Analytical Modeling of Posttensioned C-Shaped CLT Core Walls
Bibliographic record
Abstract
Post-tensioned (PT) timber technology, also referred to as Pres-Lam (prestressed laminated timber) provides a low damage seismic design solution. So far PT timber research and practical implementation have focused on moment resisting frames, planar shear walls and coupled planar shear wall—or column-wall-column—systems and their analytical prediction models were adapted and extended from precast concrete to account for the unique characteristics of engineered timber. Following a recent experimental study on a PT cross-laminated timber (CLT) C-shaped core-wall system aiming to enhance lateral strength and stiffness, this paper presents an analytical framework/model to capture three unique kinematic rocking mechanisms for a PT C-shaped CLT core-wall system connected primarily with self-tapping screws. Depending on the relative stiffness of the screwed connections to the PT and the energy dissipaters, the model considers different kinematic responses, and that a staged kinematic response could occur at different imposed core-wall base connection rotations. It also accounts for the material inhomogeneity of CLT with nonedge glued lamella and implements a nonlinear spring model for the screwed connections calibrated from component testing and expected elastic core-wall deformations. The study showed that, for the given specimen configurations presented, the compressive flange wall could be neglected for a PT C-shaped CLT core wall. The analytical model was verified against three large-scale 8.6 m high PT C-shaped core-wall experimental tests and the model prediction error was within 10%. The analytical model was limited to capturing the envelope (push-over) curve of a four wall PT C-shaped CLT core-wall system.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".