Innovative Applications of Parametric Design and Digital Tools in Architecture: Exploring the Integration of Generative Design and BIM Technology
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
Through parametric design and generative design, as well as the broader Building Information Modeling (BIM) approach, there is now a whole body of new tools being used by architects to are opening up new ways of designing buildings in innovative, efficient and sustainably responsible ways. This paper presents the emergence of parametric design and its evolution from simple structural optimisations to complex fulling the design of complete buildings and entire urban areas. The paper discusses the integration of both parametric design and generative design with Building Information Modelling (BIM). This technology pairing enables architects to research and test hundreds of design alternatives and optimise for particular variables, such as structural integrity, material efficiency and energy use. This paper showcases a number of case studies of how these technologies are applied to develop innovative and sustainable urban environments (eg, Sidewalk Toronto) and discusses the challenges associated with adopting these technologies, such as computational requirements and a lack of digital interoperability between these technologies. The paper concludes by identifying the innovation opportunities for sustainable development and the future of architectural practice that these technologies are offering.
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 | 0.001 | 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 it