Texture Changes of Carbon Steel and Stainless Steel as a Result of Wear
Bibliographic record
Abstract
In this research, surface texture changes of carbon steel AISI 1045 and stainless steel AISI 304 under simultaneous wear and corrosion were investigated. A solution of 3.5 % wt. NaCl was used as the corrosion agent and a pin-on-disk tribometer was employed to perform wear and corrosion wear tests.Texture investigations of the worn samples have shown texture changes after wear and corrosion-wear tests. In worn carbon steel samples after dry wear test, {011}<100> and {111} fiber texture components were developed in initially random oriented samples, whereas under corrosive-wear conditions, {111}<011> texture and {001}<110> texture were developed. In the stainless steel samples, {112}<110> texture component was observed under both dry and corrosive wear conditions, in the samples that had random grain orientations before corrosion and corrosion-wear tests.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".