Impact of Key DMD Parameters on Modal Analysis of High-Reynolds-Number Flow Around an Idealized Ground Vehicle - Hamed Ahani; Mesbah Uddin (Applied Sciences)
This study provides a detailed analysis of the convergence criteria for dynamic mode decomposition (DMD) parameters, with a focus on sampling frequency and period in high-Reynolds-number flows. The analysis is based on flow over an idealized road vehicle, the Ahmed body (<semantics>Re=7.7×105</semantics>), using computational fluid dynamics (CFD) data from improved delayed detached eddy simulation (IDDES). The pressure and velocity spectrum analysis validated IDDES’s ability to capture system dynamics, consistent with existing studies. For a comprehensive understanding of the contributions of different components of the circle, the Ahmed body was divided into three regions: (a) front; (b) side, lower, and upper surfaces; and (c) rear fascia. Both pressure and skin-friction drag were analyzed in terms of frequency spectra and cumulative energy. Key findings show that a 90% contribution to the pressure drag comes from modes with a frequency of less than 26 Hz (<semantics>St</semantics> = 0.187), while the friction drag requires 84 Hz (<semantics>St</semantics> = 0.604) for similar energy capture. This study highlights the significance of accounting for intermittency and non-stationary behavior in turbulent flows for DMD convergence. A minimum of 3000 snapshots is necessary for the convergence of DMD eigenvalues, and sampling frequency ratios between 5 and 10 are needed to achieve a reconstruction error of less than 1%. The sampling period’s convergence showed that <semantics>T*=250</semantics> (equivalent to 20 cycles of the slowest coherent structures) stabilizes coherent mode shapes and energy levels. Beyond this, DMD may become unstable. Additionally, mean subtraction was found to improve DMD stability. These results offer critical insights into the effective application of DMD in analyzing complex vehicle flow fields.