Database of tall pre‐Northridge steel moment frames for earthquake performance evaluations
Bibliographic record
Abstract
This article describes a detailed database of tall steel moment frame buildings that are representative of the construction practices in San Francisco prior to the 1994 Northridge earthquake. The database contains design details that affect the structural performance of steel moment frames, including frame geometry, member cross‐section sizes, and gravity system characteristics. This database also captures irregularities that might impact seismic response, such as podiums, setbacks, mass concentrations (mechanical, electrical, and plumbing (MEP) floors), interrupted column lines, and atriums. The database includes information on 89 moment frame buildings, 14 of which were built before 1960 and are constructed with riveted connections, while the remaining 75 have welded flange connections like those that suffered brittle fracture during the 1994 Northridge earthquake. The buildings are further distinguished between space frame, perimeter frame, and partial space frame systems. For about half (41/89) of the buildings in the database, section sizes of representative structural members were collected, which enabled the evaluation of the seismic design, elastic, and inelastic response using computational workflows. The design diagnostics indicate that most of the buildings meet the minimum seismic strength and strong‐column weak‐beam requirements of modern building codes, even though they were not necessarily designed with this intent. On the contrary, about one‐third of the buildings do not meet the seismic design drift limit of current codes, and about half of them have weak beam‐column panel zones. This database, associated structural analysis models, and processing scripts are published at DesignSafe https://doi.org/10.17603/ds2‐wjad‐r340 to facilitate collaboration and continued development of open‐source data for high‐resolution simulations to inform risk mitigation strategies on a regional scale.
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 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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".