Inkjet Droplets Contours
Contributors
Project leader:
Researcher:
Description
This dataset provides a structured representation of droplet shapes generated in drop-on-demand (DoD) inkjet experiments, enabling quantitative analysis and data-driven modeling of droplet formation processes.
It consists of two main files:
- HDF5 File: Contour-Based Representation
The HDF5 file contains the extracted contours of droplet boundaries, obtained from high-speed images available in the companion dataset (DOI: 10.5281/zenodo.13862494). Each group in the HDF5 file corresponds to a single experimental case (image). For each group:
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- The input parameters (inkjet trigger signal characteristics) are stored as attributes.
- The droplet contour(s) are stored as arrays of 2D points representing the boundary.
- A parametrized representation of the contour is provided using Elliptic Fourier Descriptors (EFDs).
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CSV File: Tabular Parametric Dataset
The CSV file contains a tabulated dataset of 274,911 samples, where each row corresponds to one experimental case. Columns include:
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- Trigger signal parameters (input variables)
- Elliptic Fourier Descriptors (EFDs) representing droplet morphology
This file is particularly suited for statistical analysis, regression, and machine learning applications, providing a compact, low-dimensional representation of droplet shapes.
Data Processing and Tools:
- Image processing and contour extraction were performed using our open-source pipeline: https://github.com/DropletDynamics/InkJetDroplet
- Elliptic Fourier Descriptors were computed using: https://github.com/hbldh/pyefd
Licence:
This dataset is licensed under CC BY-NC-SA for non-commercial use.
If you modify or adapt the dataset, you must share the modified version under the same license (CC BY-NC-SA) and credit the original source.
For commercial use, a separate license is required—please contact droplets@cimne.upc.edu for details.
Files
Contours.csv
Additional details
Funding
- Agencia Estatal de Investigación
- Towards establishing a Digital twin for manufacturing via drop-on-demand inkjet printing, Proyectos Estratégicos Orientados a la Transición Ecológica a la Transición Digital 2022–2024 TED2021-130471B-I00
- Agencia Estatal de Investigación
- DEsign-supporting Computational framework for modelIng Coupled Mircorfluidics in Advanced manufacturing. PID2022-137472OB-I00
Dates
- Created
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2024-12-04
Software
- Repository URL
- https://github.com/playpaolo/InkJetDroplet
- Programming language
- Python
- Development Status
- Active