阅读说明：本技术 一种热障涂层数值重构模型测试方法和装置 (Thermal barrier coating numerical reconstruction model testing method and device ) 是由 王玉璋 龙芸 陈小虎 翁一武 于 2020-06-02 设计创作，主要内容包括：本发明涉及一种热障涂层数值重构模型测试方法,具体包括以下步骤：步骤S1：建立热障涂层模拟区域,预设热障涂层的系统结构；步骤S2：搭建陶瓷层,将致密8mol％氧化钇稳定氧化锆作为陶瓷层的第一生长相,其生长核根据生成概率随机布置在陶瓷层中；步骤S3：生长核根据生长概率进行生长,直到孔隙率达到预设体积分数；步骤S4：搭建粘结层、基地和冷却气膜,输出基础涂层网格文件进入可视化软件,生成热障涂层数值重构模型；步骤S5：根据预设的裂纹变形率和颗粒变形率生成对应的缺陷结构,并通过基于耦合双分布函数的格子玻尔兹曼方法计算模型的有效热导率。与现有技术相比,本发明具有真实有效地表征涂层内部结构形貌特征、使用成本较低等优点。(The invention relates to a thermal barrier coating numerical reconstruction model test method, which specifically comprises the following steps: step S1: establishing a thermal barrier coating simulation area, and presetting a system structure of a thermal barrier coating; step S2: building a ceramic layer, taking compact 8 mol% yttria-stabilized zirconia as a first growth phase of the ceramic layer, and randomly arranging growth nuclei in the ceramic layer according to the generation probability; step S3: growing the growth nucleus according to the growth probability until the porosity reaches a preset volume fraction; step S4: building a bonding layer, a base and a cooling air film, outputting a basic coating grid file to enter visual software, and generating a thermal barrier coating numerical reconstruction model; step S5: and generating a corresponding defect structure according to a preset crack deformation rate and a preset particle deformation rate, and calculating the effective thermal conductivity of the model by a lattice boltzmann method based on a coupling double distribution function. Compared with the prior art, the method has the advantages of truly and effectively representing the internal structural morphology characteristics of the coating, low use cost and the like.)

1. A thermal barrier coating numerical reconstruction model test method is characterized by comprising the following steps:

step S1: establishing a thermal barrier coating simulation area, and presetting a system structure of the thermal barrier coating, wherein the system structure comprises the number of coating layers and a defect structure;

step S2: building a ceramic layer on the top of the thermal barrier coating, taking compact 8 mol% yttria-stabilized zirconia as a first growth phase of the ceramic layer, and randomly arranging growth nuclei of a plurality of first growth phases in the ceramic layer according to corresponding generation probabilities;

step S3: the growth nuclei grow towards a plurality of directions according to the growth probability of the growth nuclei until the porosity of the ceramic layer reaches a preset volume fraction;

step S4: building a bonding layer, a base and a cooling air film of the thermal barrier coating on the ceramic layer after growth is completed, outputting a basic coating grid file of the thermal barrier coating, and entering visual software to generate a thermal barrier coating numerical reconstruction model;

step S5: the thermal barrier coating numerical reconstruction model is in a digital grid form, a corresponding defect structure is generated according to the crack deformation rate and the particle deformation rate preset by the system structure, and the effective thermal conductivity of the thermal barrier coating numerical reconstruction model is calculated by a lattice boltzmann method based on a coupling double distribution function.

2. The method for testing the numerical reconstruction model of the thermal barrier coating according to claim 1, wherein the probability of generating the growth nuclei is smaller than the predetermined volume fraction.

3. The method for testing the numerical reconstruction model of the thermal barrier coating according to claim 1, wherein in step S5, the crack defect is generated by the crack deformation rate, and the corrosion defect is generated by the particle deformation rate.

4. The method for testing the numerical reconstruction model of the thermal barrier coating according to claim 3, wherein the crack defect is formed by constructing a two-dimensional crack cross section on a cross section of the ceramic layer, and then performing three-dimensional growth of a longitudinal crack according to the crack cross section, wherein the shape of the crack cross section randomly changes in an ellipse, and the growth point of the crack cross section satisfies the following formula:

wherein, F_cAs the crack deformation ratio, (x)₁,y₁) Coordinates of a growth point of the cross section of the crack, and satisfies:

wherein a and b are process variables, a > b > 0.

5. The method for testing the numerical reconstruction model of the thermal barrier coating according to claim 3, wherein the particles of the corrosion defects are grown in the spheroidal body, and the growing points satisfy the following formula:

wherein (x)₂,y₂Z) coordinates of the growth point of the grain corroding the defect, F_pThe particle deformation ratio is defined as r being the equivalent particle diameter and r > 0.

6. The method for testing the numerical reconstruction model of the thermal barrier coating according to claim 1, wherein the double distribution functions calculated by the lattice boltzmann method of the coupled double distribution function are specifically a density distribution function and a temperature distribution function, and the specific formula is as follows:

wherein r is a coordinate vector; e.g. of the type_iA direction vector being a discrete velocity; t is time;_tis the time step; tau is_fIs the fluid dimensionless relaxation time; f. of_i(r, t) and f_i ^eq(r, t) are a particle density distribution function and an equilibrium state density distribution function corresponding to the i direction, respectively; tau is_TDimensionless relaxation time for the temperature field; t is_iAnd T_i ^eq(x, t) are a temperature distribution function corresponding to the i direction and an equilibrium temperature distribution function, respectively.

7. The method for testing the numerical reconstruction model of the thermal barrier coating according to claim 6, wherein the calculation formula of the macroscopic parameters of the numerical reconstruction model of the thermal barrier coating is as follows:

wherein rho is the density of the thermal barrier coating numerical reconstruction model, u is the speed of particles in the thermal barrier coating numerical reconstruction model, and T is the temperature of the thermal barrier coating numerical reconstruction model.

8. The method for testing the numerical reconstruction model of the thermal barrier coating according to claim 7, wherein the calculation formula of the effective thermal conductivity of the numerical reconstruction model of the thermal barrier coating is as follows:

wherein λ is_eFor effective thermal conductivity, as the coating thickness, q is the steady state heat flow through the coating of thickness.

9. An apparatus for reconstructing a model test method based on thermal barrier coating values, comprising a memory and a processor, wherein the method is stored in the memory in the form of a computer program and executed by the processor, and when executed implements the following steps:

step S1: establishing a thermal barrier coating simulation area, and presetting a system structure of the thermal barrier coating, wherein the system structure comprises the number of coating layers and a defect structure;

step S2: building a ceramic layer on the top of the thermal barrier coating, taking compact 8 mol% yttria-stabilized zirconia as a first growth phase of the ceramic layer, and randomly arranging growth nuclei of a plurality of first growth phases in the ceramic layer according to corresponding generation probabilities;

step S3: the growth nuclei grow towards a plurality of directions according to the growth probability of the growth nuclei until the porosity of the ceramic layer reaches a preset volume fraction;

step S4: building a bonding layer, a base and a cooling air film of the thermal barrier coating on the ceramic layer after growth is completed, outputting a basic coating grid file of the thermal barrier coating, and entering visual software to generate a thermal barrier coating numerical reconstruction model;

step S5: the thermal barrier coating numerical reconstruction model is in a digital grid form, a corresponding defect structure is generated according to the crack deformation rate and the particle deformation rate preset by the system structure, and the effective thermal conductivity of the thermal barrier coating numerical reconstruction model is calculated by a lattice boltzmann method based on a coupling double distribution function.

10. The device of claim 9, wherein the probability of generating the growth nuclei is smaller than the predetermined volume fraction.

Technical Field

The invention relates to the technical field of porous media, in particular to a method and a device for testing a numerical reconstruction model of a thermal barrier coating.

Background

The thermal barrier coating coated on the surface of the high-temperature component has good thermal insulation performance. With the continuous improvement of the requirement on the combustion efficiency of the gas turbine, the temperature of the gas is also greatly improved, which provides a serious challenge for the thermal barrier coating.

Thermal barrier coatings, which are typically composed of a substrate, a bond coat, and a ceramic layer, are a typical multilayer structure system. Due to the preparation process, a certain amount of pores are inevitably formed inside the ceramic layer of the current thermal barrier coating. Meanwhile, in the service process of the thermal barrier coating, an oxide layer is formed between the ceramic layer and the bonding layer, and large cracks are generated inside the ceramic layer. The thermal barrier coating has a complex microstructure and is in a severe service environment, and the thermal barrier coating has huge physical, thermal and mechanical property differences among layers, so that the thermal barrier coating cracks and peels under unpredictable conditions to cause failure of the coating. The failure types of the thermal barrier coating are mainly divided into the following five types: high temperature oxidation, high temperature sintering, thermal stress mismatch, high temperature corrosion and particle erosion. It is also important to understand the structural changes at the microscopic level of the coating to remove macroscopic flaking and volume changes, despite the above failure modes of the coating. Therefore, qualitative, especially quantitative, description of the relevant properties of the different microstructures in the coating and the constitutive relations determining these properties is essential to establish a reliable and accurate coating microstructure model. These microstructures will have a direct impact on the thermal, mechanical and physical properties of the coating, such as thermal conductivity, elastic modulus, density and hardness. The microstructure characteristics of the coating are quantitatively depicted, so that the method has important significance on the performance research of the coating in practical application. However, the microstructure of the coating is complex in shape, large in size variation span and has certain random distribution, and accurate description is difficult. The current research work mainly focuses on observing and statistically analyzing the morphological characteristics of the pores and the like of the coating by adopting a quantitative metallographic analysis means, but the experimental observation and the appearance description cannot comprehensively and quantitatively analyze the internal mechanism which plays a role in determining the apparent properties of the thermal barrier coating by a series of factors such as porosity, the morphological characteristics of the pores, the interaction among the pores and the like. Therefore, it is necessary to digitize the microstructure of the coating from a microscale, establish a reconstruction model capable of reflecting the microstructure properties of the coating, and study the coupling heat exchange rules inside the coating and between the coating and the gas film through a numerical means on the basis.

Since the thermal barrier coating belongs to the porous medium, a great deal of researchers have developed more intensive research on a numerical reconstruction method of the porous medium. The methods are mainly classified into a reconstruction method based on image recognition, a reconstruction method based on a conceptual model, and a reconstruction method based on statistics. The image recognition model is closest to the actual pore morphology because of the characteristics of high precision, no damage to samples and the like. Generally, a digital scanning technology such as X-ray and CT scanning is used to digitally image a porous medium, and a structural grid composed of a plurality of pixels is generated through noise processing and threshold judgment. The grid may be visualized by post-processing software. But it is expensive and difficult to be widely used due to its reliance on high-resolution imaging devices and the development of image processing techniques. The conceptual model abstracts the pores in the porous medium into a sphere, an ellipsoid, a fusiform and the like, so that the thermodynamic and chemical characteristics and related mechanisms of the porous medium can be qualitatively or semi-quantitatively explained more flexibly. However, the extracted pore characteristics are too ideal, and the calculation of the actual problem has large deviation. The statistical model is a model established based on a two-phase material statistical law, wherein solid skeleton parameters and gas pore parameters can be obtained by a mercury intrusion method, an adsorption method, a sedimentation method and the like. The model has better similarity with a real pore. However, due to the multi-solution of the statistical model, a large amount of grid independence verification and statistical mean value calculation are needed to obtain a more accurate calculation result. The reconstruction method is often used for reconstructing porous media such as rocks and soil. In addition, most of the existing pore models only study the influence of the numerical change of the porosity on the coating performance, and rarely consider the change of the degradation of the thermodynamic performance of the coating caused by the change of the size, the shape, the position and the like of the pores. In the few pore models describing pore morphology, pores are directly simplified into spherical, ellipsoidal or fusiform shapes with uniform distribution and equal size. This simplistic assumption has a large deviation from reality and is not universally applicable. Meanwhile, the pore models cannot reflect the complex structure of the thermal barrier coating after failure in the high-temperature service process.

Disclosure of Invention

The invention aims to provide a thermal barrier coating numerical reconstruction model test method and a thermal barrier coating numerical reconstruction model test device for overcoming the defects of high cost and large deviation from the actual situation in the prior art.

The purpose of the invention can be realized by the following technical scheme:

a thermal barrier coating numerical reconstruction model test method specifically comprises the following steps:

step S1: establishing a thermal barrier coating simulation area, and presetting a system structure of the thermal barrier coating, wherein the system structure comprises the number of coating layers and a defect structure;

step S2: building a ceramic layer on the top of the thermal barrier coating, taking compact 8 mol% yttria-stabilized zirconia as a first growth phase of the ceramic layer, and randomly arranging growth nuclei of a plurality of first growth phases in the ceramic layer according to corresponding generation probabilities;

step S3: the growth nuclei grow towards a plurality of directions according to the growth probability of the growth nuclei until the porosity of the ceramic layer reaches a preset volume fraction;

step S4: building a bonding layer, a base and a cooling air film of the thermal barrier coating on the ceramic layer after growth is completed, outputting a basic coating grid file of the thermal barrier coating, and entering visual software to generate a thermal barrier coating numerical reconstruction model;

step S5: the thermal barrier coating numerical reconstruction model is in a digital grid form, a corresponding defect structure is generated according to the crack deformation rate and the particle deformation rate preset by the system structure, and the effective thermal conductivity of the thermal barrier coating numerical reconstruction model is calculated by a lattice boltzmann method based on a coupling double distribution function.

The generation probability of the growth nuclei is smaller than the preset volume fraction.

Different data points are adopted in the thermal barrier coating numerical reconstruction model to represent different structures.

In the step S5, the crack defect is generated by the crack deformation rate, and the corrosion defect is generated by the particle deformation rate, and the two defect structures may exist separately or simultaneously.

Furthermore, the crack defect firstly forms a two-dimensional crack cross section on one cross section of the ceramic layer, and then carries out longitudinal crack three-dimensional growth according to the crack cross section, the shape of the crack cross section randomly changes in an ellipse, and the growth point of the crack defect meets the following formula:

wherein, F_cAs the crack deformation ratio, (x)₁,y₁) Coordinates of a growth point of the cross section of the crack, and satisfies:

wherein a and b are process variables, a > b > 0.

Further, the particles of corrosion defects finish growing in the spheroids, and the growing points satisfy the following formula:

wherein (x)₂,y₂Z) coordinates of the growth point of the grain corroding the defect, F_pThe particle deformation ratio is defined as r being the equivalent particle diameter and r > 0.

The double distribution functions calculated by the lattice boltzmann method of the coupled double distribution functions are specifically a density distribution function and a temperature distribution function, the density distribution function is used for simulating a velocity field, and the temperature field is solved through the temperature distribution function, and the specific formula is as follows:

wherein r is a coordinate vector; e.g. of the type_iA direction vector being a discrete velocity; t is time;_tis the time step; tau is_fIs the fluid dimensionless relaxation time; f. of_i(r, t) and f_i ^eq(r, t) are a particle density distribution function and an equilibrium state density distribution function corresponding to the i direction, respectively; tau is_TDimensionless relaxation time for the temperature field; t is_iAnd T_i ^eq(x, t) are a temperature distribution function corresponding to the i direction and an equilibrium temperature distribution function, respectively.

Further, a D3Q19 discrete velocity model is adopted, and after collision and migration of fluid particles, the macroscopic parameters of the thermal barrier coating numerical reconstruction model are obtained as follows:

wherein rho is the density of the thermal barrier coating numerical reconstruction model, u is the speed of particles in the thermal barrier coating numerical reconstruction model, and T is the temperature of the thermal barrier coating numerical reconstruction model.

Further, the calculation formula of the effective thermal conductivity of the thermal barrier coating numerical reconstruction model is as follows:

wherein λ is_eFor effective thermal conductivity, as the coating thickness, q is the steady state heat flow through the coating of thickness.

An apparatus for reconstructing a model testing method based on thermal barrier coating values, comprising a memory and a processor, the method being stored in the memory in the form of a computer program and being executed by the processor, and when executed performing the steps of:

step S1: establishing a thermal barrier coating simulation area, and presetting a system structure of the thermal barrier coating, wherein the system structure comprises the number of coating layers and a defect structure;

step S2: building a ceramic layer on the top of the thermal barrier coating, taking compact 8 mol% yttria-stabilized zirconia as a first growth phase of the ceramic layer, and randomly arranging growth nuclei of a plurality of first growth phases in the ceramic layer according to corresponding generation probabilities;

step S3: the growth nuclei grow towards a plurality of directions according to the growth probability of the growth nuclei until the porosity of the ceramic layer reaches a preset volume fraction;

step S4: building a bonding layer, a base and a cooling air film of the thermal barrier coating on the ceramic layer after growth is completed, outputting a basic coating grid file of the thermal barrier coating, and entering visual software to generate a thermal barrier coating numerical reconstruction model;

step S5: the thermal barrier coating numerical reconstruction model is in a digital grid form, a corresponding defect structure is generated according to the crack deformation rate and the particle deformation rate preset by the system structure, and the effective thermal conductivity of the thermal barrier coating numerical reconstruction model is calculated by a lattice boltzmann method based on a coupling double distribution function.

Compared with the prior art, the method takes a compact solid phase in a thermal barrier coating system as a growth phase, builds a ceramic layer according to the growth probability, combines with other functional layers and enters a basic coating grid file into visual software to generate a thermal barrier coating numerical reconstruction model, and generates a corresponding defect structure according to the preset crack deformation rate and the preset particle deformation rate to perform the related experiment of the thermal barrier coating. The numerical reconstruction model of the thermal barrier coating has higher matching degree with the actual coating, can truly and effectively represent the internal structural morphology characteristics of the coating, has lower use cost and is suitable for large-batch coating research.

Drawings

FIG. 1 is a schematic flow diagram of the present invention;

FIG. 2 is a schematic structural diagram of a numerical reconstruction model of a thermal barrier coating according to the present invention;

FIG. 3 is a schematic structural diagram of a base ceramic layer according to the present invention, wherein FIG. 3(a) is a 3D complete structural diagram of the base ceramic layer, FIG. 3(b) is a schematic cross-sectional diagram of the base ceramic layer, and FIG. 3(c) is a schematic pore-filling diagram of the base ceramic layer;

FIG. 4 is a structural schematic view of a crack defect of the present invention;

FIG. 5 is a schematic view of a corrosion defect according to the present invention;

fig. 6 is a graph comparing numerical simulations and experiments showing the effective thermal conductivity of the coating of the present invention as a function of porosity.

Detailed Description

The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.

As shown in fig. 1, a thermal barrier coating numerical reconstruction model test method is low in use cost, can truly and effectively represent the internal structural morphology characteristics of a coating, and specifically includes the following steps:

step S1: establishing a thermal barrier coating simulation area, and presetting a system structure of a thermal barrier coating, wherein the system structure comprises the number of coating layers and a defect structure;

step S2: building a ceramic layer on the top of the thermal barrier coating, taking compact 8 mol% yttria-stabilized zirconia as a first growth phase of the ceramic layer, and randomly arranging a plurality of growth nuclei of the first growth phase in the ceramic layer according to corresponding generation probability;

step S3: growing the growth nuclei in multiple directions according to the growth probability until the porosity of the ceramic layer reaches a preset volume fraction;

step S4: building a bonding layer, a base and a cooling air film of the thermal barrier coating on the ceramic layer after growth is completed, outputting a basic coating grid file of the thermal barrier coating, and entering visual software to generate a numerical reconstruction model of the thermal barrier coating;

step S5: the thermal barrier coating numerical reconstruction model is in a digital grid form, a corresponding defect structure is generated according to a crack deformation rate and a particle deformation rate preset by a system structure, and the effective thermal conductivity of the thermal barrier coating numerical reconstruction model is calculated by a lattice Boltzmann method based on a coupling double distribution function.

The generation probability of the growth nucleus is less than the preset volume fraction.

Fig. 2 shows a numerical reconstruction model of a thermal barrier coating with crack defects, wherein the thicknesses of the ceramic layer and the bonding layer are between 100-500 μm, the thickness of the substrate is more than 3mm, and the alloy thermal conductivity of the substrate is far larger than that of the ceramic layer and the bonding layer, so that only the ceramic layer and the bonding layer structure is generally considered in the heat transfer calculation.

Different data points are adopted in the thermal barrier coating numerical reconstruction model to represent different structures, a compact framework material in a ceramic layer is composed of a number 1, and a pore structure in the ceramic layer is represented by a number 0.

Air is filled in the pores, and as shown in fig. 3, thermal barrier coating numerical reconstruction models with different porosities are generated according to a preset system structure.

In step S5, a crack defect is generated by the crack deformation ratio, and a corrosion defect is generated by the particle deformation ratio, and both defect structures may exist separately or simultaneously.

Furthermore, a crack cross section with a two-dimensional shape is constructed on one cross section of the ceramic layer for crack defects, then the longitudinal crack three-dimensional growth is carried out according to the crack cross section, the shape of the crack cross section randomly changes in an ellipse, and the growth point of the crack cross section meets the following formula:

wherein, F_cAs the crack deformation ratio, (x)₁,y₁) Coordinates of a growth point of the cross section of the crack, and satisfies:

wherein a and b are process variables, a > b > 0.

The crack deformation rate represents the approximation degree of the cross section shape of the vertically grown crack and the ellipse, and the closer the crack deformation rate is to 0, the smaller the deformation is, and the closer the cross section shape of the crack is to the ellipse. As shown in FIG. 4, is F_cWhen the ceramic layer containing the cracks is reconstructed as a model at 0.2, the cross section of the cracks is approximately elliptical in shape.

The corrosive salt medium is fused and deposited on the surface of the coating under the high-temperature condition, some corrosive salt medium permeates into the coating gaps, and then granular, blocky and short rod-shaped corrosion products are generated, and the shapes of the substances can be simplified into spheres corresponding to corrosion defect granules. The particles with corrosion defects finish growing in the spheroids, and the growing points meet the following formula:

wherein (x)₂,y₂Z) coordinates of the growth point of the grain corroding the defect, F_pThe particle deformation ratio is defined as r being the equivalent particle diameter and r > 0.

The particle deformation rate represents the approximation degree of the generated particle morphology and the sphere, and the closer the particle deformation rate is to 0, the smaller the generated deformation is, and the closer the particle morphology is to the sphere. The reconstructed particles that produced spheroids at different particle deformation rates are shown in figure 5.

The double distribution functions calculated by a lattice boltzmann method of the coupled double distribution functions are specifically density distribution functions and temperature distribution functions, the density distribution functions are used for simulating a speed field, the temperature field is solved through the temperature distribution functions, and the specific formula is as follows:

wherein r is a coordinate vector; e.g. of the type_iA direction vector being a discrete velocity; t is time;_tis the time step; tau is_fIs the fluid dimensionless relaxation time; f. of_i(r, t) and f_i ^eq(r, t) are a particle density distribution function and an equilibrium state density distribution function corresponding to the i direction, respectively; tau is_TDimensionless relaxation time for the temperature field; t is_iAnd T_i ^eq(x, t) are a temperature distribution function corresponding to the i direction and an equilibrium temperature distribution function, respectively.

Further, a D3Q19 discrete velocity model is adopted, and after collision and migration of fluid particles, the macroscopic parameters of the thermal barrier coating numerical reconstruction model are obtained as follows:

wherein rho is the density of the thermal barrier coating numerical reconstruction model, u is the speed of particles in the thermal barrier coating numerical reconstruction model, and T is the temperature of the thermal barrier coating numerical reconstruction model.

Further, the calculation formula of the effective thermal conductivity of the thermal barrier coating numerical reconstruction model is as follows:

wherein λ is_eFor effective thermal conductivity, as the coating thickness, q is the steady state heat flow through the coating of thickness.

As shown in fig. 6, the thermal barrier coating numerical reconstruction model with different porosities built by the invention is compared with the effective thermal conductivity of the coating with the same porosity in the experiment, the thermal conductivity distribution curve coincidence rate is higher, and the relative error is within 5%, so that the thermal barrier coating numerical reconstruction model built by the invention can effectively replace the real thermal barrier coating to carry out the experiment, and has higher authenticity and accuracy.

An apparatus for reconstructing a model test method based on thermal barrier coating values, comprising a memory and a processor, the method being stored in the memory in the form of a computer program and being executed by the processor, and when executed performing the steps of:

step S1: establishing a thermal barrier coating simulation area, and presetting a system structure of a thermal barrier coating, wherein the system structure comprises the number of coating layers and a defect structure;

step S2: building a ceramic layer on the top of the thermal barrier coating, taking compact 8 mol% yttria-stabilized zirconia as a first growth phase of the ceramic layer, and randomly arranging a plurality of growth nuclei of the first growth phase in the ceramic layer according to corresponding generation probability;

step S3: growing the growth nuclei in multiple directions according to the growth probability until the porosity of the ceramic layer reaches a preset volume fraction;

step S4: building a bonding layer, a base and a cooling air film of the thermal barrier coating on the ceramic layer after growth is completed, outputting a basic coating grid file of the thermal barrier coating, and entering visual software to generate a numerical reconstruction model of the thermal barrier coating;

step S5: the thermal barrier coating numerical reconstruction model is in a digital grid form, a corresponding defect structure is generated according to a crack deformation rate and a particle deformation rate preset by a system structure, and the effective thermal conductivity of the thermal barrier coating numerical reconstruction model is calculated by a lattice Boltzmann method based on a coupling double distribution function.

In addition, it should be noted that the specific embodiments described in the present specification may have different names, and the above descriptions in the present specification are only illustrations of the structures of the present invention. All equivalent or simple changes in the structure, characteristics and principles of the invention are included in the protection scope of the invention. Various modifications or additions may be made to the described embodiments or methods may be similarly employed by those skilled in the art without departing from the scope of the invention as defined in the appending claims.