Inverse estimation of the annual heat flux through the internal surface of a multilayer wall in an occupied prefabricated house from field measurements
Bibliographic record
Abstract
Understanding transient heat transfer in building assemblies is important for improving the energy efficiency of the built environment. This paper describes an inverse analysis to evaluate the field energy performance of a multilayer prefabricated wall. The purpose is to estimate the heat flux through the internal surface of a wall in an occupied lightweight house in Quebec City (Canada). The inverse problem modeling was based on one-year on-site temperature measurements which convey the in-use thermal behavior of the wall assembly. The inner surface experienced an outward heat flux for most of the year. The greatest heat loss was around 5.5 W m −2 in winter and the greatest heat gain was around 1.0 W m −2 in summer. In the heating period, the indoor environment lost about 18 kW h m −2 (6.5 × 10 7 J m −2 ) of thermal energy. There was a total thermal gain of around 1 kW h m −2 (3.5 × 10 6 J m −2 ) during the free cooling period. Based on the heat flux estimations, the effective thermal resistance of the assembly was found to be 6% lower than its theoretical value, but still in compliance with Canadian building standards.
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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 | 0.000 | 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".