Molecular dynamics simulation of plastic deformation in polyethylene under uniaxial and biaxial tension
Bibliographic record
Abstract
Plastic deformation of polyethylene in uniaxial and biaxial loading conditions is studied using molecular dynamics simulation. Effects of tensile strain rates from 1 × 10 5 to 1 × 10 9 s −1 , and mass density in the range of 0.923–0.926 g/cm 3 on mechanical behaviour and microstructure evolution are examined. Two biaxial tensile deformation modes are considered. One is through simultaneous stretching in both the x and y directions and the other sequential stretching, firstly in the x-direction and then in the y-direction while strain in the x-direction remains constant. Tangent modulus and yield stress that are determined using the stress–strain curves from the molecular dynamics simulation show a strong dependence on the deformation mode, strain rate and mass density, and all are in good agreement with results from the experimental testing, including fracture behaviour which is ductile at a low strain rate but brittle at a high strain rate. Furthermore, the study suggests that the stress–strain curves under uniaxial tension and simultaneous biaxial tension at a relatively low strain rate contain four distinguishable regions, for elastic, yield, strain softening and strain hardening, respectively, whereas under sequential biaxial tension, stress increases monotonically with the increase of strain, without noticeable yielding, strain softening or strain hardening behaviour. The molecular dynamics simulation also suggests that an increase in the strain rate enhances the possibility of cavitation. Under simultaneous biaxial tension, with the strain rate increasing from 1 × 10 6 to 1 × 10 9 s −1 , the molecular dynamics simulation shows that polyethylene failure changes from a local to a global phenomenon, accompanied by a decrease of the void size and increase of uniformity in the void distribution. Under sequential biaxial tension, on the other hand, the density of the cavities is clearly reduced.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".