DEVELOPMENT OF NOVEL GENETIC PROGRAMMING-BASED ANALYTICAL CORRELATIONS FOR EVALUATING THE IMPACT OF NANOFLUID SHAPE AND CONCENTRATION ON THERMAL PERFORMANCE, PRESSURE DROP, AND FOULING RESISTANCE IN PLATE HEAT EXCHANGERS

Plate heat exchangers (PHEs) are crucial in industrial applications where efficiency and performance are of paramount importance. This study introduces an innovative approach using advanced genetic programming (GP) to develop analytical correlations that elucidate the effects of nanoparticle shape on PHE thermal performance. Various nanoparticle shapes, concentrations, and sizes were investigated through comprehensive numerical simulations to assess their impact on heat transfer, pressure drop, and fouling resistance. The genetic programming technique yielded precise analytical models, providing a robust predictive framework for performance metrics. Notably, cylindrical nanoparticles at 0.35% concentration demonstrated optimal heat transfer efficiency with minimal pressure drop, outperforming spherical and platelet shapes. The novelty of this dual approach, combining genetic programming with numerical simulations, advances the understanding of nanofluid applications in heat exchangers and lays a foundation for future optimization of nanoparticle shapes to achieve superior thermal performance and energy efficiency in industrial applications.