Repository for: "Extreme statistic and extreme events in dynamical models of turbulence"
<div>This repository contains underlying data, post-processing scripts and figure scripts, corresponding to the article "Extreme statistic and extreme events in dynamical models of turbulence", X.M. de Wit, G. Ortali, A. Corbetta, A.A. Mailybaev, L. Biferale, F. Toschi, 2024, Phys. Rev. E 109 (5), 055106.</div> <div> </div> <div><strong>Data</strong></div> <div>Raw data of the obtained moments and histogram of the structure function are provided in 'PRODUCTION/STAT_RUNS/' and 'VALIDATION/STAT_RUNS/' respectively for the production runs and validation runs.</div> <div> </div> <div><strong>Post-processing</strong></div> <div>Various post-processing routines for e.g. the computation of the anomalous scaling exponents are provided in the Jupyter notebooks 'PROD_process.ipynb' and 'VALI_*_process.ipynb' respectively for the production runs and validation runs. The computation of the singularity spectrum is provided in 'PROD_singularity_spec.ipynb'.</div> <div> </div> <div><strong>Figures</strong></div> <div>Reproduction of the figures as appearing in the paper can be done using the corresponding Jupyter notebooks labeled as 'PAPER_*.ipynb'.</div>
ShareScore
24/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 8
- Reuse readiness
- 8
- Engagement
- 0