Simulations of the Concentration Fields of Rosette-Type Multiport Buoyant Discharges Using Combined CFD and Multigene Genetic Programming Techniques

Journal of Marine Science and Engineering

Abdolmajid Mohammadian¹  Xiaohui Yan²  Jianwei Liu²  Yan Wang² 

[1] Department of Civil Engineering, University of Ottawa, Ottawa, ON K1N 6N5, Canada;School of Water Resources Engineering, Dalian University of Technology, Dalian 116024, China;

关键词: numerical modeling;    computational fluid dynamics;    multigene genetic programming;    rosette-type diffusers;    buoyant discharges;   

DOI  :  10.3390/jmse9111311

来源: DOAJ

【 摘 要 】

Rosette-type diffusers are becoming popular nowadays for discharging wastewater effluents. Effluents are known as buoyant jets if they have a lower density than the receiving water, and they are often used for municipal and desalination purposes. These buoyant effluents discharged from rosette-type diffusers are known as rosette-type multiport buoyant discharges. Investigating the mixing properties of these effluents is important for environmental impact assessment and optimal design of the diffusers. Due to the complex mixing and interacting processes, most of the traditional simple methods for studying free single jets become invalid for rosette-type multiport buoyant discharges. Three-dimensional computational fluid dynamics (3D CFD) techniques can satisfactorily model the concentration fields of rosette-type multiport buoyant discharges, but these techniques are typically computationally expensive. In this study, a new technique of simulating rosette-type multiport buoyant discharges using combined 3D CFD and multigene genetic programming (MGGP) techniques is developed. Modeling the concentration fields of rosette-type multiport buoyant discharges using the proposed approach has rarely been reported previously. A validated numerical model is used to carry out extensive simulations, and the generated dataset is used to train and test MGGP-based models. The study demonstrates that the proposed method can provide reasonable predictions and can significantly improve the prediction efficiency.

【 授权许可】

Unknown