Dynamic Relaxation and New Periodic Symmetry Techniques for Simulating Atomistic Dislocation Models Subjected to Two-Dimensional External Forces
Bibliographic record
Abstract
The movement and interactions of dislocations, under the potential energy and the external driving forces, affect the performance of materials in various applications. The Dynamic Relaxation (DR) technique, the Embedded Atom method (EAM) potential function and a newly developed periodic symmetry method are combined and expanded for simulations of the relaxation of atomistic models with dislocation defects subjected to two-dimensional external forces. This paper focuses on solving two challenges in the simulation: (i) it evaluates correct internal forces and corresponding external forces with more complicated periodic boundary in the model and (ii) finds a proper way to revise the displacement field of atoms in the boundary layers to satisfy the requirements of the periodic symmetry in the direction other than the direction of dislocation line. The numerical parameters, such as the choice of damping ratios and the variation of forces in different directions, are studied. The example given, illustrated by behaviour of stress and/or displacement components, deals with and compares the relaxation of a dislocation model under biaxial external forces.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".