SEISMIC HAZARD CONTROL TECHNOLOGIES FOR BUILDINGS, BRIDGES, AND SENSITIVE EQUIPMENT: CASE STUDIES
Bibliographic record
Abstract
Seismic hazards pose significant risks to the built environment, necessitating the implementation of effective measures to mitigate their potential impacts. Over the past few years, there has been a notable upsurge in the development of seismic control technologies, underscoring their indispensable role in ensuring effective earthquake protection. This paper presents an overview of seismic hazard control technologies for buildings, bridges, and sensitive equipment, focusing on real-world case studies from USA, Canada, Mexico, New Zealand, Peru, Chile, and Japan. The presented case studies cover new buildings, retrofit of existing and historical buildings, new bridges, retrofit of existing bridges, sensitive critical equipment, and expensive artwork. The paper showcases the widespread utilization of various technologies including 2D and 3D seismic isolation systems for buildings, bridge, equipment, and artwork, different types of dampers including viscous wall dampers and cylindrical oil dampers for different structures.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".