Intelligent and optimized nanofluid heat transfer for tube shape heat exchanger

The heat exchange approach is used in various thermal systems for industrial applications. The optimal heat exchange system possesses efficiency in heat management, minimal operating load with maximum outcomes, operational flexibility of the moving fluids, better heat transfer capacity with optimal flow management, and low initialization cost and maintenance charges. The inclusion of nanofluids in heat exchange systems is a recently evolved approach. Thereafter, the effective functioning of the heat exchange system is primarily based on the nanoparticle characteristics along with the hot fluid. This study aims to deliver a novel decision hybrid optical system (DHOS) in heat exchange systems to predict outcomes. The heat exchange system adopted is of shell and tube type with titanium dioxide (TiO2) as the heat exchanging fluid running on the tubes with TiO2-based nanoparticles. The model is optimized for optimal drop in pressure and transfer of heat. Then, the parameters in the system in transferring heat, entropy measure, and error rate are determined and correlated with the recent models. The bejan number of the entropy measure is also specified for the heat exchange system.