Oxidative Desulfurization of Fuel Oil: Modeling Based on Artificial Neural Network

Abstract

Oxidative desulfurization of fuel oil was investigated using a process consisting of oxidation and distillation steps. In the oxidation step, various organic carboxylic acid/H2 O2 systems, especially acetic acid/H2 O2, were used as oxidant. They oxidize both easy and refractory sulfur compounds and convert them into oxidized sulfur compounds. The oxidized sulfur compounds are finally removed from fuel oil by distillation in the presence of water. The sulfur content of fuel oil was decreased to levels as low as 20 ppm (up to 90%) in a short contact time, ambient temperature, and atmospheric pressure. The results showed that applying this process did not have any deleterious influence on the distillation characteristic, composition, and content of fuel oil that was examined. An artificial neural network, using back propagation (BP), was also utilized for modeling oxidative desulfuration process of fuel oil. The comparison between the output of ANN modeling and the experimental data showed satisfactory agreement.