Modelling the relationship between drinking water turbidity and other indicators of water
quality in Al-Sin drinking water purification plant using Dynamic Artificial neural
networks could help in the implementation of the stabilization for the per
formance of the
plant because these neural networks provide efficient tool to deal with the complex,
dynamic and non-linear nature of purification processes. They have the ability to response
to various instant changes in parameters influencing water purification.
In this research, four models of feed-forward back-propagation dynamic neural network
were designed to predict the effluent turbidity from Al-Sin drinking water purification
plant. The models were built based on turbidity, pH and conductivity of raw water data
while the effluent turbidity data were used for verify the performance accuracy of each
network. The results of this research confirm the ability of dynamic neural networks in
modeling and simulating the non-linearity behavior of water turbidity as well as to predict
its values. They can be used in Al-Sin drinking water purification plant in order to achieve
the stabilization of its performance.
Green chemistry requires concepts and industrial ecology using natural systems to rid industrial water flow from heavy metals, which effects badly on health and environment.
For this purpose, the changes in coefficient of distribution of mercury has
been studied in system with two phases, liquid (water contaminated with mercury) - solid (metal pyrite)
correlation of the following factors: Time of mixing phases, size of the developed steel, change the values of pH, concentration of elemental mercury, the concentration of calcium as a competitor to the occupation of sites available on the solid phase, the ratio V / M presents the water phase size on the mass of phase, which reflects the remaining time of water phase in the solid phase. The results show that pyrite can be proposed as safe environmental solution for purification of water phase of mercury, after controlling for some operation transactions.
