Parameter calibration of discrete element simulation for the interaction between heavy soil and soil-engaging components in shellfish culture
Bibliographic record
Abstract
Shellfish culture heavy soils are suitable for the cultivation of marine organisms and are essential for the development of marine fisheries. To study both the interaction between heavy soil particles and that between the soil and soil-engaging components of agricultural machinery in shellfish culture, the simulation parameters in the model were determined. To study the interaction between soil particles in the viscous soil of shellfish culture with moisture content of 26.51% ± 1%. Discrete element method is used to establish the accumulation simulation experiment; the contact parameters between soil particles were calibrated. The response surface optimization technique was used to create the accumulation angle regression model. To study the interaction between the soil and soil-engaging components, the static friction coefficient between the heavy soil and soil-engaging components was determined by static friction experiment. The contact parameters between the soil and soil-engaging components were calibrated by the slope simulation experiment; the rolling distance regression model was established by response surface optimization methodology. The findings demonstrate that the optimized soil model can simulate the actual soil, and reflect the interaction between the heavy soil particles, soil, and the soil-engaging components of agricultural machinery, which not only provides a theoretical basis for the design and optimization of soil-engaging components of agricultural machinery in heavy soil, but also provides a new way for the research and development of agricultural machinery in a complex environment.
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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 | 0.001 | 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".