Hydraulic structures are anything that can be used to divert, restrict, stop, or otherwise manage the natural flow of water. They can be made from materials ranging from large rock and concrete to obscure items such as wooden timbers or tree trunks. Nowadays, there are many hydraulic structures failure such as pipelines, dams and bridge collapsed due to the scour problems. Interactions between the pipeline and its erodible bed under strong current and/or wave conditions may cause scour around the pipelines. This process involves the complexities of both the three-dimensional flow pattern and sediment movement. Scour underneath the pipeline may expose a section of the pipe, causing it to become unsupported. Accurate estimate of the scour depth is important in the design of submarine pipelines (Chiew, 1991). The estimation of the scour characteristics of underwater pipelines continues to be a concern for hydraulic engineers. A number of empirical formulas have been developed in the past to estimate equilibrium scour depth below pipelines, including Chao and Hennessy (1972), Kjeldsen et aI., (1973), Ibrahim and Nalluri (1986), Dutch research group (Bijker and Leeuwestein, 1984), Moncada and Aguirre (1999), and Chiew (1991). However, the main deficiency of these formulas is that the empirical equations do not model actual scour process. Predictive approaches such as artificial neural networks (ANN) (Azmathullah et aI., 2005) and genetic programming have been recently shown to yield effective estimates of scour around hydraulic structures.
Prediction of scour below submerged pipieline crossing a river using genetic programming