Predicting Extreme Dynamic Response of Offshore Jacket Platform Subject to Harsh Environment

Saeed Khalaj, Farshad BahooToroody, Leonardo Leoni, Filippo De Carlo, Gianpaolo Di Bona, Antonio Forcina and Salvatore Caddemi

Mathematical Problems in Engineering, 2022, vol. 2022, 1-15

Abstract: Offshore jacket platforms (OJPs) may be exposed to harsh environmental conditions during their operation in different return periods. It is necessary to evaluate the dynamic performance of the OJPs subjected to extreme wave loadings to secure a safe operation. In the earlier studies, various approaches were introduced to analyze the response of an OJP in different sea states. However, the serious shortcoming of the proposed methods is computationally time consuming and requires a considerable amount of simulations to evaluate the performance of the OJP. Accordingly, these approaches would not analyze the dynamic performance of the OJP realistically. In this study, the dynamic performance of an OJP subject to a harsh environment is evaluated considering a time-domain simulation. The developed model will result in a more realistic response by simulating the whole structure subjected to 1800 seconds of extreme wave loading in the light of the sea environment randomness. The application of the methodology is demonstrated by assessing the performance of a fabricated OJP subjected to extreme wave loadings in the North Sea. The dynamic analysis shows that among all assigned probability distribution functions (PDFs), the most suitable distribution for predicting the maximum deck displacement in all return periods was generalized extreme value (GEV). Moreover, the results show that the response of the structure is likely to remain in the safe limit condition in the 1-year return period. In contrast, in other return periods, the OJP will exceed the safe limit condition. The proposed method is beneficial for future risk and reliability analyses that require a great deal of data derived from numerical simulations.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1622243

DOI: 10.1155/2022/1622243

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