Laser deposition workpiece temperature field simulation and microstructure prediction method and system

Abstract

The invention provides a laser deposition workpiece temperature field simulation and microstructure prediction method and system, and relates to the technical field of additive manufacturing. Constructing a finite element model of the deposition structure, and setting laser deposition parameters; constructing a heat source model and a surface growth model; selecting a material type and a calculation type, and setting the mass ratio of each element in the mixed powder as a deposition material, and the material thermophysical property parameters and the temperature gradient of the mixed powder; constructing a laminar fluid flow equation; constructing a non-isothermal flow equation and an equation that the surface tension coefficient changes along with the temperature; simulating a temperature field and a velocity field in the laser deposition manufacturing process; and according to the temperature field and velocity field distribution result, the temperature gradient and the solidification rate of each area in the sedimentary structure are calculated, and microstructure morphology prediction is carried out according to the temperature gradient and the solidification rate. The problem that in the prior art, it is difficult to predict temperature distribution and microstructure morphology of a deposited layer of the titanium-based composite manufactured through laser deposition is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of additive manufacturing, and particularly relates to a method and a system for simulating the temperature field and predicting the microstructure of a laser deposition part. Background Art

[0002] In laser-assisted rapid prototyping manufacturing, the deposited layer is formed by melting metal powder and depositing it on the surface of the base metal. This process involves many complex physical phenomena, such as the interaction between the laser and the powder, heat transfer and mass transfer, fluid flow, melting and solidification, etc. When performing laser deposition, the composition design of the deposited material is one of the important factors. The ceramics in ceramic-reinforced metal matrix composites have characteristics such as high hardness and high melting point, and can form uniformly dispersed reinforcing phases in the deposited layer, improving the wear resistance of titanium alloys. Moreover, titanium alloys themselves have good corrosion resistance and can meet the harsh requirements of complex working conditions.

[0003] Due to advantages such as metallurgical bonding between the deposited layer and the substrate, concentrated energy, small heat-affected zone, and less damage to the substrate, laser deposition technology is applied to the high-performance repair of various metal parts. Mastering the relationship between process parameters and thermal response can effectively predict residual stress, deformation, microstructure, and mechanical properties, as well as optimize process parameters. During the laser deposition process, there are many influencing factors for the temperature field, such as powder feeding rate, deposited layer thickness, laser power, and scanning speed. It is very difficult to study the thermodynamic mechanism or detect the molten pool temperature and the stress generated by the coating by experimental methods. Numerical simulation provides an effective means for studying the complex physical and chemical phenomena in the laser deposition process. The simulation of the laser deposition temperature field is of great value for deducing the evolution law of the coating microstructure and predicting solidification structure defects. Currently, the common methods for simulating the temperature field include COMSOL multi-physics field analysis, ANSYS birth and death element analysis, and Fluent molten pool fluid analysis, etc. Among them, COMSOL is outstanding in terms of the depth of multi-physics field coupling and modeling flexibility, and is particularly suitable for complex temperature field problems that require simultaneous consideration of multi-field coupling such as heat-mechanics-electricity-current.

[0004] However, in previous studies on the laser deposition manufacturing process, the laminar flow, fluid heat transfer, Marangoni effect, and the surface deposition layer growth process have not been fully coupled. These physical phenomena are coupled with each other and jointly determine the behavior of the molten pool and the quality of the deposition layer. However, due to the complexity of these coupling relationships, current research is mostly limited to the independent analysis of single or partial phenomena, and the interaction mechanism has not been comprehensively revealed. Therefore, a systematic study of these coupling phenomena is of great significance for optimizing process parameters, improving the quality of the deposition layer, and enhancing the mechanical properties of titanium matrix composites. In addition, no scholar has systematically studied the correlation between the temperature field distribution and the microstructure evolution of the composite material to reveal the regulation mechanism of the reticular microstructure, and thus improve the mechanical properties of the titanium matrix composite. This research will fill the gap in the current field and provide a theoretical basis for optimizing process parameters. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a method and system for simulating the temperature field and predicting the microstructure of laser deposition parts, so as to solve the problem of the difficulty in predicting the temperature distribution and microstructure morphology of the deposition layer of titanium matrix composites by laser deposition manufacturing in the prior art.

[0006] The first aspect of the present invention provides a method for simulating the temperature field and predicting the microstructure of laser deposition parts, including the following steps:

[0007] Construct a finite element model of the deposition structure and set the laser deposition parameters of the finite element model of the deposition structure;

[0008] Based on the laser displacement, construct a heat source model and a surface growth model of the deposition structure;

[0009] Select the material type and calculation type, and set the mass ratio of each element in the mixed powder used as the deposition material, the material thermophysical parameters of the mixed powder, and the temperature gradient; the material thermophysical parameters of the mixed powder include density, thermal conductivity, and isobaric heat capacity;

[0010] Construct a laminar fluid flow equation;

[0011] Considering non-isothermal flow and the Marangoni effect, construct a non-isothermal flow equation and an equation for the variation of the surface tension coefficient with temperature respectively;

[0012] Use the established finite element model of the deposition structure, heat source model, surface growth model of the deposition structure, laminar fluid flow equation, non-isothermal flow equation, and equation for the variation of the surface tension coefficient with temperature to simulate the temperature field and velocity field of the laser deposition manufacturing process, and obtain the distribution results of the temperature field and velocity field;

[0013] According to the distribution results of the temperature field and velocity field, calculate the temperature gradient and solidification rate of each region in the deposition structure, and predict the microstructure morphology based on the temperature gradient and solidification rate.

[0014] Furthermore, build a finite element model of the deposition structure and set the laser deposition parameters of the finite element model of the deposition structure, specifically:

[0015] A1: According to the sizes of the deposition layer and the substrate during the laser deposition process, build a finite element model of the deposition structure and perform mesh element division on the built finite element model of the deposition structure; the finite element model of the deposition structure includes a deposition layer region and a substrate region;

[0016] A2: Set the laser deposition parameters, including the ambient temperature, laser power, spot radius, laser scanning speed, deposition radius, melting temperature of the deposition material, temperature of the transition zone between the deposition layer and the substrate, coefficient of expansion, and laser absorption rate; the deposition material is a mixed powder, including different metal powders in a set ratio.

[0017] Furthermore, build a heat source model and a surface growth model of the deposition structure, specifically:

[0018] B1: Build a laser displacement model for determining the laser movement trajectory;

[0019] The laser displacement model includes the laser displacement in the horizontal direction and the laser displacement perpendicular to the horizontal direction;

[0020] The laser displacement in the horizontal direction is a piecewise function:

[0021]

[0022] where x 00 is the laser spot coordinate in the horizontal direction, v is the laser scanning speed, t is the time, and T' is the end time of the laser moving in the positive horizontal direction;

[0023] The laser spot coordinate y 00 perpendicular to the horizontal direction is: the laser displacement in the vertical direction in the first pass is 0, and the laser displacements in other passes except the first pass are sequentially spaced a set distance from the previous pass;

[0024] B2: Based on the laser displacement model, build a heat source model;

[0025] Adopt a moving Gaussian heat source as the heat source model, specifically:

[0026]

[0027] Wherein, P1 represents the heat flux density, a represents the laser absorption rate, p_laser represents the laser power, r_spot represents the spot radius, pi represents the pi of the circumference ratio, x represents the distance that the laser moves in the horizontal direction, and y represents the distance that the laser moves in the vertical direction;

[0028] B3: Construct a surface growth model of the deposition structure;

[0029] The surface growth model of the deposition structure is:

[0030]

[0031] Wherein, sg represents surface growth and rp represents the deposition radius.

[0032] Further, the laminar fluid flow equation is:

[0033]

[0034] Wherein, ρ is the fluid density, is the gradient operator, μ is the viscosity, u is the velocity field vector, F represents the volume force, and p is the pressure.

[0035] Further, the non-isothermal flow equation is:

[0036]

[0037] Wherein, ρ1 is the fluid density, T is the fluid temperature, c p is the specific heat capacity at constant pressure, k is the thermal conductivity, Φ is the viscous dissipation term, Q represents the external heat source term, u·▽T represents the temperature field change caused by fluid motion, and ▽·(k·▽T) represents the energy transfer caused by heat conduction;

[0038] The equation for the surface tension coefficient varying with temperature is:

[0039]

[0040] Wherein, σ T is the surface tension coefficient, T M is the melting point of the composite material, σ M is the surface tension at the melting point T M and is the temperature coefficient of the surface tension.

[0041] Further, the temperature gradient is defined as follows:

[0042]

[0043] Wherein, ΔT g is the temperature gradient, and They are the partial derivatives of temperature in the x, y, and z directions in the rectangular coordinate system, respectively;

[0044] The solidification rate is defined as follows:

[0045]

[0046] where V is the solidification velocity, k is the thermal conductivity, ΔT is the undercooling degree, ρ s is the material density, L is the latent heat of solidification, and δ is the thickness of the solidified layer;

[0047] The prediction of the microstructure morphology based on the temperature gradient and the solidification rate is as follows: Calculate the product of the temperature gradient and the solidification rate. The larger the value, the smaller the dendrite size. Then, based on the dendrite size, judge the microstructure morphology.

[0048] The second aspect of the present invention provides a temperature field simulation and microstructure prediction system for a laser deposition part, which is used to implement the temperature field simulation and microstructure prediction method of the laser deposition part, including:

[0049] A finite element model construction module, which is used to construct a finite element model of the deposition structure and set the laser deposition parameters of the finite element model of the deposition structure;

[0050] A heat source model construction module, which is used to construct a heat source model;

[0051] A surface growth model construction module, which is used to construct a surface growth model of the deposition structure;

[0052] A parameter setting module, which is used to select the material type and calculation type, and set the mass ratio of each element in the mixed powder used as the deposition material, the material thermal physical properties parameters of the mixed powder, and the temperature gradient; the material thermal physical properties parameters of the mixed powder include density, thermal conductivity, and constant pressure heat capacity;

[0053] A laminar fluid flow equation construction module, which is used to construct a laminar fluid flow equation;

[0054] A non-isothermal flow equation construction module, which is used to construct a non-isothermal flow equation;

[0055] An equation construction module for the change of surface tension coefficient with temperature, which is used to construct an equation for the change of surface tension coefficient with temperature;

[0056] A simulation module, which is used to simulate the temperature field and velocity field in the laser deposition manufacturing process according to the established finite element model of the deposition structure, heat source model, surface growth model of the deposition structure, laminar fluid flow equation, non-isothermal flow equation, and equation for the change of surface tension coefficient with temperature, and obtain the temperature field and velocity field distribution results;

[0057] The microstructure morphology prediction module is used to calculate the temperature gradient and solidification rate of each region in the deposition structure according to the distribution results of the temperature field and velocity field, and predict the microstructure morphology based on the temperature gradient and solidification rate.

[0058] The third aspect of the present invention provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the steps of the method for simulating the temperature field and predicting the microstructure of a laser deposition part are executed.

[0059] The fourth aspect of the present invention provides a computer-readable storage medium. A computer program is stored in the computer-readable storage medium. When the computer program is run by a processor, the steps of the method for simulating the temperature field and predicting the microstructure of a laser deposition part are executed.

[0060] Compared with the prior art, the advantages and beneficial effects of the present invention are as follows:

[0061] (1) The present invention establishes a transient model with coexisting three-dimensional multi-physical fields, and simultaneously considers laminar flow, fluid heat transfer, Marangoni effect, and the growth process of the surface deposition layer, and can more accurately predict the temperature change of the laser deposition layer.

[0062] (2) The method of the present invention can realize the prediction of the microstructure morphology in the laser deposition process by analyzing the temperature gradient and solidification rate, provides a prerequisite for optimizing the laser deposition process parameters, and improves the mechanical properties of the laser deposition. Description of the Drawings

[0063] Figure 1 is a flowchart of the method for simulating the temperature field and predicting the microstructure of a laser deposition part in an embodiment of the present invention;

[0064] Figure 2 is a schematic diagram of the finite element model of the deposition layer and the substrate in the laser deposition process in an embodiment of the present invention;

[0065] Figure 3 is a schematic diagram of the values of the density, thermal conductivity, and specific heat capacity of the mixed powder changing with temperature in an embodiment of the present invention;

[0066] Among them, (a) is the curve of density changing with temperature; (b) is the curve of thermal conductivity changing with temperature; (c) is the curve of specific heat capacity changing with temperature;

[0067] Figure 4 is a schematic diagram of the temperature field and the cross-sectional morphology of the molten pool in the laser deposition manufacturing in an embodiment of the present invention;

[0068] Among them, (a) shows the temperature field results at 6000 ms, 12000 ms, 18000 ms, and 24000 ms; (b) shows the comparison between the experimental and simulated results of the molten pool cross-sectional morphology.

[0069] Figure 5 This is the temperature curve of the temperature monitoring points (A - D) along the center of the light spot downward at times T1 - T4 in the embodiment of the present invention.

[0070] Among them, (a) is the temperature curve of the temperature monitoring points (A - D) along the center of the light spot downward at time T1; (b) is the temperature curve of the temperature monitoring points (A - D) along the center of the light spot downward at time T2; (c) is the temperature curve of the temperature monitoring points (A - D) along the center of the light spot downward at time T3; (d) is the temperature curve of the temperature monitoring points (A - D) along the center of the light spot downward at time T4.

[0071] Figure 6 This is the schematic diagram of the phase content in the composite material at different temperatures in the embodiment of the present invention.

[0072] Figure 7 This is the schematic diagram of the laser deposition manufacturing velocity field in the embodiment of the present invention.

[0073] Among them, (a) is the schematic diagram of the laser deposition manufacturing velocity field at 6000 ms; (b) is the schematic diagram of the laser deposition manufacturing velocity field at 12000 ms; (c) is the schematic diagram of the laser deposition manufacturing velocity field at 18000 ms; (d) is the schematic diagram of the laser deposition manufacturing velocity field at 24000 ms.

[0074] Figure 8 This is the microstructure morphology of different heat - affected zones in the molten pool in the embodiment of the present invention. Detailed implementation manners

[0075] In order to make the purpose, technical solutions and innovative points of the present invention clearer, the following combines the drawings and examples to further describe the detailed implementation manners of the present invention in detail. It should be noted that the specific examples described here can be used to disclose the present invention and can also be extended and applied to other laser - deposited parts of titanium - based composite materials.

[0076] Taking the laser additive manufacturing of thin - walled parts as an example in this embodiment, the present invention uses TC4 as the composite material matrix and TiB as the strengthening phase, and establishes a temperature field simulation and microstructure prediction method for laser - deposited parts considering heat transfer, fluid flow, convection, and the growth process of the surface deposition layer, which can accurately predict the temperature field distribution of the laser - deposited layer and the microstructure morphology, such as Figure 1 As shown, this method includes the following steps:

[0077] Step 1: Construct a finite element model of the deposition structure and set the laser deposition parameters of the finite element model of the deposition structure;

[0078] Step 1.1: According to the sizes of the deposition layer and the substrate during the actual laser deposition process, construct a finite element model of the deposition structure and perform mesh element division on the constructed finite element model of the deposition structure; the finite element model of the deposition structure includes a deposition layer region and a substrate region;

[0079] In this embodiment, the deposition structure is the deposition structure of a titanium matrix composite. The deposition layer region is 20 mm long, 10 mm wide, and 2 mm high; the substrate region is 20 mm long, 10 mm wide, and 4 mm high; the finite element model of the deposition structure is as Figure 2 shown; the finite element model includes two parts: the bottom substrate and the deposition layer. In order to reduce the model calculation time while ensuring the model accuracy, the method of local mesh refinement is adopted. Considering that the deposition layer region is mainly laminar flow, the laminar flow calculation domain is refined, and coarser mesh sizes are used for other parts;

[0080] Step 1.2: Set the laser deposition parameters, including the ambient temperature, laser power, spot radius, laser scanning speed, deposition radius, melting temperature of the deposition material, temperature of the transition zone between the deposition layer and the substrate, coefficient of expansion, and laser absorptivity; the deposition material is a mixed powder, including different metal powders in a set ratio;

[0081] In this example, the laser deposition parameters are set as follows: ambient temperature 273.15 K, laser power 1600 W, spot radius 1.5 mm, scanning speed 2 mm / s, deposition radius 2.5 mm, melting temperature 1933 K, temperature of the transition zone between the deposition layer and the substrate ±70 K, coefficient of expansion 8.6e-5 1 / K, laser absorptivity 0.7;

[0082] Step 2: Based on the laser displacement, construct a heat source model and a surface growth model of the deposition structure;

[0083] Step 2.1: Construct a laser displacement model for determining the laser movement trajectory;

[0084] The laser displacement model includes the laser displacement in the horizontal direction and the laser displacement perpendicular to the horizontal direction;

[0085] The laser displacement in the horizontal direction is a piecewise function:

[0086]

[0087] where x 00 is the laser spot coordinate in the horizontal direction, v is the laser scanning speed, t is the time, and T' is the end time of the laser moving in the positive horizontal direction;

[0088] The laser spot coordinate y perpendicular to the horizontal direction 00 is as follows: the laser displacement in the vertical direction in the first pass is 0, and the laser displacements in other passes except the first pass are successively separated from the previous pass by a set distance;

[0089] In this example, the interval between each pass is set to 3 mm according to the spot radius;

[0090] Step 2.2: Based on the laser displacement model, construct a heat source model;

[0091] In this example, laser deposition manufacturing is carried out on a three-dimensional multi-physics field. The fiber laser used has a Gaussian energy distribution and a low laser scanning speed. Therefore, a moving Gaussian heat source model is selected, and the ambient temperature at the start of laser deposition manufacturing is set to room temperature (273K). In addition, the model uses a moving mesh method based on the arbitrary Lagrangian-Euler method to track the change of the free surface;

[0092] In this embodiment, a moving Gaussian heat source is used as the heat source model, specifically:

[0093]

[0094] In the formula, P1 represents the heat flux density, a represents the laser absorption rate, p_laser represents the laser power, r_spot represents the spot radius, pi represents the circumference ratio π, x represents the distance of laser movement in the horizontal direction, and y represents the distance of laser movement in the vertical direction;

[0095] Step 2.3: Construct a surface growth model of the deposition structure. Subsequently, according to the surface growth model of the deposition structure, the boundary of the substrate can be realized to change according to the melting speed of the mixed powder through the ALE moving mesh provided by the COMSOL Multiphysics software;

[0096] The surface growth model of the deposition structure is:

[0097]

[0098] In the formula, sg represents surface growth, and rp represents the deposition radius;

[0099] Step 3: Select the material type and calculation type, and set the mass ratio of each element in the mixed powder used as the deposition material, the material thermal property parameters of the mixed powder, and the temperature gradient; the material thermal property parameters of the mixed powder include density, thermal conductivity, and constant pressure heat capacity;

[0100] In this embodiment, the material type is selected in the JMatPro software, and the mass ratio of each element is set. In this example, the addition content of TiB is selected as 5%, the calculation type (Phases and Properties) is selected, the temperature gradient is set to 20°C, and the thermal physical parameters of the material are set as the linear interpolation of the mixed powder and the matrix. The required density, thermal conductivity, and constant-pressure heat capacity parameters are calculated and obtained, as Figure 3 shown;

[0101] Step 4: Construct the laminar fluid flow equation;

[0102] In this embodiment, when performing the simulation of laser deposition manufacturing of titanium matrix composites, some physical processes are simplified: (1) The molten metal is an incompressible Newtonian fluid, and the flow is considered to be in a laminar state. The heat conduction and heat convection between the deposited powder and the matrix, and the heat radiation and heat convection between the matrix and the environment are considered; (2) The heat flow loss caused by evaporation is ignored;

[0103] Assume that the melt is a Newtonian incompressible fluid and the flow state is laminar;

[0104] In COMSOL, the coupling of laminar flow and heat transfer between solids and fluids is specifically adopted to construct the laminar fluid flow equation, specifically:

[0105]

[0106] In the formula, ρ is the fluid density, ▽ is the gradient operator, μ is the viscosity, u is the velocity field vector, F represents the volume force, and p is the pressure;

[0107] Step 5: Consider non-isothermal flow and the Marangoni effect, and construct the non-isothermal flow equation and the equation of the surface tension coefficient varying with temperature respectively;

[0108] During the laser deposition process, the surface tension difference increases with the increase of the surface temperature difference. Due to the existence of the surface tension difference, the melt is subjected to unbalanced forces, resulting in Marangoni convection, which acts together with the buoyancy to form the internal circulation of the molten pool. However, the influence of buoyancy on the flow of the molten pool is much smaller than that of the Marangoni flow, so it is ignored. In addition to the Marangoni effect, the influence of non-isothermal flow on the flow of the melt in the molten pool is also considered;

[0109] In this embodiment, the non-isothermal flow and the Marangoni effect are considered to simulate the laser deposition manufacturing of titanium matrix composites. Specifically, based on the analysis of the temperature field, the fluid flow equation and the non-isothermal flow equation are added to simulate the melt flow in the molten pool during laser cladding, and the change of the flow state of the flow field during the laser deposition process is analyzed;

[0110] The non-isothermal flow equation is:

[0111]

[0112] In the formula, ρ1 is the fluid density, T is the fluid temperature, c p is the specific heat capacity at constant pressure, k is the thermal conductivity, Φ is the viscous dissipation term, Q represents the external heat source term, u·▽T represents the change in the temperature field caused by fluid motion (convection), and ▽·(k·▽T) represents the energy transfer caused by heat conduction;

[0113] When there is a surface tension gradient at the two-phase interface, the Marangoni effect will occur, and the equation for the change of the surface tension coefficient with temperature can be expressed as:

[0114]

[0115] In the formula, σ T is the surface tension coefficient, T M is the melting point of the composite material, σ M is the surface tension at the melting point T M , and is the temperature coefficient of the surface tension;

[0116] Step 6: Use the established finite element model of the deposition structure, heat source model, surface growth model of the deposition structure, laminar fluid flow equation, non-isothermal flow equation, and the equation for the change of the surface tension coefficient with temperature to simulate the temperature field and velocity field during the laser deposition manufacturing process, and obtain the distribution results of the temperature field and velocity field;

[0117] In this embodiment, the program is executed to obtain the transient three-dimensional temperature fields at different times (6 s, 12 s, 18 s, and 24 s), as Figure 4 (a) shows. Set temperature monitoring points, set a monitoring point every 0.38 mm from the surface along the center of the light spot downward, and set four monitoring points A, B, C, and D. The melt width and melt height obtained in this example are close to the experimental measurements, as Figure 4 (b) shows, indicating that the accuracy of the numerical simulation is relatively high, and the model can better reflect the change of the melt pool morphology during the actual laser deposition manufacturing process;

[0118] Obtain the temperature-time change curves of the monitoring points at different times, as Figure 5 shown. Obtain the temperature change curves of each phase of the composite material through the JMatPro software, as Figure 6 shown. Combining Figure 5 the temperature monitoring points, it can be obtained that during the deposition process from 0 s to 3 s, except for the center of the melt pool, the temperatures of each point basically remain at 1000 K to 1400 K. Therefore, the constituent phases in the composite material are α-Ti, β-Ti, and TiB. The contents of α-Ti and β-Ti change greatly with temperature, while the content of TiB hardly changes with temperature.

[0119] Figure 7The velocity distribution within the molten pool is described. The length and direction of the red arrows represent the direction and magnitude of the simulated velocity vectors at the tails of the arrows. Since the temperature at the center of the molten pool is the highest and the surface tension gradient is the smallest, the flow rate of the melt is the lowest. Driven by the Marangoni effect, the molten material flows from the center to the periphery, and the calculated maximum surface flow rate is 0.1025 m / s.

[0120] Step 7: According to the results of the temperature field and velocity field distributions, calculate the temperature gradients and solidification rates in each region of the deposition structure, and predict the microstructure morphology based on the temperature gradients and solidification rates;

[0121] In this embodiment, according to the temperature change curves of the monitoring points, the temperature gradients and solidification rates of each region are obtained.

[0122] The temperature gradient in this example is defined as follows:

[0123]

[0124] where ΔT g is the temperature gradient, and are the partial derivatives of temperature in the x, y, and z directions (height direction) in the rectangular coordinate system, respectively. If only the temperature gradient in a certain direction needs to be calculated, only the partial derivative in that direction needs to be considered. In this example, only the temperature gradient in the z direction is of concern.

[0125] The solidification rate is defined as follows:

[0126]

[0127] where V is the solidification rate, k is the thermal conductivity (W / m·K), ΔT is the degree of supercooling (i.e., the difference between the temperature of the liquid substance and the solidification point temperature, K), ρ s is the density of the substance (kg / m 3 ), L is the latent heat of solidification (J / kg), and δ is the thickness of the solidified layer (m);

[0128] The calculated temperature gradients of each region are shown in Table 1. G×R affects the size of the solidification structure. The larger its value, the smaller the size of the dendrites, and the deposition layer will obtain a finer size. According to Table 1, it can be judged that the microtopographies of the A-B, B-C, and C-D regions are extremely fine acicular martensite tissue, fine cellular equiaxed crystals, and coarser dendritic tissues, as Figure 8 shown;

[0129] Table 1

[0130]

[0131] In the present invention, a three-dimensional model is established for the laser deposition process of titanium matrix composites. The Lagrangian-Eulerian ALE moving mesh method is used to freely track the molten pool surface, and the influence of different laser powers and powder ratios on the Marangoni effect is analyzed in combination with convective heat transfer, providing theoretical guidance for obtaining better deposited layer structures.

[0132] In the present invention, the method of comparison and control variables is adopted to analyze the dynamic changes of the temperature field during the laser deposition process, and the interaction between the laser and the powder, as well as the influence of different process parameters on the microstructure of the temperature field, are discussed in combination with experimental verification. The results are more persuasive and representative.

[0133] This embodiment also provides a temperature field simulation and microstructure prediction system for laser deposition parts, which is used to implement the temperature field simulation and microstructure prediction method for laser deposition parts, and includes:

[0134] A finite element model construction module, which is used to construct a finite element model of the deposition structure and set the laser deposition parameters of the finite element model of the deposition structure;

[0135] A heat source model construction module, which is used to construct a heat source model;

[0136] A surface growth model construction module, which is used to construct a surface growth model of the deposition structure;

[0137] A parameter setting module, which is used to select the material type and calculation type, and set the mass ratio of each element in the mixed powder used as the deposition material, the material thermophysical parameters of the mixed powder, and the temperature gradient; the material thermophysical parameters of the mixed powder include density, thermal conductivity, and constant pressure heat capacity;

[0138] A laminar fluid flow equation construction module, which is used to construct a laminar fluid flow equation;

[0139] A non-isothermal flow equation construction module, which is used to construct a non-isothermal flow equation;

[0140] An equation construction module for the change of surface tension coefficient with temperature, which is used to construct an equation for the change of surface tension coefficient with temperature;

[0141] A simulation module, which is used to simulate the temperature field and velocity field during the laser deposition manufacturing process according to the established finite element model of the deposition structure, heat source model, surface growth model of the deposition structure, laminar fluid flow equation, non-isothermal flow equation, and equation for the change of surface tension coefficient with temperature, and obtain the distribution results of the temperature field and velocity field;

[0142] A microstructure morphology prediction module, which is used to calculate the temperature gradient and solidification rate of each region in the deposition structure according to the distribution results of the temperature field and velocity field, and predict the microstructure morphology according to the temperature gradient and solidification rate.

[0143] This embodiment also provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the steps of the method for simulating the temperature field and predicting the microstructure of a laser deposition part are executed.

[0144] This embodiment also provides a computer-readable storage medium. A computer program is stored in the computer-readable storage medium. When the computer program is run by a processor, the steps of the method for simulating the temperature field and predicting the microstructure of a laser deposition part as described are executed.

Claims

1. A method for simulating the temperature field and predicting the microstructure of a laser deposition part, characterized in that, It includes the following steps: Construct a finite element model of the deposition structure and set the laser deposition parameters of the finite element model of the deposition structure; Based on the laser displacement, construct a heat source model and a surface growth model of the deposition structure; Select the material type and calculation type, and set the mass ratio of each element in the mixed powder used as the deposition material, the material thermophysical parameters of the mixed powder, and the temperature gradient; the material thermophysical parameters of the mixed powder include density, thermal conductivity, and constant pressure heat capacity; Construct a laminar fluid flow equation; Considering non-isothermal flow and the Marangoni effect, construct a non-isothermal flow equation and an equation for the variation of the surface tension coefficient with temperature respectively; Use the established finite element model of the deposition structure, heat source model, surface growth model of the deposition structure, laminar fluid flow equation, non-isothermal flow equation, and equation for the variation of the surface tension coefficient with temperature to simulate the temperature field and velocity field during the laser deposition manufacturing process, and obtain the distribution results of the temperature field and velocity field; According to the distribution results of the temperature field and velocity field, calculate the temperature gradient and solidification rate of each region in the deposition structure, and predict the microstructure morphology based on the temperature gradient and solidification rate.

2. A method for simulating the temperature field and predicting the microstructure of a laser deposition part according to claim 1, characterized in that, The construction of the finite element model of the deposition structure and the setting of the laser deposition parameters of the finite element model of the deposition structure are specifically as follows: A1: According to the sizes of the deposition layer and the substrate during the laser deposition process, construct a finite element model of the deposition structure and divide the grid elements of the constructed finite element model of the deposition structure; the finite element model of the deposition structure includes a deposition layer region and a substrate region; A2: Set the laser deposition parameters, including the ambient temperature, laser power, spot radius, laser scanning speed, deposition radius, melting temperature of the deposition material, temperature of the transition zone between the deposition layer and the substrate, expansion coefficient, and laser absorption rate; the deposition material is a mixed powder, including different metal powders in set proportions.

3. A method for simulating the temperature field and predicting the microstructure of a laser deposition part according to claim 1, characterized in that, The construction of the heat source model and the surface growth model of the deposition structure are specifically as follows: B1: Construct a laser displacement model for determining the laser movement trajectory; The laser displacement model includes the laser displacement in the horizontal direction and the laser displacement perpendicular to the horizontal direction; The laser displacement in the horizontal direction is a piecewise function: where x 00 is the coordinate of the laser spot in the horizontal direction, v is the scanning speed of the laser, t is the time, and T' is the end time when the laser moves in the positive horizontal direction; The laser spot coordinate y perpendicular to the horizontal direction 00 is as follows: the laser displacement in the vertical direction in the first pass is 0, and the laser displacements in other passes except the first pass are successively separated from the previous pass by a set distance; B2: Based on the laser displacement model, construct a heat source model; Adopt a moving Gaussian heat source as the heat source model, specifically: In the formula, P1 represents the heat flux density, a represents the laser absorption rate, p_laser represents the laser power, r_spot represents the spot radius, pi represents the pi (π), x represents the distance of laser movement in the horizontal direction, and y represents the distance of laser movement in the vertical direction; B3: Construct a surface growth model of the deposition structure; The surface growth model of the deposition structure is: In the formula, sg represents surface growth and rp represents the deposition radius.

4. A method for simulating the temperature field and predicting the microstructure of a laser deposition part according to claim 1, characterized in that The laminar fluid flow equation is: In the formula, ρ is the fluid density, ▽ is the gradient operator, μ is the viscosity, u is the velocity field vector, F represents the volume force, and p is the pressure.

5. A method for simulating the temperature field and predicting the microstructure of a laser deposition part according to claim 1, characterized in that, The non-isothermal flow equation is: where ρ1 is the fluid density, T is the fluid temperature, c p is the specific heat capacity at constant pressure, k is the thermal conductivity, Φ is the viscous dissipation term, Q represents the external heat source term, represents the change in the temperature field caused by fluid motion, represents the energy transfer caused by heat conduction; The equation for the variation of the surface tension coefficient with temperature is: In the formula, σ T is the surface tension coefficient, T M is the melting point of the composite material, σ M is the surface tension at the melting point T M , and is the temperature coefficient of the surface tension.

6. The method for simulating the temperature field and predicting the microstructure of a laser deposition part according to claim 1, wherein, The temperature gradient is defined as follows: where, ΔT g is the temperature gradient, and are the partial derivatives of temperature in the x, y, and z directions in the rectangular coordinate system, respectively; The solidification rate is defined as follows: where V is the solidification rate, k is the thermal conductivity, ΔT is the degree of supercooling, ρ s is the density of the substance (kg / m 3 ), L is the latent heat of solidification, and δ is the thickness of the solidified layer; The prediction of the microstructure morphology according to the temperature gradient and the solidification rate is specifically as follows: calculate the product of the temperature gradient and the solidification rate. The larger the value, the smaller the dendrite size, and then judge the microstructure morphology according to the dendrite size.

7. A temperature field simulation and microstructure prediction system for laser deposition parts, which is used to implement the temperature field simulation and microstructure prediction method for laser deposition parts described in any one of claims 1-6, characterized in that, It includes: A finite element model construction module, which is used to construct a finite element model of the deposition structure and set the laser deposition parameters of the finite element model of the deposition structure; A heat source model construction module, which is used to construct a heat source model; A surface growth model construction module, which is used to construct a surface growth model of the deposition structure; A parameter setting module, which is used to select the material type and calculation type, and set the mass ratio of each element in the mixed powder used as the deposition material, the material thermophysical parameters of the mixed powder and the temperature gradient; the material thermophysical parameters of the mixed powder include density, thermal conductivity and constant pressure heat capacity; A laminar fluid flow equation construction module, which is used to construct a laminar fluid flow equation; A non-isothermal flow equation construction module, which is used to construct a non-isothermal flow equation; An equation construction module for the change of surface tension coefficient with temperature, which is used to construct an equation for the change of surface tension coefficient with temperature; A simulation module, which is used to simulate the temperature field and velocity field of the laser deposition manufacturing process according to the established finite element model of the deposition structure, heat source model, surface growth model of the deposition structure, laminar fluid flow equation, non-isothermal flow equation and the equation for the change of surface tension coefficient with temperature, and obtain the temperature field and velocity field distribution results; A microstructure morphology prediction module, which is used to calculate the temperature gradient and solidification rate of each region in the deposition structure according to the temperature field and velocity field distribution results, and predict the microstructure morphology according to the temperature gradient and solidification rate.

8. An electronic device, characterized in that, It includes: A processor, a memory and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the steps of a method for simulating the temperature field and predicting the microstructure of a laser deposition part according to any one of claims 1-6 are executed.

9. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium. When the computer program is run by the processor, the steps of a method for simulating the temperature field and predicting the microstructure of a laser deposition part according to any one of claims 1-6 are executed.

Images