State-of-the-Art of Digital Tools Used by Architects for Solar Design
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
Until recently, building information modeling (BIM) software such as Autodesk Revit, Bentley Architecture, Graphisoft ArchiCAD, and Vectorworks Architect focused primarily on modeling and refining building geometry. Users relied on third-party software such as Green Building Studio, Ecotect, Hevacomp and IES VE to analyze the energy consumption of a building. A series of developments in the past few years (since 2008) changed that: there are many CAAD software today which include some form of connection to an energy simulation program thereby allowing passive solar gains preduction. Amongst the CAAD tools reviewed, the following BIM applications offer the most interesting possibilities for energy simulations including passive solar gains predictions: Allplan, ArchiCAD, DDS-CAD PV, MicroStation, Revit and Vectorworks. Google SketchUp, which is not a BIM application, also integrates many plugins: IES VE-Ware, OpenStudio, and Google SketchUp Demeter, which allow performing thermal simulations based on IES VE, EnergyPlus and Green Building Studio. Google SketchUp is widely recognized for being used at EDP and is often used in the architect's workflow as a predecessor software to another more complex BIM or non-BIM applications (e.g. AutoCAD).
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.
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 it