## 1 Introduction  
Selective laser melting (SLM) is one of the important additive manufacturing technologies for metals. It can realize the forming of parts with complex structures through layer-by-layer powder spreading, laser beam melting and solidification [1]. In the performance evaluation of metal additive manufacturing products, internal quality, surface quality, internal stress and forming dimensional accuracy are very important indicators. However, the characteristics of organization and defects are different from traditional metal parts, traditional methods for predicting and detecting internal defects of metal parts cannot be applied to metal additive manufacturing parts. At present, additive manufacturing still has great challenges in terms of stability and consistency. Therefore, how to obtain defect-free high-quality parts is a major technical challenge. Experimental and numerical simulation research methods have been used by many researchers to discuss defect forming mechanism, prediction methods and control strategies. A very complicated thermal physical interaction process is contained in the SLM process. Understanding the characteristics of a temperature field is very helpful for selecting reasonable process parameters to control the forming quality of the material. However, due to the very small size of the powders and the very short phase transition time, it is difficult to obtain a better analysis and observation effect of the process by simple experimental methods. In order to ensure the printing quality, it is a very effective method to use numerical simulation analysis methods to observe the configuration and temperature field of the melt pool and optimize process parameters. The size of the melt pool is very important for the forming of the alloy. During the processing of SLM, the laser will quickly melt the metal powder into liquid metal to form a melt pool. If the scanning heat input parameters are set improperly, defects such as pores will appear in the final formed part, and the shape and flow of the melt pool are closely related to the setting of the process parameters. The appropriate melt pool size can largely reduce the occurrence of defects in formed parts. For modelling the melt pool, computational fluid dynamics (CFD) is the most widely used method, in which finite element method (FEM) [2] or finite volume method (FVM) [3] approaches are applied [4]. [PERSON] et al. [5] found that the increase in laser power or the decrease in scanning rate will cause the temperature in the melt pool to increase, and the size of the melt pool will increase accordingly by combining simulation and experiment. In the SLM process, the surface tension caused by the temperature gradient has an important influence on the shape distribution and evolution of the melt pool. [PERSON] et al. [6] established a three-dimensional finite element model of SLM IN718 and found that the Marangoni effect driven by surface tension makes the fluid in the melt pool mainly convection outward. [PERSON] et al. [7] found that when the laser scanning speed (the laser power is 200 W, laser beam radius is 35 \(\upmu\)m) is above 1.3 m/s, the melt pool is in an unstable state and a large number of ball defects will be generated. In the interval of 0.8 m/s-1.3 m/s, the melt pool is in a transitional state, and it is prone to necking defects. When the speed drops to the interval of 0.3 m/s-0.8 m/s, the melt pool is in a stable state and has a concave feature. [PERSON] and [PERSON] et al. [8] analyzed the influence of recoil pressure under different laser parameters on the temperature field and velocity field of the melt pool. Taking 316 L stainless steel powder as the study object, through numerical simulation and experimental research, it is finally found that during the laser scanning process, the surface tension and recoil pressure have reached a dynamic balance, and the depression produced by the melt pool will be continuously filled.