Rehabilitation Of Water Distribution Systems Research Articles

Multi‐criteria analysis applied to ranking rehabilitation strategies of water distribution networks

Rehabilitation of water distribution systems is a complex task that water companies have to tackle continually to keep high‐quality service. The larger and more complex the network, the harder to make decisions about the network maintenance strategy to be implemented. Considering pipe replacement as a strategy for water network rehabilitation, this work presents a combination of water distribution system analysis and multi‐criteria analysis to rank alternatives for pipe replacement. A set of eight performance criteria is used to evaluate the rehabilitation alternatives. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is herein adopted to rank the solutions, coupled with a final sensitivity analysis on criteria weights. The obtained results point out as pipe replacement is an essential strategy for rehabilitation since the eight evaluation criteria are improved. The sensitivity analysis shows the best solutions' robustness, with just a few variations in their position in the ranking. The most frequent best solution is then hydraulically evaluated, showing the real benefits of pipe replacement in terms of pressure deficit reduction.

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

This paper presents a methodology to find the optimal design or rehabilitation of water distribution system (WDS) under both steady-state and transient conditions. Then, assessing the obtained optimal solution and studying its stability, reliability, due to uncertainty in pipe roughness coefficients (CHW). The WDS optimization objective is to minimize the rehabilitation cost by installing new pipes parallel to the existing ones achieving all hydraulic constraints. For this purpose, particle swarm optimization (PSO) is used as an optimization tool and Monte Carlo simulation (MCS) is applied to generate multiple realizations of CHW for different coefficient of variation (COVCHW). A comparison between crisp shape and continuous shape (S-shape) fuzzy membership functions is carried out to study the hydraulic availability indices to nodal pressure head values resulted from pipe roughness uncertainty. Both steady-state nodal and system reliabilities are estimated while, only the transient system reliability is calculated for the obtained optimal solution. The proposed methodology is applied on the New York City tunnel network (NYCTN) and the corresponding reliability is analyzed. Results show that as pipe roughness uncertainty increases, WDS reliability decreases.

Impact of problem formulations, pipe selection methods, and optimization algorithms on the rehabilitation of water distribution systems

AbstractGiven the continuous aging of pipeline infrastructure buried underground, water utilities need to make a strategic plan on how to maintain the entire water distribution systems (WDSs) to ensure the required standard of supply. This paper investigates the nexus of three key factors that have a significant impact on the decision-making process of the rehabilitation plan for WDSs. The factors considered include the problem formulations, the pipe selection methods for identifying critical components of WDSs, and the multi-objective evolutionary algorithms (MOEAs). The nexus was revealed by considering all the combinations of two variants for each factor. The optimal rehabilitation problem of the Exeter network was used as a case study. Results exhibit that the problem formulation determined the range of Pareto fronts essentially, which should give the highest priority in the decision-making process. The pipe selection method played a secondary role, mainly affecting the shape of Pareto fronts. Optimization algorithms also had a considerable impact on the optimality of solutions, subject to their characteristics and parameter settings. This paper also highlights that breakthroughs need to focus on these key factors to facilitate a more cost-effective solution to the rehabilitation of large WDSs.

A comprehensive criteria-based multi-attribute decision-making model for rehabilitation of water distribution systems

The main objective of this work is to develop a comprehensive criteria-based multi-attribute decision-making model to plan the rehabilitation of water networks. Among the main features of this model is the capability to simultaneously analyse comprehensive criteria for the rehabilitation of water networks; where there is a significant uncertainty within the operational data. In this model, which is called as WDSR model, using a fuzzy TOPSIS technique, it is possible to adjust the criteria based on the local conditions, and to weight them based on the group decision-making of experts. In this paper, using the WDSR model, the rehabilitation plan of the ‘Anytown’ water network is prioritised through two methods. The first method uses a predefined template of WDSR, and the second uses a local template based on the conditions within the study area. The obtained results show the potential of the WDSR in the rehabilitation planning of water networks, where is encountered with numerous criteria, a significant uncertainty in the recorded data and hesitation in group decision-making of experts. It was found that, for rehabilitation of network zones, predefined template of WDSR is preferred, while for pipe rehabilitation, it is essential to use local template layer.

CORRELATION BETWEEN COST AND PERFORMANCE OF DRINKING WATER PIPE NETWORK DURING NORMAL OPERATING CONDITIONS

Now a days, large expenditures are spent on maintenance and rehabilitation of water distribution systems due to lack of performance. This research work is concerned with investigating the relationship between the cost of a certain water distribution network design and its performance during normal operating conditions. Noting that performance is expressed by an efficiency index. By analyzing eighteen alternative designs of a particular networks, it has been concluded that the efficiency of water delivery is inversely proportional to the cost of a water distribution system with a strong coefficient of determination. Also, increasing the number of pipes in a network would result in more leakage problems and subsequently lower efficiency. Finally, the proposed equation that describes the cost-efficiency relationship can be effectively utilized to determine the cost of a design with desirable efficiency or the efficiency corresponding to a known cost.

Rehabilitation of a Water Distribution System Using Sequential Multiobjective Optimization Models

Identification of the optimal rehabilitation plan for a large water distribution system (WDS) with a substantial number of decision variables is a challenging task, especially when no supercomputer facilities are available. This paper presents an initiative methodology for the rehabilitation of WDS based on three sequential stages of multiobjective optimization models for gradually identifying the best-known Pareto front (PF). A two-objective optimization model is used in the first two stages where the objectives are to minimize rehabilitated infrastructure costs and operational costs. The optimization model in the first stage applies to a skeletonized WDS. The PFs obtained in Stage 1 are further improved in Stage 2 using the same two-objective optimization problem but for the full network. The third stage employs a three-objective optimization model by minimizing the cost of additional pressure reducing valves (PRVs) as the third objective. The suggested methodology was demonstrated through use of a real and large WDS from the literature. Results show the efficiency of the suggested methodology to achieve the optimal solutions for a large WDS in a reasonable computational time. Results also suggest the minimum total costs that will be obtained once maximum leakage reduction is achieved due to maximum possible pipeline rehabilitation without increasing the existing tanks.

Water Distribution System Rehabilitation under Climate Change Mitigation Scenarios in Canada

Many countries are considering policy instruments such as a carbon tax and economic discounting to reduce greenhouse gas (GHG) emissions in key sectors like the water sector. This paper examines the impact of economic discounting and a carbon tax on the optimization of water main rehabilitation. A new pipe rehabilitation optimization algorithm that accounts for GHGs was developed and applied to the Fairfield water distribution system in Amherstview, Ontario, Canada. GHG intensity factors for the provinces of Ontario (low-carbon) and Alberta (high-carbon) were applied to the Fairfield network. In both cases, adopting a low discount rate and levying a carbon tax had a weak effect in reducing energy use, GHG emissions, pipe breaks, and leakage. Further, a low discount rate and a carbon tax encouraged the search process to invest in rehabilitation early in the planning period to reduce continuing leakage, pipe repair, energy, and GHG costs.

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.

Reducing the Complexity of Multiobjective Water Distribution System Optimization through Global Sensitivity Analysis

AbstractThis study investigates the use of global sensitivity analysis as a screening tool to reduce the computational demands associated with multiobjective design and rehabilitation of water distribution systems (WDS). Sobol’s method is used to screen insensitive decision variables and guide the formulation of reduced complexity WDS optimization problems (i.e., fewer decision variables). This sensitivity-informed problem decomposition dramatically reduces the computational demands associated with attaining high-quality approximations for optimal WDS trade-offs. This study demonstrates that the results for the reduced-complexity WDS problems can then be used to precondition and significantly enhance full search of the original WDS problem. Two case studies of increasing complexity—the New York Tunnels network and the Anytown network—are used to demonstrate the proposed methodology. In both cases, sensitivity analysis results reveal that WDS performance is strongly controlled by a small proportion of deci...

Fuzzy probabilistic design of water distribution networks

The primary aim of this paper is to present a fuzzy probabilistic approach for optimal design and rehabilitation of water distribution systems, combining aleatoric and epistemic uncertainties in a unified framework. The randomness and imprecision in future water consumption are characterized using fuzzy random variables whose realizations are not real but fuzzy numbers, and the nodal head requirements are represented by fuzzy sets, reflecting the imprecision in customers' requirements. The optimal design problem is formulated as a two‐objective optimization problem, with minimization of total design cost and maximization of system performance as objectives. The system performance is measured by the fuzzy random reliability, defined as the probability that the fuzzy head requirements are satisfied across all network nodes. The satisfactory degree is represented by necessity measure or belief measure in the sense of the Dempster‐Shafer theory of evidence. An efficient algorithm is proposed, within a Monte Carlo procedure, to calculate the fuzzy random system reliability and is effectively combined with the nondominated sorting genetic algorithm II (NSGAII) to derive the Pareto optimal design solutions. The newly proposed methodology is demonstrated with two case studies: the New York tunnels network and Hanoi network. The results from both cases indicate that the new methodology can effectively accommodate and handle various aleatoric and epistemic uncertainty sources arising from the design process and can provide optimal design solutions that are not only cost‐effective but also have higher reliability to cope with severe future uncertainties.

Prioritised rehabilitation of water distribution networks using dissipated power concept to reduce non-revenue water

This paper presents a new prioritisation approach to the problem of rehabilitation of water distribution systems. It consists in a algorithm that, based on the resilience index and on the unitary power concepts, selects the most important pipes to be replaced in order to achieve two main objectives: first, to reduce loss of water due to leakage by decreasing and levelling pressures along the entire network; second, to reduce the dissipated energy in the system, making it more efficient and reliable. Additionally, the implemented algorithm finds profitable rehabilitation schemes and allows the identification of the appropriate point at which, according to the economic and hydraulic criteria established by the user, the process of replacing pipes should be stopped. This paper includes three case studies – one hypothetical and two real water distribution systems – in which the algorithm was tested. For these networks hydraulically and economically near-optimal rehabilitation schemes were achieved.

Application of Artificial Neural Networks (ANN) to model the failure of urban water mains

This paper presents an application of Artificial Neural Networks (ANN) to model the failure rate and estimate the optimal replacement time for the individual pipes in an urban water distribution system. The performances of the ANN are examined using a 14-year data set collected in a city in the north of France. The first part of the paper presents the collected data. The second part describes the construction and validation of six ANN models. After a discussion of the performances of these models, they are used for the prediction of water mains failure and the determination of the benefit index, which allows optimization of investment for the rehabilitation and maintenance of urban water mains. The spatial repartition of the risk of degradation is illustrated using a geographic information system, which constitutes an effective tool for the elaboration of strategies of rehabilitation of water distribution systems.

Use of geospatial information system based tool for renovation and rehabilitation of water distribution systems

Normally, decision makers use number of pipe broken in specific sections of water distribution systems to determine the pipes to be replaced. This index cannot solely evaluate hydraulic and quality parameters of the system and effects of pipe renovation on the system performance. In this study, a methodology is presented to manage the rehabilitation and replacement of water distribution network using hydraulic and geospatial information systems models. A preprocessor subroutine is developed to link geospatial information systems and hydraulic software. Hydraulic parameters together with the attribute data of pipes are used to determine the required renovation schemes based on several criteria. The proposed indices consist of pipe breaks and leakage analyses, hydraulic and quality performance and mechanical reliability of the network. A novel approach is also introduced to calculate leakage values throughout the network. Results of a real case study by the developed model introduced replacement of 4 km 40 mm galvanized pipes instead of 11 km 100 mm asbestos-cement pipes from conventional method. It is observed that the suggested geographic information system based model produces more realistic results with less cost for renovation schemes in comparison with conventional method which just consider number of bursts as a key criterion.

Probabilistic building block identification for the optimal design and rehabilitation of water distribution systems

The multi-objective design and rehabilitation of water distribution systems (WDS) is defined as the search for the set of system designs which offers the best trade-off between competing design objectives. Typically these objectives will consist of the cost of implementing a system design and a measure of the performance of that system. These measures are often in competition since improvements in the performance of a system generally come at a cost. Here three genetic algorithms which use probabilistic methods to identify building blocks—the Univariate Marginal Distribution Algorithm (UMDA) (Mühlenbein 1997), the hierarchical Bayesian Optimisation Algorithm (hBOA) (Pelikan 2002) and the Chi-Square Matrix methodology (Aporntewan & Chongstitvatana 2004)—are compared to the well-known multi-objective evolutionary algorithm NSGAII (Deb et al. 2002) for the multi-objective design and rehabilitation of water distribution systems. For single-objective problems the identification of building blocks has been seen to make evolutionary algorithms more scalable to large problems than simple genetic algorithms. In this paper these algorithms are shown to offer significantly better solutions than NSGA-II for the case of large systems. However, this improvement comes at the expense of diversity of solutions in the fronts identified.

Optimal Scheduling of Replacement and Rehabilitation of Water Distribution Systems

Many municipal water distribution systems across North America are reaching or have exceeded their design lives and, therefore, require extensive upgrading through rehabilitation and/or replacement. However, these needs far surpass the available resources, and decision makers must prioritize their replacement/rehabilitation needs. One such approach is the determination of the optimal replacement time based on the minimization of the total or annual average cost during a predetermined service period. This paper describes a simple approach for the optimization of replacement/rehabilitation activities for a network of buried pipes, which is based on the assumption that the occurrence of breaks in a pipeline segment follows a nonhomogeneous Poisson process. Equations for evaluating the optimal replacement time are derived by minimizing the expected annual average cost during the service period of the pipeline segment. Predictions are compared with those obtained by minimizing the expected total (accumulated) cost during the service or planning period. The use of the proposed approach is illustrated via numerical examples. Optimal replacement time predictions, based on minimization of the annual average cost, were found to be significantly longer than those obtained based on minimization of the total cost for the case—where break occurrence rate follows an exponential function.

Economic level of reliability for the rehabilitation of hydraulic networks

The problem of water distribution system rehabilitation is formulated here as a multiobjective optimisation problem under uncertainty. The two objectives are to minimise the structural rehabilitation cost and to maximise the hydraulic reliability of the system. In this context, reliability is defined as a probability of simultaneously satisfying minimum pressure head constraints at all nodes in the network. An economic analysis has been performed, taking into account not only the structural costs but also lost revenue owing to the volume of water required by users but not supplied to them because of the structural inadequacy of the network. Because of the uncertainty in water demand, a probabilistic approach is used within the optimisation model. The probabilistic distribution and its parameters were estimated through an experimental study conducted on a real water distribution network. The recently developed robust Non-dominated Sorting Genetic Algorithm II optimisation algorithm is used to solve the optimisation problem. The methodology presented allows the identification of the specific optimal solution of the Pareto front that corresponds to minimal structural cost and minimal lost revenue yet corresponding to a high level of reliability – the economic level of reliability. This value could be assumed as the optimal solution or as a lower threshold, which restricts the gamut of technically feasible solutions that could be adopted in a rehabilitation programme.

Risk- and robustness-based solutions to a multi-objective water distribution system rehabilitation problem under uncertainty

The water distribution system (WDS) rehabilitation problem is defined here as a multi-objective optimisation problem under uncertainty. Two alternative problem formulations are considered. The first objective in both approaches is to minimise the total rehabilitation cost. The second objective is to either maximise the overall WDS robustness or to minimise the total WDS risk. The WDS robustness is defined as the probability of simultaneously satisfying minimum pressure head constraints at all nodes in the network. Total risk is defined as the sum of nodal risks, where nodal risk is defined as the product of the probability of pressure failure at that node and consequence of such failure. Decision variables are the alternative rehabilitation options for each pipe in the network. The only source of uncertainty is the future water consumption. Uncertain demands are modelled using any probability density functions (PDFs) assigned in the problem formulation phase. The corresponding PDFs of the analysed nodal heads are calculated using the Latin Hypercube sampling technique. The optimal rehabilitation problem is solved using the newly developed rNSGAII method which is a modification of the well-known NSGAII optimisation algorithm. In rNSGAII a small number of demand samples are used for each fitness evaluation leading to significant computational savings when compared to the full sampling approach. The two alternative approaches are tested, verified and their performance compared on the New York tunnels case study. The results obtained demonstrate that both new methodologies are capable of identifying the robust (near) Pareto optimal fronts while making significant computational savings.

A self-adaptive boundary search genetic algorithm and its application to water distribution systems

The success of the application of genetic algorithms (GA) or evolutionary optimization methods to the design and rehabilitation of water distribution systems has been shown to be an innovative approach for the water industry. The optimal design and rehabilitation of water distribution systems is a constrained non-linear optimization problem. Constraints (for example, the minimum pressure requirements) are generally handled within genetic algorithm optimization by introducing a penalty cost function. The optimal or near optimal solution is found when the pressures at some nodes are close to the minimum required pressure or at the boundary of critical constraints. This paper presents a new approach called the self-adaptive boundary search strategy for selection of penalty factor within genetic algorithm optimization. The approach co-evolves and self-adapts the penalty factor such that the genetic algorithm search is guided towards and preserved around constraint boundaries. Thus it reduces the amount of simulation computations within the GA search and enhances the efficacy at reaching the optimal or near optimal solution. To demonstrate its effectiveness, the self-adaptive boundary search strategy is applied to a case study of the optimization of a water distribution system in this paper. It has been shown that the boundary GA search strategy is effective at adapting the feasibility of GA populations for a wide range of penalty factors. As a consequence, the boundary GA has been able to successfully find the least cost solution in the case study more effectively than a GA without the boundary search strategy. Thus a reliable least cost solution is guaranteed for the GA optimization of a water distribution system.

Scheduling of water distribution system rehabilitation using structured messy genetic algorithms.

A methodology is presented for the optimal design and scheduling of investment for the rehabilitation of water distribution networks. Based on the evolutionary programming technique known as Structured Messy Genetic Algorithms, the methodology utilizes a multi-objective formulation which improves the evolutionary process and provides nondominated optimal solutions over a range of costs and benefits. The model is applied to an example-a small artificial network of fifteen pipes. The effects on the optimal solutions of varying parameters such as interest rate and inflation rate are also investigated.

Long‐term planning methodology for water distribution system rehabilitation

The most expensive component of a water supply system is the distribution network. Deterioration due to aging and stress causes increased operation and maintenance costs, water losses, reduction in the quality of service, and reduction in the quality of water supplied. In this paper an approach is proposed in which the water distribution network economics and hydraulic capacity are analyzed simultaneously over a predefined analysis period while the deterioration over time of both the structural integrity and the hydraulic capacity of every pipe in the system is explicitly considered. The cost associated with each pipe in the network is calculated as the present value of an infinite stream of costs. In Kleiner et al. [this issue] a methodology is presented to implement this approach into a decision support system that facilitates the identification of an optimal rehabilitation strategy.