Journal of Pipeline Systems Engineering and Practice

In this investigation, analyses of pressure fluctuations during oil and gas pipeline operations are performed. The analyses are performed in a way to capture all the variables of pressure fluctuations and their magnitudes in terms of crack growth rate. It is found that pipeline spectra can be categorized into three main types: underload-dominant, mean load-dominant, and overload-dominant spectra, depending on their locations with respect to a compressor or pump station. The underload spectra—typical of pressure fluctuations at the discharging sites—are the most severe in terms of crack growth as these spectra are subjected to the highest pressure level and the largest magnitude and frequency of pressure fluctuations. The underload spectra are further analyzed in terms of loading and unloading frequency, maximum stress-intensity factor, stress-intensity factor range, numbers of minor cycles between two adjacent underloads, and their potential for crack growth. Special attention is paid to the difference between oil and gas pipeline spectra. The frequency of pressure fluctuations is found to vary over a much wider range during oil pipeline operation than during gas pipeline operation, and the occurrence of crack growth contributing loading events is significantly more frequent in oil pipeline spectra than in gas pipeline spectra. It is recommended that the supervisory control and data acquisition (SCADA data) is recorded at a minute rate for gas pipelines and at a second rate for oil pipelines in order to capture most crack-growth-contributing events of pressure fluctuations during pipeline operation.

An image analysis–based method for retrieving high-resolution bathymetry data from historic pipeline inspection video is detailed. The resulting time-dependant bathymetric datasets are used to inform an improved understanding of pipe-soil and pipe-soil-fluid interaction. This allows better management of existing pipelines and improved design of new pipelines. The pipeline and seabed positions are extracted automatically from the survey video, spurious points removed, the data scaled, and interpolation applied. The data can then be projected in various forms, for different applications. Drawing on field data from Australia’s North West Shelf, applications of the method are described. For pipeline design, it is shown how improvements in on-bottom stability and changes in seabed friction can be quantified for mobile seabeds and through buckling sections of pipeline. This approach unlocks advances in existing design practice by providing quantification of the effects of seabed mobility. The processes and mechanisms that lead to through-life changes in pipeline embedment, soil support, and hydrodynamic shielding can be quantified, allowing design to move beyond the usual assumptions of a pipeline embedment that is invariant in time and space.

An experimental study was conducted to investigate selective removal of particles and shifting in particle-size distribution during a pipeline transportation of sediment deposits under turbulent flow of water. Presence of sediment deposits is encountered in various pipeline transportation operations (e.g., transport of oil, gas, oil sands, and slurry). Effectively removing solids from pipelines is an important part of the pipeline transportation-operation design process. Mechanisms of particle removal from sediment deposits in pipelines could vary depending on the particle size. Understanding how the transport mechanisms are related to particles sizes would help in designing better operational practices. Four different particle-size ranges were selected for experiments: (1) small particles ($d_p<60\mathrm{\mu m}$), (2) intermediate-size particles ($50\mathrm{\mu m}<d_p<150\mathrm{\mu m}$), (3) coarse particles ($d_p>150\mathrm{\mu m}$), and (4) poly-dispersed particles (mixed range). Experiments were performed at three different flow rates, all ensuring turbulent flow conditions, but velocities well below the critical velocity for particle removal (i.e., suspension from the bed). Samples from sediment deposits were taken during the transport experiments using custom-designed bottom extractors at different time intervals. The particle-size distributions (PSDs) of the samples were analyzed using an automated image analyzer equipped with specialized software. Results showed that interparticle attractive forces were dominant among small-size particles, which makes removal of smaller particles within the group more difficult; as a result, concentration of smaller particles within the group increased over the time. For intermediate-size particles, interparticle attractive forces became insignificant. With intermediate-size particles, the turbulent burst forces were able to lift the smaller particles within the group from the interface of the sediment deposits into the main flow. Consequently, the concentration of larger particles increased at the bed, whereas the concentration of the smaller particles, which can be lifted by the bursting force (velocity dependent), was reduced. For large-size particles, the hydrodynamic drag was the major force mobilizing the particles. The particles were moved by rolling, sliding, and saltation mode; therefore, the PSD for the large-sized particles stayed almost the same.

This paper presents a model for the integrated risk-based prioritization of municipal infrastructure assets. The model is a three-module decision-making tool for planning risk-based rehabilitation of water and sewer networks sharing the same corridor. The model is developed to identify corridor segments, assess risk of individual and integrated asset networks, and to set priorities for intervention plans of related critical corridor segments. The probability of failure of water pipe segments is calculated utilizing data from municipal inspection reports, while the probability of failure of sewer pipe segments is determined by soliciting experts’ opinions. The consequences of failure for individual water and sewer networks account for 13 economic, social, and environmental factors. Risk matrices are used to determine the criticality index of water and sewer segments depending on the combinations of probability and consequences of failure for each network measured on an ordinal scale. To integrate water and sewer indices, a novel dynamic weighting system is introduced to account for the varying impact of different pipe segments deterioration on the overall risk index. A case study from the metropolitan area of the city of Montreal in Canada is analyzed to illustrate the use of the developed model and highlight the essential features of its functions. The developed model is a well-structured decision support tool that utilizes input data commonly collected by municipalities. This model is expected to assist municipal engineers and decision makers to prioritize inspections, rehabilitation and replacement decisions, and optimize budget allocation and resource usage.

Underground asset locating practices use new and existing technologies to accurately identify, characterize, and map buried utilities through the integration of professional utility records, visual site inspection, geophysical techniques, survey, and utility exposure. The efficient use of locating practices allows effective condition assessment and renewal engineering applications, which, in turn, improves asset management practices for water utilities. Utility engineers, managers, and practitioners need to be familiar with all locating technologies (working principles, capabilities, and limitations) to have an effective selection of the appropriate technologies for every scenario. There are capabilities and limitations of all existing underground utility locating technologies that are used by water utilities. This paper provides the factors affecting the reliability of underground pipe locating surveys and presents an overview of the capabilities and limitations of the locating technologies to guide water pipeline infrastructure practitioners through literature. Application of underground utility locating technologies by water and wastewater utilities was investigated through case studies and phone interviews. Recommendations on ways to improve locating technology applications for water and wastewater utilities were made based on the literature and practice review.

The Guided Boring Method (GBM), also referred to as Pilot Tube Microtunneling (PTMT), is a widely used trenchless technology for pipeline installation with grade precision. However, PTMT is not applicable in nondisplaceable soils, where it is unable to install pilot tubes. In this context, this study introduces a Modified Guided Boring Method (MGBM) for pipeline installation in nondisplaceable soils. The guided boring is performed without the use of pilot tubes and coupled with hollow-center augers for target site path. This study presents the first pipeline installation project performed with the MGBM, and the case study results confirm that this technology can successfully install pipelines with grade precision in hard ground conditions. This study also assesses the MGBM’s economic performance using the project’s productivity and risk measurements, which can be used to facilitate budget and time estimates of future projects.

As a follow up to previous studies on numerical analysis of engineering systems, this paper utilizes Microsoft Excel Solver in solving pipe network analysis problems. Continuity and head loss equations were developed from three different pipe networks. Flow and head loss in the pipes were determined using Microsoft Excel Solver and Hardy Cross (standard) methods. These flows and head loss in the pipse were evaluated economically using operational cost and statistically [coefficient of determination (CD), total error, model of selection criterion (MSC), average error, and correlation coefficient (R)]. The study revealed that flow in pipes is a function of the method, withdrawal at the node, and length and diameter of the pipe. Statistical evaluation revealed that CD, total error, MSC, root error, and R were 0.041; 4.55; 0.041; 2.13; and 0.2025; and 1.0000; $2.25\times {10}^{-4}$; 29.647; $1.60\times {10}^{-7}$; and 1.000 for Microsoft Excel Solver and Hardy Cross methods, respectively. Economic evaluations showed that cost of head loss per hour and cost per person per day for these systems (for the two communities) were (1) US$999.44 and US$47.49; and (2) US$1219.85 and US$59.04 for Microsoft Excel Solver and Hardy Cross methods, respectively. It was concluded that the Microsoft Excel Solver method is a better choice than Hardy Cross method in pipe network analysis based on higher values of correlation coefficient, CD, and MSC coupled with lower values of total error and root error as well as higher economic value (lower cost of head loss per hour and lower cost of head loss per person per day).