Dataset for Off-centered stagnation-controlled strategy mechanism on heat transfer aspects of chemically reactive non-Newtonian nanofluid

The current data is associated with the study on the off-centered stagnation-controlled strategy mechanism on a non-Newtonian chemically reactive nanofluid using an artificial neural network analysis. When evaluating the mass and heat transport of fluid flow, the importance of both active and passive control of nanoparticles is considered. It is designed to monitor the numerical approximation of the heat transfer rate for different parameters in both control scenarios through testing, training, and validation. The Excel file contains the numerically generated Nusselt number values corresponding to varying values of the heat source/sink parameter and Brownian motion parameter. It also contains the Nusselt number values predicted using the ANN model, together with the associated error and absolute error values for both active and passive control cases.