Response of earthquake-resistant reinforced-concrete buildings to blast loadingThis article is one of a selection of papers published in the Special Issue on Blast Engineering.
Bibliographic record
Abstract
Recent bomb attacks on buildings have raised awareness about the vulnerability of structures to blast effects. The resiliency of structures against blast-induced impulsive loads is affected by structural characteristics that are also important for seismic resistance. Deformability and continuity of structural elements, strength, stiffness, and stability of the structural framing system and resistance to progressive collapse are factors that play important roles on the survivability of buildings under both blast and seismic loads. The significance of these structural parameters on blast resistance of reinforced concrete buildings is assessed through structural analysis. Both local element performance and global structural response are considered while also assessing the progressive collapse potential. The buildings under investigation include 10-storey moment resisting frames with or without shear walls. The blast loads selected consist of different charge-weight and standoff distance combinations. The results are presented in terms of ductility and drift demands. They indicate improved performance of seismic-resistant buildings when subjected to blast loads, in terms of local column performance, overall structural response, and progressive collapse potential.
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) | 0.000 | 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) | 0.002 | 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".