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http://hdl.handle.net/10397/82213
Title: | Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants | Authors: | Shamshirband, S Babanezhad, M Mosavi, A Nabipour, N Hajnal, E Nadai, L Chau, KW |
Issue Date: | 2020 | Source: | Engineering applications of computational fluid mechanics, 2020, v. 14, no. 1, p. 367-378 | 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. | Keywords: | Bubble column reactor Ant colony optimization algorithm (ACO) Flow pattern Machine learning Computational fluid dynamics (cfd) Big data |
Publisher: | Taylor & Francis | Journal: | Engineering applications of computational fluid mechanics | ISSN: | 1994-2060 | EISSN: | 1997-003X | DOI: | 10.1080/19942060.2020.1715842 | Rights: | © 2020 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited The following publication Shahaboddin Shamshirband, Meisam Babanezhad, Amir Mosavi, NarjesNabipour, Eva Hajnal, Laszlo Nadai & Kwok-Wing Chau (2020) Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biologicalants, Engineering Applications of Computational Fluid Mechanics, 14:1, 367-378 is available at https://dx.doi.org/10.1080/19942060.2020.1715842 |
Appears in Collections: | Journal/Magazine Article |
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