Monitoring Structural Response of a Wooden Light-Frame Industrial Shed Building to Environmental Loads
Bibliographic record
Abstract
Light-frame wooden buildings are highly complex and redundant structural systems that behave as assemblies of folded and interlocked rib-stiffened plate systems. This paper describes structural monitoring experiments on one such structure. A single storey industrial shed building located in Québec City, Canada, was monitored to determine its displacement response to wind and snow loads. Displacements were correlated with real-time estimates of these environmental loads. Observations encompassed deformations of a continuous strip of the wall and roof. Artificial (static) distributed and point loads were also applied to the structure to enhance understanding of how structural components interact. Limited finite element analysis was conducted for the rib stiffened roof system and the overall assembly, with agreement between predicted deformations and those observed under environmental or artificial loads. Measured response under snow loads confirmed theoretical expectations that composite action and load sharing are important mechanisms for light-frame buildings. The general trends for the main wind effects with steady wind direction were set, but simplified pressure coefficients had to be used for this study. A more detailed description of the wind load is needed, which can be obtained with measurements of the pressure distribution on the envelope of the building in full scale, supplemented with a wind-tunnel study. This project proved the feasibility of real-time monitoring and was the precursor for a larger monitoring project currently in progress at the University of New Brunswick.
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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".