Effects of Wood Density And Interlocked Grain on the Shear Strength of Three Amazonian Tropical Hardwoods
Bibliographic record
Abstract
Three tropical hardwoods, ishpingo (Amburana cearensis A.C. Smith), pumaquiro (Aspidosperma macrocarpon Mart.), and tulpay (Clarisia racemosa Ruiz and Pav.), were studied to determine the effects of wood density and interlocked grain on the shear strength parallel to grain.The maximum angular deviation (MAD) and the interlocked grain index (IG) were used to evaluate interlocked grain.The parameters were determined for interlocked grain samples and for ASTM D 143 shear blocks.There was a strong relationship between the interlocked grain parameters for the three species.MAD was simpler to evaluate compared to IG.The interlocked grain was highly variable within wood species.Failure of sheared blocks was irregular and in general followed the interlocked grain pattern.Hence, apparent shear strength was calculated using either a measured shear area (actual shear strength) or a fixed shear area of 2500 mm 2 (nominal shear strength).Wood density positively affected the apparent shear strength of the wood.The relationships were stronger for actual shear strength compared to nominal shear strength.For all species studied, the interlocked grain negatively affected actual shear strength.The relationships between nominal shear strength and interlocked grain parameters were positive for ishpingo and tulpay, but negative for pumaquiro.Finally, we concluded that the ASTM D 143 block shear test method should be adapted for woods with heavily interlocked grain.
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 | 0.001 | 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".