Positioning grids at critical locations for the design of water distribution network

 A water distribution network (WDN) is a critical and life-line infrastructure that transports and distributes water, an essential resource for human life, to local communities. A WDN is often modeled as a two-dimensional complex network consisting of vertices (nodes) and pipes (edges), and it has both characteristics of lattice-like and tree-like structures. With these characteristics, Son et al. (2021) proposed an approach to identify an optimal grid ratio in terms of functionality - efficiency and vulnerability - of a WDN using the lattice to tree network model (LTNM). Their result showed that the grid ratio of a real WDN is often significantly lower than the optimal value, which means that the function of the WDN can be improved by increasing the grid ratio. However, as the range of functions varies depending on where grids are located at a fixed grid ratio, simply adding pipes without considering their location does not incur a linear increase in system function. Therefore, it is important to identify the critical locations to add pipes where the functions of the system are most improved. In addition, it is necessary to determine if adding pipes is possible or not since pipe installation is not allowed for some places. In this study, we (1) identify possible spots where pipes can be added, (2) rank the identified spots where pipes are added regarding the extent of increments of function, and (3) propose an optimal (or a suboptimal) design with an optimally increased with grid ratio by adding pipes to the ranked locations in order. The results indicate that, the performance of WDNs which originally had low grid ratios are improved by adding pipes at reliable spots. The proposed approach illustrates how the structure and function of existing WDNs can be developed by modifying the proportion of grids.

 

Acknowledgments: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2019R1C1C1008017).