A. Panizzo

Application of wavelet transform analysis to landslide generated waves

The aim of this paper is to illustrate the results of a preliminary study on aerial landslide-generated waves, which has been mainly intended to establish a method for analyzing water surface records. Some simple physical experiments, reproducing the Scott Russells wave generator, were carried out in a small two-dimensional wave flume; the Wavelet Transform (WT) is applied to analyze wave measurements and it is shown that useful information can be obtained by means of this technique. The celerity of impulsively generated waves, reflection by an overflow structure and seiching phenomena of the flume are studied. A discussion of the results along with some remarks about ongoing research is also given.

SPH modelling of water waves generated by submarine landslides

The present work introduces a numerical representation of the rheological non Newtonian Bingham model by means of the Smoothed Particle Hydrodynamics (SPH) approach. The model is first re-written using the SPH formalism. Then, it is tested using an annular viscometer test case. Finally, the generation of tsunami waves due to underwater landslide is faced, considering the experimental work of Rzadkiewicz et al. (1997). The implemented rheological SPH model is used to simulate the landslide deformation, and its interaction with water, thus simulating also the generation and propagation of surface tsunami waves.

Smoothed Particle Hydrodynamics for Water Waves

Smoothed Particle Hydrodynamics provides a numerical method particularly well suited to examine the breaking of water waves due to the ability of the method to cope with splash. The method is a meshfree Lagrangian method that allows the computational domain to deform with the flowing liquid. Here we discuss the appropriate kernels used in the interpolation and the time stepping alogrithms. Applications to water waves are shown. Copyright ?? 2007 by ASME.

Analysis of Wave Transmission Behind Low-Crested Structures Using Neural Networks

This paper aims to improve the prediction of wave transmission behind low-crested rubble mound breakwaters by employing artificial neural networks. Data from physical experiments on rubble mound low-crested structures have been gathered within the European research program DELOS and this dataset has been used. The results compared to classical formulations in the prediction of the wave transmission coefficient as a function of both hydraulic and structural parameters.