溶质再分配系数对激光熔覆溶质分布的影响

Effect of Solute Redistribution Coefficient on Solute Distribution in Laser Cladding

为了提高沉积层溶质分布的预测精度,研究溶质再分配系数对沉积层溶质分布的影响机制,本研究团队将体积平均法和非平衡溶质再分配系数计算方法相结合,分别建立动态溶质再分配系数凝固模型和恒定溶质再分配系数凝固模型,模拟45钢表面316L不锈钢涂层的激光熔覆过程,分析熔覆过程中的流动、传热和传质现象。结果表明:两种模型预测的温度场分布、熔池形貌、熔池流场等结果的差异性并不明显,但在元素分布方面,动态溶质再分配系数凝固模型的误差更小,更接近实验结果。分析后认为,溶质再分配系数在沉积层溶质分布过程中起主导控制作用,动态溶质再分配系数更接近真实的熔池凝固过程,从而使预测准确性更高。

Objective Laser cladding technology, which is the foundation of laser remanufacturing technology, can improve the wear resistance, corrosion resistance, high-temperature resistance, and other properties of the substrate surface. However, the experimental method requires a significant amount of time and energy to optimize the parameters of laser cladding, and numerical simulation provides an efficient way to study such a complex physical phenomena. Moreover, laser cladding is a non-equilibrium solidification process, but most of the numerical simulations have neglected it. This study demonstrates a three-phase solidification model based on the volume-averaged method and investigates the influence of the solute redistribution coefficient on the solute distribution in the deposition layer during non-equilibrium solidification. Additionally, accurate prediction of the solute distribution on the deposition layer has also been presented in this study during the laser cladding.Methods A three-phase solidification model based on the volume-averaged method is established in this study, with considerations of non-equilibrium dynamic solute redistribution coefficient and constant solute redistribution coefficient. Both models investigate the laser cladding of 316 L stainless steel powder on 45 steel substrates. The experimental results on the geometrical morphology and chromium concentration of the cladding layer validate the numerical results. By comparing the temperature field, flow field, and solute field of the two models, the influence of the solute redistribution coefficient on the cladding process during non-equilibrium solidification is explored;furthermore, whether the dynamic solute redistribution coefficient should be considered in the solidification model is determined by comparing the prediction accuracy of chromium concentration between the two solidification models.Results and Discussions In this paper, the mass of element mesh diffusion is used to calculate the relatively accurate moving velocity of the solid-liquid interface, and the dynamic solute redistribution coefficient is calculated accordingly(Fig. 2). The solute redistribution coefficient in the laser cladding process is greater than the constant solute redistribution coefficient(Fig. 7). The geometrical morphologies of the cladding layer are obtained by using the two solidification models, which are in good agreement with the experimental data(Fig. 6). At the same time point, the temperature(Fig. 5) and flow fields(Fig. 8) of the two solidification models are identical. In the molten pools of the two solidification models, there are clockwise and counter-clockwise vortices and the chromium element in the powder diffuses to all parts of the cladding layer due to the vortices’ action. Moreover, the solute distribution in the deposition layer obtained by the two solidification model’s simulation is compared with the experimental data which shows that the content of chromium element in both the models decreases from above to below(Fig. 9 and Fig. 10). The dynamic solute redistribution coefficient, on the other hand, is more consistent with the experimental solidification process, the most absolute errors between the simulation results of the solidification model with dynamic solute redistribution coefficient and the experimental data are within 0.5%(Fig. 11), and the element segregation phenomenon is more obvious and closer to the experimental data(Fig. 12).Conclusions A three-phase solidification model based on the volume-averaged method with considerations of nonequilibrium dynamic solute redistribution coefficient and constant solute redistribution coefficient is established. The morphologies of the temperature field and flow field are the same when compared to the simulation results of the two solidification models, as is the variation trend of solute field concentration. However, the dynamic solute redistribution coefficient solidification model predicts the solute distribution in the deposition layer with less error and is closer to the experimental data. In the laser cladding process, the solidification rate of the molten pool varies with the change in the solute redistribution coefficient, which leads to the instability of the solute distribution process and obvious element segregation. Our findings indicate that the dynamic solute redistribution coefficient has a significant impact on solute distribution in the deposition layer. To more accurately predict the solute distribution in the deposition layer, the change in the solute redistribution coefficient should be considered in the laser cladding process simulation.