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Correlation analysis between energy indices and source-to-node shortest pathway of water distribution network

상수도관망 수원-절점 최소거리와 에너지 지표 상관성 분석

  • Lee, Seungyub (Department of Civil and Environmental Engineering, University of Utah) ;
  • Jung, Donghwi (Department of Civil Engineering, Keimyung University)
  • 이승엽 (유타대학교 토목환경공학과) ;
  • 정동휘 (계명대학교 토목공학과)
  • Received : 2018.08.25
  • Accepted : 2018.09.13
  • Published : 2018.11.30

Abstract

Connectivity between water source and demand node can be served as a critical system performance indicator of the degree of water distribution network (WDN)' failure severity under abnormal conditions. Graph theory-based approaches have been widely applied to quantify the connectivity due to WDN's graph-like topological feature. However, most previous studies used undirected-unweighted graph theory which is not proper to WDN. In this study, the directed-weighted graph theory was applied for WDN connectivity analyses. We also proposed novel connectivity indicators, Source-to-Node Shortest Pathway (SNSP) and SNSP-Degree (SNSP-D) which is an inverse of the SNSP value, that does not require complicate hydraulic simulation of a WDN of interest. The proposed SNSP-D index was demonstrated in total 42 networks in J City, South Korea in which Pearson Correlation Coefficient (PCC) between the proposed SNSP-D and four other system performance indicators was computed: three resilience indexes and an energy efficiency metric. It was confirmed that a system representative value of the SNSP-D has strong correlation with all resilience and energy efficiency indexes (PCC = 0.87 on average). Especially, PCC was higher than 0.93 with modified resilience index (MRI) and energy efficiency indicator. In addition, a multiple linear regression analysis was performed to identify the system hydraulic characteristic factors that affect the correlation between SNSP-D and other system performance indicators. The proposed SNSP is expected to be served as a useful surrogate measure of resilience and/or energy efficiency indexes in practice.

수원과 수용가 간 연결성은 비정상상황 시 상수도관망의 기능 유지 정도를 나타내는 시스템 특성 중 하나이다. 상수도관망은 점과 선으로 구성된 그래프로 간략화 될 수 있기 때문에, 연결성 평가를 위해 주로 그래프 이론이 적용되었다. 하지만, 대부분의 연구는 상수도관망에 적합하지 않은 무향-비가중 그래프 이론을 적용하였다. 본 연구에서는 유향-가중 그래프 이론을 상수도관망에 적용하였으며, 이를 기반으로 복잡한 수리해석 없이 상수도관망 연결성을 평가할 수 있는 지표인 SNSP (Source to Node Shortest Pathway)와 이의 역수인 SNSP-Degree (SNSP-D)를 제안하였다. 국내 J시 42개의 상수도관망을 이용하여 개발된 SNSP와 기존 상수도관망 성능평가지표 사이의 상관성 분석을 수행 및 검증하였다. 기존 상수도관망 성능평가지표는 수리해석 결과를 지표 계산에 이용하는 3개의 회복력(Resilience) 지표와 에너지 효율 지표이다. 분석 결과, SNSP의 역수인 SNSP-D의 합과 기존 상수도관망 성능지표 사이에 평균적으로 0.87 이상의 높은 피어슨 상관계수(Pearson Correlation Coefficient, PCC) 값이 도출되었다. 특히, 회복력 지표 중 하나인 Modified Resilience Index (MRI)와 에너지 효율 지표의 경우 PCC 0.93 이상의 높은 상관관계를 가지는 것으로 나타났다. 또한 다중 회귀 분석을 통해 SNSP-D와 회복력 및 에너지 효율 간의 상관성에 영향을 미치는 수리학적 변인을 확인하였다. 본 연구에서 제안한 SNSP 지표가 상수도관망의 대략적인 회복력 및 에너지 효율 수준을 알려줄 수 있는 지표로 실무에서 널리 활용될 것으로 기대된다.

Keywords

References

  1. Alenazi, M. J., and Sterbenz, J. P. (2015), "Comprehensive comparison and accuracy of graph metrics in predicting network resilience.", 11th International Conference on Design of Reliable Communication Networks (DRCN2015), IEEE, pp. 157-164.
  2. Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O'Rourke, T. D., Reinhorn, A. M., Shinozuka, M., Tierney, K., Wallace, W. A., and von Winterfeldt, D. (2003). "A Framework to quantitatively assess and enhance the seismic resilience of communities." Earthquake spectra. Vol. 19, No. 4, pp. 733-752. https://doi.org/10.1193/1.1623497
  3. Davidson, J., Bouchart, F., Cavill, S., and Jowitt, P. (2005). "Realtime connectivity modeling of water distribution networks to predict contamination spread." Journal of Computing in Civil Engineering. Vol. 19, No. 4, pp. 377-386. https://doi.org/10.1061/(ASCE)0887-3801(2005)19:4(377)
  4. Di Nardo, A., Di Natale, M., Giudicianni, C., Greco, R., and Santonastaso, G. F. (2017). "Complex network and fractal theory for the assessment of water distribution network resilience to pipe failures." Water Science and Technology: Water Supply, ws2017124.
  5. Dijkstra, E. W. (1959). "A note on two problems in connexion with graphs" (PDF). Numerische Mathematik. Vol. 1, pp. 269-271, doi: 10.1007/BF01386390.
  6. Herrera, M., Abraham, E., and Stoianov, I. (2016). "A graph-theoretic framework for assessing the resilience of sectorised water distribution networks." Water Resources Management, Vol. 30, No. 5, pp. 1685-1699. https://doi.org/10.1007/s11269-016-1245-6
  7. Jun, H. (2006). "An evaluation of the pipe failure impact in a water distribution system considering subsystem isolation." Journal of Korean Water Resource Association, Vol. 39, No. 2, pp. 89-98. https://doi.org/10.3741/JKWRA.2006.39.2.089
  8. Jung, D., and Kim, J. (2018). "Water Distribution System Design to Minimize Costs and Maximize Topological and Hydraulic Reliability." Journal of Water Resources Planning and Management, Vol. 144, No. 9, p. 06018005. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000975
  9. Kessler, A., Ormsbee, L., and Shamir, U., (1990). "A methodology for least-cost design of invulnerable water distribution networks." Civil Engineering Systems, Vol. 7, No. 1, pp. 20-28. https://doi.org/10.1080/02630259008970566
  10. Ministry of Environment (2010). Water distribution system stadards.
  11. Park, J. H., Han, K. Y., (1998). "Application of Graph Theory for the Pipe Network Analysis." Journal of Korean Water Resource Association, Vol. 31, No. 4, pp. 439-448.
  12. Prasad, T. D., and Park, N. S. (2004). "Multiobjective genetic algorithms for design of water distribution networks." Journal of Water Resources Planning and Management. Vol. 130, No. 1, pp. 73-82. https://doi.org/10.1061/(ASCE)0733-9496(2004)130:1(73)
  13. Price, E., and Ostfeld, A. (2015). "Graph theory modeling approach for optimal operation of water distribution systems." Journal of Hydraulic Engineering, Vol. 142, No. 3, p. 04015061. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001099
  14. Rhee, K. H., Oh, C. J., and Kang, Y. D. (2001). "Valve Searching Algorithm for Pipeline Control". Journal of Korean Society of Water & Wastewater, Vol. 15, No. 3, pp. 222-228.
  15. Rossman, L. A. (2000). "EPANET 2: users manual."
  16. Sonak, V. V., and Bhave, P. R. (1993). "Global optimum tree solution for single-source looped water distribution networks subjected to a single loading pattern." Water Resources Research, Vol. 29, No. 7, pp. 2437-2443. https://doi.org/10.1029/93WR00289
  17. Todini, E. (2000). "Looped water distribution networks design using a resilience index based heuristic approach." Urban water, Vol. 2, No. 2, pp. 115-122. https://doi.org/10.1016/S1462-0758(00)00049-2
  18. Yazdani, A., and Jeffrey, P. (2012). "Water distribution system vulnerability analysis using weighted and directed network models." Water Resources Research, Vol. 48, No. 6.
  19. Yazdani, A., and Jeffrey, P. (2010). "A complex network approach to robustness and vulnerability of spatially organized water distribution networks." In 12th annual Water Distribution Systems Analysis conference, WDSA2010, Tucson, USA. pp. 129-130.
  20. Yazdani, A., and Jeffrey, P. (2011). "Applying network theory to quantify the redundancy and structural robustness of water distribution systems." Journal of Water Resources Planning and Management, Vol. 138, No. 2, pp. 153-161. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000159
  21. Yazdani, A., Otoo, R. A., and Jeffrey, P. (2011). "Resilience enhancing expansion strategies for water distribution systems: A network theory approach." Environmental Modelling & Software, Vol. 26, No. 12, pp. 1574-1582. https://doi.org/10.1016/j.envsoft.2011.07.016
  22. Yoo, D. G., Chung, G., Sadollah, A., and Kim, J. H. (2015). "Applications of network analysis and multi-objective genetic algorithm for selecting optimal water quality sensor locations in water distribution networks." KSCE Journal of Civil Engineering, Vol. 19, No. 7, pp. 2333-2344. https://doi.org/10.1007/s12205-015-0273-8