TY - JOUR
T1 - Tsunami risk assessment using spatial modes extracted from results of numerical analysis
AU - Tozato, Kenta
AU - Kotani, Takuma
AU - Hatano, Ryo
AU - Takase, Shinsuke
AU - Moriguchi, Shuji
AU - Terada, Kenjiro
AU - Otake, Yu
N1 - Publisher Copyright:
©2020 by the Japan Society for Computational Engineering and Science.
PY - 2020
Y1 - 2020
N2 - This study presents a new framework of simulation-based tsunami risk assessment with the help of a mode decomposition technique. In the proposed framework, a series of numerical simulations is performed in consideration of uncertainties to investigate tendency of a risk index. Spatial modes are then extracted from the simulated results using the theory of the proper orthogonal decomposition(POD), and a surrogate model is defined as a linear combination of the spatial modes. After the surrogate model is obtained, the Monte Carlo simulation is performed using the surrogate model to discuss tsunami risk based on probabilistic risk analysis. In this study, the proposed method is applied to risk evaluation of the tsunami force acting on the buildings in a simple condition. According to the obtained results, the proposed framework can provide an efficient approach of the probabilistic tsunami risk analysis, and it has high potential for disaster risk evaluation.
AB - This study presents a new framework of simulation-based tsunami risk assessment with the help of a mode decomposition technique. In the proposed framework, a series of numerical simulations is performed in consideration of uncertainties to investigate tendency of a risk index. Spatial modes are then extracted from the simulated results using the theory of the proper orthogonal decomposition(POD), and a surrogate model is defined as a linear combination of the spatial modes. After the surrogate model is obtained, the Monte Carlo simulation is performed using the surrogate model to discuss tsunami risk based on probabilistic risk analysis. In this study, the proposed method is applied to risk evaluation of the tsunami force acting on the buildings in a simple condition. According to the obtained results, the proposed framework can provide an efficient approach of the probabilistic tsunami risk analysis, and it has high potential for disaster risk evaluation.
KW - Mode Decomposition
KW - Monte Carlo method
KW - Proper Orthogonal Decomposition
KW - Reduced Order Model
KW - Singular Value Decomposition
UR - http://www.scopus.com/inward/record.url?scp=85081171419&partnerID=8YFLogxK
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U2 - 10.11421/jsces.2020.20200003
DO - 10.11421/jsces.2020.20200003
M3 - Article
AN - SCOPUS:85081171419
SN - 1344-9443
VL - 2020
JO - Transactions of the Japan Society for Computational Engineering and Science
JF - Transactions of the Japan Society for Computational Engineering and Science
M1 - 20200003
ER -