Identifying the Critical Pipe in Water Distribution Network: Sensitivity Matrix Approach
- 1Korea University, College of Engineering, Department of Civil, Environmental and Architectural Engineering, Seoul, Korea, Republic of (superthgml@korea.ac.kr)
- 2Korea University, College of Engineering, School of Civil, Environmental and Architectural Engineering, Seoul, Korea, Republic of (sunnyjung625@korea.ac.kr)
Water distribution network (WDN) is a civil infrastructure for reliable water supply. Among many components in WDN, the pipe delivers the required water demand to users. Pipe bursts, the rupture of pipe wall, cause water losses out of the network and low pressure at the customer’s tap, while its impact varies at different locations. It is important to identify such critical pipes (CPs) and to minimize the failure severity. However, previous CP identification methods are generally complicated and difficult to adopt in practice, highlighting the need for the development of a novel, but practical and simple method. To that end, this study proposes a CP selection approach based on a sensitivity matrix constructed with pipe burst simulation. A sensitivity matrix is constructed by simulating a single pipe failure condition (row) and computing the variation of resulting nodal pressures (column). Then, the summation of the column element’s absolute values is formulated as a new CP index. Finally, the pipe with the maximum CP index value is defined as the most critical pipe. Moreover, this sensitivity matrix can be visualized by the heatmap, which shows the relative influence by using a color density. CP index is presented as the darkest part in the heatmap. The proposed method is demonstrated in two benchmark networks of different layouts, Hanoi and Mays. Despite its simplicity, the proposed method could identify the source pipes which are generally considered to be critical in the engineering sense.
How to cite: Kim, S. and Jung, D.: Identifying the Critical Pipe in Water Distribution Network: Sensitivity Matrix Approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13730, https://doi.org/10.5194/egusphere-egu23-13730, 2023.