Bifurcation analysis of compressible flow past a rotating cylinder for high rotation rate

The present study reports a comprehensive bifurcation analysis of flow past a rotating cylinder at a fixed rotation rate by varying free-stream Reynolds number (Re∞) from 1000–6000 in intervals of 50. Two-dimensional compressible Navier–Stokes equations are solved using dispersion relation preserving numerical methods over 101 test cases, amounting to 106 core hours of computing. The dataset produced from high-fidelity simulations serves as a useful benchmarking tool for testing compressible flow solvers, estimating unsteady force distribution and vorticity dynamics. For moderate Re∞, rotation induces circulation that reduces pressure drag with increasing Re∞. For higher Re∞, boundary layer becomes thinner with suppressed flow separation, but the effect of rotation saturates. Thus, benefits of increasing Re∞ taper off and pressure recovery stalls. The bifurcation analysis reveals a critical Re∞ of 5650 beyond which the global behavior of the Magnus–Robins effect changes significantly. Supercritical flow is receptive to time-dependent instabilities, and structures in wake of the cylinder become dynamically unstable. Even small changes in Re∞ lead to different instantaneous force distributions and sharp fluctuations in lift and drag calculations. Stronger, coherent vortices in the wake generate consistent, high-energy periodic signals, contributing to strong Fourier amplitudes in spectra. An artificial neural network (ANN) is trained using simulation datasets to serve as a fast, inexpensive alternative for calculating lift, drag, and onset time of instability. The ANN reduces time required for simulation by 99.9%, enabling dense parametric sweeps. Maximum accuracy achieved for the ANN is between 90% and 99% for the parameters examined.