Development of Protective Thermal Spray Coatings for Lightweight Al Brake Rotor Discs
Bibliographic record
Abstract
Abstract This paper reports on the performance evaluation of stainless steel (SS) thermal spray coatings aimed at shielding lightweight aluminum (Al) brake rotor disks from excessive heat and providing an adequate tribological surface in contact with brake pads. Coating wear, corrosion and heat resistance performances were evaluated using pin-on-disk, cyclic corrosion tests and thermal cycling using a custom laser rig, respectively. Arc spray optimized coatings displayed lower or equivalent wear rates when compared with the baseline gray cast iron disks, with similar frictional behavior. However, arc spray coating exhibited low adhesion which limits the maximum coating thicknesses achievable and leads to early coating spalling after about 1000 thermal cycles. Arc sprayed coatings also corroded and delaminated under corrosion tests. Optimized cold spray coatings present high corrosion resistance and could resist above 10,000 thermal cycles without spalling. However, cold spray coatings exhibit wear rates at least 4 times those of the cast iron. Taking advantage of both types of coatings, it was found that the production of a duplex coating made of a cold spray bond coat and an arc spray top coat could meet the requirements for protecting Al disks, with near 50% weight reduction.
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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) | 0.000 | 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 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".