Punching Shear of Flat Slabs with Pultruded GFRP Stay-in-Place Structural Forms
Bibliographic record
Abstract
This paper examines the punching shear behavior of a new concrete flat slab design, incorporating a glass fiber-reinforced polymer (GFRP) stay-in-place (SIP) structural form system and orthogonal GFRP top rebar mesh. The SIP form system comprises I-beams supported on the four sides of a column and flat plates with T-up ribs supported by, and adhesively bonded to, the bottom flanges of the I-beams. The web and top flange of the I-beams are embedded in the slab, thereby providing flexural and shear reinforcement, while the SIP ribbed plates provide the bottom reinforcement. Four full-scale interior slab–column specimens, 2000 × 2000 × 200 mm3, were tested under axial compression applied to the column. The slabs have a central 300 × 300-mm square column extending 300 mm on either side of the slab. The study assessed the contributions to punching shear strength of different components of the GFRP system. The new design experienced a 29% higher punching shear strength than the control slab with GFRP rebar only, and was much more ductile. The load dropped gradually over a large range of deflection, increasing the ductility index from 1.6 in the control slab to 3.1 in the slab incorporating the new design. An analytical model is developed for punching shear strength, accounting for concrete contribution and flexural and web contributions of I-beams. Results agreed with experimental strength, within −6% to +13%. A parametric study examined a range of rebar reinforcement ratios, different GFRP I-beam sizes and a comparable steel I-beam.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".