Model testing of dynamic response of loess to impact load from helicopter landing
Bibliographic record
Abstract
To investigate the dynamic behaviour of loess under the impact loads of two tyres attached to a helicopter’s landing gear, a loading device capable of simultaneously applying dual impact loads was designed. A series of physical model tests, varying in impact energy and water content of the loess samples, were conducted. The study explored the settlement pattern, vertical dynamic stress distribution, and the effects of impact energy and water content. Results revealed that settlement in the shallow layer exhibits a characteristic W-shape, while the vertical dynamic stress time curve displays a single peak pulse. Settlement and vertical dynamic stress increase with higher impact energy. Increasing the water content of the loess sample results in greater settlement but lower vertical dynamic stress. For the simulated helicopter, when the tyre impact energy increases from 23.8 to 60.8 kJ, the resultant crater depth in loess with a moisture content of 16% increases from 7.6 to 18.1 cm, an increase of 11.5 cm. The peak vertical dynamic stress at a depth of 10 cm along the centerline of the tamper increases from 590.98 to 1449.4 kPa, more than doubling. These findings are valuable for the design of landing sites and landing gear systems.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".