A numerical simulation method for the spray deposition behavior of cermet composite coatings with Al2O3 ceramic as strengthening phase

Abstract

The application provides a numerical simulation method for spraying and depositing cermet composite coating with Al2O3 ceramic as a reinforced phase, and belongs to the technical field of computer-aided design of coating spraying and deposition. In order to solve the problem that the existing numerical simulation method cannot effectively simulate the characteristics of Al2O3 brittle particles added in metal particles and cannot accurately characterize the performance of Al-Al2O3 mixed particle coating, the method comprises the following steps: step one, constructing a three-dimensional model of metal particles and a substrate; step two, setting model parameters and boundary conditions through a Johnson-Cook constitutive model, and carrying out mesh division on the particles and the substrate, setting the impact time and the initial speed, and solving; step three, setting the physical parameters of alumina through a Johnson Holmquist 2 constitutive model, setting the initial speed and temperature; step four, solving through a solver; and step five, guiding practical operation according to the output results. The application adopts the mode of coupling Johnson-Holmquist and Johnson-Cook to simulate the Al-Al2O3 composite spraying behavior, which is more suitable for the actual deposition situation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer-aided design of coating spraying deposition, in particular to a numerical simulation method for spraying deposition behavior of a cermet composite coating with Al2O3 ceramic as a strengthening phase. BACKGROUND

[0002] At present, aluminum, titanium, copper, magnesium and the like are often used as spraying materials for cold spraying, and a certain amount of ceramic particles need to be doped in the coating of a single material such as pure aluminum coating to improve the performance of the pure aluminum coating due to the low hardness and low wear resistance of the coating.

[0003] Many scholars have studied and simulated the deformation behavior of deposited particles in the spraying process by using numerical simulation software. Yang Shiyi et al. conducted a numerical simulation study on the strain field around the embedded particles, simulated the strain field in the particle embedding process by using Lsdyna simulation software, and analyzed the plastic deformation of the particles to promote the combination of the particles and the surface of the substrate due to the change of the equivalent plastic strain field caused by the plastic deformation of the particles. However, the experimental model used to describe the particle impact cannot represent the actual multi-particle spraying condition, and the influence of the temperature field change around the particles on the particle deposition behavior during the particle impact process is ignored, so it has certain one-sidedness. Some scholars have introduced the deformation process of ceramic particles during low-speed impact through experimental simulation. Due to the selected experimental method, the cracks of the ceramic particles are generated from the center of the ceramic particles, which cannot represent the cracking of the ceramic particles under all conditions. SUMMARY

[0004] The technical problem to be solved by the present application is:

[0005] The existing numerical simulation method cannot effectively simulate the characteristics of the metal particles after adding Al2O3 brittle particles, and cannot accurately represent the performance of the Al-Al2O3 mixed particle coating.

[0006] The technical scheme adopted by the present application to solve the above technical problems is:

[0007] The present application provides a numerical simulation method for spraying deposition behavior of a cermet composite coating with Al2O3 ceramic as a strengthening phase, comprising the following steps:

[0008] Step 1: According to the structural characteristics of the metal particles in the metal coating, a three-dimensional model of the metal particles and the substrate is constructed.

[0009] Step two, import the three-dimensional model into the ansys software, set the material properties and physical parameters of the metal particles and the substrate through the Johnson-Cook constitutive model respectively; Set the symmetry surface attribute, and finally set the interaction parameters between the metal particles and the substrate, then set the boundary conditions, and divide the grid of the particles and the substrate; Get the constitutive model of the metal particles and the substrate; Set the impact time and initial velocity, and solve to get the K file;

[0010] Step three, import the obtained K file into Lsdyna software, modify the physical parameters of part of the metal particles to the physical parameters of aluminum oxide through Johnson Holmquist 2 constitutive model, set the initial velocity and temperature;

[0011] Step four, submit the modified K file to the solver, adjust the control parameters of the solution, output the plastic strain results of the particles, the temperature change cloud diagram of the particle impact process and the damage degree results of the ceramic particles;

[0012] Step five, analyze the output results to guide the spraying operation in practice.

[0013] Optionally, the three-dimensional model of the metal particles and the substrate in step one is constructed by solidwork.

[0014] Optionally, the three-dimensional model of the metal particles and the substrate is composed of 15 hemispherical particles and 1 cuboid substrate, and the 15 hemispherical particles are arranged in the order of 4, 5 and 6 from top to bottom; The particle diameter is 20μm, and the length, thickness and height of the substrate are 10 times, 5 times and 5 times the particle diameter respectively.

[0015] Optionally, in step two, the material property of the metal particles is set as aluminum, and the material property of the substrate is set as steel; The physical parameters include material temperature, density, thermal conductivity, elastic modulus, thermal expansion coefficient, melting point, Poisson's ratio, specific heat, initial yield stress, material strain hardening modulus, hardening index, strain rate constant, temperature constant and Grunesien state equation coefficient; The interaction parameters are set as the interaction force between the particles and the interaction force between the particles and the substrate, and the friction coefficient between the particles and the friction coefficient between the particles and the substrate.

[0016] Optionally, in step two, setting the boundary conditions specifically sets the bottom of the substrate as a fixed constraint.

[0017] Optionally, in step two, the grid division of the particles is in the form of independent division, and the substrate is in the form of gradual grid, the grid division of the contact area is relatively dense, and the grid gradually increases away from the contact area.

[0018] Optionally, in step three, the physical parameters of alumina include: density, elastic modulus, elastic limit, pressure at the Hugoniot elastic limit, maximum static tensile strength, bulk modulus, pressure constant, failure strength constant, intact strength parameter, reference strain rate, energy loss factor, normalized strength parameter of intact material, normalized strength parameter of failed material, strain rate effect parameter, damage factor, exponential damage factor, and failure control parameter.

[0019] Optionally, in step three, for elastic modulus values ​​that are difficult to obtain, the elastic modulus of Al2O3 at different temperatures is obtained by fitting a curve between existing elastic modulus and temperature, specifically as follows:

[0020]

[0021] In the formula, E is the elastic modulus, and a1 and b1 are constants.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] This invention provides a numerical simulation method for the spraying and deposition behavior of metal-ceramic composite coatings with Al2O3 ceramic as the reinforcing phase. The method considers the deformation process of the metal material. During impact simulation, the metal material softens and heats up upon impact pressure, undergoing further softening and deformation deposition as the temperature rises. Simultaneously, the method considers the collision of brittle Al2O3 ceramic particles and employs a coupled Johnson-Holmquist and Johnson-Cook constitutive model. This approach improves the deformation behavior of the metal material after softening, maintaining a certain level of plastic deformation strength. This makes the spraying and deposition behavior more realistic, enhancing the accuracy of the simulation results. It provides important evidence and simulation tools for studying the spraying quality of metal-ceramic composite coatings with added reinforcing phases.

[0024] This invention models the deposition behavior of spray coatings, which can reflect the crack generation mechanism and deformation of alumina particles during impact and breakage. Based on the obtained coating results and the damage results of alumina particles, it can provide guidance for spray coating work to obtain coatings with high hardness, corrosion resistance and wear resistance in practice. Attached Figure Description

[0025] Figure 1 This is a flowchart of the numerical model method in an embodiment of the present invention;

[0026] Figure 2 This is a three-dimensional model of the metal particles and the substrate in an embodiment of the present invention;

[0027] Figure 3 This is a model diagram of mesh generation for particles and substrate in an embodiment of the present invention;

[0028] Figure 4 The numerical model of Al-Al2O3 mixed particles in the embodiment of the present application;

[0029] Figure 5 The graph of the relationship between the elastic modulus of Al2O3 and temperature in the embodiment of the present application;

[0030] Figure 6 The strain graph of multiple particles impacting a steel substrate in the embodiment of the present application;

[0031] Figure 7 The comparative graph of the compression rate of aluminum particles impacting the lowermost layer of particles at different speeds and the compression rate of Al-Al2O3 mixed particles impacting the lowermost layer of particles in the embodiment of the present application;

[0032] Figure 8 The damage value curve graph of Al-Al2O3 mixed particles impacting ceramic particles in a steel substrate at different initial speeds in the embodiment of the present application;

[0033] Figure 9 The curve graph of the damage degree factor changing with temperature at different preheating temperatures in the embodiment of the present application;

[0034] Figure 10 The optical micrographs of pure aluminum sprayed coating and composite sprayed coating with Al2O3 ceramic as a strengthening phase in the embodiment of the present application. DETAILED DESCRIPTION

[0035] In the description of the present application, it should be explained that the terms "first", "second", "third" mentioned in the embodiments of the present application are only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second", "third" can explicitly or implicitly include one or more features.

[0036] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0037] In combination with Figure 1 The present application provides a numerical simulation method of spraying and depositing behavior of a cermet composite coating with Al2O3 ceramic as a strengthening phase, which comprises the following steps:

[0038] Step one, according to the structural characteristics of the metal particles in the metal coating, a three-dimensional model of the metal particles and the substrate is constructed;

[0039] Among them, the three-dimensional model of the metal particles and the substrate is constructed by solidwork;

[0040] As shown in Figure 2 The three-dimensional model of the metal particles and the substrate is specifically composed of 15 hemispherical particles and one cuboid substrate, the 15 hemispherical particles are sequentially accumulated from top to bottom in the arrangement mode of 4, 5 and 6; wherein the particle diameter is 20 μm, and the length, thickness and height of the substrate are 10 times, 5 times and 5 times of the particle diameter, respectively.

[0041] The three-dimensional model is constructed as a half model in step one, and the symmetry plane attribute is set in subsequent step two, so as to reduce the calculation amount.

[0042] In step two, the three-dimensional model is imported into the ansys software, the material properties and physical parameters of the metal particles and the substrate are set through the Johnson-Cook constitutive model; the symmetry plane attribute is set, and finally the interaction parameters between the metal particles and between the metal particles and the substrate are set, then the boundary conditions are set, and the particles and the substrate are meshed; the constitutive model of the metal particles and the substrate is obtained; the impact time and the initial velocity are set, and the K file is obtained by solving;

[0043] The material properties of the metal particles are set as aluminum, and the material properties of the substrate are set as steel, and the physical parameters all include material temperature, density, thermal conductivity, elastic modulus, thermal expansion coefficient, melting point, Poisson's ratio, specific heat, initial yield stress, material strain hardening modulus, hardening index, strain rate constant, temperature constant and Grunesien state equation coefficient; the interaction parameters are specifically set as the interaction force between the particles and the interaction force between the particles and the substrate, and the friction coefficient between the particles and the friction coefficient between the particles and the substrate are set;

[0044] The boundary conditions are specifically set as the bottom of the substrate is set as a fixed constraint;

[0045] As shown in Figure 3 The meshing of the particles is in the form of independent division, the meshing of the substrate is in the form of gradual change, and the meshing of the contact area is relatively dense, and the mesh gradually becomes larger away from the contact area;

[0046] The physical parameters of the metal particles and the substrate are shown in Table 1, the friction coefficient between the particles is set as 0.2, and the friction coefficient between the particles and the substrate is set as 0.2.

[0047] Table 1

[0048]

[0049] In the table, A is the initial yield stress, B is the material strain hardening modulus, N is the hardening index, C is the strain rate constant, M is the temperature constant, and Grunesien is the state equation coefficient.

[0050] Step three, as shown in Figure 4 The obtained K file is imported into Lsdyna software, the physical parameters of part of the metal particles are modified to the physical parameters of aluminum oxide by Johnson Holmquist 2 constitutive model, and the initial velocity and temperature are set.

[0051] The physical parameters of aluminum oxide include density, elastic modulus, elastic limit, pressure under Hugoniot elastic limit, maximum static tensile strength, bulk modulus, pressure constant, damage strength constant, intact strength parameter, reference strain rate, energy loss factor, normalized strength parameter of intact material, normalized strength parameter of damaged material, strain rate effect parameter, damage factor, exponential damage factor and failure control parameter.

[0052] As shown in Figure 5 For the value of the elastic modulus which is not easy to obtain, the elastic modulus of Al2O3 at different temperatures is obtained by fitting the existing elastic modulus and temperature, and the specific process is as follows:

[0053]

[0054] In the formula, E is the elastic modulus, and a1 and b1 are constants, respectively.

[0055] The constants a1 and b1 are 493.9 and-0.051, respectively.

[0056] The physical parameters of aluminum oxide are shown in Table 2.

[0057] Table 2

[0058]

[0059] In the table, HEL is the elastic limit, PHEL is the pressure under Hugoniot elastic limit, T is the maximum static tensile strength, K1 is the bulk modulus, K2 and K3 are the pressure constants, A is the normalized strength parameter of intact material, N is the intact strength parameter, C is the strain rate effect parameter, B is the normalized strength parameter of damaged material, M is the damage strength constant, BEAT is the energy loss factor, EPSI is the reference strain rate, D1 is the damage factor, D2 is the exponential damage factor, and FS is the failure control parameter.

[0060] Step four, the modified K file is submitted to the solver, the control parameters of the solution are adjusted, the plastic strain results of the particles, the temperature change cloud diagram of the particle impact process and the damage degree results of the ceramic particles are outputted.

[0061] The output results are analyzed

[0062] Through the summary and analysis of the simulation results, it can be concluded that the optimal parameters for depositing the steel substrate with pure aluminum particles are an initial speed of 350 m / s and a preheating temperature of 500 DEG C.

[0063] As shown in Figure 6 Fig. 6, the plastic strain of the deposited layer at 55 ns under the condition that the initial speed of the particles is 350 m / s and the preheating temperature is 500 DEG C can be seen. Compared with the pure 1060 Al particles, the impact of the Al2O3 ceramic particles on the front row particles further compresses the area where the front row particles do not deform well, intensifies the deformation of the deposited Al particles as a whole, and leads to more intense plastic deformation of the deposited particles, thereby improving the density of the lowermost deposited layer. This is consistent with the actual situation, and the addition of Al2O3 can improve the density of the coating in the actual spraying process, which further verifies the accuracy of the model constructed by the method.

[0064] As shown in Figure 7 Fig. 7, under the condition that the preheating temperature is 500 DEG C, the compression rate of the bottom layer particles gradually increases with the increase of the initial speed, and the compression rate of the 1060 Al-Al2O3 mixed particles is obviously higher than that of the pure Al particles. This indicates that the addition of Al2O3 particles with high hardness has a greater force on the bottom layer particles, resulting in more intense deformation and a significant improvement in the compression rate.

[0065] As shown in Table 3, the porosity of the coating formed under different initial speeds under the condition that the preheating temperature is 500 DEG C is shown. Specifically, by setting different simulation speeds, the deposition results of the particles are solved under the same time, and the cross-sectional view of the deposition results is imported into the imageJ software to obtain the porosity of the coating.

[0066] Table 3

[0067]

[0068] As can be seen from the table, the porosity of the coating decreases with the increase of the initial speed of the particles, and the porosity of the coating formed by the mixed particles with hard phases is less than that of the coating formed by the pure Al particles. This indicates that the addition of Al2O3 particles can effectively improve the quality of the coating and enhance its corrosion resistance.

[0069] As shown in Figure 8 Fig. 8, under the condition that the preheating temperature is 500 DEG C, the damage degree of the Al2O3 particles gradually increases with the increase of the initial speed. When the initial speed reaches 600 m / s, the ceramic particles are broken as a whole. The broken parts will be dispersed into the voids in the coating and deepen the mechanical engagement degree between the deposited particles and the substrate.

[0070] This is because the initial velocity gives the ceramic particles an initial kinetic energy, when it collides with the already deposited particles, itself will be subjected to interaction force, when this force exceeds the maximum stress that the Al2O3 particles can withstand, it will begin to produce cracks or even break.

[0071] The damage factor refers to the area of the Al2O3 particles that produces cracks or breaks during the impact deposition process, accounting for the percentage of the overall area of the particles.

[0072] The relationship between the damage factor and the velocity is:

[0073] D K =aln(-bln(V))

[0074] In the formula, D K is the damage factor, a and b are constants, which are 586 and-0.186 respectively;

[0075] Considering the influence of the initial velocity on the coating compression rate, porosity and particle damage value, the optimal initial velocity is determined to be 350 m / s.

[0076] As Figure 9 shown, under the condition of an initial velocity of 350 m / s, the damage factor gradually increases with the increase of the preheating temperature, among which,

[0077] The relationship between the damage factor and the preheating temperature is:

[0078] D K =K1+K2T N

[0079] In the formula, K1, K2 and N are constants, which are 40.6, 5.02 and 3.37 respectively, and T is the preheating temperature.

[0080] It can be seen that the influence of the preheating temperature on the damage of Al2O3 particles is less than that of the initial velocity on the damage of Al2O3 particles. According to the relationship between ceramic damage and initial velocity and preheating temperature, combined with the actual requirements of the cold sprayed coating, the optimal operating parameters are determined to be a particle initial velocity of 350 m / s and a preheating temperature of 500℃.

[0081] As Figure 10The results of the pure aluminum sprayed coating and the composite sprayed coating with Al2O3 ceramic as the strengthening phase are shown, wherein the mass fraction of Al2O3 is 0%, 10%, 50% and 70% respectively, and the operation parameters are an initial speed of 350 m / s and a preheating temperature of 500 DEG C. It can be seen that the composite coating sprayed coating has smaller pore size, better coating density and higher mechanical bite degree between the coating and the substrate. The operation parameters obtained by the method and the addition of Al2O3 ceramic as the strengthening phase can obtain a better metal coating.

[0082] Although the present application discloses as above, the protection scope of the present application is not limited to this. The person skilled in the art can make various changes and modifications without departing from the spirit and scope of the present application, and these changes and modifications will fall within the protection scope of the present application.

Claims

1. A numerical simulation method of the spray deposition behavior of cermet composite coatings with AI2O3ceramics as strengthening phase, characterized in that It comprises the following steps: Step one, according to the structural characteristics of metal particles in metal coating, the three-dimensional model of metal particles and substrate is constructed; Step two, the three-dimensional model is imported into ansys software, the material properties and physical parameters of metal particles and substrate are set through Johnson-Cook constitutive model; the symmetry surface attribute is set, and finally the interaction parameters between metal particles and between metal particles and substrate are set, then the boundary conditions are set, and the mesh division of particles and substrate is carried out; the constitutive model of metal particles and substrate is obtained; the impact time and initial velocity are set, and the K file is obtained by solving; Step three, the obtained K file is imported into Lsdyna software, and the physical parameters of part of metal particles are modified to the physical parameters of alumina through Johnson Holmquist 2 constitutive model, and the initial velocity and temperature are set; Step four, the modified K file is submitted to the solver, the control parameters of the solution are adjusted, and the plastic strain results of the particles, the temperature change cloud diagram of the particle impact process and the damage degree results of the ceramic particles are outputted; Step five, the output results are analyzed to guide the spraying operation in practice; In the step two, the material properties of metal particles are set as aluminum, and the material properties of substrate are set as steel, and the physical parameters include material temperature, density, thermal conductivity, elastic modulus, thermal expansion coefficient, melting point, Poisson's ratio, specific heat, initial yield stress, material strain hardening modulus, hardening index, strain rate constant, temperature constant and Grunesien state equation coefficient; the interaction parameters are specifically set as the interaction force between particles and the interaction force between particles and substrate, and the friction coefficient between particles and the friction coefficient between particles and substrate are set.

2. The numerical simulation method of the spray deposition behavior of cermet composite coating with AI2O3 ceramic as the strengthening phase according to claim 1, characterized in that The three-dimensional model of metal particles and substrate is constructed by solidwork in the step one.

3. The numerical simulation method of the cermet composite coating spray deposition behavior with AI2O3 ceramic as the strengthening phase according to claim 2, characterized in that The three-dimensional model of metal particles and substrate is composed of 15 hemispherical particles and one cuboid substrate, and the 15 hemispherical particles are arranged in the order of 4, 5 and 6 from top to bottom; wherein the particle diameter is 20 microns, and the length, thickness and height of the substrate are 10 times, 5 times and 5 times of the particle diameter respectively.

4. The numerical simulation method of the cermet composite coating spray deposition behavior with AI2O3 ceramic as the strengthening phase according to claim 3, characterized in that In the step two, the boundary conditions are specifically set by setting the bottom of the substrate as fixed constraint.

5. A numerical simulation method of the spray deposition behavior of cermet composite coatings with AI2O3ceramics as strengthening phase according to claim 4, characterized in that In the step two, the mesh division of particles is carried out in the form of self-division, and the gradual mesh is used for the substrate, the mesh division of the contact area is relatively dense, and the mesh gradually becomes larger away from the contact area.

6. A numerical simulation method of the spray deposition behavior of cermet composite coatings with AI2O3ceramics as strengthening phase according to claim 5, characterized in that In the step three, the physical parameters of alumina include: density, elastic modulus, elastic limit, pressure under Hugoniot elastic limit, maximum static tensile strength, bulk modulus, pressure constant, damage strength constant, complete strength parameter, reference strain rate, energy loss factor, normalized strength parameter of complete material, normalized strength parameter of damaged material, strain rate effect parameter, damage factor, exponential damage factor and failure control parameter.

7. A numerical simulation method of the spray deposition behavior of cermet composite coatings with AI2O3ceramics as strengthening phase according to claim 6, characterized in that In the step three, for the value of elastic modulus which is not easy to obtain, the elastic modulus of Al2O3 at different temperatures is obtained by fitting the existing elastic modulus and temperature, which is: where E is the modulus of elasticity, and a1 and b1 are constants.

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