Inverse procedure for mechanical characterization of multi-layered non-rigid composite parts with applications to the assembly process
Bibliographic record
Abstract
In assembly process, non-rigid parts in free-state may have different forms compared to the designed model caused by gravity load and residual stresses. For non-rigid parts made by multi-layered fiber-reinforced thermoplastic composites, this process becomes much more complex due to the nonlinear behavior of the material. This paper presented an inverse procedure for characterizing large anisotropic deformation behavior of four-layered, carbon fiber-reinforced polyphenylene sulphide, non-rigid composite parts. Mechanical responses were measured from the standard three points bending test and the surface displacements of composite plates under flexural loading test. An orthotropic hyperelastic material model was implemented as a UMAT user routine in the Abaqus/Standard to analyze the behavior of flexible fiber-reinforced thermoplastic composites. Error functions were defined by subtracting the experimental data from the numerical mechanical responses. Minimizing the error functions helps to identify the material parameters. These optimal parameters were validated for the case of an eight-layered composite material.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".