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Research Progress for Three-Dimensional Reconstruction of Nanofibrous Membranes from Two-Dimensional Scanning Electron Microscope Images
Published in Francisco Torrens, A. K. Haghi, Tanmoy Chakraborty, Chemical Nanoscience and Nanotechnology, 2019
Bentolhoda Hadavi Moghadam, Shohreh Kasaei, A. K. Haghi
For obtaining a 3D point cloud, we need to compute the 3D position associated with each match. To this end, the Delaunay triangulation is an excellent way that is computed using Computational Geometry Algorithms Library (CGAL). It provides our data Points as grouped into sets of points that belong to the same global surface and evaluates the projection of each triangle of the Delaunay triangulation in the chosen views and computes the mean of the color variance of the pixels in this triangle and obtain the 3D position of the feature points to modify a generic model using a geometrical deformation (Fig. 6.4).35
A flexible and easy-to-use open-source tool for designing functionally graded 3D porous structures
Published in Virtual and Physical Prototyping, 2022
Fernando Perez-Boerema, Mojtaba Barzegari, Liesbet Geris
ASLI generates functionally graded scaffold designs following the workflow shown in Figure 2. The process starts by loading the user-provided inputs. Details concerning the user inputs are discussed in Section 2.2. Once the input files are loaded, the preprocessing takes place which, depending on the provided inputs, can include the filtering of data and the construction of linear Radial Basis Function (RBF) interpolation models. Specifics regarding the filtering are found in Section 2.1.1, while the interested reader is referred to Buhmann (2004) for detailed background information on RBF interpolation. The preprocessing is followed by the discretisation step, i.e. the step where the object with its infill is converted into a surface triangulation or volume mesh. The discretisation is performed using the Mmg library (Dapogny et al. 2020) or the Computational Geometry Algorithms Library (CGAL) (CGAL Project 2020). As a result, the user can choose between two workflows in ASLI, the Mmg workflow and the CGAL workflow. The discretised surface is automatically saved as an STL or MESH file, depending on whether it is a surface triangulation or volume mesh.
Computational modal analysis of a composite pelvic bone: convergence and validation studies
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2019
The finite element model was prepared with the aid of the Fenics library (Fenics 1.6 Logg et al. 2012). A computational tetrahedral mesh was created within the CGAL library (CGAL 3 D Mesher, The CGAL Project 2015). As input data, a binary mask composed of the cortical and trabecular region was used. The influence of the mesh resolution on the weight of the bone and its modal properties was investigated through parametric variation of the element length for every bone region. The size of the cortical and trabecular mesh elements is in the range of 1 to 7 mm according to the shortest and longest distances between outer and inner bone cortical surfaces that are 1.5 and 7.5 mm (Figure 3). The ranges of degrees of freedom (DOFs) for every bone region are: 20–500 k in cortical part, 10–500 k in trabecular region. The displacement u was approximated using a continuous Lagrange basis of the first order.
CityGML goes mobile: application of large 3D CityGML models on smartphones
Published in International Journal of Digital Earth, 2019
Christoph Blut, Timothy Blut, Jörg Blankenbach
Polygon triangulation is not a new problem. Consequently, a wealth of libraries with corresponding methods for polygon triangulation exists. These are typically written in C++ such as cgal. Only few such as JTS Topology Suite (JTS), Poly2Tri, jDelaunay or delaunay-triangulator are available in Java. We evaluated these and found that none consider all special cases that can occur in CityGML data. For instance, holes might not be considered or holes touching the outline of the polygon or another hole. Therefore, we used an existing in-house triangulation library that is implemented according to Eberly’s (2002) Ear-clipping algorithm and specifically covers possible special cases. Since the Ear-clipping method is an algorithm for polygons in 2D space, the 3D CityGML polygons must be transformed into the second dimension before applying the algorithm.