Graphite Flake Size Effects to Thermal Durability of Automobile Flywheel Under Forced Slippage
Bibliographic record
Abstract
The objective of this study is to investigate thermal durability of grey cast iron GJL250 material flywheel based on casting graphite flake size under abusive and unusual driving condition which causes forced slippage. In daily routine, drivers may make half press of clutch pedal and switch the gear out of sequence during long traffic condition. This case leads to slippage between flywheel and clutch that causes energy dissipation in clutch house. During slippage, thermal load on flywheel increases and when it reaches critical level this may cause thermal cracks on flywheel. In this study, graphite flake size effects on thermal durability were investigated. In order to simulate daily abusive usage, flywheels which have different graphite flake type and size were subjected to forced slippage test at the test bench which simulates the abusive usage on the car. The findings of this study is different size of graphite flake types on flywheel directly effects the thermal performance of material and may cause prominent cracks during over dissipated energy occurrence. At the end of the forced slippage test, the cast iron which has higher graphite size completed the test without crack, whereas prominent cracks were observed on the casting which has smaller laminar graphite size.
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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".