Virtual Testing of Strong Wood Light-Frame Shear Walls under Monotonic and Cyclic Loads: Model Development, Validation, and Parametric Studies
Why this work is in the frame
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Bibliographic record
Abstract
There is a growing demand for strong wood light-frame shear wall systems in mid-rise buildings, particularly in high-seismic zones. The best performance of these walls is achieved when most of the energy is dissipated through shear deformation in the sheathing-to-framing connectors (nails), while the framing and anchorage systems remain within their elastic regime. This study presents a numerical methodology for virtual characterization and analysis of strong wood light-frame shear walls subjected to large monotonic and cyclical loads, utilizing a 3D finite element (FE) model in the ABAQUS software. The accuracy of the predictions for both the nail connectors and the wall assembly is validated by comparing them with experimental data from the literature. The results indicate that a discrete hold-down system can overstress the end studs, increasing the risk of wood crushing. Furthermore, it is shown that optimizing the elastic properties and thickness of oriented strand board (OSB) sheathing panels can significantly improve the performance of wood light-frame shear walls without increasing the number of the nails.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it