A simulation method and system for the temperature field and stress field of a material irradiated by short-pulse laser

Abstract

The present invention belongs to the technical field of the interaction between laser and matter, and relates to a simulation method and system for the temperature field and stress field of a material irradiated by short-pulse laser. The simulation method includes: determining simulation parameters, including short-pulse laser irradiation parameters and material property parameters; constructing a thermo-mechanical coupling transient model of the material, and determining the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the model; performing grid division on the thermo-mechanical coupling transient model, and configuring solver parameters; specifically: inputting the short-pulse laser pulse width and the short-pulse laser frequency into a pre-trained linear neural network model, and calculating to obtain the solver parameters; applying the solver to solve the thermo-mechanical coupling transient model to obtain the temperature field and stress field distribution of the material at different irradiation times. The simulation method of the present invention can comprehensively and accurately capture the complex transient physical process of the material under the action of short-pulse laser.

Description

Technical Field

[0001] The present invention relates to the technical field of laser-matter interaction, and particularly to a simulation method and system for the temperature field and stress field of a material irradiated by a short-pulse laser. Background Art

[0002] In the technical field of laser-matter interaction, when a short-pulse laser irradiates a material, due to the high power density of the short-pulse laser, effective ablation of the material can be achieved. Therefore, short-pulse lasers have extensive applications in laser processing, laser damage, and other aspects.

[0003] Generally, by controlling laser parameters such as pulse width, spot radius, laser energy, etc., effective control of the material ablation effect can be achieved, such as ablation depth, ablation quality, ablation area, etc. The temperature field and stress field are two key physical quantities that can reflect the specific situation of material laser ablation. By monitoring the temperature field and stress field, a basis can be provided for optimizing the design scheme of laser irradiation ablation parameters, and thus the purpose of controlling the ablation effect can be achieved.

[0004] However, in the numerical simulation of a material irradiated by a high-energy short-pulse laser (energy density ≥ , pulse width ≤ 500 ns), the conventional finite element simulation method faces significant technical bottlenecks. Since this process involves ultrafast energy deposition (time scale order of magnitude) and extreme thermo-mechanical coupling effects (temperature gradient > , strain rate > ), using the default solver parameters of COMSOL will lead to the following problems: First, the adaptive time step control strategy is designed based on conventional thermodynamic processes, and it is prone to generate too large time steps in the transient response stage, unable to accurately capture the precise changes in physical properties; second, a smaller time step strategy is prone to lead to a huge amount of computation; how to balance the fine physical properties in the transient response stage while reducing the computation amount in the subsequent relaxation stage requires optimizing the parameters of the solver, so as to better obtain the temperature field and stress field results of the material irradiated by the short-pulse laser. Summary of the Invention

[0005] The purpose of the present invention is to optimize the laser parameter design to accurately obtain the laser irradiation material effects under various conditions, and a simulation method and system for the temperature field and stress field of a material irradiated by a short-pulse laser are proposed. The complex physical processes such as heat conduction inside the material, convective heat transfer between the surface and the environment, and thermal expansion of the material under the action of the short-pulse laser are analyzed to obtain the temperature field and stress field distributions of the material under the irradiation of the short-pulse laser.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a simulation method for the temperature field and stress field of a material irradiated by a short-pulse laser. The simulation method includes the following steps:

[0008] Determine the simulation parameters, including short-pulse laser irradiation parameters and material property parameters;

[0009] Construct a thermo-mechanical coupling transient model of the material, and determine the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the thermo-mechanical coupling transient model;

[0010] Based on the heat transfer physical field and the solid mechanics physical field, perform grid division on the thermo-mechanical coupling transient model, and configure the solver parameters; the solver parameters include the initial step size, the maximum step size constraint, and the time step for storing the results of one calculation; the solver parameters are determined by applying a pre-trained linear neural network model. Specifically: input the short-pulse laser pulse width and the short-pulse laser frequency into the pre-trained linear neural network model, and use the calculation expression of the pre-trained linear neural network model to calculate and obtain the solver parameters;

[0011] Apply the solver to solve the thermo-mechanical coupling transient model to obtain the temperature field and stress field distribution of the material at different irradiation times.

[0012] As a possible implementation, the pre-trained linear neural network model includes an input layer and an output layer; among them, the parameters of the input layer include a short-pulse laser pulse width node and a short-pulse laser frequency node; the parameters of the output layer include an initial step size node, a maximum step size constraint node, and a time step for storing the results of one calculation node.

[0013] As a possible implementation, the calculation expression of the pre-trained linear neural network model is:

[0014] ;

[0015] Among them, is the weight matrix, ; is the bias vector, ; is the initial step size; is the time step for storing the results of one calculation; is the maximum step size constraint; is the short-pulse laser pulse width; is the short-pulse laser frequency.

[0016] As a possible implementation, the parameters of the input layer and the output layer are both normalized, and the normalization range is [0, 1]; the normalization expression is:

[0017] ;

[0018] Among them, is the normalized result of the corresponding parameter value in the training dataset; is the corresponding parameter value in the training dataset; and are the minimum and maximum values of the corresponding parameter in the training dataset, respectively.

[0019] As a possible implementation, the parameter needs to satisfy the physical constraint conditions: ; in the case where the prediction result does not satisfy the above constraint conditions, correction processing should be performed, and the correction method is: .

[0020] As a possible implementation, the total calculation step of the solver is 20 - 50 times the pulse width of the short-pulse laser .

[0021] As a possible implementation, the meshing uses free triangular meshing, and the mesh element size is predefined as ultra-fine.

[0022] As a possible implementation, the range of the short-pulse laser pulse width is: 100 ps - 500 ns.

[0023] In a second aspect, the present invention provides a simulation system for the temperature field and stress field of a short-pulse laser irradiated material, specifically including:

[0024] A simulation parameter configuration unit, used to configure simulation parameters, and the simulation parameters include short-pulse laser irradiation parameters and material property parameters;

[0025] A thermo-mechanical coupling transient model construction unit for the material, constructs a thermo-mechanical coupling transient model for the material, and determines the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the thermo-mechanical coupling transient model;

[0026] A meshing unit, which performs meshing on the thermo-mechanical coupling transient model based on the heat transfer physical field and the solid mechanics physical field;

[0027] A solver parameter configuration unit, used to configure solver parameters, and the solver parameters include an initial step size, a maximum step size constraint, and a time step for storing the result of one calculation; the solver parameters are determined by applying a pre-trained linear neural network model. Specifically: input the short-pulse laser pulse width and the short-pulse laser frequency into the pre-trained linear neural network model, and use the calculation expression of the pre-trained linear neural network model to calculate and obtain the solver parameters;

[0028] Determine the elements for the distribution of the material temperature field and stress field, and use a solver to solve the thermo-mechanical coupling transient model to obtain the distribution of the temperature field and stress field of the material at different irradiation times.

[0029] Compared with the prior art, the beneficial effects produced by the present invention are as follows:

[0030] 1. A simulation method for the temperature field and stress field of a short-pulse laser irradiated material proposed by the present invention can analyze complex physical processes such as heat conduction inside the material, convective heat transfer between the surface and the environment, and thermal expansion of the material under the action of a short-pulse laser for different short-pulse laser parameters and different materials, and obtain the distribution of the temperature field and stress field of the material under short-pulse laser irradiation.

[0031] 2. A simulation method for the temperature field and stress field of a short-pulse laser irradiated material proposed by the present invention can analyze the distribution of the temperature field and stress field at different irradiation times, thereby reducing the experimental cost and shortening the experimental period.

[0032] 3. A simulation method for the temperature field and stress field of a short-pulse laser irradiated material proposed by the present invention obtains the effects of laser irradiation on the material under various working conditions, providing a technical means for the optimization design of laser parameters.

[0033] 4. The solver parameter optimization setting method proposed by the present invention can capture the fine physical characteristics in the transient response stage during the short-pulse laser irradiation process, and can also reduce the calculation amount in the relaxation stage when the laser is not acting, and better calculate the temperature field and stress field results of the short-pulse laser irradiated material. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are used to provide a further understanding of the present invention, and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention, and do not constitute an improper limitation of the present invention. In the drawings:

[0035] Figure 1 is a flow chart of the simulation method for the temperature field and stress field of a short-pulse laser irradiated material;

[0036] Figure 2 is a schematic diagram of the laser switch function in an embodiment of the present invention;

[0037] Figure 3 is a schematic diagram of the mesh division in an embodiment of the present invention;

[0038] Figure 4 is a temperature change curve diagram of four different coordinate positions ((0 mm, 0 mm), (0.5 mm, 0.5 mm), (1 mm, 1 mm), (2 mm, 2 mm)) on the upper surface of the metal in an embodiment of the present invention;

[0039] Figure 5 For the temperature field distribution of the material at three irradiation times (t1 = 0 s, t2 = 3.6×10 -7 s, t3 = 6.7×10 -7 s) in the embodiment of the present invention;

[0040] Figure 6 For the thermal expansion displacement distribution of aluminum metal material at three irradiation times (t1 = 0 s, t2 = 2.5×10 -6 s, t3 = 5×10 -6 s) in the embodiment of the present invention;

[0041] Figure 7 For the thermal stress distribution of aluminum metal material at three irradiation times (t1 = 0 s, t2 = 5×10 -7 s, t3 = 5×10 -6 s) in the embodiment of the present invention. Detailed implementation manners

[0042] In order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish identical or similar items with basically the same functions and effects. For example, the first threshold and the second threshold are only used to distinguish different thresholds, and do not limit their sequence. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order, and terms such as "first" and "second" do not necessarily limit being different.

[0043] It should be noted that in the present invention, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0044] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B may be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. The following at least one (item) or its similar expression refers to any combination of these items, including any combination of single item (item) or plural items (items). For example, at least one (item) of a, b or c may represent: a, b, c, the combination of a and b, the combination of a and c, the combination of b and c, or the combination of a, b and c, where a, b and c may be single or multiple.

[0045] An embodiment of the present invention aims to provide a simulation method and system for the temperature field and stress field of a short-pulse laser irradiated material. By optimizing the design of solver parameters, it is possible to comprehensively and accurately capture the complex transient physical phenomena of the laser irradiating the material at different times. The specific implementation is as follows:

[0046] In a first aspect, an embodiment of the present invention provides a simulation method for the temperature field and stress field of a short-pulse laser irradiated material. Refer to Figure 1 , the simulation method includes the following steps:

[0047] Determine the simulation parameters, including short-pulse laser irradiation parameters and material property parameters;

[0048] As a possible implementation, the range of the short-pulse laser pulse width is: 100 ps - 500 ns.

[0049] Exemplarily, the laser irradiation center and laser-related parameters are as shown in Table 1 below;

[0050] Table 1 Laser irradiation center and laser-related parameter table

[0051]

[0052] Exemplarily, the material property parameters include the melting point, latent heat of fusion, thermal conductivity, density, specific heat capacity at constant pressure, Young's modulus, absorption coefficient of the laser, Poisson's ratio, and coefficient of thermal expansion of the material.

[0053] Exemplarily, the materials include metals such as aluminum, iron, copper, zinc, and semiconductor materials such as silicon and germanium.

[0054] Taking aluminum metal as an example, set the geometric length L, width W, and height H of the aluminum sheet to 15 mm, 15 mm, and 0.3 mm respectively.

[0055] Exemplarily, the relevant parameters of the aluminum sheet are as shown in Table 2 below;

[0056] Table 2 Aluminum sheet-related parameter table

[0057]

[0058] Construct a thermo-mechanical coupling transient model of the material, and determine the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the thermo-mechanical coupling transient model;

[0059] Exemplarily, a thermo-mechanical coupling transient model of the material is constructed based on the COMSOL Multiphysics software.

[0060] Exemplarily, the thermo-mechanical coupling transient model is a three-dimensional multi-physics model, which is obtained by creating a solid heat transfer and solid mechanics module and performing a thermo-mechanical coupling multi-physics simulation of laser irradiated materials.

[0061] Exemplarily, the solid heat transfer module has the expression:

[0062] ;

[0063] Where, is the density of the material; is the mass heat capacity; is the heating rate; is the temperature gradient; is the thermal conductivity of the material; is the internal heat source term.

[0064] Exemplarily, the solid mechanics module has the expression:

[0065] ;

[0066] Where, is the mass density of the material; is the acceleration term, is the displacement, and t is the time; is the internal stress, and its expression is: , C is the fourth-order elasticity matrix, is the displacement strain, and its expression is .

[0067] Exemplarily, the energy deposition of the laser on the material surface has the expression:

[0068] ;

[0069] ;

[0070] Where, is the absorption coefficient of the material for the laser; is the spot radius; is the position of any point on the upper surface of the material; is the laser irradiation center position; t is the time; is the laser switch function, which is used to control the change of the laser on the time scale. This function is a Gaussian pulse function with a peak value of 1 and a standard deviation of the laser pulse width, as Figure 2 shown; is the average power of a single laser pulse; E is the energy of a single laser pulse; is the laser pulse width.

[0071] Exemplarily, the relationship between the thermal expansion strain of the material and the temperature change is:

[0072] ;

[0073] Among them, is the thermal expansion strain of the material; is the coefficient of thermal expansion of the material; is the temperature; is the volume reference temperature.

[0074] Exemplarily, for the surface boundary heat flux of the laser-irradiated material, it is denoted as , and satisfies the expression:

[0075] ;

[0076] Among them, is the boundary normal vector; is the laser heat flux; is the heat flux of convective heat transfer between the laser-irradiated surface and the environment.

[0077] For the surface boundary heat flux of the non-laser-irradiated surface all satisfy:

[0078] The convective heat transfer between the material surface and the environment is: ; where h is the convective heat transfer coefficient; is the ambient temperature; is the temperature.

[0079] Based on the heat transfer physical field and the solid mechanics physical field, the thermo-mechanical coupling transient model is meshed, as shown in Figure 3 ;

[0080] As a possible implementation, the meshing uses free triangular meshing, and the mesh element size is predefined as ultra-fine; when the material shape is a cuboid, the meshing can be carried out by the sweeping method.

[0081] Configure the solver parameters. The solver parameters include the initial step size, the maximum step size constraint, and the time step for storing the results of one calculation; the solver parameters are determined by applying a pre-trained linear neural network model; specifically: input the short pulse laser pulse width and the short pulse laser frequency into the pre-trained linear neural network model, and apply the calculation expression of the pre-trained linear neural network model to calculate and obtain the solver parameters;

[0082] As a possible implementation, the pre-trained linear neural network model includes an input layer and an output layer; among them, the parameters of the input layer include the short pulse laser pulse width node and the short pulse laser frequency node; the parameters of the output layer include the initial step size node, the maximum step size constraint node, and the time step node for storing the results of one calculation.

[0083] As a possible implementation, the computational expression of the pre-trained linear neural network model is:

[0084] ;

[0085] where is the weight matrix, ; is the bias vector, ; is the initial step size; is the time step for storing the result of one calculation; is the maximum step size constraint; is the short-pulse laser pulse width; is the short-pulse laser frequency.

[0086] As a possible implementation, the parameters of the input layer and the output layer are both normalized, and the normalization range is [0, 1]; the normalization expression is:

[0087] ;

[0088] where is the normalized result of the corresponding parameter value in the training dataset; is the corresponding parameter value in the training dataset; and are the minimum and maximum values of the corresponding parameter in the training dataset, respectively.

[0089] As a possible implementation, the parameters need to satisfy the physical constraint conditions: ; in the case where the prediction result does not satisfy the above constraint conditions, correction processing should be performed, and the correction method is: .

[0090] As a possible implementation, the total number of computational steps of the solver is 20 - 50 times the short-pulse laser pulse width .

[0091] Apply the solver to solve the thermo-mechanical coupling transient model to obtain the temperature field and stress field distributions of the material at different irradiation times.

[0092] During specific implementation, according to the pre-trained linear neural network model, set the initial step size, maximum step size constraint, and time step for storing one calculation result in the solver parameters; for example, in the output time step column in the transient solver research settings, input range(0, Pulse_Width / 30, Pulse_Width*50), in the initial step size column of the transient solver, input Pulse_Width / 5, in the maximum step size constraint column, input Pulse_Width / 20, and the time step for storing one calculation result is Pulse_Width / 30.

[0093] Exemplarily, add a probe at the position to be detected, or add cut points, cut lines, or cross-sections to the post-processed dataset to obtain the real-time change of temperature at a certain position; when the model solution is completed, add a plotting group and call the corresponding dataset to explore the results.

[0094] As Figure 4 shown, in this embodiment, select the upper surface, and the coordinates of the corresponding two-dimensional cut points are (0mm, 0mm), (0.5 mm, 0.5 mm), (1 mm, 1 mm), and (2 mm, 2 mm) respectively, and plot the temperature change curve in the one-dimensional plotting group. In this embodiment, add a three-dimensional plotting group, as Figure 5 、 6 and 7 shown, plot the temperature field distribution map, thermal expansion displacement distribution map, and thermal stress distribution map of the aluminum sheet. According to Figures 5-7 the simulation results, the temperature field distribution, thermal expansion displacement distribution, and thermal stress distribution calculation results of the material at different transient moments under short-pulse laser irradiation can be obtained, and the corresponding physical field parameters can be obtained in real time.

[0095] In a second aspect, the present invention provides a simulation system for the temperature field and stress field of a material irradiated by a short-pulse laser, specifically including:

[0096] A simulation parameter configuration unit for configuring simulation parameters, where the simulation parameters include short-pulse laser irradiation parameters and material property parameters;

[0097] A thermo-mechanical coupling transient model construction unit for constructing a thermo-mechanical coupling transient model of the material and determining the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the thermo-mechanical coupling transient model;

[0098] A meshing unit for meshing the thermo-mechanical coupling transient model based on the heat transfer physical field and the solid mechanics physical field;

[0099] A solver parameter configuration unit for configuring solver parameters, where the solver parameters include an initial step size, a maximum step size constraint, and a time step for storing the results of one calculation; the solver parameters are determined by applying a pre-trained linear neural network model. Specifically, the pulse width and frequency of the short-pulse laser are input into the pre-trained linear neural network model, and the solver parameters are calculated using the calculation expression of the pre-trained linear neural network model.

[0100] A unit for determining the distribution of the material temperature field and stress field applies the solver to solve the thermo-mechanical coupling transient model to obtain the distribution of the temperature field and stress field of the material at different irradiation times.

[0101] Although the present invention has been described in connection with various embodiments, however, in the process of implementing the claimed invention, those skilled in the art can understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure content, and the description of the drawings, etc. In the specification, the word "comprising" does not exclude other components or steps, and "a" or "one" does not exclude a plurality. A single processor or other unit can implement several functions listed in the specification. Certain measures are described in different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0102] Although the present invention has been described in connection with specific features and their embodiments, it is obvious that various modifications and combinations can be made without departing from the spirit and scope of the present invention. Accordingly, the present specification and the drawings are merely exemplary descriptions of the present invention and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present invention. Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technologies, the present invention also intends to include these changes and modifications.

Claims

1. A simulation method for the temperature field and stress field of a material irradiated by short-pulse laser, characterized in that, The simulation method includes the following steps: Determine the simulation parameters, where the simulation parameters include short-pulse laser irradiation parameters and material property parameters; Construct a thermo-mechanical coupling transient model of the material, and determine the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the thermo-mechanical coupling transient model; Perform grid division on the thermo-mechanical coupling transient model based on the heat transfer physical field and the solid mechanics physical field, and configure the solver parameters; the solver parameters include the initial step size, the maximum step size constraint, and the time step for storing the results of one calculation; the solver parameters are determined by applying a pre-trained linear neural network model. Specifically, the short-pulse laser pulse width and the short-pulse laser frequency are input into the pre-trained linear neural network model, and the solver parameters are calculated using the calculation expression of the pre-trained linear neural network model; the pre-trained linear neural network model includes an input layer and an output layer; among them, the parameters of the input layer include the short-pulse laser pulse width node and the short-pulse laser frequency node; the parameters of the output layer include the initial step size node, the maximum step size constraint node, and the time step for storing the results of one calculation node; the calculation expression of the pre-trained linear neural network model is: ； Among them, is the weight matrix, ; is the bias vector, ; is the initial step size; is the time step for storing the result of one calculation; is the maximum step size constraint; is the short-pulse laser pulse width; is the short-pulse laser frequency; Apply the solver to solve the thermo-mechanical coupling transient model to obtain the temperature field and stress field distribution of the material at different irradiation times.

2. The simulation method of the temperature field and stress field of the short-pulse laser irradiated material according to claim 1, characterized in that, The parameters of both the input layer and the output layer are normalized, and the normalization range is [0, 1]; the normalization expression is: ； Among them, is the normalization result of the corresponding parameter value in the training dataset; is the corresponding parameter value in the training dataset; and are the minimum and maximum values of the corresponding parameter in the training dataset respectively.

3. The simulation method of the temperature field and stress field of a short-pulse laser irradiated material according to claim 1, characterized in that, The parameters need to meet the physical constraint conditions: ; In the case where the prediction result does not meet the above constraint conditions, correction processing should be carried out, and the correction method is: .

4. The simulation method of the temperature field and stress field of a short-pulse laser irradiated material according to claim 1, characterized in that, The total calculation step length of the solver is 20 to 50 times the pulse width of the short-pulse laser. ​ 5. The simulation method of the temperature field and stress field of a short-pulse laser irradiated material according to claim 1, characterized in that The grid division adopts free triangular division, and the grid element size is predefined as ultra-fine.

6. The simulation method for the temperature field and stress field of a short-pulse laser irradiated material according to claim 1, characterized in that The range of the short-pulse laser pulse width is: 100 ps - 500 ns.

7. A simulation system for the temperature field and stress field of a material irradiated by short-pulse laser, characterized in that, Including: A simulation parameter configuration unit for configuring simulation parameters, where the simulation parameters include short-pulse laser irradiation parameters and material property parameters; A thermo-mechanical coupling transient model construction unit of the material, which constructs a thermo-mechanical coupling transient model of the material and determines the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the thermo-mechanical coupling transient model; A grid division unit that performs grid division on the thermo-mechanical coupling transient model based on the heat transfer physical field and the solid mechanics physical field; A solver parameter configuration unit for configuring solver parameters, where the solver parameters include the initial step size, the maximum step size constraint, and the time step for storing the results of one calculation; the solver parameters are determined by applying a pre-trained linear neural network model. Specifically, the short-pulse laser pulse width and the short-pulse laser frequency are input into the pre-trained linear neural network model, and the solver parameters are calculated using the calculation expression of the pre-trained linear neural network model; the pre-trained linear neural network model includes an input layer and an output layer; among them, the parameters of the input layer include the short-pulse laser pulse width node and the short-pulse laser frequency node; the parameters of the output layer include the initial step size node, the maximum step size constraint node, and the time step for storing the results of one calculation node; the calculation expression of the pre-trained linear neural network model is: ； Among them, is the weight matrix, ; is the bias vector, ; is the initial step size; is the time step for storing the result of one calculation; is the maximum step size constraint; is the short-pulse laser pulse width; is the short-pulse laser frequency; Apply the solver to solve the thermo-mechanical coupling transient model to obtain the temperature field and stress field distribution of the material at different irradiation times; The unit for determining the distribution of the material temperature field and stress field applies a solver to solve the thermo-mechanical coupling transient model to obtain the distribution of the material temperature field and stress field at different irradiation times.

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