Modelling of soil-tool interactions using the discrete element method (DEM)
Bibliographic record
Abstract
Soil disturbance and cutting force are two of the most common performance indicators for soil-engaging tools. In this study the interaction of two soil-engaging tools (a disc opener for fertilizer banding and a hoe opener from an air drill) with soil were modeled using Particle Flow Code in Three Dimensions (PFC3D), a discrete element modeling software. When comparing the disc model to the experiment results, the relative error was 11% for the average soil throw, 1.9% for the average draft force, and 51% for the average vertical force. Results from the soil-hoe model showed a relative error of 15% between the simulated soil throw and the measured one. In conclusion, both the soil-disc and soil-hoe models could simulate the selected soil dynamic properties (except for the vertical forces of the disc opener) with a reasonably good accuracy, considering the highly variable nature of the soil.
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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 | 0.000 |
| 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) | 0.000 | 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".