DG Boltzmann Affine-Flow Simulation Data

# DG Boltzmann Affine-Flow Simulation Data This dataset contains raw and processed data files associated with deterministic discontinuous Galerkin simulations of the reduced non-equilibrium Boltzmann equation for universal affine flows. The corresponding analysis code is maintained in the GitHub repository: https://github.com/debnath2109/DG-Boltzmann-for-affine-flows ## Dataset Contents The dataset includes velocity-space DG data files for the following affine flows: 1. Simple shear2. Pressure shear3. Bi-directional shear4. Vortex-like affine flow For each flow, data may be provided for one or more velocity-space meshes: - 27-element velocity-space mesh- 125-element velocity-space mesh The main file types are: # Initial velocity distribution values at the DG nodal points.G_INIT.dat # Time-evolved velocity distribution values. Each row corresponds to one saved time step or iteration, and each column corresponds to one DG degree of freedom / velocity node.gout.dat # Velocity-space nodal coordinates. Each row gives the three velocity components associated with a DG node.NODES.dat # Element-center or element-geometry information used by the reconstruction and collision-operator routines.ELEMENTS.dat # Precomputed sparse collision-operator entries, where applicable. These files may be large and are included only when needed for reproducibility of the original simulations.F1E-8.dat # File Organization: DG-Boltzmann-affine-flow-data-v1.0/│├── README_DATA.md├── manifest.sha256│├── initial/│ ├── G_INIT.dat│ ├── NODES.dat│ └── ELEMENTS.dat│├── simple_shear/│ ├── gout_27.dat│ └── gout_125.dat│├── pressure_shear/│ ├── gout_27.dat│ └── gout_125.dat│├── bidirectional_shear/│ ├── gout_27.dat│ └── gout_125.dat│├── vortex/│ ├── gout_27.dat│ └── gout_125.dat│└── collision_operator/ └── F1E-8.dat How to Use the DataThe data can be analyzed using the scripts in the associated GitHub repository.Typical analysis steps include: 1. Read G_INIT.dat or gout.dat.2. Read nodal velocity coordinates from NODES.dat.3. Reconstruct the DG velocity distribution on a Cartesian velocity grid.4. Fit the reconstructed distribution to an anisotropic Gaussian g(w,t) = a(t) exp[-1/2 w^T C(t)^(-1) w] 1. Extract the fitted covariance tensor C(t).2. Compute eigenvalues, eigenvectors, anisotropy ratios, and principal-axis angles.3. Compare the numerical covariance orientation with the collisionless affine prediction C_fs(t) ∝ (F^T F)^(-1), F(t) = I + tA. ChecksumsA checksum file may be included:manifest.sha256 To verify file integrity, run:sha256sum -c manifest.sha256from the dataset root directory. Notes on Large FilesSome .dat files, especially collision-operator files such as F1E-8.dat, may be several hundred megabytes or larger. These files are not stored directly in the GitHub repository because GitHub regular repositories impose a per-file size limit. They are instead archived in this dataset record. CitationIf using this dataset, please cite the Zenodo DOI associated with this archive and the related paper/manuscript.Suggested citation format: Debnath, A. and Dayal, K. DG Boltzmann affine-flow simulation data. Zenodo. DOI: <https://doi.org/10.5281/zenodo.20518886>.