Analysis of Effects of Long Term Stress and Ageing on Mechanical Performance of Discontinuous Natural Fibre-Polymer Composites
Bibliographic record
Abstract
Natural fibre-polymer based composite systems are becoming increasingly important for a large number of load-bearing applications. Those applications concern not only the building and construction domain but also the transport vehicles on road and in air where the unique benefit of these materials is their lightweight and good mechanical performance. Polymers exhibit time dependent mechanical properties influenced by temperature, moisture diffusion and other environmental factors. There is no exception for natural fibres in this respect. Although wood is highly resistant to creep due to its inherent anatomical and structural components, fibres derived from wood and other crops destroy their structural integrity. When a natural fibre and a polymer are present in a composite system this material system has thermomechanical properties changing with the environmental conditions and exhibits an internal and a global time dependent behaviour. Part of the internal time dependent behaviour is related to ageing and part is related to the interaction level of elastic and viscoelastic parts regulating stress transfers from the viscoelastic to the elastic regions. Durability analysis is the prediction of the properties of the material system for an imposed lifetime under an estimated complex mechanical history interaction with changing environmental conditions. The results of such a durability analysis are the necessary basis for a reliability estimation of the structural integrity of the component to be designed.
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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 | 0.000 |
| 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 | 0.001 |
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".