Non-spherical solid-non-Newtonian liquid fluidization and ANN modelling: Minimum fluidization velocity
| Autor: | Sudip Kumar Das, Sudipta Let, Nirjhar Bar, Samit Bikas Maiti |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Shear thinning
Materials science Applied Mathematics General Chemical Engineering 02 engineering and technology General Chemistry Mechanics 010501 environmental sciences 01 natural sciences Industrial and Manufacturing Engineering Non-Newtonian fluid Sphericity Physics::Fluid Dynamics Condensed Matter::Soft Condensed Matter 020401 chemical engineering Rheology Control theory Particle Particle size Fluidization 0204 chemical engineering Gradient descent 0105 earth and related environmental sciences |
| Zdroj: | Chemical Engineering Science. 176:233-241 |
| ISSN: | 0009-2509 |
| DOI: | 10.1016/j.ces.2017.10.050 |
| Popis: | Experiments have been carried out to determine the minimum fluidization velocity for sand particles of irregular shape and size using pseudoplastic liquids in different Perspex columns. The effect of different operating parameters, like column diameter, particle size and shape, rheological properties of the liquid on minimum fluidization velocity has been investigated. It has been observed that as sphericity of the particle decreases, minimum fluidization also decreases. Empirical correlation has been developed to predict the minimum fluidization velocity as a function of physical and dynamic variable of the system. Statistical analysis of the correlation suggests that is of acceptable accuracy. Applicability of the artificial neural network modelling using gradient descent and Levenberg-Marquardt algorithm have also been successfully tested. |
| Databáze: | OpenAIRE |
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