<scp>High‐strain‐rate</scp> mechanical performance of particle‐ and fiber‐reinforced polymer composites measured with split Hopkinson bar: A review
Bibliographic record
Abstract
Abstract Reinforcing polymers with particles and fibers has been a common strategy for decades, in order to make them suitable for high‐demanding industrial applications. As composites often undergo dynamic loads, it is important to understand their behavior under such conditions. This review first classifies the types of polymer composites and then explains their failure behavior under tension and compression loading, followed by an overview of some of the experimental procedures used to characterize the polymer composites' dynamic mechanical performance. Afterward, the most significant findings in terms of the high‐strain‐rate compressive and tensile strength and modulus of polymer composites are thoroughly discussed. The results, available in the literature, on the mechanical properties of polymer composites under quasi‐static conditions are also presented and compared with the high‐strain‐rate data. The differences are explained by discussing the changes in the structural configurations of polymer matrices under quasi‐static and dynamic loads. Lastly, conclusions and future perspectives are given, with the intent of highlighting the most promising polymer composites that can be used for a wide variety of applications.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".