Prediction of Drying Shrinkage Cracks of Steel Chip Reinforced Polymer Cement Mortar
Bibliographic record
Abstract
This paper describes experimental and analytical study of drying shrinkage crack behavior of steel chip reinforced polymer cement mortar (SCRPCM) and polymer cement mortar (PCM). (1) Drying shrinkage test is conducted with four restrained wall specimens of 2500 mm length and 150×300 mm cross section. The drying shrinkage strains, the number of cracks and the crack patterns of the specimens are observed. (2) (a) flexural creep test, (b) pull-out bond test and (c) bond creep test are carried out to evaluate the bond between the SCRPCM/PCM and the steel bar as well as creep characteristics. The shrinkage strains and creep strains of SCRPCM/PCM, and the bond stress-slip curve and bond creep of steel bars are modelled partially according to CEB-FIP Model Code. These models are incorporated with bond computation between the SCRPCM and the steel bar to predict effective strain. The bond stress distribution is computed using analytical solutions of the differential equation of the bond problem, and crack numbers are predicted. (3) 2D finite element analyses are conducted for the four restrained wall specimens of SCRPCM/PCM subjected to drying shrinkage to practically simulate the crack behaviors. The analyzed crack patterns, number of cracks and crack widths are compared with the result of drying shrinkage test.
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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 | 0.001 | 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".