Print Email Facebook Twitter Prediction of the characteristics of a tsunami wave near the Tohoku coastline Title Prediction of the characteristics of a tsunami wave near the Tohoku coastline: Numerical SWASH modelling Author Roubos, Jochem (TU Delft Civil Engineering & Geosciences) Contributor Hofland, Bas (mentor) Bricker, J.D. (graduation committee) Zijlema, Marcel (graduation committee) Esteban, Miguel (graduation committee) Degree granting institution Delft University of Technology Date 2019-07-02 Abstract To calculate tsunami forces on coastal structures, the wave type in front of the coast is of great importance. Hence this paper aims to find ways to predict the type of tsunami wave breaking. Based on literature review, video footage, analytical reasoning and numerical modelling (SWASH) it can be concluded that both the continental shelf slope (alpha_2) and the bay geometry (beta) have a significant influence on the transformation of a tsunami wave near the coastline. After conducting 1D and 2DH wave simulations, a distinction is made in three types of tsunami waves; a non-breaking front (surging), a breaking front (plunging) and an undular bore breaking front (spilling). Tsunami waves transform into these three wave types for a steep continental shelf, an intermediate sloped continental shelf, and a gentle sloped continental shelf respectively. A new tsunami breaker parameter (xi_tsunami) is proposed to predict the type of wave at the coastline in a quantitative way. Subject TsunamiBreaker parameterUndular boresSurgingClassificationContinental shelfBay geometry To reference this document use: http://resolver.tudelft.nl/uuid:421cd6b8-fd31-424a-aa9b-529dc17018eb Embargo date 2020-06-26 Bibliographical note This is a report of a master thesis, where a draft version of a publication is combined with the final report as an appendix. Part of collection Student theses Document type master thesis Rights © 2019 Jochem Roubos Files PDF Paper_and_Report_Final_Jo ... 162803.pdf 22.1 MB Close viewer /islandora/object/uuid:421cd6b8-fd31-424a-aa9b-529dc17018eb/datastream/OBJ/view