دانلود رایگان مقاله انگلیسی ارزیابی قابلیت اطمینان ساختار شناور دریایی با استفاده از شبکه بیزی - الزویر 2018

عنوان فارسی
ارزیابی قابلیت اطمینان ساختار شناور دریایی با استفاده از شبکه بیزی
عنوان انگلیسی
Reliability assessment of marine floating structures using Bayesian network
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
10
سال انتشار
2018
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
نوع مقاله
ISI
نوع نگارش
مقالات پژوهشی (تحقیقاتی)
رفرنس
دارد
پایگاه
اسکوپوس
کد محصول
E8919
رشته های مرتبط با این مقاله
مهندسی کامپیوتر، فناوری اطلاعات، عمران
گرایش های مرتبط با این مقاله
هوش مصنوعی، شبکه های کامپیوتری، سازه های دریایی
مجله
تحقیقات کاربردی اقیانوس - Applied Ocean Research
دانشگاه
National Centre for Maritime Engineering and Hydrodynamics - University of Tasmania - Launceston - Australia
کلمات کلیدی
شبکه بیزی، قابلیت اطمینان، هیدرودینامیک، ساختار شناور، سیستم مورینگ
doi یا شناسه دیجیتال
https://doi.org/10.1016/j.apor.2018.04.004
چکیده

ABSTRACT


Marine floating structures are widely used in various fields of industry from oil and gas to renewable energy. The predominant dynamic responses of these structures are controlled by mooring lines. In recent years, a number of high-profile mooring failures have highlighted the high risk of this element in floating structures. A reliable design of mooring liness is necessary to improve the safety of offshore operations. This paper proposes a novel methodology to conduct reliability analysis of moored floating structures using Bayesian network (BN). The long-term distributions of extreme responses of the floating object are estimated using analytical frequency domain method, while mooring failure probability is estimated using limit state function in the proposed BN framework. Application of the methodology is demonstrated by estimating the failure probabilities of a floating cylinder with tensioned mooring system. The proposed study also explains how the hydrodynamic and reliability analysis could be integrated with BN to assess the overall safety of the offshore structures. The methodology presented can be employed to mitigate associated risk with marine structures brought about by stochastic hydrodynamic loads.

نتیجه گیری

4. Conclusion


In this study, a methodology is developed to integrate Bayesian approaches with the hydrodynamics analysis of marine floating structures to improve their safety. For this purpose, the frequency domain approach is applied for hydrodynamic analysis given that this method provides an efficient solution to compute, either numerically or experimentally, the stochastic wave loads on structures. BNayesian network is adopted for estimating the probability of failure to identify the best design point. A floating tensioned cylinder is considered as a case study to demonstrate the application of the methodology. The structure is subjected to 12 sea states and the reliability of the mooring system is examined with respect to the allowable horizontal elongation. It is found that the structure can tolerate the extreme wave height with optimum critical surge response of XC = 3.5 m, corresponding to reliability index of almost β = 3.50. This methodology can be applied to effectively perform reliability analysis of a floating structure with tensioned mooring system. In order to use the proposed methodology for another type of failure, firstly it is necessary to develop a suitable limit state function for a particular failure scenario. The same approach should then be followed for developing the BN and estimation probability of the failure. For this purpose, a suitable limit state function, G, for a particular failure scenario (such as capsizing a vessel due to extreme roll angle) should firstly be developed and then follow the same approach proposed in Section 2.3 for developing related BN and estimation probability of the failure. Results of this research confirm that the methodology is successful in identifying the critical design point of the system with respect to hydrodynamic response of the structure in different sea states which can assist in maintaining an acceptable level of failure risk during the operational time.


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