Curved Domain Adaptive Mesh Refinement with Hexahedra

In tree-based adaptive mesh refinement (AMR) we store refinement trees in the cells of an unstructured coarse mesh. This lets us combine the speed and simpler management of structured refinement trees with the more flexible mesh generation of the unstructured coarse mesh. But this creates a conflict between performance and geometrical accuracy. If we favor speed we reduce the cells in our coarse mesh and hence reduce the accuracy of our geometrical representation. If we want more accurate results we generate a finer coarse mesh and lose performance by managing more cells in our unstructured coarse mesh. To mitigate this conflict we present the prototype of an geometry description which we implement in an already existing library. With this description we build geometry adapted hexahedral refinement trees, which also support high-order curved boundary cells. We also present examples on how to use this description. Moreover, we test the speedup of this new algorithm compared with coarse meshes with different geometrical errors

Evaluation and generic application scenarios for curved hexahedral adaptive mesh refinement

In (dynamic) adaptive mesh refinement (AMR) an input mesh is refined or coarsened to the need of the numerical application. This refinement happens with no respect to the originally meshed domain and is therefore limited to the geometrical accuracy of the original input mesh. We presented a novel approach to equip this input mesh with additional geometry information, to allow refinement and high-order cells based on the geometry of the original domain. We already showed a limited implementation of this algorithm. Now we evaluate this prototype with a numerical application and we prove its influence on the accuracy of certain numerical results. To be as practical as possible, we implement the ability to import meshes generated by Gmsh and equip them with the needed geometry information. Furthermore, we improve the mapping algorithm, which maps the geometry information of the boundary of a cell into the cell's volume. With these preliminary steps done, we use out new approach in a simulation of the advection of a concentration along the boundary of a sphere shell and past the boundary of a rotating cylinder. We evaluate the accuracy of our approach in comparison to the conventional refinement of cells to answer our research question: How does the performance and accuracy of the hexahedral curved domain AMR algorithm compare to linear AMR when solving the advection equation with the linear finite volume method? To answer this question, we show the influence of curved AMR on our simulation results and see, that it is even able to outperform far finer linear meshes in terms of accuracy. We also see that the current implementation of this approach is too slow for practical usage. We can therefore prove the benefits of curved AMR in certain, geometry-related application scenarios and show possible improvements to make it more feasible and practical in the future

Constructing a Volume Geometry Map For Hexahedra With Curved Boundary Geometries (Presentation)

In (dynamic) adaptive mesh refinement (AMR), a given input mesh is refined and coarsened during the computation to optimally adapt the resolution of the computational mesh to specific requirements. The input mesh is often the output of a mesh generator and provides information on the geometry of the domain. It is desired to keep its resolution as coarse as possible in order to benefit from the AMR mesh hierarchy and efficient mesh indexing algorithms. We present a novel approach to equip the coarse mesh with high-order geometry data and evaluate this geometry on the fine mesh elements in order to ensure geometric accuracy of the refined mesh elements, even for coarse input meshes. To this end, we construct a volume geometry map for hexahedral cells from given curved boundary geometry data and discuss our implementation in a state-of-the-art AMR library

Constructing a Volume Geometry Map for Hexahedra with Curved Boundary Geometries

: In (dynamic) adaptive mesh refinement (AMR), a given input mesh is refined and coarsened during the computation to optimally adapt the resolution of the computational mesh to specific requirements. The input mesh is often the output of a mesh generator and provides information on the geometry of the domain. It is desired to keep its resolution as coarse as possible in order to benefit from the AMR mesh hierarchy and efficient mesh indexing algorithms. We present a novel approach to equip the coarse mesh with high-order geometry data and evaluate this geometry on the fine mesh elements in order to ensure geometric accuracy of the refined mesh elements, even for coarse input meshes. To this end, we construct a volume geometry map for hexahedral cells from given curved boundary geometry data and discuss our implementation in a state-of-the-art AMR library

Constructing a Volume Geometry Map for Hexahedra with Curved Boundary Geometries

: In (dynamic) adaptive mesh refinement (AMR), a given input mesh is refined and coarsened during the computation to optimally adapt the resolution of the computational mesh to specific requirements. The input mesh is often the output of a mesh generator and provides information on the geometry of the domain. It is desired to keep its resolution as coarse as possible in order to benefit from the AMR mesh hierarchy and efficient mesh indexing algorithms. We present a novel approach to equip the coarse mesh with high-order geometry data and evaluate this geometry on the fine mesh elements in order to ensure geometric accuracy of the refined mesh elements, even for coarse input meshes.\ud To this end, we construct a volume geometry map for hexahedral cells from given curved boundary geometry data and discuss our implementation in a state-of-the-art AMR library

t8code - scalable and modular adaptive mesh refinement

t8code is a versatile open source library for parallel adaptive mesh refinement on hybrid meshes. [1] It is exascale-ready and capable of efficiently managing meshes with up to a trillion elements distributed on a million of cores as already shown in a peer-reviewed research paper. [2] On the top-level, t8code uses forests of trees to represent unstructured meshes with complex geometries. Space-filling curves index individual elements within a forest, which requires only minimal amounts of memory allowing for efficient and scalable algorithms of mesh management. In contrast to existing solutions, t8code has the capability to manage an arbitrary number of tetrahedra, hexahedra, prisms and pyramids within the same mesh. With this poster we want to present the first official release (v1.0) of our software and give a quick overview over its main features. Besides presenting the core algorithms of t8code, we give application scenarios on how our library integrates into major simulation frameworks for weather forecasting, climate modeling and engineering; and how they benefit from our approach to do AMR. [1] https://github.com/DLR-AMR/t8code [2] https://epubs.siam.org/doi/abs/10.1137/20M138303

Evaluation and generic application scenarios for curved hexahedral adaptive mesh refinement

In (dynamic) adaptive mesh refinement (AMR) an input mesh is refined or coarsened to the need of the numerical application. This refinement happens with no respect to the originally meshed domain and is therefore limited to the geometrical accuracy of the original input mesh. We presented a novel approach to equip this input mesh with additional geometry information, to allow refinement and high-order cells based on the geometry of the original domain. We already showed a limited implementation of this algorithm. Now we evaluate this prototype with a numerical application and we prove its influence on the accuracy of certain numerical results. To be as practical as possible, we implement the ability to import meshes generated by Gmsh and equip them with the needed geometry information. Furthermore, we improve the mapping algorithm, which maps the geometry information of the boundary of a cell into the cell's volume. With these preliminary steps done, we use out new approach in a simulation of the advection of a concentration along the boundary of a sphere shell and past the boundary of a rotating cylinder. We evaluate the accuracy of our approach in comparison to the conventional refinement of cells to answer our research question: How does the performance and accuracy of the hexahedral curved domain AMR algorithm compare to linear AMR when solving the advection equation with the linear finite volume method? To answer this question, we show the influence of curved AMR on our simulation results and see, that it is even able to outperform far finer linear meshes in terms of accuracy. We also see that the current implementation of this approach is too slow for practical usage. We can therefore prove the benefits of curved AMR in certain, geometry-related application scenarios and show possible improvements to make it more feasible and practical in the future

Curved Domain Adaptive Mesh Refinement with Hexahedra

In tree-based adaptive mesh refinement (AMR) we store refinement trees in the cells of an unstructured coarse mesh. This lets us combine the speed and simpler management of structured refinement trees with the more flexible mesh generation of the unstructured coarse mesh. But this creates a conflict between performance and geometrical accuracy. If we favor speed we reduce the cells in our coarse mesh and hence reduce the accuracy of our geometrical representation. If we want more accurate results we generate a finer coarse mesh and lose performance by managing more cells in our unstructured coarse mesh. To mitigate this conflict we present the prototype of an geometry description which we implement in an already existing library. With this description we build geometry adapted hexahedral refinement trees, which also support high-order curved boundary cells. We also present examples on how to use this description. Moreover, we test the speedup of this new algorithm compared with coarse meshes with different geometrical errors

Windmillception

Shown is the dynamically adapted mesh of a provided Dutch windmill geometry. The adaptation and management was handled by the highly scalable AMR library t8code, which is mainly developed at the DLR

t8code

t8code is a C/C++ library to manage parallel adaptive meshes with various element types. t8code uses a collection (a forest) of multiple connected adaptive space-trees in parallel and scales to at least one million MPI ranks and over 1 Trillion mesh elements. t8code uses space-filling curves (SFCs) to manage the adaptive refinement and efficiently store the mesh elements and associated data