Numerical Simulation of the Thermal Performance of Solarwall
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Energy consumed for heating in northern China amounts to 40% of the total energy consumption of cities and towns of the country, and the resulting environmental pollution is very severe as coal is the main fuel for heating in China. As a result, there is a growing, government-led trend of applying renewable energy in China. One area of interest lies in the use of solar energy. Although Chinese government has been promoting the use of solar energy, the development of building-integrated solar technology in China is relatively slow. Solar air heating system based on unglazed transpired collector (also known as solar wall) is a simple and inexpensive technique and is easy to be integrated in building. Solar wall is a potential replacement for glazed flat plate collectors. Such systems have been used in several large buildings in Canada, USA, and Europe, effecting considerable savings in energy and heating cost. However, the application of solar wall in China has just begun. A mathematical model of solar wall was established and numerical simulation was conducted to investigate the relationship between solar absorptive, thermal emissivity, outlet air temperature, and heat output by solar wall. Simulation results showed that solar radiation and airflow rate have strong effect on solar wall efficiency, and the effect of solar absorptivity on heat output is stronger than thermal emissivity. The effect of thermal emissivity on heat output is significant at higher outlet air temperature. Outlet air temperatures in the range of 20-35°C that is suited for ventilation can be easily achieved by solar wall. Solar wall is viable for China to reduce heating energy consumption and improve indoor air quality in winter.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it