Lateral Resistance of Sheathing-to-Framing Nailed Joints with an Intermediate Insulation Layer
Bibliographic record
Abstract
Lateral resistance of shear walls constructed with wood-based sheathing panels and lumber framing is largely governed by the strength of the sheathing-to-framing nailed joints. In new wall designs, a layer of soft thermal insulation is added between the sheathing and framing to increase the wall thermal resistance. Studying the influence of the intermediate insulation on the lateral load resistance of the nailed joint is essential for understanding the structural behavior of this kind of shear walls. An experimental study was conducted to measure the lateral resistance of the nailed joints. The results show that the insulation has a significant impact on the lateral resistance. An analytical model for predicting the lateral resistance, with embedment strengths of sheathing and framing members and nail bending strength as input parameters, was developed. The model predictions were compared with those from existing analytical models and with the experimental data. The ultimate lateral resistance of the nailed joints can be predicted with sufficient accuracy using the developed analytical model for the joints with up to 51-mm-thick intermediate insulation layers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".