The accuracy and efficiency of the efficient time simulation procedure in derivation of the 100-year responses
Offshore structures are exposed to random wave loading in the ocean environment and hence the probability distribution of the extreme values of their response to wave loading is required for their safe and economical design. To this end, the conventional (Monte Carlo) time simulation technique (CTS)...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
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2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/59500/ http://hdl.handle.net/2117/332579 |
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| Summary: | Offshore structures are exposed to random wave loading in the ocean environment and hence the probability distribution of the extreme values of their response to wave loading is required for their safe and economical design. To this end, the conventional (Monte Carlo) time simulation technique (CTS) is frequently used for predicting the probability distribution of the extreme values of response. However, this technique suffers from excessive sampling variability and hence a large number of simulated extreme responses (hundreds of simulated response records) are required to reduce the sampling variability to acceptable levels. In this paper, three different versions of a more efficient time simulation technique (ETS) are compared by exposing a test structure to sea states of different intensity. The three different versions of the ETS technique take advantage of the good correlation between extreme responses and their corresponding surface elevation extreme values, or quasi-static and dynamic linear extreme responses. The accuracy and efficiency of an alternative technique in comparison with the conventional simulation technique is investigated. The accuracy and efficiency of the efficient time simulation procedure in derivation of the 100-year responses (PDF Download Available). Available from: https://www.researchgate.net/publication/280534306_The_accuracy_and_efficiency_of_the_efficient_time_simulation_procedure_in_derivation_of_the_100-year_responses [accessed Jun 20, 2017]. |
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