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Record W4414475193 · doi:10.1016/j.nexus.2025.100537

Theoretical development and experimental validation of a thermal model comparing different greenhouse covering materials

2025· article· en· W4414475193 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnergy Nexus · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGreenhouse Technology and Climate Control
Canadian institutionsInstitut de Recherche et de Développement en AgroenvironnementUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaMitacsMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsGreenhouseRenewable energySolar energyThermalEvapotranspirationSensible heatThermal energyGreenhouse gasGreenhouse effectHeat transfer

Abstract

fetched live from OpenAlex

• Heat load of a gothic greenhouse could be simulated with a quasi-steady state model. • Energy efficiency in greenhouse depends on the covering material. • Heat for dehumidification represents a large part of the heating load. This study compared greenhouse covering materials for small to mid-scale greenhouse producers in cold regions. Small gothic greenhouses commonly use polyethylene, resulting in significant plastic waste due to the need for replacement every 3 to 5 years. To address this issue while minimizing heating loads, new covering materials with improved durability and energy efficiency created from recycled products (e.g., polymethyl methacrylate) are being developed. Potential energy savings should be assessed since their spectral and thermal properties may positively impact both solar gains and heat transfer. A comparison between conventional (e.g., polyethylene) and alternative covering materials (e.g., polycarbonate and polymethyl methacrylate) was then carried out through numerical modeling written in Python This model takes detailed parameters into account: crops, construction and covering materials, greenhouse configurations, and localization. It uses hourly weather data including temperature, humidity, atmospheric pressure, cloud cover, wind speed, and solar irradiance. The model calculates heat losses and gains through the roof, walls, perimeter, and ground, considering longwave and shortwave radiation, conduction, convection, infiltration, and energy sinks and sources induced by plant evapotranspiration or environmental control systems. Results indicated that the model effectively predicts the heating of a double polyethylene-covered greenhouse located in the province of Quebec, Canada. The simulation of the same greenhouse covered with a polymethyl methacrylate revealed that heat loads can be reduced by 8.5 %. The thermal analysis also showed that, heat used in ventilation for dehumidification could represent 29 % of all energy consumption. This study enlightens several ways to improve sustainability of the greenhouse industry regarding energy consumption and plastic waste.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.160

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 head0.014
GPT teacher head0.214
Teacher spread0.200 · 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