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Deep Fluids: A Generative Network for Parameterized Fluid Simulations
The dataset used for training the generative model, containing discrete, parameterizable fluid simulation velocity fields. -
Turbulent Flow Dataset
The dataset for the experiments comes from two dimensional turbulent flow simulated using the Lattice Boltzmann Method. The dataset consists of 1500 images of velocity fields,... -
Thermodynamics-informed super-resolution of scarce temporal dynamics data
The dataset used in this paper is a set of low-resolution velocity and pressure fields for a flow past a cylinder of a non-Newtonian fluid, generated using in-silico simulations. -
BFS simulation trajectories
The dataset used in this work is a collection of snapshots describing the evolution of two-component velocity fields in a cropped mesh of a backward-facing step (BFS)...