An advanced rate‐dependent analytical model of lead rubber bearing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Lead rubber bearings (LRBs) are a type of isolation bearing that have a combination of rubber and lead as the main components. These bearings are widely used in bridges, buildings, and other important structures due to their high load‐carrying capacity and excellent energy dissipation capability. However, the behavior of LRBs is complex and nonlinear, making it difficult to predict their behavior and performance under different loading conditions. The objective of this research is to develop a comprehensive analytical model of LRBs that can accurately predict their behavior under low to large levels of strain. The proposed model considers nonlinearity, hysteresis, stiffness, damping, and rate‐dependent behavior of LRBs. The model is also able to consider the effect of temperature on the rubber and lead components of the bearing. The developed model is validated using experimental results and is shown to provide accurate predictions of the LRB response under different strain levels. The accuracy of the developed LRB model is also validated using shake table test results of an LRB‐isolated bridge under low and large strain. This research provides a valuable tool for engineers and designers to predict the behavior and performance of LRBs and optimize their design.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it