Erosion Void Condition Prediction Models for Buried Linear Assets
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 10, Issue 1
Abstract
Sewer pipelines are a major component of any infrastructure. In fact, they are subject to deterioration through their service lives. Although researchers are pointing out the consequences of erosion voids in sewer pipelines, the literature lacks the evaluation and prediction of such a defect. This research’s main goal is to propose a model that can predict the condition of the erosion voids present outside sewer pipelines considering the fuzzy expert system. The methodology relies on different factors that are expected to contribute to the voids’ development and severity. Fuzzy membership functions are constructed for five identified factors. The aggregated index representing the condition of the studied defect is achieved by considering the relative weights of the factors collected from 32 experts. The model is implemented on two case studies. The first case study supplied average values of accuracy, precision, and true positive rate (TPR) of 83%, 80%, and 76%, respectively. The second case is used to associate the soil intrusion defect with the erosion voids condition. Accordingly, it concludes that higher soil intrusion percentages are observed in poor and critical erosion voids conditions. In addition, a regression analysis model is developed to study the relation between the structural grade of sewer pipelines and erosion voids conditions. The regression model produced a coefficient of determination () of 70.0%, minimal errors, and a high average validity percentage (AVP). This research shall help decision-makers in studying erosion voids defect to avoid major rehabilitation costs and sinkholes.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors thank Mr. Mark Roland for providing the data for Case study 1 and the city of London for providing data for Case study 2. Also, the authors thank the anonymous reviewers for their constructive comments which enhanced the quality of the paper.
References
Angkasuwansiri, T. 2013. “Development of wastewater pipe performance index and performance prediction model.” Ph.D. dissertation, Virginia Polytechnic Institute, State Univ.
Angkasuwansiri, T., and S. K. Sinha. 2014. “Development of a robust wastewater pipe performance index.” J. Perform. Constr. Facil. 29 (1): 04014042. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000499.
Azamathulla, H. M., and Z. Ahmad. 2012. “Estimation of critical velocity for slurry transport through pipeline using adaptive neuro-fuzzy interference system and gene-expression programming.” J. Pipeline Syst. Eng. Pract. 4 (2): 131–137. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000123.
Bakry, I., H. Alzraiee, K. Kaddoura, M. El Masry, and T. Zayed. 2016a. “Condition prediction for chemical grouting rehabilitation of sewer networks.” J. Perform. Constr. Facil. 30 (6): 04016042. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000893.
Bakry, I., H. Alzraiee, M. E. Masry, K. Kaddoura, and T. Zayed. 2016b. “Condition prediction for cured-in-place pipe rehabilitation of sewer mains.” J. Perform. Constr. Facil. 30 (5): 04016016. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000866.
Balkaya, M., I. D. Moore, and A. Sağlamer. 2012. “Study of non-uniform bedding due to voids under jointed PVC water distribution pipes.” Geotext. Geomembr. 34: 39–50. https://doi.org/10.1016/j.geotexmem.2012.01.003.
Chughtai, F., and T. Zayed. 2008. “Infrastructure condition prediction models for sustainable sewer pipelines.” J. Perform. Constr. Facil. 22 (5): 333–341. https://doi.org/10.1061/(ASCE)0887-3828(2008)22:5(333).
Daher, S. 2015. “Defect-based condition assessment model and protocol of sewer pipelines.” M.S. thesis, Dept. of Building, Civil, and Environmental Engineering, Concordia Univ.
Davies, J. P., B. A. Clarke, J. T. Whiter, and R. J. Cunningham. 2001. “Factors influencing the structural deterioration and collapse of rigid sewer pipes.” Urban Water 3 (1): 73–89. https://doi.org/10.1016/S1462-0758(01)00017-6.
Dubois, D., and H. Prade. 1988. Possibility theory: An approach to computerized processing of uncertainty. New York: Plenum Press.
Fathi-Moghadam, M., S. Emamgholizadeh, M. Bina, and M. Ghomeshi. 2010. “Physical modelling of pressure flushing for desilting of noncohesive sediment.” J. Hydraul. Res. 48 (4): 509–514. https://doi.org/10.1080/00221686.2010.491691.
Guo, S., Y. Shao, T. Zhang, D. Z. Zhu, and Y. Zhang. 2013. “Physical modeling on sand erosion around defective sewer pipes under the influence of groundwater.” J. Hydraul. Eng. 139 (12): 1247–1257. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000785.
Jaganathan, A. P., E. Allouche, and N. Simicevic. 2010. “Numerical modeling and experimental evaluation of a time domain UWB technique for soil void detection.” Tunneling Underground Space Technol. 25 (6): 652–659. https://doi.org/10.1016/j.tust.2009.08.006.
Jifei, W., H. Hongwei, X. Xiongyao, and X. Yadong. 2010. “Risk assessment of voids behind the lining of mountain tunnels.” In Proc., GeoFlorida 2010: Advances in Analysis, Modeling and Design, 2319–2328. Reston, VA: ASCE.
Kaddoura, K., T. Zayed, and A. H. Hawari. 2017. “Multiattribute utility theory deployment in sewer defects assessment.” J. Comput. Civ. Eng. 32 (2): 04017074. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000723.
Kamel, S., and M. A. Meguid. 2013. “Investigating the effects of local contact loss on the earth pressure distribution on rigid pipes.” Geotech. Geol. Eng. 31 (1): 199–212. https://doi.org/10.1007/s10706-012-9580-8.
Kulandaivel, G. 2004. “Sewer pipeline condition prediction using neural network models.” M.S. thesis, School of Planning, Design, and Construction, Michigan State Univ.
MacDonald, S. E., and J. Q. Zhao. 2001. “Condition assessment and rehabilitation of large sewers.” In Proc., Int. Conf. on Underground Infrastructure Research, 361–369. Ottawa: National Research Council.
Mamdani, E. H. 1974. “Application of fuzzy algorithms for simple dynamic plant.” Proc. Inst. Electr. Eng. 121 (12): 1585–1588. https://doi.org/10.1049/piee.1974.0328.
Mashford, J., D. Marlow, D. Tran, and R. May. 2010. “Prediction of sewer condition grade using support vector machines.” J. Comput. Civ. Eng. 25 (4): 283–290. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000089.
Meguid, M. A., and H. K. Dang. 2009. “The effect of erosion voids on existing tunnel linings.” Tunneling Underground Space Technol. 24 (3): 278–286. https://doi.org/10.1016/j.tust.2008.09.002.
Moser, A. 2001. Buried pipe design, 2nd ed. New York: McGraw-Hill.
Najafi, M., and G. Kulandaivel. 2005. “Pipeline condition prediction using neural network models.” In Proc., Pipelines 2005: Optimizing Pipeline Design, Operations, and Maintenance in Today’s Economy, 767–781. Reston, VA: ASCE.
O’Reilly, M. P., R. B. Rosbrook, G. C. Cox, and A. McCloskey. 1989. Analysis of defects in 180 km of pipe sewers in Southern Water Authority. Washington, DC: Transportation Research Board.
Reilly, M. 2010. “Do not call the Guatemala sinkhole a sinkhole.” National Geographic. Accessed February 13, 2018. http://news.nationalgeographic.com/news/2010/06/100603-science-guatemala-sinkhole-2010-humans-caused/.
Ross, T. J. 2010. Fuzzy logic with engineering applications. 2nd ed. Chichester, UK: Wiley.
Tan, Z., and I. D. Moore. 2007. “Effect of backfill erosion on moments in buried rigid pipes.” In Proc., Transportation Research Board Annual Conf. Washington, DC: Transportation Research Board.
Vipulanandan, C., and J. Liu. 2005. “Sewer pipe-joint infiltration test protocol developed by CIGMAT.” In Proc., Pipelines 2005: Optimizing Pipeline Design, Operations, and Maintenance in Today’s Economy, 553–563. Reston, VA: ASCE.
WRc (Water Research Centre). 2001. Sewerage rehabilitation manual. 4th ed. Swindon, UK: WRc.
Yan, J. M., and K. Vairavamoorthy. 2003. “Fuzzy approach for pipe condition assessment.” In Proc., New Pipeline Technologies, Security, and Safety, 466–476. Reston, VA: ASCE.
Zheng, T., and I. D. Moore. 2007. “Effect of backfill erosion on moments in buried rigid pipes.” In Proc., Transportation Research Board 86th Annual Meeting, Washington, DC: Transportation Research Board.
Information & Authors
Information
Published In
Journal of Pipeline Systems Engineering and Practice
Volume 10 • Issue 1 • February 2019
Copyright
©2018 American Society of Civil Engineers.
History
Received: Oct 31, 2017
Accepted: Jul 10, 2018
Published online: Oct 27, 2018
Published in print: Feb 1, 2019
Discussion open until: Mar 27, 2019
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.