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---
license: cc-by-4.0
language:
- en
pretty_name: SPH-Simulated LPBF Melt-Pool Dataset
size_categories:
- 100K<n<1M
task_categories:
- image-classification
- image-segmentation
tags:
- additive-manufacturing
- laser-powder-bed-fusion
- smoothed-particle-hydrodynamics
- melt-pool
- keyhole
- physics-simulation
- scientific-machine-learning
---
# SPH-Simulated LPBF Melt-Pool Dataset
Single-track laser powder bed fusion (LPBF) melt-pool simulations for Ti-6Al-4V,
produced with the LAMAS smoothed-particle-hydrodynamics solver. 241 simulations
sampled uniformly i.i.d. over a 4D process-parameter cube (laser power, scan
speed, laser spot radius, substrate temperature), spanning conduction, transition,
and keyhole regimes.
Companion to the NeurIPS 2026 Evaluations & Datasets Track submission
*A Simulation-Based Dataset for Melt Pool Dynamics in Single-Track Laser Powder
Bed Fusion*.
See examples folder in order to reproduce the results of the toy models.
Maintained by Ioan-Daniel Crăciun, Chair for Physics-Enhanced Machine Learning,
Technical University of Munich.
## Stats
| | |
|---|---|
| Simulations | 241 |
| Frames | 65,472 |
| Images (3 perspectives) | 196,416 |
| Top / front resolution | 256 × 256 px |
| Side resolution | 512 × 256 px |
| Material | Ti-6Al-4V |
| Atmosphere | Argon |
**Regime label distribution:** Initial Emptiness 5.0% / Forming 15.8% / Conduction 67.0% / Keyhole 0.8%.
The keyhole share is a lower bound — manual relabeling is ongoing.
## Labels
Two label types per frame:
- **Per-pixel phase** (image RGB): red = melt, green = solid substrate, blue = gas.
- **Per-frame regime** (4 classes): Initial Emptiness, Forming, Conduction, Keyhole.
Regime labels are seeded by a depth-based heuristic and verified through a
two-round human review with majority-vote consolidation.
## Process-parameter ranges
| Parameter | Symbol | Min | Max | Unit |
|---|---|---|---|---|
| Laser power | P | 76.70 | 249.99 | W |
| Scan speed | v | 0.204 | 0.998 | m/s |
| Laser spot radius | r_s | 45.10 | 89.70 | µm |
| Substrate temp. | T_s | 300.3 | 399.6 | K |
Fixed: particle spacing 4 µm, track length 1200 µm, end time 2.1 ms,
laser absorptance 0.2, wall temperature 300 K.
## Layout
```
experiments/<hash>/
├── images/{top,side,front}/ # PNGs per timestep
├── monitoring/*.dat # scalar time series
├── labels.csv # per-frame regime labels
└── metadata.json # process parameters
index.json # hash → parameters
```
## Usage
```python
from huggingface_hub import snapshot_download
path = snapshot_download(repo_id="ioandanielc/sph_dataset", repo_type="dataset")
```
## Limitations
Single-track on bare substrate (no powder bed, no multi-track). Fixed laser
absorptance. 2D cross-sections, not full 3D volumes. Keyhole class sparse by
design — the dataset is the Stage-1 initialization for an active-learning loop.
Not yet validated against experimental measurements.
## Citation
```bibtex
[bibtex placeholder — fill in after acceptance]
```
## License
CC BY 4.0.
## Contact
Ioan-Daniel Crăciun · TUM · <email-or-HF-handle>