Development of jacket platform tsunami risk rating system in waters offshore North Borneo

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• 作者：H. E. Lee ; M. S. Liew ; N. H. Mardi ; K. L. Na…
• 关键词：finite element analysis ; North Borneo ; jacket platforms ; Manila Trench ; seaquake ; SACS ; TUNA ; M2 ; tsunami simulation ; risk rating system ; risk rating model
• 刊名：Journal of Marine Science and Application
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：15
• 期：3
• 页码：307-320
• 全文大小：1,720 KB
• 刊物类别：Engineering
• 刊物主题：Offshore Engineering
  Machinery and Machine Elements
  Electrical Power Generation and Transmission
  Chinese Library of Science
  
• 出版者：Harbin Engineering University
• ISSN：1993-5048
• 卷排序：15

文摘

This work details the simulation of tsunami waves generated by seaquakes in the Manila Trench and their effect on fixed oil and gas jacket platforms in waters offshore North Borneo. For this study, a four-leg living quarter jacket platform located in a water depth of 63m is modelled in SACS v5.3. Malaysia has traditionally been perceived to be safe from the hazards of earthquakes and tsunamis. Local design practices tend to neglect tsunami waves and include no such provisions. In 2004, a 9.3M_w seaquake occurred off the northwest coast of Aceh, which generated tsunami waves that caused destruction in Malaysia totalling US$ 25 million and 68 deaths. This event prompted an awareness of the need to study the reliability of fixed offshore platforms scattered throughout Malaysian waters. In this paper, we present a review of research on the seismicity of the Manila Trench, which is perceived to be high risk for Southeast Asia. From the tsunami numerical model TUNA-M2, we extract computer-simulated tsunami waves at prescribed grid points in the vicinity of the platforms in the region. Using wave heights as input, we simulate the tsunami using SACS v5.3 structural analysis software of offshore platforms, which is widely accepted by the industry. We employ the nonlinear solitary wave theory in our tsunami loading calculations for the platforms, and formulate a platform-specific risk quantification system. We then perform an intensive structural sensitivity analysis and derive a corresponding platform-specific risk rating model.