Dede Tarwidi, Sri Redjeki Pudjaprasetya, Didit Adytia
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The effects of dispersion and non-linearity on the simulation of landslide-generated waves using the reduced two-layer non-hydrostatic model
This paper revisits the previously developed NH-2LR (reduced two-layer non-hydrostatic) model. The governing equations and numerical schemes are written in terms of normalized variables, with two dimensionless parameters representing dispersion and non-linearity. By utilizing analytical solutions and laboratory experiments, this study aims to validate the numerical NH-2LR model and investigate the effects of dispersion and non-linearity on the resulting waves. The first validation employs the analytical solution of the linear and fully dispersive model of a landslide moving with constant velocity on a flat bottom. The second validation involves a landslide hump sliding over a constant beach slope. A closer look at the run-up height reveals that this case is non-dispersive. Furthermore, we found that the dispersion effect was evident from the beginning of the wave formation process. Finally, we compare our numerical results to experiments on submarine landslides on sloping beaches. We found that dispersion is essential in the early generation and propagation of waves in off-shore regions. Moreover, non-linearity significantly influences the maximum run-up of landslide-generated waves.
期刊介绍:
Computational Geosciences publishes high quality papers on mathematical modeling, simulation, numerical analysis, and other computational aspects of the geosciences. In particular the journal is focused on advanced numerical methods for the simulation of subsurface flow and transport, and associated aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing.
Papers treating similar topics but with applications to other fields in the geosciences, such as geomechanics, geophysics, oceanography, or meteorology, will also be considered.
The journal provides a platform for interaction and multidisciplinary collaboration among diverse scientific groups, from both academia and industry, which share an interest in developing mathematical models and efficient algorithms for solving them, such as mathematicians, engineers, chemists, physicists, and geoscientists.