Abstract: To study the relationship between the surface morphology and temperature field of oil-free magnetic drill coating with laser-melted nickel-based alloy, a finite element simulation model of temperature field on the 316L stainless steel substrate surface laser-melted with Ni60 alloy was established based on ANSYS-Workbench. The temperature field changes under different process parameters were simulated for the 316L stainless steel substrate surface laser-melted with Ni60 alloy, and the effects of different laser power, rotational period, and spot diameter on the temperature of the bonding region between the overlay and the substrate, the edge temperature of the overlay, the depth of the substrate melting pool, and the dilution rate were studied. The results show that under the conditions of laser power of 1 400 W, rotational period of 18 t and spot diameter of 1.5 mm, the depth of remelting zone(RMZ) is 0.22 mm, and the metallurgical bonding effect is best. The experimental verification method proves that the single-layer single-pass overlay surface morphology distribution is basically consistent with the molten pool simulated by finite element simulation under the optimal process parameters, which proves that the simulation model can accurately reflect the temperature field distribution in the laser cladding process.

316L stainless steel is widely used in oil drilling as a corrosion-resistant non-magnetic stainless steel [1-2]. In the harsh and complex working environment underground, the drill tool works in a harsh service environment such as high pressure, high temperature and high strength for a long time. The surface of the drill tool is very prone to fatigue cracks, eccentric wear and other failure forms [3-4], which leads to frequent replacement of drill tools, reduced drilling efficiency and increased maintenance costs [5]. At present, the methods of drill tool repair are mainly surfacing and friction welding. These welding methods are prone to thermal deformation of the welding substrate and cracks on the welding surface. Compared with traditional drill tool surface repair technologies such as surfacing and friction welding [6], laser cladding has the advantages of small laser spot diameter, high energy density, uniform and fine cladding layer structure, high metallurgical bonding strength and small thermal deformation [7-10]. Since laser cladding technology involves rapid heating and cooling [11], there is a significant temperature difference between the cladding layer and the substrate, and the molten pool temperature is difficult to measure directly. Therefore, researchers generally use numerical simulation methods to explore the temperature distribution in the process [12]. By simulating and analyzing the thermal field distribution of the molten pool during laser cladding, the melting conditions of the substrate and the coating can be judged, laying a theoretical foundation for improving the cladding quality [13]. This method can also be used to optimize laser processing parameters, improve the cladding layer morphology, improve processing efficiency and reduce production costs, which is of great value in improving cladding performance [14]. Du Maohua et al. [15] used ANSYS simulation technology to simulate and analyze the influence of process parameters on the molten pool temperature by using a three-dimensional transient model of Jianli 420 alloy powder laser cladding Q235 steel. Peng Jiahui et al. [16] used finite element simulation software to simulate the temperature field distribution law of TA-2 substrate laser cladding of Ti/h-BN alloy powder and found that the established molten pool temperature distribution was consistent with the actual cladding morphology and structure, verifying the correctness of the simulation model. Wang Lipeng et al. [17] established a laser cladding simulation model of multi-physical field coupling evolution mechanism, quantitatively revealing that the cladding temperature, liquid metal flow rate and stress are positively correlated with laser power during the cladding process. Hu Zhengqiang et al. established a temperature field simulation model of WE43 magnesium alloy laser cladding of Al-Si eutectic powder, theoretically analyzed the relationship between laser power, scanning speed and temperature of cladding coating and obtained the optimal parameters [18]. The above studies show that the combination of numerical simulation and experiment to optimize process parameters and study the application of temperature field of laser cladding in simulation analysis and experimental scheme has important research value. Therefore, this study uses Ansys-Workbench to simulate and analyze the temperature field during the cladding process, optimizes the process parameters through orthogonal test method, obtains the best process parameter combination, and analyzes the molten pool temperature distribution of the best process parameter combination. Finally, this process parameter combination is used to conduct laser cladding experiments and compared with the simulation results.

1 . Establishment of laser cladding geometric feature model

First, a three-dimensional feature model of laser cladding of shaft parts with a total length of 56.0 mm and a diameter of 38.0 mm was established in Ansys-Design Modeler. In order to make the three-dimensional feature model more consistent with the actual situation, the cladding layer was set to an ellipse with a long semi-axis of 1.5 mm and a short semi-axis of 0.8 mm, as shown in Figure 1. In order to improve the calculation efficiency and accuracy of the powder temperature rise model, the following assumptions were made on the material and simulation model during the modeling process: (1) The time domain difference between the temperature rise of Ni metal powder particles and the 316L substrate was ignored; (2) It was assumed that the laser beam was vertically irradiated on the surface of the specimen and the specimen material was continuous and homogeneous; (3) The nodes were kept in the finite element grid when the material was melted; (4) The movement of 316L stainless steel in the molten pool after liquefaction was ignored. Since the equipment used in this study was a coaxial powder feeding laser cladding machine, in order to better simulate the coaxial powder feeding cladding process, the birth and death unit technology of gradual deposition or melting was used for simulation. In the simulation of the life-and-death unit method, when the laser beam moves to a unit block, the unit block is “activated” and in a recovery state, while the unit block in the area where the laser beam does not pass is “inhibited” and in a temporary zero (killed) state, and does not participate in the metallurgical bonding process of the previous cladding material, thereby realizing a synchronous laser cladding process [19]. In the laser cladding process, the temperature in the area where the laser beam acts rises significantly, and the temperature difference fluctuates greatly, so this area needs to be divided by a fine grid. To this end, the substrate is divided into multiple areas, among which the heat-affected zone uses a small-size grid, and the remaining areas are divided using an offset factor to form a grid distribution with close proximity and far sparseness, thereby improving the calculation efficiency of the temperature field. The model uses eight-node hexahedral units for grid division, and the nodes of the substrate and the cladding layer are connected to each other. The specific size and grid division are shown in Figure 1:

1.1 Temperature field analysis theory According to the first law of thermodynamics and Fourier’s law, the three-dimensional heat transfer process in laser cladding manufacturing can be described as a nonlinear transient heat conduction control equation [200]:

Where: ρ is the material density; c is the specific heat capacity; T is the temperature; t is the time; kx, ky, kz are the thermal conductivity coefficients that vary with temperature in the x, y, and z directions; Q is the thermal power per unit volume. Before solving the heat conduction equation, the initial values and boundary conditions must be preset, specifically: The ambient temperature is set to 22 °C. The thermal convection boundary conditions are：

Where: Qs is the heat flux density; h* is the convective heat transfer coefficient; T is the solid surface temperature; T0 is the surrounding fluid temperature. The thermal radiation boundary condition is：

• Where: σ is the Stefan-Boltzmann constant; ε is the blackbody radiation coefficient; Td is the absolute temperature of the object.

Heat source model selection Based on the penetration characteristics of the laser beam, this paper uses the Gaussian body heat source model for numerical simulation, as shown in Figure 2 and formula (4)： (4) Where: P(R) is the heat source density at a distance of R from the spot radius; α is the energy absorption rate; P is the laser power; R is the spot radius;  V is the laserscanning speed.

Fig.2

Schematic diagram of Gaussian moving

body heat source

• Calculation of thermal properties of materials Before simulating the temperature field of laser cladding, the thermal physical property parameters of the cladding layer and the substrate must be determined, mainly including density, specific heat, thermal conductivity and enthalpy value, etc. The thermal property data of 316L stainless steel and Ni60 alloy were simulated and calculated by JMatPro software, as shownin Figures 3to6

Fig.3 Specific heat varies with temperature

Fig.4 Thermal conductivity varies with temperature

Fig.5 Variation of enthalpy with temperature

Fig.6 Density varies with temperature

2 Process parameter optimization

The forming quality of the cladding layer obtained by laser cladding is affected by key parameters such as laser power, scanning rate and spot diameter. The combination of laser power and axis rotation period (scanning rate) determines the density of line energy. The change of spot diameter directly affects the energy density distribution in the laser irradiation area, resulting in changes in temperature value and temperature gradient during laser cladding, which in turn affects the change of remelting zone of the molten pool. Therefore, this study uses a three-factor three-level orthogonal experimental design to perform transient temperature numerical simulation at the end of cladding, and analyzes the process parameter combination through 9 sets of numerical simulation experiments to obtain the optimal process parameters. The specific parameter configuration is detailed in Table 1. Table 1 Process parameter simulation orthogonal test table

Tab.1  Orthogonal test table for process parameter simulation

The transient thermal model in Workbench is used to solve the temperature field for the 9 different process parameter combinations in Table 1. After the solution is completed, the transient temperature cloud diagram at the end of cladding is shown in Figure 7. The melting point of the substrate 316L stainless steel used in the cladding process is about 1400℃, and the melting point of the Ni60 alloy powder is about 1000℃. It can be seen from the orthogonal experimental table that at the end of cladding, the maximum transient temperature of the edge of the cladding layer for process parameter combinations No. 1 and 2 is lower than the melting point of the powder, and the edge of the cladding layer for process parameter combination No. 4 just reaches the melting point. The parameter combinations No. 3, 5 to 8 are preliminarily selected, and further screened from the aspect of cladding layer forming quality.

The depth of the remelting zone (RMZ) directly affects the interface quality and the degree of thermal damage to the substrate. A too shallow remelting zone will cause poor bonding between the substrate and the cladding layer, and it is easy to fall off under impact; a too deep remelting zone will cause the corrosion resistance of the cladding layer to decrease, so the remelting zone needs to be reasonably regulated. Existing studies have shown that the remelting zone of the single-pass cladding of Ni60 alloy on the 316L stainless steel substrate should be controlled between 0.15 and 0.30 mm. Therefore, the process parameter combination No. 9 does not meet the test requirements. In addition, the remelting zone of the process parameter combinations No. 6 to 8 is greater than 0.30 mm, and the remelting zone of the parameter combination No. 4 is close to 0.30 mm, which should also be abandoned. Therefore, No. 3 is selected as the best process parameter combination obtained in this orthogonal test, and further research is carried out. According to the molten pool simulated by the process parameter combination No. 3 in Table 1, further analysis is carried out, and cutting is carried out along the shaft end face in the middle of the cladding layer. The schematic diagram is shown in Figure 8 below, and the morphology of the molten pool during the cladding process in the red part of the figure. It can be seen that during the laser cladding manufacturing process, the temperature of the molten pool is much higher than that of other parts of the substrate, and the high-temperature part is only concentrated in the laser spot irradiation area, and the substrate is still at room temperature 22 °C away from the laser processing area. From the scale in the figure, it can be seen that the temperature distribution in different areas with a cladding time of 1.8 s, a laser power of 1 400 W, a cycle of 60 r/min, and a spot radius of 1.5 mm is shown in Figure 9. The maximum temperature of the molten pool is 2 875 °C and the minimum temperature of the molten pool is 1 400 °C. Cutting the cross section of the cladding layer along the axial plane, the maximum temperature in the molten pool is distributed on the surface of the cladding layer, and the temperature gradually decreases as it approaches the substrate.

In order to explore the distribution characteristics of the temperature field of the molten pool, this study selected different points shown in Figure 10 for temperature measurement. The temperature distribution law shown in Figure 11 was obtained through data analysis. The results show that the temperature in the center of the molten pool is the highest and gradually decreases to both sides. This distribution feature is consistent with the heat flux density characteristics of the Gaussian heat source.

3 Comparison of laser cladding experiment and simulation

3.1 Experimental system and materials

The laser cladding test equipment mainly includes LDF-3000-60 semiconductor laser, Tongfei refrigeration water cooler, KUKA six-axis robot, coaxial fiber laser cladding head and RC-PGF-D intelligent gas-borne powder feeder. The shielding gas and powder feeding gas are both high-purity argon, the shielding gas flow rate is 20 L/min, and the powder feeding gas flow rate is 6 L/min.

The substrate material is 316L stainless steel shaft. Before the experiment, the substrate surface was fully polished with sandpaper, and then the substrate surface was cleaned with anhydrous ethanol to remove defects such as oil stains and impurity particles on the substrate surface. The cladding layer material is Ni60 high-temperature cemented carbide powder, and the powder is dried before use. The chemical composition of 316L stainless steel and Ni60 alloy is shown in Table 2 and Table 3

Table 2 Chemical composition of 316L stainless steel

Tab.2  Chemical composition of 316L

Table 3 Chemical composition of Ni60 alloy powder

Tab.3  Chemical composition of Ni60

3.2  Experiment and simulation comparison

A 316L stainless steel shaft part with a length of 56 mm and a diameter of Φ38 mm was cut using a wire cutting machine, and a single-layer single-pass laser cladding experiment was performed using a laser power of 1 400 W, a spot radius of 1.5 mm, and a shaft rotation period of 60 r/min. After the experiment, the cross section of the cladding layer was cut using a wire cutting machine, and the cross section was etched using a 4% nitric acid alcohol solution. After the etching was completed, the cross-sectional morphology of the cladding layer was observed using a 39x optical microscope as shown in Figure 12. It can be seen that the cross-sectional forming state of the cladding layer is good without obvious defects.

Figure 13 is a morphology comparison between finite element simulation and experimental measurement. It can be seen that the morphology and size of the finite element simulation and experimental measurement are highly consistent, which verifies the accuracy of the simulation model. Based on this, the use of finite element simulation can effectively optimize the forming quality of the cladding layer, reduce production costs, and improve the efficiency of laser cladding technology in engineering applications.

4 Conclusions

(1) A three-factor three-level orthogonal test was conducted to simulate laser cladding under different process parameter combinations. The temperature distribution in the molten pool was used to obtain the melting state of the cladding layer and the substrate. Considering the melting state of the cladding layer and the depth of the remelting zone, the optimal process parameter combination was finally selected as follows: laser power 1 400 W, spot radius 1.5 mm and shaft rotation period 60 r/min.

(2) By further analyzing the temperature distribution cloud map under the obtained process parameter combination, it was found that the maximum temperature of the molten pool was 2 875 ℃ and the minimum temperature of the molten pool was 1 400 ℃. The temperature in the center of the molten pool was the highest and gradually decreased toward both sides. This distribution feature is consistent with the heat flux density characteristics of the Gaussian heat source.

(3) A 316L stainless steel shaft part with a length of 56.0 mm and a diameter of 38.0 mm was cut using a wire cutting machine for cladding experiments. The cross-sectional morphology of the cladding layer was observed and it was found that its forming state was good without obvious defects. The experimental results were compared with the simulation results, and it was found that the morphological dimensions of the finite element simulation and the experimental measurement were highly consistent, verifying the accuracy of the simulation model.