Thick Reinforced Concrete Walls Subjected To Non-Uniform Restrained Shrinkage
Bibliographic record
Abstract
Several researchers have studied the behavior of reinforced concrete walls under restraint shrinkage, which demonstrate the variation of the degree of restraint with different Length/Height ratios. In general, concrete standards and codes of practice recommend a minimum amount of reinforcement for shrinkage effects. This research investigates the response of thick reinforced concrete walls subjected to restraint shrinkage. The parameters studied are the thickness of reinforced concrete walls, and non-uniform distribution of shrinkage along the Length\Height and through the thickness of the wall. This study uses the non-linear finite element method to simulate the cracking behavior of the concrete and to predict tensile stresses in the reinforcement in the vicinity of Cracks. Moreover, this study investigates the influence of reinforcement ratio and compares the results with well-known concrete standards and codes of practice. It is concluded that the non-uniform shrinkage through the thickness of the wall may have significant impact on the cracking behavior of thick concrete walls. In addition, as expected, higher reinforcement ratio results in lower tensile stresses in the reinforcement. The thesis also provides guidelines for minimum reinforcement ratio.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".