Wind force test and simulation analysis for air delivery system of orchard sprayer
Bibliographic record
Abstract
<bold>Objective</bold> The orchard sprayer has been widely used in spray application and other related fields for orchards.However，there is a bottleneck problem that the weak wind force of the air supply system makes it difficult for the droplets at the nozzle outlet to be transported to the target canopy. <bold>Method</bold> In order to solve the problem，the design of Laval nozzle applied to air delivery nozzle was proposed.Based on the principle of airflow velocity growth in Laval nozzle，requirements for the integration of agricultural machinery and agronomy，the design principles of air assisted nozzle was derived，the parameters of throat at the end of the nozzle was also determined.The wind performance test platform of the air assisted nozzle was built，and the computational fluid dynamics（CFD）dynamic numerical simulation model of the flow field for the nozzle was also established.The results of wind field test showed that the relative error of wind speed value reached 8.5% at the strongly affected area of turbulence.Considering the influence of test error and turbulence fluctuation，it is reliable to use CFD method to assist the design of air delivery system for orchard sprayer.Based on Reynolds N-S equation and RNG k- ɛ turbulence model，transfer method of flow field parameters between interface areas，pressure based coupling scheme，the overall CFD flow field dynamics calculation model of orchard sprayer air conveying system was established. <bold>Result</bold> The results show that the design of the Laval nozzle at the end of the nozzle has a strong improvement effect on the internal wind speed of the pipeline，the maximum increase in wind speed of the air delivery system reaches 152.42%，with an average increase of 133.56%；the overall standard deviation of the output wind speed of 10 nozzles in the air delivery system is 0.66. <bold>Conclusion</bold> The air delivery system based on Laval nozzle is well-designed，the system overcomes the problem of choked phenomenon for air assisted nozzle and significantly improves the wind performance of the air delivery system.
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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 | 0.001 |
| 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".