Thermally magnetized Darcy–Forchheimer Eyringen micropolar material subject to chemical kinetics: A machine learning analysis

• Darcy–Forchheimer flow is modeled. • Heterogeneous–homogeneous (HH) chemical processes. • Bayesian regularization scheme (BRS) is adopted. • The results obtained through the proposed AI based NARX-BRS technique meet the reliability criteria as to the overall contribution. Artificial intelligence (AI) is revolutionizing fluid mechanics as it provides revolutionary accuracy with complex, turbulent flows that can be modeled, speed up the simulation of fluid dynamics, and gain new findings from nonconventional data analysis for which conventional computational methods are insufficient. This study presents the numerical analysis of magnetohydrodynamic (MHD) Darcy–Forchheimer micropolar fluid flow with viscous dissipation and heterogeneous–homogeneous chemical reactions using innovative AI approaches. This model is solved utilizing an Artificial Intelligence-based Nonlinear Autoregressive Exogenous (NARX) network with the Bayesian Regularization Scheme (BRS). A dataset is created in Mathematica, with the Adams numerical method, while varying values of Ka, Kp, Md, H, Pr, Q, and Rd. In the case of the formulated strengths of the developed AI based this assessment of logics are then implemented in the evaluation of the dataset of MHD-DFFMPF toward providing rationale for those expected solutions. The achieved as well as the impactful values of the performance are presented in the E −11 – E −13 range across the nine scenarios of the MHD-DFFMPF, demonstrating the model’s excellent accuracy, strong convergence behavior, and computational efficiency throughout all tested cases. It was found that the velocity increased with an increase in Ka and decreased with Kp and Md, while the temperature mount with Pr and Q; however, it dropped with Rd. These results confirmed the physical consistency and robustness of the model with nine graphical MSE trends, histogram patterns, time-series data, regression outcomes, and other supporting graphical quantum. Furthermore, the NARX-BRS model, as proposed, was shown to be trustworthy and accurate, in predicting nonlinear thermofluidic behavior of the MHD Darcy–Forchheimer micropolar system.