3D physical modeling of tsunamis generated by submerged landslides at a conical island. The role of initial acceleration

This paper presents a new set of 3D experiments aimed to gain insight on the role of the initial acceleration upon the generation process of tsunamis by submerged landslides that may occur at the flanks of conical islands. The experiments have been carried out in a large wave tank by varying the initial acceleration of the landslide model. A novel system, relying on the use of a computer controlled stepped motor, has been employed to control the motion of the landslide model. The experiments have been carried out in a parametric way by changing the initial acceleration of the landslide, aiming to reproduce different triggering mechanisms. Preliminary experimental findings confirmed the crucial role of the initial acceleration of the submerged landslide in generating tsunamis

Effects of floaters on the free surface profiles of river flows

The presence of floaters should be taken into account when dealing with hydraulic analyses, e.g. when boats are moored along the river banks or large wood is expected to be conveyed by the river flow during floods. Many approaches have been proposed so far in order to consider the effects of floaters upon the flow features. Usually, they rely on the numerical resolution of the governing equation for both the fluid and the solid phases. Hence, their computational cost can be inadequate at the early stage of hydraulic studies or when large scale analyses have to be performed. A simplified method to compute the value of the resistance coefficient able to reproduce the effects of floaters upon the flow levels is proposed herein. The method is intended to provide the hydraulic parameters to be used within standard hydraulic simulations for which the effects of floaters must be accounted for; this is obtained by means of a modified resistance coefficient

Modeling of low Mach number unsteady turbulent pipe flows

Under adiabatic conditions, and neglecting temperature variations due to entropy production, we present a set of Reynolds Averaged Navier-Stokes (RANS) equations for fluids of low compressibility, i.e., fluids in the liquid state. In the low Mach number limit, we specialize the RANS equations to the one-dimensional unsteady pipe flow, and we deduce the dimensionless number that plays a predominant role in the flow behavior. We reduce the system of equations to a linear damped wave equation, and use its analytical solution to investigate the propagation of large amplitude pressure waves in liquid-filled pipes (water hammer phenomenon). We test the model reliability by comparing the analytical solution of the proposed model against experimental data available in the literature

Decomposition of the mechanical stress tensor: from the compressible Navier–Stokes equation to a turbulent potential flow model

We frame the mechanical stress tensor decomposition in a general procedure which involves the Helmholtz-Hodge decomposition. We highlight the impact of the mechanical stress tensor decomposition on the Navier-Stokes equation, with emphasis on the dissipation function. For fluids with low compressibility, we draw some insights on the Reynolds Averaged Navier-Stokes equations, and on the Reynolds stress tensor decomposition. We derive a turbulent potential flow model, and investigate the transition from viscous potential flow to turbulent potential flow. Under low Mach number approximation, we apply the turbulent potential flow model to one-dimensional propagation of large amplitude pressure waves in liquid-filled pipe

Beach drainage system: a comprehensive review of a controversial soft-engineering method

The beach drainage can be included among the soft engineering methods aimed to counteract the shoreline retreat related to the sediment redistribution along the beach profile. The idea that the groundwater table plays a role in the mobilization of the sediment grains underlies the application of the beach drainage system (BDS) as a tool able to modify the natural dynamics of groundwater table at sandy beaches. Indeed, BDS consists of a series of alongshore buried drains aimed to lower the groundwater table. Due to the drainage, the thickening of the layer of dry sand makes the solid grains less prone to be mobilized by the action of the waves at the swash zone, where interaction phenomena between the percolating and the incoming water lens take place. This tool had a troubled history. Its first applications were encouraging. Since then, controversial performances of both experimental and prototype scale experiences have been observed around the world. This paper aims to present an up-to-date full review of the studies and experiments carried out so far, in order to provide the reader with a complete perspective on its strength and weakness as well as open challenges to be faced in the near future

Predicting outcome with Intranasal Esketamine treatment: A machine-learning, three-month study in Treatment-Resistant Depression (ESK-LEARNING)

Treatment-resistant depression (TRD) represents a severe clinical condition with high social and economic costs. Esketamine Nasal Spray (ESK-NS) has recently been approved for TRD by EMA and FDA, but data about predictors of response are still lacking. Thus, a tool that can predict the individual patients’ probability of response to ESK-NS is needed. This study investigates sociodemographic and clinical features predicting responses to ESK-NS in TRD patients using machine learning techniques. In a retrospective, multicentric, real-world study involving 149 TRD subjects, psychometric data (Montgomery-Asberg-Depression-Rating-Scale/MADRS, Brief-Psychiatric-Rating-Scale/BPRS, Hamilton-Anxiety-Rating-Scale/HAM-A, Hamilton-Depression-Rating-Scale/HAMD-17) were collected at baseline and at one month/T1 and three months/T2 post-treatment initiation. We trained three different random forest classifiers, able to predict responses to ESK-NS with accuracies of 68.53% at T1 and 66.26% at T2 and remission at T2 with 68.60% of accuracy. Features like severe anhedonia, anxious distress, mixed symptoms as well as bipolarity were found to positively predict response and remission. At the same time, benzodiazepine usage and depression severity were linked to delayed responses. Despite some limitations (i.e., retrospective study, lack of biomarkers, lack of a correct interrater-reliability across the different centers), these findings suggest the potential of machine learning in personalized intervention for TRD

Mapping and classification of ports and marinas for the definition of long-term development strategy

Mapping and classification of ports may be of great help to define effective development strategies based on the concept of “intelligent, green and integrated port”, within the frame of sustainable development. To this end, classification tools and knowledge of the initial situation are crucial points needed, just as an example, to boost the maritime and short-sea connectivity by promoting the creation of regional touristic port network, capable of implementing a smart, green, and integrated transport system. This work deals with the mapping and classification of ports and marinas. A possible methodology to define a priority matrix intervention rank is proposed and applied to all the harbors in the Puglia region, as a case study. The collected open data aim to describe several aspects: the services, the urban planning whereby the port is thought, the facilities and structures, the connection with multi-modal local transport. The mapping activity has been performed within the frame of the AI-SMART project funded by the European Regional Development Fund that aims to implement and develop a common port network in the Adriatic-Ionian area. The case study served to highlight the feasibility and applicability of the proposed method to a real case

Reduced wave time series for long-term morphodynamic applications

Shoreline models have usually been recognized by professionals as the most appropriate tool for reproducing the long-term morphodynamic evolution of the shoreline of sandy beaches. Despite their underlying simplifications, the simulation of shoreline evolution at large temporal and spatial scales may imply significant computational efforts. Hence, to reduce computational costs, many approaches aimed to optimize the size of the input wave datasets have been proposed so far. A simplified novel method to reduce long-term offshore wave series is proposed herein. The rationale of the approach is to build reduced series that induce the same morphodynamic effects in the long-term as the ones induced by the whole, and more computationally expensive, original series. The method is conceived to define offshore reduced time series with the same chronological order of the complete series and is able to represent the bi-modal features of the wave climate. In-depth hydrodynamic and morphodynamic parametric analyses have been performed and it has been demonstrated that the method is capable to get reliable reduced offshore wave time series for reproducing the long-term evolution of sandy beaches with decreased computational costs

A Sterescopic System to Measure Water Waves in Laboratories

A new system for estimating the synthetic parameters of sea states during physical investigations has been implemented. The technique proposed herein is based on stereographic analysis of digital images acquired with optical sensors. A series of ad hoc floating markers has been made and properly moored to the bottom of a large wave tank to estimate the synthetic parameters of generated waves. The implemented acquisition system and the proposed algorithm provide automatic recognition of all markers by a pair of optical sensors that synchronously captures their instantaneous location and tracks their movements over time. After transformation from the image to the real-world coordinates, water surface elevation time series have been obtained. Several experimental tests have been carried out to assess the feasibility and reliability of the proposed approach. The estimated wave synthetic parameters have been then compared with those obtained by employing standard resistive probes. The deviation were found to be equal to ~6% for the significant wave height and 1% for peak, mean, and significant wave periods

Tsunamis Generated by Submerged Landslides: Numerical Analysis of the Near-Field Wave Characteristics

ABSTRACT: The accurate modeling of the landslide?generated tsunami characteristics in the so-called near-field is crucial for many practical applications. In this paper, we present a new full-3-D numerical method for modeling tsunamis generated by rigid and impermeable landslides in OpenFOAM® based on the overset mesh technique. The approach has been successfully validated through the numerical reproduction of past experiments for landslide?generated tsunamis triggered by a rigid and impermeable wedge at a sloping coast. The method has been applied to perform a detailed numerical study of the near-field wave features induced by submerged landslides. A parametric analysis has been carried out to explore the importance of the landslide's initial acceleration, directly related to the landslide-triggering mechanisms, on the tsunami generation process and on the related wave properties. Near-field analysis of the numerical results confirms that the influence of the initial acceleration on the tsunami wave properties is significant, affecting wave height, wave period, and wave celerity. Furthermore, it is found that the tsunami generation mechanism experiences a saturation effect for increasing landslide's initial acceleration, confirming and extending previous studies. Moreover, the resulting extended database, composed of previous experimental data and new numerical ones, spanning a wider range of governing parameters, has been represented in the form of a “nondimensional wavemaker curve,” and a new relationship for predicting the wave properties in the near-field as a function of the Hammack number is proposed