A new method for measuring ice adhesion strength at an ice–substrate interface
Bibliographic record
Abstract
Abstract This research focuses on the development of a direct technique for measuring atmospheric ice adhesion strength using embedded piezoelectric film sensors at the ice‐substrate interface. The substrate is a small aluminium beam on which PVDF piezoelectric sensors are bonded. The composite beam formed by aluminium and an ice layer is submitted to sinusoidal stress at the interface by a shaker on which one end of the beam is clamped. The piezoelectric charge coefficient is used to predict the electric charge density induced on the piezoelectric film, which enables us to develop a macroscopic and direct measurement technique for determining mechanical stresses at the atmospheric‐ice‐substrate interface. The preliminary results obtained show that adhesive failure was obtained for each test for a frequency close to the natural resonance frequency of the aluminium beam. Within the limitations of the experimental conditions, it was possible using this approach to obtain ice adhesion strengths in accordance with those obtained in the literature. This demonstrates the feasibility of this simple ice adhesion testing method. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".