Estimation of scour propagation rates around pipelines while considering simultaneous effects of waves and currents conditions

Seabed offshore pipelines are widely applied to carry fluid over long distances of the seafloor. The design of offshore pipelines is conducted to bear quite a few environmental loading circumstances in order to provide a well-guarded and reliable fluid transition. Fluid leakage and pipeline vibration due to a failure of the pipeline are the prime causes of accidental catastrophes. Scour phenomena occur around offshore pipelines due to currents and/or wave conditions, consequently causing the susceptibility to pipeline failure. Then, scouring propagation rates require to be studied in three dimensions, namely beneath and normal to the offshore pipeline and the longitudinal direction of itself. In this research, Artificial Intelligent (AI) models are used to derive new regression equations based on the laboratory data for the estimation of 3D scour propagation patterns while seafloor offshore pipelines are exposed to simultaneous impacts of currents and waves. In this way, chiefly based on the experimental investigations conducted by Cheng and colleagues, seven sets of dimensional parameters were given in terms of the Shields’ parameter due to currents and waves, the Keulegan–Carpenter number, the ratio of embedment depth to pipeline diameter, the ratio of orbital velocity to current velocity, and the wave/current angle of attack. Dimensionless parameters were used to provide regression-based equations to evaluate scour propagation rates in three dimensions. The performance of AI models was evaluated by various statistical measures. The model based on our proposed equations performed better than the reported models in the literature. Even more importantly, we indicated that our model inherently has a reliable physical consistency for variations of dimensionless parameters against the scour propagation patterns