Modeling Positive Buoyant Material in Water for the Hydrogeological Risk Evaluation and Management

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (5 November 2023) | Viewed by 1352

Special Issue Editors


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Guest Editor
Department of Civil and Building Engineering, and Architecture, Università Politecnica delle Marche, Via Brecce Biance, 60131 Ancona, Italy
Interests: nonlinear analysis; data analysis; multiple regression; civil engineering; structural analysis; wave propagation; fluid mechanics; computational fluid mechanics; fluid structure interaction; renewable energy

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Guest Editor
Department of Civil and Environmental Engineering, Clarkson University, Potsdam, NY 13699-5710, USA
Interests: river ice; river hydraulics; sediment transport; ice jam and flooding; mathematical modeling; freeze up; frazil and anchor ice

Special Issue Information

Dear Colleagues,

The interest in hydraulic risk is continuously increasing due to both the increased human exposure and the rise of extreme events. Many hydraulic hazard phenomena of recent interest involve positively buoyant materials, both natural and human-made. For example, human access to remote areas has increased exposure to the risk of tsunamis generated by natural positive buoyancy materials, such as pyroclastic flow, snow avalanche, or iceberg calving. In addition, flood damage, especially in urban areas, is mainly due to the transport and impact of floating materials of various types, from lumber to vehicles to garbage. Finally, plastic pollution, by now present in all oceans and all the larger rivers worldwide, often consists of positively buoyant debris. Thus, appropriate knowledge and modeling of the interaction of positive buoyant materials with water is crucial for the study of such phenomena and, consequently, for the assessment and management of their impact.

This Special Issue aims to collect the most recent studies on positively buoyant materials in water, ranging from basic theoretical modeling to application, in the perspective of hydraulic risk. For this purpose, authors are invited to submit contributions that take into considerations the following topics:

  • Iceberg calving
  • Numerical modelling
  • Snow avalanches behavior in water
  • The dynamics of debris transported in flood
  • The dynamics of micro and macro plastics

Dr. Gianluca Zitti
Prof. Dr. Hung Tao Shen
Guest Editors

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Keywords

  • positive buoyant material
  • hydraulic rick
  • pyroclastic flow
  • snow avalanche
  • iceberg calving
  • urban flood transportation
  • ocean plastic pollution

Published Papers (1 paper)

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Research

17 pages, 4572 KiB  
Article
Temporal Prediction of Landslide-Generated Waves Using a Theoretical–Statistical Combined Method
by Zhenzhu Meng, Jinxin Zhang, Yating Hu and Christophe Ancey
J. Mar. Sci. Eng. 2023, 11(6), 1151; https://doi.org/10.3390/jmse11061151 - 31 May 2023
Cited by 3 | Viewed by 905
Abstract
For the prediction of landslide-generated waves, previous studies have developed numerous empirical equations to express the maximums of wave characteristics as functions of slide parameters upon impact. In this study, we built the temporal relationship between the wave characteristics and slide features. We [...] Read more.
For the prediction of landslide-generated waves, previous studies have developed numerous empirical equations to express the maximums of wave characteristics as functions of slide parameters upon impact. In this study, we built the temporal relationship between the wave characteristics and slide features. We gave specific insights into impulse waves generated by snow avalanches and mimicked them using a buoyant material called Carbopol whose density is close to that of water. Using the particle image velocimetry (PIV) technique, the slide’s temporal velocity field and thickness, as well as the temporal free water surface fluctuation, were determined experimentally. Using a statistical method denoted as panel data analysis, we quantified the temporal wave amplitude from the time series data of the thickness and depth-averaged velocity of the sliding mass at the shoreline. Then, the slide’s temporal thickness and velocity at the shoreline were estimated from the parameters of the stationary slide at the initial position, based on the viscoplastic theory. Combining the panel data analysis and the viscoplastic theory, the temporal wave amplitudes were estimated from the initial slide parameters. In the end, we validated the proposed theoretical–statistical combined predictive method with the support of experimental data. Full article
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