Just Suspended Speed Simulation in Torus Reactor Using Multiple Non-Linear Regression Model

Separations

article

Houssem Eddine Sayah¹  Ali Alouache²  Mohamed Annad³  Abdelouahab Lefkir³  L’hadi Nouri¹  Ammar Selatnia⁴  Mohammed Messaoudi⁵ 

[1] LRTA Laboratory, University M’hamed Bouguerra;LBSM Laboratory Ecole Normale Supérieure Kouba;Laboratory of TPiTE, National School of Public Works;Ecole Nationale Polytechnique;Nuclear Research Centre of Birine

关键词: torus reactor;    particle suspension;    MNLR;    just suspended speed;    mixing;    loop reactor;   

DOI  :  10.3390/separations10020117

学科分类：社会科学、人文和艺术（综合）

来源: mdpi

【 摘 要 】

In the chemical and water treatment industries, it is necessary to achieve maximum contact between the solid and liquid phase, thus promoting the mass and heat transfer, to obtain a homogeneous solution. Increasing stirring speed is the most recommended solution in different types of reactors: stirred tank, column, and tubular. However, this inadvertently increases the energy consumption of the industry. Determination of the minimum speed, labeled the just suspended speed (Njs) and crucial to attaining homogeneity, has been widely investigated. Numerous studies have been carried out to assess formulas for determining the solid particle speed in various reactor types. Given the limitations of the existing formulations based on a generalization of a unique equation for computing Njs for all soil classifications, it appears that most formulas can only approximate complex phenomena that depend on several parameters. A novel formula was developed, and the results given in this paper demonstrate the effectiveness of generating significant uncertainties for the estimation of Njs. The purpose of this study was the elaboration of experiment-based data-driven formulas to calculate Njs for different particle size classes. Nonlinear multiple regression (MNLR) models were used to generate the new formulas. The gradient descent optimization algorithm was employed to solve the hyperparameters of each novel equation, utilizing supervised learning. A comparison of the data indicated that the unique formulas presented in this study outperformed empirical formulas and provide a useful means for lowering energy consumption, while increasing the heat and mass transfer in torus type reactors.

【 授权许可】

CC BY