Seismic Design of CLT Shear-Wall and Glulam Moment-Resisting Frame Coupled Structure
Bibliographic record
Abstract
In response to the increasing need for sustainable construction materials, numerous innovative timber-based structural systems have been developed in the past two decades. While timber-based shear-walls are popular, moment-resisting timber frames have received less attention in recent studies. However, with the availability of ductile and resilient beam-column joints (BCJs), timber frames can now be effectively used either independently or in combination with others. This study explores the feasibility of a dual system, consisting of cross-laminated timber (CLT) balloon shear-wall and glulam moment-resisting frame (CLTW-GMRF), and investigates the potential interaction between the two systems under seismic loading. The building features ductile and energy-dissipative BCJs and hold-downs. A seismic design procedure, based on a targeted moment proportion (MP) between the two systems, is presented and applied on a 10-story building. The building is assumed to be located in Vancouver, Canada, and its seismic performance is examined using 30 ground motion records in OpenSees. The system’s efficiency with respect to engineering demand parameters is studied under different wall-to-frame MP values (50%–50% and 60%–40%) and ductility-related modification factors (2, 3, and 4). The study also investigates the system’s performance with two BCJs and hold-down alternatives with bilinear hysteretic and self-centering energy-dissipative responses. Given the availability of resilient connections, the result highlights that the CLTW-GMRF coupled system is a viable alternative for high-rise hybrid timber construction. Moreover, the system’s performance has significantly improved by using self-centering energy-dissipative systems.
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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 | 0.001 | 0.000 |
| 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".