An Assessment of the Thermal Performance of Wood Curtain Wall Frames
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.
Bibliographic record
Abstract
<p>The thermal performance of three different wood framed curtain walls was analyzed and compared to the performance of two thermally broken aluminum curtain walls and one fiberglass curtain wall. U- values for the framing members and overall curtain wall, as well as condensation resistance values were obtained as per NFRC 100 through THERM/WINDOW simulation. In addition, area weighted U-value calculations were done to assess the thermal impact that glass supports had on the frame performance. Finally, whole building energy simulation was done to compare the relative performance of the system analyzed based on the building size. On average, wood curtain wall frames were found to have lower U- values than aluminum curtain wall frames and FG curtain wall frames by 59% and 14 % respectively. In addition, curtain wall sections were found to have lower U-values with wood frames than aluminum frames by an average of 14%. On the other hand, the average condensation resistance of the wood curtain walls was found to be 12% lower than aluminum curtain walls and 3% lower than FG curtain walls. The best performing curtain wall for each frame material were also modelled in OpenStudio/EnergyPlus on two different buildings and the wood curtain wall produced a TEDI that was on average 7% lower than the aluminum curtain wall. Moreover, the glass supports used in wood curtain walls were found to have a much lower impact on the U-value of the frame than the setting chairs used in aluminum curtain walls. Average overall curtain wall U-values and TEDI for the wood and FG curtain walls were found to be virtually the same. </p>
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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 | 0.001 | 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 | 0.001 | 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 it