Calvin Siew

Pressure-Dependent EPANET Extension

In water distribution systems (WDSs), the available flow at a demand node is dependent on the pressure at that node. When a network is lacking in pressure, not all consumer demands will be met in full. In this context, the assumption that all demands are fully satisfied regardless of the pressure in the system becomes unreasonable and represents the main limitation of the conventional demand driven analysis (DDA) approach to WDS modelling. A realistic depiction of the network performance can only be attained by considering demands to be pressure dependent. This paper presents an extension of the renowned DDA based hydraulic simulator EPANET 2 to incorporate pressure-dependent demands. This extension is termed “EPANET-PDX” (pressure-dependent extension) herein. The utilization of a continuous nodal pressure-flow function coupled with a line search and backtracking procedure greatly enhance the algorithm’s convergence rate and robustness. Simulations of real life networks consisting of multiple sources, pipes, valves and pumps were successfully executed and results are presented herein. Excellent modelling performance was achieved for analysing both normal and pressure deficient conditions of the WDSs. Detailed computational efficiency results of EPANET-PDX with reference to EPANET 2 are included as well.

Penalty-Free Feasibility Boundary Convergent Multi-Objective Evolutionary Algorithm for the Optimization of Water Distribution Systems

This paper presents a new penalty-free multi-objective evolutionary approach (PFMOEA) for the optimization of water distribution systems (WDSs). The proposed approach utilizes pressure dependent analysis (PDA) to develop a multi-objective evolutionary search. PDA is able to simulate both normal and pressure deficient networks and provides the means to accurately and rapidly identify the feasible region of the solution space, effectively locating global or near global optimal solutions along its active constraint boundary. The significant advantage of this method over previous methods is that it eliminates the need for ad-hoc penalty functions, additional “boundary search” parameters, or special constraint handling procedures. Conceptually, the approach is downright straightforward and probably the simplest hitherto. The PFMOEA has been applied to several WDS benchmarks and its performance examined. It is demonstrated that the approach is highly robust and efficient in locating optimal solutions. Superior results in terms of the initial network construction cost and number of hydraulic simulations required were obtained. The improvements are demonstrated through comparisons with previously published solutions from the literature.

Assessment of penalty-free multi-objective evolutionary optimization approach for the design and rehabilitation of water distribution systems

This paper describes a penalty-free multi-objective evolutionary optimization approach for the phased whole-life design and rehabilitation of water distribution systems. The optimization model considers the initial construction, rehabilitation and upgrading costs. Repairs and pipe failure costs are included. The model also takes into consideration the deterioration over time of both the structural integrity and hydraulic capacity of every pipe. The fitness of each solution is determined from the trade-off between its lifetime costs and its actual hydraulic properties. The hydraulic analysis approach used, known as pressure-dependent modelling, considers explicitly the pressure dependency of the water supply consumers receive. Results for two sample networks in the literature are included that show the algorithm is stable and finds optimal and near-optimal solutions reliably and efficiently. The results also suggest that the evolutionary sampling efficiency is very high. In other words, the number of solutions evolved and analysed on average before finding a near-optimal solution is small in comparison to the total number of feasible and infeasible solutions. We found better solutions than those reported previously in the literature for the two networks considered. For the Kadu network, for example, the new best solution costs Rs125,460,980—a significant improvement. Additional statistics that are based on extensive testing are included.

Design optimization of cold-formed steel portal frames taking into account the effect of building topology

Cold-formed steel portal frames are a popular form of construction for low-rise commercial, light industrial and agricultural buildings with spans of up to 20 m. In this article, a real-coded genetic algorithm is described that is used to minimize the cost of the main frame of such buildings. The key decision variables considered in this proposed algorithm consist of both the spacing and pitch of the frame as continuous variables, as well as the discrete section sizes. A routine taking the structural analysis and frame design for cold-formed steel sections is embedded into a genetic algorithm. The results show that the real-coded genetic algorithm handles effectively the mixture of design variables, with high robustness and consistency in achieving the optimum solution. All wind load combinations according to Australian code are considered in this research. Results for frames with knee braces are also included, for which the optimization achieved even larger savings in cost.

Penalty-free multi-objective evolutionary approach to optimization of anytown water distribution network

This paper describes the development and application of a new multi-objective evolutionary optimization approach for the design and upgrading of water distribution systems with multiple pumps and service reservoirs. The optimization model employs a pressure-driven analysis simulator that accounts for the minimum node pressure constraints and conservation of mass and energy. Pump scheduling, tank siting and tank design are integrated seamlessly in the optimization without introducing additional heuristic procedures. The computational solution of the optimization problem is entirely penalty-free, thanks to pressure-driven analysis and the inclusion of explicit criteria for tank depletion and replenishment. The model was applied to the Anytown network that is a benchmark optimization problem. Many new solutions were achieved that are cheaper and offer superior performance compared to previous solutions in the literature. Detailed and extensive simulations of the solutions achieved were carried out. Spatial and temporal variations in water quality were investigated by simulating the chlorine residual and disinfection by-products in addition to water age. The hydraulic requirements were satisfied; efficiency of pumps was consistently high; effective operation of the new and existing tanks was achieved; water quality was improved; and overall computational efficiency was high. The formulation is entirely generic.

PRESSURE DEPENDENT EPANET EXTENSION: EXTENDED PERIOD SIMULATION

The performance of water distribution networks (WDNs) is occasionally affected by planned (system maintenance) and unplanned (fire events and main bursts) interruptions. There is always a need for water companies to study the impact of these potentially pressure deficient situations on the WDNs level of service in a realistic and practical manner. In reality, such events occur over a period of time and are usually modeled using extended period simulation (EPS). This paper presents an EPS model capable of assessing the network performance effectively and accurately under these conditions. The proposed extended period simulation model is based on pressure driven analysis (PDA) and is capable of obtaining the accurate nodal pressures and actual flows delivered at demand nodes. Simulations on the “Anytown” network were carried out to demonstrate the capability of the model. Results obtained highlighted the superiority of PDA over DDA in simulating pressure deficient networks.

Comparison of surrogate measures for the reliability and redundancy of water distribution systems

An investigation into the effectiveness of surrogate measures for the hydraulic reliability and/or redundancy of water distribution systems is presented. The measures considered are statistical flow entropy, resilience index, network resilience and surplus power factor. Looped network designs that are maximally noncommittal to the surrogate reliability measures were considered. In other words, the networks were designed by multi-objective evolutionary optimization free of any influence from the surrogate measures. The designs were then assessed using each surrogate measure and two accurate but computationally intensive measures namely hydraulic reliability and pipe-failure tolerance. The results indicate that by utilising statistical flow entropy, the reliability of the network can be reasonably approximated, with substantial savings in computational effort. The results for the other surrogate measures were often inconsistent. Two networks in the literature were considered. One example involved a range of alternative network topologies. In the other example, based on whole-life cost accounting, alternative design and upgrading schemes for a 20-year design horizon were considered. Pressure-dependent hydraulic modelling was used to simulate pipe failures for the reliability calculations.

Penalty-free multi-objective evolutionary optimization of water distribution systems

A major limitation of the widely used evolutionary optimization (EO) methods is their inability to handle constraints directly. To address this issue, penalty function methods have been used in most EO applications involving constrained problems such as those of the water distributions networks (WDNs). However, the disadvantage of penalty function methods is that the parameters involved require great expertise in calibration with numerous time consuming trial runs. In addition, penalty parameters are case sensitive and do not necessarily steer the EO search toward the best solutions in every situation. This paper presents a penalty-free multi-objective evolutionary approach (PFMOEA) for the optimization of water distribution networks. The basis behind this approach is to involve the pressure dependent analysis (PDA) in developing a multi-objective evolutionary search. PDA is capable of simulating both normal and pressure deficient networks and provides a quick and precise means to identify the feasible region of the solution space. The proposed PFMOEA couples the renowned NSGA II with an enhanced seamless version of EPANET 2 which is capable of PDA. The PFMOEA has been applied to several WDN benchmarks. Excellent results in terms of the initial network cost and number of hydraulic simulations required were obtained. Comprehensive discussions along with comparisons of solutions from previous studies are presented herein.

Augmented Gradient Method for Head Dependent Modelling of Water Distribution Networks

When analysing a pressure deficient network, it is crucial that the pressure dependent nature of nodal outflows be taken into account. The head dependent analysis (HDA) produces an accurate representation of the nodal outflows and network hydraulic performance. This is essential when modelling pipe leakages, network redundancy and reliability. These are vital aspects often considered in the optimization of a water distribution system (WDS). This paper describes an approach for head dependent analysis in which an embedded function for the head-outflow relationship is incorporated in the Gradient Method (GM). The procedure is capable of simulating both normal and deficient network operating conditions effectively. Results based on networks from the literature show that the proposed method is robust and converges smoothly and rapidly.

Penalty-free evolutionary algorithm optimization for the long term rehabilitation and upgrading of water distribution systems

The rehabilitation and upgrading of a water distribution system (WDS) involves a great amount of capital and hence the optimization of factors such as the phasing, timing and magnitude of the upgrading with regard to cost is a necessity. This paper presents a penalty-free multi-objective evolutionary algorithm (PFMOEA) model for the optimal long term upgrading of water distribution systems. The model couples a pressure dependent analysis within a multi-objective optimization frame work and has proven to be effective and efficient in locating the optimal/ near optimal solution. Herein, a real life network in Wobulenzi was used to demonstrate the efficacy of the model. Results generated by PFMOEA and the conventional linear programming (LP) are presented and compared. It is shown that PFMOEA outperforms LP in that it succeeded in finding lower network rehabilitation and upgrading cost.