Influence of Extra Weight and Tire Pressure on Fuel Consumption at Normal Tractor Slippage
Bibliographic record
Abstract
Tire pressure and wheel load are both easily managed parameters which play a significant role in tillage operations for limiting slip which involves energy loss. To a great extent, this aspect affects the fuel consumption and the time required for soil tillage. The study was focused on the tire pressure and extra weight variation effect on fuel consumption and work productivity for soil tillage at normal tractor wheels slippage (7-15%). The experimental research unit composed of an 82.3 kW 4WD tractor and a reversible 4-bodies plough is presented. Tests were carried out on a stubble loam, where slip of tractor driving wheels was < 15%, tractor front ballast mass was varied in the range from 0 to 520 kg and inflation pressure in the tires from 240 kPa to 100 kPa. Dependences of tractor performance indicators on ballast mass and tires inflation pressure are presented. When tractor tire slip varies in the range from 7 to 15 percent (which is normal slip in the soil), reducing the tires inflation pressure decreases the driving wheel slip and fuel consumption, while increases work productivity. Increasing the additional mass of the tractor (adding ballast weights) decreases the driving wheel slip, increases work productivity, but also increases fuel consumption and soil compaction.
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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 | 0.001 |
| 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".