Bibliographic record
Abstract
Contemporary wind load standards and codes of practice have placed an ever-increasing emphasis on the detailed determination of pressure coefficients appropriate for the design of low buildings of various shapes. In contrast, the evaluation of the upwind exposure is rather rudimentary, although its influence on the design wind loading may be at least as critical. Problems and discrepancies have been found in the provisions of exposure factors (Ce) when comparing different national wind standards and codes of practice, as well as when examining experimental findings in relation to code predictions. For instance, the minimum fetch length of suburban exposure required for equilibrium of wind speed profile is 460 m or 10 building heights, whichever is larger, as per ASCE 7, but 1500 m in the Canadian code NBCC 1995 (note the just released NBCC 2005 has modified this to 1000 m or 10 building heights; it also allows some interpolation of Ce values for upwind terrain patches greater than 50 m.) Problems have also been found in application of current Ce provisions for design in case of complex terrain or inhomogeneous extreme exposure. These problems may be attributed to the fact that the current codification approach is based on the assumptions that low building wind loads are well predictable with explicit analytical relationships of terrain roughness, wind speed and pressure coefficients. Roughness patches of different distance to site are considered of equal importance (as long as within a cut-off fetch length from site). Those assumptions appear to be oversimplified. The current analytical models may not predict well wind speeds at close-to-ground levels, i.e. `roughness sub-layer' [Raupach et al]. Moreover, those assumptions do not account for the turbulence loading effects which have not been fully understood yet. Wang and Stathopoulos noticed that patches of different distance to site have different strengths of impact. A wind tunnel study has been carried out investigating the low building wind load variation above different terrain configurations with particular attention to small-scale roughness changes close to site. It was found that the peak wind loads are dominated by the terrain configurations in a short distance upwind the site. This paper presents key results of this study and compares them with the ASCE 7 provisions for low buildings.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".