کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6757972 1431212 2018 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An EWA framework for the probabilistic-based structural integrity assessment of offshore platforms
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
An EWA framework for the probabilistic-based structural integrity assessment of offshore platforms
چکیده انگلیسی
Endurance Wave Analysis (EWA) is a novel, simple, economical but yet reliable method for the integrity assessment of offshore platforms against extreme irregular waves. The current paper presents a framework for the probabilistic assessment of offshore platforms based on EWA. The stochastic nature and the uncertainties in the ocean waves were taken into account by introducing a set of artificial, random and gradually intensifying wave trains. To simulate other uncertainties in the loading and the strength of the structure a Latin Hypercube Sampling (LHS) type of Monte Carlo Simulation (MCS) was employed. The EWA methodology and different structural performance criteria were considered. The EWA results were then used to obtain the hazard functions and fragility curves for a number of Engineering Demand Parameters (EDPs). Similar to onshore buildings, and for the sake of comparison only, different structural performance criteria were considered. The mean annual probabilities of structural failure (Pf) at different structural performance limit states were also competently estimated. The results proved that EWA is an effective and robust tool for the probabilistic-based assessment of offshore platforms. It yet requires very short simulation time, as compared to the costly conventional 3-h time-domain analyses. In contrast to the probabilistic seismic assessments, EWA does not requires separate Multi Stripe Analyses (MSAs), because EWA is intrinsically multi stripe.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Marine Structures - Volume 59, May 2018, Pages 60-79
نویسندگان
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