Microstructural and mechanical investigations regarding the formability of glass fiber reinforced thermoplastic pultruded profiles
Bibliographic record
Abstract
Thermoplastic fiber reinforced composites have crucial benefits over thermoset composite materials regarding sustainability and reusability, as well as in post-processing, like welding or forming. In this study in-situ pultruded unidirectional reinforced glass fiber reinforced anionic polyamide composites are investigated for their formability, to be used as local stiffening elements in light weight over molded polymer matrix composites. A forming setup was designed and manufactured and a systematic study on forming parameters was carried out in a bending radius ranging from 10 to 30 mm, pre-heating temperature from 180 to 235°C and a fiber volume content from 60 to 70 vol -%. The formed profiles were investigated regarding their stiffness in a bridged apex flexure test and a cantilever flexure test and the microstructure of the composite with microscopy and computed tomography. The ideal forming parameters were found to be 20 mm bending radius, 70 vol.-% glass fiber content and 215°C pre-heating temperature of the profiles, for the forming setup used. For forming with lower radius and temperatures, the profiles showed fiber buckling, undulations and folded fiber bundles up to fiber breakage in the inner of the formed radius. For higher temperatures, degradation on the profile surface got visible and squeeze out effects, reducing the profile shape quality. This led to lower mechanical properties and higher scatter of values. The findings give insights to process optimization for forming thermoplastic pultrusion profiles and help to prevent pre-damage during manufacturing. With this, the study participates in making fiber reinforced polymer matrix composites more sustainable and in the green transformation of structural light-weight materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".