Numerical Analysis of a Mobile Leakage-Detection System for a Water Pipeline Network
DOI:
https://doi.org/10.37934/arfmts.87.1.134150Keywords:
Water leakage, Computational Fluid Dynamics, Drag coefficient, Sensing elementAbstract
The leakages in water pipeline networks sometimes negatively affect the environment, health, and economy. Therefore, leak detection methods play a crucial role in detecting and localizing leaks. These methods are categorized into internal and external detection methods, each having its advantages and certain limitations. The internal system has its detection based on the field sensors to monitor internal pipeline parameters such as temperature and pressure, thereby inferring a leak. However, the mobility of the sensing module in the pipeline is affected by the model drag coefficient. The low drag coefficient causes the module to quickly lost control in the pipeline leading to false detection. Therefore, this study is about designing and numerically analysing a new model to achieve a higher drag value of the sensing system. The drag value of various models is determined with the help of CFD simulations in ANSYS. The outcome of this study is a new model with a drag value of 0.6915. It was achieved by implementing an aerodynamic shape, a more significant surface contact area in the middle, and canted fins at the front of the . Both pressure, drag, and skin friction were increased, so a higher drag value of the sensing module can be achieved. Through this, the mobility and control of modules in the pipeline can be improved, improving leak detection accuracy.
References
Thajudeen, Kulsanofer Syed. "The Malaysian Leaky Pipe Story." The Malaysian Reserve, February 3, 2020. https://themalaysianreserve.com/2020/02/03/the-malaysian-leaky-pipe-story/
Zaki, Muhammad Mirza Mohd, Turki Al Qahtani, Noorfaizal Yidris, Shamsuddin Sulaiman, Ahmad Hamdan Ariffin, Mohd Saffuan Yaakob, and Kamarul Arifin Ahmad. "Design and Analysis of a Water Pipe Leakage Sensor." CFD Letters 12, no. 9 (2020): 51-59. https://doi.org/10.37934/cfdl.12.9.5159
Karoui, Tarek, Seong-Yun Jeong, Yeong-Hoon Jeong, and Dong-Soo Kim. "Experimental study of ground subsidence mechanism caused by sewer pipe cracks." Applied Sciences 8, no. 5 (2018): 679. https://doi.org/10.3390/app8050679
Kwak, Pill-Jae, Sang-Hyuk Park, Chang-Ho Choi, Hyun-Dong Lee, Jae-Mo Kang, and In-Hwan Lee. "IoT (Internet of Things)-based underground risk assessment system surrounding water pipes in Korea." International Journal of Control and Automation 8, no. 11 (2015): 183-190. https://doi.org/10.14257/astl.2015.99.06
Moors, Janneke, Lisa Scholten, Jan Peter van der Hoek, and Jurjen den Besten. "Automated leak localization performance without detailed demand distribution data." Urban Water Journal 15, no. 2 (2018): 116-123. https://doi.org/10.1080/1573062X.2017.1414272
Adedeji, Kazeem B., Yskandar Hamam, Bolanle Tolulope Abe, and Adnan M. Abu-Mahfouz. "Towards achieving a reliable leakage detection and localization algorithm for application in water piping networks: An overview." IEEE Access 5 (2017): 20272-20285. https://doi.org/10.1109/ACCESS.2017.2752802
Martini, Alberto, Marco Troncossi, and Alessandro Rivola. "Vibroacoustic measurements for detecting water leaks in buried small-diameter plastic pipes." Journal of Pipeline Systems Engineering and Practice 8, no. 4 (2017): 04017022. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000287
Shukla, Harshit, Kalyan R. Piratla, and Sez Atamturktur. "Influence of soil backfill on vibration-based pipeline leakage detection." Journal of Pipeline Systems Engineering and Practice 11, no. 1 (2020): 04019055. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000435
Martini, Alberto, Marco Troncossi, and Alessandro Rivola. "Automatic leak detection in buried plastic pipes of water supply networks by means of vibration measurements." Shock and Vibration 2015 (2015). https://doi.org/10.1155/2015/165304
Yazdekhasti, Sepideh, Kalyan R. Piratla, Sez Atamturktur, and Abdul A. Khan. "Novel vibration-based technique for detecting water pipeline leakage." Structure and Infrastructure Engineering 13, no. 6 (2017): 731-742. https://doi.org/10.1080/15732479.2016.1188318
Yazdekhasti, Sepideh, Kalyan R. Piratla, Sez Atamturktur, and Abdul Khan. "Experimental evaluation of a vibration-based leak detection technique for water pipelines." Structure and Infrastructure Engineering 14, no. 1 (2018): 46-55. https://doi.org/10.1080/15732479.2017.1327544
El-Zahab, Samer, Eslam Mohammed Abdelkader, and Tarek Zayed. "An accelerometer-based leak detection system." Mechanical Systems and Signal Processing 108 (2018): 276-291. https://doi.org/10.1016/j.ymssp.2018.02.030
Solomon, David, Zeev Efrat, and Baruch Solomon. "System, method, and apparatus for synchronizing sensors for signal detection." U.S. Patent Application 14/722,912, filed December 3, 2015.
Yazdekhasti, Sepideh, Kalyan Ram Piratla, John C. Matthews, Abdul Khan, and Sez Atamturktur. "Optimal selection of acoustic leak detection techniques for water pipelines using multi-criteria decision analysis." Management of Environmental Quality: An International Journal 29, no. 2 (2018): 255-277. https://doi.org/10.1108/MEQ-05-2017-0043
El-Zahab, Samer, and Tarek Zayed. "Leak detection in water distribution networks: an introductory overview." Smart Water 4, no. 1 (2019): 1-23. https://doi.org/10.1186/s40713-019-0017-x
Abdelhafidh, Maroua, Mohamed Fourati, Lamia Chaari Fourati, Adel Ben Mnaouer, and Zid Mokhtar. "Cognitive internet of things for smart water pipeline monitoring system." In 2018 IEEE/ACM 22nd International Symposium on Distributed Simulation and Real Time Applications (DS-RT), pp. 1-8. IEEE, 2018. https://doi.org/10.1109/DISTRA.2018.8600999
Lin, Huiwen, Hezhi Lin, Xiaoxuan Fang, Mingkang Wang, and Lianfen Huang. "Intelligent pipeline leak detection and analysis system." In 2020 15th International Conference on Computer Science & Education (ICCSE), pp. 206-210. IEEE, 2020. https://doi.org/10.1109/ICCSE49874.2020.9201761
Bohorquez, Jessica, Bradley Alexander, Angus R. Simpson, and Martin F. Lambert. "Leak detection and topology identification in pipelines using fluid transients and artificial neural networks." Journal of Water Resources Planning and Management 146, no. 6 (2020): 04020040. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001187
Wu, You, Kristina Kim, Michael Finn Henry, and Kamal Youcef-Toumi. "Design of a leak sensor for operating water pipe systems." In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 6075-6082. IEEE, 2017. https://doi.org/10.1109/IROS.2017.8206506
Dvajasvie, G., Banu PK Farisha, Sachin N. Babu, K. P. Saheen, and Nikhil C. Binoy. "Leak Detection in Water-Distribution Pipe System." In 2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 1-4. IEEE, 2018. https://doi.org/10.1109/ICCONS.2018.8663193
Chatzigeorgiou, Dimitris M., Kamal Youcef-Toumi, Atia E. Khalifa, and Rached Ben-Mansour. "Analysis and design of an in-pipe system for water leak detection." In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, vol. 54822, pp. 1007-1016. 2011. https://doi.org/10.1115/DETC2011-48395
Bai, Chi-Jeng, Yang-You Lin, San-Yih Lin, and Wei-Cheng Wang. "Computational fluid dynamics analysis of the vertical axis wind turbine blade with tubercle leading edge." Journal of Renewable and Sustainable Energy 7, no. 3 (2015): 033124. https://doi.org/10.1063/1.4922192
Joung, Tae-Hwan, Hyeung-Sik Choi, Sang-Ki Jung, Karl Sammut, and Fangpo He. "Verification of CFD analysis methods for predicting the drag force and thrust power of an underwater disk robot." International Journal of Naval Architecture and Ocean Engineering 6, no. 2 (2014): 269-281. https://doi.org/10.2478/IJNAOE-2013-0178
Inc., ANSYS. "Modeling Turbulent Flows." Prof Neil W. Bressloff ~nwb Lectures. University of Southampton , June 29, 2018. https://www.southampton.ac.uk/~nwb/lectures/GoodPracticeCFD/Articles/Turbulence_Notes_Fluent-v6.3.06.pdf
