Conclusions - Pattern Recognition for Reliability Assessment of Water Distribution Networks - page 273

have been conducted to check the correlations between the pipe properties, specifically the
volumes and flows, as possible indicators of the loss of demand after the pipe failure.

The research discussed in Chapter 8: 'Economic Aspects of Decision Making in Reliability
Assessment of Water Distribution Networks' compares the implications of increased
investment and/or operational costs for the reliability of two network configurations with
different supplying scheme. The economical aspects have been taken into consideration by
applying the Present Worth method. The network layouts have been manipulated through
different topographical patterns, altitude ranges and economic scenarios. The network
reliability has been assessed for each of these combined scenarios, and additionally tested for
20 design scenarios comprising gradual increase of the pipe capacity and reduction of the
pumping capacity, while targeting the similar threshold pressure.

And at the end, Chapter 9: 'Decision Support Tool for Design and Reliability Assessment of
Water Distribution Networks' illustrates the network design tool named NEDRA, composed
of the modules for network generation and filtering, initialisation and optimisation on the
least-cost diameter, diagnostics of network geometric-, hydraulic-, and economic parameters
and the assessment of its resilience. Computations using this software can be done for single
network or a sequence of networks of virtually unlimited size and number, mutually similar
or different in properties. The tool has been demonstrated on a design example of a gravity
network of 50 nodes. 13,000 network layouts have been generated and further filtered to
arrive at 1817 layouts satisfying the configuration of the network template. Those have been
then optimised and analysed using various reliability measures against the costs comprising
the network investment, operation and maintenance, eventually arriving at the most
economically justified and reliable layout.

10.2 CONCLUSIONS IN RESPONSE TO RESEARCH QUESTIONS AND

HYPOTHESES

The conclusions presented in Chapters 3 to 9 have been reformulated to directly address the
research questions raised in Chapter 2.

Is the available demand fraction (ADF) true descriptor of network reliability? The ADF is
certainly the most transparent index because this is the only value between 0 and 1 that can
be directly converted into the loss of demand. Nevertheless, the average value of ADF may
hide pipe bursts causing rather significant loss of demand. That is why the only complete
picture about the network reliability can be obtained from the hydraulic reliability diagram
(HRD).

Are the demand-driven based reliability measures, sufficiently accurate? The two reliability
measures from the literature used for benchmarking, the resilience index of Todini ( I r ), and
the network resilience of Prasad and Park ( I n ), have proven to follow the same trend as the
indices developed in this research, in the first place the NBI. Nevertheless, the I r and
specifically the I n , evaluated some networks with pretty low values, which has been in
contradiction with relatively high value of ADF avg for these networks. This leads towards a
conclusion that two indices from the literature are, as their formulas also show, indeed mostly
sensitive on the node heads and to a lesser degree on the network connectivity. The side
effect here is that in the extreme events of pressure loss, both indices may yield arbitrarily
high- either even negative value.