Cracking and Spalling Behavior of WC-17% Co Cermet Coatings
Bibliographic record
Abstract
Abstract Thermal spray WC based powders are now frequently used as chrome replacement alternatives for a wide range of industrial and aeronautical applications. In numerous cases, the carbide materials outperform the hard chrome in many property evaluations. However, their usage on highly stressed parts, especially in fatigue loading, can be limited by spalling resistance of the coating. While HVOF is being used on many flight critical parts, stringent applications like the landing gear components of carrier-based aircraft are still under investigation. This work, on WC-17%Co, relates coating bend test performance and fatigue/cyclic step loading behavior to the processing history using different HVOF systems. Initially, twelve (12) different coatings were monitored using a DPV- 2000 for temperature/velocity profiles. The mechanical properties were then assessed using an instrumented four-point bend test as well as uniaxial cyclic loading. After mechanical testing, the coating microstructures were characterized using X-Ray diffraction and electron microscopy in order to investigate the phase content and nature. In particular, the cracks generated during the bend test were measured using SEM on sample cross sections to understand characteristics such as spacing and crack penetration to the substrate. The interactions of processing parameters with the cracking/spalling resistance of the various coating deposits will be discussed and a potential criteria for the control of cracking phenomena will be presented.
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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) | 0.001 | 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".