Experimental Study and Numerical Modeling of Rheological and Flow Behavior of Xanthan Gum Solutions Using Artificial Neural Network

被引:10
|
作者
Razi, Meisam Mirarab [1 ]
Kelessidis, Vassilios C. [2 ]
Maglione, Roberto
Ghiass, Majid [3 ]
Ghayyem, Mohammad Ali [4 ]
机构
[1] Iran Univ Sci & Technol, Dept Chem Engn, Tehran, Iran
[2] Texas A&M Univ, Dept Petr Engn, Doha, Qatar
[3] Iran Univ Sci & Technol, Iran Polymer & Petrochem Inst, Tehran, Iran
[4] Petr Univ Technol, Dept Comp Sci, Ahvaz, Iran
关键词
Artificial neural network; drilling fluid; Herschel-Bulkley; rheological properties; xanthan gum; DRILLING-FLUIDS; PRESSURE; OPTIMIZATION; PREDICTION;
D O I
10.1080/01932691.2013.809505
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
This study investigated effect of temperature, concentration, and shear rate on rheological properties of xanthan gum aqueous solutions using a Couette viscometer at temperatures between 25 degrees C and 55 degrees C and concentrations of 0.25 wt% to 1.0 wt%. The Herschel-Bulkley model described very well the non-Newtonian behavior of xanthan gum solutions. Shear rate, temperature, and concentration affected apparent viscosity and an equation was proposed for the temperature and concentration effect valid for each shear rate. This article also presents an artificial neural network (ANN) model to predict apparent viscosity. Based on statistical analysis, the ANN method estimated viscosity with high accuracy and low error.
引用
收藏
页码:1793 / 1800
页数:8
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