Development of a burst pressure prediction model for flawless and dented pipelines

  • Dohan Oh

Student thesis: Doctoral Thesis


Accurate prediction of the burst pressure of a pipeline is critical for pipeline design and safe operation. There are a number of analytical and empirical formulae derived from theoretical, numerical and experimental methods that can be used to predict the burst pressure of plain pipeline. However, there is not an equivalent method available to predict the burst pressure of dented pipeline and consequently the assessment of dents in pipelines is based on the depth or the shape of the dent. Therefore, this thesis presents the development of practical burst pressure prediction models for the flawless pipelines, which is then extended to predict the burst pressure of dented pipeline. Firstly, a study is carried out to develop a new methodology to predict the burst pressure for API 5L X-grade flawless pipelines using Finite Element Analysis (FEA). The FEA is performed using a bilinear material model with the tangent modulus calculated using the strain at Ultimate Tensile Strength (UTS). A new formula has been developed in this work to calculate the strain at UTS based on API 5L X-grade material coupon test data. A comprehensive nonlinear FEA based Parametric Study has then been conducted with this bilinear material model to derive an empirical formula for estimating the burst pressure of API 5L X grade flawless pipelines. Secondly, an empirical formula for the assessment of the structural integrity of a pipeline with an unconstrained, hemispherical, plain dent has been developed, based on the formula derived for the unflawed pipeline. Parametric studies have been conducted using non-linear FEA of the burst pressure for API 5L X52, X65 and X80 grade pipelines with a dent. An empirical formula, that can predict the burst pressure of dented pipelines is proposed, based on the output dataset derived from the FEA based Parametric Study results. Thirdly, a dent produced by a spheroidal indenter on API 5L X52 pipeline has been studied to investigate the effect of the longitudinal and transverse dent lengths on the pipeline structural integrity using FEA. According to the FEA based Parametric Study results, it shows that the burst pressure prediction for the spheroidal dent is comparable with the burst pressure prediction for the hemispherical dent for a given dent depth and longitudinal dent length. Consequently, it is confirmed that the proposed burst pressure prediction formula for the hemispherical dent is applicable to examine the structural integrity of API 5L X52 grade pipelines with an unconstrained, spheroidal, plain dent. Finally, the applicability of machine learning techniques such as Deep Neural Networks (DNN) for the prediction of burst pressure has been investigated for unflawed and dented API 5L X-grade pipelines. The burst pressure derived has been compared with the results of FEA based Parametric Study and the experimental test results and showed good agreement. Therefore, it is concluded that DNN can be another solution for predicting the burst pressure of API 5L X-grade flawless and dented pipelines.
Date of Award23 Jun 2020
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SponsorsUniversity of Strathclyde
SupervisorJulia Race (Supervisor) & Selda Oterkus (Supervisor)

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