TY - GEN
T1 - Fluid Flow Simulation from Geometry Data Based on Point Clouds
AU - Santoso, Simon
AU - Bouchiba, Hassan
AU - Silva, Luisa
AU - Goulette, Francois
AU - Coupez, Thierry
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - It is nowadays a real challenge to perform fluid flow simulation from human-acquired data, in particular when the geometries are reduced to a set of 3D points without any connectivity. Assuming that a sufficient set of points can represent the underlying geometries with a high level of details, we present in this paper a method to perform CFD computations directly from the point cloud raw data. Using an error estimator, a level-set function is built directly from the point cloud, which bypass the explicit surface reconstruction step. The level-set is then used in a mesh-adaptation procedure to optimize the representation of the distance field near the its zero value. Secondly, we use the immersion volume method to define the boundary conditions at nodes. Finally, we used a VMS finite element solver to perform the fluid flow calculation. We finally present computations on 3D point clouds self-acquired in urban environments.
AB - It is nowadays a real challenge to perform fluid flow simulation from human-acquired data, in particular when the geometries are reduced to a set of 3D points without any connectivity. Assuming that a sufficient set of points can represent the underlying geometries with a high level of details, we present in this paper a method to perform CFD computations directly from the point cloud raw data. Using an error estimator, a level-set function is built directly from the point cloud, which bypass the explicit surface reconstruction step. The level-set is then used in a mesh-adaptation procedure to optimize the representation of the distance field near the its zero value. Secondly, we use the immersion volume method to define the boundary conditions at nodes. Finally, we used a VMS finite element solver to perform the fluid flow calculation. We finally present computations on 3D point clouds self-acquired in urban environments.
KW - Anisotropic adaptive meshing
KW - Finite element for flow
KW - Immersed boundary method
KW - Point cloud geometry
U2 - 10.1007/978-3-030-30705-9_10
DO - 10.1007/978-3-030-30705-9_10
M3 - Conference contribution
AN - SCOPUS:85081717186
SN - 9783030307042
T3 - Lecture Notes in Computational Science and Engineering
SP - 109
EP - 119
BT - Numerical Methods for Flows - FEF 2017 Selected Contributions
A2 - van Brummelen, Harald
A2 - Corsini, Alessandro
A2 - Perotto, Simona
A2 - Rozza, Gianluigi
PB - Springer
T2 - 19th International Conference on Finite Elements in Flow Problems, FEF 2017
Y2 - 5 April 2017 through 7 April 2017
ER -