single-dr.php

JDR Vol.12 No.3 pp. 569-577
(2017)
doi: 10.20965/jdr.2017.p0569

Paper:

A Planning Model for Optimal Deployment of Leak Sensors in a Water Pipeline Network

Yasuhiro Arai, Akira Koizumi, Toyono Inakazu, and Wako Kawamura

Department of Civil and Environmental Engineering, Tokyo Metropolitan University (TMU)
1-1 Minami-Osawa, Hachioji-shi, Tokyo 192-0397, Japan

Corresponding author

Received:
August 31, 2016
Accepted:
March 31, 2017
Online released:
May 29, 2017
Published:
June 1, 2017
Keywords:
water pipeline, water leakage, k-median problem, facility deployment optimization plan
Abstract
When leak sensors are actually mounted on water pipelines, they are deployed at auxiliary equipment such as gate valves and fire hydrants located every few hundred meters. The total length of the water pipelines laid throughout Japan is approximately 650,000 km. Assuming a length of several thousand kilometers for a pipeline in a given target area, the possible locations for deploying sensors can number in the tens of thousands. Mounting sensors at all the possible locations would not be efficient, either economically or from a maintenance standpoint. In a pipeline network that spreads out horizontally, it is important to ensure that the sensors are deployed in a way to maximize their effectiveness at detecting water leakages. To this end, a method is needed for objectively planning the deployment of a given number of sensors on the optimal gate valves and hydrants. This study, aimed at the optimal deployment of leak sensors in a water pipeline network, proposes a planning model applying the k-median problem, a type of mathematical optimization problem, and verifies the effectiveness of this model via case studies.
Cite this article as:
Y. Arai, A. Koizumi, T. Inakazu, and W. Kawamura, “A Planning Model for Optimal Deployment of Leak Sensors in a Water Pipeline Network,” J. Disaster Res., Vol.12 No.3, pp. 569-577, 2017.
Data files:
References
  1. [1] Council on Competitiveness-Nippon: Establishment of Resilient Economy (Final report of research group in F.Y.2012), [Online] http://www.cocn.jp/thema56-L.pdf [accessed Feb. 2016]
  2. [2] Cabinet Office, Government of Japan: SIP(Cross-ministerial Strategic Innovation Promotion Program) 2015 – Japan’s first science and technology innovation opens the future –, [Online] http://www8.cao.go.jp/cstp/panhu/sip2015/34-37.pdf [accessed Feb. 2016]
  3. [3] H. Kondo and H. Abe, “Development of water leakage survey technology with high sensitivity sensor and verification of practicality,” Proceedings of National Conference of Japan Waterworks Association, pp. 462-463, 2015.
  4. [4] Y. Kawakami, K. Gouto, Y. Taguchi, S. Tamura, J. Kohatsu, K. Suzuki, and H. Ariyoshi, “Efficient maintenance of important pipelines using constant monitoring of sound pressure data,” Proceedings of National Conference of Japan Waterworks Association, pp. 460-461, 2015.
  5. [5] K. Fukushima, Y. Maruta, K. Izumi, S. Itoh, A. Yoshizawa, and T. Tanaka, “Water leakage monitoring service combining sensor and ICT,” NEC Tech. J., Vol.67, No.1, pp. 11-114, 2014.
  6. [6] Y. Arai, A. Koizumi, T. Inakazu, and W. Kawamura, “A planning model for optimal deployment of leak sensors in a water pipeline network,” J. Japan Soc. Civ. Eng. Ser. G (Environmental Res.), Vol.72, No.6, pp. II_333-II_340, 2016.
  7. [7] M. Kubo, Logistics Engineering, pp. 150-162, Asakura Publishing Co., Ltd., 2003.
  8. [8] N. Machida, T. Masaoka, M. Ohta, and T. Takeuchi, “Evaluation of existing evacuation places from the viewpoint of p-median problem – Case study in Aki city –,” Proceedings of 15th JSCE Technical research conference (Shikoku division), pp. 215-216, 2009.
  9. [9] M. Kubo, J. P. Pedroso, M. Muramatsu, and A. Rais, “Mathematical Optimization; Solving Problems using Gurobi and Python,” pp. 48-49, Kindai kagaku sha Co., Ltd., 2012.
  10. [10] GE Network Solutions, Smallworld Core Spatial Technology User’s Manual Classic user interface, pp. [16-1]-[16-20].
  11. [11] October Sky Co., Ltd., Gurobi Optiomizer/Benchmark, [Online] http://www.octobersky.jp/products/gurobi/gurobi_benchmark.html [accessed Feb. 2016]
  12. [12] A. Koizumi, Y. Arai, T. Inakazu, T. Kunizane, H. Umano, and H. Ariyoshi, “Research on mesh data diagnosis model for safety evaluation of water pipeline system,” Environ. Syst. Res., Japan Soc. Civ. Eng., Vol.36, pp. 115-123, 2008.
  13. [13] Y. Arai, T. Inakazu, A. Koizumi, H. Ariyoshi, M. Kim, and J. Koo, “Analysis of the Effects of Water Leakage Prevention Management Using Mesh Data of Water Distribution Networks,” IWA Water Loss, No.110, 8 pages, 2012.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Nov. 04, 2024