2023
DOI: 10.3390/jmse11102015
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Three-Dimensional Modeling of Tsunami Waves Triggered by Submarine Landslides Based on the Smoothed Particle Hydrodynamics Method

Zili Dai,
Xiaofeng Li,
Baisen Lan

Abstract: Submarine landslides are a global geohazard that can displace huge volumes of loose submarine sediment, thereby triggering enormous tsunami waves and causing a serious threat to coastal cities. To investigate the generation of submarine landslide tsunamis, a three-dimensional numerical model based on the smoothed particle hydrodynamics (SPH) method is presented in this work. The model is first validated through the simulation of two underwater landslide model tests, and is then applied to simulate the movement… Show more

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Cited by 34 publications
(12 citation statements)
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“…Shuai (2020) constructed a particle management system, and from the optimization of the particle system data structure, designed a three-layer structure of view Schematic of ray casting. Feng et al 10.3389/fmars.2024.1367702 volume index, flow field data grid, and particles, to quickly retrieve and render the particles in the current view volume, which greatly reduces the volume of particle visualization calculations, and improves the efficiency of the particle system to simulate the flow field (Shi et al, 2021) proposed a new method to visualize multilevel flow field dynamics based on a particle system, researched parallel particle tracking and efficient rendering, and proposed a viewport adaptive tuning algorithm that can efficiently express vector field features in multiscale situations (Zhang et al, 2019) computed the differences between the data at adjacent time points in different frames to change the attributes and introduced a Compute Unified Device Architecture (CUDA) parallel computing model to visualize large-scale particle changes, which reduced the Central Processing Unit (CPU) load and significantly improved the frame rate (Dai et al, 2023) used the smooth particle hydrodynamics (SPH) method to simulate the free surface problem in ocean engineering and reproduced the whole process of submarine landslide propagation and tsunami occurrence. However, with the current particle system visualization technology, more research still stays on the single-moment twodimensional expression effect.…”
Section: Rendering Of Vector Fieldsmentioning
confidence: 99%
“…Shuai (2020) constructed a particle management system, and from the optimization of the particle system data structure, designed a three-layer structure of view Schematic of ray casting. Feng et al 10.3389/fmars.2024.1367702 volume index, flow field data grid, and particles, to quickly retrieve and render the particles in the current view volume, which greatly reduces the volume of particle visualization calculations, and improves the efficiency of the particle system to simulate the flow field (Shi et al, 2021) proposed a new method to visualize multilevel flow field dynamics based on a particle system, researched parallel particle tracking and efficient rendering, and proposed a viewport adaptive tuning algorithm that can efficiently express vector field features in multiscale situations (Zhang et al, 2019) computed the differences between the data at adjacent time points in different frames to change the attributes and introduced a Compute Unified Device Architecture (CUDA) parallel computing model to visualize large-scale particle changes, which reduced the Central Processing Unit (CPU) load and significantly improved the frame rate (Dai et al, 2023) used the smooth particle hydrodynamics (SPH) method to simulate the free surface problem in ocean engineering and reproduced the whole process of submarine landslide propagation and tsunami occurrence. However, with the current particle system visualization technology, more research still stays on the single-moment twodimensional expression effect.…”
Section: Rendering Of Vector Fieldsmentioning
confidence: 99%
“…In recent years, advancement in computer science (He et al, 2021; Huang et al, 2023; Mao et al, 2022; Yin, Wang, et al, 2023; Yin, Wu, et al, 2023), algorithms (Dai et al, 2023; Jia et al, 2023; Xu et al, 2022; Yang et al, 2022, 2023) and GIS and remote sensing (Guan et al, 2023; Tian et al, 2019, 2020; Zhou et al, 2023; Zhou, Li, et al, 2022; Zhou, Wang, et al, 2022; Zhu et al, 2022) models can provide accurate prediction of occurrences. There are different methods including machine learning techniques using remote sensing images that were proposed and computed in geographic information system (GIS) environment to predict different geohazards like landslides, floods, land subsidence, soil/gully erosion and many others (Bagheri‐Gavkosh et al, 2021; Conoscenti et al, 2018; Souissi et al, 2020; Tehrany et al, 2015; Tien Bui et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…With the advent of advanced computational and simulation techniques, many fields of research have been revolutionized toward attaingng more comprehensive solutions 1 4 . Environmental risk assessment is one of these fields that has experienced considerable improvement in recent decades 5 . Landslide susceptibility assessment is one of these fields that plays an imperative role in harnessing this hazard in prone areas 6 , 7 .…”
Section: Introductionmentioning
confidence: 99%