Abstract

Pile-supported structures commonly found in both offshore (e.g. offshore oil and gas platforms) and coastal environments (e.g. sea bridges, piers and jetties) are generally built by means of a group of piles in different arrangements. The correct prediction of the wave loading of closely-spaced piles of these structures is vital for both safety and economical viewpoints. Unlike single isolated piles, where a large number of studies are available together with the well-known Morison equation which is still widely applied for the calculation of wave-induced force, less research studies have been made on wave-pile group interactions. In fact, no reliable wave load formula is yet available for the prediction of wave-induced forces on a slender pile, for which the pile diameter (D) is generally less than about 0.2 times the wave length (L), within a pile group.In this study, new wave load formulae for the prediction of wave-induced force on a slender pile in pile groups with different arrangements are developed using a series of laboratory data obtained from systematic model tests conducted in the 2m-wide wave flume of Leichtweiss-Institute for Hydraulic Engineering and Water Resources (LWI) in Braunschweig, Germany. For the analysis of the laboratory data and the development of the new prediction formulae, an artificial intelligence (AI)-based computational tool, named “hybrid M5MT-GP model”, is implemented. The new hybrid model and the new wave load formulae allow us to systematically assess the pile group effect (KG) as a function of the flow regime (KC number) and the relative spacing (SG/D) for each tested pile group arrangement. The results show that the pile group effect needs to be considered in calculating wave loads on the slender piles in pile groups, unless KG=1 where there is no interference effect between neighbouring piles and piles in the group can be treated as a single isolated pile. The accuracy of the new formulae in predicting pile group effect KG is confirmed by the statistical indicators using agreement index Ia, correlation coefficient CC and scatter index SI.

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