Experimental investigations of the effects of bending vibrations resonance modes on penetration into granular materials
Bibliographic record
Abstract
Abstract Inspired by the bending vibration observed in the biological locomotions such as those found in snakes, horned lizards, and sandfish, we have developed a novel vibro probe utilizing bending resonance modes to study the bending vibration effects in assisting penetration into granular materials. This approach contrasts with traditional probes that rely on longitudinal vibrations for penetration. This newly developed probe was used to experimentally investigate the impact of bending vibration in reducing the required penetration force and enhancing the penetration process within granular materials such as lunar or Martian regolith. The bending vibrations were excited by thin piezo patches attached to the probe’s machined surface without increasing the probe’s outside diameter. This simple mechanism enables pushing the whole probe inside the granular materials. Experimental modal analysis was employed to determine the resonance frequencies of the probe. Subsequently, the probe was pushed into granular materials, both with and without the bending vibrations, by a linear actuator. Experimental results indicated that employing bending vibration in one direction led to a reduction in penetration force by up to 27% while utilizing two directions resulted in a reduction of up to 42%. Additionally, when the probe stopped penetrating the soil due to insufficient axial force, bi-directional bending vibration proved more effective in swiftly fluidizing the surrounding soil. These findings highlight the efficacy of bending vibrations in compact subsurface drilling tools.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".