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Uncertainty Quantification in Computational Fluid Dynamics

  • Book
  • © 2013

Overview

Editors:
  1. Hester Bijl

    1. Faculty of Aerospace Engineering, TU Delft, Delft, The Netherlands

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  2. Didier Lucor

    1. d' Alembert Institute-CNRS, Université Pierre et Marie Curie - Paris VI, Paris, France

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  3. Siddhartha Mishra

    1. Seminar für Angewandte Mathematik, ETH Zürich, Zürich, Switzerland

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  4. Christoph Schwab

    1. ETH Zürich Seminar für Angewandte Mathematik, Zürich, Switzerland

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  • Presentation of the highly relevant issue of UQ in CFD
  • A broad spectrum of methods to efficiently compute uncertainty
  • Large number of numerical examples as verification of the proposed methods and their possible comparison?

Part of the book series: Lecture Notes in Computational Science and Engineering (LNCSE, volume 92)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xi
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  2. Non-intrusive Uncertainty Propagation with Error Bounds for Conservation Laws Containing Discontinuities

    • Timothy Barth
    Pages 1-57

  3. Uncertainty Quantification in Aeroelasticity

    • Philip Beran, Bret Stanford
    Pages 59-103

  4. Robust Uncertainty Propagation in Systems of Conservation Laws with the Entropy Closure Method

    • Bruno Després, Gaël Poëtte, Didier Lucor
    Pages 105-149

  5. Adaptive Uncertainty Quantification for Computational Fluid Dynamics

    • Richard P. Dwight, Jeroen A. S. Witteveen, Hester Bijl
    Pages 151-191

  6. Implementation of Intrusive Polynomial Chaos in CFD Codes and Application to 3D Navier-Stokes

    • Chris Lacor, Cristian Dinescu, Charles Hirsch, Sergey Smirnov
    Pages 193-223

  7. Multi-level Monte Carlo Finite Volume Methods for Uncertainty Quantification in Nonlinear Systems of Balance Laws

    • Siddhartha Mishra, Christoph Schwab, Jonas Šukys
    Pages 225-294

  8. Essentially Non-oscillatory Stencil Selection and Subcell Resolution in Uncertainty Quantification

    • Jeroen A. S. Witteveen, Gianluca Iaccarino
    Pages 295-333

  9. Back Matter

    Pages 335-341
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Keywords

About this book

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.

Editors and Affiliations

  • Faculty of Aerospace Engineering, TU Delft, Delft, The Netherlands

    Hester Bijl

  • d' Alembert Institute-CNRS, Université Pierre et Marie Curie - Paris VI, Paris, France

    Didier Lucor

  • Seminar für Angewandte Mathematik, ETH Zürich, Zürich, Switzerland

    Siddhartha Mishra

  • ETH Zürich Seminar für Angewandte Mathematik, Zürich, Switzerland

    Christoph Schwab

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