Prediction of scour depth at breakwaters due to non-breaking waves using machine learning approaches |
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| Institution: | 1. School of Civil Engineering, Iran University of Science and Technology (IUST), Tehran, Iran;2. Department of Civil, Building Engineering and Architecture(DICEA), Università Politecnica delle Marche, Ancona, Italy;3. Department of Architecture, School of Engineering, University College of Nabi Akram (UCNA), Tabriz, Iran;4. Ministry of Energy, Water Resources Management Company, Yazd Regional Water Authority, Yazd, Iran;5. Department of Arts and Architecture, Tabriz branch, Islamic Azad University, Tabriz, Iran;6. Industrial and Mechanic Engineering Faculty, Qazvin Branch, Islamic Azad University, Qazvin, Iran;1. Metocean Modelling and Analysis, Fugro GB Marine Ltd., Wallingford, OX10 9RB, UK;2. The Lyell Centre for Earth and Marine Science and Technology, Institute for Infrastructure and Environment, Heriot-Watt University, Edinburgh, UK;3. State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, 610065, Chengdu, China;1. Faculty of Civil Engineering, National Institute of Technology Warangal, India;2. Faculty of Engineering, Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, Dashte Azadegan, Iran;3. Dept. of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran;4. Water Engineering Department, Faculty of Agriculture, University of Zanjan, Zanjan, Iran;5. College of Agriculture, Waraseoni, Balaghat, M.P. 481331, India;6. Dept. of Civil & Environmental Engineering, North Dakota State University, Fargo, ND, USA;1. Department of Civil, Construction, and Environmental Engineering, North Carolina State University, 915 Partners Way, Raleigh, NC 27606, United States;2. Department of Geology, Colby College, 4000 Mayflower Hill, Waterville, ME 04901, United States;1. School of Architecture, University of Mohaghegh Ardabili, Iran;2. Department of Architecture, Faculty of Architecture, Gazi University, Ankara, Turkey;3. Young Researchers Club, Tabriz Branch, Islamic Azad University, Tabriz, Iran;4. Dept. of Sustainable and Renewable Energy Engineering, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates;5. Mechanical Engineering and Design, Aston University, School of Engineering and Applied Science, Aston Triangle, Birmingham B4 7ET, UK;1. Istanbul Technical University, Civil Engineering Faculty, Division of Hydraulics, 34469 Maslak, Istanbul, Turkey;2. Department of Civil Engineering, Democritus University of Thrace, Vasil. Sophias 12, 67100 Xanthi, Greece |
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| Abstract: | Coastal structures may cease to function properly due to seabed scouring. Hence, prediction of the maximum scour depth is of great importance for the protection of these structures. Since scour is the result of a complicated interaction between structure, sediment, and incoming waves, empirical equations are not as accurate as machine learning schemes, which are being widely employed for the coastal engineering modeling. In this paper, which can be regarded as an extension of Pourzangbar et al. (2016), two soft computing methods, a support vector regression (SVR), and a model tree algorithm (M5′), have been implemented to predict the maximum scour depth due to non-breaking waves. The models predict the relative scour depth (Smax/H0) on the basis of the following variables: relative water depth at the toe of the breakwater (htoe/L0), Shields parameter (θ), non-breaking wave steepness (H0/L0), and reflection coefficient (Cr). 95 laboratory data points, extracted from dedicated experimental studies, have been used for developing the models, whose performances have been assessed on the basis of statistical parameters. The results suggest that all of the developed models predict the maximum scour depth with high precision, the M5′ model performed marginally better than the SVR model and also allowed to define a set of transparent and physically sound relationships. Such relationships, which are in good agreement with the existing empirical findings, show that the relative scour depth is mainly affected by wave reflection. |
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| Keywords: | Seabed scour Non-breaking waves SVR M5′ model tree algorithm |
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