Verified static and dynamic models of an operational works were used alongside Monte-Carlo conditions and non-dominated sorting genetic algorithm II (NGSAII) to optimise operational regimes. Static models were found to be more suitable for whole water treatment works optimisation modelling and offered the additional advantage of reduced computational burden. Static models were shown to predict solutions of comparable cost when applied to optimisation problems while being faster to simulate than dynamic models.
- IWA Publishing
- Optimisation of water treatment works performance using genetic ...
Surface Water Monitoring - Case Study
Safe operation of a Water Treatment Plant (WTP) requires careful monitoring of the water supply influent to the plant, as a guard for any substances entering the treatment works that could negatively impact treated water quality in the distribution system. One aspect of water quality that has recently garnered more attention from authorities and utilities is Natural Organic Matter (NOM), which refers to a group of carbon-based compounds found in natural water systems formed by the decomposition of organic materials...
Potable water solutions - Case Study
Semco Maritime offer full potable water solutions, from the installation of the water disinfection systems to complete piping solutions. We provide flexible and long lasting solutions to improve the potable water systems. We design and install potable water systems using PP-R (Polypropylene – Plastic) materials and ECA clean water technology for rigs, platforms and vessels.Piping and installation solutionsPolypropylene pipes and fittings are commonly acknowledged within the offshore industry and Class...
3 Scientific Tools to Help You Better Understand Your Water Quality
There are many ways of testing and understanding your water quality with online scientific tools and models. One such resource is the National Water-Quality Assessment (NAWQA) project run by the U.S. Geological Survey (USGS). The project, which was founded in 1991 to develop reliable information about water sources to support decisions on water quality management and policy at every governmental level, uses several different types of modeling and analysis tools to estimate nutrient fluxes, pesticide concentrations...
Water quality prediction using machine learning methods
This study investigates the performance of artificial intelligence techniques including artificial neural network (ANN), group method of data handling (GMDH) and support vector machine (SVM) for predicting water quality components of Tireh River located in the southwest of Iran. To develop the ANN and SVM, different types of transfer and kernel functions were tested, respectively. Reviewing the results of ANN and SVM indicated that both models have suitable performance for predicting water quality components....
Water services in small towns in developing countries: at the tail end of development
The current lack of knowledge about small towns, the great diversity of such settlements and the pressure to ‘scale up’ interventions make it difficult for policy makers and practitioners to develop models which are suitable for these towns. Currently, principles and practices informing models for water services in urban and rural areas are applied in small towns without question. This paper highlights how these principles that are engrained in the sector, may be pernicious for expanding water services in small...