Model for Tangential Contact Damping Energy Dissipation Factor of Plane Joint Interfaces
Bibliographic record
Abstract
Due to the comprehensive applications of Hertz contact theory and fractal method, we present the model for tangential contact damping energy dissipation factor of plane joint interfaces. The energy dissipation of the entire joint surface is estimated by energy loss equation of single micro-convex body. According to the tangential force in process of micro-convex and micro-slip, the energy storage of the micro-convex body is replaced by the equivalent, and the energy storage of the composite surface of the rectifier is obtained. On the basis of the unique conversion of energy loss and storage, a model is established. The model avoids the invariance of experimental test and enhances the visualization of theoretical derivation, and can more intuitively understand the properties of damping dissipation factor. The influence law of related parameters is obtained by numerical simulation. We can see that damping loss factor of tangential decreases first and then increases when D increase and the roughness arguments are constant. When D is about 1.25, the D reaches the least value. If the D is less than 1.5, the roughness parameter and directly proportional damping dissipation factor relations, when the fractal dimension is 1.5 exactly, the roughness parameters do not produce effect, when the D is larger than 1.5, the increase of roughness, dissipation factor decreases at the same time. Comparing with the laboratory data, the results obtained by numerical simulation are in accordance with the actual situation is found. Therefore, the model is effective in certain conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".