Uncertainty Quantification in Computational Fluid Dynamics

Nonfiction, Science & Nature, Mathematics, Counting & Numeration, Computers, Advanced Computing, Computer Science
Cover of the book Uncertainty Quantification in Computational Fluid Dynamics by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319008851
Publisher: Springer International Publishing Publication: September 20, 2013
Imprint: Springer Language: English
Author:
ISBN: 9783319008851
Publisher: Springer International Publishing
Publication: September 20, 2013
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer International Publishing

Cover of the book Residual Stress, Thermomechanics & Infrared Imaging, Hybrid Techniques and Inverse Problems, Volume 7 by
Cover of the book Applications of Social Media and Social Network Analysis by
Cover of the book Adipose Tissue Biology by
Cover of the book The Evaporation Mechanism in the Wick of Copper Heat Pipes by
Cover of the book ICT Innovations for Sustainability by
Cover of the book Control Systems and Mathematical Methods in Economics by
Cover of the book Global Perspectives on Underutilized Crops by
Cover of the book Biology and Biotechnology of Patagonian Microorganisms by
Cover of the book Management of Atopic Dermatitis by
Cover of the book Microalgae Biotechnology by
Cover of the book Interactivity, Collaboration, and Authoring in Social Media by
Cover of the book Marshall Olkin Distributions - Advances in Theory and Applications by
Cover of the book Distributed Computer and Communication Networks by
Cover of the book Designing a Place Called Home by
Cover of the book Narrating Injustice Survival by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy