Physical and mechanical properties of pultruded composites containing fillers and low profile additives
Bibliographic record
Abstract
Abstract This article deals with the effect of fillers and additives content on the physical and mechanical properties of unidirectional pultruded glass/polyester composites. The physical characterization consisted of determining the void volume fraction (Vv), density, shrinkage ratio, coefficient of thermal expansion (CTE), and dynamic mechanical properties. The mechanical tests consisted of three‐point‐bending tests under static, impact, and fatigue loading. The low profile additive (LPA) has been found to compensate the cure shrinkage by microvoid formation. Dynamic mechanical analysis measurements show that the LPA slightly lowers the glass transition temperature Tg and increases the internal damping Tan δ. The transverse coefficient of thermal expansion was found to be sensitive to the LPA content. Three‐point bending tests show that the interlaminar shear strength (ILSS) is slightly sensitive to the fillers and LPA content, but the flexural strength is not affected. Impact test results on short beam shear and flexural specimens show the same behavior as in the static tests except that the LPA content has a detrimental effect on the flexural impact properties. The fatigue tests performed show that the effect of fillers is not significant, while the LPA effect is mixed. It seems that there is an LPA content for which the fatigue resistance is maximized. Finally, the wide range of behaviors and span‐to‐depth ratios investigated suggest that the ILSS as measured according to the ASTM 2344 recommendations can be largely misleading because of the unavoidable compressive yielding under the loading nose. For the materials investigated, higher span‐to‐depth ratio are more representative of the ILSS. POLYM. COMPOS., 27:71–81, 2006. © 2005 Society of Plastics Engineers
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 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".