Bibliographic record
Abstract
A great deal of understanding into the behaviour of composite steel-concrete structures in fire has been developed since the Cardington frame fire tests (UK) 1990s. This has now been broadened so that structures in fire design has a real engineering basis and is not reliant on results from single element testing in the standard furnace. Several projects involving office buildings in the UK and abroad have highlighted the need for developing the understanding of whole frame behaviour in fire. Since 9-11 robust engineering solutions where the response of the building to an event like fire is known are in great demand. The basics of structural mechanics at high temperatures can be used in design to understand many structures with the aid of computer modelling. This paper provides a direct comparison between the structural response of an 11-storey office building now constructed in the city of London, when designed in a prescriptive manner, with applied fire protection on all the load bearing steelwork, and the response of the same structure designed using a performance based approach leaving the majority of secondary steelwork unprotected. The intent is to demonstrate that structural stability during the fire limit state can be maintained in specific cases without relying on passive fire protection. This paper contributes to the field of structural fire engineering by extending the research work previously conducted by the authors1 to a real design case and addresses the issues raised by approving authorities, insurers and the client when a fire engineered approach is used to calculate structural response to fire. It also demonstrates the use of advanced analysis to understand beam-core connection response in fire, as part of a series of global finite element analyses to ensure that the unprotected structure proposed provides structural stability and maintains compartmentation for the design fires agreed with the necessary stakeholders in this project.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".