• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>ISIJ international >Strength and Ductility Balance of a Ti-5Al-2Sn-2Zr-4Cr-4Mo (Ti-17) Alloy with Various Microstructures: Experiment and Machine Learning
【24h】

Strength and Ductility Balance of a Ti-5Al-2Sn-2Zr-4Cr-4Mo (Ti-17) Alloy with Various Microstructures: Experiment and Machine Learning

机译：具有各种微结构的Ti-5AL-2SN-2ZR-4MO-4MO（TI-17）合金的强度和延展性平衡：实验和机器学习

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This work examined the tensile properties and hardness of a Ti-5Al-2Sn-2Zr-4Cr-4Mo (Ti-17) alloy having various morphology of an equiaxed, a (α +β ) bimodal, and a (α +β ) lamellar (with or without secondary α precipitates) microstructures in terms of an experimental analysis and a machine learning approach. Among the various morphology, a good balance on strength and ductility is obtained in the bimodal morphology. On the strength, higher strength is exhibited in the microstructures having secondary lamellar α precipitates. Here, we experimentally find that the primary α phase of an equiaxed grain or a lamellae acts as only the strengthening according to the rule-of-mixtures, on the other hand, the secondary lamellar α precipitates act as precipitation strengthening dominated by cutting mechanism. On the ductility, it is strongly affected by the difference in morphology and the formation of secondary lamellar α precipitates; high ductility is obtained in an equiaxed grained morphology and in the microstructure with a decreasing fraction of secondary α precipitates. A machine learning approach adapting neural network and clustering (the Ward’s method) algorithms successfully predicts the linking between the microstructural factors and the tensile properties of strength, elongation to fracture and reduction of area; a similar dominant mode to the experimental results is estimated from a machine learning approach. Additionally, a quantitative analysis on the effect of each microstructural factor is successfully estimated according to the sensitivity of variable’s importance in terms of the neural network algorithm.
机译：该作品检测了具有各种等式的形态的Ti-5Al-2SN-2ZR-4CR-4MO（TI-17）合金的拉伸性能和硬度，a（α+

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号