Bibliographic record
Abstract
Solar thermosiphons integrated into the thermal envelop of buildings has been studied for their potential to take advantage of solar energy in heating buildings. The annual performance of solar thermosiphons cannot currently be predicted with the correlations from previous research. Also, no work has been done on the supply mode of a solar thermosiphon even though it has the potential to provide heating and fresh ventilation air. An investigation was done with the goal of developing a numerical model that could predict the performance of the supply mode of a solar thermosiphon. The numerical model included infrared thermal radiation and conduction through the glass, phenomenon which had not been used in previous numerical models. To validate the numerical model a novel steady state experiment was developed. This experiment included radiation as the heat source and the ability to vary geometric lengths. The performance parameters of mass flow rate and thermal efficiency were comparable between the numerical predictions and experimental results. However, due to uncertainties in the current experimental setup, full validation of the numerical model was not possible. These uncertainties would have to be addressed before the numerical model that was developed can be fully validated and used for generating correlations. After consideration of practical implementation constrains, it was shown that it was easier to implement the indoor air curtain mode of a solar thermosiphon than the supply mode. The indoor air curtain mode provides the same amount of energy from solar radiation to heat a building as the supply mode of a solar thermosiphon.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".