Comparison of Two Subsoiler Designs Using the Discrete Element Method (DEM)
Bibliographic record
Abstract
Abstract. Subsoiling is an essential tillage practice for loosening soil and enhancing water infiltration. In this study, a discrete element model was developed and validated to simulate soil-tool interactions. The validated model was then used to evaluate two design alternatives of subsoiling tool: a non-winged tool (NW) and a winged tool (WW). The performance indicators used for the evaluation included draft force and soil disturbance area at different rake angles (ranging from 23.0° to 40.5°) and working depths (ranging from 225 to 350 mm) at a constant travel speed of 0.8 m s -1 . The results showed that the WW tool required more than twice the draft force and disturbed more than twice the soil area when compared to the NW tool, regardless of rake angle and working depth. The draft force of the NW tool had no variation over the range of rake angles tested, whereas the WW tool had the lowest draft force at 26.5°. The soil disturbance area did not show any particular trend for both design alternatives at the rake angles studied. With the increase in working depth, the soil disturbance area of the WW tool decreased; however, no change was observed for the NW tool. Considering both draft force and soil disturbance area, both the NW and WW tools should be operated at the shallowest possible depth, and the recommended rake angle was 33.5° for the NW tool and 33.5° to 40.5° for the WW tool. Keywords: DEM, Design, Disturbance, Force, Soil, Subsoiling, Tool.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".