Efficient derivation of extreme non-Gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation

Mukhlas, N. A.; Zaki, N. I. Mohd; Husain, M. K. Abu; Ahmad, Samsudin; Najafian, G.

doi:10.1080/17445302.2021.1898127

Cited by 4 publications

(6 citation statements)

References 25 publications

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“…Johari [143] introduced a technique for an optimization of the ETS method. The optimization ETS method has been validated with the MCTS method by comparing the short-term probability distribution of extreme responses at several sea states with the appearance of current impacts.…”

Section: Time Domain Methodsmentioning

confidence: 99%

“…Regarding conceptual ETS-RTS method, the proposed model was developed based on the excellent correlation found between the extreme values of surface elevation (input) and their corresponding responses (output) [138,139]. Meanwhile, the suggested number of simulations equal to N = 260 from the optimization of the ETS method would be used in the model development [143]. Hence, a simplified analysis-based time domain is introduced to overcome this issue by applying direct calculation procedures.…”

Section: Time Domain Methodsmentioning

confidence: 99%

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Offshore Structural Reliability Assessment by Probabilistic Procedures—A Review

Ahmad

Husain²,

Zaki³

et al. 2021

JMSE

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Offshore installations must be built to resist fatigue as well as extreme forces caused by severe environmental conditions. The structural reliability analysis is the popular practise to assess a variety of natural waves determined by the long-term probability distribution of wave heights and corresponding periods on the site. In truth, however, these structures are subjected to arbitrary wave-induced forces in the open ocean. Hence, it is much more reasonable to account for the changed loading characteristics by determining the probabilistic characteristics of the random loads and outcomes responses. The key challenges are uncertainties and the non-linearity of Morison’s drag element, which results in non-Gaussian loading and response distributions. This study would analyze advances achieved to date in a comprehensive probabilistic review of offshore fixed jacket-type platforms.

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Section: Time Domain Methodsmentioning

confidence: 99%

Section: Time Domain Methodsmentioning

confidence: 99%

Offshore Structural Reliability Assessment by Probabilistic Procedures—A Review

Ahmad

Husain²,

Zaki³

et al. 2021

JMSE

Self Cite

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“…The output is to verify the significant of application FMNS 𝑁𝐿 method in offshore structural analysis. Based on the current development of FMNS method done by Mukhlas et. al.…”

Section: Comparison Between Linear and Non-linear Wave Analysismentioning

confidence: 99%

“…Mukhlas et al (2018) and 2019 have discovered an alternative to the Monte Carlo approach. An efficient model has been introduced to generate the non-Gaussian stochastic structural response using a finite-memory nonlinear system known as FMNSNL (Mukhlas et al, 2021a). Based on the short-term probability distribution of an extreme non-Gaussian stochastic response, the accuracy of FMNSNL has been validated by the Monte Carlo time simulation method (Mukhlas et al, 2021b).…”

Section: Introductionmentioning

confidence: 99%

“…An efficient model has been introduced to generate the non-Gaussian stochastic structural response using a finite-memory nonlinear system known as FMNSNL (Mukhlas et al, 2021a). Based on the short-term probability distribution of an extreme non-Gaussian stochastic response, the accuracy of FMNSNL has been validated by the Monte Carlo time simulation method (Mukhlas et al, 2021b). However, the most satisfactory analysis is based on the longterm distribution (ABS, 2016;Raed et al, 2020;Haselsteiner et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Long-Term Offshore Structural Responses Based on Nonlinear Wave Modeling

Mukhlas,

Mohd Zaki,

Abu Husain

et al. 2023

JSCET

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Wind-generated random wave loads are the dominant loads to consider for maintaining the reliability of fixed offshore structures. Based on probabilistic techniques, the inherent randomness of the wave loading can be used to predict extreme offshore structural response, which is Gaussian in nature. However, researchers have found that the hydrodynamic component and structural dynamics substantially impact the frequency spectrum, leading to a non-Gaussian stochastic offshore structural response. A finite-memory non-linear system (FMNSNL) has been proven to be an efficient approach to evaluate the non-Gaussian stochastic offshore structural response compared to the conventional method, Monte Carlo time simulation. However, the analysis has been conducted based on short-term distribution only. The most satisfactory analysis is based on long-term distribution. Hence, further investigation in this paper will evaluate the long-term probability distribution of extreme offshore structural responses. As a result, a 100-year extreme offshore structural response prediction achieves 80% to 96% accuracy compared to the Monte Carlo time simulation. The probability distribution has been evaluated using the Gumbel distribution function throughout this investigation. Still, there is a little deviation at the tail end of the distribution between the simulated response values and the fitted line. A different distribution function, such as the Generalised Extreme Value (GEV) distribution, is advised for future work.

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Efficient derivation of extreme non-Gaussian stochastic structural response using the finite-memory nonlinear system (FMNS_NL). Part 1: model development

Mukhlas¹,

Zaki²,

Husain³

et al. 2021

Ships and Offshore Structures

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Efficient derivation of extreme non-Gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation

Cited by 4 publications

References 25 publications

Offshore Structural Reliability Assessment by Probabilistic Procedures—A Review

Offshore Structural Reliability Assessment by Probabilistic Procedures—A Review

Prediction of Long-Term Offshore Structural Responses Based on Nonlinear Wave Modeling

Efficient derivation of extreme non-Gaussian stochastic structural response using the finite-memory nonlinear system (FMNS_NL). Part 1: model development

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Efficient derivation of extreme non-Gaussian stochastic structural response using finite-memory nonlinear system. Part 2: model validation

Cited by 4 publications

References 25 publications

Offshore Structural Reliability Assessment by Probabilistic Procedures—A Review

Offshore Structural Reliability Assessment by Probabilistic Procedures—A Review

Prediction of Long-Term Offshore Structural Responses Based on Nonlinear Wave Modeling

Efficient derivation of extreme non-Gaussian stochastic structural response using the finite-memory nonlinear system (FMNSNL). Part 1: model development

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Efficient derivation of extreme non-Gaussian stochastic structural response using the finite-memory nonlinear system (FMNS_NL). Part 1: model development