Preprint Article Version 1 This version is not peer-reviewed

Prediction of Flow Characteristics in the Bubble Column Reactor by the Artificial Pheromone-Based Communication of Biological Ants

Version 1 : Received: 30 April 2019 / Approved: 5 May 2019 / Online: 5 May 2019 (12:59:23 CEST)

How to cite: Shamshirband, S.; Babanezhad, M.; Mosavi, A. Prediction of Flow Characteristics in the Bubble Column Reactor by the Artificial Pheromone-Based Communication of Biological Ants. Preprints 2019, 2019050025 (doi: 10.20944/preprints201905.0025.v1). Shamshirband, S.; Babanezhad, M.; Mosavi, A. Prediction of Flow Characteristics in the Bubble Column Reactor by the Artificial Pheromone-Based Communication of Biological Ants. Preprints 2019, 2019050025 (doi: 10.20944/preprints201905.0025.v1).

Abstract

In order to perceive the behavior presented by the multiphase chemical reactors,  ant colony optimization algorithm was combined with CFD data. This intelligent algorithm creates a probabilistic technique for computing flow and it can predict various levels of three-dimensional bubble column reactor. This artificial ant algorithms is mimicking the real ant behavior. We found that this method can anticipate the flow characteristics in the reactor using almost 30 % of whole data in the domain. Following discovering the suitable parameters, the method is used for predicting the points not being simulated with CFD, which represent mesh refinement of Ant colony method. In addition, it is possible to anticipate the bubble-column reactors in the absence of numerical results or training of exact values of evaluated data. The major benefits include reduced computational costs and time savings.

Subject Areas

flow pattern; machine learning; computational fluid dynamics; ant colony optimization; swarm intelligence

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.