Spatio-temporal reliability analysis of pipeline

Aryai, V 2019, Spatio-temporal reliability analysis of pipeline, Doctor of Philosophy (PhD), Engineering, RMIT University.

Document type: Thesis
Collection: Theses

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Title Spatio-temporal reliability analysis of pipeline
Author(s) Aryai, V
Year 2019
Abstract It is essential for infrastructure managers to predict the remaining service life of buried pipelines since their structural failure impact the social, environmental and financial aspects of the country. Corrosion is known to be one of the major contributors to the failure of pipeline. Reliability analysis methods are widely used for predicting the future structural integrity of pipeline subjected to corrosion. Incorporating the realistic corrosion modelling techniques based on the random-field theory into the reliability analysis methods enables spatio-temporal reliability assessment of corroding pipes. Implementation of spatio-temporal reliability analysis methods, however, requires calibration of the correlation structure that exists over the geometry of the pipe corroding surface with the real data. It has been shown that, incorporating the finite element models of corroding surfaces into the spatio-temporal reliability analysis methods provides with a comprehensive structural integrity assessment of corrosion affected structures. The existing models for corroding surfaces, however, do not consider both the spatial and temporal variations of corrosion altogether. Throughout the literature, the reliability of interconnected pipes is studied through the structural system reliability concept. It has been shown that the matrix-based system reliability (MSR) outperforms other methods due to its unique features. To account for the correlation between components, the MSR requires fitting a Dunnett-Sobel class (DS-class) correlation matrix to the general correlation coefficient matrix which can be a challenging task, especially for a large number of common source random variables.

In this research a semi-empirical time-dependent correlation length model is proposed to model the evolutions of the correlation structure of the pipe corroding surface over time. The model is developed based on the data collected from failed cast-iron water pipes buried in Melbourne suburbs. Moreover, this research proposes a FEM-based spatio-temporal reliability analysis method based on copulas and gamma process. The method is fed with the developed correlation length model to provide an ever-realistic framework for spatio-temporal reliability analysis of corroding pipes in the component level. As for the system reliability analysis, the research proposes a copula-based MSR that eliminates the need for DS-class matrix fitting. The results show that the proposed method is not only more accurate than the traditional method, but it is easier to set-up.

Finally, as a case study, this research shows the application of the proposed methodology for reliability analysis of a pipeline network with unknown failure history. The result enables for ranking the pipe segments based on the predicted time of failure and, therefore, finding the location and time of failure in a buried pipeline network with unavailable failure history. Moreover, the results indicate the necessity of the corrosion correlation structure calibration when attempting to spatio-temporal reliability analysis in both the component and the system level. The results of the proposed methodology allow asset managers to plan an accurate maintenance strategy for the pipeline. The maintenance strategies are mainly involved in finding a balance between the probability of failure and the cost of reducing the risk. Therefore, an optimal maintenance strategy can be obtained using the probability of failure estimation from the proposed method in this research and cost information which is determined by stakeholders.
Degree Doctor of Philosophy (PhD)
Institution RMIT University
School, Department or Centre Engineering
Subjects Stochastic Analysis and Modelling
Infrastructure Engineering and Asset Management
Structural Engineering
Keyword(s) Reliability Analysis
System Reliability
Service-life prediction
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Created: Wed, 05 Jun 2019, 14:04:48 EST by Adam Rivett
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