Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants

Shahaboddin Shamshirband; Meisam Babanezhad; Amir Mosavi; Narjes Nabipour; Eva Hajnal; Laszlo Nadai; Kwok Wing Chau

doi:10.1080/19942060.2020.1715842

Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants

Shahaboddin Shamshirband
, Meisam Babanezhad
, Amir Mosavi
, Narjes Nabipour
, Eva Hajnal
, Laszlo Nadai
, Kwok Wing Chau

Research output: Journal article publication › Journal article › Academic research › peer-review

23 Citations (Scopus)

Abstract

A novel combination of the ant colony optimization algorithm (ACO)and computational fluid dynamics (CFD) data is proposed for modeling the multiphase chemical reactors. The proposed intelligent model presents a probabilistic computational strategy for predicting various levels of three-dimensional bubble column reactor (BCR) flow. The results prove an enhanced communication between ant colony prediction and CFD data in different sections of the BCR.

Original language	English
Pages (from-to)	367-378
Number of pages	12
Journal	Engineering Applications of Computational Fluid Mechanics
Volume	14
Issue number	1
DOIs	https://doi.org/10.1080/19942060.2020.1715842
Publication status	Published - 1 Jan 2020

Keywords

ant colony optimization algorithm (ACO)
big data
Bubble column reactor
computational fluid dynamics (CFD)
flow pattern
machine learning

ASJC Scopus subject areas

General Computer Science
Modelling and Simulation

More information

10.1080/19942060.2020.1715842

http://hdl.handle.net/10397/82213

Cite this

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title = "Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants",

abstract = "A novel combination of the ant colony optimization algorithm (ACO)and computational fluid dynamics (CFD) data is proposed for modeling the multiphase chemical reactors. The proposed intelligent model presents a probabilistic computational strategy for predicting various levels of three-dimensional bubble column reactor (BCR) flow. The results prove an enhanced communication between ant colony prediction and CFD data in different sections of the BCR.",

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author = "Shahaboddin Shamshirband and Meisam Babanezhad and Amir Mosavi and Narjes Nabipour and Eva Hajnal and Laszlo Nadai and Chau, \{Kwok Wing\}",

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Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants. / Shamshirband, Shahaboddin; Babanezhad, Meisam; Mosavi, Amir et al.
In: Engineering Applications of Computational Fluid Mechanics, Vol. 14, No. 1, 01.01.2020, p. 367-378.

Research output: Journal article publication › Journal article › Academic research › peer-review

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AU - Shamshirband, Shahaboddin

AU - Babanezhad, Meisam

AU - Mosavi, Amir

AU - Nabipour, Narjes

AU - Hajnal, Eva

AU - Nadai, Laszlo

AU - Chau, Kwok Wing

PY - 2020/1/1

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AB - A novel combination of the ant colony optimization algorithm (ACO)and computational fluid dynamics (CFD) data is proposed for modeling the multiphase chemical reactors. The proposed intelligent model presents a probabilistic computational strategy for predicting various levels of three-dimensional bubble column reactor (BCR) flow. The results prove an enhanced communication between ant colony prediction and CFD data in different sections of the BCR.

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KW - big data

KW - Bubble column reactor

KW - computational fluid dynamics (CFD)

KW - flow pattern

KW - machine learning

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Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants

Abstract

Keywords

ASJC Scopus subject areas

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