GMDH to predict scour depth around a pier in cohesive soils |
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| Institution: | 1. Department of Civil Engineering, Shahid Bahonar University of Kerman, P.O. Box 76169133, Kerman, Iran;2. Department of Civil Engineering, Shahid Bahonar University of Kerman, P.O. Box 76169133, Kerman, Iran;3. River Engineering and Urban Drainage Research Centre (REDAC), Universiti Sains Malaysia, Penang, Malaysia;1. Shandong Provincial Key Laboratory of Ocean Engineering, Ocean University of China, No. 238 Songling Road, Laoshan District, Qingdao, Shandong 266100, China;2. Shandong Provincial Key Laboratory of Civil Engineering Disaster Prevention and Mitigation, Shandong University of Science and Technology, Qingdao 266590, China;1. Wave Energy Research Centre, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia;2. University of Cambridge, Department of Engineering, 7a JJ Thompson Avenue, Cambridge CB3 0FA, UK;3. University of Southampton, Boldrewood Innovation Campus, Southampton SO16 7QF, United Kingdom;4. The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia |
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| Abstract: | This study presents new application of group method of data handling (GMDH) to predict scour depth around a vertical pier in cohesive soils. Quadratic polynomial was used to develop GMDH network. Back propagation algorithm has been utilized to adjust weighting coefficients of GMDH polynomial thorough trial and error method. Parameters such as initial water content, shear strength, compaction of cohesive bed materials, clay content of cohesive soils, and flow conditions are main factors affecting cohesive scour. Performances of the GMDH network were compared with those obtained using several traditional equations. The results indicated that the proposed GMDH-BP has produced quite better scour depth prediction than those obtained using traditional equations. To assign the most significant parameter on scour process in cohesive soils, sensitivity analysis was performed for the GMDH-BP network and the results showed that clay percentage was the most effective parameter on scour depth. The error parameter for three classes of IWC and Cp showed that the GMDH-BP model yielded better scour prediction in ranges of IWC = 36.3–42.28% and Cp = 35–100%. In particular application, the GMDH network was proved very successful compared to traditional equations. The GMDH network was presented as a new soft computing technique for the scour depth prediction around bridge pier in cohesive bed materials. |
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