Testing and Modeling of a New Moment Connection of Concrete-Filled FRP Tubes to Footings under Monotonic and Cyclic Loadings
Bibliographic record
Abstract
This study explores a new moment connection of concrete-filled fiber-reinforced polymer (FRP) tube (CFFT) to concrete footing. The tube is tightly fitted and adhesively bonded to a short reinforced concrete stub protruding from the footing, which facilitates concrete filling of the tube without the need for shoring. To establish the critical stub length (Xcr), specimens with heavily steel-reinforced stubs varying in length from 0.5D to 2.0D, where D = diameter of the CFFT, were fabricated and tested in flexure by using a cantilever setup. The Xcr required to achieve flexural failure of the CFFT was 1.05D. Additional specimens with a sufficient stub length of 1.5D were then fabricated to examine the effect on strength and ductility of the steel reinforcement ratio (ρs) in the stub. The optimal ρs of the stub required for the CFFT to reach flexural failure was 3.2%. Finally, the effect of low-cycle reversed bending fatigue was studied with and without an axial compression load. Remarkable ductility associated with the formation of a plastic hinge was observed at ρs of 2%. An analytical model capable of predicting (1) moment capacity of the connection, (2) whether failure is governed by flexure or bond, and (3) Xcr was developed and validated. It was then used in a parametric study to explore the effects of CFFT mechanical and geometric properties on Xcr.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".