Bibliographic record
Abstract
Damping materials made of pressing wire, such as Metal Rubber (MR material), “metal-flex”, “spring cushion” etc. are used widely in vibration protection systems. They have high strength and damping, however they are non-linear and anisotropic. To use contemporary finite element software for calculation of vibration insulators made of wire damping material one should know constants of this material. Till this time this problem almost isn’t researched, there is only a few data in linear approximation. A Young modulus for pressure and bending, shear modulus, Poisson ratio, friction force for pressure and for shear, friction coefficient between wire material and steel plate are obtained for MR material made of stainless steel wire for different load directions by static experiment in the present research. An influence of deformation, relative density, wire diameter, pressing force, deformation in other direction on these constants is considered. Peculiarities of pressing wire material deformation process are discussed: a difference of Young modulus for pressure and bending, a stabilization of hysteretic loop for one direction during load in another direction, an energy dissipation coefficient for different load directions. Results of the present research not only allow calculation of vibration isolator made of MR material by finite element software, but give a method for research of other pressing wire damping materials.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.009 |
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".