Thermal and Fire Characteristics of FRP Composites for Architectural Applications
Bibliographic record
Abstract
This paper discusses the main challenges of using fiber reinforced polymers (FRPs) in architectural applications. Architects are showing increased interest in the use of FRPs in modern buildings thanks to FRPs’ ability to allow cost effective realization of unique shapes and flexible aesthetics, while accommodating architectural designs and needs. The long-term durability, weathering resistance, and the exceptional mechanical properties have recently suggested the adoption of FRPs for building façade systems in an increasing number of buildings worldwide. However, some challenges for a wider adoption of FRPs in buildings are represented by the environmental and thermal aspects of their production, as well as their resistance to the expected “fire loads”. This last aspect often raises many concerns, which often require expensive fire tests. In this paper, the results of cone calorimeter tests are compared with software simulations to evaluate the possibility of designing FRPs on the computer as opposed to current design practice that involves iterative use of fire testing. The comparison shows that pyrolysis simulations related to FRPs are still not an effective way to design fire safe FRPs for architectural applications.
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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 | 0.000 | 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 | 0.001 |
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".