Computational Scienceand Engineering.
Texts in Computational Scienceand Engineering.

Uncertainty Quantification in Computational Fluid Dynamics.css-1p8rvzy{position:absolute;padding-left:8px;}

Uncertainty Quantification in Computational Fluid Dynamics