Search Results (53)

Sewer pipelines are essential urban infrastructure that play a key role in sanitation and disaster prevention. Regular condition assessments are necessary to detect defects early and determine optimal maintenance timing. However, traditional visual inspection using closed-circuit television (CCTV) footage is time-consuming, labor-intensive, and dependent on subjective human judgment. To address these limitations, this study develops a convolutional neural network (CNN)-based sewer defect classification model and analyzes how data quality—such as mislabeled or redundant images—affects model accuracy. A large-scale public dataset of approximately 470,000 sewer images was used for training. The model was designed to classify non-defect and three major defect categories. Based on the ResNet50 architecture, the model incorporated dropout and L2 regularization to prevent overfitting. Experimental results showed the highest accuracy of 92.75% at a dropout rate of 0.2 and a regularization coefficient of 0.01. Further analysis revealed that mislabeled, redundant, or obscured images within the dataset negatively impacted model performance. Additional experiments quantified the impact of data quality on accuracy, emphasizing the importance of proper dataset curation. This study provides practical insights into optimizing data-driven approaches for automated sewer defect detection and high-performance model development. Full article

This study addresses the microbial corrosion of cement-based materials in coastal urban sewer networks, systematically investigating the kinetic mechanisms of sulfur biogeochemical cycling under seawater infiltration conditions. Through dynamic monitoring of sulfide concentrations and environmental parameter variations in anaerobic pipelines, a multiphase coupled kinetic model integrating liquid-phase, gas-phase, and biofilm metabolic processes was developed. The results demonstrate that moderate salinity enhances the activity of sulfate-reducing bacteria (SRB) and accelerates sulfate reduction rates, whereas excessive sulfide accumulation inhibits SRB activity. At 35 °C, the mathematical model coefficient “a” for sulfate reduction in the reactor with 3 g/L salinity was significantly higher than those in reactors with 19 g/L and 35 g/L salinities, with no significant difference observed between the latter two. Overall, high sulfate concentrations do not act as limiting factors for sulfide oxidation under anaerobic conditions; instead, they enhance the reaction within specific concentration ranges. The refined kinetic model enables prediction of sulfur speciation in tropical coastal urban sewer pipelines, providing a scientific basis for corrosion risk assessment. Full article

The inspection of sewer pipes in the UK is costly, and if not inspected regularly, they are costly and disruptive to repair. This paper presents the Mega-Joey, a novel miniature, tether-less robot platform that is capable of autonomously navigating and assessing confined spaces, such as small-diameter underground pipelines. This paper also discusses a novel decentralized event-based-broadcasting autonomous exploration algorithm designed for exploring such pipe networks collaboratively. The designed robot is able to operate in pipes with an inclination of up to 20 degrees in dry and up to 10 degrees in wet conditions. A team of Mega-Joeys was used to explore a test network using the proposed algorithm. The experimental results show that the team of robots was able to explore a 3850 mm long test network within a faster period (36% faster) and in a more energy-efficient manner (approximately 54% more efficient) than a single robot could achieve. Full article

Tree root intrusion can cause failures of underground sewer pipes and thus represent a major water asset management issue. If tree root intrusion is not detected early, this may lead to the interruption of wastewater services and high costs of repair to the pipeline. The objectives of this review are to assess the existing maintenance strategies, explore suitable strategies for Australia and similar settings around the world, and identify possible factors and predictive tools. Maintenance strategies can be divided into two categories: reactive and proactive approaches. The current reactive approaches are (1) mechanical techniques to clean the root mass in pipe networks and (2) chemical techniques to remove the root mass and control future growth. The literature suggests that the reactive approaches often provide only partial solutions. The proactive approaches, guided by a predictive model of tree root intrusion and its related factors, showed the potential to improve maintenance and limit the risk of the damage from re-occurring. Predictive models could help to evaluate the risk of planting trees in different conditions and minimise the damage of tree root intrusion after further multifactor investigations. Full article

Aiming to solve the problem of clearing obstacles in narrow and complex sewers, this paper introduces a visually assisted Sewer Cleaning Robot (SCR) for cleaning sewers with diameters ranging from 280 to 780 mm. The main work is carried out as follows: (a) A mobile platform is equipped with a pressing mechanism to press against the pipe walls in different diameters. The arm uses high-load linear actuator structures, enhancing load capacity while maintaining stability. (b) A Detection–Localization–Cleaning mode is proposed for cleaning obstacles. The YOLO detection model is used to identify six types of sewer defects. Target defects are then localized using monocular vision based on edge detection within defect bounding boxes. Finally, cutting is performed according to the localized defect positions. The feasibility of SCR in cleaning operations is validated through a series of experiments conducted under simulated pipeline conditions. These experiments evaluate its mobility, visual detection, and localization capabilities, as well as its ability to clear hard obstacles. This paper provides technical reserves for replacing human labor that use vision algorithms to assist in cleaning tasks within sewers. Full article

Sanitary sewer pipelines frequently experience blockages, structural failures, and overflows, underscoring the dire state of U.S. wastewater infrastructure, which has been rated a D-, while America’s overall infrastructure scores only slightly better at C-. Traditional open-trench excavation methods or excavation technology (ET) for replacing deteriorated pipes are notoriously expensive and disruptive, requiring extensive processes like route planning, surveying, engineering, trench excavation, pipe installation, backfilling, and ground restoration. In contrast, trenchless technologies (TT) provide a less invasive and more cost-effective alternative. Among these, cured-in-place pipe technology (CIPPT), which involves inserting resin-impregnated fabric into damaged pipelines, is widely recognized for its efficiency. However, a comprehensive life cycle cost analysis (LCCA) directly comparing ET and TT, accounting for the net present value (NPV) across installation, maintenance, and rehabilitation costs, remains unexplored. This study aims to establish an LCCA framework for both CIPPT and ET, specifically for sanitary sewer pipes ranging from 8 to 42 inches in diameter. The framework incorporates construction, environmental, and social costs, providing a holistic evaluation. The key costs for ET involve pipe materials and subsurface investigations, whereas TT’s costs center around engineering and design. Social impacts, such as road and pavement damage, disruption to adjacent utilities, and noise, are pivotal, alongside environmental factors like material use, transportation, project duration, and equipment emissions. This comprehensive framework empowers decision makers to holistically assess economic and environmental impacts, enabling informed choices for sustainable sewer infrastructure renewal. Full article

The renewal of underground infrastructure is an emerging challenge for most municipalities in the United States. As compared to trenchless cured-in-place pipes (CIPPs), excavation technologies (ETs) have adverse impacts on the environment. Due to its lower ecological impact, trenchless technology is preferred in comparison to conventional pipe replacement. The selection of the most appropriate method depends on factors such as the existing sewer network, traffic disruption, soil conditions, and environmental safety. Recent concerns pertaining to environmental impact have increased the demand for reduced carbon footprints. The objectives of this paper are the following: (1) to present a comprehensive review on the achievements achieved over the years in understanding the factors influencing environmental emissions from the use of CIPP and ETs and (2) to analyze and compare the environmental emissions produced from CIPPs and ETs for 8-inch-, 10-inch-, and 12-inch-diameter pipes. Published papers from 1990 through 2024 have been included, which reported emissions from both alternatives. A comparison of total environmental emissions produced from both the processes is presented. The literature review and analysis suggest that higher emissions are a result of higher fuel consumption, material use, and input allocation. The emissions of pipeline renewal methods were evaluated using USEPA’s TRACI 2.1 methodology within SimaPro software. The analysis showed that CIPP renewal greatly reduced carbon emissions when compared with ET. CIPPs exhibited approximately 70% less ecological impact, 75% less impact on human health, and 60% less depletion of resources. CIPPs reduced carbon emissions by 78–100% in comparison to ETs. The recycling materials used in CIPPs potentially reduce the environmental impact by 10%, making them highly sustainable. The installation phase should therefore be carefully analyzed for factors like the pipe material and the pipes’ external diameter in view of achieving the greatest sustainability of these methods, as these characteristics affect emissions. It can be inferred that the comparison of the emissions of both alternatives is extremely vital for sustainable underground infrastructure development. Full article

Detecting defects in complex urban sewer scenes is crucial for urban underground structure health monitoring. However, most image-based sewer defect detection models are complex, have high resource consumption, and fail to provide detailed damage information. To increase defect detection efficiency, visualize pipelines, and enable deployment on edge devices, this paper proposes a computer vision-based robotic defect detection framework for sewers. The framework encompasses positioning, defect detection, model deployment, 3D reconstruction, and the measurement of realistic pipelines. A lightweight Sewer-YOLO-Slim model is introduced, which reconstructs the YOLOv7-tiny network by adjusting its backbone, neck, and head. Channel pruning is applied to further reduce the model’s complexity. Additionally, a multiview reconstruction technique is employed to build a 3D model of the pipeline from images captured by the sewer robot, allowing for accurate measurements. The Sewer-YOLO-Slim model achieves reductions of 60.2%, 60.0%, and 65.9% in model size, parameters, and floating-point operations (FLOPs), respectively, while improving the mean average precision (mAP) by 1.5%, reaching 93.5%. Notably, the pruned model is only 4.9 MB in size. Comprehensive comparisons and analyses are conducted with 12 mainstream detection algorithms to validate the superiority of the proposed model. The model is deployed on edge devices with the aid of TensorRT for acceleration, and the detection speed reaches 15.3 ms per image. For a real section of the pipeline, the maximum measurement error of the 3D reconstruction model is 0.57 m. These results indicate that the proposed sewer inspection framework is effective, with the detection model exhibiting advanced performance in terms of accuracy, low computational demand, and real-time capability. The 3D modeling approach offers valuable insights for underground pipeline data visualization and defect measurement. Full article

Under the dual pressures of climate change and urbanization, cities in China are experiencing increasingly severe flooding. Using the Yushan Lake area in Ma’anshan City, Anhui Province, as a case study, we employed the InfoWorks Integrated Catchment Management (ICM) hydraulic model to analyze the drainage and flood prevention system of the region and assess the current infrastructure for drainage and flood control. There are 117 pipelines with a return period lower than one year for stormwater and combined sewer systems, accounting for 12.3% of the total number of pipelines. The number of pipelines meeting the one-year but not the three-year return period standard is 700, representing 70.2%. Only 17.5% of the pipelines are capable of handling events exceeding the one-year standard. In simulating a 24 h, 30-year return period rainfall event, the results indicate that floodwater accumulation in the study area is predominantly between 0.15 m and 0.3 m. Most risk areas are classified as low risk, covering an area of 36.398 hectares, followed by medium and high-risk areas, which cover 8.226 hectares and 3.087 hectares, respectively. The Ma’anshan Yushan Lake area has, overall, certain flood control capabilities but faces flood risks during storms with return periods exceeding three years. This research offers valuable insights for improving urban flood management in Ma’anshan City through the development of a stormwater management model for the Yushan Lake area. Full article

This study introduces an innovative energy harvesting system designed for industrial applications such as fluid pipelines, air conditioning ducts, sewer systems, and subsea oil pipelines. The system integrates magneto-electric flow coupling and utilizes a dynamic vibration absorber (DVA) to mitigate the vibrations induced by fluid flow while simultaneously harvesting energy through magnetic dipole–dipole interactions in a vibration energy harvester (VEH). The theoretical models, based on Hamilton’s Principle and the Biot–Savart Law, were validated through comprehensive experiments. The results indicate the superior performance of the small-magnet system over the large-magnet system in both damping and power generation. The study analyzed the frequency response and energy conversion efficiency across different parameters, including the DVA mass, spring constant, and placement location. The experimental findings demonstrated significant vibration reduction and increased voltage output, validating the theoretical model. This research offers new avenues for energy harvesting systems in pipeline infrastructures, potentially enhancing energy efficiency and structural integrity. Full article

Surface cracks and joint deteriorations are typical premature failures of urban cement concrete pavement. However, traffic loads on the urban pavement are much lower than those on highways. Limited research has been conducted to investigate the causes of accelerated damage in urban cement concrete roads. To investigate the foundation issues that may cause the accelerated damage of urban cement concrete pavements, in this study, field evaluations were conducted to assess pavement foundation support and drainage conditions. Field visual inspections, Ground Penetrating Radar (GPR) survey, Dynamic Cone Penetrometer (DCP) test, and the Core-Hole Permeameter (CHP) test were performed. In urban residential areas with inadequate subgrade bearing capacity, cement concrete pavements are prone to early damage. Foundations with a higher content of coarse particles exhibit a higher CBR value, which can extend the service life of the pavement. The compaction of foundation materials near sewer pipelines and manholes is insufficient, leading to non-uniform support conditions. Moreover, the permeability of the foundation material can influence the service life of pavement surface structures. Foundation materials with fewer fine particles enhance drainage performance, contributing to a longer service life for PCC pavements. In areas with inadequate drainage, water accumulation reduces the bearing capacity of the foundation, thereby accelerating pavement deterioration. The poor bearing capacity and drainage conditions of the foundation lead to cavities between the surface layer and foundation material thus yielding stress concentrations on the pavement surface, which cause the formation of pavement surface cracks. Full article

Pipe jacking is a trenchless technology used to install buried pipelines, such as sewer lines in wastewater management systems. Existing mechanistic approaches based on geomaterial strength parameters (i.e., friction angle and apparent cohesion) can provide an estimation of the potential jacking forces during construction. However, extracting intact rock cores for strength characterisation is challenging when dealing with highly weathered ‘soft rocks’ which exhibit RQD values of zero. Such was the case for a pipe jacking drive traversing the highly weathered lithology underlying Kuching City, Malaysia. Furthermore, mechanistic approaches face limitations during construction when jacking forces are dependent on operation parameters, such as jacking speed and lubrication. To address these knowledge gaps, the primary objectives of this study are the development of rock strength parameters based on in situ pressuremeter testing for the purpose of estimating jacking forces. Furthermore, this study investigates the influence of various pipe jacking operation parameters, with a particular focus on their impact on jacking forces in weathered ‘soft rocks’. To achieve this, a novel deep learning model with an attention mechanism is introduced. The proposed methods of rock strength parameters derived from pressuremeter testing and the utilisation of deep learning will help to provide insights into the key factors affecting the development of jacking forces. This paper successfully shows the use of in situ pressuremeter testing in developing Mohr–Coulomb (MC) parameters directly from the site. In addition, the developed deep learning model with an attention mechanism successfully highlights the significance of pipe jacking operation parameters with an accuracy of 88% in predicting the jacking forces. Full article

The restoration of aging sewer networks is a fundamental remediation approach with the aim of renewing or improving existing systems. Remediation methods include repair, renovation, and replacement (renewal). The restoration of a sewer network itself can be performed using either excavation or trenchless technologies. While these technologies offer various advantages, they also present disadvantages. The choice of a restoration technology depends on numerous parameters, including economic factors and local conditions (such as the construction of the existing sewage network, available working space, traffic load, and environmental safety restrictions). In addition to the parameters influencing the choice of restoration technology, recent considerations have been given to constraints related to greenhouse gas emissions and the corresponding carbon footprint. Carbon footprint serves as an indicator of the restoration activity’s dependence on fossil fuels, both during implementation and operation. In the 21st century, concerns regarding carbon footprints have rapidly escalated. The reduction in carbon footprints is a crucial objective from both an economic and an ecological point of view. This article specifically addresses the prospects of monitoring the carbon footprint concerning the partial restoration of a sewer network within the historical core of the city of Brno, located in the Czech Republic. This aspect constitutes the unique and innovative contribution of the paper. The intensity of the energy demand of excavation and trenchless technologies is utilized as a direct measure of the carbon footprint of each technology. The comparative assessment demonstrates that the trenchless technology used achieves a reduction of 59.2% in CO₂ emissions compared to the excavation technology. The carbon footprint of Variant 1 (trenchless technology) is 9.91 t CO₂ eq., while the carbon footprint of Variant 2 (excavation technology) is 24.29 t CO₂ eq. The restoration of open pipelines produces more emissions due to the higher energy consumption, making it more expensive in terms of fuel costs, waste disposal costs, and the corresponding environmental hazards. Full article

This paper introduces a novel method for enhancing underground pipeline inspection, specifically addressing limitations associated with traditional closed-circuit television (CCTV) systems. These systems, commonly used for capturing visual data of sewer system deformations, heavily rely on subjective human expertise, leading to limited accuracy in detection. Furthermore, their inability to perform quantitative analyses of deformation extent hampers overall inspection effectiveness. Our proposed method leverages laser point cloud data and employs a 3D scanner for objective detection of geometric deformations in underground pipe corridors. By utilizing this approach, we enable a quantitative assessment of blockage levels, offering a significant improvement over traditional CCTV-based methods. The key advantages of our method lie in its objectivity and quantification capabilities, ultimately enhancing detection reliability, accuracy, and overall inspection efficiency. Full article

Wastewater pipelines are largely buried underground, and techniques for assessing and visualizing their condition are critical for planning and rehabilitation. This paper introduces a framework for integrating Geographic Information System (GIS), 3D-creation platform, augmented reality (AR) techniques, and machine learning algorithms for the dynamic visualization of the condition of sewer networks. A sewer network in Ålesund City, Norway, was used as a case study, and the developed framework was implemented on an Android OS and Microsoft HoloLens. The results show the potential applications of the integrated framework of GIS, AR, and 3D models for sewer condition visualization. The positioning accuracy of the application for 2D objects is equivalent to that of well-designed GPS receivers (approximately 1–3 m), depending on the handheld device used. Loading and locating 3D objects will be limited by the performance of the devices used. Full article