A numerical description of nitrogen diffusion in titanium at elevated temperatures
Bibliographic record
Abstract
As part of a program to understand the dissolution of nitrogen-rich titanium solids in liquid titanium, a numerical study of nitrogen diffusion in titanium at elevated temperatures has been carried out. A Landau transformation was applied to the equations governing nitrogen diffusion which were used as the basis for the numerical models developed in this study. To begin a numerical model describing the nitriding of commercially pure titanium was developed. The numerical model was used initially to simulate nitrogen diffusion in a planar geometry and the predicted nitrogen concentration profiles and displacement of Ti-N phase boundaries showed good agreement with analytically derived solutions. The numerical model was then used to simulate nitrogen transport in commercially pure titanium cylinders. The model results were shown to be sensitive to the diffusion coefficients of Ti-N phases present in the system. Based on a sensitivity analysis, diffusion coefficients at 1650 °C of 4.3×10⁻¹¹ m²·s⁻¹, 1.6×10⁻¹¹ m²·s⁻¹ and 1.7×10⁻¹² m²·s⁻¹ for β-Ti, α-Ti and TiN phases, respectively, were back calculated using the model. The model predictions, using the new diffusion coefficients, showed good agreement with previously published data in terms of both the nitrogen concentration profiles and displacements of Ti-N phase boundaries under the conditions examined in the study. The comparison indicates the model framework is capable of accurately approximating the diffusion of nitrogen in titanium at elevated temperatures. In work that followed, the model framework was used to develop an improved numerical model for describing the dissolution of Ti-N particles in liquid titanium. The results of the improved methodology have been compared to a second finite-difference based model formulated using the conventional approach for interface motion. The improved approach accurately accounts for conservation of nitrogen associated with interface motion and hence has the potential to predict particle dissolution times more accurately in commercial melt refining operations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".