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Mingjie Zhao, Lihong Jiang, Changmin Li, Liang Huang, Chaoyuan Sun, Jianjun Li, and Zhenghua Guo, Flow characteristics and hot workability of a typical low-alloy high-strength steel during multi-pass deformation, Int. J. Miner. Metall. Mater., 31(2024), No. 2, pp.323-336. https://dx.doi.org/10.1007/s12613-023-2736-0
Mingjie Zhao, Lihong Jiang, Changmin Li, Liang Huang, Chaoyuan Sun, Jianjun Li, and Zhenghua Guo, Flow characteristics and hot workability of a typical low-alloy high-strength steel during multi-pass deformation, Int. J. Miner. Metall. Mater., 31(2024), No. 2, pp.323-336. https://dx.doi.org/10.1007/s12613-023-2736-0
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一种典型的低合金高强钢多道次变形过程的流动特性及热加工性能

摘要: 由于低合金高强钢大型构件一般采用多道次锻造成形,为了能够更好制定实际锻造工艺参数,有必要围绕低合金高强钢多道次变形过程的流动特性及热加工性能开展研究。在本研究中,对一种典型的低合金高强钢在较宽的变形温度和应变速率下进行了多道次热压缩实验。基于流动行为分析发现,材料的加工硬化速率与变形参数和变形道次有关,这主要归因于动态软化及静态软化的影响。为了实现对不同变形道次下流动行为的准确预测,提出了一个新的本构模型,将其预测精度与经典的Arrhenius本构模型和修正的ZA本构模型相比发现,新提出的本构模型具有更高的预测精度,置信水平为0.98565。基于微观组织分析,揭示了材料功耗效率与变形参数之间的关系,发现功率耗散效率不能反映整个变形过程中微观组织演化情况,而只能评估特定变形参数状态下的微观组织演化。为此,本文提出了一种新的集成热加工图,该图考虑了失稳因子、功率耗散效率以及晶粒分布和尺寸的影响。基于该热加工图,优化出低合金高强钢多道次变形的工艺参数为1223–1318 K和0.01–0.08 s−1。在优化的工艺参数范围内动态再结晶完全,平均晶粒尺寸为18.36–42.3 μm。上述研究为大型构件实际锻造成形过程工艺参数的制定提供重要的理论指导。

 

Flow characteristics and hot workability of a typical low-alloy high-strength steel during multi-pass deformation

Abstract: Heavy components of low-alloy high-strength (LAHS) steels are generally formed by multi-pass forging. It is necessary to explore the flow characteristics and hot workability of LAHS steels during the multi-pass forging process, which is beneficial to the formulation of actual processing parameters. In the study, the multi-pass hot compression experiments of a typical LAHS steel are carried out at a wide range of deformation temperatures and strain rates. It is found that the work hardening rate of the experimental material depends on deformation parameters and deformation passes, which is ascribed to the impacts of static and dynamic softening behaviors. A new model is established to describe the flow characteristics at various deformation passes. Compared to the classical Arrhenius model and modified Zerilli and Armstrong model, the newly proposed model shows higher prediction accuracy with a confidence level of 0.98565. Furthermore, the connection between power dissipation efficiency (PDE) and deformation parameters is revealed by analyzing the microstructures. The PDE cannot be utilized to reflect the efficiency of energy dissipation for microstructure evolution during the entire deformation process, but only to assess the efficiency of energy dissipation for microstructure evolution in a specific deformation parameter state. As a result, an integrated processing map is proposed to better study the hot workability of the LAHS steel, which considers the effects of instability factor (IF), PDE, and distribution and size of grains. The optimized processing parameters for the multi-pass deformation process are the deformation parameters of 1223–1318 K and 0.01–0.08 s−1. Complete dynamic recrystallization occurs within the optimized processing parameters with an average grain size of 18.36–42.3 μm. This study will guide the optimization of the forging process of heavy components.

 

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