2011
DOI: 10.1017/s0962492911000043
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Tsunami modelling with adaptively refined finite volume methods

Abstract: Numerical modelling of transoceanic tsunami propagation, together with the detailed modelling of inundation of small-scale coastal regions, poses a number of algorithmic challenges. The depth-averaged shallow water equations can be used to reduce this to a time-dependent problem in two space dimensions, but even so it is crucial to use adaptive mesh refinement in order to efficiently handle the vast differences in spatial scales. This must be done in a ‘wellbalanced’ manner that accurately captures very small … Show more

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Cited by 256 publications
(194 citation statements)
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“…D-Claw is an extension of the CLAWPACK software package [34], an open-source project for solving general hyperbolic problems (e.g. [17,[35][36][37]). …”
Section: Numerical Methods and D-claw Softwarementioning
confidence: 99%
See 1 more Smart Citation
“…D-Claw is an extension of the CLAWPACK software package [34], an open-source project for solving general hyperbolic problems (e.g. [17,[35][36][37]). …”
Section: Numerical Methods and D-claw Softwarementioning
confidence: 99%
“…[52,53]), and later specialized for depth-averaged flows across topography, such as tsunamis and overland floods (e.g. [35][36][37]). With patch-based, blockstructured AMR, the domain is discretized on numerous rectangular grids, each associated with a given level, l = 1, .…”
Section: (B) Adaptive Mesh Refinementmentioning
confidence: 99%
“…eg. [26]). Similarly, the bottom topography is measured with sonar equipment and this data collection is prone to uncertainty.…”
Section: Uncertainty Quantification (Uq)mentioning
confidence: 99%
“…TUNAMI by Goto et al (1997), MOST by Titov and Synolakis (1995) and COMCOT by Wang and Liu (2006). In recent years, finite volume Godunov-type schemes have also been implemented to solve the SWEs for tsunami modeling and have gradually gained popularity (Popinet, 2011;Leveque et al, 2011). These models boast of their automatic shock-capturing capability, superior conservation property and flexibility for implementation on different types of computational grids for better boundary fitting.…”
Section: Introductionmentioning
confidence: 99%