Study on the forming characteristics of polytetrafluoroethylene/copper jet with different preparation processes
Bibliographic record
Abstract
In this paper, PTFE/Cu composite material for liner is taken as the research object, and the preparation process and jet forming characteristics of PTFE/Cu composite liner are studied. The liners were prepared by extrusion molding, molded sintering and hot-pressing sintering. Due to different preparation processes, different microstructures of the liner can occur, including defects such as pores and microcracks, resulting in different strength and density of the liner, leading to differences in the forming characteristics of the jet. Therefore, the forming process of the jet was simulated by the finite element numerical simulation software. It was found that there was obvious radial expansion effect in the head of the jet, but with the increase of density, the radial expansion effect was weakened, and the jet velocity decreased gradually. The strength and densification of the shaped charge liner prepared by different processes were different. The densification of the molded sintering liner was generally better than that of the other two kinds of shaped charge liners. As a result, the velocity of the jet formed by the molded sintering liner is always the highest, with a numerical simulation velocity of 6642 m/s and an experimental velocity of 6534.7 m/s. The second is the jet of the hot-pressing sintering liner and the lowest velocity is the jet of the extrusion molding cover, with a numerical simulation velocity of 6482 m/s, while the experimental velocity is only 6397.9 m/s. The jet velocity measured by the pulse X-ray experiment was compared with the velocity of the numerical simulation, and the error was within 2.96%, which verifies the accuracy of the numerical simulation.
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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 | 0.001 |
| 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 | 0.001 |
| 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".