Preprints
https://doi.org/10.5194/nhess-2021-77
https://doi.org/10.5194/nhess-2021-77

  07 May 2021

07 May 2021

Review status: this preprint is currently under review for the journal NHESS.

Real-time Tsunami Force Prediction by Mode Decomposition-Based Surrogate Modeling

Kenta Tozato1, Shinsuke Takase2, Shuji Moriguchi3, Kenjiro Terada3, Yu Otake4, Yo Fukutani5, Kazuya Nojima6, Masaaki Sakuraba6, and Hiromu Yokosu7 Kenta Tozato et al.
  • 1Department of Civil and Environmental Engineering, Tohoku University, Aza-Aoba 468-1, Aramaki, Aoba-ku, Sendai 980-8572, Japan
  • 2Department of Civil Engineering and Architecture, Hachinohe Institute of Technology, 88-1 Ohbiraki, Myo, Hachinohe, Aomori 031-8501, Japan
  • 3International Research Institute of Disaster Science, Tohoku University, Aza-Aoba 468-1, Aramaki, Aoba-ku, Sendai 980-8572, Japan
  • 4Department of Civil and Environmental Engineering, Tohoku University, Aza-Aoba 6-6-01, Aramaki, Aoba-ku, Sendai 980-8579, Japan
  • 5College of Science and Engineering, Kanto Gakuin University, Mutsuura Higashi 1-50-1, Kanazawa-ku, Yokohama-shi, Kanagawa 236-8501, Japan
  • 6Research and Development Center, Nippon Koei Co., Ltd. Inarihara, 2304, Tsukuba-shi, Ibaraki 300-1259, Japan
  • 7Nuclear Safety Research Development Center, Chubu Electric Power Co., Inc., Sakura 5561, Omaezaki, Shizuoka 437-1695, Japan

Abstract. This study presents a framework for real-time tsunami force predictions by the application of mode decomposition based surrogate modelling with 2D-3D coupled numerical simulations. A limited number of large-scale numerical analyses are performed for a selection scenarios with variations in fault parameters to capture the distribution tendencies of the target risk indicators. Then, the proper orthogonal decomposition (POD) is applied to the analysis results to extract the principal modes that represent the temporal and spatial characteristics of tsunami forces. A surrogate model is then constructed by a linear combination of these modes, whose coefficients are defined as functions of the selected input parameters. 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. Combining 2D and 3D versions of the stabilized finite element method, we carry out a series of high precision numerical analyses with different input parameters to obtain a set of time history data of the tsunami forces acting on buildings and the inundation depths. POD is applied to the data set to construct the surrogate model that is capable of providing the predictions equivalent to the simulation results almost instantaneously. Based on the acceptable accuracy of the obtained results, it was confirmed that the proposed framework is a useful tool for evaluating time series data of hydrodynamic force acting on buildings.

Kenta Tozato et al.

Status: open (until 18 Jun 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-77', Anonymous Referee #1, 17 May 2021 reply
    • AC1: 'Reply on RC1', Shuji Moriguchi, 19 May 2021 reply

Kenta Tozato et al.

Kenta Tozato et al.

Viewed

Total article views: 274 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
230 37 7 274 3 1
  • HTML: 230
  • PDF: 37
  • XML: 7
  • Total: 274
  • BibTeX: 3
  • EndNote: 1
Views and downloads (calculated since 07 May 2021)
Cumulative views and downloads (calculated since 07 May 2021)

Viewed (geographical distribution)

Total article views: 245 (including HTML, PDF, and XML) Thereof 245 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 13 Jun 2021
Download
Short summary
This study presents a novel framework for real-time predictions of time-varying tsunami forces. An instant prediction is realized by the surrogate model constructed from a series of numerical analysis data based on proper orthogonal decomposition. A numerical example was presented to demonstrate the capability of the framework in evaluating the time series of tsunami forces in a selected tsunami-affected area during the Great East Japan Earthquake of 2011 with a certain degree of accuracy.
Altmetrics