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Adaptive Mesh Refinement and Large Problem Solvers
Published in O.P. Gupta, Finite and Boundary Element Methods in Engineering, 2022
Triangulation refers to drawing non-intersecting triangles through a set of points located on a plane surface. Delaunay triangulation [4] is a popular technique and the triangles formed by using this technique possess a special characteristic, namely the circle circumscribing any triangle does not enclose a fourth point. The triangles so formed are well shaped and are suitable for finite element analysis. Surface triangulation has been used to generate a surface mesh for such complex components as jet aircraft etc [5]. The first step in the procedure is to draw what is known as Voronoi polygons associated with each point (node) (i.e., Voronoi diagram(1)). These polygons are shown by dotted lines in Fig. 13.4. Each polygon encloses only one node within it.
Exploring the capabilities of portable device photogrammetry for 3D surface roughness evaluation
Published in International Journal of Mining, Reclamation and Environment, 2023
Kunze Li, Hamed Lamei Ramandi, Chengguo Zhang, Sarp Saydam, Joung Oh, Serkan Saydam
The initial assessment of the point cloud data indicated that the TLS’s results failed to meet expectations in this study because the TLS produced a point cloud that was an order of magnitude less dense than the other two methods and contained many noise points. Its sparse point clouds could not be used for high-accuracy mesh generation and quantification of surface roughness. Low-density point clouds could not retain sufficient details to produce surface triangulation. This is because the TLS used in this experiment was designed for relatively large-scale industrial applications and could not provide satisfactory results for lab-scale specimens. Portable photogrammetric devices, such as iPhone 12 Pro Max used in this study, and structured light 3D scanners provide more data points and details at this scale, as presented in Table 2.
Development of historic building information modelling: a systematic literature review
Published in Building Research & Information, 2022
Sumeyye Sena Bastem, Asli Cekmis
In HBIM, instead of a pure geometric model, the aim is to create an intelligent model that considers the originality of building elements containing semantic information and that can establish structural and functional relationships (Di Luggo & Scandurra, 2016; Stober et al., 2018). In the HBIM process, after data acquisition, a decision is made whether segmentation will be performed for point clouds. If the desired product is a mass model, segmentation is not performed. However, segmentation is performed if it is desired that the building elements should act and be shown independently in the model. In segmentation, there are two methods (Figure 7). One of these methods is boundaries extraction which converted into spline objects by removing edge boundaries. The other method is point clouds are converted into surfaces as Mesh and NURBS. Mesh model defines objects with polygons and creates polyhedra objects. Because the objects are created using meshes, they are not suitable for modelling surfaces with complex geometric shapes (Chiabrando et al., 2016; Donato et al., 2017; Oreni, Brumana, Banfi, et al., 2014). NURBS models are used for the modelling of irregular geometric shapes (Chiabrando et al., 2016; Diara & Rinaudo, 2020a; Fregonese et al., 2017; Oreni, Brumana, Torre, et al., 2014). In the implementation study performed in (Chiabrando et al., 2016), surface triangulation was used to create a surface closest to the accurate geometric surface; however, this method was deemed unsuitable for surfaces with a complex geometry such as vaults. Consequently, the most suitable method for modelling curvilinear surfaces in historic buildings was found to be the NURBS model, which is used for modelling irregular surfaces (Banfi, Chow, et al., 2018, 2017; Oreni, Brumana, Banfi, et al., 2014; Paris & Wahbeh, 2016).