The Effect of Relative Humidity on Creep Behavior of Cement Paste Microprism
Bibliographic record
Abstract
Despite decades of extensive studies, the mechanism of concrete creep remains a subject of debate, mainly due to the complex nature of cement microstructure. This complexity is further amplified by the interplay between water and the cement microstructure. The present study aimed to better understand the creep mechanism through creep tests on microprisms of cement paste at hygral equilibrium. First, microprisms with dimensions of 150 mm × 150 mm × 300 mm were prepared by precision cutting from a cement paste specimen with a water-to-cement ratio of 0.4. Subsequently, uniaxial compression and creep tests were carried out on these microprisms in a chamber with controlled relative humidity (RH). To mitigate the impact of plasticity and damage, the applied peak load was set to generate a stress level that was approximately 40% of the compressive strength. Moreover, an analytical coefficient φ was formulated to account for the foundation effect on microprism creep, agreeing with the numerical analysis employing the finite element method. Our findings showed that the microscale creep compliance varied when the RH level was changed from 90% to 11%. Furthermore, logarithmic and power-law models were both applied to simulate creep curves. Lastly, the modeled creep behaviors were compared with those obtained by microindentation experiments in previous studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".