A Robust Method to Predict Equilibrium and Kinetics of Sulfur and Nitrogen Compounds Adsorption from Liquid Fuel on Mesoporous Material

Document Type: Research Paper

Authors

1 Associate Professor, Department of Gas Engineering, Petroleum University of Technology, Ahwaz, Iran

2 M.S. Student, Department of Gas Engineering, Petroleum University of Technology, Ahwaz, Iran

3 M.S. Student, Department of Petroleum Engineering, Petroleum University of Technology, Ahwaz, Iran

Abstract

This study presents a robust and rigorous method based on intelligent models, namely radial basis function networks optimized by particle swarm optimization (PSO-RBF), multilayer perceptron neural networks (MLP-NNs), and adaptive neuro-fuzzy inference system optimized by particle swarm optimization methods (PSO-ANFIS), for predicting the equilibrium and kinetics of the adsorption of sulfur and nitrogen containing compounds from a liquid hydrocarbon model fuel on mesoporous materials. All the models were evaluated by the statistical and graphical methods. The predictions of the models were also compared with different kinetics and equilibrium models. The results showed that although all the models lead to accurate results, the PSO-ANFIS model represented the most reliable and dependable predictions with the correlation coefficient (R2) of 0.99992 and average absolute relative deviation (AARD) of 0.039%. The developed models are also able to predict the experimental data with better precision and reliability compared to literature models.

Keywords

Main Subjects


References

Ahmadi, M., Anvaripour, B., Khosravi-Nikou, M. R., and Mohammadian, M., Selective Denitrogenation of Model Fuel Through Iron- and Chromium-Modified Microporous Materials (MSU-S), Journal of Environmental Chemical Engineering, Vol. 5, p. 849–860, 2017.

Ahmadi, M. A. and Shadizadeh, S. R., New Approach for Prediction of Asphaltene Precipitation Due to Natural Depletion by Using Evolutionary Algorithm Concept, Fuel, Vol. 102, p. 716–723, 2012.

Chen, H., Wang, Y., Yang, F. H., and Yang, R. T., Desulfurization of High-sulfur Jet Fuel by Mesoporous Π-Complexation Adsorbents, Chemical Engineering Science, Vol. 64, p. 5240–5246, 2009.

Coulibaly, P. and Baldwin, C. K., Nonstationary Hydrological Time Series Forecasting Using Nonlinear Dynamic Methods, Journal of Hydrology, Vol. 307, p. 164–174, 2005.

Cybenko, G., Approximation by Superpositions of a Sigmoidal Function, Math, Control Signal Systems, Vol. 2, p. 303–314, 1989.

Esmaeili-Jaghdan, Z., Shariati, A., and Nikou, M. R. K., A Hybrid Smart Modeling Approach for Estimation of Pure Ionic Liquids Viscosity, Journal of Molecular Liquids, Vol. 222, p. 14–27, 2016.

Freundlich, H., Ueber Die Adsorption in Loesungen, Zeitschrift für Physikalische Chemie, Vol. 57, p. 385–470, 1907.

Gargiulo, N., Peluso, A., Aprea, P., Pepe, F., and Caputo, D., CO2 Adsorption on Polyethylenimine-Functionalized SBA-15 Mesoporous Silica: Isotherms and Modeling, Journal of Chemical and Engineering Data, Vol. 59, p. 896–902, 2014.

Ghiasi, M. M., Arabloo, M., Mohammadi, A. H., and Barghi, T., Application of ANFIS Soft Computing Technique in Modeling the CO2 Capture With MEA, DEA, and TEA Aqueous Solutions, International Journal of Greenhouse Gas Control, Vol. 49, p. 47–54, 2016.

Halali, M. A., Azari, V., Arabloo, M., Mohammadi, A. H., and Bahadori, A., Application of a Radial Basis Function Neural Network to Estimate Pressure Gradient in Water–oil Pipelines, Journal of the Taiwan Institute of Chemical Engineers, Vol. 58, p. 189–202, 2012.

Heidari, E., Sobati, M. A., and Movahedirad, S., Accurate Prediction of Nanofluid Viscosity Using a Multilayer Perceptron Artificial Neural Network (MLP-ANN), Chemometrics and Intelligent Laboratory Systems, Vol. 155, p. 73–85, 2016.

Kim, J. H., Ma, X., Zhou, A., and Song, C., Ultra-deep Desulfurization and Denitrogenation of Diesel Fuel by Selective Adsorption Over Three Different Adsorbents: A Study on Adsorptive Selectivity and Mechanism, Catalysis Today, Vol. 111, p. 74–83, 2006.

Koriakin, A., Ponvel, K. M., and Lee, C. H., Denitrogenation of Raw Diesel Fuel by Lithium-modified Mesoporous Silica, Chemical Engineering Journal, Vol. 162, p. 649–655, 2010.

Lagergren, S., Zur Theorie Der Sogenannten Adsorption Geloster Stoffe, Kungliga Svenska Vetenskapsakademiens, Handlingar, Vol. 24, p. 1–39, 1898.

Langmuir, I., The Constitution and Fundamental Properties of Solids and Liquids, Part I: Solids, Journal of the American Chemical Society, Vol. 38, p. 2221–2295, 1916.

Mello, M., Eić, M., Adsorption of Sulfur Dioxide From Pseudo Binary Mixtures on Hydrophobic Zeolites: Modeling of The Breakthrough Curves, Adsorption, Vol. 8, p. 279–289, 2015.

Mohammadian, M., Ahmadi, M., and Khosravi-Nikou, M. R., Adsorptive Desulfurization and Denitrogenation of Model Fuel by Mesoporous Adsorbents (MSU-S and Coo-MSU-S), Petroleum Science and Technology, Vol. 35, p. 608–614, 2017.

Mohammadian, M., Khosravi-Nikou, M. R., Shariati, A., and Aghajani, M., Model Fuel Desulfurization and Denitrogenation Using Copper and Cerium Modified Mesoporous Material (MSU-S) Through Adsorption Process, Clean Technologies and Environmental Policy, Vol. 20, p. 95–112, 2018.

Montazerolghaem, M., Rahimi, A., and Seyedeyn-azad, F., Equilibrium and Kinetic Modeling of Adsorptive Sulfur Removal from Gasoline by Synthesized Ce–Y Zeolite, Applied Surface Science, Vol. 257, p. 603–609, 2010.

Nasery, S., Barati-Harooni, A., Tatar, A., Najafi-Marghmaleki, A., and Mohammadi, A. H., Accurate Prediction of Solubility of Hydrogen in Heavy Oil Fractions, Journal of Molecular Liquids, Vol. 222, p. 933–943, 2016.

Najafi-Marghmaleki, A., Khosravi-Nikou, M. R., and Barati-Harooni, A., A New Model for Prediction of Binary Mixture of Ionic Liquids+ water Density Using Artificial Neural Network, Journal of Molecular Liquids, Vol. 220, p. 232–237, 2016.

Pawelec, B., Navarro, R. M., Campos, J. M., and Fierro, J. L., Towards Near Zero-sulfur Liquid Fuels: a Perspective Review, Catalysis Science and Technology, Vol. 3, p. 3376–3376, 2013.

Rashidi, S., Nikou, M. R. K., and Anvaripour, B., Adsorptive Desulfurization and Denitrogenation of Model Fuel Using HPW and Nio-HPW Modified Aluminosilicate Mesostructures, Microporous and Mesoporous Materials, Vol.211, p. 134–141. 2015.

Sabzevari, S. and Moosavi, M., Density Prediction of Liquid Alkali Metals and Their Mixtures Using an Artificial Neural Network Method Over the Whole Liquid Range, Fluid Phase Equilibria, Vol. 361, p. 135–142, 2014.

Santos, A. L., Reis, R. A., Rossa, V., Reis, M. M., Costa, A. L., Veloso, C. O., Henriques, C. A., Zotin, F. M., Paredes, M. L., and Silveira, E. B., Silica–alumina Impregnated with Cerium, Nickel, and Molybdenum Oxides for Adsorption of Sulfur and Nitrogen Compounds from Diesel, Materials Letters, Vol. 83, p. 158–160, 2013.

Safari, H., Nekoeian, S., Shirdel, M. R., Ahmadi, H., Bahadori, A., and Zendehboudi, S., Assessing the Dynamic Viscosity of Na–K–Ca–Cl–H2O Aqueous Solutions at High-Pressure and High-Temperature Conditions, Industrial and Engineering Chemistry Research, Vol. 53, p. 11488–11500, 2013.

Sarda, K., Bhandari, A., Pant, K., and Jain, S., Deep Desulfurization of Diesel Fuel by Selective Adsorption Over Ni/Al2O 3 and Ni/ZSM-5 Extrudates, Fuel, Vol. 93, p. 86–91, 2012.

Srivastava, V. C., An Evaluation of Desulfurization Technologies for Sulfur Removal From Liquid Fuels, Rsc Advances, Vol. 2, p. 759–783, 2012.

Sun, B., Li, G. and Wang, X., Facile Synthesis of Microporous Carbon Through a Soft-template Pathway and Its Performance in Desulfurization and Denitrogenation, Journal of Natural Gas Chemistry, Vol. 19, p. 471–476, 2010.

Tatar, A., Barati-Harooni, A., Najafi-Marghmaleki, A., Mohebbi, A., Ghiasi, M. M., Mohammadi, A. H., and Hajinezhad, A., Comparison of Two Soft Computing Approaches for Predicting CO2 Solubility in Aqueous Solution of Piperazine, International Journal of Greenhouse Gas Control, Vol. 53, p. 85–97, 2016.

Wang, L., Sun, B., Yang, F. H., and Yang, R. T., Effects of Aromatics on Desulfurization of Liquid Fuel By Π-Complexation and Carbon Adsorbents, Chemical Engineering Science, Vol. 73, p. 208–217, 2012.

Wen, J., Han, X., Lin, H., Zheng, Y., and Chu, W., A Critical Study on the Adsorption of Heterocyclic Sulfur and Nitrogen Compounds by Activated Carbon: Equilibrium, Kinetics and Thermodynamics, Chemical Engineering Journal, Vol. 164, p. 29–36, 2010.

Xia, C., Wang, J., and Mcmenemy, K., Short, Medium- and Long-term Load Forecasting Model and Virtual Load Forecaster Based on Radial Basis Function Neural Networks, International Journal of Electrical Power and Energy Systems, Vol. 32, p. 743–750, 2010.

Xu, X., Zhang, S., Li, P., and Shen, Y., Desulfurization of Jet-A Fuel in a Fixed-bed Reactor at Room Temperature and Ambient Pressure Using A Novel Selective Adsorbent, Fuel, Vol. 117, p. 499–508, 2014.

Xu, X., Zhang, S., Li, P., and Shen, Y., Equilibrium and Kinetics of Jet-A Fuel Desulfurization by Selective Adsorption at Room Temperatures, Fuel, Vol. 111, p. 172–179, 2013.

Zadeh, L. A., Fuzzy Sets, Information and Control, Vol. 8, p. 338–353, 1965.

Zamani, H. A., Rafiee-Taghanaki, S., Karimi, M., Arabloo, M., and Dadashi, A., Implementing ANFIS for Prediction of Reservoir Oil Solution Gas-oil Ratio, Journal of Natural Gas Science and Engineering, Vol. 25, p. 325–334, 2015.