STR-930: CROSS LAMINATED TIMBER WALLS WITH OPENINGS: IN-PLANE STIFFNESS PREDICTION AND SENSITIVITY ANALYSIS
Bibliographic record
Abstract
Cross-laminated timber (CLT) is gaining popularity in residential and non-residential applications in the North American construction market. An accurate quantification of in-plane stiffness of the CLT walls with openings is required to design a CLT structure subjected to lateral loads. Nevertheless, till today, no general approach is available for the design of CLT-members loaded in plane and there are no standardized methods for determining the stiffness of CLT shearwalls in the respective material design standards: the CSA O86 in Canada, and the NDS in the US. This study aims to quantify the stiffness of CLT walls with openings under in-plane loading. A finite element (FE) model of CLT walls was developed modelling wood as orthotropic elastic material and the glue-lines between layers using non-linear contact elements. The FE model was verified from test results of CLT panels under in-plane loading. A parametric study was performed to evaluate the change in stiffness of CLT walls with the variation of opening size and shape. A simplified equation to predict the in-plane stiffness of CLT walls with openings was proposed. Subsequently, a sensitivity analysis was performed using Meta-model of Optimal Prognosis (MOP) to evaluate the contribution of each parameter on the model response.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".