Tsunami risk assessment using spatial modes extracted from results of numerical analysis

Kenta Tozato, Takuma Kotani, Ryo Hatano, Shinsuke Takase, Shuji Moriguchi, Kenjiro Terada, Yu Otake

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number20200003
JournalTransactions of the Japan Society for Computational Engineering and Science
Volume2020
DOIs
Publication statusPublished - 2020

Keywords

  • Mode Decomposition
  • Monte Carlo method
  • Proper Orthogonal Decomposition
  • Reduced Order Model
  • Singular Value Decomposition

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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