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

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@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

Citations