Bibliographic record
Abstract
The application of PV systems is regarded as an important element for sustainable zero energy buildings that require energy generation through renewable energy systems. However, the appearance of building-integrated PV(BIPV) systems is not always pleasing, as some people consider them to have an undesirably machine-like and high-tech look. Such negative views of the appearance of PV systems may deter architects and designers from including this relatively new technology when designing their projects. An international web-based survey was carried out as a part of IEA SHC Programme Task 41(Solar Energy and Architecture) activities. The purpose of this survey is to help architects develop new strategies and tools to improve the incorporation of solar components into the design of new buildings. The survey was conducted internationally in 14 countries (Austria, Belgium, Canada, Denmark, France, Germany, Italy, South Korea, Norway, Portugal, Spain, Sweden, Switzerland and Australia). This paper presents a part of this international survey conducted in Korea for the Task 41’s Subtask B: Tools and Methods for Solar Design. The contents of this survey are consisted of 4 parts ; 1) Recognition of application of the solar energy 2) Application method of solar energy 3) Design method of solar energy 4) Tools for solar design. The results show that there is still a need to improve tools and methods for architects such as increased support needed for decision-making and for solar design in CAAD tools. The results also state that architects’ skills with regards to solar design in tools are ‘poor’ or ‘very poor’. Finally, the results show that tools need to be simpler, that the interoperability between software needs to be improved, and that tools should provide basic data about solar energy aspects as well as explicit feedback to the architect.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.008 |
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".