Predicting Performance Of Oriented Strandboard Under Concentrated Static Loading Conditions Using Finite Element Modeling
Bibliographic record
Abstract
Oriented strandboard (OSB) panels were tested under a concentrated static load (CSL). A finite element (FE) model with variation of stresses and strains in the thickness direction was established to simulate the deflection of OSB under 890-N CSL. The CSL ultimate load of each OSB panel was simulated by increasing the load in the FE model until the calculated stress met the corresponding measured strength. Comparison of the calculated and the experimental data showed that the initial failure had two modes: failure initiated by interlaminar shear stress in the major direction near the central layers and edge of the panel when modulus of rupture (MOR) to interlaminar shear strength ratio in the major direction was greater than 18.8, and failure initiated by bending stress in the major direction near the bottom layers and the loading spot when MOR to interlaminar shear strength ratio in the major direction was less than 17.4. Panel thickness determined the initial failure mode when the ratio of MOR to interlaminar shear strength in the major direction was between 17.4 and 18.8. The vertical density profile affected the distribution of bending stresses and MOR in the profile of panels and influenced the accuracy of the prediction of the FE model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".