Prediction of the Particle Size Distribution Parameters in a High Shear Granulation Process Using a Key Parameter Definition Combined Artificial Neural Network Model-Reference-Cited by-同舟云学术

Prediction of the Particle Size Distribution Parameters in a High Shear Granulation Process Using a Key Parameter Definition Combined Artificial Neural Network Model

Published:2015-10-26 Issue:43 Volume:54 Page:10825-10834
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Yu Huiman¹,Fu Jinsheng²,Dang Leping¹,Cheong Yuensin²,Tan Hongsing²,Wei Hongyuan¹

Affiliation:

1. School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, P. R. China

2. Procter & Gamble Technology (Beijing) Co., Ltd., Beijing 101312, P. R. China

Funder

Procter & Gamble

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.5b02679

Reference44 articles.

1. Prediction of impeller torque in high shear powder mixers

2. Population balance modelling of granulation with a physically based coalescence kernel

3. A discretized population balance for nucleation, growth, and aggregation

4. Scale-up of binder agglomeration processes

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