Neural Networks Applied to the Wave-Induced Fatigue Analysis of Steel Risers
المؤلفون المشاركون
Sagrilo, Luís V. S.
de Sousa, Fernando J. M.
Cortina, João P. R.
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-07-25
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Time domain stochastic wave dynamic analyses of offshore structures are computationally expensive.
Considering the wave-induced fatigue assessment for such structures, the combination of many environmental loading cases and the need of long time-series responses make the computational cost even more critical.
In order to reduce the computational burden related to the wave-induced fatigue analysis of Steel Catenary Risers (SCRs), this work presents the application of a recently developed hybrid methodology that combines dynamic Finite Element Analysis (FEA) and Artificial Neural Networks (ANN).
The methodology is named hybrid once it requires short time series of structure responses (obtained by FEA) and imposed motions (evaluated analytically) to train an ANN.
Subsequently, the ANN is employed to predict the remaining response time series using the prescribed motions imposed at the top of the structure by the floater unit.
In this particular work, the methodology is applied aiming to predict the tension and bending moments’ time series at structural elements located at the top region and at the touchdown zone (TDZ) of a metallic riser.
With the predicted responses (tensions and moments), the stress time series are determined for eight points along the pipe cross sections, and stress cycles are identified using a Rainflow algorithm.
Fatigue damage is then evaluated using SN curves and the Miner-Palmgren damage accumulation rule.
The methodology is applied to a SCR connected to a semisubmersible platform in a water depth of 910 m.
The obtained results are compared to those from a full FEA in order to evaluate the accuracy and computer efficiency of the hybrid methodology.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Cortina, João P. R.& de Sousa, Fernando J. M.& Sagrilo, Luís V. S.. 2018. Neural Networks Applied to the Wave-Induced Fatigue Analysis of Steel Risers. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1206410
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Cortina, João P. R.…[et al.]. Neural Networks Applied to the Wave-Induced Fatigue Analysis of Steel Risers. Mathematical Problems in Engineering No. 2018 (2018), pp.1-16.
https://search.emarefa.net/detail/BIM-1206410
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Cortina, João P. R.& de Sousa, Fernando J. M.& Sagrilo, Luís V. S.. Neural Networks Applied to the Wave-Induced Fatigue Analysis of Steel Risers. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1206410
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1206410
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر