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Salete Casino, Eduardo

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Salete Casino
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Autor: Vargas Ureña, Antonio Manuel × Tiene archivos: true ×

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Mostrando 1 - 2 de 2
  • Miniatura
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    Generalized finite difference method applied to solve seismic wave propagation problems. Examples of 3D simulations
    (Wiley, 2023) Flores, Jesús; Salete Casino, Eduardo; Benito, Juan José; Vargas Ureña, Antonio Manuel; Conde, Eduardo R.; https://orcid.org/0000-0001-5201-4277
    The simulation of seismic wave propagation generally requires dealing with complex tridimensional geometries that are irregular in shape 11 and have non-uniform properties, features that make interesting the application of the generalized finite difference method in this field. 12 This work continues the extensive developments by the research team focused on the simulation of seismic wave propagation in two-13 dimensional domains. In this new contribution, the general formulation and the treatment of free surface boundary conditions are 14 extended for the three-dimensional case and the results obtained from different examples are analyzed.
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    Publicación
    Application of finite element method to create a digital elevation model
    (MDPI, 2023-03-21) Conde López, Eduardo Roberto; Salete Casino, Eduardo; Flores Escribano, Jesús; Vargas Ureña, Antonio Manuel
    The generation of a topographical surface or digital elevation model for a given set of points in space is a known problem in civil engineering and topography. In this article, we propose a simple and efficient way to obtain the terrain surface by using a structural shell finite element model, giving advice on how to implement it. The proposed methodology does not need a large number of points to define the terrain, so it is especially suitable to be used with data provided by manual topographical tools. Several examples are developed to demonstrate the easiness and accuracy of the methodology. The digital terrain model of a real landscape is modeled by using different numbers of points (from 49 to 400) using a regular mesh or a randomly generated cloud of points. The results are compared, showing how the proposed methodology creates a sufficiently accurate model, even with a low number of points (compared with the thousands of points handled in a LiDAR representation). A real case application is also shown. As an appendix, the sample code to generate the examples is provided.