The interplay between the martensitic transformation rate and the rate of plastic relaxation during martensitic transformation in low-carbon steel, a phase-field study

IF 9.4 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Hesham Salama, Oleg Shchyglo, Ingo Steinbach
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Abstract

The complex interplay between the rapid martensitic transformation and the plastic relaxation during martensitic transformation in low-carbon steel is investigated using a combined phase-field and phenomenological crystal plasticity approach. The large transformation-induced deformations and local lattice rotations are rigorously described within the finite strain framework. The study reveals that plastic relaxation plays a crucial role in accommodating the transformation-induced deformations of martensite in the parent austenite phase. By systematically varying the plastic slip rate, imposed cooling rate, and carbon content, the simulations provide insights into the interdependence between these factors, contributing to a better understanding of the martensitic transformation process and the resulting microstructures. The phenomenological crystal plasticity model effectively relates the plastic relaxation rate to the rate of martensitic transformation with a significant time scale difference between the two processes. The findings contribute to a deeper understanding of the interplay between the rapid martensitic transformation and the requirement for plastic deformation.

Abstract Image

低碳钢马氏体相变过程中马氏体相变速率与塑性松弛速率的相互作用,进行了相场研究
采用相场与现象学晶体塑性相结合的方法研究了低碳钢马氏体相变过程中快速马氏体相变与塑性松弛之间的复杂相互作用。在有限应变框架内严格描述了大变形引起的变形和局部晶格旋转。研究表明,塑性松弛在适应相变诱发的马氏体在母体奥氏体相中的变形中起着至关重要的作用。通过系统地改变塑性滑移率、强制冷却速率和碳含量,模拟提供了这些因素之间相互依赖的见解,有助于更好地理解马氏体转变过程和由此产生的显微组织。现象学晶体塑性模型有效地将塑性松弛速率与马氏体相变速率联系起来,两者在时间尺度上存在显著差异。这些发现有助于更深入地理解快速马氏体相变与塑性变形要求之间的相互作用。
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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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