Pipelines 2023: Condition Assessment, Utility Engineering, Surveying, and Multidiscipline

Pipeline inspection data can be used to estimate a pipeline’s remaining useful life (RUL) for more improved long-term asset management strategies. With a high-confidence RUL estimation, asset deterioration projections can match the pipeline condition over time. However, RUL estimates based on first-time inspection data carry a high level of uncertainty. This is because an inspection offers a snapshot understanding of the pipeline’s condition at the time of inspection. Degradation patterns from a pipeline’s installation up to the first condition assessment can be uncertain as the degradation initiation time is difficult to pinpoint or unknown, affecting the estimated degradation rate. The uncertainty of RUL estimates decreases with multiple pipeline inspections over regular intervals. Degradation is tracked over shorter time periods enabling a better estimate of the degradation rate. As such, the predicted and actual conditions of the pipe are more closely aligned. This provides a higher level of confidence for decision-makers and stakeholders who rely on the predicted estimates of pipeline deterioration for making informed capital project planning decisions. This paper presents a case study showing how repeated pipeline inspection data can improve a predictive model—decreasing the uncertainty of the predicted deterioration rate and improving the accuracy of the RUL forecasts.

In 2003, the Middlesex County Utilities Authority (MCUA) implemented an asset management program to manage its most critical underground asset—the 102-in. prestressed concrete cylinder pipe (PCCP) Sayreville Relief Force Main (SRFM)—following two failures that occurred within the first 21 years of the force main being commissioned. At the heart of the program is the acoustic fiber optic (AFO) monitoring of the individual pipe sticks in the SRFM, which provides accurate and reliable real-time monitoring and alerts of the wire wrap breaks as they occur. The AFO monitoring data is accessed through a GIS-based web-portal. The AFO monitoring system has proven to be a powerful tool, allowing for live monitoring of the SRFM, tracking of historical data and repairs, and identifying broken wire wrap activity of interest that helps identify when pipes need repair. Additionally, the SRFM is inspected on a routine basis using visual and sounding techniques and electromagnetic technology. To determine the structural consequence of the broken wire wraps, structural analysis was performed using the American Water Works Association (AWWA) standards and nonlinear, three-dimensional finite element analysis (FEA). These analyses determine the pipe repair intervention limits. Since 2003, the MCUA has used the program to implement proactive, fully structural repairs on 41 pipes in the SRFM. As the world’s only known wastewater AFO monitoring system, the MCUA has been at the forefront of current PCCP management strategies. In combination with a robust inspection program, the MCUA has been able to anticipate pipes requiring intervention, thus preventing another catastrophic failure.

In wastewater systems, the pipe’s probability of failure (POF) and consequence of failure (COF) must be determined as part of a risk-based decision framework. By identifying the POF and COF, decision-makers can make a more informed decision about current and future rehabilitation and replacement project planning. In this study, a new risk assessment model is developed using continuous-time Markov chain (CTMC) for computing the probability of failure and the weighted average along with the weighted rating method to find the consequences of failure. Finally, the model was applied to a northeastern Louisiana wastewater network as a case study. The results showed the POF of the pipe for the next 200 years and corrosion, soil type, and waste type are the main consequences involving more costs of failure 40% of pipes need moderate to high costs, and 7% of pipes need high costs. Unfortunately, the developed model could not be validated because of insufficient data.

North Texas Municipal Water District (NTMWD) provides treated water for over 2 million people in 80 communities through a system that includes nearly 700 mi of transmission mains. Reliable operation of these transmission mains requires proactive management; therefore, NTMWD developed a risk-based linear asset management plan that allows them to make informed decisions regarding budgeting and scheduling for maintenance and repairs. This paper presents NTMWD’s approach to developing their linear asset management plan, including outlining the agency’s goals, developing a framework, gathering data, and preliminary implementation results.

Bar-wrapped concrete cylinder pipe (BWCCP) is a semi-rigid pressure pipe designed as a composite structure combining the tensile strength of steel with the compressive strength and corrosion-inhibiting properties of Portland cement mortar. As with any infrastructure component, BWCCP water mains are prone to deterioration due to aging and other influencing factors. Hence, developing a performance curve is a must to ensure proactive asset management is implemented. Although the prestressed concrete cylinder pipe (PCCP) and BWCCP both belong to the buried concrete pipes category, unlike PCCP, the steel cylinder and the reinforcement bars in the BWCCP composite undergo identical strains governed by common elastic modulus. Once the steel cylinder yields and reaches its ultimate plastic region, the pipe will fail. Therefore, correlating the adopted structural limit states for PCCP in AWWA C304 (serviceability, yield, and strength limit states) to the BWCCP performance under tension conditions may not adequately represent the pipe’s mechanical behavior. Instead, the BWCCP performance curve will adopt the residual factor of safety approach initially to estimate the BWCCP composite behavior under tension conditions. As this paper provides a methodology to assess BWCCP’s distress status in terms of residual factor of safety, pipes with low factor of safety can be identified, and decision-makers are able to allocate municipal renewal budgets to avoid catastrophic failure of BWCCP assets.

Following a high-consequence failure of a pipeline at a major freeway crossing experienced by another city in Arizona in 2022, the city of Mesa prioritized inspection of its high-consequence-of-failure AWWA C303 Bar-Wrapped Steel-Cylinder type concrete pressure pipelines (BWP) with a technology that can provide high enough resolution with actionable results. Based on the recent advances and increased track record of electromagnetic inspection, proprietary tools offered by PICA were incorporated into a visual and sounding inspection project to pilot the electromagnetic tools in about 1.7 mi of 30 in. diameter and 1 mi of 36 in. diameter BWP. The project included not only inspection of buried pipelines with unknown condition but also blind inspection of aboveground test pipes with hidden defects in the steel cylinder and reinforcing bars as well as subsequent field verification of defects that the tools identified in the buried pipelines. Field verifications included internal person-entry inspections and local external inspections in selected excavated areas as needed. This paper presents the findings from these inspections with particular emphasis on the field verification of results and discusses the effectiveness of the utilized condition assessment approach in assisting the city in its asset management program.

The Great Lake Water Authority (GLWA) owns and operates a 1,700 million gallons per day (MGD) water resource recovery facility (WRRF). As one of the largest single WRRF sites in the US, it has a complex yard piping network of gravity, pressurized pipes, and electrical systems. To support its ongoing asset management program, GLWA commissioned the implementation of a multi-step approach to address their needs for locating and creating a reliable geographical database of these assets. All collected data is stored in georeferenced 3D and 2D models and associated databases. Main attributes, such as pipe size, material, age, and construction project, were stored in the 3D model database to better fit planning and design project needs. A more accessible and lighter 2D GIS model of the system was developed for the day-to-day operation and decision-making processes, including critical features such as operating pressure, valve opening direction, photos, and ownership. These georeferenced models and data sets help the facility owner, consultants, and contractors better understand the system; plan accurately; track condition reliably; and improve site safety. This paper covers the multi-step process of collecting, organizing, and validating information, along with challenges encountered and best practices implemented.

Smart water technologies such as electromagnetic pipe inspection and online pipe monitoring are changing pipe maintenance in water utilities. The paper presents their application in a digital twin to improve asset management based on the challenge faced by the Tarragona Water Consortium (CAT) after experiencing a catastrophic failure on its main pipeline. An initial inspection with electromagnetic technology detected 35 pipes out of 13,188 with different degree of damage. Eight of them had high risk of failure and were replaced. Digital twin online pipe monitoring added 20 alarm events in six months and identified a high-risk area that is being by-passed with a new pipe. This highlights the importance of online monitoring for accurate calculation of remaining life of installed pipes to enable advanced planning and risk management. Use of gathered information leads to safe operation and increased reliability, key outcomes for water utilities as they provide a public service.

Water main breaks are a common phenomenon in cities; they disrupt water distribution to homes and businesses. The buried water infrastructure is typically installed underneath streets and roadways whereby any water pipe breaks result in the disruption of traffic and interruption to businesses in the immediate vicinity of the breaks. The main objective of this study was to determine the main factors that cause water main breaks in the city of Dallas. Linear regression method was used to analyze the main water breaks data collected from water distribution operations. The age of the pipe, as well as the minimum and maximum pipe diameters, was the independent variable in this study. The water break index was the dependent variable. The study revealed and verified that the water break index increased by age of the pipe. The size of water mains had a negative relationship with the water break index. The practical implication of this study is that the results of this study can be used in decision-making on which pipe segments should be repaired, rehabilitated, and/or replaced prior to the end of their useful design life.

Plastic pipe material is increasingly used for several applications including water, sewer, and gas applications. Plastic pipelines currently in service are generally not as old as the metallic pipelines, but there have been many seemingly premature failures warranting a comprehensive understanding of their failure mechanisms and how to keep track of them for appropriate intervention. This study provides a comprehensive review of the deterioration mechanisms for plastic pipelines informed by the state-of-the-art literature. There have been numerous papers published on various aspects of plastic pipe degradation in multiple utility sectors, and this proposed paper synthesizes the most crucial knowledge out there into a single paper for practical reference. Various material, design, installation, operational, and maintenance-related factors could affect premature failure of plastic pipelines. All such factors are highlighted in this paper. This paper is useful for utility owners and consultants dealing with any kind of plastic pipelines.

The majority of cast iron pipelines were installed in the United States in the early to mid-20th century. Most of these pipes are in a sustainable working condition; however, any failure of these pipelines could be catastrophic due to the social, political, and environmental impacts of the failure. Utility engineers have reported failures on large diameter cast iron pipes that occurred suddenly and without warning, with no signs of prior damage, cracks, leaks, and no visual evidence of corrosion on the fracture surfaces. To facilitate better decision making for capital expenditures and to address the risk associated with these assets, the fatigue failure mechanisms of cast iron pipe must be understood. In addition, for planning and capital budgeting, it is important to determine the current condition of a deteriorated pipeline and its risk of failure due to cyclic loading. In this study, structural analysis of fatigue failures for buried cast iron pipes is performed. This paper explores the level of stress on corroded pits and crack growth when subjected to internal fatigue loading such as operating pressure variations and transient pressure events. Computational modeling is utilized to inform utility owners that there is a threshold for size of initial crack and number of cycles that significantly change level of stress for cast iron pipes. It is very important to know that number of cycles before any failure happens. This will provide decision makers and utility owners a tool to enhance their asset management strategy based on inspection results combined with advanced computational fatigue modeling.

Acoustic methods of condition monitoring of pressurized fluid-filled pipes are very popular but often fail to find the location and to estimate the severity of a small pipe wall defect or a leak. An accelerometer attached to the outside wall of a pipe or hydrophone inserted in the pipe is commonly used to detect a leak in a pressurized fluid-filled pipe or estimate the pipe condition from its acoustic response. In many cases these devices are not sufficiently sensitive for the purpose because of the complexity of the buried pipe network or high attenuation of acoustic waves in it. This work demonstrates that a new type of sensor that measures simultaneously the acoustic pressure and velocity in the acoustic wave propagated in a pipe can offer a considerable improvement in terms of sensitivity and accuracy of this condition assessment method. The performance of this sensor is evaluated through numerical simulation and tested in a laboratory on a 60 m long MDPE pipe loop to detect very small leaks that existing sensing methods would struggle to detect. This device is built of off-the-shelf components and can be adapted for delivery through existing pipe entry points. In the future it could be deployed on a robot to make the condition monitoring process fully autonomous and 10−50 mm accurate.

The village of Ruidoso is a small community nestled in the mountains of Lincoln County, New Mexico, with an estimated 326 mi of water distribution lines. In FY 2020, the village produced approximately 622 MG for the year, of which only 316 MG was authorized consumption from the village’s operations and 7,525 active connections. With approximately 52.1% of water being classified as non-revenue, it was evident that there were a substantial number of undetected leaks within the system. Because of this, the village solicited proposals for leak detection services. In December 2021, Wachs Water Services entered a contract with the village of Ruidoso to conduct a system-wide leak detection survey with the primary goals of locating distribution system leaks using conventional leak detection methods and collecting the global position system (GPS) coordinates of each asset. This white paper and subsequent presentation will reveal the many challenges faced by Wachs crews, including undocumented water mains and valves discovered while surveying the system. Furthermore, this paper will reveal the savings to the villager and return on investment for the first year of its 10-year leak detection program.

A significant amount of treated drinking water is lost through leakage in water distribution systems across the globe. Conventional leakage detection techniques are ad-hoc in nature and expensive for system-wide leakage detection and severity assessment. Advanced metering infrastructure (AMI) and cyber monitoring technologies enable the collection of valuable data that could reveal pipeline conditions. This paper presents a model-based technique that leverages AMI consumption data and pressure data from large-scale distribution networks to infer leakage presence and approximate severity. Pipe roughness, effective hydraulic diameters, and leak presence and severity are considered as the unknown dynamic parameters in this study based on a Monte Carlo engine in MATLAB. For inferring the leakage presence, pipe roughness and effective hydraulic diameters are considered as stochastic variables following a certain probabilistic distribution. A neural network model is developed to predict emitter coefficients as leakage surrogate measures for all the pipelines in the distribution system’s considered pressure zone based on consumption data derived from the AMI meters and pressure data derived from the entire distribution system. The approach is demonstrated on a large-scale (>1,000 pipelines) water distribution network to evaluate the computational challenges along with the potential solutions. This study could benefit water utilities that have already installed or plan to install AMI meters.

Several physical, environmental, and operational factors contribute to the deterioration of wastewater pipelines during their service lives. Failure of this critical infrastructure would have repercussions on the economy, society, and the environment. Assessing sewers is most commonly performed by the use of closed-circuit television (CCTV) that helps in gaining knowledge of the structural and operational state of the pipelines. Identifying pipelines to be inspected annually is considered a main step toward a successful and cost-effective CCTV program. Generally, the initial process follows a desktop risk management approach that combines the condition of sewers and its criticality that cluster pipelines in short-, medium-, and long-term inspection intervals. Predicting sewers’ conditions would help select critical sewers that are most likely to fail, where these sewers will be prioritized for CCTV inspections to discern their conditions and plan for required restorations, if needed. Accordingly, the current study employs data mining algorithms, specifically Extreme Gradient Boosting (xgboost) and logistic regression (LR), to predict each pipeline’s condition based on the Pipelines Assessment Certification Program (PACP) and Water Research Centre (WRc) ratings. The models are implemented on the city of Hamilton sewer network that consists of combined and separate systems. This study attempted to address the prevalent class imbalance in pipe inspection data sets by employing a diverse range of hyperparameters. Overall, XGBoost produced more satisfying results while still falling short of acceptable average performance. Finally, the results were imported into ArcGIS to better depict the expected sewer condition. Comparing these algorithms shows that these techniques can be further improved by utilizing additional data sets collected from various municipalities across North America.

Water pipelines are crucial components of water supply systems that safely supply water produced by water purification plants to consumers. Metal pipelines deteriorate over time owing to various physical, environmental, and operational factors; in particular, corrosion occurs inside and outside the pipelines due to the characteristics of the pipeline material. In this study, models were developed using machine-learning algorithms to predict internal and external corrosion depth. The hyperparameters of each model were determined through Bayesian optimization, and model training, validation, and prediction were performed. The proposed machine-learning techniques for predicting the corrosion depth of water pipelines can overcome current limitations, such as the prediction of deterioration and residual life of water pipelines and the selection of the diagnostic points of the pipelines. These models may be increasingly valuable with changes in the technological paradigm of diagnostic methods.

Condition assessments of metallic pipelines deploying “next-generation” free-swimming ultrasonic inspection platforms provide high-resolution, multi-layered information on metal wall corrosion, out-of-roundness, and lining condition. While these data layers inform efficient pipeline management decisions, they also generate immense amounts of data to be analysed and interpreted. With the rapid advancements in computing hardware, artificial intelligence (AI) in the form of machine learning has been widely applied in data analytics and image recognition problems in recent decades. We show the promising results of using support vector machine (SVM), and then convolutional neural network (CNN) on the problem of analyzing pipeline condition assessment data for wall-loss defects. Additionally, we discuss the challenges that pipes of various materials and manufacture dates pose to AI-driven analytics, and how these challenges are being overcome. Finally, we will look to the future and explore AI analytics’ potential to monitor change in pipeline conditions over time. This will power predictive analytics allowing pipeline owners to adjust inspection intervals, or in the case of some larger utilities, enable the ability to predict where they need to perform in-field work to optimize capital expenditures and resource planning.

Wastewater collection systems become less effective over time, necessitating ongoing changes and the creation of asset management frameworks on the side of utility owners to keep their assets operating as intended. Since inspecting every sewer pipe is time-consuming and costly, developing prediction models that can anticipate sewer pipes’ current and future state is vital. In this research, two machine learning methods including k-nearest neighbors (KNN) and decision tree have been investigated in order to create a prediction model for sewer pipes of two cities in USA. The data which is used is a combined data from Tampa, Florida, and Dallas, Texas, containing nine physical and environmental variables. F1-score and area under the curve (AUC) were calculated to compare the effectiveness of developed models. It was concluded that the decision tree model performed better than the other. The overall F1-score for the decision tree model was 0.73 and for KNN was 0.70.

Inspection and condition assessment of pipelines play a vital role in the successful operation and maintenance of systems. In the United States, closed-circuit television (CCTV) is the commonly used device for inspecting the inner environment of sanitary sewer pipes. Inspection of every individual sanitary sewer pipe segment is not feasible for any municipality owing to its large inventory of pipes and incurred cost. Machine learning (ML) algorithms, such as logistic regression (LR), k-nearest neighbors (k-NN), and random forests (RF), were employed to develop condition prediction models that could predict the sanitary sewer pipes in need of repair or a maintenance activity. Although the LR model was unable to capture any sewer pipe in poor condition, the same model has resulted in a reasonably higher area under the curve (AUC) value of 0.76. This phenomenon was found to be due to higher imbalance in the data set. Therefore, the study aimed to overcome the limitation of imbalanced classification by employing techniques such as random under sampling and random over sampling. ML algorithms were employed for all three sampled data sets. With an F1-score of 0.94, the RF model outperformed both LR and k-NN models. The developed models can be utilized by utility owners and municipal asset managers to make more informed decisions on future inspections of sewer pipelines.

Pipelines play a pivotal role in the oil and gas industry as they are currently the most widely used method for conveying hydrocarbon fluids, natural gas, and petroleum products around the world. These pipelines require continuous monitoring and surveillance to ensure sustained infrastructural stability and undistorted output. Although pipeline monitoring has advanced over the years, there remains a critical need for an effective monitoring system with real-time feedback and the ability to detect minor leakages that many sensors might fail to detect. Deep learning (DL), a subset of machine learning, can be integrated with unmanned aerial vehicles to collect and analyze sensor data to solve this problem. DL using specific algorithms with pre-trained models based on historical data can detect external leakages and cracks. They can also predict likely areas of damage that could be omitted in conventional damage monitoring. Recently, there has been an increasing popularity in the use of sensor-equipped drones for monitoring pipelines in the oil and gas industry because of the numerous advantages it offers. A prominent advantage is that integrating and analyzing the data set obtained from an unmanned aerial vehicle (UAV) with DL algorithms can give real-time feedback and predict possible areas on the pipeline which show the likelihood of deterioration over time. This paper proposes a framework that integrates UAVs with DL for the monitoring of pipelines in the oil and gas industry. It is expected that the application of this framework will ensure a more efficient and proactive pipeline monitoring procedure for mitigating hazards and preventing accidents associated with oil and gas leakage or spillage.

Recent advancements and interest in leakage detection of the water pipeline systems are due to the aging drinking water infrastructure and scarcity of fresh drinking water across the globe. Approximately 20% of treated drinking water is lost due to leakages caused by deteriorating water distribution networks. The current leakage detection techniques only provide information about the leaks during testing and do not support real-time monitoring. This study is focused on developing machine learning models based on supervised classification algorithms for fast and reliable leakage detection through flow-induced surface vibration data that can be used for near real-time monitoring. A two-looped real-life polyvinyl chloride (PVC) pipeline network comprising an 820-L reservoir, a pump, various bends, diameters, leakage simulators, soil backfills, and a flowmeter is used to collect flow-induced surface vibration data using six accelerometers. Six accelerometers are mounted on the unburied section of the test bed to collect vibration signals for various non-leaky and leaky scenarios for training and validating the machine learning models. The models are trained using 80% of the vibration signals and validated using the remaining 20%. The performance of machine learning models is assessed using accuracy, recall, precision, F-score, and area under the curve. A summary of hyperparameter tuning and training time is also included in this study to discuss the trade-off between the required computing resources and the accuracies of the machine learning model. The result presented in this study provides a methodology and machine learning models that can be used further to develop real-time monitoring approaches for drinking water pipeline systems.

This paper concerns a case history of a buried gas transmission line which had been exposed to mine subsidence ground movements. The mine subsidence movements were the result of longwalling ore at a depth of approximately 1,600 ft. As the extraction of the ore progressed, the stress in the monitored pipeline worsened and was approaching unacceptable levels. The excessive pipe compression resulted when it was exposed to the compression zone of the subsidence basin created by the mining. In order to relieve ground movement induced compressive stress, the line was uncovered. As more of the pipeline was exposed, the pipe abruptly bowed in the trench excavation. An analysis of this pipe deformation which was performed is provided in this paper. This bowing/buckling phenomenon is not specifically covered in the ASME code. Also, discussed in this paper are ways to mitigate this pipe deformation or upheaval buckling from occurring.

Maintaining legacy gas pipeline infrastructure is an ongoing challenge throughout the United States, with thousands of miles of aging natural gas pipelines that are in critical need of repair or replacement. Open cut excavation replacement, to date, has been the most common solution used in the gas industry, but this method is costly, disruptive, and time-consuming, and requires either turning off gas flow or bypassing the lines to maintain service. Until recently, there has been a lack of investment in the research and development of innovative, cost-effective solutions to solve these and other gas industry-related pipeline issues. The US Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E) was initiated to address needs like this, making investments in key research and development initiatives like Rapid Encapsulation of Pipelines Avoiding Intensive Replacement (REPAIR). REPAIR was created to develop advanced technology for inspecting and rehabilitating natural gas pipelines using minimally invasive trenchless methods. The challenge presented by ARPA-E is to develop a robust trenchless alternative to the traditional open-cut replacement of deteriorated steel and iron gas lines that has a 50-year+ design life. Warren Environmental, General Electric Global Research, and Garver are one of 10 teams that were selected to take on this significant endeavor, proposing their PipeLine Underground Trenchless Overhaul (PLUTO) system. PLUTO includes sophisticated robotic systems for highly dexterous operation/mobility, coating/lining application technologies, and advanced inspection/testing equipment. As the system is developed and enters commercial service for gas pipeline rehabilitation, the team is also exploring the suitability of these technologies for water and wastewater applications, the nuclear energy sector, and emerging hydrogen pipe lining opportunities.

Hazardous liquid pipelines are mandated to maintain a minimum cover depth below the river bottom at crossings of inland bodies of water with widths greater than 30 m (100 ft) from high water mark to high water mark as per United States Federal Regulation 49 CFR Part 195.248, Subpart D—Construction. These prescribed installation depths apply during the initial pipeline construction phase and not during system operation. Over time, river scour results in a reduction in the prescribed depth of cover that can compromise the pipelines. This research involved development of a River Scour Monitoring System (RSS) to benefit society by serving as an active monitoring system capable of determining the degree of scour in a riverbed thereby alerting pipeline operators should the amount of cover of the pipeline become reduced. The technology used was based on a temperature gradient decay method for monitoring a subject pipeline river crossing for scour conditions. Field demonstrations at three crossing sites provided a validation of the applicability for detecting depletion of cover above an installed pipeline.

This study aims to provide a comprehensive review of the mechanism of erosion and corrosion, and unveiling critical factors affecting these threats, and identify the current knowledge gaps in erosion/corrosion assessment methodologies and mitigation strategies for reducing erosion/corrosion threats. The results reveal that the erosion-corrosion process in pipelines is highly intricate due to the large number of factors involved, as each of the erosion-corrosion factors identified can influence the erosion-corrosion damages. It is very difficult to predict damage rates of erosion-corrosion in field conditions. The erosion-corrosion process generally involves electrochemical and mechanical processes that interact with one another, resulting in the prevention of erosion-corrosion progression being complicated as an effective solution that should ensure that neither erosion nor corrosion occurs under normal operating circumstances. Moreover, there is presently no industry-recognized guideline document or standard for mitigating erosion-corrosion damage. API RP 14E has been widely utilized for assessing erosional velocity for decades. However, the equation by API RP 14E ignores most of the critical factors, which could provide incorrect results in most circumstances and frequently unjustifiably limits production rate or overestimates pipe diameters. Different mitigation strategies, including applying inhibitors, composite pipe materials, or utility pigging, are investigated as a comparison with recommendations.

Critical infrastructure systems, such as gas pipeline networks, are essential to the modern community’s survival. In severe seismic hazard zones, earthquakes can cause catastrophic damages to gas pipeline networks. The damages disrupt the gas supply, resulting in various direct and indirect losses to the utilities that serve the community. Resource constrained proactive rehabilitation of these pipelines under seismic uncertainty presents a challenge for gas utilities. Existing seismic susceptibility assessment models of gas pipeline networks have evaluated connectivity loss (CL). However, there is limited research that determines the optimum rehabilitation policy that minimizes connectivity loss within resource constraints. This study aims to identify critical pipes of a gas pipeline network for rehabilitation minimizing the network’s connectivity loss when only a limited length of pipes can be rehabilitated. With this aim in mind, four specific tasks are completed: (1) characterization of spatial seismic hazards in terms of peak ground velocity, (2) determination of pipe repair rate using the empirical fragility curves, (3) evaluation of gas pipeline network’s connectivity loss, and (4) minimization of the expected value of connectivity loss using a genetic algorithm (GA). A simulation-based approach is used to evaluate the seismic hazard, network-level seismic susceptibility assessment, and evaluation of the gas pipeline network’s connectivity loss while accounting for relevant uncertainties. Monte Carlo simulations were carried out to emulate the stochastic nature of the damages to the gas pipeline network. The methodology’s application has been illustrated on a reference network to identify the critical pipelines of that gas pipeline network. The outcomes were compared with the rehabilitation policies determined from a length-based rehabilitation approach. The comparison demonstrated significant improvement in connectivity loss while using GA-based rehabilitation approach. The proposed approach is expected to assist the gas utilities in making rehabilitation decisions to reduce connectivity loss of the gas pipeline networks.

Installation of composite pipelines via plowing has been an accepted industry standard for decades. By applying similar principles from composite pipe plowing we wanted to see if steel pipe plowing was viable and had similar benefits of increased production during the installation and remediation phases. The biggest challenge to overcome was the lack of flexibility that steel pipe has when compared to composite style pipes. Composite pipe can be plowed via an enlarged chute, similar to a cable, with a specific bend radius that is larger than the minimum bend radius of the pipe. We developed a pipe pulling method which functions as a hybrid of a horizontal directional drill (HDD) and conventional plowing method. The plow is modified and fitted with a specialized expander head, and the steel drag section is installed inside the expander head. The plow then installs the pipe, which is set up as if it were an HDD pullback, by pulling it into the ground. General findings were that installation of steel pipelines is possible using the pipe pulling method. Installation efficiency increases varied and were heavily dependent on right of way alignment. The best utilization of the method was on long sections. This is due to the travel time between sections, setup, and take down making up the majority of time required versus actual plowing. This constant setup time is very consistent between long and short sections. The longest section of pipe installed was just over 3,100 linear feet (install plowing time 1.5 h) versus the shortest section of 300 linear feet (install plowing time 0.25 h). Right of Way (ROW) restoration time and effort was dramatically reduced using the pulling method. Conventional plow rip was restored via track packing. Topsoil stripping was not required, allowing vegetation regrowth and complete restoration after three weeks in summer condition. Soil saturation affects the restoration, with dryer soils causing more plow rip heave, versus wetter soils leaving more significant rutting that requires clean up. The steel pull method, while deemed successful, has limitations and cannot be applied to all pipeline installation projects. Soil conditions, ROW alignment, terrain, and pipe coating material will all impact production gains. The paper also discusses steps to mitigate some of these factors to make the method applicable to a wider range of projects.

Omaha Metropolitan Utilities District (MUD) has used electromagnetic (EM) inspection technology for 15 years to inspect some of the more distressed prestressed concrete cylinder pipe (PCCP) in its system. Up until 2021, robotics was the exclusive delivery system for the EM inspection technology. In 2021, it was proposed that a free-swimming tool be used to inspect 6.6 mi of a critical 54-in. PCCP potable water main that had not yet been inspected. The advantage of using a free-swimming tool for this length of inspection run is the total inspection time which is one day (8−14 h) versus a week or more (six to eight days) for the robotics tool. The free-swimming tool also requires limited tapping on the main, one at the insertion location, and one tap at the extraction location.

Prestressed concrete cylinder pipe (PCCP) is a composite pipe that combines the compressive strength of concrete, the watertightness of the steel cylinder, and the tensile strength of pre-stressing wires. Because of their use in large-diameter transmission mains and corresponding consequence of failure, mitigating failure risk through proactive condition assessment and pipe rehabilitation have largely been adopted by the industry as a best management practice. PCCP failure can be multifaceted; while the most traditional approach to PCCP condition assessment has focused on quantifying broken wire wraps to model the state of pipes, Baltimore has observed multiple distressed pipes with no corresponding broken wire wraps. Forms of distress observed correspond to longitudinal failure due to uneven settling of bedding material due to poor installation, overlap of underground assets, and transition from encasements. Baltimore’s experience illustrates the importance of combining inspection methodologies for a more holistic condition assessment approach, where leak detection and visual and sounding inspections should be complemented with electromagnetic surveys to identify all pipes with an unacceptable high risk of failure. Best management practices for prevention of these failure modes as well as appropriate rehabilitation option are also discussed.

The city of Phoenix (city) operates a 7,000-mi distribution system serving over 1.7 million people and has completed over 225 mi of prestressed concrete cylinder pipe (PCCP) inspections. Answering the need for improving rehabilitation and re-inspection timing without unnecessarily increasing risk, the city developed and piloted a method to use inspection data to extend re-inspection intervals and execute appropriately timed repair projects. The pilot study included one mile of 48- and 54-in. PCCP across a planning horizon through approximately 2050. The subject pipeline was manufactured in 1985, showed an increasing trend in structural damage across two electromagnetic inspections, and had been repaired using carbon fiber-reinforced polymer (CFRP) at a railroad crossing where differential settlement had damaged the pipe. Goals of the pilot study included: evaluate feasibility of PCCP deterioration modeling, establish risk parameters for deterioration analysis, and develop risk-based re-inspection and renewal actions and timing. Secondary factors were considered, including treatment of CFRP re-inspection requirements according to American Water Works Association (AWWA) C305 CFRP Renewal and Strengthening of Prestressed Concrete Cylinder Pipe (PCCP), and the high prevalence of wire breaks adjacent to joints on the PCCP. Uncertainty of wire break reporting near joints is an accepted limitation of electromagnetic inspection and was factored into the analysis. The analysis showed the pipeline could be managed through continued re-inspections and select pipe replacements, rather than larger-scale rehabilitation. Factoring in the city’s relatively conservative risk parameters, the analysis also justified extending re-inspection intervals from the city’s standard 10 years to 18 years for the subject pipeline.

The water distribution system in the United States consists of 2.2 million miles of pipelines with water main breaks that the American Society of Civil Engineers (ASCE) 2021 Report Card estimated results in six billion gallons of drinking water lost daily. Detecting the state of pipeline deterioration should always be a top priority in the water pipeline industry. This paper statistically evaluates data from more than 70,000 electromagnetic inspections that have been performed since the installation of these pipes in 1971. The scope of this paper is related to performance and degradation of prestressed concrete cylinder pipe (PCCP) which is used in large diameter water transmission to predict remaining useful life (RUL) using different modeling technologies such as the artificial neural network. The objective of this research is to prepare a model to predict the RUL of PCCP. The results showed that the artificial neural network (ANN) method is very accurate method for calculating the (RUL) with a 97.9% accuracy value. Broken wires and internal water pressure were found to be the most important parameters to calculate the RUL of PCCP for the two diameters 72- and 90-in. considered. This paper should serve as a guideline for future research designed to investigate additional diameters.

Condition assessment of prestressed concrete cylinder pipe (PCCP) mains often deploys “electromagnetic testing” to identify the location and quantity of broken prestressing wire wraps in a pipeline. Until recently, the use of near field electromagnetic nondestructive testing was only offered by a single company, due to patent protection. However, as patents associated with this technology began expiring, the ability to provide this service has been offered by multiple firms. Recent industry advancements have resulted in new technology firms providing near field testing (NFT) of PCCP to report the location and quantity of broken prestressing wire wraps. This offers multiple benefits to the water community including increased innovation and the potential to reduce condition assessment costs. This paper evaluates and compares the results of NFT technologies utilized by two technology companies, one firm with significant experience and a second firm with a recently developed tool.

A 1940s era 48-in. lined cylinder pipe (LCP) prestressed concrete cylinder pipe (PCCP) raw water main started experiencing an increase in failures in the last decade. In order to proactively manage the main, Saginaw Midland Municipal Water Supply Corporation (SMMWSC) executed a condition assessment of the main, including a probability of failure evaluation. Less than 1% of the inspected pipes had indications of prestressing wire breaks. The probability of failure evaluation performed in 2019 estimates that three pipes have a probability of failure above 50% by 2049, when operating at the design plus surge pressure of 250 psi.

The Central Arizona Project (CAP) operates and maintains two (2) 21-ft (6.4 m) diameter steel pipes as part of the aqueduct system that delivers almost 2 billion gallons of Colorado River water per day, to Maricopa, Pinal, and Pima Counties in central and southern Arizona. The water is delivered to municipalities, industries, Native American communities, and agricultural users; over 5 million people (more than 80% of the population of Arizona) are provided water by the aqueduct system. The approximately 350 mi (563 km) long aqueduct system is composed of about 300 mi (483 km) of open channel canals, about 10 mi (16 km) of tunnels, and roughly 40 mi (64 km) of pipelines. The system traverses rugged mountains, desolate deserts, and highly populated urban areas as it conveys water from Lake Havasu at the western edge of the state to just beyond the southern boundary of the San Xavier Indian Reservation south of Tucson. As the aqueduct spans the state, it crosses several natural waterways. To facilitate not interrupting the natural waterways, the open channel canal transitions to a closed conduit and proceeds beneath the watercourse. Depending on the location within the aqueduct these pipelines range in size from 13-ft (3.9 m) to 21-ft (6.4 m), and include steel, monolithic concrete, and prestressed concrete pipelines. These large diameter water pipelines can be considered “forever assets”—there is no real service end-of-life, but there may be an economic end-of-life; for pipelines that is when it is more economical to replace the entire pipeline rather than continue to perform scheduled and unscheduled maintenance and/or repair. This paper examines the evaluation and results of a life-cycle cost analysis (LCCA) performed by CAP in attempting to determine the most cost-effective strategy in maintaining not only the two large diameter steel water pipelines but apply the maintenance strategies analyzed to CAP’s other pipelines.

In 2017, the Lake Huron Primary Water Supply System (LHPWSS) undertook a study to examine and predict the remaining useful life of its 30 mi (48-in.) PCCP pipeline. This pipeline was previously assessed using electromagnetic technology to determine broken wire wraps as well as continuously monitored for breakage with an acoustic fiber optic (AFO) cable along the length of the pipeline. The original study in 2017 focused on utilizing this inspection and monitoring data to develop a predictive model to forecast when each of the nearly 10,000 pipes will reach their respective “limit state” based on structural analysis of the pipeline. The inspection and monitoring data acquired from the pipeline was used as a case study to calculate deterioration rates across the length of the pipeline and provide the Water Supply System with information regarding when individual pipes may reach their failure limits so that long-term management strategies could be evaluated. Since the initial modelling in 2017, five more years of data have been collected along this pipeline from the AFO system. Additionally, the LHPWSS has collected high-resolution transient pressure data from points along the pipeline to determine the potential effects that the pressure changes may have on (1) pipeline damage; and (2) changes in pumping configurations. This paper is a comparative study of the initial analysis and the updated study based on the new data collected. In particular, the new analysis highlights how sections of the pipeline which resulted in high probability of failure in the 2017 study reacted to operational changes that modified the pressures in these areas in the intervening five years. The LHPWSS’ data shows that its transmission mains (like others in North America) have very low rates of damage. Regardless of any stated design life, these assets, like the Golden Gate Bridge, are not assets to be replaced after a set number of years but can be maintained virtually in perpetuity. To this end, in the near-term, the updated predictive modelling informs the urgency associated with an individual pipe segment that is showing signs of deterioration such that the LHPWSS can plan how quickly it needs to intervene and replace a pipe. In the long term, LHPWSS uses the predictive modelling information to forecast the number of pipe segments that are expected to be replaced over the capital planning period and incorporate this information into the asset management planning programme and budget development process.

Washington Suburban Sanitary Commission (WSSC Water) is not only one of the largest water and wastewater utilities in the United States, but it also has a very complex water system with approximately 850 mi of water transmission mains (16-in. and greater), 87 different pressure zones, 16 pump stations, two water treatment plants, 56 tanks and reservoirs, more than 180 PRVs, and more than 2,080 large isolation valves (16 in. and larger). The backbone of WSSC’s potable water transmission system is 145 mi of large diameter (36-in. and greater) pre-stressed concrete cylinder pipe (PCCP), 80% of which is monitored with a near-real-time pipeline acoustic fiber optic (AFO) system and 10 pressure transient monitors in two areas of interest. WSSC Water has a proactive approach to manage their water system with a water main replacement program, tank rehabilitation program, large valve replacement program, and a five-year cycle PCCP condition assessment program. All of these factors result in a water system that does not always operate in a predictable manner and is subject to pressure variations that make it susceptible to pressure transients. These transients can lead to main breaks, increased leakage, and water quality problems due to backflow and intrusion. This paper will show two case studies in two different areas of interest that were identified during Phase 1 of WSSC Water’s transient pressure monitoring pilot. Through the analysis of the data registered by sensors at storage facilities, pump stations, and valve vaults via WSSC Water’s SCADA system, 10 transient pressure monitors and the AFO system, a correlation between the exacerbation of wire breaks and the pressure events in the water system was discovered.

Charlotte Water is the largest public water and wastewater utility in the Carolinas and greater Mecklenburg County, including the towns of Matthews, Mint Hill, Pineville, Huntersville, Davidson, and Cornelius. Their vast system includes many large diameter arteries that collect and deliver its water supply. For years they have taken a proactive approach in understanding and managing the condition of their pipeline infrastructure. Population and service demand growth over the last decade has moved Charlotte Water to lean in and use its existing resilience to stay ahead of unexpected large diameter concrete pipeline failures. Charlotte Water has faced the challenge of measuring and calculating risk within its aging, irreplaceable, concrete pipelines, and is now able to prioritize incremental inspection and repair, and earmarks capital funds appropriately in future years. Beginning with two of their most critical pipelines, the utility now understands how to manage these large diameter concrete pipelines within a full asset management cycle that has been established around a comprehensive, tailored, pipeline management strategy.

This paper discusses prestressed concrete cylinder pipe (PCCP) prestressing wire testing results from 2017 to 2021 and the correlation between dynamic strain aging (DSA) and hydrogen embrittlement. It provides a case study on how this information affected GLWA’s pipeline management approach. Additionally, in August 2022, Great Lakes Water Authority (GLWA) experienced a main break on a 120-in. PCCP water main that caused disruptions to more than 1,000,000 customers. A forensic investigation was also performed on this water main, and lengths of prestressing wire were submitted for the laboratory testing. The results of this testing are also included as a case study.

A study was performed to examine the comprehensive prestressed concrete cylinder pipe (PCCP) management strategy implemented by Miami-Dade Water and Sewer Department (MDWASD), the fifth-largest water utility in the United States. The strategy developed targets safely and effectively extending the serviceable life of MDWASD’s large-diameter pipe assets where replacement is cost-prohibitive and preventing catastrophic failures in a high-density urban environment. The strategy is built upon recurring electromagnetic inspections and continuous acoustic fiber optic (AFO) monitoring, but is augmented using visual and sounding practices, leak detection, transient pressure monitoring, design checks, finite element analysis, remaining useful life, and capital planning studies. A 12-year study of Route 1A, a 54-in. transmission main, will serve as the conduit to showcase the pipeline management strategy and the operational implementation throughout MDWASD’s 240 mi of PCCP mains and how a failing pipeline can be stabilized and managed for years to come.

Managing deteriorating water infrastructure requires that asset owners shift towards a data-based management approach that uses various data types for decision making and long-term capital planning projects. This paper presents how leveraging different data sources for a prestressed concrete cylinder (PCCP) pipeline was used by the city of Baltimore to make short- and long-term, data-driven rehabilitation decisions. The pipeline had undergone multiple repairs in successive years, and Baltimore needed better definition of long-term capital needs. For this work, various analyses were performed using different data sources, such as current condition data, future projected state leveraging a statistical degradation model and a finite element analysis, and information from soil sample data. These data have been integrated to provide a better overview of areas with higher levels of distress along the pipeline using spatial analytics. The results were presented in an interactive dashboard, allowing for a better visualization of the results.

SewerVUE Technology (SewerVUE) was subcontracted by Whissell Contracting and the city of Calgary to inspect two critical sanitary trunks located under Memorial Drive in Calgary, Alberta, Canada. Measurements of sediment levels, structural defects, and wall thicknesses of approximately 600 linear meters of 1,200 mm I.D. and 1,950 mm I.D. R.C.P. were taken. An advanced multi-sensor robotic float equipped with HD closed circuit television (CCTV), sonar, and 3D Light Detection and Ranging (LiDAR) was used. Quantifications of the staining and sediment deposits throughout the pipe were reported along with joints and wall loss. Equipped with this data, the city of Calgary and its engineers can make evidence-based decisions regarding the pipes’ rehabilitative needs. This case study demonstrates the use of advanced pipe condition assessment technologies as a cost-effective, non-destructive means to refine the estimated remaining useful life (RUL) of an interceptor, accurately determine the overall severity of pipe degradation, and provide a basis for improved cost allocation or timing of rehabilitation efforts.

Pipe penetrating radar (PPR) is the underground in-pipe application of GPR, a non-destructive testing method that can detect defects and cavities within and outside mainline diameter (>10 in./250 mm) non-ferrous (reinforced concrete, vitrified clay, PVC, HDPE, etc.) pipes. The key advantage of PPR is the unique ability to measure pipe wall thickness and deterioration including voids outside the pipe, enabling accurate predictability of needed rehabilitation, or the timing of replacement. This paper presents the recent advancements in PPR inspection technology and discusses one specific case study: the Los Angeles County Sanitation Districts (LACSD) in Los Angeles, California, USA. Two pipes were inspected: a 647.3 ft long, 25-in. NRCP (non-reinforced concrete pipe) sanitary sewer pipe (JOD-4) and a 22.6 ft, 48-in. RCP (reinforced concrete pipe) sanitary sewer pipe (JOH-9B). Both pipes had known issues of corrosion, erosion, and sedimentation. The objective of the PPR survey was to determine the condition and remaining service life of the pipes by mapping their wall thickness, and rebar cover, and detecting voids and/or other anomalies within or outside the pipe wall. The PPR results showed that JOD-4 had 28 deposits and 37 type 2 anomalies (voids), and JOH-9B had 6 deposits and encrustations. These findings were used by LACSD to make decisions about the necessary repairs and maintenance for these pipes to ensure their safe and efficient operation.

Timely inspection of sewer pipelines is necessary to track pipelines’ conditions and to also respond to intervention needs in case of major operational and structural defects. Asset owners usually confront difficulties in determining the annual sewer inspection needs they need to achieve annually while balancing budgets, and risks associated in case pipelines are not inspected. Risks of failures associated with these pipelines, if they occur and critical, are costly due to potential consequences on the society, environment, and economy. Proper management of these networks begins with understanding their risks in case pipelines failed which will then aid in prioritizing pipelines for inspections in the short- and long-term periods. Therefore, the main objective of this paper is to develop a risk-based matrix that will identify the inspection frequency of sewers depending on their criticality and conditions. As part of this paper, a four-point scale criticality model development will be discussed, which was then implemented on the city of Hamilton sewer network. The results of the vulnerability analysis and condition grading will be summarized to associate the findings of both criticality and conditions with sewer inspection frequency. The sewer funding needs are analyzed based on a 20-year period, identifying pipelines that need to be inspected in the short-, medium-, and long-term. While this paper will summarize the findings of the project completed for the city, this paper will assist other asset owners in implementing a systematic criticality framework and a risk-based decision matrix to determine the time of inspection per sewer pipe in their network to better allocate inspection budgets.

The San Jose-Santa Clara Regional Wastewater Facility (RWF) has 67,000 linear feet of wastewater process piping that carries raw sewage, liquids, and sludge between the various unit treatment process areas. Much of the process piping at the RWF has remained in service continuously over the years without interruption, with 70% being over 25 years old and greater than 10% over 50 years old. In June 2015, Black & Veatch collaborated with the city of San Jose to develop a risk-based framework that prioritized various process piping condition assessment work and developed guidelines for conducting the condition assessments. Since then, V&A Consulting Engineers has evaluated 25% of the wastewater process piping, obtaining visual and physical condition data to support Black & Veatch’s rehabilitation prioritization and design efforts. This paper will present: (1) benefits of adopted condition assessment protocols for prioritization and design, (2) benefits of a specific inspection approach for various pipe materials ranging in diameter up to 144 in., and (3) lessons learned from operational/shutdown conditions.

The Potomac Interceptor (PI) is a gravity sewer system that takes wastewater from Virginia and Maryland and delivers it to DC Waters’ Blue Plains Advanced Wastewater Treatment Plant in Washington, DC. DC Water has been performing condition assessments on these pipes and found that a number of reinforced concrete pipeline reaches had experienced various levels of corrosion. The problem DC Water faced was determining which portions should be included in the capital improvement plan (CIP) for rehabilitation. The condition assessments indicated many of the impacted pipes had the same National Association of Sewer Service Companies’ (NASSCO) Pipeline Assessment Certification Program (PACP) ratings 4 and 5. Rehabilitation of all the pipes with these high PACP ratings was prohibitively expensive. This paper will discuss the methodology used in detail, and benefits of this type of alternative condition analysis. Also, the paper will cover how this methodology, if applied by the industry, could potentially allow utilities to spread their CIP costs over longer periods to help ease the financial burden on rate paying customers.

It has been reported that at least 70% of projects experience delays and/or budget overruns due to utility conflicts. Inaccurate utility information means increased risk of utility hits. It is important that the underground infrastructure industry realize that the continued increase in the number of subsurface utility hits is unacceptable. In 1996, Purdue University was selected by the Federal Highway Administration (FHWA) to study the effectiveness of subsurface utility engineering (SUE) as a means of reducing costs and delays on highway projects. Virginia, North Carolina, Ohio, and Texas were selected to be part of this study. These four states had a total of 71 projects studied in detail. This study (publication no. FHWA-IF-00-014) states: “A savings of $4.62 for every $1.00 spent on SUE was quantified from a total of 71 projects. These projects had a combined construction value in excess of $1 billion. The costs of obtaining Quality Level ‘B’ (QL B) and Quality Level ‘A’ (QL A) data on these 71 projects were less than 0.5 percent of the total construction costs, and it resulted in a construction savings of 1.9 percent over traditional Quality Level C (QL C) and/or Quality Level D (QL D) data.” On October 1, 2015, the ASCE Utility Engineering and Surveying Institute (UESI) was officially established. In August 2016, the first utility investigation school (UIS) which was developed by ASCE’s UESI was held at Louisiana Tech University. The five-day training schools were taught by the foremost experts in the geophysics and subsurface utility engineering field. So far, the Buried Asset Management Institute–International (BAMI-I) and the UESI have conducted 15 UIS in different locations such as Louisiana Tech University, Purdue University, Colorado School of Mines, Lawrence Technological University, University of Texas at Arlington. BAMI-I teamed up with the California Department of Transportation (Caltrans) and conducted the 13th and 14th UIS on September 19−23, and November 14−18, 2022, in San Diego and Sacramento, California, respectively. This paper will describe what BAMI-I is doing to develop industry professional development courses and university level courses.

The American Society of Civil Engineers (ASCE) defines utility engineering as a branch of civil engineering that focuses on the plan, position, design, construction, operation, and maintenance of utilities. Additionally, in 2002, ASCE published the first national standard for subsurface utility engineering (SUE) (i.e., ASCE 38). The second version of the ASCE 38 was published in 2022. One of the objectives of ASCE 38 is reducing the number of damages to underground utilities. The number of damages to subsurface infrastructure is a concerning issue in modern cities where essential daily services such as potable water, natural gas, and electricity are delivered through a dense network of underground utilities. This study explores the current understanding and utilization of ASCE 38 in the United States. Accordingly, an online stratified random sample survey was designed to collect relevant information from practitioners in the state of North Carolina. Among other findings, the lack of awareness of the SUE standard and its guidelines is of significant concern. Accordingly, an effort is needed to raise awareness and investment in SUE. Thus, the study results are anticipated to contribute to better utilization of ASCE 38, which helps improve damage prevention efforts in the United States.

Advancements in digital design platforms have brought about increased use of 3D modeling of utility mapping for design purposes. While 3D models can be a useful tool to mitigate risk to a project, the accuracy and remaining uncertainty of such models must be documented in detail in order to truly minimize project risk and maximize the value of the model. ASCE 38-22 has elevated the understanding of risk associated with different quality levels. The inclusion or expansion of 3D depictions of utilities should start with ASCE 38-22 and provide clarity and source of the vertical or z values of utility information depicted in the model. The use of records, geophysical depths, sizes and shapes of structures, historical local knowledge, and professional best estimates to populate depth values all bring their own uncertainty to the 3D model. Understanding that uncertainty is a necessary component of the design engineers’ knowledge to mitigate and manage project risks. This paper will provide suggested best practices to the creation of a 3D utility model, based on case studies.

As a newly developing industry, subsurface utility engineering (SUE) is increasingly applied in municipal projects. Economic benefits when performing SUE are primarily derived from reducing unnecessary utility relocations and delay claims. Utility investigation is a critical part of SUE before determining utility relocations. Successful utility investigations include reviewing and documenting existing utility records, applying geophysical devices to detect underground utilities, or physically exposing unobservable utilities. The electromagnetic utility locator is a geophysical device universally applied to detect unseen underground metallic pipelines or cables. However, in congested utility areas, such as intersections, if the clearances between multiple metallic utilities are limited, it is possible that the locator cannot detect the correct utility line. This is because when two cables are too close, the target cable signal can cross over to a more conductive one, which may indicate that an inductive current flows in the non-target cable. This phenomenon is called signal coupling. In this article, the mechanism of this signal coupling will be discussed. Lab research in 2019 indicated that transmitter frequency and the clearance between utilities were related to signal coupling. However, two cases in the Dallas area showed that varying frequencies, power output, or ground wire location did not mitigate the coupling situation. Designators’ working experience can help identify the occurrence of signal coupling.

Transportation agencies are often challenged with delays in the delivery of critical projects due to unreliable utility conflict resolution processes. Utility conflicts may not be avoidable in transportation project design, and subsequently, warrant relocation before the transportation contractor begins their work. Based on many factors such as the type and size of the project, types of utilities in conflict, and prior rights, the process of utility coordination and relocation can become unreliable, potentially leading to significant project delays and opportunity costs. Many utility owners are either resource-constrained or less trusty of transportation agencies’ plan to follow through a conceived project, and therefore may not act in a timely manner to meet the needs of the transportation agencies. Some of the delays are also caused by inappropriate planning and incorrect relocations by the utility owners. This study reviewed the utility conflict management processes currently implemented at the South Carolina Department of Transportation (SCDOT) and subsequently identified the most critical factors leading to transportation project delays. A qualitative analysis of eight focus groups of the SCDOT employees forms the basis for this study. This paper would be beneficial to utility owners in developing better working relationships with their state DOTs.

DC Water’s interagency planning and design teams coordinate and review various design projects routinely to ensure there are no proposed conflicts with our existing infrastructure. As utility corridors become more congested due to continuous development, the request for design waivers has increased significantly. The interagency planning and design teams worked together to develop a set of mitigation tables that address some common horizontal and vertical clearance issues between our water and sewer infrastructure and other utilities and structures. The outcome of this collaboration is transparent guidelines that reduce review times. Moreover, designers have clear guidance, which makes the design process more efficient by removing unknowns and reducing meetings. As a result of these tables, the teams have realized the mitigation tables are just a starting point and will not address every situation the designers or reviewers will encounter. Continuous table development and efficiencies of the design review process will continue.

Our infrastructure above and below ground changes daily. As-built records for utilities are unreliable, lost, or damaged, making it more challenging to determine their location underground. There also could be other facilities, objects, and structures, etc., underground, which are critical to identify to be successful. How do we know what else is below ground? The ASCE 38-02 and newly published 38-22 Standard Guideline for Investigating and Documenting Existing Utilities provide many techniques for finding underground utilities. But what about the other objects, including structures or private utilities, that could affect a project? These can include abandoned utilities, vaults, underground tanks, and septic systems. These may not show up on any records or have any above ground features to facilitate identifying them. This paper will discuss different types of equipment and techniques that can be used to help determine what else may be underground. These include electromagnetic methods (pipe and cable locators, radio frequency identification, terrain conductivity metal detectors, ground penetrating radar, and infrared), elastic wave (acoustic), magnetic, and the use of metadata.

Mitigating utility risks on projects through the application of subsurface utility engineering (SUE) is an effective way to reduce the overall costs of projects and to mitigate the risks of project delays due to constructability issues, contractor delays, and redesign. Since implemented in 2003, compliant SUE investigations have been completed per the American Society of Civil Engineers (ASCE) 38-02, and now 38-22 Standards throughout the US and Canada. This paper will focus on detailing the best practices to completing SUE investigations under these standards.

A time-domain electromagnetic induction metal detector (TDEMI) was tested in conjunction with a drone, also known as an unmanned aircraft system (UAS), to identify buried metallic objects (ferrous and non-ferrous) at two sites on the RELLIS campus of Texas A&M University in Bryan, Texas. The airborne TDEMI instrument was newly released and is specifically designed by the manufacturer to be deployed by UAS. RELLIS, a former military airfield often used for research testing due to limited and controlled access, contains many unknown utilities from earlier uses. One test site was a 27-acre triangular section that previously included warehouses with related utilities. The other site was a one-acre rectangular section where a solar research site is planned. Site preparation work had begun on the smaller site when a previously unknown jet fuel line and valve were uncovered. The UAS test was expanded to cover this site to quickly map the location and extent of the jet fuel line within the solar project limits. The TDEMI instrument was able to identify the location of previously unknown pipelines at the large site as well as show the location and direction of a jet fuel pipeline at the planned solar site. The test results were used by facility personnel to advise the future design for the site. In addition to detecting metallic pipelines and utilities, the TDEMI system can detect and map underground storage tanks and other buried metallic features. The application of the technology on a UAS platform makes the TDEMI system deployable in areas where land-based data collection is not optimal. A discussion of the advantages and disadvantages of the use of UAS-based TDEMI operation is further discussed.

In 2021, WaterOne and Pure Technologies (Xylem) conducted an inline free-swimming ultrasonic pipe wall inspection of a 30-in. diameter ductile iron pipe (DIP) transmission main. The 30-in. main spans for 3.6 mi across three municipalities and consists of both unwrapped 1966 DIP and 1992 polywrapped DIP. After successfully validating defects throughout the pipeline, WaterOne leveraged the same technology in 2022 to perform inspections on four additional pipelines: a 1950 20-in. cast iron main, a 1992 polywrapped 20-in. DIP main, and a 24-in. DIP main with both unwrapped 1985 and polywrapped 1991 mains. This paper summarizes the operational aspects of the conducted pipe inspections. The inspection results identified pipe wall loss due to corrosion with examples of validations and air pocket and leak detection results. This paper also presents how these actionable insights inform pipeline management decisions. Lessons learned from both the utility’s and vendor’s perspectives are also shared.

Aurora Water and Jacobs Engineering Group Inc. (Jacobs) have developed a tiered approach for condition assessment for buried pipelines that minimizes risk for the client and helps the client make informed decisions on rehabilitation or replacement. The tiered approach considers the value added from low-cost evaluations prior to spending more money on costly advanced pipeline inspection tools. This paper discusses the tiered condition assessment approach, testing, rehabilitation selection and installation, and validation of condition assessment tools. In 2016, an investigation project was initiated to obtain background information about a 30-in. steel pipeline with a history of breaks. From background information, it was determined the pipeline had failures in a single concentrated reach, which was characterized by the presence of petroleum contaminated soils. The investigation focused on this particular reach, and corrosion control methods for the pipeline (e.g., coatings, linings, and cathodic protection) were evaluated. Based on the corrosion control assessment, appropriate advanced pipeline inspection tools were selected for detailed evaluation. The overall condition assessment conclusions suggested rehabilitation of the deteriorated section of pipeline. Sliplining with Fusible PVC (polyvinyl chloride) pipe was selected as the preferred technology to rehabilitate the pipeline. In 2021, sliplining rehabilitation was successfully installed. Two large sections of existing steel pipe were removed for the sliplining rehabilitation. These two sections of pipe were evaluated and used to successfully validate the results of the initial condition assessment.

In 2020, the city of Corpus Christi moved forward with a condition assessment project examining a series of underwater crossings and a portion of steel waterline. Through this work, indirect corrosion surveys were used to get a better understanding of the exterior condition of the pipeline. The city has used this study, and others like it, to better plan for future condition assessment projects as part of its asset management program. Based on the results from the initial study, other studies have begun, and the city has almost doubled the future budgets for assessment and rehab. The asset management program has resulted in moving toward an indefinite delivery indefinite quantity (IDIQ) contract for providing support to effectively use condition assessment funds where needed for in-depth study of the complete asset condition. This paper will discuss the indirect assessment methodology and results, how this information has been used to further the city’s asset management, and how it has impacted planning for future assessment and rehabilitation funds.