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W 颗粒增强 Ti 基金属-金属复合材料的准静态和动态力学行为

Translated title of the contribution: Quasi-static and dynamic behavior of W particle reinforced Ti matrix metal-metal composite
  • 李谋
  • , 周睿
  • , 杜萌
  • , 曹远奎
  • , 刘彬
  • , 刘咏*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Ti matrix metal-metal composites exhibit good comprehensive properties such as strength and plasticity. The quasi-static and dynamic behavior of W particle reinforced Ti matrix metal-metal composites (Ti-W) were investigated by scanning electron microscopy (SEM), X-ray diffractometry (XRD), material mechanical properties test, split Hopkinson pressure bar (SHPB) and MATALAB software. The results show that Ti-W composites exhibit a dual phase heterostructure composed of β-Ti and β-W. When the content of element W in the composite is greater than 25% (mole fraction), fine W-rich phase is precipitated in the tissue. The maximum yield strength and ultimate strength of Ti-W composites can reach 1567 MPa (Ti-30W) and 1726 MPa (Ti-30W) under quasi-static condition. The maximum yield strength and ultimate strength can reach 2148 MPa (Ti-15W) and 2908 MPa (Ti-30W) under dynamic condition. Therefore, Ti-W composites exhibit obvious strain strengthening effect. By comparing the applicability of the modified Johnson-Cook (JC) constitutive model and Back-Propagation (BP) neural network model to the mechanical behavior of Ti-W composites, it is found that BP neural network can better describe the quasi-static and dynamic behavior of Ti-W composite. 
Translated title of the contributionQuasi-static and dynamic behavior of W particle reinforced Ti matrix metal-metal composite
Original languageChinese (Simplified)
Pages (from-to)66-75
Journal中国有色金属学报
Volume32
Issue number1
Online published20 Aug 2021
DOIs
Publication statusPublished - Jan 2022

Research Keywords

  • Ti-W 金属−金属复合材料
  • 应变速率强化
  • Johnson-Cook (JC) 本构模型
  • Back-Propagation (BP) 神经网络模型
  • Ti-W metal-metal composite
  • strain rate strengthening
  • Johnson-Cook (JC) constitutive model
  • Back-Propagation (BP) neural network model

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