Achieving Solar Energy in Architecture-IEA SHC Task 41
Bibliographic record
Abstract
Despite the wide diversity of available solar technologies, solar energy systems are still not considered as main stream technologies in building practice. This may be attributed to several factors such as lack of awareness and knowledge among architects, lack of tools supporting the design process, and lack of solar products designed for building integration. In order to address these issues, the IEA SHC Task 41 “Solar Energy and Architecture” was carried out during 2009 to 2012. The main aim was to promote the use of solar energy systems within high quality architecture. The main expected outcome is an increased use of solar energy in buildings, reducing the non-renewable energy use and GHG emissions. Fourteen countries participated. The work was organized in three subtasks: A) integration criteria and guidelines, B) tools and methods for architects, and C) case studies and communication guidelines. This article presents an overview of the Task's activities and results. The results include an inventory of computer tools, a literature review, a survey on solar systems perception and use by architects, a survey on needs regarding tools for solar design, recommendations for computer tool developers and different guidelines for solar product developers and architects. Finally an extensive collection of more than 250 case studies with integration of solar systems was evaluated and resulting in the online publication of around 65 selected cases demonstrating inspiring solar architecture. The results of Task 41 are also currently being disseminated through seminars and workshops for building professionals.
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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 | 0.026 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".