Lateral resistance performance of wood-frame shear walls with wooden nail connections: Experimental and finite element analysis
Bibliographic record
Abstract
Modern architecture and engineering increasingly favor timber structures due to their sustainability. Wooden nails, as eco-friendly alternatives to traditional metal connectors, offer promising potential for widespread adoption. This study analyzed the influence of various parameters on the shear performance of wooden nail connections through monotonic loading tests. Key factors examined included sheathing panel material (oriented strand board (OSB) and structural plywood (SP)), thickness (9.5 and 12 mm), as well as nail diameter (3.7 and 4.7 mm), spacing (50 and 100 mm), and cap configuration (with/without caps) on the mechanical behavior of the joints. Analyzing load-displacement curves and mechanical parameters (ultimate load, stiffness, ductility) reveals several key findings: nail cap design has minimal impact on shear performance compared to other factors; joints with SP sheathing panel material show significantly higher shear-bearing capacity than those with OSB. Stiffness and ductility vary across specimen groups, with group O9-4.7 (denoting OSB sheathing, 9.5 mm thickness, and 4.7 mm nail diameter) having the highest stiffness (1 332 N/mm) and group O12-4.7 (OSB sheathing, 12 mm thickness, and 4.7 mm nail diameter) showing superior ductility (3.47). Additionally, a comprehensive finite element (FE) simulation of full-size wood-frame shear walls using OpenSees software provides insights into the influence of sheathing panel form, material properties, and thickness on lateral resistance performance.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".