Collaborative design method of thermal physical property gradient distribution and braided structure of CMC materials

Abstract

The present invention discloses a collaborative design method for the gradient distribution of thermal property parameters of CMC materials and a braided structure. The method uses fluent to calculate the blade temperature field under non-uniform inflow conditions, sets the thermal property parameters of CMC materials by means of UDF, and extracts the fluid-solid convection heat transfer boundary of CMC turbine blades after the calculation is completed. Then, the COMSOL livelink for MATLAB tool is used to perform multi-objective optimization on the thermal property gradient distribution of CMC turbine blades under non-uniform inflow conditions. In order to reduce the optimization calculation cycle, only the solid model of the turbine blade is simulated and calculated during the optimization calculation process. The fluid-solid heat transfer boundary uses the fluid-solid convection heat transfer boundary extracted from the above fluent. Finally, an experiment is carried out to test the macroscopic equivalent thermal conductivity of CMC materials in all directions when doped with different contents of C nanotubes, and a two-way mapping relationship between the macroscopic equivalent thermal conductivity of CMC materials and the doping content of C nanotubes in CMC materials is established, so as to realize the optimization design of the collaborative braided structure of the thermal property gradient distribution of CMC material turbine blades.

Description

Technical Field

[0001] The invention belongs to the technical field of engineering thermophysics, and in particular relates to a collaborative design method of a CMC material thermal property parameter gradient distribution and a braided structure. Background Art

[0002] With the continuous development of aircraft engine technology, the performance indicators of engines are constantly improving, resulting in higher and higher requirements for materials in aircraft engines. In particular, the improvement of engine thrust-to-weight ratio has made the temperature of turbine inlet gas higher and higher. The combustion chamber temperature of modern aircraft engines is as high as 2200K. Even after the use of mixing and cooling technology, the temperature of the gas discharged from the combustion chamber exceeds 1600K. This has exceeded the heat resistance limit of metal material turbine blades. Therefore, ceramic matrix composites (Ceramic Matrix Composite, referred to as CMC materials) with good high temperature resistance and mechanical capabilities have become one of the most promising research directions.

[0003] Since the temperature of the high-temperature gas discharged from the combustion chamber is non-uniform, there is a large temperature gradient in the hot end parts of the aircraft engine. However, CMC materials are more sensitive to thermal stress due to the large difference in thermal expansion coefficients between the fiber and the matrix. NASA reported that when the turbine inlet temperature is higher than 1750K, the stress level of the CMC turbine components must be analyzed in detail and strict requirements must be met. This is because the internal stress caused by the temperature difference has a significant effect on the strength of the internal reinforcing fibers of the CMC. At present, most of the research on turbine blades under non-uniform inflow conditions is based on metal blades, while there are few studies based on the temperature field characteristics of CMC material turbine blades under non-uniform inflow conditions. However, according to the above analysis of the thermal properties of CMC materials and the temperature field characteristics results obtained under uniform inflow conditions, there must be differences between the temperature field characteristics of metal blades under non-uniform inflow conditions and the temperature field characteristics of CMC turbine blades under non-uniform inflow conditions. And because the macroscopic equivalent thermal conductivity of CMC materials is related to parameters such as material weaving method, weaving angle, fiber thermal conductivity, and matrix thermal conductivity, the thermal physical properties parameters of CMC material turbine blades have certain designability based on the internal microstructure of the material. This provides a certain space for optimizing the thermophysical property gradient of CMC turbine blades under non-uniform incoming flow conditions. As the exhaust temperature of the combustion chamber of modern aircraft engines is getting higher and higher, the exhaust temperature after mixing and cooling is getting closer and closer to the ultimate heat resistance temperature of CMC materials. Therefore, it is necessary to explore the internal heat transfer mechanism of woven structure CMC materials under non-uniform incoming flow heat loads, and to optimize the internal structure of CMC materials and the distribution of thermophysical property gradients of turbine blades to achieve the reduction of the maximum temperature and temperature gradient of CMC material turbine blades under non-uniform incoming flow heat loads. Summary of the invention

[0004] The present invention aims at the demand of efficient heat dissipation. Considering the heterogeneous and anisotropic characteristics of the braided CMC material, the traditional thermal analysis method based on homogeneous metal materials will hardly reflect the influence of the material structure characteristics on the internal heat transfer and temperature field distribution. Therefore, the optimization design of the internal structure of the CMC material and the thermal physical property gradient distribution of the turbine blade is carried out to reduce the maximum temperature and temperature gradient of the CMC material turbine blade under the non-uniform incoming heat load.

[0005] To achieve the above object, the technical solution adopted by the present invention is:

[0006] The collaborative design method of the gradient distribution of thermal physical property parameters of CMC materials and the braided structure includes the following steps:

[0007] Step 1: Use the fluent platform to calculate the temperature field parameters of the CMC turbine blades under non-uniform inflow conditions and extract the convective heat transfer coefficient parameters;

[0008] Step 2: Partition the CMC turbine blades and import the extracted fluid-solid heat transfer boundary conditions into the COMSOL platform;

[0009] Step 3: Use COMSOL livelink for MATLAB to perform multi-objective optimization on the thermal physical property gradient distribution of CMC turbine blades under non-uniform flow conditions;

[0010] Step 4: Experimentally test the macroscopic equivalent thermal conductivity of CMC materials containing different contents of C nanotubes in various directions, and establish a corresponding function between the macroscopic equivalent thermal conductivity and different contents of C nanotubes; calculate the C nanotube content at different positions of the CMC turbine blade based on the numerical value of the macroscopic equivalent thermal conductivity of different parts of the CMC turbine blade, and realize the coordinated design of the gradient distribution of the thermal physical properties of the CMC material and the braided structure.

[0011] Preferably, in step one, the fluent platform is used to calculate the temperature field of the CMC turbine blade under non-uniform inflow conditions, wherein the non-uniform inflow conditions are given in the form of hot spots at the turbine gas inlet, and the CMC turbine blade material settings are set in the form of udf. After the calculation, the surface temperature field parameters and convective heat transfer coefficient parameters of the CMC turbine blade are derived.

[0012] Preferably, in step 2, the CMC turbine blade is partitioned according to the UV line on the surface of the CMC turbine blade, the material thermal conductivity of each area is saved, and the CMC turbine blade surface temperature field parameters and convective heat transfer coefficient calculated by the fluent platform are imported into the COMSOL platform as input parameters through the interpolation method.

[0013] Preferably, in step three, the optimization algorithm for multi-objective optimization of the thermal physical property gradient distribution of CMC turbine blades under non-uniform incoming flow conditions uses the non-dominated genetic algorithm NSGA-Ⅱ, the optimization objectives are the maximum surface temperature of the CMC turbine blades and the maximum temperature gradient of the CMC turbine blades, and the optimization parameters are the thermal conductivity of the material in each area saved in step two.

[0014] Preferably, in step 4, for the experimental pieces used for the experiment, the percentage contents of C nanotubes are 0%, 3.75%, 7.5%, 11.25%, and 15%, respectively, and the experimental pieces are 2.5-dimensional CMC material pieces.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] In response to the demand for efficient heat dissipation of CMC turbine blades of aircraft engines, the present invention carries out an optimized design of the coordinated braiding structure of the thermophysical property gradient distribution of CMC material turbine blades based on the designability of the internal microstructure of the material, thereby reducing the maximum temperature and temperature gradient of the CMC turbine blades. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is the triaxial high pressure model of the present invention;

[0018] Figure 2 The triaxial high-pressure blade and upper and lower edge plate model of the present invention;

[0019] Figure 3 is the fluid domain model of the present invention;

[0020] Figure 4 This is a partition diagram of the guide vane model of the present invention. DETAILED DESCRIPTION

[0021] The present invention will be further described below with reference to Examples and Comparative Examples.

[0022] Example:

[0023] This example demonstrates the specific implementation steps of the collaborative design method of the gradient distribution of thermal physical property parameters of CMC materials and the braided structure. The model used in this example is Figure 1 As shown, the model is a triaxial high-pressure part model, including guide vanes and moving blades, i.e., upper and lower edge plates, of which there are 28 guide vanes and 57 moving blades.

[0024] To facilitate simulation calculation, the model is divided into periods in this example, and a fluid domain model for simulation is added to it. The dynamic blade, stationary blade, and upper and lower edge plate models used for simulation are shown in Figure 1. Figure 2As shown in the figure. The fluid domain includes the stationary domain of the guide vane part and the rotating domain of the moving blade part. The rotation angle of the periodic surface of the fluid domain of the moving blade part is 6.31578947°, and the rotation angle of the periodic surface of the fluid domain of the guide vane part is 12.857142857°. The fluid domain model is shown in the figure. Figure 3 shown.

[0025] In the material setting part, fluent udf is used to set the thermal conductivity of CMC blades to change with the blade shape. The fluid is air, and the boundary conditions are input based on the results obtained from the project experiment. The calculation begins.

[0026] After the calculation is completed. Since the subsequent optimization process is carried out in COMSOL, it is necessary to export the guide vane surface convective heat transfer boundary calculated in Fluent. This article uses the method of exporting the guide vane surface convective heat transfer coefficient. First, you need to customize a convective heat transfer coefficient parameter in Fluent. The definition method of this parameter is shown in Formula 1:

[0027]

[0028] Where h is the convective heat transfer coefficient on the outer surface of the guide vane, q is the convective heat flux, T is the fluid temperature near the guide vane, T 0 is the blade surface temperature. Since the maximum temperature of the blade outer surface is 1504K, this paper sets the outer surface fluid temperature of the blade cavity part to 1600K and the outer surface fluid temperature of the trailing edge part to 1400K. When calculating in COMSOL, the given convective heat transfer coefficients are required to be positive numbers, so after deriving the convective heat transfer coefficient of the guide vane outer surface, the derived data needs to be de-negated.

[0029] In order to reduce the amount of calculation, only the thermal properties of the solid domain guide vane model are optimized during the optimization calculation. In order to facilitate the setting of the material thermal properties during subsequent optimization, the guide vane model needs to be partitioned before the calculation. The partition results are as follows: Figure 4 As shown, the total number of guide vane partitions is 163.

[0030] In COMSOL, the material density, heat-melting properties of all partitions were set to be the same as those of the CMC material manufactured by Suzhou Sailifei Co., Ltd. The thermal conductivity was set to be isotropic, and the initial value of the thermal conductivity of all partitions was set to 20 W / (K·m).

[0031] The inner and outer surfaces of the guide vanes and the air film holes are set as convective heat transfer boundaries, and the convective heat transfer boundaries exported by FLUENT are imported by interpolation.

[0032] The tool used for optimization simulation in this example is COMSOL livelink for MATLAB. The optimization method used is non-dominated genetic algorithm (NSGA-Ⅱ). The optimization variable is the thermal conductivity of all partitions of the blade, and the optimization goal is to reduce the maximum temperature of the outer surface of the guide vane and reduce the maximum temperature gradient of the guide vane. The NSGA-Ⅱ algorithm is executed by MATLAB, and the optimization initial variables and optimization target calculation solutions are obtained by MATLAB controlling COMSOL calculation. The NSGA-Ⅱ multi-objective optimization algorithm technology is relatively mature and will not be introduced in detail.

[0033] In this example optimization, the population size is set to 70, the number of individual genes is 163, the thermal conductivity optimization range is 10-50W / (K·m), the maximum number of iterations is 100, the crossover ratio is set to 80%, and the mutation ratio is set to 30%.

[0034] After optimization by NSGA-Ⅱ algorithm, the maximum temperature of the outer surface of the blade is 1457.41K, and the maximum temperature gradient is 158402.52K / m. The maximum temperature of the outer surface of the guide vane is reduced by 45.4318K compared with 1502.85K before optimization. The maximum temperature gradient is reduced by 87024.1006K / m compared with 245426.62K / m before optimization. The temperature gradient after optimization is reduced by 35.458% compared with the temperature gradient value before optimization.

[0035] Finally, experiments were carried out to test the macroscopic equivalent thermal conductivity of 2.5-dimensional CMC materials in all directions when the doping percentage of C nanotubes was 0%, 3.75%, 7.5%, 11.25%, and 15%. A bidirectional mapping relationship between the macroscopic equivalent thermal conductivity of CMC materials and the C nanotube doping content of CMC materials was established. The doped C nanotube content in different regions of CMC turbine blades was deduced based on the macroscopic equivalent thermal conductivity results of CMC turbine blades in different regions obtained by the above optimization, and the optimized design of the coordinated weaving structure of the thermal physical property gradient distribution of CMC material turbine blades was achieved.

[0036] In summary, the present invention aims at the demand for efficient heat dissipation of CMC turbine blades of aircraft engines, and based on the designability of the internal microstructure of the material, optimizes the design of the internal structure of the CMC material and the gradient distribution of the thermal properties of the turbine blades, slightly reduces the maximum temperature of the outer surface of the CMC turbine blades, and greatly reduces the temperature gradient of the CMC turbine blade materials. Finally, experiments are carried out to test the macro equivalent thermal conductivity of CMC materials in all directions when doped with different contents of C nanotubes, establish a two-way mapping relationship between the macro equivalent thermal conductivity of CMC materials and the doping content of C nanotubes in CMC materials, and infer the content of C nanotubes doped in different regions of CMC turbine blades based on the results of the macro equivalent thermal conductivity of CMC turbine blades in different regions obtained by the above optimization, so as to achieve the optimization design of the coordinated braiding structure of the thermal property gradient distribution of CMC material turbine blades.

[0037] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A collaborative design method for the gradient distribution of thermal physical property parameters of CMC materials and the braided structure, characterized in that: The following steps are involved: Step 1: Use the fluent platform to calculate the temperature field parameters of the CMC turbine blades under non-uniform inflow conditions and extract the convective heat transfer coefficient parameters; Step 2: Partition the CMC turbine blades and import the extracted fluid-solid heat transfer boundary conditions into the COMSOL platform; Step 3: Use COMSOL livelink for MATLAB to perform multi-objective optimization on the thermal physical property gradient distribution of CMC turbine blades under non-uniform flow conditions; Step 4: Test the macroscopic equivalent thermal conductivity of CMC materials containing different contents of C nanotubes in all directions through experiments, and establish the corresponding relationship function between the macroscopic equivalent thermal conductivity and different contents of C nanotubes; calculate the C nanotube content at different positions of the CMC turbine blade according to the numerical value of the macroscopic equivalent thermal conductivity of different parts of the CMC turbine blade, and realize the coordinated design of the gradient distribution of the thermal physical property parameters of the CMC material and the braided structure; In step 1, the fluent platform is used to calculate the temperature field of the CMC turbine blade under non-uniform flow conditions, where the non-uniform flow conditions are given in the form of hot spots at the turbine gas inlet, and the CMC turbine blade material settings are set in the form of udf. After the calculation is completed, the surface temperature field parameters and convection heat transfer coefficient parameters of the CMC turbine blade are derived; In step 2, the CMC turbine blades are partitioned according to the UV lines on the surface of the CMC turbine blades, the thermal conductivity of the materials in each area is saved, and the surface temperature field parameters and convection heat transfer coefficient of the CMC turbine blades calculated by the fluent platform are imported into the COMSOL platform as input parameters through the interpolation method; In step three, the optimization algorithm for multi-objective optimization of the thermal physical property gradient distribution of CMC turbine blades under non-uniform inflow conditions uses the non-dominated genetic algorithm NSGA-Ⅱ. The optimization objectives are the maximum surface temperature of the CMC turbine blades and the maximum temperature gradient of the CMC turbine blades. The optimization parameters are the thermal conductivity of the materials in each area saved in step two.

2. The collaborative design method of the CMC material thermal property parameter gradient distribution and braided structure according to claim 1, characterized in that: In step 4, for the experimental pieces used for the experiment, the percentage contents of C nanotubes are 0%, 3.75%, 7.5%, 11.25%, and 15%, respectively, and the experimental pieces are 2.5-dimensional CMC material pieces.

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