Energy efficiency plays a large role in the sustainability effort of water utilities. In gravity-fed pipe networks that present excessive pressures, the installation of micro turbines or pumps-as-turbines for energy recovery can provide significant benefits. The main obstacles associated with this kind of solution include the high cost of implementation (equipment and installation) and the time-consuming task of searching for potential and feasible sites for the power plant implementation. In this work, a numerical methodology for the analysis of any water supply and distribution network in order to optimally locate sites for maximum energy recovery and to preliminarily select or design turbines is proposed and validated with a case study. The idea of this decision support tool is to facilitate the assessment of the potential for energy production in networks and encourage the implementation of this type of efficiency measure. The proposed approach consists of two main stages: (1) identification of potential sites for energy recovery through an optimization procedure and (2) selection of adequate types of turbine and preliminary feasibility analysis.

Researchers and engineers commonly rely on modelling and simulation computer programs to improve the management, design and operational efficiencies in water supply systems. The reliability of some efficiency measures, however, is known to be highly dependent on the modelling accuracy of the selected modelling/simulation tool. Although a number of papers have been recently published related to the use of variable-speed pumps in water networks, there are no relevant studies on the analysis and improvement of the methods used to model the behaviour of these pumps. Consequently, the present work focuses on the methods used to model efficiency curves of variable-speed pumps. A new approach for the prediction of the speed-adjusted curves is proposed and preliminary results using two distinct pumps are presented and discussed. The proposed method is capable of satisfactorily predicting the behaviour of the pumps, demonstrating its potential to be effectively used in modelling tools.

The development of full-field measurement methods has enabled a new trend of heterogeneous mechanical tests. The inhomogeneous strain fields retrieved from these tests are being widely used in the calibration of constitutive models for sheet metals. However, today, there is no mechanical test able to characterize the material in a large range of strain states. The aim of this work is to present a heterogeneous mechanical test with an innovative tool/specimen shape, capable of producing rich heterogeneous strain paths and thus providing extensive information on material behavior. The proposed specimen is found using a shape optimization process where an index that evaluates the richness of strain information is used. In this work, the methodology and results are extended to non-specimen geometry dependence and to the non-dependence of the geometry parametrization through the use of the Ritz method for boundary value problems. Different curve models, such as splines, B-splines, and NURBS, are used, and C1 continuity throughout the specimen is guaranteed. Moreover, several deterministic and stochastic optimization methods are used in order to find the method or the combination of methods able to minimize the cost function effectively. Results demonstrated that the solution is dependent on the geometry definition, as well as on the optimization methodology. Nevertheless, the obtained solutions provided a wider spectrum of strain states than standard tests.

Predicting future water demands is becoming essential for the efficient management of water supply systems (WSS). To improve the operations of a Portuguese network, short-term water demand forecasting models are applied to a number of datasets collected from distinct locations in the network. Traditional forecasting models, such as exponential smoothing and naïve models, and artificial neural network (ANN)-based models are developed and compared. Additionally, the influence of anthropic and weather variables in the ANN-based models is also analysed. Results demonstrate that, for this case-study, ANN-based models outperform the traditional models when external predictors such as anthropic and weather variables are included in the models. However, the inappropriate choice of such variables may lead to worse forecasting performances.

The scientific research devoted to modelling and simulation of water supply systems is, most of the times, dependent on the use of computer simulation programmes that requires a previous understanding on each specific programme particularities. At the same time, such programmes do not demonstrate to be open, with unconcealed data, simple and intuitive enough for teaching practices in the field of hydraulics. Therefore, other educational tools or approach should be taken. A numerical educative tool, developed in an Excel spreadsheet for the modelling and simulation of water networks operations is presented in this article. Intuitive and easy to adapt to several situations, the developed Excel-based tool presents large possibilities, not only for decision-support concerning the application of certain efficiency measures but also for pedagogical activities, allowing to understand with detail and immediately the effect of any control and/or design change in the daily operation of a water network, and hence in the associated daily energetic costs. Additionally, a number of analyses concerning the convenience of applying efficiency measures in such systems (namely the use of variable-speed pumps) is suggested and performed resorting to the developed tool. The developed tool has been applied in Fluid Mechanics classes with large success, demonstrating great potential for educational purposes.