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    Artificial neural network modeling for predict performance of pressure filters in a water treatment plant

    , Article Desalination and Water Treatment ; Volume 39, Issue 1-3 , Feb , 2012 , Pages 192-198 ; 19443994 (ISSN) Tashaouie, H. R ; Gholikandi, G. B ; Hazrati, H ; Sharif University of Technology
    Taylor and Francis Inc  2012
    Pressure filters are popular in small municipal water treatment plants. One of the principles for designing and using the various units of water treatment plants is the ability of assigning and predicting the performance of those units under different and various conditions that could be verified by making pilot scale tests and could be modeled by means of available programs and software such as artificial neural network. The goals of this study that was conducted to predict pressure filter efficiency are: (1) evaluations of pressure filter efficiency for turbidity removal under different conditions such as turbidity of raw water, filtration rate and filter pressure changes; (2) statistical... 

    An investigation into the effect of alloying elements on the recrystallization behavior of 70/30 brass

    , Article Journal of Materials Engineering and Performance ; Volume 19, Issue 4 , June , 2010 , Pages 553-557 ; 10599495 (ISSN) Shafiei, A. M ; Roshanghias, A ; Abbaszadeh, H ; Akbari, G. H ; Sharif University of Technology
    An Artificial Neural Network (ANN) model has been designed for predicting the effects of alloying elements (Fe, Si, Al, Mn) on the recrystallization behavior and microstructural changes of 70/30 brass. The model introduced here considers the content of alloying elements, temperature, and time of recrystallization as inputs while percent of recrystallization is presented as output. It is shown that the designed model is able to predict the effect of alloying elements well. It is also shown that all alloying elements strongly affect the recrytallization kinetics, and all slow down the recrystallization process. The effect of alloying elements on the activation energy for recrystallization has... 

    Data-based modeling and optimization of a hybrid column-adsorption/depth-filtration process using a combined intelligent approach

    , Article Journal of Cleaner Production ; Volume 236 , 2019 ; 09596526 (ISSN) Salehi, E ; Askari, M ; Aliee, M. H ; Goodarzi, M ; Mohammadi, M ; Sharif University of Technology
    Elsevier Ltd  2019
    Lack of robust techniques for optimization of hybrid separation systems is obvious in the literature. A novel hybrid approach for modeling and optimization of a hybrid process consisting of fixed-bed adsorption column (FBAC) and dead-end filtration (DEF) for the removal of methylene blue from water was presented. Artificial neural network (ANN), response surface methodology (RSM) and genetic algorithm (GA) were used for this purpose. ANN was employed to successfully approximate the breakthrough curves. Central composite design was used to investigate the impact of the operating variables, i.e. feed flowrate, initial concentration, adsorption bed length, and filter type on the removal rate as... 

    Viscosity prediction of ternary mixtures containing ILs using multi-layer perceptron artificial neural network

    , Article Fluid Phase Equilibria ; Volume 326 , 2012 , Pages 15-20 ; 03783812 (ISSN) Lashkarblooki, M ; Hezave, A. Z ; Al Ajmi, A. M ; Ayatollahi, S ; Sharif University of Technology
    Elsevier  2012
    Ionic liquids (ILs) have been considered as a good candidate to be replaced by the conventional solvent in recent years due to their potential consumptions and unique properties. In the present study, artificial neural network was used to predict the ternary viscosity of mixtures containing ILs. A collection of 729 experimental data points were gathered from the previously public shed literatures. Different topologies of a multilayer feed forward artificial neural network (MFFANN) were examined and optimum architecture was determined. Ternary viscosity data from the literature for 5 ILs with 547 data points have been used to train the network. In addition, to differentiate dissimilar... 

    Analyzing and predicting permeability coefficient of roller-compacted concrete (RCC)

    , Article Journal of Testing and Evaluation ; Volume 49, Issue 3 , 2019 ; 00903973 (ISSN) Heidarnezhad, F ; Toufigh, V ; Ghaemian, M ; Sharif University of Technology
    ASTM International  2019
    The permeability of roller-compacted concrete (RCC) substantially affects its functionality and safety. This study investigates the effect of mix design parameters on the performance of RCC. For this purpose, approximately 500 laboratory specimens were prepared and tested. A formula and an artificial neural network (ANN) were proposed to predict the permeability coefficient of RCC by considering the main parameters, which were then verified independently using new specimens. Furthermore, the experimental data were analyzed by the Taguchi method and analysis of variance (ANOVA) to evaluate the level of parameter contribution. Based on the results, the permeability coefficient was highly... 

    A novel enzyme based biosensor for catechol detection in water samples using artificial neural network

    , Article Biochemical Engineering Journal ; Volume 128 , 2017 , Pages 1-11 ; 1369703X (ISSN) Maleki, N ; Kashanian, S ; Maleki, E ; Nazari, M ; Sharif University of Technology
    Elsevier B.V  2017
    Biosensors could be used as digital devices to measure the sample infield. Consequently, computational programming along with experimental achievements are required. In this study, a novel biosensor/artificial neural network (ANN) integrated system was developed. Poly (3,4-ethylenedioxy-thiophene)(PEDOT), graphene oxide nano-sheets (GONs) and laccase (Lac) were used to construct a biosensor. The simple and one-pot process was accomplished by electropolymerizing 3,4-ethylenedioxy-thiophene (EDOT) along with GONs and Lac as dopants on glassy carbon electrode. Scanning electron microscopy (SEM) and electrochemical characterization were conducted to confirm successful enzyme entrapment. The...