Tensile, Torsional and Bending Strain at the Adhesive Rupture of an Iced Substrate
Bibliographic record
Abstract
In order to develop an effective deicing device using mechanical deformation of substrates, the adhesive and/or cohesive strains of ice at rupture were measured for three different modes of solicitation: tensile, twisting and bending. A total of 108 icing/deicing tests were conducted with aluminum and nylon samples covered with hard rime ice deposits 2, 5, and 10 mm thick strained at various strains rates in brittle regime at −10°C. Real time deformation was precisely monitored using a strain gage fixed to the A1 interface, and force by means of load cells and a torque-meter. Deicing strain was determined at the time of ice detachment, which corresponds to a visible, instant change in the slope of stress-strain curves. The mean values of deicing strains, ε %, measured in tensile, torsion and bending experiments are respectively, 0.037 ± 0.015%, 0.043 ± 0.023% and 0.004 ± 0.003% As for adhesion strength, the highest values were obtained in tension, 4 MPa ± 50%, and the lowest in bending, 0.014 MPa ± 36%. In torsion, the value was intermediary, at 1.26 MPa ± 67%. Measurements also showed that deicing stress and strain tended to increase with substrate roughness, whereas they decrease with increasing ice thicknesses. In summary, this work points out the effects of two major factors on ice adhesion strength, the solicitation mode and the ice thickness. Finally these results suggest that the first criteria for a mechanical deicing device has to satisfy to be effective is to have the capacity to generating a strain at around 0.04% ice/substrate interface.
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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 | 0.000 |
| 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".