Wind and Snow Loads—An International Perspective
Bibliographic record
Abstract
Buildings need to be designed to withstand wind loads regardless of where they are located and the laws of physics governing wind loads do not change when crossing political boundaries, nor do basic statistical principles. Likewise in the colder regions of the world snow loads need to be designed for and design values should again be governed by the laws of physics and statistics. However, as any designer working internationally knows, the requirements of building codes can be very different in different parts of the world. Part of this is understandable due to the geographic dependence of climate. Some is also due to historically different approaches to risk and different rates of advancement technically. However, the largest cause is the large gaps in knowledge that still exist in many aspects of wind and snow loads, and these gaps will continue to exist, making international consensus difficult, unless some of the advanced countries decide to increase considerably the research funding directed to these topics. This presentation will discuss some of the differences and similarities of wind and snow provisions in the codes of various countries and discuss approaches to improving consistency and uniformity of methods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".