Software for Simulation of Oxidation Processes
Bibliographic record
Abstract
A methodology for discrete simulation has been developed that incorporates many structural characteristics of polycrystalline material properties, such as: texture, grain boundaries, microstructure, phase composition, chemical composition, stored energy, and residual stresses. The computer models that have been developed to study oxidation processes are based on a quantitative description of the oxide and substrate structure. That description allows for the simulation of the transport of metal and oxygen ions along interfaces and bulk portions of material and the formation of oxide structure. The proposed model can help researchers and engineers to understand the physical mechanism of oxidation in order to predict material behavior and optimize material processing and properties. In this paper, the results on the simulation of the oxidation process are presented on different substrates of Zr-Nb alloys, which are used for the manufacturing the pressure tubes used in the CANDU nuclear reactors. The effects of substrate texture, microstructure, grain boundaries, and beta phase distribution on oxidation kinetics and hydrogen permeation are demonstrated.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.009 |
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".