From Architectural Sketch to Feasible Structural System Solution
Bibliographic record
Abstract
Timely engineering feedback to the architect during the design process can result in improved building performance. Architectural sketches convey the architect's initial design intentions and explorations. As such, they become the first means for communicating with the structural engineer. The goal of this research project is therefore to provide the structural engineer with the mechanisms for devising feasible structural solutions from architectural sketches thus enabling early collaboration. This project is being carried out in collaboration with the LUCID group from the University of Liège, in Belgium. The project combines the strengths of two computer-based prototypes: EsQUIsE developed by the LUCID group for capturing and interpreting freehand architectural sketches, and StAr developed by the authors for assisting engineers during conceptual structural design. Such early collaboration assistance enables the architect to assess the structural consequences of his/her designs at sketching time without interfering with creative work, and it provides an opportunity for the engineer to get involved earlier on in the building design process and voice structural concerns in a timely manner.
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 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 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".