OPTIMAL LOCATION OF SURFACE BUOYS FOR TSUNAMI WARNING SYSTEM

As a natural disaster with one of the greatest destructive power, tsunami is capable of destroying vehicles, buildings, infrastructures in the coastal area. Some places in the world (including Indonesia and Japan) are more prone to tsunami then others, due to their geographic location being close to...

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Bibliographic Details
Main Author: La'Lang, Raynaldi
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/53710
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:As a natural disaster with one of the greatest destructive power, tsunami is capable of destroying vehicles, buildings, infrastructures in the coastal area. Some places in the world (including Indonesia and Japan) are more prone to tsunami then others, due to their geographic location being close to tectonic plate boundaries. In these places, especially, tsunami warning system is implemented in order to anticipate upcoming tsunamis and mitigate the resulting damages. This work proposes a method to find the optimal location of surface buoys, which is a detection component of the modern Deep-ocean Assessment and Reporting of Tsunamis (DART), to minimize tsunami detection time which would allow for longer evacuation time. The method is primarily composed of two parts: Shallow Water Equations (SWE) and Particle Swarm Optimization (PSO). A staggered finite volume scheme on the Shallow Water Equations is used to generate tsunami waves and calculate their travel time to any given point in two-dimensional space. The numerical scheme was tested against various conditions in which it showed to give accurate results. Then, the Particle Swarm Optimization algorithm is used to find the optimal location of surface buoys that would minimize the detection time, given some depth or domain constraints. This method was applied to find the optimal location of surface buoys in simple bathymetry, as well as one based on a tsunami incident in Palu (2018). The result of this work proved that this method is able to reduce detection time significantly, compared to shore-based tide gauges.