Characterizing nonlinear flow dynamics in hydrodynamic and magnetohydrodynamic regimes through modal decomposition

The study delves into the dynamic behavior of fluid flows in hydrodynamic (HD) and magnetohydrodynamic (MHD) regimes, specifically focusing on the influence of varying magnetic field strengths on vortex shedding around a cylinder. Employing advanced modal decomposition techniques such as Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD), the research unveils the intricate characteristics of these flow fields. In HD scenarios, the flow exhibits complex, periodic patterns with notable vortex shedding, whereas in MHD scenarios, the introduction of magnetic fields gradually transforms the flow into a more stable and streamlined state. The study significantly demonstrates the damping effect of magnetic fields on vortex intensity and oscillations, leading to a uniform flow at higher field strengths. This study leverages DMD to predict future flow dynamics in both HD and MHD regimes around a cylinder. By using snapshots from CFD simulations at Re $=$ 120, we validate DMD’s predictive capabilities by comparing predicted snapshots with CFD results at corresponding time instants. This approach not only demonstrates DMD’s robustness in capturing complex flow behaviors but also highlights its potential for real-time monitoring and control in industrial applications. The findings provide new insights into the temporal dynamics of MHD flows and open avenues for optimizing flow control strategies in engineering systems.