Flood propagation in rivers is strongly influenced by the presence of bridges and other hydraulic structures. Among the available approaches for including these elements in numerical models, the adoption of Internal Boundary Conditions (IBC), given its ability to capture backwater, is suitable for field-scale analyses for flood hazard assessment. In this paper, the implementation of internal boundary conditions in the two-dimensional shallow water code named “PARFLOOD” is presented. The application to experimental and real test cases shows that the proposed IBC model can handle both low and high flow conditions for bridges, while being flexible for other types of structures (e.g. flow-through dams). Moreover, the model is computationally efficient (physical/computational time ratio around 20–30 for domains with ~106 cells), thanks to the code parallelization on GPU.

Internal boundary conditions for a GPU-accelerated 2D shallow water model: Implementation and applications / Dazzi, S.; Vacondio, R.; Mignosa, P.. - In: ADVANCES IN WATER RESOURCES. - ISSN 0309-1708. - 137:(2020), p. 103525. [10.1016/j.advwatres.2020.103525]

Internal boundary conditions for a GPU-accelerated 2D shallow water model: Implementation and applications

Dazzi S.
;
Vacondio R.;Mignosa P.
2020-01-01

Abstract

Flood propagation in rivers is strongly influenced by the presence of bridges and other hydraulic structures. Among the available approaches for including these elements in numerical models, the adoption of Internal Boundary Conditions (IBC), given its ability to capture backwater, is suitable for field-scale analyses for flood hazard assessment. In this paper, the implementation of internal boundary conditions in the two-dimensional shallow water code named “PARFLOOD” is presented. The application to experimental and real test cases shows that the proposed IBC model can handle both low and high flow conditions for bridges, while being flexible for other types of structures (e.g. flow-through dams). Moreover, the model is computationally efficient (physical/computational time ratio around 20–30 for domains with ~106 cells), thanks to the code parallelization on GPU.
2020
Internal boundary conditions for a GPU-accelerated 2D shallow water model: Implementation and applications / Dazzi, S.; Vacondio, R.; Mignosa, P.. - In: ADVANCES IN WATER RESOURCES. - ISSN 0309-1708. - 137:(2020), p. 103525. [10.1016/j.advwatres.2020.103525]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2878690
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