Hot Compression Deformation, Constitutive Model, and Microstructure Evolution of Austenitic-TWIP/Martensitic-HFS Composite Steel

IF 4 3区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Mingrong Fan, Hongyu Zhou, Wu Peng, Lingyi Kong, Yingying Feng, Zongan Luo
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Abstract

To address the challenges of low predictive accuracy, data sensitivity, and model complexity inherent in the Arrhenius phenomenological model for predicting the flow stress of twinning-induced plasticity (TWIP) and hot-formed steel (HFS) composites, a Bayesian-optimized XGBoost (BO-XGBoost) model was developed and rigorously validated through comparative analysis. The results demonstrate that the predictive performance of the BO-XGBoost model was significantly improved compared to the Arrhenius model. Specifically, the root mean square error decreased from 16.3160 to 1.0554, corresponding to an accuracy improvement of approximately 93.5%. Using the predicted flow stress values from the BO-XGBoost model, hot processing maps for the tested steel were constructed, and the microstructures under various deformation conditions were characterized in detail. The results indicate that, at high temperatures or low strain rates, the flow curves primarily exhibit recrystallization behavior. In contrast, at higher strain rates or lower temperatures, the flow curves display characteristics of work hardening. Specifically, multiple peak flow curves were observed at a strain rate of 0.1 s−1 and deformation temperatures ≤ 1050 °C. The changes in the flow curves are attributed to the competition between work hardening, controlled by dislocation accumulation and interaction, and softening, governed by dynamic recovery and recrystallization. Furthermore, the hot processing maps reveal that the tested steel demonstrates optimal machinability within the deformation temperature range of 1075–1150 °C and strain rate range of 0.05–0.5 s−1. This finding provides valuable insights for optimizing processing conditions and enhancing the material performance of TWIP and HFS composites in manufacturing and industrial applications.

Graphical Abstract

奥氏体- twip /马氏体- hfs复合钢的热压缩变形、本构模型及组织演变
为了解决Arrhenius现象学模型在预测孪生诱导塑性(TWIP)和热成形钢(HFS)复合材料流变应力时存在的预测精度低、数据敏感性低和模型复杂性等问题,提出了一种贝叶斯优化XGBoost (BO-XGBoost)模型,并通过对比分析进行了严格验证。结果表明,与Arrhenius模型相比,BO-XGBoost模型的预测性能得到了显著提高。具体来说,均方根误差从16.3160下降到1.0554,准确度提高了约93.5%。利用BO-XGBoost模型预测的流变应力值,构建了试验钢的热加工图,并对不同变形条件下的组织进行了详细表征。结果表明,在高温或低应变速率下,流动曲线主要表现为再结晶行为。相反,在较高应变速率或较低温度下,流动曲线表现出加工硬化的特征。其中,在应变速率为0.1 s−1、变形温度≤1050℃时,出现了多峰流动曲线。流动曲线的变化是由位错积累和相互作用控制的加工硬化与动态恢复和再结晶控制的软化相互竞争的结果。在1075 ~ 1150℃的变形温度范围和0.05 ~ 0.5 s−1的应变速率范围内,试验钢具有最佳的切削性能。这一发现为优化加工条件和提高TWIP和HFS复合材料在制造和工业应用中的材料性能提供了有价值的见解。图形抽象
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来源期刊
Metals and Materials International
Metals and Materials International 工程技术-材料科学:综合
CiteScore
7.10
自引率
8.60%
发文量
197
审稿时长
3.7 months
期刊介绍: Metals and Materials International publishes original papers and occasional critical reviews on all aspects of research and technology in materials engineering: physical metallurgy, materials science, and processing of metals and other materials. Emphasis is placed on those aspects of the science of materials that are concerned with the relationships among the processing, structure and properties (mechanical, chemical, electrical, electrochemical, magnetic and optical) of materials. Aspects of processing include the melting, casting, and fabrication with the thermodynamics, kinetics and modeling.
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