Hybrid Experimental–AI Framework for Thermal Performance Optimization of ZnO–Water Nanofluids in Automotive Radiators

Abstract The growing need for enhanced thermal regulation in both electric and internal combustion engine vehicles has driven significant research efforts toward the development of next-generation heat exchanger technologies. Motivated by the pressing need for thermally consistent and high-fidelity prediction tools in contemporary automobile systems, this study introduces a novel hybrid framework by coupling empirical results from ZnO–water nanofluid experiments with physics-informed neural networks (PINN). This approach is crucial for connecting empirical data with fundamental physical rules for accurate thermal prediction. The experimental investigations were carried out across a range of operating parameters, including nanoparticle volume concentrations from 0 to 0.1%, inlet temperatures between 40 °C and 80 °C, and volume flow rates varying from 5 to 11 LPM. Major results revealed that the highest thermal enhancement was achieved at a ZnO concentration of 0.025%, which led to an increase of up to 213% in the convective heat transfer coefficient and a 214% improvement in the Nusselt number relative to pure water, particularly under low-temperature conditions. Beyond this concentration, performance deteriorated due to agglomeration and increased viscosity. Using the experimental data, both artificial neural network (ANN) and physics-informed neural network (PINN) models were developed to predict key parameters such as the Nusselt number and heat transfer coefficient. The PINN model outperformed the ANN, yielding approximately 7.6% higher R 2 for the heat transfer coefficient (0.9167 vs 0.8354) and 8.7% higher R 2 for Nusselt number predictions (0.8697 vs 0.7901). These findings highlight the importance of creating a high-fidelity digital twin architecture that addresses the ‘black-box’ constraints of traditional AI, offering a comprehensive solution for real-time optimization and monitoring of advanced automobile cooling systems.