Simulation method for metal matrix surface layer grain refinement based on pulse laser cleaning

Abstract

The invention provides a simulation method for metal matrix surface layer grain refinement based on pulse laser cleaning. The simulation method comprises the following steps that a finite element model of a metal material is established through UG three-dimensional modeling software; setting the finite element model into an IGS format, importing the finite element model into Procast, and constructing a grain growth simulation environment of the metal material geometric model; performing grid division on the metal material geometric model; setting material parameters of the metal material geometric model; introducing a pulse laser heat source to establish a heat source model; initial conditions and boundary conditions of the metal material geometric model are set, and the change condition of the grain size after simulation is completed is analyzed through a Procast post-processing # imgabs0 # module. The method has the technical effect that the method is suitable for numerical simulation of grain refinement distribution on the surface layer of the pulse laser cleaning metal matrix.

Description

Technical Field

[0001] The invention belongs to the technical field of laser cleaning of metal material surfaces, and in particular relates to a simulation method for grain refinement of a metal substrate surface layer based on pulse laser cleaning. Background Art

[0002] In recent years, pulse laser cleaning technology has been widely used in the field of metal surface treatment due to its high efficiency, environmental protection, and non-contact characteristics. A large number of researchers have proved that pulse laser cleaning can not only effectively remove pollutants such as oxide layers, paint, and grease on the metal surface by properly adjusting process parameters such as laser power, scanning speed, and spot size, but also improve the microstructure of the metal material surface through local heating, thereby improving the physical and chemical properties of the material.

[0003] Although pulsed laser cleaning technology performs well in the metal surface cleaning process, there is a lack of systematic research in the field of analysis and regulation of the impact on the metal matrix, especially the impact and law of laser cleaning parameters on the grain size of the substrate surface. Therefore, it is necessary to find a method to analyze the impact of laser cleaning process parameters on the grain size of the metal substrate surface to guide the optimization of the laser cleaning process. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art and provide a new technical solution for a simulation method of grain refinement of the surface layer of a metal substrate by pulsed laser cleaning.

[0005] According to one aspect of the present invention, a simulation method for grain refinement of a metal substrate surface layer based on pulsed laser cleaning is provided, comprising the following steps:

[0006] Step S100, establishing a finite element model of the metal material by using UG three-dimensional modeling software;

[0007] Step S200, setting the finite element model in IGS format and importing it into Procast to construct a grain growth simulation environment for the metal material geometry model;

[0008] Step S300, meshing the geometric model of the metal material;

[0009] Step S400, setting material parameters of a metal material geometric model;

[0010] Step S500, introducing a pulsed laser heat source to establish a heat source model;

[0011] Step S600, setting the initial conditions and boundary conditions of the metal material geometric model, and The module analyzes the change in grain size after the simulation is completed.

[0012] Optionally, in step S200, the size of the metal material geometric model is 100 mm×100 mm×30 mm.

[0013] Optionally, in step S300, a meshing method of tetrahedral units and surface meshes is adopted, and the minimum unit size is 2 mm.

[0014] Optionally, in step S400, the material parameters of the metal material geometric model include chemical element content, Young's modulus, Poisson's ratio, thermal expansion coefficient, thermal conductivity, yield stress and growth kinetics parameters.

[0015] Optionally, in step S500, a uniformly distributed heat flux density is introduced on the upper surface of the metal material geometric model as a laser heat source model.

[0016] Optionally, in step S500, Pressure is introduced on the upper surface of the metal material geometric model as a shock wave pressure heat source model.

[0017] Optionally, Pressure is introduced on the upper surface of the metal material geometry model as a shock wave pressure heat source model, specifically:

[0018] The shock wave pressure generated by the laser during laser cleaning will affect the change in grain size. The grain size is determined according to the shock wave pressure P, and the shock wave pressure P is calculated using the following formula:

[0019]

[0020] In the above formula, P max is the maximum shock wave pressure when the laser shock ends; α is the internal energy distribution coefficient; Z is the sum of the acoustic impedance of the confinement layer and the metal material; I0 is the theoretical maximum laser power, and the calculation formula is as follows:

[0021]

[0022] In the above formula, β is the absorption coefficient of the metal material to the pulse laser; E is the energy of the laser pulse, in joules; τ is the pulse width, in seconds; A is the area of ​​the spot, in m 2 .

[0023] Optionally, in step S600, the initial conditions of the metal material geometric model include material type, initial temperature and nucleation area.

[0024] Optionally, in step S600, the boundary conditions of the metal material geometric model include cooling conditions, body nucleation conditions and surface nucleation conditions.

[0025] Optionally, the finite element model of the metal material is a three-dimensional grain refinement model.

[0026] A technical effect of the present invention is:

[0027] In an embodiment of the present application, the simulation method for grain refinement of the surface layer of a metal substrate by pulsed laser cleaning utilizes Procast simulation software to customize the laser loading heat source and plan the laser distribution area. It is suitable for numerical simulation of grain refinement distribution of the surface layer of a metal substrate by pulsed laser cleaning. It can not only visualize and quantitatively analyze the effects of different laser powers, pulse widths, spot diameters, and different cooling methods on grain refinement effects, but also can guide the optimization experiment of the process parameters for grain refinement of metal materials during laser cleaning. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic flow chart of a simulation method for grain refinement of a metal substrate surface layer based on pulsed laser cleaning according to an embodiment of the present invention;

[0029] Figure 2 Grid diagram of geometric model division and laser distribution diagram in Procast numerical simulation;

[0030] Figure 3 A graph showing the change of grain size with distance under different convective heat transfer coefficient cooling methods according to an embodiment of the present invention;

[0031] Figure 4 This is a graph showing the change of grain size with distance under different laser powers according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present application.

[0033] The embodiments of the present application will be described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and should not be construed as limitations on the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0034] According to one aspect of the present invention, a simulation method for grain refinement of a metal substrate surface layer based on pulsed laser cleaning is provided, comprising the following steps:

[0035] Step S100, establishing a finite element model of the metal material by using UG three-dimensional modeling software;

[0036] Step S200, setting the finite element model in IGS format and importing it into Procast to construct a grain growth simulation environment for the metal material geometry model;

[0037] Step S300, meshing the geometric model of the metal material;

[0038] Step S400, setting material parameters of a metal material geometric model;

[0039] Step S500, introducing a pulsed laser heat source to establish a heat source model;

[0040] Step S600, setting the initial conditions and boundary conditions of the metal material geometric model, and The module analyzes the change in grain size after the simulation is completed.

[0041] In an embodiment of the present application, the simulation method for grain refinement of the surface layer of a metal substrate by pulsed laser cleaning utilizes Procast simulation software to customize the laser loading heat source and plan the laser distribution area. It is suitable for numerical simulation of grain refinement distribution of the surface layer of a metal substrate by pulsed laser cleaning. It can not only visualize and quantitatively analyze the effects of different laser powers, pulse widths, spot diameters, and different cooling methods on grain refinement effects, but also can guide the optimization experiment of the process parameters for grain refinement of metal materials during laser cleaning.

[0042] Optionally, in step S200, the size of the metal material geometric model is 100 mm×100 mm×30 mm, which helps to accurately construct a grain growth simulation environment of the metal material geometric model.

[0043] Optionally, in step S300, a meshing method of tetrahedral units and surface meshes is adopted, and the minimum unit size is 2 mm, which is helpful to realize meshing of the geometric model of metal materials.

[0044] Optionally, in step S400, the material parameters of the metal material geometric model include chemical element content, Young's modulus, Poisson's ratio, thermal expansion coefficient, thermal conductivity, yield stress and growth kinetics parameters, which helps to comprehensively and accurately set the material parameters of the metal material geometric model.

[0045] Optionally, in step S500, a uniformly distributed heat flux density is introduced on the upper surface of the metal material geometric model as a laser heat source model.

[0046] Optionally, in step S500, Pressure is introduced on the upper surface of the metal material geometric model as a shock wave pressure heat source model.

[0047] Optionally, Pressure is introduced on the upper surface of the metal material geometry model as a shock wave pressure heat source model, specifically:

[0048] The shock wave pressure generated by the laser during laser cleaning will affect the change in grain size. The grain size is determined according to the shock wave pressure P, and the shock wave pressure P is calculated using the following formula:

[0049]

[0050] In the above formula, P max is the maximum shock wave pressure when the laser shock ends; α is the internal energy distribution coefficient; Z is the sum of the acoustic impedance of the confinement layer and the metal material; I0 is the theoretical maximum laser power, and the calculation formula is as follows:

[0051]

[0052] In the above formula, β is the absorption coefficient of the metal material to the pulse laser; E is the energy of the laser pulse, in joules; τ is the pulse width, in seconds; A is the area of ​​the spot, in m 2 .

[0053] The above implementation method is helpful for accurate simulation of grain refinement of the surface layer of a metal substrate cleaned by pulsed laser.

[0054] Optionally, in step S600, the initial conditions of the metal material geometric model include material type, initial temperature and nucleation area. This helps to The module accurately analyzes how the grain size changes after the simulation is completed.

[0055] Optionally, in step S600, the boundary conditions of the metal material geometric model include cooling conditions, body nucleation conditions and surface nucleation conditions. This helps to The module accurately analyzes how the grain size changes after the simulation is completed.

[0056] Optionally, the finite element model of the metal material is a three-dimensional grain refinement model. Exemplarily, the three-dimensional grain refinement model is a three-dimensional laser surface treatment metal material surface grain growth model.

[0057] In a specific implementation, see Figure 1 The simulation method for grain refinement of the surface layer of a metal matrix by pulsed laser cleaning comprises the following steps:

[0058] (1) Establish a three-dimensional grain refinement model;

[0059] Select the model plate through UG software and select the sketch function; select the xy plane design model with a length of 100mm and a width of 100mm. Use the stretching function to extend 30mm along the z-axis direction to set a rectangular block with a size of 100mm×100mm×30mm.

[0060] (2) Model import;

[0061] The finite element model was set to IGS format and imported into Procast software.

[0062] (3) Grid division;

[0063] See also Figure 2 , which is a mesh diagram for dividing the geometric model of metal materials in the present invention. In the Mesh module of Procast, the surface connectivity problem is first detected and repaired. Using the surface mesh function, the minimum unit size is set to 2mm and applied to the entire substrate surface, resulting in 18836 units. Then, after the division is completed, the surface mesh is detected and corrected. Next, choose to create a volume mesh to ensure calculation accuracy, discretize the three-dimensional geometric model into tetrahedral units, a total of 187755, and create 26884 new nodes.

[0064] (4) Material parameter setting;

[0065] The material of the metal material geometry model is TC4 titanium alloy, and its specific parameters include chemical element content, Young's modulus, Poisson's ratio, thermal expansion coefficient, thermal conductivity, yield stress and growth kinetics parameters.

[0066] (5) Establishment of laser heat flux density heat source model;

[0067] Select the Cast module of Procast, and in the process condition manager, select Heatflux as the laser heat flux density. The specific parameters are shown in Table 1. Apply it on the upper surface of the substrate in a uniform distribution manner.

[0068] Table 1

[0069]

[0070] (6) Establishment of shock wave pressure model;

[0071] During the laser cleaning process, shock wave pressure is generated. Theoretically, the expression of shock wave pressure P is:

[0072]

[0073] In the above formula, P maxis the maximum shock wave pressure when the laser shock ends; α is the internal energy distribution coefficient, which is usually taken as 0.2; Z is the sum of the acoustic impedances of the confinement layer and the metal material, and the acoustic impedance of water is 0.165×10 6 g cm -2 ·s -1 , the acoustic impedance of metal materials is 2.41×10 6 g cm -2 ·s -1 ; I0 is the theoretical maximum value of laser power, and the calculation formula is as follows:

[0074]

[0075] In the above formula, β is the absorption coefficient of metal material to pulse laser, which is taken as 0.42 here; E is the energy of laser pulse, in joule (J); τ is the pulse width, in seconds (s); A is the area of ​​the spot, in m 2 .

[0076] Exemplarily, the laser power is set to 12W, 18W, 24W, 30W, 36W, and 42W.

[0077] (7) Setting the initial conditions of the material;

[0078] In the Cast module of Procast, select Volume Manager, select Alloy as the material type, select 1700℃ for the initial temperature, and open Unit, select 100% for the coverage area Fill. The calculated matrix mass is 1.35Kg. Select Calculation Zone in the left toolbar of the Procast software to add the material nucleation area. Set the maximum X to 100, the maximum Y to -100, and the minimum Z to -30.

[0079] (8) Set the boundary conditions of the material;

[0080] In the Cast module of Procast, select the process condition manager and add two cooling conditions: air cooling and water cooling. Select the bottom surface and four side surfaces of the substrate as the cooling area. The specific parameters are shown in Table 2. Add the surface nucleation condition parameters on the substrate and add the body nucleation condition parameters on the entire substrate surface. The specific parameters are shown in Tables 3 and 4.

[0081] Table 2

[0082]

[0083] Table 3

[0084]

[0085] Table 4

[0086]

[0087] (9) Analysis of simulation results;

[0088] like Figure 3 As shown in FIG. 1 , it is a curve diagram of the change of grain size with distance under the air cooling condition designed by the present invention. As can be seen from the figure, with the increase of the convective heat transfer coefficient, the grain size increases first and then decreases. When the convective heat transfer coefficient is 10W / (m2·k), the grain size is the smallest.

[0089] like Figure 4 The figure shows the variation curve of grain size with distance under different laser powers designed by the present invention. The air cooling method is selected, and the convection heat transfer coefficient is 100W / (m 2 |k), the ambient temperature is 25℃. As can be seen from the figure, the effect of laser power on grain size is nonlinear. When the laser power is 18W, the grain refinement effect is the best.

[0090] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A simulation method for grain refinement of metal substrate surface by pulsed laser cleaning, characterized in that: The steps include: Step S100, establishing a finite element model of the metal material by using UG three-dimensional modeling software; Step S200, setting the finite element model in IGS format and importing it into Procast to construct a grain growth simulation environment for the metal material geometry model; Step S300, meshing the geometric model of the metal material; Step S400, setting material parameters of a metal material geometric model; Step S500, introducing a pulsed laser heat source to establish a heat source model; Step S600, setting the initial conditions and boundary conditions of the metal material geometric model, and The module analyzes the change in grain size after the simulation is completed.

2. The simulation method for grain refinement of the surface layer of a metal substrate based on pulsed laser cleaning according to claim 1 is characterized in that: In step S200, the size of the metal material geometric model is 100 mm×100 mm×30 mm.

3. The simulation method for grain refinement of the surface layer of a metal substrate based on pulsed laser cleaning according to claim 1, characterized in that: In step S300, a meshing method of tetrahedral units and surface meshes is adopted, and the minimum unit size is 2 mm.

4. The simulation method for grain refinement of the surface layer of a metal substrate based on pulsed laser cleaning according to claim 1, characterized in that: In step S400 , the material parameters of the metal material geometric model include chemical element content, Young's modulus, Poisson's ratio, thermal expansion coefficient, thermal conductivity, yield stress, and growth kinetics parameters.

5. The simulation method for grain refinement of the surface layer of a metal substrate based on pulsed laser cleaning according to claim 1, characterized in that: In step S500, a uniformly distributed heat flux density is introduced on the upper surface of the metal material geometric model as a laser heat source model.

6. The simulation method for grain refinement of the surface layer of a metal substrate based on pulsed laser cleaning according to claim 1, characterized in that: In step S500, Pressure is introduced on the upper surface of the metal material geometric model as a shock wave pressure heat source model.

7. The method for simulating grain refinement of the surface layer of a metal substrate by pulsed laser cleaning according to claim 6, characterized in that: Pressure is introduced on the surface of the metal material geometry model as the shock wave pressure heat source model, specifically: The shock wave pressure generated by the laser during laser cleaning will affect the change in grain size. The grain size is determined according to the shock wave pressure P, and the shock wave pressure P is calculated using the following formula: In the above formula, P max is the maximum shock wave pressure when the laser shock ends; α is the internal energy distribution coefficient; Z is the sum of the acoustic impedance of the confinement layer and the metal material; I0 is the theoretical maximum laser power, and the calculation formula is as follows: In the above formula, β is the absorption coefficient of the metal material to the pulse laser; E is the energy of the laser pulse, in joules; τ is the pulse width, in seconds; A is the area of ​​the spot, in m 2 .

8. The method for simulating grain refinement of the surface layer of a metal substrate by pulsed laser cleaning according to claim 1, characterized in that: In step S600, the initial conditions of the metal material geometric model include material type, initial temperature and nucleation area.

9. The simulation method for grain refinement of the surface layer of a metal substrate based on pulsed laser cleaning according to claim 1, characterized in that: In step S600, the boundary conditions of the metal material geometric model include cooling conditions, body nucleation conditions and surface nucleation conditions.

10. The simulation method for grain refinement of the surface layer of a metal substrate based on pulsed laser cleaning according to claim 1, characterized in that: The finite element model of the metal material is a three-dimensional grain refinement model.

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