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2026 Michel ONE CYLinder Bluff Body Flow Benchmark

Théodore Michel, Antoine Campos

2026encomputational fluid dynamicssurrogate modelinggraph neural networkstransformersunstructured meshesbluff-body flows

Abstract

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Graph-based surrogate models offer a promising route to accelerate computational fluid dynamics (CFD) simulations on unstructured meshes. However, their development is limited by the scarcity of benchmark datasets spanning multiple flow regimes and standardized protocols for long-horizon autoregressive prediction. We introduce ONECYL (ONE CYLinder), a new benchmark for unsteady flow past a circular cylinder across laminar, transitional, and high-Reynolds-number regimes. The benchmark comprises 450 high-fidelity Variational Multiscale finite-element simulations (270,000 flow snapshots) with randomized cylinder geometries, providing time-resolved velocity and pressure fields together with mesh connectivity, geometric descriptors, Reynolds numbers, and integrated aerodynamic quantities. Beyond the dataset, ONECYL establishes a unified evaluation framework combining full-field rollout errors, virtual probes, and drag and lift predictions to assess numerical accuracy and physical fidelity. To accompany the benchmark, we develop a Graph Transformer as a reference baseline predicting velocity and pressure fields autoregressively on unstructured meshes. Using ONECYL, we investigate geometric representations and physics-based regularization across the three Reynolds-number regimes. The results show that explicitly encoding the cylinder geometry through a level-set representation consistently improves long-horizon prediction accuracy and generalization to unseen geometries, while divergence-based regularization becomes increasingly beneficial as flow complexity increases. The initializer–iterator strategy enables end-to-end prediction from the prescribed initial and boundary conditions, eliminating the need for a CFD-computed initialization during inference while maintaining stable 600-step rollouts. The ONECYL benchmark and accompanying Graph Transformer baseline provide a reproducible framework for evaluating graph-based surrogate models and establish a foundation for future research on long-horizon prediction of unsteady bluff-body flows.

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Cite This Work

@article{06155e7c-f263-4118-ae91-504a3c8fc5d2,
  title={2026 Michel ONE CYLinder Bluff Body Flow Benchmark},
  author={Théodore Michel and Antoine Campos},
  year={2026},
  language={en}
}
TY  - JOUR
TI  - 2026 Michel ONE CYLinder Bluff Body Flow Benchmark
AU  - Théodore Michel
AU  - Antoine Campos
PY  - 2026
LA  - en
ER  -

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