Titanium Heat Treatment Property Predictor
Predicts mechanical properties from titanium alloy chemistry and heat-treatment cycle.
This model is a reference implementation. Industrial use requires validation on plant-specific data. Customer-specific fine-tuning remains private unless explicitly approved for publication.
Input schema
| Field | Type | Description |
|---|---|---|
| composition | float[] · wt% | Alloy composition + interstitials |
| ht_cycle | float[] | Temperature / time / cooling path |
Output schema
| Field | Type | Description |
|---|---|---|
| yield_strength | float · MPa | Predicted yield strength |
| hardness | float · HV | Predicted hardness |
Training data & evaluation
Training data type
Public literature + synthetic
Evaluation metrics
Limitations
- Coverage is strongest for common Ti-6Al-4V variants.
Discussion
- s.Validation note
s.iyer
ML researcher · 3d
Reproduced the reported metric on the public split with a fixed seed. Numbers line up within noise, so it's a good baseline to build on.
18 - l.Improvement
l.zhang
Process engineer · 1w
Adding an uncertainty head would make this far more useful for prioritization. Happy to open a PR against the reference repo.
11
Validate on your data, keep the result private
Reference models are a starting point. We can fine-tune privately on plant-specific data, with customer-owned IP and no public disclosure.