Dataset of sound field simulations above finite absorbers
<p>The authors' documentation on the training, validation, and testing datasets in their paper "<em>Sound absorption estimation of finite porous samples with deep residual learning</em>."</p> <p>The sound fields are generated with a simplified boundary element method (BEM) of a baffled porous layer on a rigid backing using the Delany–Bazley–Miki model. Further information on the contents of this database can be found in <em>documentation.pdf</em>.</p> <p>More details on the models and reproduction of results of the paper using this database can be found in the GitHub repo: <a href="https://github.com/eliaszea/finite-absorber-ML">https://github.com/eliaszea/finite-absorber-ML</a>. </p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4