Research on Analysis of Friction and Lubrication Characteristics of Piston-Cylinder System in Internal Combustion Engines Using Improved Multi-Layer Thermal Resistance Model
Bibliographic record
Abstract
To analyze the friction and lubrication characteristics of the piston-cylinder system in internal combustion engines using an improved multi-layer thermal resistance model, this study combines the theory of thermal boundary conditions to design a lubrication and friction calculation model, and conducts numerical computations and experimental research. Firstly, a lubrication model for the piston skirt-cylinder liner is proposed, which includes key parameters such as the lubrication model for the piston skirt and the lubricating oil characteristic equation. Secondly, the friction and lubrication theory for the piston ring-cylinder liner is discussed, which includes the leakage model and the piston ring lubrication model. Additionally, the multi-layer thermal resistance model is improved to accurately describe the lubrication of the piston assembly under the thermal boundary conditions of the cylinder liner. Subsequently, experimental research is conducted to investigate the friction and lubrication characteristics of the piston-cylinder system in internal combustion engines under different temperatures. The experiments reveal that: (1) Linear function 1 and sinusoidal function 1 perform well in the piston skirt of the cylinder liner, with lower average friction power consumption and relatively small relative errors of 5% and 6%, respectively. (2) In the experimental study of the friction and lubrication characteristics of the piston ring-cylinder liner, function 2 in the linear function approach has slightly higher average friction power consumption compared to function 1. In the parabolic function approach, function 1 exhibits lower average friction power consumption, while function 2 significantly increases it. In conclusion, this research comprehensively explores the friction and lubrication characteristics of the piston-cylinder system in internal combustion engines by introducing an improved multi-layer thermal resistance model. The aim of this study is to provide theoretical foundations and experimental evidence for further optimizing the design and operation of internal combustion engines.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".