Structural and nonstructural performance of a seismically isolated building using stable unbonded fiber‐reinforced elastomeric isolators
Bibliographic record
Abstract
Summary Stable unbonded fiber‐reinforced elastomeric isolators (SU‐FREIs) exhibit a characteristic horizontal softening and stiffening response, similar to other adaptive devices such as the triple friction pendulum and sliding systems with variable curvature. The transition between the softening and stiffening occurs at a displacement corresponding to a unique deformation known as full rollover . In this paper, the full rollover displacement of SU‐FREIs is altered by using modified support geometry (MSG), a geometric modification of the upper and lower supports applied to tailor the hysteresis loops of the isolator. Experimental results are used to calibrate a numerical model of a base‐isolated structure. The model demonstrates that the stiffening regime provides minimal restraint against displacements during events that meet or exceed the maximum considered earthquake. A parametric study revealed that the level of stiffening required to restrain displacements during large events is significant. This increase in stiffness is reflected in an increase in the response of the structure and light nonstructural components. Full rollover and MSG is considered advantageous to maintain horizontal stability and provide control over the stiffening of SU‐FREIs. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".