Experimental and Modeling Study of Sliding Wear Performance for Selected Molybdenum Stellite Alloys
Bibliographic record
Abstract
This thesis presents an experimental and modeling study of wear performance of molybdenumcontaining Stellite alloys. The wear testing conditions are of the pin-on-disc type using a tungsten carbide (WC) ball against the Stellite alloys in dry-sliding mode at ambient temperature. Three variables are explored; they are (i) two rotational speeds (50 rpm and 60 rpm) of the WC ball, (ii) two normal loads (15 N and 25 N) on the system, and (iii) various time durations (1 hr up to 60 hrs). In addition to the standard wear condition of running a continuous test, another factor of interrupting the test at various intervals is introduced. It is found that by removing the alloy specimen to take interval measurements, and then replacing the same specimen back into the system, the wear loss reduces across each of the alloys under all conditions. Phase evaluation for each of the alloys is undertaken using SEM, EDX and XRD analysis techniques. This reveals the complexity of the microstructures in terms of the various carbides and intermetallics that could be present in each alloy. The volume fraction of carbides is the principal attribute of the Stellite alloys.
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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 | 0.001 | 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".