MétaCan
Menu
Back to cohort
Record W2805597550 · doi:10.11159/ffhmt18.126

Solar Heat Pipe for Greenhouse Application in the Arctic Regions: A Case Study

2018· article· en· W2805597550 on OpenAlexvenueno aff
Ryan Cain, Casey Hoflich, Joseph Ofeldt, Karlin Swearingen, Sunwoo Kim

Bibliographic record

VenueProceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouseArcticEnvironmental scienceMeteorologyOceanographyGeographyGeology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.273
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the ... International Conference on Fluid Flow, Heat and Mass TransferSame topicClimate change and permafrostFrench-language works237,207