Effective range of base isolation design parameters to improve structural performance under far and near-fault earthquakes
Bibliographic record
Abstract
Triple Friction Pendulum Isolators (TFPIs) have been widely used to enhance the seismic capacity of structures in the recent decade. This study intends to measure the effect of different Ground Motion (GM) sets, including Far-Fault (FF) and Near-Fault (NF) records, on the seismic response of the Triple Friction Pendulum (TFP) isolated structures. For this aim, different Engineering Demand Parameters (EDP), including Inter-story Drift Ratio (IDR), absolute floor acceleration, base shear, residual displacement, and damage energy are measured using numerous Nonlinear Time History (NTH) analyses. A three-dimensional mid-rise special moment resisting frames (SMFs) steel building isolated with TFPIs has been designed as per ASCE 7-16. In addition, the separate and simultaneous effect of raising the damping ([Formula: see text]) and the period ([Formula: see text]) of the base isolation system on the seismic responses of the superstructure are measured to assess the structural performance and estimate the damage energy. The [Formula: see text] and the [Formula: see text] are amplified up to 30% and 4.5 times of the superstructure period in incremental steps, respectively. The results show that the damage energy of the superstructure in the Initial Design Parameters' Values (IDPVs) of the isolator under NF records with Forward-Directivity pulses (NF-FD-GMs) is more significant than damping energy, while an inverse trend has occurred for other GM sets. Increasing the IDPVs up to a certain level reduces most EDPs and consequently causes an improvement in the seismic performance of the superstructure. The novel developed empirical relationships can be utilized as useful tools to predict IDRs and the damage states of the superstructure. The variations of the EDPs with respect to simultaneous or separate increasing the IDPVs are also reported for different GM sets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".