Cylinder wake at Re=100 — rotary-control training dataset
Training data for a mesh-transformer dynamics surrogate of the 2D cylinder wake (HydroGym / Firedrake, Re=100, M=8,744 mesh vertices), actuated by cylinder rotation. Built for a GNN-MPC pipeline: the surrogate learns the one-step map (x_k, Omega_k) -> x_{k+1} at the control period dt = 0.1 (10 solver substeps of dt=0.01, matched sampling).
Contents
dataset/traj_XXX.npz— 220 trajectories, 300 control steps each (66,000 transitions). Per file:v[301, 8744, 2] float32 CG1 velocity snapshots (vertex order matchesmesh/),cmd_omega[300],meas_omega[301] (wall-measured rotation — integrity check vs the actuator-lag model holds to 5.8e-5 across all files),CL,CD[301],meta(JSON job spec incl. RNG seed — every trajectory exactly regenerable).dataset/manifest.json— job specs and the frozen train/val/test split (192/14/14, split by trajectory). Test = special trajectories (unforced replays + sinusoids), quarantined for evaluation.dataset/norm_stats.npz— normalization statistics, train split only.mesh/cylinder_re100_dataset.npz— vertex positions [8744,2], triangles [17258,3], node types (0 interior, 1 cylinder, 2 inlet, 3 outlet, 4 freestream), plus a 201-frame uncontrolled reference movie.constants/actuation_constants.json— measured plant constants: R=0.5, U_inf=1, actuator lag tau=0.0556, sign conventions, base-flow growth rate sigma=0.1506, St_linear=0.139, St_nonlinear=0.172, Omega_max=2.0.checkpoints/— Firedrake restart files: settled limit cycle, unstable steady base flow qB (Newton+continuation), and the six growth-run amplitude rungs used as corridor initial conditions.scripts/— full generation + training code (HydroGym 1.0 / Firedrake).
Trajectory composition
| kind | count | initial condition | forcing |
|---|---|---|---|
| cycle_ou | 100 | limit cycle, random phase | clipped OU walk (a=0.93), tiered sigma |
| growth_ou | 90 | growth-run amplitude rungs | clipped OU walk |
| qB_nudge_ou | 16 | base flow + fresh random nudge | gentle OU walk |
| unforced / sine | 14 | cycle & corridor | none / sinusoidal Omega |
Excitation follows Eberhard et al. (arXiv:2602.17601): random-walk inputs at the MPC sampling period; volume calibrated to Garnier et al. (arXiv:2508.18051).
Regenerability
scripts/generate_dataset.py --id N with dataset/manifest.json reproduces any
trajectory bit-for-bit (deterministic solver, stored seeds) given a HydroGym
1.0 + Firedrake environment and the checkpoints/ restart files.
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Papers for melloyello/graphtrans
Paper • 2602.17601 • Published
Training Transformers for Mesh-Based Simulations
Paper • 2508.18051 • Published • 1