Afshin Tatar
Higher Degree by Research Candidate
School of Chemical Engineering
Faculty of Sciences, Engineering and Technology
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Language Competencies
Language Competency English Can read, write, speak, understand spoken and peer review Persian Can read, write, speak, understand spoken and peer review
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Journals
Year Citation 2024 Esmaeili-Jaghdan, Z., Tatar, A., Shokrollahi, A., Bon, J., & Zeinijahromi, A. (2024). Machine learning modelling of dew point pressure in gas condensate reservoirs: application of decision tree-based models. Neural Computing and Applications, 36(4), 1973-1995.
2023 Tatar, A., & Shafiei, A. (2023). Connectionist Models for Asphaltene Precipitation Prediction by <i>n</i>-Alkane Titration─Pressure and Crude Oil Properties Considered. Industrial and Engineering Chemistry Research, 62(34), 13281-13302.
2023 Lashkenari, M. S., Bagheri, M., Tatar, A., Rezazadeh, H., & Inc, M. (2023). A further study in the prediction of viscosity for Iranian crude oil reservoirs by utilizing a robust radial basis function (RBF) neural network model. Neural Computing and Applications, 35(14), 10663-10676.
Scopus6 WoS42023 Ghasemi, M., Tatar, A., Shafiei, A., & Ivakhnenko, O. P. (2023). Prediction of asphaltene adsorption capacity of clay minerals using machine learning. Canadian Journal of Chemical Engineering, 101(5), 2579-2597.
Scopus1 WoS12023 Behvandi, R., Tatar, A., Shokrollahi, A., & Zeinijahromi, A. (2023). Evaluation of phase equilibrium conditions of clathrate hydrates in natural gas binary mixtures: Machine learning approach. Geoenergy Science and Engineering, 224, 26 pages.
2023 Rayhani, M., Tatar, A., Shokrollahi, A., & Zeinijahromi, A. (2023). Exploring the power of machine learning in analyzing the gas minimum miscibility pressure in hydrocarbons. Geoenergy Science and Engineering, 226, 20 pages.
Scopus22022 Shafiei, A., Tatar, A., Rayhani, M., Kairat, M., & Askarova, I. (2022). Artificial neural network, support vector machine, decision tree, random forest, and committee machine intelligent system help to improve performance prediction of low salinity water injection in carbonate oil reservoirs. Journal of Petroleum Science and Engineering, 219, 19 pages.
Scopus8 WoS52022 Mirzaie, M., Esfandyari, H., & Tatar, A. (2022). Dew point pressure of gas condensates, modeling and a comprehensive review on literature data. Journal of Petroleum Science and Engineering, 211, 17 pages.
Scopus9 WoS52022 Tatar, A., Esmaeili-Jaghdan, Z., Shokrollahi, A., & Zeinijahromi, A. (2022). Hydrogen solubility in n-alkanes: Data mining and modelling with machine learning approach. International Journal of Hydrogen Energy, 47(85), 35999-36021.
Scopus9 WoS12022 Yerkenov, T., Tazikeh, S., Tatar, A., & Shafiei, A. (2022). Asphaltene Precipitation Prediction during Bitumen Recovery: Experimental Approach versus Population Balance and Connectionist Models. ACS Omega, 7(37), 33123-33137.
Scopus2 WoS2 Europe PMC22021 Ghorbani, H., Wood, D. A., Choubineh, A., Tatar, A., Abarghoyi, P. G., Madani, M., & Mohamadian, N. (2021). Prediction of oil flow rate through an orifice flow meter: Artificial intelligence alternatives compared (vol 6, pg 404, 2019). PETROLEUM, 7(2), 2 pages. 2021 Tatar, A., Askarova, I., Shafiei, A., & Rayhani, M. (2021). Data-Driven Connectionist Models for Performance Prediction of Low Salinity Waterflooding in Sandstone Reservoirs. ACS Omega, 6(47), 32304-32326.
Scopus11 WoS10 Europe PMC22021 Sayahi, T., Tatar, A., Rostami, A., Anbaz, M. A., & Shahbazi, K. (2021). Determining solubility of CO<inf>2</inf> in aqueous brine systems via hybrid smart strategies. International Journal of Computer Applications in Technology, 65(1), 1-13.
Scopus11 WoS82020 Mirzaie, M., & Tatar, A. (2020). Modeling of interfacial tension in binary mixtures of CH<inf>4</inf>, CO<inf>2</inf>, and N<inf>2</inf> - alkanes using gene expression programming and equation of state. Journal of Molecular Liquids, 320, 15 pages.
Scopus25 WoS202020 Ghorbani, H., Wood, D. A., Choubineh, A., Mohamadian, N., Tatar, A., Farhangian, H., & Nikooey, A. (2020). Performance comparison of bubble point pressure from oil PVT data: Several neurocomputing techniques compared. Experimental and Computational Multiphase Flow, 2(4), 225-246.
Scopus36 WoS312020 Tatar, A., Moghtadaei, G. M., Manafi, A., Cachadiña, I., & Mulero, Á. (2020). Determination of pure alcohols surface tension using Artificial Intelligence methods. Chemometrics and Intelligent Laboratory Systems, 201, 14 pages.
Scopus11 WoS72020 Ghorbani, H., Wood, D. A., Choubineh, A., Tatar, A., Abarghoyi, P. G., Madani, M., & Mohamadian, N. (2020). Prediction of oil flow rate through an orifice flow meter: Artificial intelligence alternatives compared. Petroleum, 6(4), 404-414.
Scopus512019 Barati-Harooni, A., Najafi-Marghmaleki, A., Hoseinpour, S. A., Tatar, A., Karkevandi-Talkhooncheh, A., Hemmati-Sarapardeh, A., & Mohammadi, A. H. (2019). Estimation of minimum miscibility pressure (MMP) in enhanced oil recovery (EOR) process by N<inf>2</inf> flooding using different computational schemes. Fuel, 235, 1455-1474.
Scopus34 WoS252019 Rashid, S., Ghamartale, A., Abbasi, J., Darvish, H., & Tatar, A. (2019). Prediction of Critical Multiphase Flow Through Chokes by Using A Rigorous Artificial Neural Network Method. Flow Measurement and Instrumentation, 69, 9 pages.
Scopus25 WoS192019 Ameli, F., Hemmati-Sarapardeh, A., Tatar, A., Zanganeh, A., & Ayatollahi, S. (2019). Modeling interfacial tension of normal alkane-supercritical CO<inf>2</inf> systems: Application to gas injection processes. Fuel, 253, 1436-1445.
Scopus13 WoS102019 Tatar, A., Barati, A., Najafi, A., & Mohammadi, A. H. (2019). Radial basis function (RBF) network for modeling gasoline properties. Petroleum Science and Technology, 37(11), 1306-1313.
Scopus8 WoS32019 Moghadasi, R., Rostami, A., Tatar, A., & Hemmati-Sarapardeh, A. (2019). An experimental study of Nanosilica application in reducing calcium sulfate scale at high temperatures during high and low salinity water injection. Journal of Petroleum Science and Engineering, 179, 7-18.
Scopus20 WoS182019 Rahmati, A. S., & Tatar, A. (2019). Application of Radial Basis Function (RBF) neural networks to estimate oil field drilling fluid density at elevated pressures and temperatures. Oil and Gas Science and Technology, 74, 6 pages.
Scopus16 WoS122018 Najafi-Marghmaleki, A., Tatar, A., Barati-Harooni, A., Arabloo, M., Rafiee-Taghanaki, S., & Mohammadi, A. H. (2018). Reliable modeling of constant volume depletion (CVD) behaviors in gas condensate reservoirs. Fuel, 231, 146-156.
Scopus28 WoS202018 Hemmat Esfe, M., Tatar, A., Ahangar, M. R. H., & Rostamian, H. (2018). A comparison of performance of several artificial intelligence methods for predicting the dynamic viscosity of TiO2/SAE 50 nano-lubricant. Physica E: Low-Dimensional Systems and Nanostructures, 96, 85-93.
Scopus78 WoS652018 Hoseinpour, S. A., Barati-Harooni, A., Nadali, P., Mohebbi, A., Najafi-Marghmaleki, A., Tatar, A., & Bahadori, A. (2018). Accurate model based on artificial intelligence for prediction of carbon dioxide solubility in aqueous tetra-n-butylammonium bromide solutions. Journal of Chemometrics, 32(2), 20 pages.
Scopus6 WoS62018 Ahmadi, M. H., Tatar, A., Seifaddini, P., Ghazvini, M., Ghasempour, R., & Sheremet, M. A. (2018). Thermal conductivity and dynamic viscosity modeling of Fe<inf>2</inf>O<inf>3</inf>/water nanofluid by applying various connectionist approaches. Numerical Heat Transfer; Part A: Applications, 74(6), 1301-1322.
Scopus43 WoS402018 Kahani, M., Ahmadi, M. H., Tatar, A., & Sadeghzadeh, M. (2018). Development of multilayer perceptron artificial neural network (MLP-ANN) and least square support vector machine (LSSVM) models to predict Nusselt number and pressure drop of TiO<inf>2</inf>/water nanofluid flows through non-straight pathways. Numerical Heat Transfer; Part A: Applications, 74(4), 1190-1206.
Scopus59 WoS562018 Rostami, A., Kalantari-Meybodi, M., Karimi, M., Tatar, A., & Mohammadi, A. H. (2018). Efficient estimation of hydrolyzed polyacrylamide (HPAM) solution viscosity for enhanced oil recovery process by polymer flooding. Oil and Gas Science and Technology, 73, 17 pages.
Scopus44 WoS382018 Ahmadi, M. H., Tatar, A., Alhuyi Nazari, M., Ghasempour, R., Chamkha, A. J., & Yan, W. M. (2018). Applicability of connectionist methods to predict thermal resistance of pulsating heat pipes with ethanol by using neural networks. International Journal of Heat and Mass Transfer, 126, 1079-1086.
Scopus40 WoS382017 Zendehboudi, A., & Tatar, A. (2017). Oil flooded scroll compressors: Predicting the energy performance and evaluating the experimental data. Measurement: Journal of the International Measurement Confederation, 112, 38-46.
Scopus12 WoS112017 Zendehboudi, A., Tatar, A., & Li, X. (2017). A comparative study and prediction of the liquid desiccant dehumidifiers using intelligent models. Renewable Energy, 114, 1023-1035.
Scopus28 WoS252017 Najafi-Marghmaleki, A., Barati-Harooni, A., Tatar, A., Mohebbi, A., & Mohammadi, A. H. (2017). On the prediction of Watson characterization factor of hydrocarbons. Journal of Molecular Liquids, 231, 419-429.
Scopus25 WoS192017 Tatar, A., Barati-Harooni, A., Najafi-Marghmaleki, A., & Bahadori, A. (2017). Accurate prediction of CO<inf>2</inf> solubility in eutectic mixture of levulinic acid (or furfuryl alcohol) and choline chloride. International Journal of Greenhouse Gas Control, 58, 212-222.
Scopus18 WoS162017 Najafi-Marghmaleki, A., Tatar, A., Barati-Harooni, A., & Mohammadi, A. H. (2017). A GEP based model for prediction of densities of ionic liquids. Journal of Molecular Liquids, 227, 373-385.
Scopus12 WoS112017 Barati-Harooni, A., Najafi-Marghmaleki, A., Tatar, A., Mohebbi, A., Khaksar-Manshad, A., & Mohammadi, A. H. (2017). An accurate model for prediction of wax deposition in oil systems. Petroleum and Coal, 59(6), 797-807. 2017 Zendehboudi, A., & Tatar, A. (2017). Utilization of the RBF network to model the nucleate pool boiling heat transfer properties of refrigerant-oil mixtures with nanoparticles. Journal of Molecular Liquids, 247, 304-312.
Scopus40 WoS362017 Barati-Harooni, A., Nasery, S., Tatar, A., Najafi-Marghmaleki, A., Isafiade, A. J., & Bahadori, A. (2017). Prediction of H<inf>2</inf>S Solubility in Liquid Electrolytes by Multilayer Perceptron and Radial Basis Function Neural Networks. Chemical Engineering and Technology, 40(2), 367-375.
Scopus10 WoS92017 Dadkhah, M. R., Tatar, A., Mohebbi, A., Barati-Harooni, A., Najafi-Marghmaleki, A., Ghiasi, M. M., . . . Pourfayaz, F. (2017). Prediction of solubility of solid compounds in supercritical CO<inf>2</inf> using a connectionist smart technique. Journal of Supercritical Fluids, 120, 181-190.
Scopus23 WoS202016 Nasery, S., Barati-Harooni, A., Tatar, A., Najafi-Marghmaleki, A., & Mohammadi, A. H. (2016). Accurate prediction of solubility of hydrogen in heavy oil fractions. Journal of Molecular Liquids, 222, 933-943.
Scopus36 WoS312016 Tatar, A., Barati-Harooni, A., Najafi-Marghmaleki, A., Mohebbi, A., Ghiasi, M. M., Mohammadi, A. H., & Hajinezhad, A. (2016). Comparison of two soft computing approaches for predicting CO<inf>2</inf> solubility in aqueous solution of piperazine. International Journal of Greenhouse Gas Control, 53, 85-97.
Scopus36 WoS312016 Barati-Harooni, A., Najafi-Marghmaleki, A., Tatar, A., & Mohammadi, A. H. (2016). Experimental and modeling studies on adsorption of a nonionic surfactant on sandstone minerals in enhanced oil recovery process with surfactant flooding. Journal of Molecular Liquids, 220, 1022-1032.
Scopus85 WoS702016 Barati-Harooni, A., Soleymanzadeh, A., Tatar, A., Najafi-Marghmaleki, A., Samadi, S. J., Yari, A., . . . Mohammadi, A. H. (2016). Experimental and modeling studies on the effects of temperature, pressure and brine salinity on interfacial tension in live oil-brine systems. Journal of Molecular Liquids, 219, 985-993.
Scopus55 WoS462016 Tatar, A., Barati-Harooni, A., Partovi, M., Najafi-Marghmaleki, A., & Mohammadi, A. H. (2016). An accurate model for predictions of vaporization enthalpies of hydrocarbons and petroleum fractions. Journal of Molecular Liquids, 220, 192-199.
Scopus16 WoS162016 Sayahi, T., Tatar, A., & Bahrami, M. (2016). A RBF model for predicting the pool boiling behavior of nanofluids over a horizontal rod heater. International Journal of Thermal Sciences, 99, 180-194.
Scopus55 WoS522016 Barati-Harooni, A., Najafi-Marghmaleki, A., Tatar, A., Arabloo, M., Phung, L. T. K., Lee, M., & Bahadori, A. (2016). Prediction of frictional pressure loss for multiphase flow in inclined annuli during Underbalanced Drilling operations. Natural Gas Industry B, 3(4), 275-282.
Scopus92016 Tatar, A., Barati-Harooni, A., Moradi, S., Nasery, S., Najafi-Marghmaleki, A., Lee, M., . . . Bahadori, A. (2016). Prediction of heavy oil viscosity using a radial basis function neural network. Petroleum Science and Technology, 34(21), 1742-1748.
Scopus9 WoS52016 Najafi-Marghmaleki, A., Tatar, A., Barati-Harooni, A., Mohebbi, A., Kalantari-Meybodi, M., & Mohammadi, A. H. (2016). On the prediction of interfacial tension (IFT) for water-hydrocarbon gas system. Journal of Molecular Liquids, 224, 976-990.
Scopus15 WoS132016 Tatar, A., Barati-Harooni, A., Najafi-Marghmaleki, A., Ahmadi-Pour, M., Nadali, P., & Mohammadi, A. H. (2016). Prediction of moisture content of natural gases using a GA-RBF model. Journal of Molecular Liquids, 223, 994-999.
Scopus4 WoS42016 Najafi-Marghmaleki, A., Tatar, A., Barati-Harooni, A., Choobineh, M. J., & Mohammadi, A. H. (2016). GA-RBF model for prediction of dew point pressure in gas condensate reservoirs. Journal of Molecular Liquids, 223, 979-986.
Scopus22 WoS142016 Tatar, A., Nasery, S., Bahadori, A., Bahadori, M., Najafi-Marghmaleki, A., & Barati-Harooni, A. (2016). Implementing radial basis function neural network for prediction of surfactant retention in petroleum production and processing industries. Petroleum Science and Technology, 34(11-12), 992-999.
Scopus10 WoS102016 Tatar, A., Nasery, S., Bahadori, M., Bahadori, A., Bahadori, M., Barati-Harooni, A., & Najafi-Marghmaleki, A. (2016). Prediction of water removal rate in a natural gas dehydration system using radial basis function neural network. Petroleum Science and Technology, 34(10), 951-960.
Scopus13 WoS122016 Tatar, A., Najafi-Marghmaleki, A., Barati-Harooni, A., Gholami, A., Ansari, H. R., Bahadori, M., . . . Bahadori, A. (2016). Implementing radial basis function neural networks for prediction of saturation pressure of crude oils. Petroleum Science and Technology, 34(5), 454-463.
Scopus21 WoS192016 Tatar, A., Naseri, S., Bahadori, M., Hezave, A. Z., Kashiwao, T., Bahadori, A., & Darvish, H. (2016). Prediction of carbon dioxide solubility in ionic liquids using MLP and radial basis function (RBF) neural networks. Journal of the Taiwan Institute of Chemical Engineers, 60, 151-164.
Scopus60 WoS502016 Tatar, A., Barati, A., Yarahmadi, A., Najafi, A., Lee, M., & Bahadori, A. (2016). Prediction of carbon dioxide solubility in aqueous mixture of methyldiethanolamine and N-methylpyrrolidone using intelligent models. International Journal of Greenhouse Gas Control, 47, 122-136.
Scopus55 WoS502016 Tatar, A., Barati-Harooni, A., Najafi-Marghmaleki, A., Norouzi-Farimani, B., & Mohammadi, A. H. (2016). Predictive model based on ANFIS for estimation of thermal conductivity of carbon dioxide. Journal of Molecular Liquids, 224, 1266-1274.
Scopus30 WoS262016 Rezaei, A., Abdi-Khangah, M., Mohebbi, A., Tatar, A., & Mohammadi, A. H. (2016). Using surface modified clay nanoparticles to improve rheological behavior of Hydrolized Polyacrylamid (HPAM) solution for enhanced oil recovery with polymer flooding. Journal of Molecular Liquids, 222, 1148-1156.
Scopus94 WoS892016 Naseri, S., Tatar, A., & Shokrollahi, A. (2016). Development of an accurate method to prognosticate choke flow coefficients for natural gas flow through nozzle and orifice type chokes. Flow Measurement and Instrumentation, 48, 1-7.
Scopus32 WoS212016 Afshin, T., Ali, B. H., Hossein, M., Saeid, N., Meysam, B., Moonyong, L., . . . Adel, N. M. (2016). Prediction of water formation temperature in natural gas dehydrators using radial basis function (RBF) neural networks. Natural Gas Industry B, 3(2), 173-180.
Scopus72015 Tatar, A., Shokrollahi, A., Lee, M., Kashiwao, T., & Bahadori, A. (2015). Prediction of supercritical CO<inf>2</inf>/brine relative permeability in sedimentary basins during carbon dioxide sequestration. Greenhouse Gases: Science and Technology, 5(6), 756-771.
Scopus13 WoS112015 Darvish, H., Nouri-Taleghani, M., Shokrollahi, A., & Tatar, A. (2015). Geo-mechanical modeling and selection of suitable layer for hydraulic fracturing operation in an oil reservoir (south west of Iran). Journal of African Earth Sciences, 111, 409-420.
Scopus27 WoS202015 Shokrollahi, A., Tatar, A., & Safari, H. (2015). On accurate determination of PVT properties in crude oil systems: Committee machine intelligent system modeling approach. Journal of the Taiwan Institute of Chemical Engineers, 55, 17-26.
Scopus59 WoS522015 Tatar, A., Shokrollahi, A., Halali, M. A., Azari, V., & Safari, H. (2015). A Hybrid Intelligent Computational Scheme for Determination of Refractive Index of Crude Oil Using SARA Fraction Analysis. Canadian Journal of Chemical Engineering, 93(9), 1547-1555.
Scopus25 WoS232015 Nouri-Taleghani, M., Mahmoudifar, M., Shokrollahi, A., Tatar, A., & Karimi-Khaledi, M. (2015). Fracture density determination using a novel hybrid computational scheme: A case study on an Iranian Marun oil field reservoir. Journal of Geophysics and Engineering, 12(2), 188-198.
Scopus25 WoS172015 Tatar, A., Naseri, S., Sirach, N., Lee, M., & Bahadori, A. (2015). Prediction of reservoir brine properties using radial basis function (RBF) neural network. Petroleum, 1(4), 349-357.
Scopus292015 Naseri, S., Tatar, A., Bahadori, M., Rozyn, J., Kashiwao, T., & Bahadori, A. (2015). Application of Radial Basis Function Neural Network for Prediction of Titration-Based Asphaltene Precipitation. Petroleum Science and Technology, 33(23-24), 1875-1882.
Scopus10 WoS92015 Tatar, A., Naseri, S., Bahadori, M., Rozyn, J., Lee, M., Kashiwao, T., & Bahadori, A. (2015). Evaluation of Different Artificial Intelligent Models to Predict Reservoir Formation Water Density. Petroleum Science and Technology, 33(20), 1749-1756.
Scopus7 WoS52014 Tatar, A., Yassin, M. R., Rezaee, M., Aghajafari, A. H., & Shokrollahi, A. (2014). Applying a robust solution based on expert systems and GA evolutionary algorithm for prognosticating residual gas saturation in water drive gas reservoirs. Journal of Natural Gas Science and Engineering, 21, 79-94.
Scopus44 WoS402014 Hemmati-Sarapardeh, A., Shokrollahi, A., Tatar, A., Gharagheizi, F., Mohammadi, A. H., & Naseri, A. (2014). Reservoir oil viscosity determination using a rigorous approach. Fuel, 116, 39-48.
Scopus117 WoS1062013 Tatar, A., Shokrollahi, A., Mesbah, M., Rashid, S., Arabloo, M., & Bahadori, A. (2013). Implementing Radial Basis Function Networks for modeling CO<inf>2</inf>-reservoir oil minimum miscibility pressure. Journal of Natural Gas Science and Engineering, 15, 82-92.
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Book Chapters
Year Citation 2018 Tatar, A. (2018). Microbial Enhanced Oil Recovery: Microbiology and Fundamentals. In Fundamentals of Enhanced Oil and Gas Recovery from Conventional and Unconventional Reservoirs (pp. 291-508). Elsevier.
Scopus12
- Lecturer "Python Programming", Islamic Azad University, Iran, 2023
- Teaching Assistant “Formation Evaluation, Petrophysics & Rock Properties”, The University of Adelaide, Australia, 2023
- Teaching Assistant “Unconventional Resources and Recovery”, The University of Adelaide, Australia, 2024
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