Modelling of upheaval buckling of offshore pipeline buried in clay soil using genetic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @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