Daniele Laucelli

Development of rehabilitation plans for water mains replacement considering risk and cost-benefit assessment

The economic and social costs of pipe bursts in water distribution networks (WDNs) are very significant. Water managers need reliable replacement plans for critical pipes, balancing investment with expected benefits in a risk-based management scenario. Thus, a robust and feasible decision support tool for water system rehabilitation is required. This kind of tool should incorporate (i) a model to forecast pipe failures and (ii) a strategy to solve a multi-objective optimisation problem trading investment vs. benefits. The former requires the collection of company asset data and the statistical modelling of pipe bursts. In this article, the burst modelling is performed by the evolutionary polynomial regression technique, providing a symbolic model for predicting pipe bursts. The benefits of burst reduction achieved by mains rehabilitation are evaluated by a multi-objective optimisation model over a short-term planning horizon (taken to be one year in this study). The multi-objective strategy is embedded in a genetic algorithm search methodology. The procedure identifies different subsets of pipes scheduled for rehabilitation, ranging from no-replacement (i.e., no reduction of the predicted number of bursts) to the complete replacement scheme (i.e. maximum reduction of the predicted number of bursts), trading cost of rehabilitation against achieved benefits. The result of the strategy is a Pareto (trade-off) front, which by itself does not provide any prioritisation of pipes for replacement. Thus, the article introduces a further processing step by which pipes are prioritised for rehabilitation based on the number of times each belongs to a solution on the Pareto front. By considering costs and such priority rating of each main, an improved investments/benefit diagram is constructed. The procedure is tested on a real-world UK WDN.

Scour depth modelling by a multi-objective evolutionary paradigm

Local scour modelling is an important issue in environmental engineering in order to prevent degradation of river bed and safeguard the stability of grade-control structures. Many empirical formulations can be retrieved from literature to predict the equilibrium scour depth, which is usually assumed as representative of the phenomenon. These empirical equations have been mostly constructed in some ways by leveraging regression procedures on experimental data, usually laboratory observations (thus from small/medium scale experiments). Laboratory data are more accurate measurements but generally not completely representative of the actual conditions in real-world cases, that are often much more complex than those schematized by the laboratory equipment. This is the main reason why some of the literature expressions were not adequate when used for practical applications in large-scale examples. This work deals with the application of an evolutionary modelling paradigm, named Evolutionary Polynomial Regression (EPR), to such problem. Such a technique was originally presented as a classical approach, used to achieve a single model for each analysis, and has been recently updated by implementing a multi-modelling approach (i.e., to obtain a set of optimal candidate solutions/models) where a multi-objective genetic algorithm is used to get optimal models in terms of parsimony of mathematical expressions vs. fitting to data. A wide database of field and laboratory observations is used for predicting the equilibrium scour depth as a function of a set of variables characterizing the flow, the sediments and the dimension of the grade-control structure. Results are discussed considering two regressive models available in literature that have been trained on the same data used for EPR. The proposed modelling paradigm proved to be a useful tool for data analysis and, in the particular case study, able to find feasible explicit models featured by an appreciable generalization performance.

Operational and Tactical Management of Water and Energy Resources in Pressurized Systems: Competition at WDSA 2014

AbstractOptimal management of water and energy resources worldwide is a basis for environmental and socioeconomic sustainability in urban areas, which has become even more relevant with the advent of the smart and water sensitive city paradigm. In water distribution networks (WDNs) water resource management is concerned with increased efficiency, which is primarily related to the reduction of leakages, whereas energy management refers to optimal pump, valve, and source scheduling strategies considering the hydraulic system requirements. These management goals require planning of asset renewal and improvement works in the short time (operational) and medium time (tactical) horizons, considering the financial sustainability of relevant actions. The battle of background leakage assessment for water networks (BBLAWN) was designed as a competition held at the 16th Water Distribution Systems Analysis Conference, in Bari (Italy) in 2014 (WDSA), to address the aforementioned management goals. The teams taking par...

Computationally Efficient Modeling Method for Large Water Network Analysis

AbstractNowadays, the unprecedented computing power of desktop personal computers and efficient computational methodologies such as the global gradient algorithm (GGA) make large water-distribution-system modeling feasible. However, many network analysis applications, such as optimization models, require running numerous hydraulic simulations with modified input parameters. Therefore, a methodology that can reduce the computational burden of network analysis and still provide the required model accuracy is needed. This paper presents a matrix transformation approach to convert the classic GGA, which is implemented within the widely available freeware EPANET 2, into a more computationally efficient enhanced global gradient algorithm (EGGA). The latter achieves improved efficiency by reducing the size of the mathematical problem through the transformed topological representation of the original network model. By removing serial nodes and serial pipe sections from the original topological representation whil...

Water Distribution Network Pressure-Driven Analysis Using the Enhanced Global Gradient Algorithm (EGGA)

Pressure-driven analysis of water distribution networks (WDNs) can realistically reproduce the actual behavior of the hydraulic system, especially with reference to leakages, which are not under human control, and, sometimes to demands in pressure-deficient conditions. Classical WDN models represent the demand and leakage outflows in terms of either prior fixed nodal discharges, in classical demand-driven analysis, or dependent on actual nodal pressures, in pressure-driven analysis. This work presents a WDN pressure-driven algorithm that allows accounting for actual leakage and demand patterns along pipes or, as a complementary feature, for network topological simplification. It is on the basis of the enhanced global gradient algorithm (EGGA) and has been introduced and discussed in comparison to classical pressure-driven GGA. Three test networks have been used to study the convergence issue of the newly proposed algorithm, and the largest network has been used to discuss its computational efficiency.

Operational Optimization: Water Losses versus Energy Costs

Management efficiency of water distribution networks (WDNs) is of relevant interest for the water industry, and operational optimization plays an important role. The energy to pump water is a significant element of operational costs and depends on electricity tariffs varying over time. As a result, pumping optimization accounting for electricity costs and relevant boundary conditions of a WDN, e.g., demands, is of practical interest. When the electricity tariffs are lower, for example, during the night hours, optimization generally results in pumping more water during those hours, if the presence of tanks, which are internal to the hydraulic system, allows for water storage. Nevertheless, the pressure and therefore, water leakage of the network greatly vary from night to daylight hours. Pressure and leakage generally increase in the night because of a lower level of demands and a greater level of pressures. Previous studies rarely account for this. This work investigates pumping optimization background leaks, i.e., the nonrevenue water cost beside the energy cost. It is shown and discussed that the reduction of background leaks conflict with, and generally dominate, energy cost. DOI: 10.1061/(ASCE)HY.1943- 7900.0000681.

Assessing climate change and asset deterioration impacts on water distribution networks: Demand-driven or pressure-driven network modeling?

This manuscript compares demand-driven and pressure-driven hydraulic network simulation models for assessing hydraulic capacity under uncertain scenarios. A stochastic approach is implemented assuming possible alteration of boundary conditions due to climate and socio-economic changes (i.e., the increase of peaks of customers demands), and system deterioration (i.e., the increase of pipe internal hydraulic resistances and background leakages). Two real water distribution networks located in Southern Italy are used for analyses. Results show that demand-driven analysis underestimates the hydraulic network capacity with respect to pressure-driven analysis. In fact, pressure-driven analysis assumes the components of model demands (human-based and leakage-based) as dependent on pressure status of the system, and thus returns a more reasonable number and location of critical nodes than demand-driven analysis. Furthermore, demand-driven analysis does not predict the water demand that can be realistically supplied to customers under pressure-deficient system functioning. Therefore, the use of pressure-driven analysis is advisable to support water managers to allocate budgets for planning rehabilitation works aimed at increasing the hydraulic capacity of the networks.

Modeling Local Water Storages Delivering Customer Demands in WDN Models

Water distribution network (WDN) models account for customer-demands as water withdrawals concentrated in nodes. Customer- demands can be assumed to be constant or varying with nodal head/pressure entailing demand-driven or pressure-driven simulation, respec- tively. In both cases, the direct connection of customer properties to the hydraulic system is implicitly assumed. Nonetheless, in many technical situations, the service pipe fills a local private storage (e.g., a roof tank or a basement tank) from which the water is actually delivered to customers by gravity or pumping systems. In such contexts, the service pipe fills the local tank by means of a top orifice. Consequently, what is really connected to the hydraulic system is a tank, which is subject to a filling/emptying process while supplying water to customers. Therefore, since modeling this technical situation in WDN analyses is necessary, the paper develops a formulation for nodal water withdrawals in WDN models accounting for the filling/emptying process of inline tanks between the hydraulic network and customers. The formulation is also introduced in a widely used method for steady-state WDN modeling, the global gradient algorithm, and its effectiveness to increase the hydraulic accuracy of results is discussed using a simple case study and a small network. DOI: 10.1061/(ASCE) HY.1943-7900.0000812.

Vulnerability Assessment of Water Distribution Networks under Seismic Actions

AbstractA methodology to analyze the vulnerability of water distribution networks (WDNs) to earthquakes by means of risk assessment is presented. The consequences of multiple pipe failures due to earthquakes are investigated in terms of unsupplied demand to customers. To this aim the steady-state WDN analysis is performed considering system topology changes due to closing isolation valves in order to separate the network segments where failures occur. The pipe failure probability is calculated using fragility curves from the American Lifelines Association (ALA). The identification of the worst pipe failure scenarios as trade-offs between unsupplied demand and probability of occurring is formulated as a multiobjective combinatorial problem and solved using a multiobjective genetic algorithm as optimization strategy. The methodology is applied to the Exnet network. Results show that WDN seismic vulnerability depends also on network segmentation due to the existing isolation valve system. The methodology all...

Optimal Design of District Metering Areas for the Reduction of Leakages

AbstractThe division of water distribution networks (WDNs) into district metering areas (DMAs) is a challenging issue and can be effective for analysis, planning, and management purposes. This cont...