DYNAMIC PERFORMANCE OF A FULL-SCALE WOOD FRAME SUBJECTED TO CYCLIC LOAD TESTING
Bibliographic record
Abstract
The strength-to-weight ratio of wood structural elements makes them very attractive on an engineering design point of view.This is one of the reasons why wooden buildings are known to perform well during seismic events of medium and high intensities.However, ductility and over strength factors, making it possible to design structures having the capacity to resist a seismic event by its inelastic properties, are not well characterized and leads to a local over design of assemblies and critical wood sections.The primary objective of this study is to characterize the cyclic behaviour of a diagonally braced full-scale frame.This study focuses on capacity design to have the dowel assemblies as the main dissipator of energy.A full-size frame specimen was subjected to cyclic loading.The frame was built with glulam timber elements joined together with hidden steel plates and fastened with dowels.The cyclic loading results demonstrated a global ductile behaviour, a good redistribution of the internal efforts in the assemblies, a reduction of the secant stiffness after the yielding point, increment of the dissipation of energy, great over-strength, and minor damage in the timber elements.This supports the use of this type of frame with a capacity design focused on a ductile behaviour.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".