Researchers have introduced BubbleSH, a new dataset designed for data-driven modeling of bubbly flows. This dataset captures transient, three-dimensional bubble-swarm dynamics from high-fidelity simulations, providing detailed information on bubble trajectories, velocities, and shape evolution. Bubble morphology is compactly represented using spherical harmonics, making the dataset suitable for developing models that can predict future trajectories and shape changes in complex multiphase systems. AI
IMPACT Enables development of generative models for complex fluid dynamics simulations.
RANK_REASON The cluster describes a new dataset and benchmark for data-driven modeling of multiphase systems, published on arXiv.
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