Analytical model for lateral deflection of multi-storey platform-type CLT shear walls accounting for floor-wall interaction
Bibliographic record
Abstract
The lateral design of multi-panel CLT shear walls requires reliable prediction of elastic rocking drift, yet most existing methods are limited to single-storey systems and neglect floor-wall interactions. This paper presents a design-oriented analytical framework for multi-storey, multi-panel walls under coupled-panel (CP) behaviour. A generalized matrix formulation is developed to compute the rocking rotations of floors and wall panels at each storey, applicable to any configuration of storeys and panels. The analytical conditions required to ensure CP behavior are derived and discussed. To validate the model’s mathematical accuracy and practical applicability, numerical models involving two- and four-storey configurations with varying numbers of panels are analyzed. Additionally, experimental results from a two-storey, two-panel shear wall test available in literature are used to verify the predictive performance of the proposed approach. The results demonstrate that the method provides accurate estimates of lateral deformation and offers a viable analytical tool for the design of CLT shear wall systems in multi-storey applications. A comparison between the analytical model introduced in this study and that of established previously with no wall-floor interaction are presented, indicating significant impact of such introduction on reducing the CLT shear wall inter-storey rocking deformation. • Analytical model predicts rocking of multi-storey CLT walls with floor interaction. • Matrix expressions yield wall and floor rocking rotations for any panel–storey set. • CP behaviour requirements developed for side and middle panels. • FE walls (2-4 storeys, 2-4 panels) confirm model accuracy and key assumptions. • Tests show rotation errors: 2–9% (1st storey) and 4–17% (2nd), high fidelity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".