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This paper presents a probabilistic method to assess the lateral buckling response of a pipeline. The method is based on a Monte Carlo (MC) simulation in which the lateral buckling response is predicted through the use of a surrogate model that employs artificial neural networks (ANNs) calibrated from nonlinear finite element (FE) analyses. The method presented intends to improve on current industry best practice by directly considering the limit states relevant to global buckling to produce designs with consistent levels of reliability.
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Sicilia et al. (2015) studied this question.
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