Novel Correlation for Critical Speed for Solid Suspension in Stirred Tanks Developed Using Machine Learning Models Trained on Literature Data-Reference-Cited by-同舟云学术

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Novel Correlation for Critical Speed for Solid Suspension in Stirred Tanks Developed Using Machine Learning Models Trained on Literature Data

Published:2023-05-24 Issue:22 Volume:62 Page:8954-8971
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Joshi Sumit S.¹,Dalvi Vishwanath H.¹^ORCID,Vitankar Vivek S.²,Joshi Aniruddha J.³,Joshi Jyeshtharaj B.¹⁴^ORCID

Affiliation:

1. Department of Chemical Engineering, Institute of Chemical Technology, Mumbai400019, India

2. FluiDimensions − Engineering Simulations and Consulting, Pune411045, India

3. RPDS Innovations Private Limited, Pune411057, India

4. Homi Bhabha National Institute, Anushaktinagar, Mumbai400085, India,

Funder

United Phosphorous limited

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.3c00488

Reference66 articles.

1. Suspending of solid particles in liquid by agitators

2. Design rules for suspending concentrated mixtures of solids in stirred tanks

3. Suspension of solid particles in turbine agitated baffled vessels

4. Complete suspension of particles in mechanically agitated vessels

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A data-driven model of drop size prediction based on artificial neural networks using small-scale data sets;Chinese Journal of Chemical Engineering;2024-02

2. Novel Correlation for the Solid–Liquid Mass Transfer Coefficient in Stirred Tanks Developed by Interpreting Machine Learning Models Trained on Literature Data;Industrial & Engineering Chemistry Research;2023-11-04

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