Development Of A Dynamic Failure Model For Polymeric Adhesives
Bibliographic record
Abstract
One method to improve armor performance of land vehicles under ballistic impact is to better design the adhesive layer used to bond the ceramic tiles to the metal/composite backing layer. This presentation will explore the development of a finite element model to simulate failure of polymeric adhesives used in these systems. The adhesive layer plays a critical role in controlling wave propagation that leads to damage accumulation within the armor structure during impact. Modelling the dynamic failure of the adhesive layer is performed using the cohesive zone modelling (CZM) approach in the explicit nonlinear finite element software, LS-DYNA . Specifically, the trilinear traction separation law is implemented in cohesive elements. The CZM approach is an energy-based method combining fracture mechanics with stress-based criteria to predict the initiation and direction of crack growth. The model is validated using force-displacement curves of the double cantilever beam (DCB) and end-notched flexure (ENF) tests for the polyurethane adhesive, SikaForce TM6 7752-L60. These tests determine the tensile and shear critical energy release rates of the adhesive layer, respectively. The validation process considers the variability in material properties used in these experiments. After validation, the adhesive model is implemented into a full-scale numerical model of the add-on armor system that also comprises of ceramics and steels. Overall, this study aims at providing novel insights in the modelling of adhesives using CZM for applications in armor systems.
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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 | 0.000 | 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) | 0.000 | 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".