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通过数值模拟对高性能装甲钢进行弹道分析。

Ballistic analysis of high-performance armor steel by numerical simulation.

作者信息

Li Deda, Huang Feng, Ren Binzhi, Zhang Wei, Xiong Junjie, Zhou Binjun, Guo Xun

机构信息

School of Mechanical and Vehicle Engineering, West Anhui University, Luan, 237012, China.

Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, 430070, China.

出版信息

Sci Rep. 2024 May 20;14(1):11466. doi: 10.1038/s41598-024-62482-5.

DOI:10.1038/s41598-024-62482-5
PMID:38769430
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11668866/
Abstract

In order to establish a connection between the ballistic performance and mechanical properties of armor steel, a ballistic simulation model was developed and subsequently validated for accuracy and reliability. The mechanical properties of the target plate were described using the Johnson-Cook constitutive relation. An analysis was conducted to investigate the impact of the J-C parameters of the target plate on its ballistic performance, revealing a strong linear relationship between them. Subsequently, a mathematical model represented as H = 14.82 - 0.0048A - 0.0023B + 5.95n - 81.3C was derived, and its accuracy was demonstrated to exceed 90%. This mathematical model can effectively predict the ballistic performance of the armor steel, even when its mechanical properties undergo variations during the production process. This prediction capability significantly contributes to reducing research costs and time.

摘要

为了建立装甲钢的弹道性能与力学性能之间的联系,开发了一个弹道模拟模型,并随后对其准确性和可靠性进行了验证。使用约翰逊-库克本构关系描述了靶板的力学性能。进行了一项分析,以研究靶板的J-C参数对其弹道性能的影响,结果表明它们之间存在很强的线性关系。随后,推导了一个数学模型,即H = 14.82 - 0.0048A - 0.0023B + 5.95n - 81.3C,其准确性被证明超过90%。即使装甲钢的力学性能在生产过程中发生变化,该数学模型也能有效地预测其弹道性能。这种预测能力显著有助于降低研究成本和时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/e76c72cdf5f1/41598_2024_62482_Fig12_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/cb31f174d371/41598_2024_62482_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/2ac9b1833e17/41598_2024_62482_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/3ee12568ab35/41598_2024_62482_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/1e33760eb41f/41598_2024_62482_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/c0eb69a35f35/41598_2024_62482_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/e812a3001b10/41598_2024_62482_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/9ec5b8628cba/41598_2024_62482_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/22f9ce9d258a/41598_2024_62482_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/d781bba98ba4/41598_2024_62482_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/40a6c1d8ebcd/41598_2024_62482_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce74/11668866/e76c72cdf5f1/41598_2024_62482_Fig12_HTML.jpg

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