Modeling dynamic behaviours of wharf piles due to wave, sediment and liquified soil effets

Dynamic behaviour of marine structures composed of single piles and pile groups can be numerically and anaylitically calculated. Especially, the governing equation of dynamic behaviour of pile must be firstly derived by considering the external forces including both of environmental loads such as wave, sediment and liquified soil, and structural-functional loads and pile structural parameters. Design parameters for determining wave equation changes according to the contruction depth of piles. Design parameters are of great importance in the calculation of hydrodynamic forces that affect the piles. The governing wave theory in the useful life of a pier can be determined depending on the wave period, water depth and wave height. It is known that the flow rate calculated according to the wave theories increases the density of seawater and trigers the sediment transport at the sea bed. In this study, the motion of a axially compressed single pile under linear and non-linear wave forces, suspended bed load and liquified soil pressure is formulized and numerically analyzed. Wave and sediment motions as Newtonian fluid and liquified soil motion as Non-Newtonian fluid covering the power-law rule are defined in accordance with the Navier-Stokes equation. Pile dynamical analysis is numerically performed by using the ABAQUS software in accordance with initial and boundary conditions of this study. While modelling the cylindirical steel pipe-like pile system in the defined marine environment system, the 2-main models and 5-sub models for each main model based on differentiation of external forces consisting of wave forces, sediment and liqified soil motions for both axially compressed and non-compressed pile have been setuo. Wave-induced hyrodynamic pressures and flow velocities around the pile and horizontal displacements and the Von-Mises stresses varying along steel pile are analyzed seperately for each developed model. Such resulting parameters are evaluated and correlated with each other by taking multi-regression analysis.