Статті в журналах: "Pipe condition assessment"

1

van Laarhoven, Karel, Jip van Steen, Frank van der Hulst, and Hector Hernandez Delgadillo. "CT Scans of Asbestos Cement Pipes as a Reference for Condition Assessment of Water Mains." Water 13, no. 17 (August 30, 2021): 2391. http://dx.doi.org/10.3390/w13172391.

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The water distribution network of The Netherlands contains around 30,000 km of asbestos cement (AC) pipes, which constitutes around 25% of the total network. As a pipe material, AC has a relatively poor performance, and therefore is a high priority for renewal. To help decide an effective order of replacement, the water utilities need condition assessment techniques that help them determine which pipes have the highest risk of failure. In the presented work, X-ray computed tomography (CT) was used to measure the degradation of AC pipes taken out of the field. These scans provide a description of the pipe degradation with unmatched detail. The results are compared with strength tests performed on the same pipes, revealing that detailed knowledge of the complete pipe degradation is more important than previously assumed. Moreover, comparison of the CT results to those of a commercial, non-destructive inspection technique was used as a new avenue for validation of this technique, demonstrating its future usefulness for attaining the detailed measurement of pipe degradation required by water utilities.

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2

Atique, Farzana, and Nii Attoh-Okine. "Copula parameter estimation using Bayesian inference for pipe data analysis." Canadian Journal of Civil Engineering 45, no. 1 (January 2018): 61–70. http://dx.doi.org/10.1139/cjce-2017-0084.

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Water main systems are aging and becoming a growing concern for maintenance. The structural deterioration of water mains is affected by different factors, such as pipe age, pipe material, soil condition, and pipe size, among others. Various methods of modeling have been used to predict the failure of water mains. Since pipe networks are underground and obtaining data on pipe conditions is very costly, statistical modeling has been widely used for pipe condition assessment. An emerging statistical method known as copula modeling is used here for pipe data analysis. The copula method is very useful in cases where marginals belong to different families of distributions. It is also useful for generating a large number of data points when it is difficult to obtain a data set, as is the case for pipe condition assessment, and where data sets have random variables belonging to non-Gaussian family distributions. Different copula families are applied here to model the dependency between the pipe age and repair age of pipes. The paper uses a Bayesian framework to estimate the parameter values in the copula model. This approach offers an additional option for estimating copula parameters for pipe data.

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3

Shi, He, Jinzhe Gong, Peter R. Cook, John W. Arkwright, Gretel M. Png, Martin F. Lambert, Aaron C. Zecchin, and Angus R. Simpson. "Wave separation and pipeline condition assessment using in-pipe fibre optic pressure sensors." Journal of Hydroinformatics 21, no. 2 (February 12, 2019): 371–79. http://dx.doi.org/10.2166/hydro.2019.051.

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Abstract The use of two pressure transducers in close proximity can enable the separation of the directional travelling pressure waves in pipelines. However, the implementation of this measurement strategy in real water pipes is difficult due to the lack of closely located access points. This paper reports the use of a customised in-pipe fibre optic pressure sensor array for hydraulic transient wave separation and pipeline condition assessment. The fibre optic pressure sensor array can be inserted into a pressurised pipeline through a single access point. The array consists of multiple fibre Bragg grating (FBG)-based pressure sensors in close proximity (∼0.5 m apart). A previously developed wave separation algorithm is adapted to analyse the transient pressure measurement from the FBG sensors. The resultant directional pressure waves are then used to detect pipe sections with a thinner wall thickness. A challenge is the influence of the in-pipe fibre optic sensing cable on the transient pressure measurement. The impact is analysed and adjustments to the pipeline condition assessment algorithm are undertaken to resolve the issue. The successful experimental application verifies the usefulness of the in-pipe fibre optic sensor array, which can facilitate transient-based pipeline condition assessment for buried water pipes with limited access points.

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4

Nguyen, Lam Van, and Razak Seidu. "Application of Regression-Based Machine Learning Algorithms in Sewer Condition Assessment for Ålesund City, Norway." Water 14, no. 24 (December 7, 2022): 3993. http://dx.doi.org/10.3390/w14243993.

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Predicting the condition of sewer pipes plays a vital role in the formulation of predictive maintenance strategies to ensure the efficient renewal of sewer pipes. This study explores the potential application of ten machine learning (ML) algorithms to predict sewer pipe conditions in Ålesund, Norway. Ten physical factors (age, diameter, depth, slope, length, pipe type, material, network type, pipe form, and connection type) and ten environmental factors (rainfall, geology, landslide area, population, land use, building area, groundwater, traffic volume, distance to road, and soil type) were used to develop the ML models. The filter, wrapper, and embedded methods were used to assess the significance of the input factors. A dataset consisting of 1159 inspected sewer pipes was used to construct the sewer condition models, and 290 remaining inspections were used to verify the models. The results showed that sewer material and age are the most significant factors, otherwise the network type is the least contributor affecting the sewer conditions in the study area. Among the considered ML models, the Extra Trees Regression (R2 = 0.90, MAE = 11.37, and RMSE = 40.75) outperformed the other ML models and it is recommended for predicting sewer conditions for the study area. The results of this study can support utilities and relevant agencies in planning predictive maintenance strategies for their sewer networks.

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5

Bechet, Quentin, Xavier Philoleau, Melissa Mellado-Ruiz, Amanda Siqueira, and Michelle Aguilar. "Using artificial intelligence to improve pipe condition assessment." Water e-Journal 5, no. 3 (2020): 1–12. http://dx.doi.org/10.21139/wej.2020.020.

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Inspection and condition assessments of network infrastructure are critical for water utilities and city councils to ensure the structural integrity and functionality of sewer pipes and stormwater drains. These assessments are necessary to identify the pipes requiring rehabilitation before they deteriorate past the point of renewal. In practice, these assessments are performed manually through camera inspection of the pipes. However, the visual observation of the resulting footage can be biased by the operator subjectivity. VAPAR.Solutions is a cloud platform that automates condition assessment directly from a pipe’s CCTV footage. In this context, VAPAR, an Australian-based company, developed a deep-learning algorithm to code inspection videos automatically and consistently. This study aimed to evaluate the performance of this auto-coding algorithm by using a dataset of 203 inspection videos captured in stormwater and sewer pipes in Victoria, Australia. This study revealed that the VAPAR algorithm missed fewer defects in sewer and stormwater pipes (13.2%) than the operator during visual inspection (36.6%). The VAPAR algorithm was, however, ‘over-sensitive’ and generated 28.1% of false alarms, against 7.8% for the operator. This study also revealed that the VAPAR algorithm was significantly more accurate than the operator at grading the pipes, with an accuracy between 76.3-79.8% against 48.5-52.2% for the operator.

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6

Zhu, Juanjuan, Joby B. Boxall, Andrew F. Hills, Rob S. Dwyer-Joyce, Sean R. Anderson, and Richard P. Collins. "Assessing Ground Support of Plastic Pipes Using Ultrasound." Infrastructures 6, no. 2 (February 19, 2021): 30. http://dx.doi.org/10.3390/infrastructures6020030.

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The ability to detect early signs of failure in buried pipe infrastructure is necessary to facilitate the continued use of ageing infrastructure for delivery of society’s essential services and move beyond disruptive and expensive reactive maintenance and repair. This paper reports detailed experiments on the use of in-pipe ultrasound techniques for assessment of ground conditions around buried plastic pipes. Two sets of ultrasonic experiment on the soil conditions are presented: (1) existence, shape, and dimension of void, and (2) water content in the soil. The ultrasound technique is shown to be capable for detecting water filled voids and assessing the soil support, critical early indicators of failure. The technique requires water as the transmission media hence is naturally suited to application in operational water distribution systems. The work represents an important advance in in-pipe condition assessment of plastic pipes, demonstrates the practical capability of the ultrasound technique, which is critical for progression towards proactive maintenance, offering cost and service improvements.

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7

Steed, H., S. Mandhle, and E. Steitle. "Retooling Condition Assessment When You Can’t Inspect Pipe." Proceedings of the Water Environment Federation 2016, no. 13 (January 1, 2016): 5339–57. http://dx.doi.org/10.2175/193864716819706239.

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8

Mashford, John, David Marlow, and Stewart Burn. "An Approach to Pipe Image Interpretation Based Condition Assessment for Automatic Pipe Inspection." Advances in Civil Engineering 2009 (2009): 1–11. http://dx.doi.org/10.1155/2009/317097.

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Condition assessment forms an important part of the asset management of buried pipelines. This is carried out through the use of inspection systems which usually consist of an image acquisition device attached to a mobile robotic platform. Complete or partial automation of image interpretation could increase the efficiency and objectivity of pipe inspection. A key component of an automatic pipe inspection system is the segmentation module. This paper describes an approach to automatic pipe inspection using pixel-based segmentation of colour images by support vector machine (SVM) coupled with morphological analysis of the principal component of the segmented image. The morphological analysis allows the principal component of the segmented image to be decomposed into the pipe flow lines region, the pipe joints, and adjoining defects. A simple approach to detecting pipe connections using fuzzy membership functions relating to defect size and location is also described.

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9

Arsénio, André Marques, Jan Vreeburg, and Luuk Rietveld. "Index of Joint Condition for PVC push-fit joints." Water Supply 14, no. 5 (May 13, 2014): 857–65. http://dx.doi.org/10.2166/ws.2014.043.

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The Index of Joint Condition (IJC) for polyvinyl chloride (PVC) push-fit joints, discussed in this article, was derived from installation guidelines and from destructive laboratory tests. The IJC is presented in a graphical framework and is a powerful tool to employ in order to visualize and compare, in situ, results obtained during condition assessment of PVC joints. The graphical results can also be translated into a numerical grade that allows comparing the conditions of various pipes and of individual joints. The applicability of the IJC is demonstrated in the condition assessment of 222 joints inspected in eight different sessions that encapsulate more than 2 km of older (more than 40 years) and newer pipes (less than 2 months). While, for the new pipe, all joints were considered to be in good condition – low replacement priority –, several joints in older pipes were considered to have high replacement priority.

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10

Chen, C. N., and H. Y. Chen. "Distributions of Pore Water Pressure Surround a Horizontal Drain Pipe on a Retaining wall Under Steady State Condition." Journal of Mechanics 29, no. 2 (December 20, 2012): 263–72. http://dx.doi.org/10.1017/jmech.2012.132.

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AbstractThis article presents the results from a study of drainage rates and groundwater pressure distributions surrounding a horizontal drain pipe. The pipe is assumed to be applied on a retaining wall and reached a steady state condition. The optimized design pattern for horizontal drain pipes on a retaining wall is deeply related to the efficiency of dissipation of groundwater and the pore pressure behind the wall. Therefore, simulations of groundwater flow through a single horizontal drain pipe with different sizes (diameters and lengths) and depths by a 3-D finite element program model would lead us to find out the mechanism of the drainage pattern. The study has revealed the equalized water pressure contours surrounding the horizontal drain pipe exhibited horn shapes distributions. The biggest but still has a closed shape of horn was named Characterized Iso-pressure Surface (CIPS) in this research. It was found to be a good object to reflect the effects of single drain pipe so as to explore the mechanisms of drainage pattern. This research conducted a series study of dimension factor influence. It could be a help in developing assessment and design methods for horizontal drain pipes applied to the retaining wall.

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11

Richarz, Werner, Harrison F. Richarz, John Sun, Fatemeh Karimi, and Taiwo Ricketts. "Sound and vibration measurements for pipe wall condition assessment of concrete pressure pipes." Journal of the Acoustical Society of America 150, no. 4 (October 2021): A67. http://dx.doi.org/10.1121/10.0007644.

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12

Ulapane, Nalika, Alen Alempijevic, Teresa Vidal Calleja, and Jaime Valls Miro. "Pulsed Eddy Current Sensing for Critical Pipe Condition Assessment." Sensors 17, no. 10 (September 26, 2017): 2208. http://dx.doi.org/10.3390/s17102208.

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13

Koo, Dae-Hyun, and Samuel T. Ariaratnam. "Innovative method for assessment of underground sewer pipe condition." Automation in Construction 15, no. 4 (July 2006): 479–88. http://dx.doi.org/10.1016/j.autcon.2005.06.007.

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14

Piegdoń, Izabela, and Barbara Tchórzewska-Cieślak. "The Use Of Fuzzy Set Theory In Exploitation Management Process On The Water Supply Network." Journal of KONBiN 35, no. 1 (November 1, 2015): 109–18. http://dx.doi.org/10.1515/jok-2015-0044.

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Abstract Daily exploitation of the network, collected data base concerning the pipes failures and knowledge of employees forming the base of data using in effective failure removal process. The paper presents a methodology of assessment of technical condition of water pipes, based on ranking the failures and danger degree they present resulting the lack of water supply to the water consumers. Often decision making process take place under uncertainty conditions, therefore presented method is based on assessment of degree of danger pipe failure making by experts using fuzzy theory and fuzzy sets. In the paper a fuzzy graph including various types of failures causing lack of water supply was presented.

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15

Atambo, Daniel, Vinayak Kaushal, and Mohammad Najafi. "CONDITION PREDICTION OF SANITARY SEWERAGE PIPELINE SYSTEMS USING MULTINOMIAL LOGISTIC REGRESSION." Journal of Engineering in Agriculture and the Environment 8, no. 3 (October 17, 2022): 9. http://dx.doi.org/10.37017/jeae.v8i3.37.

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It is important for the sanitary sewerage pipeline system to be in a good condition for providing safe conveyance of the wastewater from households, businesses, and industries to the wastewater treatment plants. Water utilities inspect sewer pipelines to decide which segments of the sanitary sewer pipes need renewal or replacement. This process of inspecting the sewer pipes is described as condition assessment. The objective of this paper is to develop Multinomial Logistic Regression (MLR) to predict the condition rating of sanitary sewerage pipelines using inspection and condition assessment data. MLR model was developed from the City of Dallas's data. The MLR model was built using 80% of randomly selected data and validated using the remaining 20% of data. The significant physical factors influencing sanitary pipes condition rating included diameter, age, pipe material, and length. Soil type was the environmental factor that influenced sanitary sewer pipes condition rating. The accuracy of the performance of the MLR was found to be 75%. This developed model will help the policymakers and sanitary sewer utility managers to predict sanitary sewer pipes condition rating that enables to prioritize the sanitary sewer pipes to be rehabilitated and/or replaced.

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16

Wang, Chen-wan, Zhi-guang Niu, Hui Jia, and Hong-wei Zhang. "An assessment model of water pipe condition using Bayesian inference." Journal of Zhejiang University-SCIENCE A 11, no. 7 (July 2010): 495–504. http://dx.doi.org/10.1631/jzus.a0900628.

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17

Hassan, Syed Ibrahim, L. Minh Dang, Irfan Mehmood, Suhyeon Im, Changho Choi, Jaemo Kang, Young-Soo Park, and Hyeonjoon Moon. "Underground sewer pipe condition assessment based on convolutional neural networks." Automation in Construction 106 (October 2019): 102849. http://dx.doi.org/10.1016/j.autcon.2019.102849.

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18

Ross, Robert, Alex Stumpf, Dean Barnett, and Richard Hall. "Condition Assessment for Concrete Sewer Pipes Using Displacement Probes: A Robotic Design Case Study." Robotics 10, no. 2 (April 27, 2021): 64. http://dx.doi.org/10.3390/robotics10020064.

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Worldwide, millions of kilometres of sewers are constructed from concrete pipes. Unfortunately, concrete sewers are susceptible to corrosion from biogenic hydrogen sulphide, and, though they may pass visual inspection, their ability to hold together under load may be degraded. This paper presents the design of a teleoperated robot with a protractible probe, that allows an operator to apply a localised load to selected points within a concrete sewer pipe. We report findings from laboratory and field trials of our prototype, with initial results suggesting that this approach has the potential to contribute useful information to sewer maintenance planning.

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19

Elshaboury, Nehal, Eslam Mohammed Abdelkader, Abobakr Al-Sakkaf, and Ghasan Alfalah. "Teaching-Learning-Based Optimization of Neural Networks for Water Supply Pipe Condition Prediction." Water 13, no. 24 (December 11, 2021): 3546. http://dx.doi.org/10.3390/w13243546.

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The bulk of water pipes experience major degradation and deterioration problems. This research aims at estimating the condition of water pipes in Shattora and Shaker Al-Bahery’s water distribution networks, in Egypt. The developed models involve training the Elman neural network (ENN) and feed-forward neural network (FFNN) coupled with particle swarm optimization (PSO), genetic algorithms (GA), the sine cosine algorithm (SCA), and the teaching-learning-based optimization (TLBO) algorithm. For the Shattora network, the inputs to these models are pipe characteristics such as length, wall thickness, diameter, material, lining and coating, surface type, traffic distribution, cathodic protection, flow velocity, and c-factor. For the Shaker Al-Bahery network, the data gathered include length, material, age, diameter, depth, and wall thickness. Three assessment criteria are used to evaluate the suggested machine learning models, namely index of agreement (IOA), correlation coefficient (R), and root mean squared error (RMSE). The results reveal that coupling FFNN with the TLBO algorithm outperforms other prediction models. Therefore, the FFNN-TLBO model can be a valuable tool for simulating the water network pipe condition. This study could help the water municipality allocate the available budget effectively and plan the required maintenance and rehabilitation actions.

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20

Stanić, N., C. de Haan, M. Tirion, J. G. Langeveld, and F. H. L. R. Clemens. "Comparison of core sampling and visual inspection for assessment of concrete sewer pipe condition." Water Science and Technology 67, no. 11 (June 1, 2013): 2458–66. http://dx.doi.org/10.2166/wst.2013.138.

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Sewer systems are costly to construct and even more costly to replace, requiring proper asset management. Sewer asset management relies to a large extent on available information. In sewer systems where pipe corrosion is the dominant failure mechanism, visual inspection by closed circuit television (CCTV) and core sampling are among the methods mostly applied to assess sewer pipe condition. This paper compares visual inspection and drill core analysis in order to enhance further understanding of the limitations and potentials of both methods. Both methods have been applied on a selected sewer reach in the city of The Hague, which was reportedly subject to pipe corrosion. Results show that both methods, visual inspection and core sampling, are associated with large uncertainties and that there is no obvious correlation between results of visual inspection and results of drill core analysis.

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21

Ross, Robert, Avinash Baji, and Dean Barnett. "Inner Profile Measurement for Pipes Using Penetration Testing." Sensors 19, no. 2 (January 10, 2019): 237. http://dx.doi.org/10.3390/s19020237.

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Penetration testing has been used to measure material properties for over fifty years. Currently, it is under-utilised as a contemporary scientific and engineering tool for investigating the condition of pipes whose inner surface has been exposed to chemical attack. We describe the design, development and calibration of a portable probe which uses a penetrative strain gauge load cell to measure where the semi-solid surface starts and stops within a pipe. We also describe the results of field tests of the probe in concrete sewers, affected by internal corrosion, where the probe proved to be a fast and reliable method for collecting pipe profile information. The results indicate significant benefit in the use of penetrometers to perform concrete sewer condition assessment.

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22

Zhu, Juanjuan, Richard P. Collins, Joby B. Boxall, Robin S. Mills, and Rob Dwyer-joyce. "Non-Destructive In-Situ Condition Assessment of Plastic Pipe Using Ultrasound." Procedia Engineering 119 (2015): 148–57. http://dx.doi.org/10.1016/j.proeng.2015.08.866.

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23

Nicholas, D., M. Heathcote, and G. Moore. "Practical condition assessment options for critical trunk watermains." Water Supply 3, no. 1-2 (March 1, 2003): 1–9. http://dx.doi.org/10.2166/ws.2003.0079.

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A review, originally carried out for Sydney Water Corporation, of a complete range of direct and indirect methodologies used to assess the condition of buried cast iron and steel water pipelines is presented. These techniques include pipe sampling, pit depth measurement, soil testing using various parameters, as well as other non-destructive testing (NDT) based on various electromagnetic principles. Both the literature and comprehensive field trials have shown that soil testing using linear polarisation resistance (LPR) methodologies as an input to statistical analysis packages is a cost-effective technique. Direct evaluation using remote field eddy current intelligent pigs can also be very useful for the direct examination of critical watermains but is limited to smaller sizes of DN 150-DN 375.

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24

Jukowski, Michał, Krzysztof Śledziewski, and Mateusz Hypki. "Assessment of the impact of vibrations on the track surface from impact loads." MATEC Web of Conferences 252 (2019): 01007. http://dx.doi.org/10.1051/matecconf/201925201007.

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Dynamic development of the linear infrastructure in Poland directly contributed to the increase in the number of engineering sites and facilities. Due to ground conditions and values of exploitation loads, in some cases bridge supports must be placed on foundation piles, the method of execution of which may cause significant dynamic impact on the structures located in the close vicinity. The paper assesses the impact of dynamic actions resulting from impact loads during impact pile driving of FRANKA piles with the use of a guide pipe on the railway track surface, on which there is continuous railway vehicle traffic. The tests have shown that the serviceability limit condition has been met and that the construction works do not result in exceeded values of vibration acceleration.

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25

Khazraeializadeh, Soroush, Leon F. Gay, and Alireza Bayat. "Comparative analysis of sewer physical condition grading protocols for the City of Edmonton." Canadian Journal of Civil Engineering 41, no. 9 (September 2014): 811–18. http://dx.doi.org/10.1139/cjce-2014-0077.

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Condition assessment is a key component of successful asset management, and many diverse condition assessment protocols exist for sewer mains. These protocols are used to generate condition grades for sewer mains after inspection. Condition assessment protocols are important because renewal actions for sewers are prioritized based on condition grades. If condition grades assigned to sewers do not reflect actual pipe conditions close enough, the resulting allocation of resources will not be the best. This paper presents a comparison of three possible sewer condition assessment protocols for the City of Edmonton: the Pipeline Assessment and Certification Program quick grading method, the Manual of Sewer Condition Classification fourth edition, and the City of Edmonton’s Sewer Physical Condition Classification Manual. The results show that structural sewer condition grades depend significantly on the protocol used; therefore, protocol selection has significant financial consequences for asset management programs in the city.

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26

Jiang, Jian Qun, Xiao Wen Yao, and Yi Ting Lu. "Seismic Damage Assessment of Urban Water Supply Pipeline." Applied Mechanics and Materials 316-317 (April 2013): 723–26. http://dx.doi.org/10.4028/www.scientific.net/amm.316-317.723.

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Water supply pipeline system is a key issue in urban lifeline engineering, and the seismic assessment for the system damage is of significant importance. In this study, method of seismic damage assessment on underground water supply pipeline is introduced. With emphasis on the uncertainties of earthquake level, ground condition, soil-pipe interaction and capacity to resist pipe deformation in longitudinal direction, the check point method is applied to the reliability study of water pipeline, and a case study is presented to show the implementation of the proposed model.

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Zhang, Chi, Aaron C. Zecchin, Martin F. Lambert, Jinzhe Gong, and Angus R. Simpson. "Multi-stage parameter-constraining inverse transient analysis for pipeline condition assessment." Journal of Hydroinformatics 20, no. 2 (February 1, 2018): 281–300. http://dx.doi.org/10.2166/hydro.2018.154.

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Abstract Fault detection in water distribution systems is of critical importance for water authorities to maintain pipeline assets effectively. This paper develops an improved inverse transient analysis (ITA) method for the condition assessment of water transmission pipelines. For long transmission pipelines ITA approaches involve models using hundreds of discretized pipe reaches (therefore hundreds of model parameters). As such, these methods struggle to accurately and uniquely determine the many parameter values, despite achieving a very good fit between the model predictions and measured pressure responses. In order to improve the parameter estimation accuracy of ITA applied to these high dimensional problems, a multi-stage parameter-constraining ITA approach for pipeline condition assessment is proposed. The proposed algorithm involves the staged constraining of the parameter search-space to focus the inverse analysis on pipeline sections that have a higher likelihood of being in an anomalous state. The proposed method is verified by numerical simulations, where the results confirm that the parameters estimated by the proposed method are more accurate than the conventional ITA. The proposed method is also verified by a field case study. Results show that anomalies detected by the proposed methods are generally consistent with anomalies detected by ultrasonic measurement of pipe wall thickness.

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Laakso, Tuija, Teemu Kokkonen, Ilkka Mellin, and Riku Vahala. "Sewer Life Span Prediction: Comparison of Methods and Assessment of the Sample Impact on the Results." Water 11, no. 12 (December 16, 2019): 2657. http://dx.doi.org/10.3390/w11122657.

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Survival models can support the estimation of the resources needed for future renovations of sewer systems. They are particularly useful, when a large share of network will need renovation. This paper studies modelling sewer deterioration in a context, where data are available for pipes selected for inspections due to suspected or experienced poor condition. We compare the random survival forest and the Weibull regression for modelling survival and find that both methods yield similar results, but the random survival forest performs slightly better. We propose a method for estimating the range in which the actual network survival curve lies. We conclude that in order to reach reliable results, a life span model needs to be constructed based on a random sample of pipes, which are then consecutively inspected and in addition, censoring and left truncation need to be accounted for. The inspection data applied in this paper had been collected with the aim of finding pipes in poor condition in the network. As a result, the data were biased towards poor condition and unrepresentative in terms of pipe ages.

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29

Malek Mohammadi, Najafi, Kaushal, Serajiantehrani, Salehabadi, and Ashoori. "Sewer Pipes Condition Prediction Models: A State-of-the-Art Review." Infrastructures 4, no. 4 (October 22, 2019): 64. http://dx.doi.org/10.3390/infrastructures4040064.

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Wastewater infrastructure systems deteriorate over time due to a combination of aging, physical, and chemical factors, among others. Failure of these critical structures cause social, environmental, and economic impacts. To avoid such problems, infrastructure condition assessment methodologies are developing to maintain sewer pipe network at desired condition. However, currently utility managers and other authorities have challenges when addressing appropriate intervals for inspection of sewer pipelines. Frequent inspection of sewer network is not cost-effective due to limited time and high cost of assessment technologies and large inventory of pipes. Therefore, it would be more beneficial to first predict critical sewers most likely to fail and then perform inspection to maximize rehabilitation or renewal projects. Sewer condition prediction models are developed to provide a framework to forecast future condition of pipes and to schedule inspection frequencies. The objective of this study is to present a state-of-the-art review on progress acquired over years in development of statistical condition prediction models for sewer pipes. Published papers for prediction models over a period from 2001 through 2019 are identified. The literature review suggests that deterioration models are capable to predict future condition of sewer pipes and they can be used in industry to improve the inspection timeline and maintenance planning. A comparison between logistic regression models, Markov Chain models, and linear regression models are provided in this paper. Artificial intelligence techniques can further improve higher accuracy and reduce uncertainty in current condition prediction models.

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30

Zhao, Shan, and Imad Al-Qadi. "Pavement drainage pipe condition assessment by GPR image reconstruction using FDTD modeling." Construction and Building Materials 154 (November 2017): 1283–93. http://dx.doi.org/10.1016/j.conbuildmat.2017.06.103.

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31

Garshasbi, Maryam, and Golam Kabir. "Earthquake Resilience Framework for a Stormwater Pipe Infrastructure System Integrating the Best Worst Method and Dempster–Shafer Theory." Sustainability 14, no. 5 (February 25, 2022): 2710. http://dx.doi.org/10.3390/su14052710.

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Stormwater pipe infrastructure is a fundamental requirement of any nation, but pipes can be damaged in natural disasters. Consequently, evaluating the resilience of stormwater infrastructure to earthquake damage is an essential duty for any city because it outlines the capability to recover from a disaster after the event. The resilience quantification process needs various data types from various sources, and uncertainty and partial data may be included. This study recommends a resilience assessment framework for stormwater pipe infrastructure facing earthquake hazards using Hierarchical Evidential Reasoning (HER) on the basis of the Dempster–Shafer (D-S) theory. The developed framework was implemented in the City of Regina, SK, Canada to quantify the resilience of the stormwater pipe infrastructure. First, various resilience factors were identified from the literature. Based on experts’ judgment, the weight of these factors was determined using the Best Worst Method (BWM). After that, the resilience was determined using the D–S theory. Finally, sensitivity analysis was conducted to examine the sensitivity of the factors of the recommended hierarchical stormwater infrastructure resilience model. The recommended earthquake resilience assessment model produced satisfying outcomes, which showed the condition state of resilience with the degree of uncertainty.

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32

Alkhimenko, Alexey. "Corrosion testing of experimental steels for oilfield pipelines." E3S Web of Conferences 121 (2019): 01001. http://dx.doi.org/10.1051/e3sconf/201912101001.

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Emergency equipment failures at oilfield pipelines are often associated with corrosion damage of the pipe material. Optimization of the chemical composition of the used steel can play a significant role in increasing the corrosion resistance under the condition of ensuring the metallurgical quality of pipes. This article presents a comparative assessment of the corrosion resistance of the used Fe-Cr-Cu-Mn-V steel and experimental compositions, basing on the results of electrochemical studies and tests for general corrosion.

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33

Robert, D. J., P. Rajeev, J. Kodikara, and B. Rajani. "Equation to predict maximum pipe stress incorporating internal and external loadings on buried pipes." Canadian Geotechnical Journal 53, no. 8 (August 2016): 1315–31. http://dx.doi.org/10.1139/cgj-2015-0500.

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Pipelines used for water and other services are very important lifelines in modern society. Commonly, these buried pipes are subjected to significant stresses due to external (traffic and earth) and internal (water pressure) loads. As many of these pipelines were laid sometime in the last century or earlier, in most cases their condition has deteriorated primarily by electrochemical and (or) microbiological corrosion. Corrosion activity (internal and external) can manifest in various forms, but in many cases will lead to reduced pipe thickness, which in turn leads to an increase in pipe stresses induced by the external and internal loads. Currently available analytical procedures to estimate pipe stresses are based on oversimplifications such as the two-dimensional (2-D) analysis based on Winkler springs, limiting their application to general pipe burial conditions. This paper describes the application of a three-dimensional (3-D) finite element method to analyse a buried pipe subjected to external and internal loads. Firstly, the finite element model is validated against the data from field tests conducted on the basis of a cast iron pipe that was laid in 1930 at Strathfield, Sydney, Australia. The results of these 3-D finite element analyses are then used to develop a closed-form expression to predict maximum stresses in pipes of different sizes buried in different soil types. Having obtained a good agreement between the proposed model outcomes and the 3-D finite element analysis results, the proposed model has been validated against the field test data under different internal and external loadings. The verified outcomes of the model reveal that it can be used to predict maximum stresses without conducting a full-scale finite element analysis, which often requires specific computational resources and computational skills. Furthermore, the proposed model can be used in probabilistic analyses, where a large number of calculations need to be carried out to account for the uncertainty of the input variables. The applications of the model are also discussed in relation to the assessment of pipe performance and remaining safe life.

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Kerres, Karsten, Sylvia Gredigk-Hoffmann, Rüdiger Jathe, Stefan Orlik, Mustafa Sariyildiz, Torsten Schmidt, Klaus-Jochen Sympher, and Adrian Uhlenbroch. "Future approaches for sewer system condition assessment." Water Practice and Technology 15, no. 2 (April 8, 2020): 386–93. http://dx.doi.org/10.2166/wpt.2020.027.

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Abstract Different analytical approaches exist to describe the structural substance or wear reserve of sewer systems. The aim is to convert engineering assessments of often complex defect patterns into computational algorithms and determine a substance class for a sewer section or manhole. This analytically determined information is essential for strategic rehabilitation planning processes up to network level, as it corresponds to the most appropriate rehabilitation type and can thus provide decision-making support. Current calculation methods differ clearly from each other in parts, so that substance classes determined by the different approaches are only partially comparable with each other. The objective of the German R&D cooperation project ‘SubKanS’ is to develop a methodology for classifying the specific defect patterns resulting from the interaction of all the individual defects, and their severities and locations. The methodology takes into account the structural substance of sewer sections and manholes, based on real data and theoretical considerations analogous to the condition classification of individual defects. The result is a catalogue of defect patterns and characteristics, as well as associated structural substance classifications of sewer systems (substance classes). The methodology for sewer system substance classification is developed so that the classification of individual defects can be transferred into a substance class of the sewer section or manhole, eventually taking into account further information (e.g. pipe material, nominal diameter, etc.). The result is a validated methodology for automated sewer system substance classification.

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35

Barbera, Daniele, Hao Feng Chen, and Ying Hua Liu. "Creep Fatigue Life Assessment of a Pipe Intersection with Dissimilar Material Joint by Linear Matching Method." Applied Mechanics and Materials 853 (September 2016): 366–71. http://dx.doi.org/10.4028/www.scientific.net/amm.853.366.

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As the energy demand increases the power industry has to enhance both efficiency and environmental sustainability of power plants by increasing the operating temperature. The accurate creep fatigue life assessment is important for the safe operation and design of current and future power plant stations. This paper proposes a practical creep fatigue life assessment case of study by the Linear Matching Method (LMM) framework. The LMM for extended Direct Steady Cycle Analysis (eDSCA) has been adopted to calculate the creep fatigue responses due to the cyclic loading under high temperature conditions. A pipe intersection with dissimilar material joint, subjected to high cycling temperature and constant pressure steam, is used as an example. The closed end condition is considered at both ends of main and branch pipes. The impact of the material mismatch, transitional thermal load, and creep dwell on the failure mechanism and location within the intersection is investigated. All the results demonstrate the capability of the method, and how a direct method is able to support engineers in the assessment and design of high temperature component in a complex loading scenario.

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36

L. Wong, R. Deo, S. Rathnayaka, B. Shannon, C. S. Zhang, J. Kodikara, W. K. Chiu, and H. Widyastuti. "Water Pipe Condition Assessment Using Submersible Quasi-distributed Optical Fibre based Pressure Transducers." Electronic Journal of Structural Engineering 18, no. 1 (January 1, 2018): 54–60. http://dx.doi.org/10.56748/ejse.182291.

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Transient based technique is known as one of the most economical ways for pipeline condition assessment. This technique involves monitoring and analysing pressure transient profiles at multiple points in a distributed system. Its application is restricted due to its low spatial resolution (10 m). It is hypothesised that by increasing the number of pressure transducers and reducing the gauge length (distance between the transducers), the spatial resolution of the measurements would highly be improved. However, the deployment of pressure transducers is restricted to the location of the hydrants. In this paper, a submersible quasi-distributed optical fibre based pressure sensors were proposed, constructed and tested in laboratory to verify this concept. For this context, this paper describes the proposed optical device and presents some preliminary analysis and results obtained from a set of experiments. The experimental results show that using the quasi-distributed optical fibre based pressure transducers for pressure transient analysis can potentially detect small anomalies (200 mm) and measure the growth of the anomalies along a water pipe.

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37

Li, Zhidong, Bang Zhang, Yang Wang, Fang Chen, Ronnie Taib, Vicky Whiffin, and Yi Wang. "Water pipe condition assessment: a hierarchical beta process approach for sparse incident data." Machine Learning 95, no. 1 (June 29, 2013): 11–26. http://dx.doi.org/10.1007/s10994-013-5386-z.

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38

Liu, Yong Gang, Fang Po Li, Ding Peng Ye, and Xue Qing Teng. "Simulation on Stress Distribution of Drill Pipe’s Surface Initial Crack." Applied Mechanics and Materials 184-185 (June 2012): 460–64. http://dx.doi.org/10.4028/www.scientific.net/amm.184-185.460.

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Abstract: In drilling process, drill pipes’ out surface always have lots of pits and scratches due to the corrosive and erosion of mud or wear of well wall in work environment. Through establishing drill pipe’s working model and constitutive equations with Finite Element Analysis Software, the paper have simulated stress distribution on drill pipe body under two different condition that without mechanical damage and with initial crack. Analysis results show that the maximum stress increases with the increasing of initial crack depth, and the maximum stress position turns to crack circumferential root from the crack radial root with the increasing of initial crack’s depth. The analysis result is completely consistent with the actual morphology of crack propagation, as a result, the simulation analysis provides a effective new methods and reference for remaining life assessment and failure analysis of drill pipe.

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39

Sorge, Christian, Thomas Christen, and Hans-Joachim Mälzer. "Maintenance strategy for trunk mains: development and implementation of a high spatial resolution risk-based approach." Water Supply 13, no. 1 (February 1, 2013): 104–13. http://dx.doi.org/10.2166/ws.2012.085.

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This paper describes an enhanced concept for determining the right time and place for maintenance works (in this case rehabilitation and renewal), within the scope of a risk-based maintenance strategy for trunk mains, including a technical and economic risk assessment. The risks considered include damage caused by pipe failure (main burst) like revenue loss, third party property damage as well as damage to intangible assets (loss of company reputation). The innovative part of this concept is the intelligent combination of a remaining-service-life prognosis for pipelines with structural load factor verification, technical condition assessments, geo-referenced analyses and detailed costing. This approach allows a very detailed risk assessment of several thousand pipe sections (high spatial resolution approach). The outcome based on this concept are the required maintenance items (what and where) and a catalogue of maintenance actions (how and when) including maintenance type and costs.

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Vankov, Yuri, Aleksey Rumyantsev, Shamil Ziganshin, Tatyana Politova, Rinat Minyazev, and Ayrat Zagretdinov. "Assessment of the Condition of Pipelines Using Convolutional Neural Networks." Energies 13, no. 3 (February 1, 2020): 618. http://dx.doi.org/10.3390/en13030618.

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Pipelines are structural elements of many systems. For example, they are used in water supply and heat supply systems, in chemical production facilities, aircraft manufacturing, and in the oil and gas industry. Accidents in piping systems result in significant economic damage. An important factor for ensuring the reliability of energy transportation systems is the assessment of real technical conditions of pipelines. Methods for assessing the state of pipeline systems by their vibro-acoustic parameters are widely used today. Traditionally, the Fourier transform is used to process vibration signals. However, as a rule, the oscillations of the pipe-liquid system are non-linear and non-stationary. This reduces the reliability of devices based on the implementation of classical methods of analysis. The authors used neural network methods for the analysis of vibro-signals, which made it possible to increase the reliability of diagnosing pipeline systems. The present work considers a method of neural network analysis of amplitude-frequency measurements in pipelines to identify the presence of a defect and further clarify its variety.

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41

Plihal, H., F. Kretschmer, D. Schwarz, and Th Ertl. "Innovative sewer inspection as a basis for an optimised condition-based maintenance strategy." Water Practice and Technology 9, no. 1 (March 1, 2014): 88–94. http://dx.doi.org/10.2166/wpt.2014.010.

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Currently, around 100,000 km of public sewers are operated in Austria, with cleaning as one of the main tasks for a wastewater utility. Due to the precarious financial situation of many cities and municipalities sewer cleaning represents a considerable financial burden, resulting in the extension of cleaning intervals and the delay of required cleaning activities. Different approaches to sewer management can be distinguished. If a selective strategy is adopted, only pipe sections with deposits are cleaned. Thus, detailed information regarding the amount of deposits is required. A simple and quick method to inspect the sewer system and assess the degree of sediments is by means of a manhole-zoom camera. The current research project INNOKANIS investigates the operational condition assessment of sewers by means of different manhole-zoom cameras. So far the data suggest that the majority of investigated pipe sections belongs to the self-cleaning category. Only 1% of the pipe sections of combined sewers and 11% of sanitary sewers require additional cleaning. The example of the city of Salzburg illustrates the potential savings in connection with sewer cleaning if a selective approach is adopted. Following a strategic change, the sewer cleaning expenses decreased by 60% within a year.

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42

Laakso, Tuija, Suvi Ahopelto, Tiia Lampola, Teemu Kokkonen, and Riku Vahala. "Estimating water and wastewater pipe failure consequences and the most detrimental failure modes." Water Supply 18, no. 3 (August 14, 2017): 901–9. http://dx.doi.org/10.2166/ws.2017.164.

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Abstract Failures of water and wastewater networks can lead to severe consequences for the human, natural and built environments. This paper presents how data on networks and their immediate environment together with graph analysis can be used to estimate the severity of pipe failure consequences. A case study concerning a large water and wastewater utility revealed that ca. 14% of the water distribution pipes and ca. 25% of the sewers had potentially severe failure consequences with regard to at least one factor considered. The most detrimental failure modes connected to these pipes were identified. An assessment of the most important information needs revealed that a number of crucial source data sets were missing. The results can be used to support asset management decisions aiming at risk alleviation, e.g. when estimating the resources needed for network maintenance, condition inspections or renovations and when planning excavation works.

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43

Zieliński, A., H. Paszkowska, P. Skupień, and G. Golański. "Assessment of Service Life of HCM12 Steel After 100 000 Hrs of Service." Archives of Metallurgy and Materials 61, no. 2 (June 1, 2016): 1021–29. http://dx.doi.org/10.1515/amm-2016-0173.

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AbstractThe subject of the research was a material in the form of a ϕ38×4 pipe from HCM12 steel used for steam superheater coils in power boilers with supercritical and ultra-supercritical steam parameters. This article presents results of investigations of mechanical properties and microstructure of material of the examined tube in the as-received condition and after 100,000 h service at 585°C under creep conditions. Creep tests were carried out for the material after 100,000 h service to determine the disposable residual life. The impact of changes in mechanical properties and degradation of the microstructure on the loss of creep resistance compared to the as-received condition was assessed. The investigations have revealed that the examined steel after 100,000 h service meets the requirements for this steel in the as-received condition with regard to strength properties at room and elevated temperature. The creep tests have revealed a significant loss of creep resistance, which was estimated at around 60-70% compared to the as-received condition.

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44

Zhang, Xin, Wensong Zhou, Hui Li, and Yuxiang Zhang. "Data-Driven Damage Classification Using Guided Waves in Pipe Structures." Applied Sciences 12, no. 21 (October 26, 2022): 10874. http://dx.doi.org/10.3390/app122110874.

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Damage types are important for structural condition assessment, however, for conventionally guided wave-based inspections, the characteristics extracted from the guided wave packets are usually used to detect, locate and quantify the damages, but not classify them. In this work, the data-driven method is proposed to classify the common damages in the pipe utilizing the guided wave signals obtained from numerous damage detection tests. The fundamental torsional mode T(0,1) is selected to conduct the guided wave-based damage detection to reduce the complexity of signal processing for its almost non-dispersive property. A total of 520 groups of experimental data under different degrees of damage were obtained to verify the proposed method. Finally, with help of a deep neural network (DNN) algorithm, all response data from the damages in the pipes were all clearly classified with quite high probability.

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45

You, Ri. "Analysis of Circumferential Cracking Due to Wire Breaks in PCCP." Advanced Materials Research 446-449 (January 2012): 2860–65. http://dx.doi.org/10.4028/www.scientific.net/amr.446-449.2860.

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The prestressing wires of prestressed concrete cylinder pipe (PCCP) provide concrete core with compressive stress to resist internal pressure. Broken wires resulting from corrosion and embrittlement may cause cracking in pipe wall and increase the risk of failure with time. By developing a simplified model to reveal the mechanism of circumferential cracking due to wire breaks in PCCP, the longitudinal bending of pipe wall is analyzed, and the maximum number of broken wires can be determined conveniently by the equations derived in this paper. Verification against results of finite element analysis shows that the presented method has decent accuracy which is not significantly influenced by effective pipe length and wall thickness. By comparing the calculated maximum number of broken wires with the actual number of broken wires detected by inspection and monitoring technologies, circumferential cracking in prestress loss zone can be predicted, thus aiding condition assessment of PCCP.

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46

Yang, Chun Ting, and Yang Liu. "Research on Fault Diagnosis of PCCP Based on Support Vector Machine." Advanced Materials Research 108-111 (May 2010): 409–14. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.409.

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Recent years, many utilities have experienced catastrophic rupture of critical Prestressing Concrete Cylinder Pipe (PCCP) lines throughout the world. Much attention has been focused on reliably assessing the condition of PCCP mains. However, assessment of embedded prestressing wire is difficult. Continuous acoustic monitoring can provide a means of locating problematic pipe sections. In this paper the application of support vector machine (SVM) in acoustic signal detection is proposed. And the effect of this method is investigated. Some key parameters of SVM and kernel functions are surveyed. SVM methods are more effective, especially for the case of lack of training samples. The experiment shows that the SVM method has good classification ability and robust performances. The techniques can provide the opportunity to identify problematic pipe sections and repair the pipe prior to failure. Therefore it can help to prolong the life of a suspect pipeline while minimizing the potential for catastrophic failure.

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47

Arifin, Muhamad, Arif Cahyono, Idam Putra, and Badrul Munir. "Assessment of Offshore Piping Composite Repair Technology for Life Extension Program Case in Pertamina Hulu Energy West Madura Offshore." MATEC Web of Conferences 269 (2019): 06005. http://dx.doi.org/10.1051/matecconf/201926906005.

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The pipe work repair method such as clamps and pipe connector as the use of metallic repair component have been used for maintenance and repair application in oil and gas industry and cover the most common types of defect to pressurize system like internal and external corrosion and also cover situations where the damage is severe. On the other hand with a process safety precausion and production concern, in oil and gas facility the use of metallic repair is very challenging and most of the time will come as last option scenario. Composite repair which are now increasing in application to pipe repair situations may come as a solution. This paper provides assessment of offshore piping composite repair for life extension program of pressure system in West Madura Offshore. Assessment come to a conclusion that the composite repair at field PHE WMO which operate on envelop of 700 psi and temperature range of 20°C-80°C are still in good condition and retain the integrity of the asset, from where then the repair is considered to extent its lifetime.

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48

Shotskiy, S. A., and S. L. Golofast. "Analysis of the Linear Section Risk Level Including Changes in the Pipe Material Strength Properties during Main Oil Pipeline Operations." Occupational Safety in Industry, no. 3 (March 2021): 7–14. http://dx.doi.org/10.24000/0409-2961-2021-3-7-14.

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Strength properties of the pipe material are random variables and have a statistical straggling that differs for pipe products of different grades. Distribution of these properties significantly effects on the results of calculating the current level of strength reliability and risk of linear sections for the main pipelines. The reliability of such calculations results depends not only on the distribution that obeys the strength properties of the pipe material at the surveyed section, but also on the dispersion limits of these properties. At present, the main pipelines have significant service lives. Due to this, when making assessment of the technical condition, safety, and risk level of linear sections, the issue is raised of how stable the distribution is related to the pipe steel strength properties with an increase of the service life for the main pipeline. The results of studies are presented concerning the actual distribution and limits of dispersion for the strength properties of pipe steel grade 17G1S after a long-term operation of the main pipeline. It is established that the regularities and strength properties dissipation limits for the material of a pipe made of the above steel are changing with time. Based on the results of the study, a practical example is considered related to the assessment of the effect of the identified changes on the probability of failure and the risk level for one of sections at the linear part of the main oil pipeline. The results obtained in the work substantiate the need in considering changes in the distribution of strength properties that arises with an increase in the main pipelines service life. The outlined approach allows to increase the reliability of risk assessment results for the main pipelines having long-term service life.

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49

You, Ri, and Hong Bo Gong. "Steel-Cylinder Yielding Analysis of PCCP with Broken Wires." Advanced Materials Research 503-504 (April 2012): 819–23. http://dx.doi.org/10.4028/www.scientific.net/amr.503-504.819.

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The prestressing wires of prestressed concrete cylinder pipe (PCCP) provide pipe wall with compressive stress to resist internal pressure. Broken wires may cause yielding of steel cylinder and increase the risk of pipe failure with time. In order to reveal the mechanism of steel-cylinder yielding in PCCP with broken wires, a simplified model is developed and the maximum number of broken wires to preclude exceeding limit stress in steel cylinder can be determined conveniently by the equations derived in this paper. Verification analysis shows that the solution of simplified model agrees well with that of nonlinear finite element analysis. By comparing the calculated maximum number of broken wires with the detected actual number of broken wires, steel-cylinder yielding in prestress loss zone can be predicted, thus aiding condition assessment of PCCP

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50

Sempewo, Jotham Ivan, and Lydia Kyokaali. "Comparative performance of regression and the Markov based approach in the prediction of the future condition of a water distribution pipe network amidst data scarce situations: a case study of Kampala water, Uganda." Water Practice and Technology 14, no. 4 (November 12, 2019): 946–58. http://dx.doi.org/10.2166/wpt.2019.075.

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Abstract Globally, water utilities are grappling with the challenge of predicting the condition of deteriorating pipe network infrastructure amidst financial constraints and data-scarce scenarios. As a result, new innovative approaches such as statistical regression and Markov-based approaches have been introduced to aid water distribution pipe renewal decision making. However, comparison of the performance of these models under limited data has not been undertaken so far. In addition, the models have been applied elsewhere, in different environments and data availability scenarios. This paper addresses therefore the mentioned research gap and compares the performance of statistical regression and Markov models in the prediction of a condition of a pipe in a developing country. In addition, the criticality analysis of a block is studied. The data used for assessment is from Kampala water, the largest area in the National Water and Sewerage Corporation, Uganda. The results show that 78.26% of the prediction of the regression model is accurate in comparison to 88.4% for the Markov model. This means that the Markov-based approach is more superior than a regression model in a data scarce scenario. The approach will go a long way in helping water utilities in development of water decision pipe renewal plan amidst a limited budget and in data scarce scenarios.

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