Nu Dataset for GNP Flow in Sinusoidal Microchannels

This dataset contains the Nusselt number (Nu) values obtained from a comprehensive 3D CFD study of graphene-water nanofluid flow through sinusoidal microchannels with square cross-sections. The study investigates the effects of six key parameters on convective heat transfer: Reynolds number (Re), nanoparticle concentration (wt.%), amplitude (A) and frequency (ω) of the sinusoidal path, microchannel thickness, and the number of sinusoidal waves (serpentines).

A total of 30 CFD simulations were performed in three parametric groups to obtain the corresponding Nu values. The configurations vary systematically to isolate the influence of each parameter pair. The average Nusselt numbers for each case are reported and have been used further in a two-step machine learning framework for predictive modeling and optimization.

This dataset is intended to support reproducibility, comparative analysis, and future research in microchannel heat sink design and nanofluid applications.