Seismic Vulnerability Assessment and Strengthening of Heritage Timber Buildings: A Review
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
Recent studies highlight the potential impact of earthquakes on cultural heritage sites and monuments, which in turn yield significant adverse impacts on economies, politics, and societies. Several aspects such as building materials, structural responses, and restoration strategies must be considered in the conservation of heritage structures. Timber is an old organic construction material. Most of the historic timber structures were not designed to withstand seismic forces; therefore, the seismic vulnerability assessment of heritage timber structures in areas with high seismic hazard is essential for their conservation. For this purpose, different strategies for the numerical modeling of heritage timber buildings have been developed and validated against tests results. After performing seismic analysis using detailed analytical methods and predicting the susceptible structural components, strengthening techniques should be utilized to mitigate the risk level. To this aim, various methods using wooden components, composite material, steel components, SMA etc., have been utilized and tested and are reviewed in this study. There are still some gaps, such as full-scale numerical modeling of strengthened buildings and investigating the soil–structure interaction effects on the seismic behavior of buildings that should be investigated.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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