Impulse waves are generated by rapid subaerial mass movements including landslides, avalanches and glacier break-offs, which pose a potential risk to public facilities and residents along the shore of natural lakes or engineered reservoirs. Therefore, the prediction and assessment of impulse waves are of considerable importance to practical engineering. Tsunami Squares, as a meshless numerical method based on a hybrid Eulerian-Lagrangian algorithm, have focused on the simulation of landslide-generated impulse waves. An updated numerical scheme referred to as Tsunami Squares Leapfrog, was developed which contains a new smooth function able to achieve space and time convergence tests as well as the Leapfrog time integration method enabling second-order accuracy. The updated scheme shows improved performance due to a lower wave decay rate per unit propagation distance compared to the original implementation of Tsunami Squares. A systematic benchmark testing of the updated scheme was conducted by simulating the run-up, reflection and overland flow of solitary waves along a slope for various initial wave amplitudes, water depths and slope angles. For run-up, the updated scheme shows good performance when the initial relative wave amplitude is smaller than 0.4. Otherwise, the model tends to underestimate the run-up height for mild slopes, while an overestimation is observed for steeper slopes. With respect to overland flow, the prediction error of the maximum flow height can be limited to ± 50% within a 90% confidence interval. However, the prediction of the front propagation velocity can only be controlled to ± 100% within a 90% confidence interval. Furthermore, a sensitivity analysis of the dynamic friction coefficient of water was performed and a suggested range from 0.01 to 0.1 was given for reference.
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http://dx.doi.org/10.1038/s41598-024-63010-1 | DOI Listing |
MethodsX
December 2024
Program Studi Ilmu Komunikasi, Fakultas Ilmu Komunikasi, Universitas Islam Riau, Jalan Kaharuddin Nst No.113, Simpang Tiga, Kec. Bukit Raya, Kota Pekanbaru, Riau, Indonesia.
The goal of this research is to develop a model employing deep neural networks (DNNs) to predict the effectiveness of mangrove forests in attenuating the impact of tsunami waves. The dataset for the DNN model is obtained by simulating tsunami wave attenuation using the Boussinesq model with a staggered grid approximation. The Boussinesq model for wave attenuation is validated using laboratory experiments exhibiting a mean absolute error (MAE) ranging from 0.
View Article and Find Full Text PDFSci Rep
June 2024
School of Highway, Chang'an University, Xi'an, China.
Impulse waves are generated by rapid subaerial mass movements including landslides, avalanches and glacier break-offs, which pose a potential risk to public facilities and residents along the shore of natural lakes or engineered reservoirs. Therefore, the prediction and assessment of impulse waves are of considerable importance to practical engineering. Tsunami Squares, as a meshless numerical method based on a hybrid Eulerian-Lagrangian algorithm, have focused on the simulation of landslide-generated impulse waves.
View Article and Find Full Text PDFHeliyon
August 2023
The Doctoral School of Earth Sciences, Department of Geology and Meteorology, Institute of Geography and Earth Sciences, Faculty of Sciences, University of Pécs, Pécs, Hungary.
The 1693 tsunami was the most extensive earthquake-tsunami event in Sicily, submerging Catania, Augusta, and Syracuse. However, the earthquake rupture, water level, arrival time, and furthest inundation distance of the tsunami waves are not yet known. This study aims to investigate the tsunamigenic source, run-up height, furthest inundation distance, and arrival time of the 1693 tsunami waves on the east coast of Sicily.
View Article and Find Full Text PDFMethodsX
March 2023
Industrial and Financial Mathematics Research Group, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Bandung, Indonesia.
Accurate and computationally efficient prediction of wave run-up is required to mitigate the impacts of inundation and erosion caused by tides, storm surges, and even tsunami waves. The conventional methods for calculating wave run-up involve physical experiments or numerical modeling. Machine learning methods have recently become a part of wave run-up model development due to their robustness in dealing with large and complex data.
View Article and Find Full Text PDFJ Nutr Health Aging
February 2023
Aki Yazawa, PhD, Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, 677 Huntington Ave. Boston, MA 02115, USA, Tel: +1-617-432-0235; Fax: +1-617-432-3123, E-mail: ORCID: 0000-0002-4335-3880.
Objectives: Research suggests that cardiometabolic disease risks are elevated among survivors of natural disasters, possibly mediated by changes in diet. Using the Brief Dietary History Questionnaire, we examined (1) dietary patterns among older survivors of the 2011 Great East Japan Earthquake and Tsunami, and (2) the contribution of posttraumatic stress symptoms (PTSS)/depressive symptoms, as well as relocation to temporary housing on dietary patterns and (3) gender differences in the associations.
Design, Setting And Participants: Data came from a prospective cohort study of 1,375 survivors aged 65-89 years (44.
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