平板冲击载荷作用下TiZrNb耐火多主元合金的冲击变形与剥落

IF 11.2 1区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Xiaying Ma, Kerong Ren, Rong Chen, Hang Wang, Zihan Zhang, Peiyuan Ma, Shun Li, Jiaqiang Wu
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引用次数: 0

摘要

耐火多主元素合金具有优良的力学性能,具有良好的工程应用前景。然而,由于缺乏关于rmpea动态特性的知识,这限制了考虑冲击性能的rmpea材料设计。为了解决这一问题,本研究通过单级气枪板冲击实验,研究了单相体心立方(BCC) TiZrNb RMPEA在381 ~ 723 m s−1冲击速度下的动态压缩和碎裂行为。Hugoniot参数为c0=4.162 km s−1,s = 1.005,颗粒强度为2.18 ~ 2.41 GPa。显微组织分析表明,碎裂损伤主要包括晶间和晶内裂纹的混合。动态变形主要受位错交叉滑移和剪切带(SBs)控制,Laves相引起局部应力集中,促进空洞聚结,降低小块强度。此外,通过冷能混合理论和粒子群优化-反向传播神经网络(PSO-BPNN)模型,结合力学理论和人工智能算法,建立了价电子浓度、原子质量、冲击压力与冲击体积模量之间的定量关系,为mpea的冲击性能材料设计提供了关键见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Shock-induced deformation and spallation of TiZrNb refractory multi-principal element alloy subjected to plate impact loadings

Shock-induced deformation and spallation of TiZrNb refractory multi-principal element alloy subjected to plate impact loadings
Refractory multi-principal element alloys (RMPEAs) have favorable engineering application prospects due to their exemplary mechanical properties. However, there is a dearth of knowledge regarding the dynamic properties of RMPEAs, which constrains the material design of RMPEAs considering impact performances. To address this issue, in this study, the dynamic compression and spallation behavior of a single-phase body-centered cubic (BCC) TiZrNb RMPEA at impact velocities of 381–723 m s−1 via single-stage gas gun plate impact experiments was investigated. The Hugoniot parameters were c0=4.162 km s−1 and s = 1.005, with a spall strength of 2.18–2.41 GPa. Microstructural analysis showed that spallation damage primarily involved a mix of intergranular and intragranular cracks. Dynamic deformation was mainly controlled by dislocation cross-slip and shear bands (SBs), with the Laves phase inducing localized stress concentrations that promoted void coalescence and reduced spall strength. Moreover, a quantitative relationship between the valence electron concentration, the atomic mass, the impact pressure and the shock bulk modulus was established, through the cold-energy mixture theory and a Particle Swarm Optimization-Back Propagation Neural Network (PSO-BPNN) model, which combined the theory of mechanics and the artificial intelligence algorithm, offering key insights into the materials design for the impact performance of MPEAs.
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来源期刊
Journal of Materials Science & Technology
Journal of Materials Science & Technology 工程技术-材料科学:综合
CiteScore
20.00
自引率
11.00%
发文量
995
审稿时长
13 days
期刊介绍: Journal of Materials Science & Technology strives to promote global collaboration in the field of materials science and technology. It primarily publishes original research papers, invited review articles, letters, research notes, and summaries of scientific achievements. The journal covers a wide range of materials science and technology topics, including metallic materials, inorganic nonmetallic materials, and composite materials.
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