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To obtain a body-fitted and isotropic particle distribution, an initial configuration (see [Sampling of Geometries](@ref sampling_of_geometries)) is first generated. This configuration is then packed using a [`ParticlePackingSystem`](@ref).
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The preprocessing pipeline consists of the following steps:
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- Load geometry: Fig. 1, [`load_geometry`](@ref).
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- Compute the signed distance field (SDF): Fig. 2, [`SignedDistanceField`](@ref).
- Initial sampling of the interior particles with inside-outside segmentation: Fig. 4, [`ComplexShape`](@ref).
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- Pack the initial configuration of interior and boundary particles (Fig. 5): Fig. 6, [`ParticlePackingSystem`](@ref).
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The input data can either be a 3D triangulated surface mesh represented in STL format or a 2D polygonal traversal of the geometry (see [`load_geometry`](@ref)).
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The second step involves generating the SDF (see [`SignedDistanceField`](@ref)), which is necessary for the final packing step as it requires a surface detection.
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The SDF is illustrated in Fig. 2, where the distances to the surface of the geometry are visualized as a color map.
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As shown, the SDF is computed only within a narrow band around the geometry’s surface, enabling a face-based neighborhood search (NHS) to be used exclusively during this step.
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In the third step, the initial configuration of the boundary particles is generated (orange particles in Fig. 3).
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Boundary particles are created by copying the positions of SDF points located outside the geometry but within a predefined boundary thickness (see [`sample_boundary`](@ref)).
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In the fourth step, the initial configuration of the interior particles (green particles in Fig. 4) is generated using the hierarchical winding number approach (see [Hierarchical Winding](@ref hierarchical_winding)).
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After steps **1** through **4**, the initial configuration of both interior and boundary particles is obtained, as illustrated in Fig. 5.
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The interface of the geometry surface is not well resolved with the initial particle configuration.
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Thus, in the final step, a packing algorithm by Zhu et al. [Zhu2021](@cite) is applied utilizing the SDF to simultaneously optimize the positions of both interior and boundary particles,
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yielding an isotropic distribution while accurately preserving the geometry surface, as illustrated in Fig. 6.
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