Study of Surface Wear and Damage Induced by Dry Sliding of Tempered AISI 4140 Steel against Hardened AISI 1055 Steel
Bibliographic record
Abstract
ABSTRACT: In industry, the sliding mechanical systems are subject to friction and wear phenomena. These phenomena can be the origin of a reduction of the efficiency of the mechanical system even to be responsible for its incapacity. Generally, the materials of the parts which are moving relative (tribological couple) of these systems are low alloy steels and carbon steels, thanks to their good mechanical and tribological properties. The present work aimed to study, the surface wear and damage induced by dry sliding of hard carbon steel AISI 1055 (disc) against tempered low alloy steel AISI 4140 (pin) with different hardness and applied loads was investigated. The results revealed that the interaction between the applied load and pin hardness result in complex thermo-mechanical behaviour of the worn surfaces. When a lower hardness pin is used, the main wear mechanisms observed on the discs were abrasion, adhesion, and oxidation. When a higher hardness pin is used, the wear of the discs is governed by delamination, oxidation, and plastic deformation. In particular, third-body wear occurs at high applied load resulting in higher wear rate of high hardness pins compared to low hardness pins.
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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 | 0.000 |
| 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) | 0.002 | 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".