Experimental Investigations Using Computer Vision for Debris Motion Generated by Solitary Waves SCIE SCOPUS

Cited 2 time in WEB OF SCIENCE Cited 3 time in Scopus
Title
Experimental Investigations Using Computer Vision for Debris Motion Generated by Solitary Waves
Author(s)
Kim, Taeyoon; Hwang, Taegeon; Baek, Seungil; Hong, Sunghoon; Kim, Jiwon; Lee, Woo-Dong
KIOST Author(s)
Hong, Sunghoon(홍성훈)
Alternative Author(s)
홍성훈
Publication Year
2023-06
Abstract
A tsunami created by the momentary release of a large amount of energy accumulated in the ocean crust destroys coastal structures and generates considerable debris, posing a serious threat to coastal communities. Hence, understanding the movement characteristics of drifting attributed to tsunamis for coastal disaster prevention is necessary. In this study, a color-based Debris mOtion Tracking (DOT) model is developed to understand the behavioral characteristics of drifting caused by solitary waves. The behavioral characteristics of drifting are analyzed quantitatively based on the weight of the debris, scale of solitary waves, and revetment type, which have not been considered previously. The DOT model tracks the drifting behavior more accurately than the existing commercial programs. In a laboratory experiment, the kinetic energy, and maximum debris velocity increase with an increase in the magnitude of solitary waves. An analysis of the drifting characteristics based on revetment type reveals that the initial acceleration of drifting in the wave absorbing revetment (WAR) is higher than that in the vertical revetment (VR). Velocities of vertical and horizontal flow develop in VR and WAR, respectively, and thus the momentum flux acted more strongly. Further, overtopping the wave characteristics based on the revetment type determines the drifting behavior.
ISSN
1793-4311
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/44386
DOI
10.1142/S1793431123500161
Bibliographic Citation
Journal of Earthquake and Tsunami, v.17, no.4, 2023
Publisher
World Scientific Publishing Co.
Keywords
shipping container; Computer vision; debris motion; revetment type; solitary wave
Type
Article
Language
English
Document Type
Article; Early Access
Files in This Item:
There are no files associated with this item.

qrcode

Items in ScienceWatch@KIOST are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse