Intelligent airflow control technology for microbubble drag reduction based on improved ant colony optimization algorithm

Abstract

Objective In order to improve the actual efficiency of microbubble drag reduction technology, this study develops intelligent airflow control technology for microbubble drag reduction based on an improved ant colony optimization (ACO) algorithm.MethodsBased on the mechanism of microbubble drag reduction, the ideal optimal airflow rate at different speeds is obtained by carrying out microbubble drag reduction tests on a self-developed ship model prototype. The software system of intelligent airflow control technology is developed by employing the improved ACO algorithm. A self-propelled test on a ship model installed with an intelligent control hardware system is carried out to verify the actual drag reduction effect of this technology. ResultsThe technology proposed in this study can effectively control the airflow to reach the optimal microbubble drag reduction condition, and can also monitor the speed change and adaptively control the airflow to achieve the best drag reduction conditions at various speeds.Conclusion This technique improves the automation and intelligence level of microbubble drag reduction technology while enhancing its actual efficacy.

Keywords

• microbubble drag reduction
• improved ant colony optimization algorithm
• intelligent control of airflow
• self-propelled model test