Study of Brazilian native wood 'Caryocar villosum' rolling shear properties to produce CLT panels.
Bibliographic record
Abstract
Abstract The utilization of Cross-Laminated Timber (CLT) in construction has surged for its sustainable nature and structural efficiency. However, existing research predominantly focuses on CLT production using softwood species, neglecting the potential of utilizing hardwoods. This study investigated rolling shear strength (frs) and stiffness (Grs) 3-layer CLT elements made from Pequiá ("Caryocar villosum"). Experimental shear (vertical and inclined) and bending tests were conducted on different samples of specimens. Complementing the experimental work, numerical simulations using ABAQUS software were employed. Results indicated similar average resistances (frs) across different tests. The higher average stiffness (Grs) was observed in vertical shear compared to inclined shear tests. The vertical shear test was deemed more suitable for determining stiffness. Furthermore, the panel’s average stiffness was found to be greater than the beam’s average stiffness. An analytical equation was developed for the three-layer panel, and it was effective in estimating the rolling shear stiffness from bending tests. Additionally, numerical modeling successfully identified the regions of highest stress concentration, where ruptures occurred in the samples tested experimentally. These ruptures mainly occurred due to the concentration of shear stresses in the central layer of the CLT samples, with the contribution of normal compression and tensile stresses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".