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The accuracy of the MFMNS and FMNS models in predicting long-term distribution of the extreme values of offshore structural response

Mohd. Zaki, Noor Irza and Abu Husain, M. K. and Najafian, G. (2014) The accuracy of the MFMNS and FMNS models in predicting long-term distribution of the extreme values of offshore structural response. In: 33rd International Conference on Ocean, Offshore and Arctic Engineering, ASME 2014, 8-13 June, 2014, USA.

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Official URL: http://dx.doi.org/10.1115/OMAE2014-23142

Abstract

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 of great value in the design of these structures. Due to nonlinearity of the drag component of Morison's wave loading and also due to intermittency of wave loading on members in the splash zone, the response is often non-Gaussian; therefore, simple techniques for derivation of the probability distribution of extreme responses are not available. Monte Carlo time simulation technique can be used to derive the probabilistic properties of offshore structural response, but the procedure is computationally demanding. Finite-memory nonlinear system (FMNS) modeling of the response of an offshore structure exposed to Morison's wave loading has been introduced to reduce the computational effort, but the predictions are not very good for low intensity sea states. To overcome this deficiency, a modified version of the FMNS technique (referred to as MFMNS modeling) was proposed which improves the accuracy, but is computationally less efficient than the FMNS modeling. In this study, the accuracy of the 100-year responses derived from the long-term probability distribution of extreme responses from FMNS and MFMNS methods is investigated.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:offshore structures, response extreme values
Subjects:T Technology
Divisions:Razak School of Engineering and Advanced Technology
ID Code:62838
Deposited By: Fazli Masari
Deposited On:18 Jun 2017 05:58
Last Modified:18 Jun 2017 05:58

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