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https://scholarbank.nus.edu.sg/handle/10635/161252
DC Field | Value | |
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dc.title | LONG-TERM EXTREME RESPONSE ANALYSIS OF MOORING LINES | |
dc.contributor.author | DARRELL LEONG WAI KIT | |
dc.date.accessioned | 2019-11-01T18:00:55Z | |
dc.date.available | 2019-11-01T18:00:55Z | |
dc.date.issued | 2019-05-07 | |
dc.identifier.citation | DARRELL LEONG WAI KIT (2019-05-07). LONG-TERM EXTREME RESPONSE ANALYSIS OF MOORING LINES. ScholarBank@NUS Repository. | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/161252 | |
dc.description.abstract | The prediction of long-term extreme response poses a challenging practical problem when assessing the structural reliability of offshore installations against severe events. High industry return period requirements necessitate observations of exceedingly rare events, often demanding unrealistically massive Monte Carlo sampling of computationally intensive dynamic analyses across the environmental scatter diagram. This dissertation addresses the problem in four stages. First, a case study of a simulated floating installation moored in the Gulf of Mexico is described, along with a joint-probabilistic model of environmental uncertainties fitted to historical data. Next, the native reliability formulation is presented, providing expectations on computational expenditure by conventional solutions. Third, the use of subset simulation is demonstrated as a robust validation methodology for evaluating extreme mooring tensions of rare probabilities. Lastly, four approaches developed during the course of the Ph.D. are proposed as efficient, feasible solutions to assessing long-term system reliability. The novel methodologies of Crossing rate Monte Carlo, auto-control variates, along with two unique variants of Point Estimation Methods are performed on the case study and validated with subset results, each demonstrating substantial speedups with varying success in computational expediency and approximation accuracy. | |
dc.language.iso | en | |
dc.subject | extreme value, Monte Carlo, reliability, variance reduction, probability, floating structures | |
dc.type | Thesis | |
dc.contributor.department | CIVIL & ENVIRONMENTAL ENGINEERING | |
dc.contributor.supervisor | LOW YING MIN | |
dc.contributor.supervisor | YOUNGKOOK KIM | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY | |
Appears in Collections: | Ph.D Theses (Open) |
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LeongD.pdf | 7.74 MB | Adobe PDF | OPEN | None | View/Download |
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