Modeling of Oil-Water Emulsion Separation in Ultrasound Standing Wavefield by Neural Network

Abstract

A new approach has been introduced for separation of oil-in-water emulsion by using ultrasound standing wavefield. A neural networks model was used to simulate changes in the size of droplet during treatment. Model outputs were then validated and generalization capability was evaluated. For each network, the optimum values of isotropic spread were obtained by minimizing the root mean square error and maximizing the corresponding coefficient. It was found that the predicted values were in good agreements with experimental results. Also, increasing voice speed was demonstrated to predict size of emulsion particles more efficiently and accurately.

Recent developments, challenges, and prospects of ultrasound-assisted oil technologies

“…In addition, emulsions could lead to clogging, corrosion and erosion in pipelines during transportation and the poisoning of catalysts in the refining process [16] , [17] , [18] , [19] , [20] , [21] , [22] . Hence, there are many studies that have been reported on the demulsification of crude oil [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] , [47] .…”

“…The approaches that have been pursued in the demulsification process includes biological [23] , [24] , [25] , chemical [26] , [27] , [28] , [29] , [30] , [31] and physical [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] , [47] separation processes. Although biological separation through bacteria or synthetic agents provides better environmental benefits when compared to chemical demulsifiers, the separation process takes significant amount of time that could disrupt oil production.…”

“…Membranes are often affected by fouling which causes reduced flux, lower lifespan, costly maintenance and subsequent damage of the membrane [34] . Ultrasonic assisted demulsification of oil emulsions could potentially resolve many challenges faced by the other technologies either when used as an integrated addition or as standalone [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] .…”

“…Similar improvements in the rate of oil recovery by 20–75% have been shown in several laboratory and field studies [14] , [9] , [10] , [11] . Developments have been witnessed as well in the dehydration of water in oil emulsions, with separation efficiencies between 20 and 95% [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] , [53] . Due to these significant developments and numerous research findings in US assisted oil technologies which has seen sustained increment in the past decade, there is a need for a detailed review which highlights the progress and challenges as well as prospects ( Fig.…”

Prediction of Density, Surface Tension, and Viscosity of Quaternary Ammonium-Based Ionic Liquids ([N222(n)]Tf2N) by Means of Artificial Intelligence Techniques

“…[42][43][44][45][46][47][48][49][50][51][52] For example, by using ANN technique, Mohanty [42] estimated the vapor liquid solubility of binary mixtures with an average absolute deviation of 3% for liquid phase and less than 0.02% for vapor phase mole fractions. Nguyen et al [43] applied ANN with 8:6:7:4 network as the optimum architecture to estimate vapor-liquid equilibrium data and bubble point for ternary systems with the lowest possible error.…”