Lubricated friction behaviour of thermal spray steel coated cylinder bores studied using a long-stroke reciprocating tribometer
Bibliographic record
Abstract
Purpose This paper aims to study the effectiveness of using thermal spray (TS) coated bores in reducing friction under the mixed lubrication (ML) and elastohydrodynamic lubrication (EHL) regimes. Design/methodology/approach A reciprocating tribometer with a stroke length of 100 mm, was built to measure the coefficient of friction (COF) at the mid-stroke and ring reversal positions and to conduct sliding tests at a speed range of 0.31–3.14 m/s. Samples taken from fine-honed TS coated bores and also from cast iron (CI) liners that underwent a standard-honing process were tested against ring segments coated with chromium nitride (CrN) and diamond-like carbon. Findings Construction of Stribeck curves demonstrated that TS coatings showed a transition from ML to EHL at a lower speed (0.94 m/s) compared with CI (1.26 m/s) regardless of the counterfaces used. Lower COFs of 0.05–0.08 in ML was measured for TS coatings compared with those of 0.06–0.09 for CI in ML. Once EHL was reached, the COF of TS coatings decreased to 0.02–0.03 similar to those of CI. Examination of wear patterns suggested that the low roughness combined with high oil retention capability might be responsible for the reduced transition speed and the expanded EHL region for the TS coated surfaces. Originality/value With the EHL friction captured in a bidirectional sliding mode using a long-stroke tribometer, this work contributes to the understanding of the low-friction behaviour of TS coatings.
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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 | 0.001 |
| 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".