Thermal dynamics of nanofluids with aggregating nanoparticles and magnetic heating: Utilization of Maxwell-Bruggeman and Kreiger-Dougherty models

Nanoparticle aggregation plays a critical role in enhancing heat transfer processes across various industries. Controlling nanoparticle aggregation can significantly improve thermal efficiency in energy systems, such as solar thermal collectors. Furthermore, in electronic cooling applications, understanding nanoparticle behaviour is vital for optimizing heat dissipation in micro and nano-scale devices. Given the wide-ranging significance of these applications, the current study concentrates on the mathematical modelling and numerical computation of local non-similar flow through a stretching surface coupled with nanoparticle aggregation. Because of viscous dissipation, a constant wall temperature causes local non-similarity, which is a key novelty of our present work. Furthermore, this investigation examines the impact of a uniform magnetic force on heat transfer and fluid flow. The Maxwell-Bruggeman and Kreiger-Dougherty models are used to represent accurately the viscosity and thermal conductivity of a nanofluid containing aggregated nanoparticles. Additionally, the study examines the entropy generation within a local non-similar nanofluid flow featuring nanoparticle aggregation. The pseudo-similarity variable, stream-wise transformed coordinates, dimensionless velocity components, and temperature are used to transform the set of governing equations and associated boundary conditions into dimensionless form. These non-dimensional equations are developed to a second level of truncation. For numerical solutions, a robust numerical scheme called the generalized differential quadrature method is implemented. The findings are visually presented and discussed, encompassing both scenarios with and without aggregation. The study provides a numerical comparison of heat transfer enhancement in tabular format concerning the growing values of nanoparticle volume fraction, considering both the presence and absence of aggregation. Notably, the results reveal that heat transfer enhancement is substantially more pronounced in the presence of aggregation than in its absence. Moreover, the analysis underscores that nanoparticle aggregation leads in higher entropy generation. It is observed that when aggregation is not taken into consideration, the velocity profile is lower when it is. Furthermore, it is found that as the values of the transformed stream-wise coordinate, Hartman number and temperature difference parameter grew, Bejan's number profile diminished.