期刊
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
卷 57, 期 1, 页码 259-267出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.iecr.7b02869
关键词
-
资金
- project VAL ORCOMP through INTERREG V A Spain Portugal (POCTEP) under European Regional Development Fund (ERDF), by the Portuguese Foundation for Science and Technology (FCT) [0119_VALORCOMP_2_P]
A tapered fluidized bed with variable fluid velocity throughout the bed length is a special type of fluidized system. Accurate estimation of hydrodynamic characteristics of the tapered fluidized bed is required for adjusting the operational conditions, optimum design, and process control of this system. In this way, minimum fluidization velocity (U-mf), minimum velocity of full fluidization (U-mff), and maximum pressure drop (Delta P-max) are the main hydrodynamic characteristics of the tapered fluidized bed. In this study, an artificial neural network (ANN) paradigm was developed for prediction of these parameters. Parameters of the ANN model was adjusted through minimization of the absolute average relative deviation (AARD) and mean square error (MSE) via a back-propagation algorithm. Finally, the proposed model predicted the experimental data of U-mf, U-mff, and Delta P-max, with AARD of 1.1%, 1.36%, and 0.89%, respectively, while the best obtained results by five different empirical correlations were 4.12%, 9.4%, and 5.14% for U-mf, U-mff, and Delta P-max.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据