36 datasets found

The dataset used for testing the generative model, containing 3D liquid simulations.

The dataset used for testing the generative model, containing 3D smoke simulations.

The dataset used for testing the generative model, containing 2D smoke plume simulations.

The dataset used for training the generative model, containing discrete, parameterizable fluid simulation velocity fields.

2D turbulence data set is the vorticity field from direct numerical solutions of 2-dimensional Navier-Stokes equations using pseudo-spectral methods in a periodic domain

Two benchmark data sets: 2D turbulence and clouds of Jupiter, are chosen for validation against a survey of LCS to methods from [44], and a simulated climate data set...

The dataset is used to study the transport of aerosol particles in an air-based environment.

The dataset used in this paper is a high-resolution turbulent channel flow data from UT Texas and JHTD at Reynolds number of 1000.

The dataset used in this paper is a high-resolution isotropic turbulence data from UP Madrid turbulence database (UPMTD) at Reynolds number of 315.

The dataset used in this paper is a high-resolution incompressible isotropic turbulence data from John Hopkins University turbulence database (JHTD) at Reynolds number of 433.

A dataset of turbulent boundary layer flow measurements.

A dataset of turbulent channel flow simulations.

The dataset used for testing the U-Net and U-Net-MG models for flow past a stationary cylinder, flow past two cylinders in out-of-phase motion, and flow past an oscillating foil.

The dataset is used for reconstruction of nonlinear flow from spatially sparse observations.

The dataset is a two-dimensional turbulent flow, analyzed using a convolutional autoencoder echo state network (CAE-ESN) for spatiotemporal decomposition and prediction of...

A Point-Cloud Deep Learning Framework for Prediction of Fluid Flow Fields on Irregular Geometries

The dataset used in this paper is a collection of solutions for advection of a square wave and a Gaussian function on an unstructured mesh.

The dataset used in this paper is a collection of solutions for 2D flow past a cylinder solved on an unstructured mesh.

The dataset used in this paper is a collection of trajectory data of the time range [0, T ] for training, and the remaining time range (T, T + δ] for testing.

Synthetic data set of the Burgers equation ut = νuxx − uux, with a delta peak initial condition u(x, t = 0) = Aδ(x) and domain t ∈ [0.1, 1.1], x ∈ [−3, 4].