A Novel Space-Time Finite Element Algorithm to Investigate the Hygro-Mechanical Behaviours of Wood Fiber-Polymer Composites
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Bibliographic record
Abstract
Moisture-induced swelling, or hygroexpansion, has been known to greatly deteriorate the durability of wood fiber-polymer composites (WPC). It is generally very expensive to perform experiments to completely obtain the diffusion kinetics as the process occurs in a very extended period of time. For the first time, we have developed a space-time finite element algorithm that employs time discontinuous Galerkin (TDG) method for time-dependent 3D hygro-mechanical behaviours of WPC. The formulation of matrix equations in spatial and temporal domains are explained in detail. A block Gauss-Seidel iterative method is used in the predictor/multi-corrector multi-pass algorithm, which efficiently yields unconditionally stable and high-order accurate solutions. The model is validated by comparing the predicted time-dependent hygroexpansion with that obtained in a previous experimental study. The quantitative analysis ensures the reliability of model, based on a Fickian diffusion process. With our adaptive time-stepping scheme that bases on the embedded solution from the multi-pass iterations, the model efficiently progresses the kinetics with relatively large time steps. A runtime of a few hours compared to about three months of actual laboratory experimentation confirms the novelty and robustness of our model.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it