Study of a phase change material integrated in a building wall: experiments and modelling
Bibliographic record
Abstract
This thesis studies the behaviour of a phase change material that has been integrated in a building wall for heat storage and thermal comfort purposes. The phase change material, manufactured as thin, almost squared panels, is tested in a controlled environment under certain thermal conditions. Several layers of panels of this material are embedded on the interior of a wall of a small test wooden room. \nThe material is first heated and then left to cool down in order to observe its performance before, during and after its phase change. In other words, to observe its transition from solid to liquid and then back to solid. The temperature at every layer is recorded at short intervals for the duration of the experiment and this temperature profile is later plotted against time for a neat analysis of the panels. A finite difference model is developed to predict the material behaviour, and the relevance of the most important model parameters is briefly explained. The model is compared to the experimental data and the fit of the model is discussed. \nResults show that the material behaves differently when warming up than when cooling down. The freezing point is slightly lower than the melting one. The model reasonably fits the data although it is better at predicting the warming phase.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".