Master of Science
The existence of blockages in pipeline networks leads to serious issues that affect the efficiency of the infrastructure, losses of services and environmental risks. To these regards, this study proposes a technique to identify the pipes that are blocked within pipeline or a complex pipe network. This thesis focuses on detecting blockages by using a technique based on a few measurements that are usually gathered from normal operational conditions of the pipeline system. The same approach can be implemented in different fields of engineering to identify the damage, which it is the object of recent interest and development. Such technique can provide significant economic benefits especially for the gas and oil industries (i.e., this pipe blockage detection method leads to time and monetary savings compared to traditional inspection techniques which are more expensive). Long term blockages have the potential to cause permanent damage inside the pipes. To this respect, an optimization procedure that relies upon non-invasive measurements of the flow rate and pressure head, is used to assess the system functionality through Genetic Algorithms (GAs) that aim to solve this problem and perform the optimization procedure. The framework of this technique relies on both a Finite Element-like simulator and GAs to perform the optimization procedure. More investigations have been done experimentally and numerically in this study to determine the occlusions that occur inside looped or branched pipeline networks. The main contribution of the following study explores the validity, sensitivity and accuracy of such methodology by considering different blockage scenarios through two major parts: Part 1 (Experimental work) - A series of experiments were designed and performed by our team, involving myself and 7 more students from the civil and mechanical engineering departments under my supervision, in the span of 12 weeks to validate the robustness of the proposed technique empirically. The study was proven numerically by some researchers with real cases [Marzani et al., 2013 and Bocchini et al., 2014], while there has not been any research publicly available to validate this technique experimentally. For the first time, a comprehensive empirical study has examined the capability of this technique to identify the presence of blockages within different pipeline networks (evaluate the accuracy and the sensitivity). Several looped and branched networks by utilizing PVC pipes were tested throughout this study. The experimental data (flow in pipes and nodal pressure heads) acquired from the testing were analyzed and used to validate the proposed technique. Based on empirical data, it is evident that the technique could successfully identify the location of blockages inside the pipes with a reasonable degree of accuracy. More importantly, the proposed technique can cope even with missing measurements. Such technique is still a valid option for detecting the blockage in pipeline system, but with limitation in the accuracy based on several parameters (i.e., the structure of the network itself, the selected objective function and boundary conditions). Results, errors and conclusions are presented thereafter. Part 2 (Theoretical work) – Several numerical tests have been conducted to improve the technique by considering parametric studies. The theoretical work is focused on assessing the accuracy, robustness, computational efficiency and limits of applicability of the methodology. Many parameters are taken into consideration, such as friction factor (��), objective function (� (�)) and other design criteria (i.e., the input data) to observe its effect on the technique’s sensitivity. As a part of this study, strategies to improve the technique are investigated and summarized. Then, real cases are considered to evaluate the overall performance of the suggested technique. The results of blockage identification, advantages and disadvantages of the procedure for practical implementation are presented.
Khazaali, Mohanad Abdulzahra Ani, "Optimization Procedure to Identify Blockages in Pipeline Networks via non-invasive Technique based on Genetic Algorithms" (2017). Theses and Dissertations. 2660.