Abstract

This paper presents an iterative method for the optimisation of the total costs for the rehabilitation of water-supply pipe networks with flow and pressure deficiency at the consumer nodes. The procedure is based on the exchange gradient concept of Granados for the economic design of pressurised networks. The substitution of pipe sections, relining and increase in pumping head are considered as being rehabilitation options. An initial solution is obtained for the deficient network by determining the required pumping head that would meet the pressure and discharge requirements at all the nodes. Subsequently, the pumping head is reduced in stages and for each reduction; the network of minimum cost is obtained by the substitution or relining of individual pipes in part or in full. The optimal solution is reached when the marginal annual cost of pipe rehabilitation exceeds the reduction in annual pumping costs.

Highlights

  • The basic objective of all water-supply pipe networks is to meet the flow demands at the nodes subject to a minimum pressure requirement

  • The rehabilitation of water-supply networks to meet the demand is a major task for the water-supply agencies and selecting a cost-effective method that will restore or update the system is of utmost importance

  • The process of rehabilitation of pipe networks may be divided into two distinct phases: namely, the diagnostic phase and the rehabilitation phase

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Summary

Introduction

The basic objective of all water-supply pipe networks is to meet the flow demands at the nodes subject to a minimum pressure requirement. Even when a network is initially designed to meet all the current demands and the expected increases within a reasonable future, often the networks fail to meet the flow and pressure requirements over time. This could be due to either a higher than expected rise in flow demand or due to the deterioration of the network or a combination of both. The maintenance costs, may be assumed to be common and similar in all scenarios and excluded from the optimisation process

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