The impact on structural embodied carbon of using loads obtained from wind tunnel testing vs code-based loads
Bibliographic record
Abstract
<p>RWDI possesses one of the world's most extensive portfolios of data from structural wind tunnel tests. Drawing upon our wealth of experience, RWDI has carried out studies to compare wind loads achieved by undertaking site-specific wind tunnel tests against values obtained using an analytical code-based approach. In one of the studies, the peak overturning moments of ten prominent tall buildings in the UK were estimated from wind tunnel tests conducted by RWDI. Comparing these loads against values based on Eurocode and the UK National Annex, wind tunnel testing led to an average 35% reduction in wind loads for structural design. The loading reduction is attributed to various important factors that are elaborated further in this paper. In addition, notable UK and worldwide case studies are presented to demonstrate the benefits of wind tunnel testing in delivering more optimised structures and contributing to the reduction of embodied carbon.</p>
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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".