The aim of this work was to evaluate a smart electronic tongue device as an alternative for qualitative and quantitative monitoring of drinking water. The smart electronic tongue consisted of a voltametric polypyrrole sensor array, linked with a multi-channel electronic system (multipotentiostat) based on PSoC (programable system on chip) technology controlled by a smartphone with a data acquisition and control app. This device was used in the monitoring of drinking water from the Sincelejo city water supply system; also, water samples collected and analyzed by the public health agency were used. The voltammetric measurements carried out with the smart electronic tongue showed cross-sensitivity of the polypyrrole sensor array, which allowed the discrimination of the samples through of principal component analysis by artificial neural networks. In addition, the voltammetric signals registered with the smart electronic tongue allowed, through partial least square (PLS) by artificial neural networks analysis, estimating the concentrations of some important analytes in the evaluation of the physicochemical quality of drinking water with R2 values higher than 0.70. The results allowed to conclude that the smart electronic tongue can be a valuable analytical tool that allows, in a single measure, to perform qualitative and quantitative chemical analysis (alkalinity, calcium, residual chlorine, chlorides, total hardness, phosphates, magnesium, and sulfates), it is also a fast, portable method that can complement traditional analyzes.
Drinking water distribution networks form an essential part of modern-day critical infrastructure. Sectorizing a network into district metered areas is a key technique for pressure management and water loss reduction. Sectorizing an existing network from scratch is, however, an exceedingly complex design task that designs in a well-studied general mathematical problem. Numerical optimization techniques such as evolutionary algorithms can be used to search for near-optimal solutions to such problems, but doing so within a reasonable time frame remains an ongoing challenge. In this work, we introduce two heuristic tricks that use information of the network structure and information of the operational requirements of the drinking water distribution network to modify the basic evolutionary algorithm used to solve the general problem. These techniques not only reduce the time required to find good solutions but also ensure that these solutions better match the requirements of drinking water practice. Both techniques were demonstrated by applying them in the sectorization of the actual distribution network of a large city.
In this research, reliability indicators of water distribution networks were evaluated under pipe failure conditions. The case studies included two benchmark networks and one real-life water distribution network in Iran with more hydraulic constraints. Some important reliability indicators were presented, such as resilience index, network resilience, modified resilience index, and minimum surplus head index. GANetXL was used to do the one-objective and two-objective optimization of the previously mentioned water distribution networks in order to not only minimize the cost but also maximize the reliability indicators. Moreover, the results of a statistical analysis for each pipe were used to determine the sensitive pipes that were of the most failure probability. GANetXL is an optimization tool in the Microsoft Excel environment and works based on a genetic algorithm. GANetXL has the capability of being linked to EPANET (hydraulic simulation software). The results obtained clearly showed that network resilience index was poor performance when compared with the other indexes under pipe failure conditions, especially in real-life networks that include small pipe diameters. It was also showed that if a water distribution network was optimized only in terms of cost, then there would be an unacceptable pressure drop at some nodes in case of pipe failure.
Abstract. The inherent havoc caused by scarcity of potable water and transmission of water-borne diseases in some parts of Nigeria have created a public health concern. This study seeks to investigate water purification of four different water samples (namely: water from flowing river; freshly dug well or groundwater; rainwater from the rooftop; and heavily polluted dirty water) consumed by the people in the local community using solar desalination method. A single basin solar still was constructed and experimental studies were carried out to determine the influence of solar insolation and temperature variations on the yield of the distillate. The quality of the distillate was tested by measuring the total dissolved solid (TDS) and electrical conductivity. These were compared to World Health Organization (WHO) standard for drinkable water. These parameters were measured for each water sample before and after desalination to determine the efficiency of the solar still. Results showed a wide gap between the values of TDS and EC before and after desalination of the water samples. The values obtained were in accordance with the requirement of World Health Organization for quality drinkable water. The water becomes clear and less turbid after desalination.
Natural particles are frequently applied in drinking water treatment processes in fixed bed reactors, fluidised bed reactors, and sedimentation processes to clarify water and to concentrate solids. When particles settle, it has been found that, in terms of hydraulics, natural particles behave differently when compared to perfectly round spheres. To estimate the terminal settling velocity of single solid particles in a liquid system, a comprehensive collection of equations is available. For perfectly round spheres, the settling velocity can be calculated quite accurately. However, for naturally polydisperse non-spherical particles, experimentally measured settling velocities of individual particles show considerable spread from the calculated average values. This work aims to analyse and explain the different causes of this spread. To this end, terminal settling experiments were conducted in a quiescent fluid with particles varying in density, size, and shape. For the settling experiments, opaque and transparent spherical polydisperse and monodisperse glass beads were selected. In this study, we also examined drinking-water-related particles, like calcite pellets and crushed calcite seeding material grains, which are both applied in drinking water softening. Polydisperse calcite pellets were sieved and separated to acquire more uniformly dispersed samples. In addition, a wide variety of grains with different densities, sizes, and shapes were investigated for their terminal settling velocity and behaviour. The derived drag coefficient was compared with well-known models such as the one of Brown and Lawler (2003). A sensitivity analysis showed that the spread is caused, to a lesser extent, by variations in fluid properties, measurement errors, and wall effects. Natural variations in specific particle density, path trajectory instabilities, and distinctive multi-particle settling behaviour caused a slightly larger degree of the spread. In contrast, a greater spread is caused by variations in particle size, shape, and orientation. In terms of robust process designs and adequate process optimisation for fluidisation and sedimentation of natural granules, it is therefore crucial to take into consideration the influence of the natural variations in the settling velocity when using predictive models of round spheres.
