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    Application of ANFIS-PSO as a novel method to estimate effect of inhibitors on asphaltene precipitation

    , Article Petroleum Science and Technology ; Volume 36, Issue 8 , 2018 , Pages 597-603 ; 10916466 (ISSN) Malmir, P ; Suleymani, M ; Bemani, A ; Sharif University of Technology
    Taylor and Francis Inc  2018
    Abstract
    Asphaltene precipitation in petroleum industries is known as major problems. To solve problems there are approaches for inhibition of asphaltene precipitation, Asphaltene inhibitors are known effective and economical approach for inhibition and prevention of asphaltene precipitation. In the present study Adaptive neuro-fuzzy inference system (ANFIS) was coupled with Particle swarm optimization (PSO) to create a novel approach to predict effect of inhibitors on asphaltene precipitation as function of crude oil properties and concentration and structure of asphaltene inhibitors.in order to training and testing the algorithm, a total number of 75 experimental data was gathered from the... 

    A mechanistic study of emulsion flooding for mobility control in the presence of fatty acids: Effect of chain length

    , Article Fuel ; Volume 276 , 2020 Alizadeh, S ; Suleymani, M ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    Emulsion flooding is a promising method for enhanced oil recovery (EOR). The static and dynamic behavior of the emulsions is greatly influenced by the nature of the applied surfactant. In this work, the effect of fatty acids, as natural surface-active agents, and their chain length on the emulsion behavior was investigated in both bulk and porous media. A panel of the fatty acids with different chain lengths (6 < C < 18) was applied at constant concentration and pH. Upon the static stability tests, emulsion stability at the optimum value of chain length (C14) was increased by two orders of magnitude. Under the optimal condition, the hydrogen bonding between dissociated and undissociated... 

    An intelligent modeling approach for prediction of thermal conductivity of CO2

    , Article Journal of Natural Gas Science and Engineering ; Volume 27 , November , 2015 , Pages 138-150 ; 18755100 (ISSN) Shams, R ; Esmaili, S ; Rashid, S ; Suleymani, M ; Sharif University of Technology
    Elsevier  2015
    Abstract
    In the design of a carbon dioxide capture and storage (CCS) process, the thermal conductivity of carbon dioxide is of special concern. Hence, it is quite important to search for a quick and accurate determination of thermal conductivity of CO2 for precise modeling and evaluation of such a process. To achieve this aim, a robust computing methodology, entitled least square support vector machine (LSSVM) modeling, which is coupled with an optimization approach, was used to model this transport property. The model was constructed and evaluated employing a comprehensive data bank (more than 550 data series) covering wide ranges of pressures and temperatures. Before constructing the model, outlier...