Characterization of Low- and High-Velocity Responses of Basalt–Epoxy and Basalt–Elium Composites
Bibliographic record
Abstract
Currently, fiber-reinforced polymer composites (FRPs) used for demanding structural applications predominantly utilize carbon, glass, and aramid fibers embedded in epoxy resin, albeit occasionally polyester and vinyl ester resins are also used. This study investigates the feasibility of employing recyclable and sustainable materials to formulate a composite suitable for load-bearing structural applications, particularly in scenarios involving low-velocity and high-velocity impacts (LVIs and HVIs, respectively). The paper presents a comparative analysis of the performance of basalt-Elium, a fully recyclable, sustainable, and environmentally friendly composite, with an epoxy-based counterpart. Moreover, an accurate and reliable numerical model has been developed and introduced through which the response of these composites can be examined efficiently and accurately under various loading states. The results of this investigation demonstrate the viability of the basalt-elium composite as a fully recyclable and sustainable material for crafting efficient and lightweight composites. Additionally, the accurately developed finite element model presented here can be used to assess the influence of several parameters on the composite, thereby optimizing it for a given situation.
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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 | 0.000 |
| 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) | 0.001 | 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".