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    Accurate prediction of viscosity of mixed oils

    , Article Petroleum Science and Technology ; Volume 39, Issue 9-10 , 2021 , Pages 351-361 ; 10916466 (ISSN) Khoshmardan, M. A ; Mehrizadeh, M ; Zand, N ; Najafi Marghmaleki, A ; Sharif University of Technology
    Bellwether Publishing, Ltd  2021
    Abstract
    Viscosity of mixed oil is an important parameter which is required in transportation and production processes of mixed crude oils. There is no universal and general model for prediction of viscosity of mixed oils at different conditions. Hence, developing simple, accurate and general models for prediction of mixed oil viscosity is of great importance. In this work three computer based models named MLP-NN, PSO-RBF and Hybrid-ANFIS were developed for prediction of viscosity of mixed oils. A number of 513 experimental data covering wide ranges of influencing parameters were utilized to develop the models. The accuracy of predictions of the developed models was examined by using different... 

    Spotlight on kinetic and equilibrium adsorption of a new surfactant onto sandstone minerals: A comparative study

    , Article Journal of the Taiwan Institute of Chemical Engineers ; Volume 50 , May , 2015 , Pages 12-23 ; ISSN: 18761070 Arabloo, M ; Ghazanfari, M. H ; Rashtchian, D ; Sharif University of Technology
    Abstract
    This paper presents a state of the art review of adsorption models for a new plant-based surfactant adsorption onto sandstone minerals. The adsorption data at both kinetic and equilibrium modes were obtained from batch experiments. Four adsorption kinetic models, five two-parameter, and six three-parameter equilibrium models were used for interpretation of the obtained data. Among the two and three-parameter isotherm models applied, the Jovanovic and the Khan isotherms showed the best fit, respectively. And the pseudo-second order model presented a better fit than other kinetic models. Finally, a computer-based modeling approach was developed and used for predicting the kinetics of... 

    Spotlight on kinetic and equilibrium adsorption of a new surfactant onto sandstone minerals: A comparative study

    , Article Journal of the Taiwan Institute of Chemical Engineers ; Volume 50 , May , 2015 , Pages 12-23 ; 18761070 (ISSN) Arabloo, M ; Ghazanfari, M. H ; Rashtchian, D ; Sharif University of Technology
    Taiwan Institute of Chemical Engineers  2015
    Abstract
    This paper presents a state of the art review of adsorption models for a new plant-based surfactant adsorption onto sandstone minerals. The adsorption data at both kinetic and equilibrium modes were obtained from batch experiments. Four adsorption kinetic models, five two-parameter, and six three-parameter equilibrium models were used for interpretation of the obtained data. Among the two and three-parameter isotherm models applied, the Jovanovic and the Khan isotherms showed the best fit, respectively. And the pseudo-second order model presented a better fit than other kinetic models. Finally, a computer-based modeling approach was developed and used for predicting the kinetics of... 

    Accurate prediction of kinematic viscosity of biodiesels and their blends with diesel fuels

    , Article JAOCS, Journal of the American Oil Chemists' Society ; Volume 97, Issue 10 , September , 2020 , Pages 1083-1094 Mehrizadeh, M ; Nikbin Fashkacheh, H ; Zand, N ; Najafi Marghmaleki, A ; Sharif University of Technology
    Wiley-Blackwell  2020
    Abstract
    Viscosity of mixtures of biodiesels (admixtures) and mixtures of biodiesel/diesel (blends) is a important parameter for determining their combustion behavior. There is no universal and general model for prediction of viscosity of these systems at different conditions. Hence, developing simple, accurate, and general models for prediction of viscosity of these systems is of great importance. In this work, three computer-based models named multilayer perceptron neural network (MLP-NN), radial basis function optimized by particle swarm optimization (PSO-RBF), and adaptive neuro fuzzy inference system optimized by hybrid approach (Hybrid-ANFIS) were developed for prediction of viscosity of blends...