Continuum Compressive Damage Modelling in Composites Using Genetic Algorithms and Nonlocal Averaging
Bibliographic record
Abstract
Continuum modelling of progressive damage in finite element analyses of fibre-reinforced polymers (FRPs) has become a popular tool because of its computational efficiency and ease of implementation. However, two of the major limitations are (i) mesh size and mesh orientation dependencies and (ii) the transparent determination of suitable input parameters. This study presents a combination of genetic algorithms (GA) with nonlocal continuum damage models to overcome these limitations. The use of GA provides an objective calibration process of input parameters, while nonlocal averaging of computed strain fields enables consistent damage evolution in FRPs irrespective of the underlying finite element mesh. The simulation of compact compression and open-hole compression tests on IM7/8552 carbon-fibre-reinforced polymers validates the calibration process and demonstrates the advantages of nonlocal damage modelling over conventional local approaches.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".