Modeling high velocity impact on thin woven composite plates: a non-dimensional theoretical approach
Bibliographic record
Abstract
A new theoretical energy-based model that predicts the ballistic behavior of thin woven composite laminates is presented. This model formulated for high velocity impacts, where the boundary conditions (applied at the external edges of the impacted plate) do not play a relevant role. This can be assumed as the mechanical waves do not reach the borders during the impact event, being the local structural behavior responsible for the ballistic performance. A non-dimensional formulation is used to analyze the influence of material properties and geometrical parameters in the ballistic response of the laminate. The model is physically-based on the energy contribution of different energy-absorption mechanisms. A 3 D finite element model previously developed is used to simulate the performance of the laminate under high velocity impacts and to validate the hypotheses of the theoretical model. A comparison between FE and theoretical models is performed by means of energy-absorption mechanisms. For that, the failure modes of the FE model are related to the corresponding energy-absorption mechanisms of the theoretical associated. The evaluation of the theoretical results is straightforward although the FEM results require the evaluation of the energy absorbed by each element that fails under each criterion. The predictive capability of the proposed model is verified against experimental results, which were obtained from previous studies carried out by the authors. The results obtained show the dependencies between the ballistic response and the non-dimensional physical parameters of the model. Furthermore, the proposed model can be used to see the relative importance of the different energy-absorption mechanisms involved and the comparison of these mechanisms between the theoretical and the FE models can reflect the different roles played by them, depending on the material properties and geometrical characteristics of the laminate. These results highlight the relevance of the in-plane energy-absorption mechanisms, which rule the penetration process for thin laminates.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".