Luisa Fernanda Ribeiro Reis

Multiobjective Evolutionary Algorithms Applied to the Rehabilitation of a Water Distribution System: A Comparative Study

Recognising the multiobjective nature of the decision process for rehabilitation of water supply distribution systems, this paper presents a comparative study of two multiobjective evolutionary methods, namely, multiobjective genetic algorithm (MOGA) and strength Pareto evolutionary algorithm (SPEA). The analyses were conducted on a simple hypothetical network for cost minimisation and minimum pressure requirement, treated as a two-objective problem. For the application example studied, SPEA outperforms MOGA in terms of the Pareto fronts produced and processing time required.

Avaliação do gerenciamento de resíduos de serviços de saúde por meio de indicadores de desempenho

O presente trabalho propos um modelo de avaliacao do gerenciamento de RSS em estabelecimentos de saude, com o uso de indicadores de desempenho. A proposta consistiu em identificar esses indicadores a partir dos dados qualitativos obtidos por entrevistas, cujas respostas foram associadas a escalas numericas e inseridas no programa Statistica (StatSoft®) para efetuar a analise fatorial (AF). Para isso, foi elaborado um roteiro de entrevista, especialmente preparado com 29 variaveis de observacao e aplicado a 98 profissionais da saude da Santa Casa de Misericordia de Sao Carlos (SP). Os indicadores de desempenho foram submetidos ao julgamento de especialistas para a sua classificacao em ordem de importância, com o uso da matriz de avaliacao do metodo AHP (Analytic Hierarchy Process). Por fim, foi composto um indice global, que possibilitou a avaliacao geral da situacao investigada, em uma escala de zero a um, indicando que acoes de melhoria para esse gerenciamento devem ser desenvolvidas. Este trabalho foi desenvolvido a fim de estruturar um modelo de avaliacao de desempenho por meio da identificacao de indicadores qualitativos, auxiliando na eficiencia do processo de gerenciamento de residuos em ambientes de saude.

Unsteady Flow with Cavitation in Viscoelastic Pipes

The current paper focuses on the analysis of transient cavitating flow in pressurised polyethylene pipes, which are characterized by viscoelastic rheological behaviour. A hydraulic transient solver that describes fluid transients in plastic pipes has been developed. This solver incorporates the description of dynamic effects related to the energy dissipation (unsteady friction), the rheological mechanical behaviour of the viscoelastic pipe and the cavitating pipe flow. The Discrete Vapour Cavity Model (DVCM) and the Discrete Gas Cavity Model (DGCM) have been used to describe transient cavitating flow. Such models assume that discrete air cavities are formed in fixed sections of the pipeline and consider a constant wave speed in pipe reaches between these cavities. The cavity dimension (and pressure) is allowed to grow and collapse according to the mass conservation principle. An extensive experimental programme has been carried out in an experimental set-up composed of high-density polyethylene (HDPE) pipes, assembled at Instituto Superior Tecnico of Lisbon, Portugal. The experimental facility is composed of a single pipeline with a total length of 203 m and inner diameter of 44 mm. The creep function of HDPE pipes was determined by using an inverse model based on transient pressure data collected during experimental runs without cavitating flow. Transient tests were carried out by the fast closure of the ball valves located at downstream end of the pipeline for the non-cavitating flow and at upstream for the cavitating flow. Once the rheological behaviour of HDPE pipes were known, computational simulations have been run in order to describe the hydraulic behaviour of the system for the cavitating pipe flow. The calibrated transient solver is capable of accurately describing the attenuation, dispersion and shape of observed transient pressures. The effects related to the viscoelasticity of HDPE pipes and to the occurrence of vapour pressures during the transient event are discussed.

Operational Optimization of WDS Based on Multiobjective Genetic Algorithms and Operational Extraction Rules Using Data Mining

The growth of cities, associated with the lack of investment in basic infrastructure, has rendered water supply systems complex and difficult to operate. The efficient operation of such systems is a fundamental tool for extending the system’s service life as much as possible, thus ensuring a reliable service to the consumers while keeping electrical energy and maintenance costs at acceptable levels. Efficient operation requires knowledge of the system, supported by tools such as models for hydraulic simulation, optimization, and definition of rules, provides the operator with proper conditions for the rational operation of the system’s units. This paper aims to develop a computational model for the optimal operational control of macro water distribution systems using the EPANET2 hydraulic simulator, SPEA (Strength Pareto Evolutionary Algorithm) multiobjective genetic algorithms, and data mining to extract operational rules for the system. The studies were conducted on the macro system of the city of Goiânia, Brazil, chosen due to its complex characteristics, showing that solutions for its satisfactory operation can be quickly produced as a substitute to the personal judgment of the operator. Introduction and Rationale The concept of systems operation, understood by laypersons as a mere sequence of equipment commands whose objective is to meet the demand (Zahed Filho, 1990), is actually far more complex, involving aspects of planning, control and supervision, and infrastructural consumer support and services, considered simultaneously and interdependently. The operation plan requires that at least four basic conditions be met: a) a clear definition of the objectives to be achieved; b) the availability of mathematical analysis models; c) equipment to process these models; and d) knowledge of the system (Luvizotto Jr, 1995). Seeking greater reliability in the establishment of the system operating rules, new hydraulic techniques associated with optimization algorithms have been developed. Righetto (2002) emphasizes that the interface between models for 1 Designer Manager, SANEAGO S.A., Goiânia, Brazil and Honorary University Fellow, Department of Engineering, School of Engineering and Computer Science, University of Exeter, North Park Road, Exeter, EX4 4QF, UK; phone 44 1392 263646; tinil@sc.usp.br and I.B.Carrijo@ex.ac.uk 2 Associate Professor – Sao Carlos School of Engineering, University of Sao Paulo, Av. Trabalhador Sao Carlense, 400, Sao Carlos, Sao Paulo, Brazil; phone 55 16 2739545; fernanda@sc.usp.br 3 Professor, Department of Engineering, School of Engineering and Computer Science, University of Exeter, North Park Road, Exeter, EX4 4QF, UK; phone 44 1392 263633; G.A.Walters@ex.ac.uk 4 Professor, Department of Engineering, School of Engineering and Computer Science, University of Exeter, North Park Road, Exeter, EX4 4QF, UK; phone 44 1392 263637; D.Savic@ex.ac.uk hydraulic simulation, optimization and definition of operating rules must be built carefully to make the model transparent, facilitate the introduction of restrictive inequalities and obtain objective function values in the successive steps required by an optimizer. The purpose of this work is to present a methodology to achieve the optimal operation of water distribution systems, essentially macro systems (skeleton), concerning the costs of the operation and the hydraulic benefits. It represents an attempt to provide appropriate operation rules in order to minimize costs and maximize hydraulic benefits. Based on the knowledge of the system, provided by technical and commercial georeferenced records, the purpose is to optimize its operation through multiobjective genetic algorithms (MOGAs). This is supported by a realistic hydraulic simulation model of the system behavior, and the production of operational rules through the data mining process. Methodology The optimization model implemented here takes into account two objectives: the minimization of the operational costs and the maximization of the hydraulic benefits. Where the hydraulic benefits are considered as the index of demand met, adequate levels of water in the tanks, and minimum and maximum pressures at the demand points for a 24-hour period of analysis. Hydraulic Simulation of the System.The hydraulic simulation evaluates the system’s response to operational decisions in terms of the state variables, i.e., pressure, flow rate and tank level. It is therefore an essential tool for the computational routine, which evaluates the established objectives. EPANET2, via Toolkit Library, Rossman (2001), is used for this purpose. Operational Optimization using Multiobjective Genetic Algorithms (MOGAs). According to Deb(2001) and Deb et al.(2002), since 1993, different evolutionary algorithms have been proposed for the solution of multiobjective optimization problems. The Multi-Objective Genetic Algorithm (MOGA), the Niched-Pareto Genetic Algorithm (NPGA), and the Non-dominated Sorting Genetic Algorithm (NSGA), were the precursors of this technique, whose basic characteristics are: evaluation of the members of a population based on the Pareto dominance concept and on preservation of the diversity of solutions. Although these algorithms have proven efficient in obtaining multiple non-dominant solutions to various engineering problems, researchers have suggested the introduction of elitism to improve their convergence properties. Several algorithms stand out among the multiobjective evolutionary algorithms that consider elitism, i.e., the Strength Pareto Evolutionary Algorithm (SPEA and SPEAII), the Pareto Archived Evolution Strategy (PAES), the elitist GA of Rudolph, Pareto Envelope-based Selection Algorithm (PESA and PESAII ) and Non-dominated Sorting Genetic Algorithm (NSGAII). This work uses the elitism-based SPEA method. Uniform crossover and nonuniform mutation were adopted, following an analysis of the results of several tests using various different operators (Cheung et al., 2003). Extraction of Rules using Data Mining. There is a set of methods known as expert systems or knowledge-based systems whose classification models can be developed according to two main routes. The first obtains rules for the model through interviews based on experts and the inclusion of previous knowledge in the system. The second creates an inductive model through the generalization of a large record of collected and classified data. According to Bessler et al. (2003), the method called data mining used in this work belongs to the second aforementioned route, which creates a classification model through the discovery and analysis of patterns that can be found in the data records. To apply the algorithms, several specific characteristics of the data must be analyzed. All the information about the cases (or examples) has to be presented in the form of attributes and each case is allocated to a discrete predefined class. The main function of a data mining program is generally to construct classification models as decision trees for later application. That, however, is not the main objective in this work. The classifier called rulesets is used to extract operational rules from a set of examples (cases) supplied by the optimization model (Pareto front). The decision tree tool SEE5, which is the most recent version of the C4.5 inducer described by Quinlan (1993), is used for this purpose. Description of the Problem Focusing on the development of a flexible tool that is easily handled by water supply systems operators, clearly providing a set of operational rules according to the working conditions of each unit of the system, part of the macro piping system of Goiânia, Brazil, was considered for analysis and evaluation of the results. For a clearer picture of the proposed application a diagram is shown of the system under study (Figure 1). Definition of the Objective Functions Several studies developed in the past showed that, of all the parameters relating to the operational costs, the most relevant one is the cost of electric energy consumption at water pumping stations. Another possibility is the system’s reliability in meeting consumer needs coherently. In this case, several parameters can be listed. The reliability of water supply systems can be considered from a hydraulic or mechanical standpoint. The former involves physical parameters that vary according to the operational changes in the system, while the latter involves the possible interventions on equipment. As in Walters et al. (1999), this work evaluates two basic objectives, the economic objective and the objective of hydraulic benefits of the water distribution systems. In the case of the economic objective, the intention is to minimize the costs of electrical energy consumption at the pumping stations. The daily cost for each pump at a pumping station is given by the sum of the cost of the maximum demand factor and the measured cost of consumption.

Maximum Design Flow Estimates for Large Basins Using the Local Frequency Analysis (LFA) and the Most Probable Maximum Hydrograph (MPMH) Methods – a Critical Analysis

Statistical and deterministic methods have been severely criticized regarding their ability to calculate peak flows. The recently proposed method denominated as Most Probable Maximum Hydrograph (MPMH), applicable to large hydrographic basins, promises to overcome the difficulties faced in the most traditional methods (statistical and deterministic). The method not only uses the peak flow as in the statistical methods, and not requires detail information about the physical and meteorological characteristics of the hydrographic basin as in the deterministic method. The MPMH method takes information from observed hydrographs as base time, maximum flow and its respective volume. Using simple linear regression equations or simple exponential distribution adjusted to mean hydrograph volumes, the MPMH method is used to calculate design hydrograph, based on observed hydrographs volumes and the respective return periods. This paper assesses the applicability of the MPMH method by evaluating the influence of data characteristics as size of data series, removal of outliers and lowest values of the flow series on the peak flow estimates. In this paper it is shown that the MPMH method has great potential for estimation of design flows when compared to traditional methods. Besides that, it is shown that the difficulty in the use the MPMH method lies in deciding the base time (duration of the direct runoff hydrograph) of the standard hydrograph for the basin, which proved to be a decisive factor to estimate the peak flow and hydrograph volumes.