Solar Heat Pipe for Greenhouse Application in the Arctic Regions: A Case Study
Bibliographic record
Abstract
Rural communities throughout arctic and subarctic regions of the world have difficulties providing cost-effective means of growing produce during the winter months. Plants need light and heat in order to survive and grow, both of which are in short supply during the long, cold winters. The average temperature of the spring and fall seasons in Fairbanks, Alaska is only about 30 to 40F, which provides unreliable conditions to grow most crops. The traditional growing season in northern areas is roughly four months long, which is too short for many plants to grow and/or produce fruit. The purpose of the present research is to evaluate the use of solar heat pipe vacuum collectors to elongate the growing season of greenhouses in the arctic regions. The greenhouse utilizes the collection and retention of solar heat and a thermal mass to store the heat during days and release during nights. The solar heat pipe captures solar radiation, which heats a water-propylene glycol mix to act as the carrying medium. This fluid is pumped into the adjacent greenhouse and through the thermal mass unit. The thermal mass consists of two concrete slabs and dissipates the stored heat to normalize temperature fluctuations between night and day. A test greenhouse was built with dimensions of 12 ft by 10 ft with a height of 6 to 8 ft in Fairbanks, Alaska. Data collections for a performance analysis were made in April 2017. The experiments showed that the temperature of the greenhouse was above 60F, at an external temperature of 32F. The solar heat pipe with thermal mass system increased the average greenhouse temperature by 11F.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".