Wind-Induced Loads on the Foundation of a Low-Rise Building: Full-Scale and Wind Tunnel Experimentation
Bibliographic record
Abstract
Structural monitoring of an instrumented experimental single-storey wood building provided important information regarding the behaviour and response of low-rise buildings subjected to wind loads. Foundation wind-induced loads were captured by twenty-seven three-dimensional load cells simultaneously with the envelope pressures and weather characteristics. The distribution of the total wind load to each wall is examined and normalized to the wind speed for each direction. The correlation between loads acting on different wall segments is also quantified in the form of participation factors. In parallel with full-scale findings, a scaled model of the experimental building and its surroundings is tested in a boundary layer wind tunnel. The detailed pressure distribution information for thirty-six wind angles of attack obtained through three different upstream terrain simulations is used to generate expected total uplift wind force. The findings are compared to data acquired directly from the foundation load cells located in the test house. The comparison revealed that in most cases wind tunnel values are within the range of the field results. Discrepancies are somewhat higher for wind tunnel tests conducted using the open/suburban terrain compared to the urban terrain simulation. The results are significant for the improvement of the wind tunnel testing and simulation procedures, for the development of code and standard provisions, as well as for the verification of the finite element numerical model of the test house.
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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 | 0.000 | 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) | 0.001 | 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 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".