Investigation of Interface Fracture between BFPMPC and Cement Concrete
Bibliographic record
Abstract
Recently, there has been wide concern about the mechanical properties of the repair interface for the magnesium phosphate cement mortar as a repair material with Portland cement concrete pavement. In this paper, based on the previous research results about basalt fiber reinforced and polymer modified magnesium phosphate cement (BFPMPC) mortar, the fracture behavior of the interfacial transition zone (ITZ) for BFPMPC and Portland cement concrete (PCC) was further pursued and studied. Firstly, a nanoindentation test was carried out on the repair interface with creep characteristics. Results showed that a synergistic effect and elastic moduli of multiple ITZs in repair interface were verified and determined. Then, the creep characteristic of ITZ was described by proposed fractional rheology characteristics in BFPMPC-PCC ITZ with further validation by finite element analysis. Finally, the interface fracture model combined with dislocation theory was proposed and analyzed. The results showed that satisfactory agreements had been obtained between the calculated results of interface fracture model and experiments. It was indicated that the fracture essence for BFPMPC-PCC ITZ was revealed by the interface fracture model. This finding, as a novel aspect and insight for interface fracture of bi-cementitious-based materials, was provided and the pursued direction of materials design for interface enhancement in pavement rapid repair was expected.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".