Energy Optimized Envelope for Cold Climate Indoor Agricultural Growing Center
Bibliographic record
Abstract
This paper presents a study of the development of building envelope design for improved energy performance of a controlled indoor agricultural growing center in a cold climate zone (Canada, 54° N). A parametric study is applied to analyze the effects of envelope parameters on the building energy loads for heating, cooling and lighting, required for maintaining growing requirement as obtained in the literature. A base case building of rectangular layout, incorporating conventionally applied insulation and glazing components, is initially analyzed, employing the EnergyPlus simulation program. Insulation and glazing parameters are then modified to minimize energy loads under assumed minimal lighting requirement. This enhanced design forms a base case for analyzing effects of additional design parameters—solar radiation control, air infiltration rate, sky-lighting and the addition of phase change materials—to obtain an enhanced design that minimizes energy loads. A second stage of the investigation applies a high lighting level to the enhanced design and modifies the design parameters to improve performance. A final part of the study is an investigation of the mechanical systems and renewable energy generation. Through the enhancement of building envelope components and day-lighting design, combined heating and cooling load of the low level lighting configuration is reduced by 65% and lighting load by 10%, relative to the base case design. Employing building integrated PV (BIPV) system, this optimized model can achieve energy positive status. Solid Oxide Fuel Cells (SOFC), are discussed, as potential means to offset increased energy consumption associated with the high-level lighting model.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".