Articles | Volume 23, issue 5
https://doi.org/10.5194/nhess-23-1891-2023
https://doi.org/10.5194/nhess-23-1891-2023
Research article
 | 
25 May 2023
Research article |  | 25 May 2023

Optimal probabilistic placement of facilities using a surrogate model for 3D tsunami simulations

Kenta Tozato, Shuji Moriguchi, Shinsuke Takase, Yu Otake, Michael R. Motley, Anawat Suppasri, and Kenjiro Terada

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-208', Anonymous Referee #1, 11 Sep 2022
    • AC1: 'Reply on RC1', Kenta Tozato, 20 Sep 2022
  • RC2: 'Comment on nhess-2022-208', Anonymous Referee #2, 29 Oct 2022
    • AC2: 'Reply on RC2', Kenta Tozato, 07 Nov 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (13 Jan 2023) by Rachid Omira
AR by Kenta Tozato on behalf of the Authors (21 Feb 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (16 Mar 2023) by Rachid Omira
RR by Anonymous Referee #2 (20 Mar 2023)
ED: Publish subject to minor revisions (review by editor) (11 Apr 2023) by Rachid Omira
AR by Kenta Tozato on behalf of the Authors (25 Apr 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (26 Apr 2023) by Rachid Omira
AR by Kenta Tozato on behalf of the Authors (28 Apr 2023)
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Short summary
This study presents a framework that efficiently investigates the optimal placement of facilities probabilistically based on advanced numerical simulation. Surrogate models for the numerical simulation are constructed using a mode decomposition technique. Monte Carlo simulations using the surrogate models are performed to evaluate failure probabilities. Using the results of the Monte Carlo simulations and the genetic algorithm, optimal placements can be investigated probabilistically.
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