کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1720189 1014237 2011 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction of wave-induced scour depth under submarine pipelines using machine learning approach
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی دریا (اقیانوس)
پیش نمایش صفحه اول مقاله
Prediction of wave-induced scour depth under submarine pipelines using machine learning approach
چکیده انگلیسی

The scour around submarine pipelines may influence their stability; therefore scour prediction is a very important issue in submarine pipeline design. Several investigations have been conducted to develop a relationship between wave-induced scour depth under pipelines and the governing parameters. However, existing formulas do not always yield accurate results due to the complexity of the scour phenomenon. Recently, machine learning approaches such as Artificial Neural Networks (ANNs) have been used to increase the accuracy of the scour depth prediction. Nevertheless, they are not as transparent and easy to use as conventional formulas. In this study, the wave-induced scour was studied in both clear water and live bed conditions using the M5’ model tree as a novel soft computing method. The M5’ model is more transparent and can provide understandable formulas. To develop the models, several dimensionless parameter, such as gap to diameter ratio, Keulegan–Carpenter number and Shields number were used. The results show that the M5’ models increase the accuracy of the scour prediction and that the Shields number is very important in the clear water condition. Overall, the results illustrate that the developed formulas could serve as a valuable tool for the prediction of wave-induced scour depth under both live bed and clear water conditions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Ocean Research - Volume 33, Issue 1, February 2011, Pages 54–59
نویسندگان
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