Improving the Seismic Behavior of Symmetrical Steel Structures Under Near-Field Earthquake Using a Base Isolation Method Lead Rubber Bearing Isolator
Bibliographic record
Abstract
In this study, the function and application of seismic isolation system through lead rubber bearing isolator (LRB) in near-fault earthquakes are compared with fixed-base structures. As a result of their high frequency content, near-fault earthquakes impose huge energy on structures and cause severe damages. One of the appropriate solutions for this issue is the use of LRB which decreases the amount of imposed energy on structures. To improve the function of isolated structures under the near-fault earthquakes, isolators are designed in a way to tolerate the vertical component of earthquakes. To this purpose, we limit the displacements due to the horizontal movements of isolator through Gap spring which acts as a retaining wall and prevent shocks to other buildings. Moreover, this approach decreases the vertical movements of isolators and indirectly improves their behavior. In the current study, three buildings with four, eight, and 12 floors (with and without gap spring) were included. Isolators were manually designed in accordance with AASHTO-LRB regulations and the behaviors of both isolators and buildings are considered non-linear. Then we analyzed and compared the amount of energy, displacement, and acceleration of structure at the center of roof. The results indicated a significant decrease in the results of base shear, the acceleration of roof center, floors drift and energy imposed on the structure in the isolated system in comparison with the fixed-base structure.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 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".