Non-Local Damage Model to Predict the Effect of Pre-Strain on Ductile Fracture in Aluminum Alloy 5052
Bibliographic record
Abstract
Metallic components may develop plastic deformation before in-service loading (pre-strain) due to manufacturing process and/or unexpected loading. This pre-strain not only affects the yield strength of the material but also influences its fracture properties. The work presented here employed laser drilled model materials to better understand the effect of pre-strain on ductile fracture in aluminum alloy 5052. The micron-size laser drilled holes mimic voids forming during ductile fracture. These laser holes are introduced after the material has been pulled in tension to various amounts of pre-strain. The effect of pre-strain on void growth and linkage leading to fracture is studied. A non-local damage is used in a finite element model to predict linkage between voids. This non-local damage has only two adjustable parameters, namely the local failure strain in uniaxial tension and the characteristic length L which intervenes in the non-local averaging scheme. The precise arrangement of the laser holes can be exactly reproduced in the finite element model which allows the model to be validated with the experimental results.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".