Simplified Approximations for Critical Design Parameters of Rectangular Fiber-Reinforced Elastomeric Isolators
Bibliographic record
Abstract
Analytical solutions for critical design properties of elastomeric bearings, such as the compression modulus, bending modulus, and maximum shear strain due to compression or rotation, including the compressibility of the elastomer, have been developed for most basic laminated elastomeric bearing geometries. Due to the introduction of extensible fiber reinforcement, these analytical solutions have been expanded to include the extensibility of the reinforcement as an additional design parameter. Extensible reinforcement can have a pronounced effect on these design properties, comparable to the compressibility of the elastomer. These analytical solutions have previously been used to derive simplified approximations appropriate for use in design codes and standards. Thus far, a rectangular bearing geometry, which is in fact the most common in bridge bearing applications, has been largely omitted from these derivations. Simplified approximations for the compression modulus, maximum shear strain due to compression, and bending modulus of a rectangular laminated bearing with extensible reinforcement are proposed and evaluated against the analytical solution, including the effects of compressibility of the elastomer and extensibility of the reinforcement.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".