Applying Modern Optimization Techniques for Prediction Reaction Kinetics of Iraqi Heavy Naphtha Hydrodesulferization

Zaidoon M. Shakor --- Anfal H. Sadeiq

Engineering and Technology Journal مجلة الهندسة والتكنولوجيا
ISSN: 16816900 24120758 Year: 2018 Volume: 36 Issue: 11 Part (A) Engineering Pages: 1171-1175
Publisher: University of Technology الجامعة التكنولوجية


In this study, a powerful modern optimization techniques such as GeneticAlgorithm (GA), Particle Swarm Optimization (PSO) and Artificial neural network (ANN)were applied to estimate the optimal reaction kinetic parameters for Heavy naphthaHydrodesulferization (HDS), the hydrodesulferization unit located in AL-Daura refineryBaghdad/Iraq.The reactions was carried out in a fixed-bed reactor packed with Co-Mo/γAl2O3catalyst and the operatingwas 315-400 °C temperature 35 bar Pressure and 0.5-2.1hr-1 liquid hourly space velocity. The result showed that hydrodesulferization of heavynaphtha follows the pseudo-first order reaction kinetics. This study signifies that thereaction kinetic parameters calculated by Genetic Algorithm was found to be moreaccurate and gives the highest correlation coefficient (R2= 0.9507) than the other twomethods. ANN technology by using the topology of (3-3-1-1) provides an effective tool tosimulate and understand the non-linear behavior of the process. The modelresult showedvery good agreement with the experimental data with less than 5%. mean absolute error.


Hydrodesulferization --- Reaction Kinetics --- Genetic Algorithm --- Particle Swarm Optimization --- Artificial neural network.