Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/15166
Title: Data analysis for improved risk assessment in underground pipelines
Authors: Anes-Arteche, Francisco
Advisors: Yu, K
Wang, B
Keywords: Pipeline corrosion;ECDA;Quantile regression;Data analysis;DCVG
Issue Date: 2017
Publisher: Brunel University London
Abstract: This thesis describes research relating to data analysis for improved risk assessment in buried pipelines. The kind of pipelines being considered includes onshore underground pipelines. External corrosion in buried pipelines is often complex to understand due to the diversity of factors affecting the corrosion process and in many cases, these pipelines operate in hostile environments. They may be less susceptible to failure and their failure may have different consequences in relation to aboveground pipelines. However, there is a limitation with respect what inspection techniques are efficient and therefore the assessment process is more difficult to be carried out. One of the major integrity risks to aging pipelines is the degradation and failure of the protective coating, leading to external corrosion. A commonly used approach for the assessment of external corrosion risk of buried pipelines is based on measurements from indirect inspections which are used to assess the likelihood of external corrosion. The underlying assumption is that indirect measurements can provide data to reliably identify corrosion defects on the pipeline, and prioritise defects according to their risk to pipeline integrity. One established method to determine the condition of the pipeline coating is to use an above-ground technique, such as DCVG, to locate the severity of the any coating defects, that may be present on a pipeline. Whilst the location aspect of this technique is very accurate and reliable, the severity may not correlate very well with the actual size of the coating defect when examined after excavation. Therefore, there is a need to refine the coating defect sizing model to provide a better indication of the severity of coating defects. However, there is little available research carried out to investigate this in a systematic manner. A further area of uncertainty relates to the correlation between the indirect inspection measurements, and the severity of the corrosion found following excavation. The development and refinement of regression models to address this link is required to ensure better corrosion predictions and improved inspection plans. The aim of the research described in this thesis is to analyse the external corrosion phenomenon in underground pipelines through the analysis of data from inspection reports and soil surveys. This aim has been achieved through specific studies at TWI, two of which are described in this thesis. The contribution to knowledge of the research included in this thesis is the improvement on the understanding of pipeline coating condition and external corrosion phenomenon in underground pipelines through the analysis of data from inspection reports and soil survey. Also, the identification of key factors affecting external corrosion along the probability distribution function, including factors that affect the initiation of corrosion and factors which have more importance in cases of severe corrosion. The novelty of the research herein presented relies in the application of quantile regression to pipeline data combined with soil properties which has never been applied before. The results improve the understanding of pipeline coating condition and external corrosion in underground pipelines. Also, it proposes suggestions for improving the interpretation of the NACE ECDA SP-0502 standard which may lead to significant savings in the pipeline industry.
Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London
URI: http://bura.brunel.ac.uk/handle/2438/15166
Appears in Collections:Dept of Mathematics Theses

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