Implementing Anisotropic Adaptive Mesh Refinement in OpenFOAM

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/174173
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Type: Examensarbete för masterexamen
Master Thesis
Title: Implementing Anisotropic Adaptive Mesh Refinement in OpenFOAM
Authors: Karlsson, Jonas
Abstract: The field of computational fluid dynamics (CFD) is growing steadily, with a rate proportional to the computational tools available. With today’s computing power available in CPU’s and clusters we are able to solve cases that were considered impossible just a few years ago. Although as we all know, even with great computational power and brute-force approaches, some problems will remain unsolvable. With this realization, adaptive mesh refinement (AMR) was introduced as a way of adapting the mesh as to reduce the computational error. AMR is relevant for CFD since it can greatly reduce the computational effort needed to solve a lot of cases. This can in turn make previously intractable simulations solvable. In this thesis we will look at how implementing a specific type of AMR could be done - namely anisotropic AMR for the OpenFOAM code-base. We will briefly look at some papers to get an idea of what constraints the mesh should satisfy and to see what kind of data-structure for the refinement history is needed. We will also look at similar functionality currently available in the OpenFOAM code. With this knowledge we define a design criteria we will use for implementing anisotropic AMR in OpenFOAM. This implementation will result in a working example of anisotropic AMR. We have also defined a tree used for storing the refinement changes that can be used for other types of AMR in the OpenFOAM codebase. We also show some graphical results of a case refined using the anisotropic AMR defined in this thesis and compare these to an isotropic refinement.
Keywords: Data- och informationsvetenskap;Computer and Information Science
Issue Date: 2013
Publisher: Chalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)
Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers)
URI: https://hdl.handle.net/20.500.12380/174173
Collection:Examensarbeten för masterexamen // Master Theses



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