This study aims to investigate the effects of implicit numerical excitation on the receptivity of flow inside a square lid-driven cavity (LDC) leading to bifurcation and instability for a fixed (257 × 257) grid with different temporal resolutions via the solution of the Navier-Stokes equation. Computational results have been provided showing the flow dynamics of the LDC problem as explained with a time series at a representative point near the top corner of the cavity at (0.95, 0.95) for supercritical Reynolds numbers with respect to the bifurcation phenomenon by lowering the time step. As the accuracy of numerical methods plays a vital role in capturing the dynamics at different Reynolds numbers, this vortex-dominated flow is explained for bifurcation and instability. We propose this as a benchmark problem for the direct numerical simulation (DNS) and for machine learning (ML) of fluid flow that will lead to efficient ML algorithms and an understanding of flow receptivity, instability, and transition by DNS.

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