Comportement thermohydrique d’une paroi en béton : influence du type de béton, influence du type de chargement
Bibliographic record
Abstract
Tests simulating “the accidental conditions” and the “test of heating,” without the contribution of humidity, have been carried out on test equipment that we designed and fabricated in the scope of this work. The tests have been carried out on laterally sealed and insulated cylindrical specimens of ordinary or high-performance concrete having a thickness of 1.3 m. Experimental results present temperature, pressure, and moisture distribution throughout the specimens and permit to characterize the hygrothermal behaviour of a concrete wall. The different aspects of the phenomena affecting a two-phase transfer (steam, water) in a porous medium are presented. Test results show that high-performance concrete exposed to an increase in temperature presents a particular hygrothermal behaviour, because of its microstructure, that is put into evidence, notably while looking at the role of the silica fume. The migration of water is not as rapid in high-performance concrete as in ordinary concrete, which is favourable for tightness. Numerical investigation consists of adapting a heat and mass transfer model, initially built for ordinary concrete, to the high-performance concrete used in this work.Key words: hygrothermal behavior, concrete wall, ordinary concrete, high-performance concrete, leak tightness, temperature distribution, pressure distribution, moisture distribution.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".