Blast testing of CFRP and SRP strengthened RC columns
Bibliographic record
Abstract
Blast testing on scaled reinforced concrete columns was conducted to study the behaviour of Steel Reinforced Polymer (SRP) wrapped columns in both flexure and shear.Two vertical testing frames were constructed to support each two columns per blast in a fixed-fixed configuration while applying a static axial load of 300 kN.The specimens were exposed to blast waves at a variety of incident pressures which resulted in damage from minor to severe.A reflected impulse which resulted in moderate damage was then selected and used to study the effects of varying the density of SRP wraps.CFRP strengthening was also used in order to compare the effects of the two strengthening materials.An SRP/CFRP hybrid combination using SRP for longitudinal or flexural strengthening and CFRP sheets for transverse or shear strengthening was tested.It was observed that the SRP strengthened columns were quite similar to those strengthened with CFRP.The experimental results were compared to both analytical SDOF models as well as numerical models created using advanced explicit analysis software.SRP appeared to be a very effective external strengthening material for increasing the resistance of concrete components, providing similar performance to other FRP (CFRP) wraps at potentially lower cost.The SRP materials proved to be quite resilient even when exposed to a close-proximity explosion where spalling of the RC columns was significantly reduced.
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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) | 0.001 | 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".