Coupled Atomistic/Discrete Dislocation Simulations of Nanoindentation at Finite Temperature
Bibliographic record
Abstract
Simulations of nanoindentation in single crystals are performed using a finite temperature coupled atomistic/continuum discrete dislocation (CADD) method. This computational method for multiscale modeling of plasticity has the ability of treating dislocations as either atomistic or continuum entities within a single computational framework. The finite-temperature approach here inserts a Nose-Hoover thermostat to control the instantaneous fluctuations of temperature inside the atomistic region during the indentation process. The method of thermostatting the atomistic region has a significant role on mitigating the reflected waves from the atomistic/continuum boundary and preventing the region beneath the indenter from overheating. The method captures, at the same time, the atomistic mechanisms and the long-range dislocation effects without the computational cost of full atomistic simulations. The effects of several process variables are investigated, including system temperature and rate of indentation. Results and the deformation mechanisms that occur during a series of indentation simulations are discussed.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".