Development of a novel self-centering balloon-type CLT shear wall system for tall buildings
Bibliographic record
Abstract
The use of mass timber structures has considerably grown in recent years. This has increased the demand for sustainable, resilient, and high-performance mass timber structural systems. In this thesis, a novel self-centering balloon-type cross-laminated timber (CLT) shear wall system named the dual-pinned self-centering coupled CLT shear wall (DSCW) is proposed for tall buildings. The DSCW consists of two sets of CLT panels that are pinned at their base and coupled to one another using self-centering friction dampers. Optional V-shaped truss assemblies can also be used at the base of the panels. This thesis also presents a procedure that can be used to design the DSCW. This procedure is a modified version of the equivalent energy design procedure (EEDP). It ensures that the DSCW meets different roof displacements targets and performance objectives at various shaking intensities. The procedure was used to design the DSCWs of a 12-story prototype building located in the high-seismicity region of Vancouver (Canada). The DSCWs of the prototype building were numerically modeled and subjected to nonlinear time history analyses as well as to an incremental dynamic analysis. The results of these various analyses demonstrate that the DSCWs of the prototype building achieve the target roof displacements and performance objectives. The results also show that the DSCWs meet the seismic performance requirements of FEMA P695.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".