Analysis of the passive design and solar collection techniques of the houses in the 2009 U.S. Department of Energy's Solar Decathlon competition
Bibliographic record
Abstract
The U.S. Department of Energy‘s Solar Decathlon is a competition in which twenty university teams compete to design and build the best completely solar powered house. The biennial competition culminates with the teams reconstructing their houses on the National Mall in Washington, DC for a week of tours and contests. In order for houses to be successful they must take advantage of passive solar design techniques while maximizing the solar energy collected through photovoltaic and thermal collectors.\nInternal temperature, internal humidity, overall energy balance, site insolation, site temperature and site humidity data were measured for all twenty houses in 15 minute intervals for the eight days of the competition period. Photovoltaic conversion and thermal energy collection were predicted through simple equations which utilized site insolation and temperature data along with collector parameters and orientation. The construction documents for all twenty houses were analyzed for passive solar design techniques. Passive solar data was quantified through use of several rules of thumb. The passive solar design techniques analyzed were direct–gain, indirect–gain, thermal mass, daylighting, insulation, window placement, and shading.\nMeasured internal temperature and energy usage data were compared with the quantified passive solar rule of thumb values and plotted. Trendlines were fit to the resulting plots using simple linear regression. These trendlines were used to discuss patterns that emerged correlating each passive solar design technique to house performance. These correlations were also used to discuss the validity of the rules of thumb as a design tool.\nThe results for adherence to the passive solar rules of thumb and solar energy collection were combined to provide rankings of the best designed solar houses. The top three designs based on these criteria were Team Ontario/BC, Team Alberta, and University of Minnesota. These rankings were compared to combined placement in the comfort zone competition and the energy balance competition. Only one of the three predicted best houses was also in the top three for actual competition performance: Team Ontario/BC.\nStrong relationships emerged between insulating values and internal temperature control. Strong relationships were also found between thermal storage volume and predicted total thermal collection. The plotted comparisons contradicted many of the limits associated with the passive solar rules of thumb. The rules of thumb are best used as quick calculations and estimations and a more refined computer model should be used for more accurate results.
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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 | 0.001 |
| 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".