Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/118794
Título: | Graph-grammar based algorithm for asteroid tsunami simulations | Autores/as: | Maczuga, Paweł Oliver Serra, Albert Paszyńska, Anna Valseth, Eirik Paszyński, Maciej |
Clasificación UNESCO: | 1208 Probabilidad | Palabras clave: | Finite Element Method Graph Grammar Longest-Edge Refinement Algorithm Non-Linear Wave Equation Scientific Computing In Julia |
Fecha de publicación: | 2022 | Publicación seriada: | Journal of Computational Science | Resumen: | Around 1 million kilometers from Earth, five times the distance from Earth to the Moon, a large asteroid passed without harm to the Earth. Theoretically, however, the event of the asteroid falling into Earth, causing the tsunami, is possible since there are over 27,000 near-Earth asteroids [1], and the Earth's surface is covered in 71 percent by water. We introduce a novel graph-grammar-based framework for asteroid tsunami simulations. Our framework adaptively generates the computational mesh of the Earth model. It is built from triangular elements representing the seashore and the seabed. The computational mesh is represented as a graph, with graph vertices representing the computational mesh element's interiors and edges. Mesh refinements are often performed by the longest-edge refinement algorithm. We have expressed this algorithm by only two graph-grammar productions. The resulting graph represents the terrain approximating the topography with a prescribed accuracy. We generalize the graph-grammar mesh refinement algorithm to work on the entire Earth model, allowing the generation of the terrain topography, including the seabed. Having the seashore and the seabed represented by a graph, we introduce the finite element method simulations of the tsunami wave propagation. We illustrate the framework with simulations of the disastrous asteroid falling into the Baltic sea. | URI: | http://hdl.handle.net/10553/118794 | ISSN: | 1877-7503 | DOI: | 10.1016/j.jocs.2022.101856 | Fuente: | Journal of Computational Science[ISSN 1877-7503],v. 64, (Octubre 2022) |
Colección: | Artículos |
Citas SCOPUSTM
2
actualizado el 24-nov-2024
Citas de WEB OF SCIENCETM
Citations
2
actualizado el 24-nov-2024
Visitas
55
actualizado el 18-may-2024
Google ScholarTM
Verifica
Altmetric
Comparte
Exporta metadatos
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.