ABSTRACT This study investigates mixed convection heat transfer of water AL 2 O 3 Nanofluid inside a corrugated cavity containing star shaped heated baffles. The effects of the Rayleigh number, nanoparticle volume fraction, and baffle position are examined under buoyancy‐driven flow conditions. The governing equations are solved using the finite element method, and the thermal performance is evaluated through the average Nusselt number at the heated walls. To validate the numerical results, an artificial neural network model is developed based on the simulation data. The ANN predictions show excellent agreement with the numerical results, with correlation coefficients close to one. The results indicate that the use of nanofluids significantly enhances convective heat transfer. Moreover, the inclination of the baffles improves heat transport by directing buoyant flow toward the center of the cavity. The star‐shaped cavity design further enhances heat transfer by strengthening fluid circulation and thermal mixing. Overall, the combined FEM‐ANN approach provides a reliable tool for predicting mixed convection heat transfer in complex geometries.
Salma et al. (Sun,) studied this question.