µCT-images reconstruction The µCT images data were reconstructed with Simpleware. A median filter was applied to the raw images to reduce the noise level and then the images were segmented to extract the scaffold region. The mask created in the segmentation process was smoothed using the recursive Gaussian filter and a final binarisation filter was applied to the mask in order to eliminate the connection between the background images and the segmented mask. Then, a surface triangular mesh was generated to represent the µCT-based scaffold geometry. The surface mesh was exported in STL format. This reconstruction process is explained with more details in section 3.2.1.2. Fluid volume mesh generation The STL mesh of the trimmed scaffold was imported into ICEM Ansys and located inside a CAD-based rectangular channel following the specifications of the experimental microfluidic chamber (see Figure 43). The fluid domain was meshed with tetrahedral elements using the robust octree algorithm (see section 3.2.1.5). Mesh sensitivity analysis was carried out by calculating the impact of the maximum length of the edge of the triangular faces of the tetrahedral elements inside the scaffold region and the maximum length for the elements outside it on velocity values (see results in section 4.3.1.2.1). As a result, around 4 million elements represented the fluid domain with maximum element length of 20 µm inside the scaffold and maximum length of 0.1 mm outside it. Despite of the fact that the elements outside the scaffold can be up to five times bigger than the ones inside it, the meshing algorithm applied provides a smooth transition from the elements far from the scaffold to the elements close to it. Figure Geometrical boundary conditions of the CFD model.
µCT-images reconstruction The µCT images data were reconstructed with Simpleware. A median filter was applied to the raw images to reduce the noise level and then the images were segmented to extract the scaffold region. The mask created in the segmentation process was smoothed using the recursive Gaussian filter and a final binarisation filter was applied to the mask in order to eliminate the connection between the background images and the segmented mask. Then, a surface triangular mesh was generated to represent the µCT-based scaffold geometry. The surface mesh was exported in STL format. This reconstruction process is explained with more details in section 3.2.1.2. Fluid volume mesh generation The STL mesh of the trimmed scaffold was imported into ICEM Ansys and located inside a CAD-based rectangular channel following the specifications of the experimental microfluidic chamber (see Figure 43). The fluid domain was meshed with tetrahedral elements using the robust octree algorithm (see section 3.2.1.5). Mesh sensitivity analysis was carried out by calculating the impact of the maximum length of the edge of the triangular faces of the tetrahedral elements inside the scaffold region and the maximum length for the elements outside it on velocity values (see results in section 4.3.1.2.1). As a result, around 4 million elements represented the fluid domain with maximum element length of 20 µm inside the scaffold and maximum length of 0.1 mm outside it. Despite of the fact that the elements outside the scaffold can be up to five times bigger than the ones inside it, the meshing algorithm applied provides a smooth transition from the elements far from the scaffold to the elements close to it. Figure Geometrical boundary conditions of the CFD model.
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