Articles | Volume 22, issue 4
https://doi.org/10.5194/nhess-22-1267-2022
https://doi.org/10.5194/nhess-22-1267-2022
Research article
 | 
11 Apr 2022
Research article |  | 11 Apr 2022

Rapid tsunami force prediction by mode-decomposition-based surrogate modeling

Kenta Tozato, Shinsuke Takase, Shuji Moriguchi, Kenjiro Terada, Yu Otake, Yo Fukutani, Kazuya Nojima, Masaaki Sakuraba, and Hiromu Yokosu

Data sets

K-Tozato/3D_tsunami_simulation: (Dataset_for_NHESS) K. Tozato https://doi.org/10.5281/zenodo.6394294

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Short summary
This study presents a novel framework for rapid tsunami force predictions through the application of mode-decomposition-based surrogate modeling with 2D–3D coupled numerical simulations. A numerical example is presented to demonstrate the applicability of the proposed framework to one of the tsunami-affected areas during the Great East Japan Earthquake of 2011.
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