Title
Uncertainty Quantification in Computational Fluid Dynamics (Lecture Notes in Computational Science and Engineering, 92),Used
Delivery time: 8-12 business days (International)
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 socalled multilevel Monte Carlo method (MLMC)), momentbased stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENOWENO 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 (fluidstructure 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.
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This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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