# Simple CFD Simulations and Visualisation using OpenFOAM and ParaView. Sachiko Arvelius, PhD

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1 Simple CFD Simulations and Visualisation using OpenFOAM and ParaView Sachiko Arvelius, PhD

2 Purpose of this presentation To show my competence in CFD (Computational Fluid Dynamics) simulation and visualisation using OpenFOAM ( and ParaView ( To suggest potential hydrological applications by OpenFOAM 2

3 OpenFOAM (2.4.0) on Linux-platform Visualisation by ParaView (4.1.0) 3

4 Simple case for CFD simulation Lid-driven cavity flow in a two-dimensional square domain. All the boundaries of the square are walls. The top wall moves in the xdirection at a speed of 1 m/s while the other 3 are stationary. The flow to be simulated is laminar (Re=10 102) to turbulent (Re=104), but isothermal and incompressible. 4

5 Set-ups for Lid-driven cavity flow dz=0.01 m *Only the internal mesh (for volume fields) is shown. Number of cells: 20x20x1 (so that the size of one cell is 0.005(m)x0.005(m)x0.01(m)). Mesh grading towards the wall is not necessary when using the standard k-ε model for turbulent flow (e.g. Re=104). Therefore, all the cases use the same geometry. Using Navier-Stokes equation with only kinematic quantities, i.e. no external force such as gravity (g). Changing Re (Reynolds Number) from 10 to 104 logarithmically. Using the laminar model for Re

6 Simulation Results Shown by the distribution and the profile (along Y-axis in a slice normal to X-direction, See the figure on the left side) of kinematic pressure (p=p/ρ0 and the unit is m2s-2). because the velocity field converges faster than the pressure field. 6

7 Kinematic pressure distribution and profile for the lid-driven cavity flow, laminar (Re=102) to turbulent (Re=104) Re=102 Time=0.5 s Re=103 Re=104 Time=1.0 s 7

8 Re=102 Time=1.5 s Re=103 Re=104 Time=2.0 s The pressure field for Re=102 converged before Time=2.0 s. Therefore the run is terminated at Time=2.0 s. Time=4.0 s 8

9 Re=103 Re=104 Time=6.0 s For the case of Re=103, a cavity started to develop nearby the top-right corner and shifted to the centre as time passes. The pressure field is fluctuating and never converges and thus the run is terminated at Time=8 s. 4 For the case of Re=10, a cavity is developing continuously because the shear energy (by moving lid) which is converted into turbulent kinetic energy is supplied continuously. Time=8.0 s 9

10 Simulation Results Converged velocity field for the case of Re=104. The velocity field converged at around Time=4.9 s. The distribution of the turbulent kinetic energy (k [m2s-2]) at Time=0.5 s (left) and Time=4.0 s (right). As seen in the figures, The energy generation takes place continuously nearby the right-hand side wall (close to X=0.1). 10

11 VOF and Parallel Processing for CFD simulation Dam break A transient flow of two fluids (water and air) separated by a sharp interface. VOF is the volume of fluid method in which a specie transport equation is used to determine the relative volume fraction of the two phases, or phase fraction (α), in each computational cell. 11

12 Phase fraction (α) in VOF Volume Field (air) (water) Boundary The computational volume field is initially set as non-uniform, i.e. water and air, and the interface between them is separated sharply by phase fraction (α). The phase fraction can have any value between 0 and 1, and 0 means air and 1 does water in this case. An interface between the species is not explicitly computed by the VOF method. Therefore α=0.65 means that water occupies the volume of the cell by 65%. The transitional colours (i.e. colours for 0<α<1, neither red nor blue) are due to the interpolation. 12

13 Comparison in terms of mesh resolutions, of a transient flow of two fluids finer resolution Time=0.2 s. The water hits the obstacle and collapses. The bounce of the water in the finer resolution has a detailed structure interpreted as splash. Time=0.6 s. The behaviour of the water after collapsing is much complicated but sharp for the finer resolution. One can see a clear void in the opposite side of the obstacle in the finer resolution case. 13

14 Comparison in terms of mesh resolutions, of a transient flow of two fluids (continued) finer resolution Time=1.0 s. The bounce-off sharpness of the returning wave is different: the shaper, the finer. There are still several voids seen in the finer resolution case. Time=1.6 s. The free surface of the water, i.e. the interface between water and air, is still complicated for the finer resolution case. 14

15 Run Time and Parallel Processing The Courant number is variable because that the meshes are non-uniform and the cells are fractionated. The number of iterations (No Iterations) has no meaning for simulating a transient flow. The above is a run log for the dam break simulation. The number of cells for this simulation is 2268 and it took s for the 2-second simulation. Very simply, the execution time per mesh took 5.75 ms. 15

16 Run Time and Parallel Processing (continued) The above is a run log for the dam break simulation with the higher mesh resolution. The number of cells for this simulation is 7700 and it took s for the 2-second simulation. Very simply, the execution time per mesh took ms and it took almost double time compared to the previous case. 16

17 Run Time and Parallel Processing (continued) The CPU specification of the machine is Intel CoreTM x 2 cores (x 2 threads) Therefore it is possible to execute 4-CPU parallel processing. The below is the beginning of a run log for multi (e.g. 4 for this case) parallel processing. 17

18 Run Time and Parallel Processing (continued) The above is a run log for the dam break simulation with the higher mesh resolution. The number of meshes for this simulation is 7700 and it took only s for the 2-second simulation, and reducing about 32% of the execution time thanks to the 4-CPU parallel processing. 18

19 Comparison between single-processed and multi-processed (domain decomposition) Process 2, Time=0 s Process 3, Time=0 s No decompose, Time=0 s Process 1, Time=0 s Process 0, Time=0 s 19

20 Comparison between single-processed and multi-processed (domain decomposition) (continued) Process 3, Time=0.3 s No decompose, Time=0.3 s Process 0, Time=0.3 s Process 1, Time=0.3 s 20

21 Comparison between single-processed and multi-processed (domain decomposition) (continued) Process 2, Time=1.0 s No decompose, Time=1.0 s In detail, there are many differences between singleprocessed result and multiprocessed result at Time=1.0 s. Such a discrepancy takes place as the calculation time passes. So far, no investigation to explain such discrepancies has been done. Process 1, Time=1.0 s Process 0, Time=1.0 s 21

22 CFD Applications Hydrological applications of CFD Example 1: Dam of high concentration of heavy metal (mercury) in the bottom and being covered by oil layer is going to break. This case is handling multi phases, surface tensions and contact angle to the walls (in terms of wettability). Extension: Flow of multi-phase, immersible fluids through a porous media, e.g. penetration of water containing heavy metals into the soil (multi-phase infiltration) 22

23 Example 1: Heavy metal outflow air oil 0.10 m water m mercury Time=0 s If the fraction ratio is 1 (100%), it is shown by red colour. air m oil water mercury 23

24 Example 1: Heavy metal outflow (continued) air oil water Despite the bottom layer of heavy metal is dammed by the remaining barrier, a small amount of the heavy metal is leaked being accompanied by the outflow of the upper layer of water. (Time=0.5 s) mercury 24

25 CFD Applications Hydrological applications of CFD Example 2: Mesh generation and conversion for complicated geometries, e.g. natural terrains. Dynamic mesh (displacing river across the canyon), Monitoring the changing wind path (the compressible flow (air) interacting with both the fixed wall (terrain) and incompressible flow (water in the river)) due to the displacing river. 25

26 Example 2: Mesh generation and conversion The geometry of the terrain is given as STL (stereolithography) file format and the size of this case is 3.0km x 3.0km x 218m. This will be bottom wall (boundary) having partially dynamic (displacing) cells of the computational domain

27 Example 2: Mesh generation and conversion (continued) The upper half computational domain has a form of box with homogeneous meshes in the upper region and grading meshes (for higher resolution) in the lower region. This is due to that complicated flow behaviours take place close to the terrain. 27

28 Example 2: Mesh generation and conversion (continued) homogeneous grading refined refined The figure on the left side shows a schematic cross-section in an arbitrary YZ-plane, concerning internal meshes (of computational domain). The domain consists of two parts: the upper half domain (a box form) which has homogeneous meshes (in 3D, regular hexahedron) in the upper part and grading meshes (in 3D, cuboid) in the lower part; the lower half domain which has the meshes consistent with the upper half domain in the centre and the refined meshes along the terrain. refined 28

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