scholarly journals Assessment of optimal water distribution systems design under steady-state and transient conditions due to pipe roughness uncertainty

Author(s):  
Hamdy A. El-Ghandour ◽  
Samer M. Elabd ◽  
Emad Elbeltagi
2019 ◽  
Vol 68 (6) ◽  
pp. 399-410
Author(s):  
Denis Nono ◽  
Innocent Basupi

Abstract Booster chlorination designs have been widely based on predefined (deterministic) network conditions and they perform poorly under uncertainty in water distribution systems (WDSs). This paper presents a scenario-based robust optimisation approach which was developed to obtain booster chlorination designs that withstand uncertain network operations and water demand conditions in the WDSs. An optimisation problem was formulated to minimise mass injection rates and the risk of chlorine disinfection. This problem was solved by a non-dominated sorting genetic algorithm (NSGA-II). The proposed approach was demonstrated using the Phakalane network in Botswana. The results present robust booster chlorination (RBC) designs, which indicate the number of boosters, locations and injection rates in the network. The performance of RBC designs evaluated under uncertainty reveals lower risks of chlorine disinfection compared to deterministic-based designs. The proposed approach obtains booster chlorination designs that respond better to uncertainty in the operations of WDSs.


2010 ◽  
Vol 12 (4) ◽  
pp. 424-445 ◽  
Author(s):  
Stefano Alvisi ◽  
Marco Franchini

This paper presents a procedure based on the use of grey numbers for the calibration (with uncertainty) of pipe roughness in water distribution systems. The pipe roughness uncertainty is represented through the grey number amplitude (or interval). The procedure is of a wholly general nature and can be applied for the calibration (with uncertainty) of other parameters or quantities, such as nodal demands. In this paper, for the purpose of roughness calibration, a certain number of nodal head measurements made under different demand conditions is assumed to be available at different locations (nodes); all other topological and geometric characteristics of the system are considered to be known exactly. The general approach to pipe roughness calibration (taking account of uncertainty) focuses on identifying the grey roughness values which produce grey head values at the measuring nodes such as to encompass the observed values grouped on the basis of the different demand scenarios and, at the same time, have as small an ‘amplitude’ as possible. The proposed procedure was applied to two synthetic case studies and to one real network. The tests on the synthetic case studies show that the proposed procedure is able to correctly solve the inverse problem, i.e. it can identify the known grey roughness numbers even when they overlap; the same applies when the known grey roughness numbers collapse into known white roughness numbers. The test on the real case offers the possibility of highlighting the potentials of the procedure when applied within a context where measurement errors and other uncertainties are present. The procedure entails computing times that may become lengthy. However, it is possible to reduce these computing times considerably by replacing the hydraulic simulator—to which a number of calls must be made during the calibration procedure (for objective function evaluation)—with an approximation based on a first-order Taylor series expansion. This approach introduces acceptable approximations within the context of the problem considered.


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