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Meshing of porous foam structures on the micro-scale

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Abstract

A semi-automatic block-structured grid generation technique for hexahedral meshing of porous open cell Kelvin foam structures for investigation of the pore scale fluid flow is presented. The performance of the algorithm is compared with a tetrahedral full automatic Delaunay meshing technique. In the first part of the paper the meshing strategies are explained. In the second part grid generation times, simulation times and the mesh quality are evaluated. For this Computational Fluid Dynamics (CFD) simulations for both a diffusion-dominated case (Re = 0.129) and a convection-dominated case (Re = 129) are carried out and analysed on four different cell resolutions of each mesh type. For the quality evaluation three different a posteriori error estimates are studied for the two mesh types on the different mesh sizes. The results are: the block-structured grid generation technique is about 10–20 times faster than the tetrahedral full automatic technique. While the mean field error estimates are comparable for both meshes, the maximum field error estimates for the block-structured meshes are only half of those for the tetrahedral meshes. Reaching simulation results of the same quality the hexahedral mesh needs about 20–40% less iterations with comparable mesh sizes. The time per iteration for the hexahedral meshes are up to 94% smaller than for the tetrahedral meshes. This makes the semi-automatic block-structured grid generation technique especially suitable for parameter studies and for the investigation of micro-scale flows in foam structures consisting of large quantities of Kelvin cells.

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Notes

  1. Although the Weaire–Phelan foam, described by Weaire and Phelan [26], has a lower specific surface energy there is still a debate about its occurrence in real foams. Whereas the Kelvin foam can be observed for small bubbles equal sized and spaced bubbles nobody observed the Weaire–Phelan foam in nature yet as mentioned by Weaire [25]. If an equal distribution of cell pressures and cell volumes is assumed, it is conjectured in the scientific community, see for example Kusner and Sullivan [17], that the Kelvin foam is the best model.

  2. In the [001] direction the structure has already a repeatable geometry so that cyclic boundary condition could be used. However, for the study presented in this paper the structure is further copied and translated to form a small foam structure of 2 × 2 × 2 Kelvin cells, which allows the use of cyclic instead of symmetry boundary conditions in the two remaining directions.

  3. Kelvin foams consisting of more Kelvin cells can easily be created by just copying and translating this structure along the [100], [010] and [001] directions.

  4. Aspect ratio is the ratio of the longest cell edge to the shortest cell edge.

  5. Non-orthogonality is the angle between the line connecting two cell centres and the face normal of the connecting cell face.

  6. Skewness measures how much the line between two cell centres misses the face centre of the connecting cell face. This distance is normalised by the approximate distance from the face centre to the edge of the face in the direction of the skewness.

  7. The directions are given in Fig. 2.

  8. For this computing timing the wall clock time of first 100 iterations was measured and than normalised by the number of cells and iterations.

  9. Also called residual of the momentum predictor.

Abbreviations

a :

Coefficient of the momentum matrix

l :

Edge length

t s :

Thickness of the struts

\(d_{\text{pore}}=\sqrt{\frac{6}{\Uppi}\sqrt{3}}(l-t_{s})\) :

Pore diameter, as defined by Xu et al. [29]

\(d_{\text{cell}}=2\sqrt{2}l\) :

Cell diameter, as defined by Mills [20]

h :

Mesh spacing

\(\Upphi\) :

Porosity

S V :

Surface area per unit volume solid

Re pore :

Reynolds number based on pore diameter as char. length

u :

Physical velocity

\({\bf u}_{\text{mean}}=\frac{1}{V}\int{\bf u}{\text{d}}V=\frac{Q}{A}\) :

Volume averaged mean velocity through the porous media (flow rate divided by cross-sectional area)

\(u^{+}=\sqrt{\nu\left(\frac{{\text{d}}u}{{\text{d}}y}\right)_{y=0}}\) :

Friction velocity

\(y^{+}=\frac{u^{+}y}{\nu}\) :

Dimensionless wall distance

y :

Distance to the nearest wall

ν :

Kinematic viscosity

ρ :

Density

ψ :

Flow limiter

r :

Local ratio of upstream to downstream gradient of u i

α :

Under-relaxation factor

V :

Volume

A :

Face area of computing cell

[]cell :

Cell of the porous media

[]pore :

Pore of the porous media

[] P :

Index denoting computational cell of interest

[] N :

Index denoting neighbour computational cell to the one of interest

RiEE:

Error estimation based on Richardson’s extrapolation

REE:

Residual error estimate

MEE:

Momentum error estimate

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Acknowledgments

This work presents a part of the results obtained under contract number SFB 799 C1, sponsored by the Deutsche Forschungsgemeinschaft (DFG), Germany.

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Correspondence to J. Klostermann.

Appendix

Appendix

1.1 Residual definition

The residual res(u) and res(p) are deduced from the momentum predictor and the pressure corrector of the SIMPLE algorithm. Let’s recall the discretised form of the momentum equation:

$$ a_{P}{\bf U}_{P} =H\left({\bf U}\right)-\frac{1}{\rho}\nabla p $$
(9)

with H(U) =  −∑ N a N U N representing the matrix coefficients (a N ) of the neighbouring cells multiplied by their velocity (U N ), the matrix coefficient a p and the velocity U P at the cell of cell of interest indexed by P. As mentioned before, the pressure gradient is defined as \(\nabla p=\nabla P+\frac{\triangle\tilde{p}}{L}\hat{e}\) for our periodic problem. The cell values for the velocity residualFootnote 9 is defined by:

$$ {\text{res}}_{P}(U_{x,y,z}) =\left|\left({\bf U}_{P}\cdot\nabla\right){\bf U}_{p}+\frac{1}{\rho}\nabla p+\nabla\cdot\left(\nu\nabla{\bf U}_{P}\right)\right|_{x,y,z} $$

The \(\left|\,\right|_{xyz}\) operator denotes the componentwise magnitude of the vector. Dividing (9) by a P , taking the divergence and with the continuity equation (Eq. 1) the pressure correction is obtained:

$$ \nabla\cdot{\bf U}_{P} = \nabla\cdot\left(\frac{H\left({\bf U}\right)}{a_{P}}\right)-\nabla\cdot\left(\frac{1}{a_{P}}\frac{1}{\rho}\nabla p\right)=0 $$
(10)

which gives a corrected pressure field which is in accordance to the predicted velocity field. The cell values for the pressure residual are calculated from this pressure corrector by:

$$ {\text{res}}_{P}(p) = \left|\nabla\cdot\left(\frac{H\left({\bf U}\right)}{a_{P}}\right)-\nabla\cdot\left(\frac{1}{a_{P}}\frac{1}{\rho}\nabla p\right)\right| $$
(11)

All the cell residuals are summed up over the whole domain and normalised to

$$ res(U_{x,y,z}) = \frac{\sum_{P}\left({\text{res}}_{P}(U_{x,y,z})\right)}{F_{\text{norm}}(U_{x,y,z})} $$
(12)

and

$$ res(p) = \frac{\sum_{P}\left({\text{res}}_{P}(p)\right)}{F_{\text{norm}}(p)} $$
(13)

with the normalisation factors F norm(U x,y,z ) for the velocity residuals res P (U x,y,z )

$$ \begin{aligned} F_{\text{norm}}(U_{x,y,z}) & = \left|\sum_{P}\left(a_{P}{\bf U}_{\text{cell}}-a_{U,P}U_{\text{ref}}\right)\right|_{x,y,z} \\ & \quad + \left|\sum_{P}\left(H\left({\bf U}\right)-\frac{1}{\rho}\nabla p-a_{U,P}U_{\text{ref}}\right)\right|_{x,y,z}+10^{-20}\frac{m}{s} \end{aligned} $$
(14)

and the normalisation factors F norm(p) for res(p)

$$ \begin{aligned} F_{\text{norm}}(p) &= \left|\sum_{P}\left(a_{p,P}p_{P}-a_{p,P}p_{\text{ref}}\right)\right| \\ & \quad + \left|\sum_{P}\left(\nabla\cdot\left(\frac{H\left({\bf U}\right)}{a_{U,P}}\right)-a_{p,P}p_{\text{ref}}\right)\right|+10^{-20}\frac{m^{2}}{s^{2}}. \end{aligned} $$
(15)

The reference values are defined by \(U_{\text{ref}}=\frac{\sum_{P}\left(U_{x,y,z}\right)}{N_{P}}\) and \(p_{\text{ref}}=\frac{\sum_{P}\left(p\right)}{N_{P}}. \) Note that a p,P in F norm(p) are the matrix coefficients of the pressure corrector (Eq. 10). The last terms on the RHS of (14) and (15) are introduced to prevent division by zero in (12) and (13).

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Klostermann, J., Schwarze, R. & Brücker, C. Meshing of porous foam structures on the micro-scale. Engineering with Computers 29, 95–110 (2013). https://doi.org/10.1007/s00366-011-0247-5

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