Effects of an inclined heated fin in a lid-driven cavity with non-Newtonian bioconvection: A computational fluid dynamics and artificial intelligence analysis
Shafqat Hussain, Hakan F. Öztop, Musaad S. Aldhabani, Fatih Ertam
Abstract
This paper examines the effects of an inclined heated fin on fluid flow and heat transfer within a lid-driven cavity in the presence of non-Newtonian bioconvection. With the help of computational fluid dynamics (CFD) and artificial intelligence (AI) analysis, the complex interplay between the bioconvection of motile microorganisms and the thermal performance with in the cavity is investigated. The CFD simulations examine deep insights into the velocity and temperature fields and highlight the impact of inclined heated fin on the overall thermal performance of the system. AI models are used to predict and optimize the thermal characteristics based on various controlling parameters. The obtained results demonstrate that incorporating an inclined heated fin can improve and control the heat transfer efficiency. A total of twelve datasets created for this study were analyzed using the Categorical Boosting (CATBoost) regression algorithm. The target data were accurately predicted in over 96% of the test data for each dataset. Despite each dataset containing over 170 000 data points, the algorithm demonstrated rapid performance. The results indicate that the CATBoost algorithm achieved successful outcomes on the CFD data.