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

• Published in: Engineering applications of computational fluid mechanics Vol. 14; no. 1; pp. 367 - 378
• Main Authors: Shamshirband, Shahaboddin, Babanezhad, Meisam, Mosavi, Amir, Nabipour, Narjes, Hajnal, Eva, Nadai, Laszlo, Chau, Kwok-Wing
• Format: Journal Article
• Language: English
• Published: Hong Kong Taylor & Francis 01.01.2020; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Algorithms; Ant colony optimization; ant colony optimization algorithm (ACO); big data; Bubble column reactor; Bubble columns; Chemical reactors; Computational fluid dynamics; computational fluid dynamics (CFD); Flow characteristics; flow pattern; machine learning; Mathematical models; Three dimensional models
• ISSN: 1994-2060; 1997-003X; 1997-003X
• DOI: 10.1080/19942060.2020.1715842

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.