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Time-Spatial Analysis of the Functioning of the Water Distribution System in the Mathematical Modeling Process

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper presents the process of the temporal and spatial functioning of the water distribution system in the mathematical modeling process. The research was carried out on the Bialystok water network model with particular emphasis on the efficiency and energy efficiency of the pumping units located on the analyzed water distribution system (SDW). The calculations and calibration of the model were performed using the ISYDYW software, with particular emphasis on time and spatial distribution. Particular situations were analyzed, especially when the system operated in exceptional conditions, which most often resulted in failure, leading to a shortage of water supply, and thus energy losses of the pumping units. The obtained results allowed demonstrating the auxiliary role of the simulation method in determining and predicting the effects on the existing emergency states. Possible scenarios were prepared for the observed changes, both in the entire network and at the selected points of the pump systems. Assuming the duration of the failure, its consequences were determined and presented in the form of the indicators discussed.
Rocznik
Strony
90--99
Opis fizyczny
Bibliogr. 25 poz., rys.
Twórcy
  • Department of Water Supply and Sewerage, Faculty of Civil Engineering and Environmental Sciences, Bialystok University of Technology, ul. Wiejska 45E, 15-351 Bialystok, Poland
Bibliografia
  • 1. Alegre H., Covas D., Coelho S.T., Almeida M.C., Cardoso M.A. 2012. An integrated approach for infrastructure asset management of urban water systems. Water Asset Management International, 8, 10–14.
  • 2. Alperovits E., Shamir U. 1977. Design of optimal water distribution systems. Water Resour. Res., 13(6), 885–900
  • 3. Arai Y., Koizumi A., Inakazu T., Watanabe H., Fujiwara M. 2010. Study on failure rate analysis for water distribution pipelines. J. Water Supply Res. Technol., 59, 429–435.
  • 4. Carravetta A., del Giudice G., Fecarotta O., Ramos H. 2012. Energy production in water distribution networks: A PAT design strategy. Water Resour. Manag., 26, 3947–3959.
  • 5. De Marchis M., Milici B., Volpe R., Messineo A. 2016. Energy Saving in Water Distribution Network through Pump as Turbine Generators: Economic and Environmental Analysis, Energies, 9, 877.
  • 6. Description of the ISYDYW 2.0 application environment simulator of complex water supply systems. 2010 User Manual, Politechnika Krakowska.
  • 7. Fontana N., Giugni G., Portolano D. 2012. Losses reduction and energy production in water-distribution networks. J. Water Resour. Plan. Manag., 138, 237–244.
  • 8. Knapik K. 2000. Dynamiczne modele w badaniach wodociągowych, Wydawnictwo Politechniki Krakowskiej, Kraków.
  • 9. Nazif S., Karamouz M., Tabesh M., Moridi A. 2010. Pressure management model for urban water distribution networks. Water Res. Manag., 24, 437–458.
  • 10. Park S., Kim K. 2017. Development of new computational methods for identifying segments and estimating the risk of water supply interruption for a segment in water pipe networks. Desalination Water Treat., 99, 211–219.
  • 11. Praneeth P., Vasan A., Srinivasa Raju K. 2018. Pipe Size Design Optimization of Water Distribution Networks Using Water Cycle Algorithm. 4th International Conference on Harmony search. Soft Computing and Applications.
  • 12. Ramos H.M., Borga A., Simão M. 2009. New design solutions for low-power energy production in water pipe systems. Water Sci. Eng., 2, 69–84.
  • 13. Robles-Velasco A., Cortés P., Muñuzuri J., Onieva L. 2020. Prediction of pipe failures in water supply networks using logistic regression and support vector classification. Reliab. Eng. Syst. Saf., 196.
  • 14. Romano M., Kapelan Z. 2014. Adaptive water demand forecasting for near real-time management of smart water distribution systems, Environ. Modell. Softw., 60, 265.
  • 15. Sinagra M., Sammartano V., Morreale G.,Tucciarelli T. 2017. A new device for pressure control and energy recovery in water distribution networks. Water, 9, 309.
  • 16. Sitzenfrei R., Möderl M., Rauch W. 2013. Automatic generation of water distribution systems based on GIS data. Environ. Model. Softw., 47, 138–147.
  • 17. Studziński J. 2014. Some algorithms supporting the water network management by use of simulation of network hydraulic model. Industrial Simulation Conference (ISC), Hoegskolan, EUROSIS, 33–37.
  • 18. Tabesh M., Soltani J., Farmani R., Savic D. 2009. Assessing pipe failure rate and mechanical reliability of water distribution networks using data-driven modeling. J. Hydroinform, 11, 1–17.
  • 19. Todini E. 2000. Looped water distribution networks design using a resilience index based heuristic approach. Urban Water, 2, 115–122.
  • 20. Trębicka A. 2018. Dynamic model of the water distribution system as an analysis tool in the management of the Łapy water supply network. Economic and Environment, 3, 118–126.
  • 21. Trębicka A. 2018. Efficiency End Optimum Decisions in the Modelling Process of Water Distribution, Journal of Ecological Engineering, 19(6), 254–258.
  • 22. Vasan A., Slobodan P., Simonovic. 2011. Optimization of Water Distribution Networks Using Differential Evolution, Journal of Water Resources Planning and Management, ASCE, 136(2), 279–287.
  • 23. Vicente D., Garrote L., Sánchez R., Santillán D. 2015. Pressure management in water distribution systems: Current status, pro-posals, and future trends. J. Water Resour. Plan. Manag., 142.
  • 24. Walski T., Chase D.V., Sawicki D.A. 2011. Water distribution modeling. HaestadPress., Waterbury, CT, USA.
  • 25. Zheng F., Simpson A., Zecchin A. 2015. Improving the efficiency of multi-objective evolutionary algorithms through decomposition: An application to water distribution network design. Environ. Model. Softw., 69, 240–252.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4e729985-f6d2-493f-8098-ebe00cd62af4
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