A Distributed Computing Workflow for Modelling Environmental Flows in Complex Terrain - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2015

A Distributed Computing Workflow for Modelling Environmental Flows in Complex Terrain

Résumé

Numerical modelling of extreme environmental flows such as flash floods, avalanches and mudflows can be used to understand fundamental processes, predict outcomes and assess the loss potential of future events. These extreme flows can produce complicated and dynamic free surfaces as a result of interactions with the terrain and built environment. In order to resolve these features that may affect flows, high resolution, accurate terrain models are required. However, terrain models can be difficult and costly to acquire, and often lack detail of important flow steering structures such as bridges or debris. To overcome these issues we have developed a photogrammetry workflow for reconstructing high spatial resolution three dimensional terrain models. The workflow utilises parallel and distributed computing to provide inexpensive terrain models that can then be used in numerical simulations of environmental flows. A section of Quebrada San Lazaro within the city of Arequipa, Peru is used as a case study to demonstrate the construction and usage of the terrain models and applicability of the workflow for a flash flood scenario.
Fichier principal
Vignette du fichier
978-3-319-15994-2_32_Chapter.pdf (4 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01328566 , version 1 (08-06-2016)

Licence

Paternité

Identifiants

Citer

Stuart R. Mead, Mahesh Prakash, Christina Magill, Matt Bolger, Jean-Claude Thouret. A Distributed Computing Workflow for Modelling Environmental Flows in Complex Terrain. 11th International Symposium on Environmental Software Systems (ISESS), Mar 2015, Melbourne, Australia. pp.321-332, ⟨10.1007/978-3-319-15994-2_32⟩. ⟨hal-01328566⟩
74 Consultations
82 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More