In-situ testing and numerical study of thermal performance of blind systems in a cold climate zone
Bibliographic record
Abstract
Windows account for approximately 30 % of total energy loss in buildings. While extensive research has focused on the thermal performance of windows and blinds in hot climates, studies on their insulative properties in cold climates remain limited. This study evaluates the thermal performance of a blind system installed in an office through in-situ measurements and numerical analysis. Three distinct shade positions were tested: Baseline (fully open), Fully Closed, and Half Open. Results showed that fully closed shades reduced energy loss by 11.25 %, while the half-open position achieved a 5.34 % reduction. A strong correlation was observed between measured U-values and those predicted by CFD simulations. CFD analysis further revealed that U-values significantly decreased as the distance between the shade and the window increased, stabilizing at an optimal threshold, suggesting that shades should be installed at an optimal distance for maximum insulation. Additionally, an exponential relationship between thermal transmittance and outdoor temperature was identified in the unshaded condition, a novel finding. These insights offer valuable guidance for optimizing blind system designs and control strategies to enhance seasonal energy efficiency in buildings. • In-situ U-values show better-than-expected performance at lower temperatures. • ‘Performance U-Value’ highlights discrepancies between theoretical and measured values. • A novel measurement approach captures dynamic thermal performance of window shades. • Internal roller shades can achieve 11.25 % heating energy savings over 4 months. • U-value variations with window-shade distances suggest optimal insulative configurations.
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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".