Strengthening of simply supported deep beams with openings using steel-reinforced ECC and externally bonded CFRP sheets
Why this work is in the frame
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Bibliographic record
Abstract
In many practical applications, openings in deep beams are essential for accommodating services like ducts, pipes and cables. However, openings can significantly disrupt the load-transfer mechanism and reduce the shear strength of the beam, potentially leading to premature failure. Strengthening techniques are thus used to restore or enhance the load-carrying capacity and structural performance of deep beams with openings. The effectiveness of a novel strengthening approach that combines reinforced engineered cementitious composites (ECCs) and externally bonded carbon-fibre-reinforced polymer (CFRP) sheets was investigated. ECC reinforced with galvanised steel wire mesh was applied to the beam sides, with steel anchors to connect it to the concrete. CFRP sheets were then glued onto the hardened ECC surface. ECCs are highly ductile, fibre-reinforced cementitious materials with superior crack resistance and energy dissipation capabilities. Externally bonded CFRP sheets provide additional shear reinforcement and confinement owing to their high tensile strength. Six reinforced concrete deep beam specimens were fabricated and tested to investigate the effects of opening shape (rectangular or circular) and size on shear capacity. Load–deflection responses, crack patterns and failure modes were obtained. A non-linear finite-element model, developed to simulate the strengthening technique, was validated using the experimental findings. The results of this work provide valuable guidelines for enhancing the performance of deep beams with openings using reinforced ECCs and externally bonded CFRP sheets.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it