Thermo-Fluid Dynamic Performance of Self-Similar Dendritic Networks: CFD Analysis of Structural Isomers

This study investigates the asymmetric effects applying heat transfer as a diagnostic tool in dendritic networks with symmetrical branching, characterized by the geometric property of self-similarity. Using a Computational Fluid Dynamics (CFD) model, we analyze five structural isomers of a three-level dichotomous branching network to evaluate the relationship between fluid dynamics, heat transfer, and geometric configuration. The main constraints are geometrical; that is, the volume at each branching level remains constant, and homothetic relationships respect the Hess–Murray law both for diameters and angles between sister tubes. The model considers an incompressible and stationary Newtonian fluid flow with Reynolds numbers ranging from 10 to 2000 and heat transfer in the range 1 to 1000 W/m2. Our results show that significant asymmetries in flow distribution and temperature profiles emerge in these symmetric structures, primarily due to the successive alignment of tubes between different branching levels. We found that the isomer with the lowest pressure drop is not the same as the one providing the most uniform flow distribution. Crucially, thermal analysis proves to be more sensitive than fluid dynamic analysis for detecting flow asymmetries, particularly at low Reynolds numbers less than 50 and q″ = 1000 W/m2. While heat transfer does not significantly alter the fluid dynamic asymmetry, its application as a diagnostic tool for identifying flow asymmetries is effective and crucial for such purposes.