Development of a Conservative Hamiltonian Dynamic System for the Early Detection of Leaks in Pressurized Pipelines
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Doi: 10.28991/CEJ-2024-010-04-01
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Xie, J., Huang, B., & Dubljevic, S. (2024). Moving Horizon Estimation for Pipeline Leak Detection, Localization, and Constrained Size Estimation. doi:10.2139/ssrn.4730270.
Speziali, S., Bianchi, F., Marini, A., Menculini, L., Proietti, M., Termite, L. F., Garinei, A., Marconi, M., & Delogu, A. (2021). Solving Sensor Placement Problems in Real Water Distribution Networks Using Adiabatic Quantum Computation. IEEE International Conference on Quantum Computing and Engineering (QCE), Broomfield, Colorado, United States. doi:10.1109/qce52317.2021.00079.
Verde, C., & Torres, L. (2017). Modeling and monitoring of pipelines and networks. Springer, Cham, Switzerland. doi:10.1007/978-3-319-55944-5.
Rodríguez Calderón, W., & Pallares Muñoz, M. R. (2007). A numerical water-hammer model using Scilab. Ingeniería e Investigación, 27(3), 98–105. doi:10.15446/ing.investig.v27n3.14850. (In Spanish).
Firouzi, A., Yang, W., Shi, W., & Li, C.-Q. (2021). Failure of corrosion affected buried cast iron pipes subject to water hammer. Engineering Failure Analysis, 120, 104993. doi:10.1016/j.engfailanal.2020.104993.
Sánchez-Jiménez, A. D., Torres, L., & López-Estrada, F. R. (2020). Euler-Lagrange approach for modeling water pipelines with leaks. Memorias del Congreso Nacional de Control Automático, 1-7.
Macias, G., & Lee, K. (2022). Optimal Gas Leak Localization and Detection using an Autonomous Mobile Robot. Proceedings of the 9th International Conference of Control, Dynamic Systems, and Robotics (CDSR’22), Niagara Falls, Canada. doi:10.11159/cdsr22.122.
Schneider, J., Tél, T., & Neufeld, Z. (2002). Dynamics of “leaking” Hamiltonian systems. Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 66(6), 6. doi:10.1103/PhysRevE.66.066218.
Torres, L., & Besancon, G. (2019). Port-Hamiltonian Models for Flow of Incompressible Fluids in Rigid Pipelines with Faults. 2019 IEEE 58th Conference on Decision and Control (CDC), Nice, France. doi:10.1109/cdc40024.2019.9029170.
Perryman, R., Taylor, J. A., & Karney, B. (2022). Port-Hamiltonian based control of water distribution networks. Systems & Control Letters, 170. doi:10.1016/j.sysconle.2022.105402.
Lopezlena, R. (2014). Computer implementation of a boundary feedback leak detector and estimator for pipelines II: Leak estimation. Memorias del XVI Congreso Latinoamericano, 14-17 October, 2014, Cancún, Mexico.
Rashad, R., Califano, F., Schuller, F. P., & Stramigioli, S. (2021). Port-Hamiltonian modeling of ideal fluid flow: Part II. Compressible and incompressible flow. Journal of Geometry and Physics, 164. doi:10.1016/j.geomphys.2021.104199.
Beattie, C., Mehrmann, V., Xu, H., & Zwart, H. (2018). Linear port-Hamiltonian descriptor systems. Mathematics of Control, Signals, and Systems, 30(4). doi:10.1007/s00498-018-0223-3.
Zi Li, L., Rosli, M. I., & Panuh, D. (2019). Velocity Modelling for Pipeline Inspection Gauge. Jurnal Kejuruteraan, 31(2), 275–280. doi:10.17576/jkukm-2019-31(2)-11.
Bendimerad-Hohl, A., Matignon, D., Haine, G., & Lefèvre, L. (2024). On implicit and explicit representations for 1D distributed port-Hamiltonian systems. arXiv Preprint, arXiv:2402.07628. doi:10.48550/arXiv.2402.07628.
Zhang, J., Zhu, Q., & Lin, W. (2024). Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation laws. Physical Review Research, 6(1), 12031. doi:10.1103/PhysRevResearch.6.L012031.
Eidnes, S., Stasik, A. J., Sterud, C., Bøhn, E., & Riemer-Sørensen, S. (2023). Pseudo-Hamiltonian neural networks with state-dependent external forces. Physica D: Nonlinear Phenomena, 446, 446. doi:10.1016/j.physd.2023.133673.
Sultana, S., & Rahman, Z. (2013). Hamiltonian Formulation for Water Wave Equation. Open Journal of Fluid Dynamics, 3(2), 75–81. doi:10.4236/ojfd.2013.32010.
Przystupa, K., Ambrożkiewicz, B., & Litak, G. (2020). Diagnostics of Transient States in Hydraulic Pump System with Short Time Fourier Transform. Advances in Science and Technology Research Journal, 14(1), 178–183. doi:10.12913/22998624/116971.
Ji’e, M., Yan, D., Sun, S., Zhang, F., Duan, S., & Wang, L. (2022). A Simple Method for Constructing a Family of Hamiltonian Conservative Chaotic Systems. IEEE Transactions on Circuits and Systems I: Regular Papers, 69(8), 3328–3338. doi:10.1109/TCSI.2022.3172313.
Phipps Electronics. (2024). YF-S201 Hall Effect Water Flow Meter / Sensor. Phipps Electronics, North Revesby, Australia. Available online: https://www.phippselectronics.com/product/yf-s201-hall-effect-water-flow-meter-sensor/ (accessed on March 2024).
Urbanowicz, K., Duan, H. F., & Bergant, A. (2020). Transient liquid flow in plastic pipes. Strojniski Vestnik/Journal of Mechanical Engineering, 66(2), 77–90. doi:10.5545/sv-jme.2019.6324.
Kulmány, I. M., Bede-Fazekas, Á., Beslin, A., Giczi, Z., Milics, G., Kovács, B., Kovács, M., Ambrus, B., Bede, L., & Vona, V. (2022). Calibration of an Arduino-based low-cost capacitive soil moisture sensor for smart agriculture. Journal of Hydrology and Hydromechanics, 70(3), 330–340. doi:10.2478/johh-2022-0014.
Bedford, A. (2021). Hamilton’s Principle in Continuum Mechanics. Springe, Cham. Switzerland. doi:10.1007/978-3-030-90306-0.
DOI: 10.28991/CEJ-2024-010-04-01
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