Modelling of upheaval buckling of offshore pipeline buried in clay soil using genetic programming

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@Article{Nazari:2015:ES,

• author = "Ali Nazari and Pathmanathan Rajeev and Jay G. Sanjayan",
• title = "Modelling of upheaval buckling of offshore pipeline buried in clay soil using genetic programming",
• journal = "Engineering Structures",
• volume = "101",
• pages = "306--317",
• year = "2015",
• ISSN = "0141-0296",
• DOI = "doi:10.1016/j.engstruct.2015.07.013",
• URL = "http://www.sciencedirect.com/science/article/pii/S0141029615004563",
• abstract = "Offshore pipeline is generally recognised to be the safest and most economical way to transport oil and gas. These pipelines are operated in elevated temperatures and pressures those are much higher than the ambient conditions. That will causes axial expansion in the pipeline, if such expansion is restrained by soil friction, the compressive force will be built up in the pipe, finally, induces the buried pipeline to buckle in the vertical plane. This paper investigates the effect of uncertainty in soil, operating condition and pipe properties on upheaval buckling behaviour of offshore pipeline buried in clayey soil. To simulate the upheaval buckling, a 2-D finite element model of 500 m long pipeline-seabed soil system was developed in OpenSEES using the thermal element. Using the finite element model prediction of upheaval buckling height, a total number of 12 upheaval buckling height prediction models were proposed by using genetic programming with varying levels of complexity and accuracy. To achieve the best performance model, a scoring table was proposed considering several factors including coefficient of determination, sum of errors, difference between training and testing errors, sum of residuals, deviation of predicted results from experimental one and complexity and generality of the models. Finally, the effect of each parameter on upheaval buckling displacement was studied by parametric analysis and the results were compared by simulated ones. On the basis of the results, most of the models developed using genetic programming show very good prediction with the numerical results. The developed model can be used to improve the design and upheaval bucking risk assessment of buried pipeline.",
• keywords = "genetic algorithms, genetic programming, Offshore pipeline, Upheaval buckling, Finite element",

}

Genetic Programming entries for Ali Nazari Pathmanathan Rajeev Jay G Sanjayan

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