A B S T R A C TNowadays, water availability and quality represent a major challenge. In 2050, the United Nations Organization predicts that 44% of the world population will face severe water scarcity. Countries located in sub-humid and semi-arid regions of the world will be especially concerned for this problem, because of their low supply of rainwater. The aim of this study is to suggest the disinfection treatment by irradiation as a complement wastewater treatment to obtain a safe microbial quality of water and permit its reuse. This last is limited to 1.000 CFU/100 ml (i.e. equivalent to 3 log) of fecal coliforms by the Algerian and WHO standards. The experiments were conducted to disinfect wastewater by UVA, UVC, and solar radiation. The UVA and UVC disinfection treatments were carried out using an experimental bench composed of three flat-bottom flasks and three Erlenmeyers of 2 L each. The solar disinfection treatment was experimented using a 30 L-tubular photoreactor in a stationary and a dynamic flow. The disinfection results indicate a reduction in 2.47 log of total coliforms, 3 log reduction of fecal coliforms, 2.67 log reduction of streptococci, 3.17 log reduction of staphylococci, 0.08 log reduction of yeasts, 0.19 log reduction of molds, and a reduction of 1.17 log of sulfite-spores.
Résumé -Développement de corrélations pour la prédiction des propriétés des fractions pétrolières par les algorithmes génétiques -Notre étude concerne la caractérisation des fractions pétrolières dont les propriétés thermodynamiques et physiques peuvent seulement être connues par une expérimentation lourde et coûteuse due à la multiplicité de leurs constituants. Après une introduction des éléments et des nouvelles tendances dans l'utilisation des techniques d'intelligence artificielle, cet article prouve que les algorithmes génétiques peuvent être appliqués à ce domaine du pétrole. Par conséquent, nous proposons une approche empirique pour estimer les propriétés critiques et le facteur acentrique des fractions pétrolières, basée sur leurs points d'ébullition et densité facilement accessibles. Les algorithmes génétiques nous fournissent aussi une forme appropriée de fonction pour la prédiction de ces propriétés. Des résultats très prometteurs sont obtenus et plusieurs perspectives méritant d'autres investigations sont soulignées.
Abstract -Developing Correlations for Prediction of Petroleum Fraction Properties Using GeneticAlgorithms -This paper deals with the characterization of petroleum fractions whose thermo-physical behaviours can only be known through expensive measurement efforts due to the multiplicity of their constituents. After introducing the issue and new trends in the use of artificial intelligence techniques, this paper shows how genetic algorithms can be applied to this field. Hence, we propose an empirical approach for estimating petroleum fractions critical properties and acentric factor based on their boiling point and density that can be easily obtained. Genetic algorithms provide us with a proper function form for the prediction. Moreover, very promising results are obtained and several relevant issues that deserve further investigations are emphasized.
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