Climate Chamber Experiment-Based Thermal Analysis and Design Improvement of Traditional Huizhou Masonry Walls
Bibliographic record
Abstract
Supported by thousands of years of history, traditional Huizhou buildings have played a vital role, both functionally and culturally, as residential buildings in China. Masonry walls are one of the key building components of a Huizhou building; however, the traditional Huizhou masonry wall structure, predominantly a hollow brick structure, cannot meet the local building energy code requirements, and thus needs to be improved. Within this context, the present research measures the actual thermal performance of traditional Huizhou masonry walls for historical buildings and new-built buildings, which results in mean thermal transmittances of 1.892 W/m2·K and 2.821 W/m2·K, respectively, while the local building energy code requires a minimum thermal transmittance of 1.500 W/m2·K. In order to improve the thermal performance of traditional Huizhou masonry walls, four design scenarios for wall insulation are proposed and tested in a climate chamber: (1) hollow brick wall with inorganic interior insulation mortar, (2) solid brick wall with inorganic interior insulation mortar, (3) hollow brick wall with foamed concrete, and (4) hollow brick wall with foamed concrete plus inorganic interior insulation mortar. The experiment results indicate that, among the four proposed design scenarios, only scenario 4 can significantly improve the thermal performance of Huizhou masonry walls and meet the building energy code requirements, with a mean thermal transmittance of 1.175 W/m2·K. This research lays the foundation for improving the thermal performance of Huizhou masonry walls with new insulation and construction technology, thereby helping to improve the quality of life of Huizhou residents while respecting the cultural significance of the traditional Huizhou building.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".