Cooling of a hot elastic wall in a double vented cavity system by using sinusoidal corrugated porous partition during hybrid nanofluid forced convection and AI-assisted modeling

The need for new cooling solutions is growing for thermal management and energy storage in various energy systems. This study proposes a novel cooling system for sinusoidal corrugated porous partition (SCPP) with hybrid nanofluid for hot elastic wall in a double vented cavity (VEC) system. Both rigid and elastic wall scenarios are taken into consideration in the numerical analysis based on the finite element method (FEM), which is carried out for various values of the left cavity flow Reynolds number ( Re L between 200 and 1000), wave amplitude ( A f between 0.01 and 0.25), and wave number ( N f between 1 and 6) of SCPP. A cooling model is developed using an artificial neural network (ANN) approach, and comparisons with computational fluid dynamics (CFD) simulations are executed. In contrast to the rigid scenario, the vortex size below the entrance port is impacted at the maximum Re L due to the heated elastic wall’s significant deformation. In the case of rigid walls, the average Nusselt number (Nu) with Re L is enhanced by 132%, whereas in the case of elastic walls, it is enhanced by 255%. The cooling performance improvement with the highest corrugation amplitude is 7.2% for rigid case and 12.4% for elastic case. The average Nu variation increases by 3% for elastic scenarios and by 9% for rigid scenarios when the wave number of corrugation is changed. The optimal cooling performance is achieved with the ANN model for rigid walled configuration at ( Re L , A f , N f )=(1000, 0.25, 3), and for elastic walled configuration at ( Re L , A f , N f )=(1000, 0.25, 2). The maximum cooling performance case provides cooling performance boost factors of 4.16 and 4.32 for the rigid and elastic cases, respectively, in contrast to the reference configuration of Re L =200 with a flat partition.