Experimental and ABAQUS finite element studies on latania fiber-reinforced epoxy composite degradation upon water absorption
Bibliographic record
Abstract
Latania fiber is a novel natural fiber that exhibits superior mechanical properties compared to the widely used jute fiber. The main objective of this research is to investigate the influence of humidity and temperature on the aging of latania fiber-reinforced epoxy (LFRE) composites. Standard flat specimens, fabricated by hand lay-up, were immersed in distilled water and the Caspian Sea water at temperatures of 4 and 25 °C. Fick's law and the hyperbolic tangent methods were employed to characterize the moisture diffusion response. Lowering the service temperature reduced the moisture uptake rate and the water diffusion coefficient. Tensile tests were conducted to analyze and compare the mechanical behavior of pristine and aged LFRE composites. Both tensile modulus and strength were reduced upon moisture uptake. The fracture morphology of the water-aged LFRE composites was examined by scanning electron microscopy after tensile tests. The finite element ABAQUS was used to model the water diffusion into LFRE. With limited data on water absorption in this novel LFRE composite and increasing demand for sustainable materials, this study addresses a gap in understanding environmental durability essential for broader structural applications.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".