Developing Multi-Scale Model for Graphene Cement Nanocomposite: Study of Damage Initiation
Bibliographic record
Abstract
Damage initiation due to the interfacial debonding plays a vital role in the mechanical properties of graphene-reinforced concrete. In this research, multi-scale modeling is exploited to study the effect of volume fraction, aspect ratio, and interaction properties of the multi-layer graphene nanoplatelets (GNPs) on the mechanical properties of reinforced concrete, assuming perfectly bonded and cohesively bonded interaction between the contact surface of the matrix and the GNPs. The cohesive zone model has been used to observe the debonding behavior and damage initiation between the concrete matrix and nanocomposites for cohesively bonded interaction. The required cohesive zone parameters were estimated based on the previously calculated information on graphene–graphene interactions. The results show that by increasing the volume fraction and aspect ratio of GNP, nanofiller improves the mechanical properties of the nanocomposite. In addition, results reveal that interaction properties significantly affect the mechanical properties of graphene-reinforced concrete.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".