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 publicationJournal articleAcademic researchpeer-review

7 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 languageEnglish
Pages (from-to)367-378
Number of pages12
JournalEngineering Applications of Computational Fluid Mechanics
Volume14
Issue number1
DOIs
Publication statusPublished - 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

  • Computer Science(all)
  • Modelling and Simulation

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