The breakout failure mechanism of un-trenched submarine pipelines subject to current-induced hydrodymic loading involves complex interactions between the pipe and the surrounding soil. Methods commonly used in conventiol stability alyses of pipelines do not adequately consider several important factors, such as the effects of seabed slope and pipe anchorages. In this paper, a self-evolving artificial neural network (SEANN) is used to develop an empirical relation between the coefficient of ultimate lateral soil resistance to breakout, the properties of the pipe, and the supporting seabed. Additiol parameters such as the angle of inclition of the seabed to the horizontal and the pipe's rolling restraint condition are also included as variables affecting the resistance coefficient. The results of the model validation with previous experimental data demonstrate the abilities of the proposed SEANN. Its performance was found to surpass that of BPN networks with various types of activation functions. Compared with the method described in the DNV manual, the proposed model provides better predictions of the ultimate soil resistance.
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