کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4991698 | 1457117 | 2017 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Modelling of dust removal in rotating packed bed using artificial neural networks (ANN)
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
جریان سیال و فرایندهای انتقال
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چکیده انگلیسی
Artificial neural network (ANN) models, including the Cascade-forward back propagation neural network (CFBPNN), feed-forward back propagation neural network (FFBPNN) and Elman-forward back propagation neural network (EFBPNN), were proposed to predict the dust removal efficiency in rotating packed bed (RPB) to speed up its development. Total 326 data sets for separation grade efficiency had been collected from literatures for training and verifying the model. Gas Reynolds number (ReG), liquid Reynolds number (ReL), rotational Reynolds number (ReÏ), M (d02ÏL/dp2/Ïp) and Csi/ÏG were used as input data. While, the variable η (separation grade efficiency) was taken as output data for each model. Various of hidden neurons were compared based on the mean square error (E2), coefficient of determination (R2) and residual for each model. The separation grade efficiency in RPB was also compared with other existed dust removal equipments.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Thermal Engineering - Volume 112, 5 February 2017, Pages 208-213
Journal: Applied Thermal Engineering - Volume 112, 5 February 2017, Pages 208-213
نویسندگان
Weiwei Li, Xiaoli Wu, Weizhou Jiao, Guisheng Qi, Youzhi Liu,