Effect of Construction Minor Defects on the Ductility of Reinforced Concrete Drilled Shafts
Bibliographic record
Abstract
Reinforced concrete drilled shafts are a form of deep foundation that is capable of resisting large axial forces, shears and bending moments.They are commonly used in long span bridges and high-rise buildings because of their economy.Since they are cast below ground level, they can be exposed to different construction defects in the form of soil inclusions and steel cage offset.Nonedestructive testing is often used for quality assurance purposes, but such techniques can only detect moderate to large flaws.In this research, one intact and five defective shafts are tested in the structural laboratory under pure axial compression to determine the effect of voids, out-of-position of steel cages and steel bar corrosion on ductility.Two types of voids equal to 15% of the shaft's cross-sectional area are considered, one forming within the concrete cover and the other penetrating inside the concrete core.The 1830 mm long shafts had a 305 mm diameter; they were tested under displacement-controlled condition inside a universal test machine.Findings of the study showed that the presence of minor defects has little effect on the structural behavior within the service load level, but great impact on the ductility.Also, the impact of a deep void or corroded reinforcement through a surface void on the ductility is much more significant than that of a surface void or steel cage offset.
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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 | 0.000 | 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".