Structural Performance of CLT Shear Walls with Hyperelastic Hold Downs
Bibliographic record
Abstract
Cross-laminated timber (CLT) provides a solution for numerous structural applications, including entire seismic force resisting systems. The primary objective of the research presented herein was to develop a CLT shear wall system with hyperelastic elastomeric hold downs (HDs) that provide the required uplift resistance and deformability, so that the CLT panels develop coupled-panel rocking behavior, without strength and stiffness degradation in the HDs. Secondary objectives consisted of the mechanical characterization of the hyperelastic HD as a function of its geometry, and the determination of minimum edge and end distances to avoid brittle failure in the CLT, for development of capacity-based design procedures for this system. To achieve these objectives, the individual components (HDs, steel rods, spline joints, and CLT panels) were tested along with a total of 66 full-scale shear walls. The tests demonstrated that (1) the HDs remain elastic under rocking kinematics provided that the elastic limit of the steel rod is not exceeded, (2) sufficient CLT width can prevent undesired brittle CLT failure before steel yielding in the rods, and (3) the shear wall strength and stiffness is a function of HD size and the panel-to-panel shear connection properties. The hyperelastic HD assembly provides design engineers with a low-damage alternative to contemporary HD solutions for platform-type CLT shear walls.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 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".