New equations and methods for solving the size effects in the comparison of 2D Finite Element Analysis


The work “New equations and methods for solving the size effects in the comparison of 2D Finite Element Analysis” was presented in the 10th European Association of Vertebrate Palaeontologists Meeting (Teruel, Espanya). The work from the (Laboratori per la Innovació Tecnològica de les estructures i els Materials) LITEM of the Universitta Politècnica de Catalunya (UPC) and the Institut Català de Paleontologia (IPC) is signed by Jordi Marcé-Nogué, Daniel DeMiguel, Josep Fortuny, Soledad de Esteban-Trivigno and Lluís Gil

Some of the FE models described in the literature assume the hypothesis of being 2D (Rayfield, 2004, 2005; Pierce et al., 2008; Fletcher et al., 2010). Although a 2D model is not entirely reflective of the morphology of the vertebrate bone structures, it can be used as a first approximation to study its behaviour. This is due to the fact that it allows us to reduce the computational analysis time and the reconstruction process, design a strategy to deal with subsequent 3D and more detailed models (Rayfield, 2004) and reducing time in the computational analysis and in all the geometrical processes of reconstruction. Up to date, several studies have focused on comparing models of different species (Dumont et al., 2005; Macho et al., 2005; McHenry et al., 2006; Wroe et al., 2007) and the interest in the comparative analysis is increasing with the common usage of the FEA in biomechanics. The 2D procedure is specially suitable for comparing models of different species when the number of specimens is large (Pierce et al., 2008; Fletcher et al., 2010; Fortuny et al., 2011) and the duty of creating and analysing the models could be highly reduced with it. The main interest of FEA comparative analysis is to model the shape of specimens in order to infer functional morphology and relating it to different adaptations (e.g. diet, swimming, etc.). To compare shapes is needed to scale specimens. Although some papers discussed the effect of the size and shape in three-dimensional models (see (Dumont et al., 2009) for a discussion), there is no any paper focused on these effects in two dimensions. For this reason, we here present and discuss a new procedure to reduce the effect of the size in 2D models.

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