Experimental and Numerical Investigations on Solidification Thermodynamics of H13 Steel with Multi components

Tengfei Luo, Weiling Wang, Tingrui Shang, Hongliang Liu, Sen Luo, Miaoyong Zhu
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Abstract

Thermodynamic data is of great significance to investigate the formation and control mechanisms of solidification defects during the casting process of H13 steel which is high in Si, Cr, Mo, and V elements. It has been proven that the conventional Ueshima model based on the equilibrium phase diagrams of Fe-X (X = C, Si, Mn, P, S, Cr, Mo, and V) binary alloys cannot accurately predict the phase transition in the solidification of H13 steel with multi components. So, the pseudo-binary phase diagrams of Fe-X alloys at different initial concentrations were calculated via Thermo-Calc software. And, the datasets of liquidus and δ/γ phase transition temperatures were obtained. Then, a backpropagation (BP) neural network model was developed to predict the δ/γ phase transition temperature. While, the slopes of liquidus lines were fitted. These updates were implanted into the Ueshima model. And, the BP-Ueshima model was validated with the phase transition temperatures measured via the differential scanning calorimetry (DSC) test. Subsequently, the phase transition and solute micro-segregation behaviors in the solidification of H13 steel were analyzed as well as the influences of solute elements. The results show that the predicted liquidus temperature (TL) and solidus temperature (TS) of H13 steel via BP-Ueshima model agree with the experimental results. As the cooling rate increases from 10 to 20 °C/min, the phase transition temperatures change slightly. Both the solidus and liquidus temperatures decrease with increase of the initial contents of solute elements. Increasing the initial contents of C and Mn can enhance TP and Tδ (the vanishing temperature of δ phase), whereas the trend is reversed for the other solute elements. Changes of the phase transition temperatures depends on the segregation behaviors of solute elements. The micro-segregation ratios of solute elements in the liquid phase at the end of solidification decreases in the order of S, P, Si, Mo, C, V, Mn, and Cr, respectively. It is determined by the redistributive capacity at the solid/liquid interface and the back diffusion in the solid phase of solute elements.

Abstract Image

多成分 H13 钢凝固热力学的实验和数值研究
热力学数据对于研究含硅、铬、钼和钒元素较多的 H13 钢在铸造过程中凝固缺陷的形成和控制机制具有重要意义。实践证明,基于 Fe-X(X = C、Si、Mn、P、S、Cr、Mo 和 V)二元合金平衡相图的传统 Ueshima 模型无法准确预测多组分 H13 钢凝固过程中的相变。因此,通过 Thermo-Calc 软件计算了不同初始浓度下 Fe-X 合金的伪二元相图。并获得了液相和δ/γ 相变温度数据集。然后,建立了一个反向传播(BP)神经网络模型来预测δ/γ 相变温度。同时,对液相线的斜率进行了拟合。这些更新被植入上岛模型。然后,通过差示扫描量热法(DSC)测试测得的相变温度验证了 BP-Ueshima 模型。随后,分析了 H13 钢凝固过程中的相变和溶质微偏析行为以及溶质元素的影响。结果表明,通过 BP-Ueshima 模型预测的 H13 钢的液相温度(TL)和固相温度(TS)与实验结果一致。随着冷却速度从 10 ℃/min 增加到 20 ℃/min,相变温度略有变化。固相温度和液相温度都随着溶质元素初始含量的增加而降低。增加 C 和 Mn 的初始含量可提高 TP 和 Tδ(δ 相的消失温度),而其他溶质元素的趋势则相反。相变温度的变化取决于溶质元素的偏析行为。凝固末期液相中溶质元素的微偏析比依次为 S、P、Si、Mo、C、V、Mn 和 Cr。这取决于固/液界面的再分布能力和溶质元素在固相中的反向扩散。
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