Performance of Concrete-Filled FRP Tubes under Field Close-in Blast Loading
Bibliographic record
Abstract
Blasts, whether deliberate or accidental, are a great concern for a society’s critical infrastructure as well as expeditionary military installations. Improvement to existing construction methods that enhance blast resilience can ultimately save lives and property. Concrete-filled FRP tubes (CFFTs) are known to improve a conventional reinforced concrete member’s resistance to traditional loads by strengthening, protecting, and confining the reinforced concrete core. Glass fibre reinforced polymer (GFRP) tubes are readily available in a variety of sizes suitable for use as a stay-in-place structural formwork for midsized reinforced concrete members, which can simplify and expedite construction. These advantages point to CFFTs’ great potential in resisting blast loads. This study aimed to quantify the advantages of encasing a reinforced concrete member with a GFRP tube subjected to close-in blast loading and to investigate the effects of the presence of the tube, the internal steel reinforcement ratio, and the blast scaled distance on CFFTs’ behavior under blast loading. This was accomplished by testing four CFFT and reinforced concrete specimen pairs under blast and monotonic loading. The specimens were tested in pairs to facilitate comparisons. The CFFT specimens performed significantly better than the conventional reinforced specimens, showing greater robustness with decreased localized damage and reduced residual displacements. This indicated the need for developing analysis and design procedures for this system. Therefore, a procedure for developing Pressure-Impulse diagrams for the tested CFFT specimens was outlined and their use for the design of CFFTs under close-in blast loads was explained. A numerical procedure for developing equivalent close-in blast forcing functions was also outlined.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".