Influence of the design parameters on the stress state of saddle-supported pipelines: an artificial neural network approach

Abstract

A neural network methodology is herein applied to numerically treat the sensitivity analysis problem of above-ground pipelines under static loading by taking into account the possibility of development of uplifting phenomena at the pipe–saddle interfaces. Assuming classical frictionless unilateral contact to mathematically describe the pipeline support conditions coupled by an appropriate finite element scheme, the discrete problem is put in the form of an inequality constrained quadratic optimization problem with respect to either displacements or stresses. In order to investigate the structural response and the stress states of the above-ground pipeline at hand with respect to the variation of critical design parameters which are the pipe thickness and the support conditions, the sensitivity analysis problem is formulated as a quadratic programming problem with the design parameters appearing in the quadratic term. The feasibility of using appropriately designed neural networks to model the complicated nonlinear relationship between the several input parameters associated with above-ground pipelines and their support conditions is thus demonstrated.