arXiv:2607.07275v1 Announce Type: new Abstract: Bubbly flows exhibit complex multiscale dynamics, with deformable bubbles interacting through the surrounding liquid and giving rise to strongly coupled kinematic and morphological behavior. We present BubbleSH, a bubbly flows dataset consisting of transient, three-dimensional bubble-swarm dynamics obtained from high-fidelity direct numerical simulations of bubbles rising in a periodic domain. The dataset provides time-resolved bubble trajectories, velocities, and shape evolution, with bubble morphology compactly represented using spherical harmo
The increasing sophistication of AI models and computational fluid dynamics simulations enables the creation of high-fidelity datasets like BubbleSH to tackle complex physical phenomena.
Precise modeling of bubbly flows is critical for optimizing industrial processes, energy systems, and understanding natural phenomena, with AI offering new avenues for analysis and prediction.
This dataset offers a standardized, high-fidelity resource for training and validating AI models in complex fluid dynamics, previously reliant on more constrained empirical or simulated data.
- · AI researchers in fluid dynamics
- · Chemical engineering
- · Energy sector
- · Computational fluid dynamics software developers
Improved AI models for simulating and predicting multiphase flow behaviors become more accessible.
Optimization of industrial processes, such as chemical reactors or heat exchangers, leading to greater efficiency and reduced energy consumption.
New material designs or system architectures that leverage sophisticated control over bubbly flows for novel applications in energy or manufacturing.
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