The metallic shaped charge liner (SCL) is widely utilized in the defense industry, oil perforation, cutting, and other industrial fields due to the powerful penetration performance. However, quantitative law and underlying mechanisms of material properties affecting SCL penetration performance are unclear. Based on the real and virtual material properties, by combining numerical simulation with machine learning, the influence of material properties on SCL penetration performance was systematically studied. The findings in the present work provided new insights into the penetration mechanism and corresponding influencing factors of the metal jet. It indicated that penetration depth was dominated by the melting point, specific heat, and density of the SCL materials rather than the conventionally perceived plasticity and sound velocity. Average perforation diameter was dominated by the density and plasticity of the SCL materials. Particularly, the temperature rise and thermal softening effect of the SCL controlled by the melting point and specific heat have a significant effect on the "self-consumption" of the metal jet and further on the penetration ability. Additionally, the density of the SCL influences the penetration depth deeply via dynamic pressure of the jet, but the influence of density on penetration depth decreases with the increase in density. The correlation between the key properties and penetration performance was obtained according to a quadratic polynomial regression algorithm, by which the penetration potential of SCL materials can be quantitatively evaluated. Overall, the present study provides a new SCL material evaluation and design method, which can help to expand the traditional penetration regime of the SCL in terms of the penetration depth and perforation and is expected to be used for overcoming the pierced and lateral enhancement trade-off.
Revealing the Influence of Material Properties of Shaped Charge Liner on Penetration Performance via Numerical Simulation and Machine Learning.
阅读:15
作者:Wang Yan, Liu Jinxu, Liu Xingwei, Feng Xinya, Du Yifan, Cao Jie
| 期刊: | Materials | 影响因子: | 3.200 |
| 时间: | 2025 | 起止号: | 2025 Jun 11; 18(12):2742 |
| doi: | 10.3390/ma18122742 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
