Published July 21, 2025 | Version v2

Transient Simulation Datasets Using Allen-Cahn and Eriksson-Johnson Equations

  • 1. ROR icon Commonwealth Scientific and Industrial Research Organisation
  • 2. ROR icon Curtin University
  • 3. ROR icon BRAC University

Description

These datasets contain low- and high-resolution numerical simulations of transient initial-boundary-value problems based on the Allen-Cahn and Eriksson-Johnson equations. These data were used in the paper, "PC-SRGAN: Physically Consistent Super-Resolution Generative Adversarial Network for General Transient Simulations", which proposes a physics-informed super-resolution model to reconstruct fine-resolution solutions from coarse simulations. 

Structure

Each of these datasets is split into training, validation and test subsets, each of which has two folders: one for low and another for the high-resolution simulations. Each simulation instance is a folder named after its parameters. Inside that lowest-level folder, each sample is a numpy file (.npy) of a 1-channel image (filename denotes the time point of the simulation). All four of these datasets have a file (index-val-mapping.csv) in their root directory, which provides the mapping of parameters (as seen in the lowest-level folder names) and their actual values.

Dataset statistics

  • Allen-Cahn with Periodic boundary
    ‣ Training: 55,062 samples
    ‣ Validation: 9,065 samples
    ‣ Test: 7,973 samples
    ‣ Total: 72,100 samples
  • Allen-Cahn with Periodic boundary (x4)
    ‣ Training: 27,662 samples
    ‣ Validation: 4,506 samples
    ‣ Test: 3,882 samples
    ‣ Total: 36,050 samples

  • Allen-Cahn with Neumann boundary
    ‣ Training: 15,732 samples
    ‣ Validation: 2,590 samples
    ‣ Test: 2,278 samples
    ‣ Total: 20,600 samples

  • Eriksson-Johnson with Dirichlet boundary
    ‣ Training: 51,875 samples
    ‣ Validation: 8,494 samples
    ‣ Test: 7,352 samples
    ‣ Total: 67,721 samples

The dataset marked "x4" is for 4 times super-resolution (8x8 => 32x32), whereas the rest are for 8 times super-resolution (8x8 => 64x64). These data can be used to benchmark super-resolution methods for physics-based simulations. Refer to the paper for details.

Version history

  • Version 1: Released all three x8 datasets.
  • Version 2: Added the x4 dataset, with no change to earlier datasets.

Files

Files (5.0 GB)

Name Size
md5:c69ca915a7e22974b4273f8d98e0f9e0
615.2 MB Download
md5:e1ecb075adc604c51773694239788474
2.0 GB Download
md5:2da92d5c70a45e864057b5023764f667
273.9 MB Download
md5:3a61b03cc656ef120b72e70eacd1b1a6
2.0 GB Download

Additional details

Related works

Is new version of
Dataset: 10.5281/zenodo.15681250 (DOI)
Is supplement to
Publication: arXiv:2505.06502 (arXiv)

Software

Repository URL
https://github.com/hasan-rakibul/PC-SRGAN
Programming language
Python , Shell
Development Status
Active