Prediction of melt pool depth and dilution in laser powder deposition
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a mathematical model of laser powder deposition (LPD) to predict temperature field, melt pool depth and dilution. The model validated by experiments is developed using the moving heat source method. In this method, the temperature distribution inside the clad and the substrate is obtained using the superposition principle and the solution of the heat diffusion due to a point heat source. The model, which can be used in real-time applications, predicts the melt pool depth and dilution as a function of clad height and clad width, which in practice can be measured by a vision system. Numerical and experimental analyses show a non-linear behaviour of the melt pool depth as a function of process speed. This indicates that the melt pool depth has a maximum at a certain process speed. The comparisons between the numerical and experimental results show that this model is capable of predicting the characteristics of the LPD process accurately. Using the model, some general curves that show the behaviours of the melt pool depth and dilution as a function of clad height, scanning speed and laser power are illustrated.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it