Journal of Pipeline Systems Engineering and Practice

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.

The slurry pipeline system as the means of transportation is reviewed showing the process of transportation starting from the beneficiation of ore at the mine site to the dewatering stage at the process plant. A detailed analysis of the pipeline system for being the most cost-effective method of transportation in comparison with other modes of transportation like trucks, railway networks, barges, belt conveyors, and pneumatic pipeline systems was assessed. The parameters affecting the slurry flow behavior like solid concentration, the velocity of flow, pressure drop, particle size distribution, temperature, pH, different modal distributions, and additives were discussed along with their effects on the rheology. Developing a model that helps in estimating the flow behavior of high-concentration slurry has been a major concern over the years with the increasing need for transporting high-density throughput, and a few models evaluating the effects were developed in the literature and discussed here. To acquire a deeper understanding of the solid-liquid slurry flow, computational fluid dynamics is commonly used as a tool for simulating the parameters governing the motion of the flow. The solid concentration distribution, velocity profile distribution, and pressure drop as the dominant factors for estimating the flow behavior are studied, along with other parameters like skin friction coefficient, shear stress distribution, turbulent viscosity, and contours of different profiles. A comparative study of experimental and simulated results was also reviewed, measuring the randomness of asymmetry between measured and predicted data.

Conduits with noncircular (primarily egg-shaped and arched) cross sections were used widely in the past to improve flow conditions and reduce sedimentation, particularly in combined sewer systems, as shown in the literature. Rehabilitation of such noncircular pipes can be undertaken with flexible liners such as fiber reinforced polymer (FRP). A new finite-element analysis (FEA) based design method is proposed by the authors for anisotropic and flexible liners. The proposed computational model with three-dimensional FEA was validated by laboratory testing and compared to a design equation in the literature for flexible liners. The laboratory test was composed of parallel plate loading on a stand-alone, egg-shaped FRP liner sample based on ASTM D2412. The proposed FEA model was shell based with finer triangle element mesh control on singular points. The FEA model factored in the host pipe, liner, as well as the lined-pipe–soil interaction as the surrounding soil providing elastic support. The FEA results correlated with those of Thepot method and lab tests 99% and 83%, respectively. Upon validating the proposed FEA model, the method was further applied to a tunnel with a teardrop cross section and an arch-shaped large sewer. The results of the analysis performed suggest that the proposed computational method with the FEA, by utilizing the customized parameters described above, offered a practical means to overcome the complexities of using anisotropic and flexible liners in noncircular conduits. The lab test results on the egg-shaped FRP liner sample suggest both the Thepot method and the proposed FEA model were on the conservative side.

To analyze the mechanical behavior of the shield tunnel segment lining of underwater pipelines, based on the prototype segment structure practically applied in a project, a local model test of the combined shield segment considering front and rear ring staggered joints was designed. The internal forces and strains, joint opening and misalignment, and structural deflection change with the axial pressure ratio at different locations of the segment in the range of axial pressure ratio 0.02–0.54 were investigated, and the final failure form of the segment structure was also obtained. The experiment results show that in the assembly segments, the middle segment has the highest stiffness, followed by the side segments. When the segments are damaged, the maximum opening of the longitudinal joint is $1.75\mathrm{mm}$. Because the overall damage of the segments is earlier than the joint damage, it is suggested that the development of structural cracks, joint misalignment, and structural deflection be taken as the basis for evaluating the safety of tunnel segments. When the axial compression ratio is loaded above 0.50, top concrete crush damage occurred in the middle segment, while the concrete on both sides happened to incur an oblique 45° shear damage.

Abstract

Tunneling in urban environments is challenging due to the number of pipelines to cross, which may adversely impact the pipelines due to tunneling-induced ground settlement. An adequate vertical separation distance between the bottom of the pipeline and tunnel crown is not always possible, and a minimum volume loss may be difficult to achieve due to subsurface conditions encountered and tunneling methods available. Therefore, the impact to the existing pipelines from tunneling needs to be assessed to mitigate the risk. Considering gap formation beneath the existing pipeline explicitly and a limiting overburden loading acting on the pipeline, this study proposes a design-oriented analytical approach to estimate the upper bound of the maximum bending moment of the pipeline induced by tunneling. A dimensionless quantity, namely, the overburden loading factor defined as the ratio of overburden loading and the minimum required loading to eliminate the gap, is introduced to evaluate the extent of gapping, by which gap formation can be predicted. The effect of pipe-soil interaction, which reduces the maximum bending moment in the pipeline, is considered by conducting nonlinear Winkler-based finite element analyses with varying stiffness factors. The design chart and table are presented to provide a more accurate estimation of the maximum bending moment, especially for greater stiffness factors. It is demonstrated for small overburden loading and stiffness factors, i.e., wider gaps, a perpendicular crossing may not always be the worst-case scenario. As illustrated by the partially supported beam model, the effect of the increase in the unsupported span is greater than the effect of the reduction of the curvature of the settlement trough for these cases. Design examples are provided to demonstrate the analytical procedure step-by-step, and a comparison with previous studies is made. It is demonstrated with reasonable conservatism for small to moderate stiffness factors, the proposed design-oriented analytical approach can straightforwardly predict the maximum bending moment in pipelines.

Practical Applications

It is common to cross beneath an existing buried pipeline in the proximity for any tunneling project in urban areas due to the restrictions of underground space, soil conditions, right-of-way, and construction costs, etc. Considering gap formation beneath and an ultimate overburden loading on the existing pipeline, this study can be used to estimate the maximum bending moment in the existing pipeline due to ground settlement induced by tunneling, especially in the preliminary stage when the soil information is unavailable. The analytical procedure can be easily implemented by hand calculation or a spreadsheet, and more accurate results can be found with the aid of a chart and table provided when the soil information is available. The results obtained can assist the tunnel practitioners to determine an adequate separation distance, intersection angle, and an appropriate tunneling method to minimize the impact to the existing pipeline. Three detailed design examples are provided in the Appendix to illustrate the procedure step-by-step.

Abstract

Close examination of the parameters that characterize the spatial variability of the soil is necessary to understand how this variability can be used to study the structural behavior of buried large-diameter water transmission mains. In this research, a sensor-enabled geotextile was laid in a trench along a renewed water transmission pipeline segment to measure the ground strain during its installation and the first months of pipeline operation. A methodological approach was developed to identify, from experimental semivariograms built from ground strain measurement profiles, the scale of fluctuation that characterizes the horizontal spatial structure of the soil. Using both an experimental onsite test and a numerical model of the pipeline, the spatial variability was assumed to correspond to the soil modulus parameter in the model. The numerical results were well matched with the experimental test measurements. Both parameters, the scale of fluctuation and the soil modulus, were identified as important factors for understanding the spatial behavior of the soil–pipe system.

Practical Applications

Soil heterogeneity affects the structural response of a buried pipe with respect to force redistribution and structural displacement, and its influence appears mainly in the longitudinal direction. This heterogeneity results in the spatial variability of soil properties. Furthermore, the geomechanical behavior of buried pipes is subject to random uncertainties. In the framework of this study, the uncertain variables are treated by the theory of probabilities. Such an approach can be integrated into the context of asset management of a network of water transmission pipes. Thus, wishing optimized management of a network, the project manager needs a tool allowing him to evaluate the geomechanical performance of the pipes and to see if it is necessary to proceed to a follow-up in terms of inspection, maintenance, or renewal. This study showed that both soil modulus and the horizontal correlation length parameter of soil properties could characterize the spatial variability of a pipe site. By integrating these parameters into a numerical tool, a manager can incorporate spatial variability in a simple way while maintaining full control over their variability.

Burst pressure is an essential parameter to measure the residual bearing capacity of pipelines with corrosion defects. Accurate prediction of burst pressure is beneficial to evaluate the remaining life of pipelines. The traditional estimation formulas mainly focus on single-point corrosion but seldom consider the case of multipoint corrosion. Although DNV-RP-F101 considers multipoint corrosion, this method only considers the influence of axial spacing of adjacent corrosion defects on burst pressure but does not consider the influence of circumferential spacing. This work refers to the pipe corrosion criterion (PCORRC) and DNV-RP-F101 methods and modifies the calculation formula of the PCORRC method by introducing ($D-t$). The average relative error is only 11.46%, which is 27.65% lower than the previous formula. In addition, this paper presents a method for estimating the burst pressure of pipelines with multipoint corrosion defects. This method considers not only the axial spacing between defects but also the circumferential spacing. The results show that the maximum relative error is 6.52%. A machine learning modeling framework for predicting burst pressure in multipoint corroded pipelines is proposed. The case using radial basis function neural network as the prediction tool shows that the average Pearson correlation coefficient of the prediction results in the test set is 0.903, indicating that the prediction performance is good.

Marston’s theory is typically used to predict earth loads acting on culverts installed in negative projecting trenches. This theory assumes that trench walls are vertical; however, many excavations are done with sloping walls for constructability and safety. In this study, the effect of trench geometry on the loading conditions of negative projecting box culverts was evaluated. Centrifuge testing and numerical modeling was performed to evaluate the influence of trench wall angle, trench depth, and trench width on the vertical and horizontal earth pressures exerted on the box culvert. Sixteen model geometries were evaluated, and the experimental and numerical results are shown to be in reasonably good agreement. It was found that Marston’s theory is appropriate for negative projecting culverts constructed in trenches with vertical sidewalls; such an approach is conservative and overestimated the vertical loading conditions by approximately 15%. However, for configurations with inclined trench walls, it was found that the culvert loading was increased considerably and Marston’s theory was not appropriate. Very little positive arching and load reduction was realized when such culverts were installed in trenches with sloped walls. It is recommended that numerical modeling be performed during design of negative projecting culverts constructed with sloped sidewalls, or that positive projecting conditions be assumed to ensure that design loads are conservative.

Pipeline condition assessment is a cost-effective method to determine the status of pipeline structure and predict failure probability. Although 100% inspection may not be feasible for decision makers, recent advancements in machine learning techniques have enabled more effective pipeline condition assessment. This paper provides a comprehensive review of machine learning applications in pipeline condition assessment, covering aspects such as fault diagnosis, risk prediction, parameter prediction, and visual defect recognition. The present study endeavors to make the following contributions: (1) extraction of the model, data size, and other relevant information from 91 papers, (2) in-depth analysis of the state of the art and frameworks of the models discussed in the 91 papers, (3) summary of the data characteristics, input variables, and accuracy of machine learning models, and (4) exploration of the potential avenues for future research in the use of machine learning for pipeline condition assessment. This review aims to serve as a practical reference for scholars engaged in related research. The review highlights the fact that the majority of the models employed in pipeline condition assessment are original, and the utilization of hybrid models remains limited. Transfer learning and reinforcement learning are identified as potential avenues for future research because they hold promise in facilitating the adaptive selection of model inputs and the transfer of models to similar projects. Furthermore, breaking down data barriers is deemed essential for advancing the use of machine learning in pipeline condition assessment.

Abstract

To address the low-efficiency issue of the manual assessment method for sewer pipe defects, we propose a defect severity assessment model based on automated pipe calibration (DSA-APC), which can provide automated and quantitative assessments. First, the cross-section feature is extracted by automated pipe calibration. A pipe cross-section feature extraction algorithm based on restricted Hough gradient transform (RHGT) is proposed. Then, a fine-defect feature extraction method based on edge detection is proposed to extract the features of pipe defects more finely. Finally, according to the assessment standards of the sewer pipe defect, a defect severity assessment table is constructed, and the area ratio of the defect feature and cross-section feature is used to evaluate the severity. Experiments are carried out on the Songbai data set and Level-sewer10 data set. The average absolute deviation of the DSA-APC model is 2.008%, and the average accuracy is 86.73%. The experimental results show that the DSA-APC model can correctly evaluate the severity level of sewer pipe defects, which has a good practical application value.

Practical Applications

A defect severity assessment model is proposed to provide automated and quantitative assessments of the severity of sewer pipeline defects. The model uses deep learning and image processing methods to process the video and images collected from investigation robots to obtain assessment results for each pipeline. Experimenting on a real data set, the model achieved an evaluation accuracy of 86.73%. The model can automatically evaluate the defect level of the pipeline and achieve a competitive performance compared with manual evaluation. The technologies chosen for the model are practical and have been appropriately adapted and improved for the actual sewer pipeline systems, making the model both efficient and practical. The pipeline maintenance manager is able to use the model to assess and analyze the health condition of the pipeline system and develop appropriate repair plans for pipeline system problems. Although this study is specific to sewer pipeline assessment, its findings have implications for all other pipeline systems. As a new attempt, our assessment model of pipelines from a visual perspective is simple and efficient. We think that our model will have many practical applications in the field of pipeline systems.

In urban blasting engineering, researching the dynamic response of buried pipeline is a method for evaluating the stability of the pipeline. The dynamic response of buried pipeline under blasting includes peak particle velocity (PPV) and peak effective stress (PES) on the pipeline. This paper aims to analyze the dynamic response of the concrete pipeline with bell-and-spigot joints under a metro-connected aisle blasting, and provide a PPV safety criterion for evaluating the stability of the field concrete pipeline. This includes an analysis of the dynamic response of the concrete pipeline in the field monitoring and numerical simulation. The monitoring results reveal that the PPV is affected by the field factor, such as the explosion source distance, and it is noteworthy that the Sadovsky’s formula considering the influence of explosion source distance (data correlation coefficient—0.708) has higher accuracy in predicting the PPV compared to the original Sadovsky’s formula (data correlation coefficient—0.632). The dynamic response distribution characteristics of the concrete pipeline are analyzed based on the numerical simulation, and the results show that the PES of the joint is three times stronger than that of the barrel. A PPV safety criterion ($1.43\mathrm{cm}/\mathrm{s}$) is provided for the site to evaluate the stability of the concrete pipeline according to the dynamic response of the pipeline joint.

Indonesia was the eighth largest exporter of liquefied natural gas in 2021, with a total export volume of $14.6\mathrm{billion}{\mathrm{m}}^3$. Therefore, transporting natural gas becomes an essential program to support the increase of liquefied natural gas. Through the Cooperation Contract Contractors (CCC), a cooperation contract between government of Indonesia (GoI) and Oil Company, the government appoints the engineering, procurement, and construction (EPC) contractor to build the pipeline. However, EPC contractors are at significant risk in calculating contingency costs resulting in cost overruns. This study identified contingency risk factors, determined the most effective risks, and developed contingency costs for EPC pipeline projects. A literature review was conducted, a probability matrix for risk ranks was developed, and Monte Carlo simulation was used. The results indicated that there are risk factors significantly influencing the calculation of contingency costs for EPC pipeline projects, namely changes in the scope of work, delays in permits from the government or regulatory authorities, issues with local communities and the project environment, delays in the construction work, and the material delivery of long-lead items. Based on these factors, the contingency cost risk in a pipeline EPC project determined using Monte Carlo simulation was 14.87%. Before utilizing risk modeling, an efficiency of 4.23%, or a cost savings of $3,323,064.71, was achieved. For future research, it would be preferable to simulate more than three sample EPC projects to analyze variances in contingency costs.

The pipe component of a water distribution network (WDN) is sized based on the fixed design demand considering a peak factor and design period. Simulation of the designed network by a hydraulic solver provides nodal pressure head, head loss, velocity, and flow in each pipe as the prime outputs for the design demand, and it can also be used for extended-period simulation for a particular demand pattern over the supply hours. But, in reality, the behavior of the network does not match with such a result in an intermittent water supply (IWS) system due to the fact that all house service connections behave as an uncontrolled orifice. This has made it a challenging task in understanding and in predicting the behavior of the networks by the municipal engineer once the water starts flowing through the house service connections (HSCs). Though the municipal engineer provides the same pipe size for HSCs to all residences, the flow received by each house could vary based on the available pressure head at the ferrule point of the main water supply pipeline. In reality, maintaining constant pressure at each HSC is not feasible due to frictional head loss. Hence, variation in flow at the HSC is inevitable even with a small water supply system. This paper illustrates how to simulate the behavior of an IWS system based on the number of HSCs provided to each pipeline using a hydraulic solver. Hydraulic simulation of the water distribution network that provides IWS to consumers can be implemented easily by adding a fictitious node by assigning an appropriate emitter coefficient to each demand node through a fictitious link having a check valve in it. The method for finding the appropriate value of the emitter coefficient that helps in simulating HSCs is illustrated in the present work.