Publications Scientifiques
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Item Process Parameters and Intensification Effects of a Microwave Exposure Applied for the Extractive Oxidation of Diesel: An Optimization Using Response Surface Methodology(Pleiades Publishing, 2024) Bedoud, Karim; Mesdour, Souad Hammadou née; Boufades, Djamila; Moussiden, Anissa; Benmabrouka, Hafsa; Hamada, Boudjema; Kaddour, OmarExtractive oxidation of diesel via microwave processing using sulfuric acid and two synthesized pyridinium- or methylpyridinium-based ionic liquids has been studied as a sustainable and clean technology. The Central Composite Design (CCD) representing one of the response surface methods was applied for the experimental design, mathematical modeling, optimization, and factor-influence study, which covered the 0.75–1.75 [CH2COOHmPy][HSO4]/[H2SO4] volumetric range, 40–80°C temperature range, and 120–300 s radiation exposure time. The developed model properly fitted experimental results, with a coefficient of determination (R2) equal to 0.9832 that indicated its accuracy. The highest predicted sulfur removal (93.338%) as well as a significant removal of nitrogen and aromatic compounds was obtained for [CH2COOHmPy][HSO4]/[H2SO4] = 1.57, T = 71.7°C, and exposure time equal to 208 s. Microwave-assisted extractive oxidation demonstrated a considerable potential as the energy-saving technology, which meets the future need for producing clean fuels with low content of heteroatoms and polyaromatic hydrocarbons.Item Extractive/Oxidative desulfurization optimization of diesel feed stock by ionic liquid utilization/ thermodynamic analysis(2022) Rahawi, Qasim Y.; Berrabia, Nadjet; Hamada, Boudjema; Daabo, Ahmed MahmoodThe current research paper focuses on the physico-chemical optimization’s parameters for the Microwave Assisted Extractive/ Oxidative Desulfurization (MAEOD) of a real Algerian diesel. The oxidative desulfurization was carried out using vanadyl acetyl acetonate as catalyst, hydrogen pyroxide (30%) as oxidant and an acid Bronsted Ionic Liquid (IL) in situ synthesized as extractor. The utilized optimization method is consistent with the full factorial experiment. The engaged parameters are the masse ratio (catalyst/oil), the volume ratio (IL/oil), and the reaction time. Quantification of total sulfur in samples was realized by X-ray fluorescence and a regression model is formed. The most important model parameters’ interaction effects are examined and the ISO-response curves are outlined in order to simulate the optimal conditionsItem Modeling wax disappearance temperature using advanced intelligent frameworks(American Chemical Society, 2019) Benamara, Chahrazed; Nait Amar, Menad; Gharbi, Kheira; Hamada, BoudjemaThe deposition of wax is one of the most potential problems that disturbs the flow assurance during production processes of hydrocarbon fluids. In this study, wax disappearance temperature (WDT) that is recognized as a vital parameter in such circumstances is modeled using advanced machine learning techniques, namely, radial basis function neural network (RBFNN) coupled with genetic algorithm (GA) and artificial bee colony (ABC). Besides, an accurate and user-friendly correlation was established by implementing the group method of data handling. Results revealed the high reliability of the proposed hybrid models and the established correlation. Moreover, RBFNN coupled with ABC (RBFNN-ABC) was found to be the best paradigm with an overall average absolute relative error value of 0.5402% and a total coefficient of determination (R2) of 0.9706. Furthermore, the performance comparison showed that RBFNN-ABC and the established explicit correlation outperform the prior intelligent and thermodynamic models. Finally, by performing the outlier detection, the quality of the utilized database was assessed, the applicability realm of the best model was delineated, and only one point was found as doubtful