Hybrid parallel smooth particle hydrodynamic for probabilistic tsunami risk assessment and inland inundation

被引:0
|
作者
Sihombing, Fritz [1 ]
Torbol, Marco [1 ]
机构
[1] UNIST, Ulsan, South Korea
基金
新加坡国家研究基金会;
关键词
smooth particle hydrodynamic; parallel computing; tsunami risk assessment; probabilistic approach; dynamic analysis; INDIAN-OCEAN TSUNAMI; FIELD SURVEY; EARTHQUAKE; SUMATRA; SIMULATION; INDONESIA; ERUPTION; IMPACT;
D O I
10.12989/sss.2019.22.2.185
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The probabilistic tsunami risk assessment of large coastal areas is challenging because the inland propagation of a tsunami wave requires an accurate numerical model that takes into account the interaction between the ground, the infrastructures, and the wave itself. Classic mesh-based methods face many challenges in the propagation of a tsunami wave inland due to their ever-moving boundary conditions. In alternative, mesh-less based methods can be used, but they require too much computational power in the far-field. This study proposes a hybrid approach. A mesh-based method propagates the tsunami wave from the far-field to the near-field, where the influence of the sea floor is negligible, and a mesh-less based method, smooth particle hydrodynamic, propagates the wave onto the coast and inland, and takes into account the wave structure interaction. Nowadays, this can be done because the advent of general purpose GPUs made mesh-less methods computationally affordable. The method is used to simulate the inland propagation of the 2004 Indian Ocean tsunami off the coast of Indonesia.
引用
收藏
页码:185 / 194
页数:10
相关论文
共 45 条
  • [41] Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization
    Mohaghegh, Zahra
    Kazemi, Reza
    Mosleh, Ali
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2009, 94 (05) : 1000 - 1018
  • [42] Bayesian update of the parameters of probability distributions for risk assessment in a two-level hybrid probabilistic-possibilistic uncertainty framework
    Pedroni, N.
    Zio, E.
    Pasanisi, A.
    Couplet, M.
    SAFETY, RELIABILITY AND RISK ANALYSIS: BEYOND THE HORIZON, 2014, : 3295 - 3302
  • [43] Lung cancer risk in relation to traffic-related nano/ultrafine particle-bound PAHs exposure: A preliminary probabilistic assessment
    Liao, Chung-Min
    Chio, Chia-Pin
    Chen, Wei-Yu
    Ju, Yun-Ru
    Li, Wen-Hsuan
    Cheng, Yi-Hsien
    Liao, Vivian Hsiu-Chuan
    Chen, Szu-Chieh
    Ling, Min-Pei
    JOURNAL OF HAZARDOUS MATERIALS, 2011, 190 (1-3) : 150 - 158
  • [44] A Hybrid Intelligent Model for Urban Seismic Risk Assessment from the Perspective of Possibility and Vulnerability Based on Particle Swarm Optimization
    Chu, Jinlong
    Zhang, Qiang
    Wang, Ai
    Yu, Haoran
    SCIENTIFIC PROGRAMMING, 2021, 2021
  • [45] Empirical Comparison of Two Methods for the Bayesian Update of the Parameters of Probability Distributions in a Two-Level Hybrid Probabilistic-Possibilistic Uncertainty Framework for Risk Assessment
    Pedroni, N.
    Zio, E.
    Pasanisi, A.
    Couplet, M.
    ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 2016, 2 (01):