Applying Simultaneously Monte Carlo Method and Dimension Reduction in Calculating the Reliability of Water Column Separation Phenomenon

Document Type : Civil Article

Authors

Civil Engineering Department, University of Sistan and Baluchestan, Zahedan, Iran

Abstract

Network reliability is one of the main effective indicators for designing and managing water distribution networks in normal or critical operating conditions. Occurrence of transient flow and sometimes the water column separation phenomenon is one of the factors of reducing reliability in water distribution networks. The increase in pressure caused by the mentioned phenomenon can cause financial and life damages, which makes it necessary to discuss the reliability of the network, occurrence the transient flow and water column separation. In this article, with the help of the Monte Carlo method and the dimension reduction method, the reliability of the water supply network has been investigated, taking the conditions of the occurrence of the water column separation phenomenon. For this purpose, the Loop system of Wang et al. (2017) was simulated in ANSYS Fluent software and the results of these simulations were called as input data for the mentioned methods in Matlab.
 Examining the reliability results showed that the occurrence of the water column separation phenomenon reached the probability of network failure to 0.247. Also, the comparison of the probability of failure of variables effective in creating pressure shows that the probability of failure caused by the valve closing time and the distance from the upstream valve with amounts 0.209 and 0.0158 have the highest and lowest values, respectively. The result of this research shows that the dimension reduction method, along with the Monte Carlo method, is a practical solution for calculating and analyzing the reliability of the water supply network.

Keywords

Main Subjects

References

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Journal of Modeling in Engineering
Volume 22, Issue 79
November 2024
Pages 311-323

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History

  • Receive Date: 28 November 2023
  • Revise Date: 18 May 2024
  • Accept Date: 25 May 2024

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