Ablation heat transfer simulation method considering microstructure evolution for resin-based material

Abstract

The invention discloses a resin-based material ablation heat transfer simulation method considering microstructure evolution, which comprises the following steps of: cutting material samples from different positions of a pneumatically heated material to obtain a material density value, calculating to obtain a pyrolysis degree, further obtaining matrix physical properties under different pyrolysis degrees, and simultaneously observing the microstructure of each material sample to obtain the thermal conductivity of the resin-based material. According to the method, the microstructure morphology, the lap joint relation between microstructure components and the mutual position relation are obtained, the evolution law of the microstructure in the aerodynamic heating process is obtained according to the statistical result, the morphology observation result of the microstructure is combined, a finite element model is established, and boundary conditions are loaded for solving. And carrying out fitting on the equivalent heat conductivity relationships corresponding to the different pyrolysis degrees to obtain a fitting relational expression of the heat conductivity of the resin-based material along with the change of the pyrolysis degrees so as to replace a corrected linear interpolation relational expression in the ablation heat transfer calculation model of the resin-based material, and calculating the ablation heat transfer of the resin-based material according to the fitting relational expression. Therefore, the ablation heat transfer model of the resin-based material is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of aircraft thermal protection, and in particular relates to an ablation heat transfer simulation method for resin-based materials taking microstructure evolution into consideration. Background Art

[0002] The development of thermal protection technology for aircraft has gone through several stages. Initially, it was heat sink-type thermal protection, which used metal heat sinks to absorb heat to block heat. However, with the severity of aerodynamic heating, it could no longer meet the requirements. Later, ablative thermal protection was developed, which used the evaporation, melting, sublimation and chemical reactions of materials to absorb heat. Ablative thermal protection has been widely used in re-entry satellites, spacecraft, etc. due to its efficient thermal protection effect. Ablative thermal protection is still widely used in returning satellites, spacecraft and other aircraft due to its simple form and good thermal protection effect and high reliability. In order to improve the thermal insulation effect while taking into account the thermal protection efficiency, nano-resin-based thermal protection materials have been developed. The main material is that the resin matrix contains nano-scale pores, which significantly reduces the thermal conductivity and density of the material without affecting the thermal protection effect and mechanical strength. It is then compounded with fibers to obtain a resin-based thermal protection material with nano-scale pores.

[0003] At present, the research on the ablation and heat transfer mechanism of homogeneous materials is relatively mature. The macroscopic thermochemical ablation theory, heat transfer control equation, surface energy conservation and mass conservation equation, loading boundary conditions are used to solve the thermal response mechanism of the material over time, including internal temperature distribution, ablation recession, and changes in carbonization layer thickness over time. The physical properties and microstructure of the material will change significantly at different stages of the pyrolysis process. There is a lack of effective experimental means for testing the physical parameters such as thermal conductivity of the material during the pyrolysis process, and there are few simulation studies. Most tests still focus on the physical parameters of the original material after complete carbonization. At different stages of the pyrolysis process, the change in the thermal conductivity of the material is usually calculated using a modified linear interpolation method. The correction coefficient is corrected by ground wind tunnel tests, which is a semi-empirical formula. Summary of the invention

[0004] The technology of the present invention solves the problem: Overcoming the shortcomings of the prior art, providing an ablation heat transfer simulation method for resin-based materials taking into account microstructure evolution, and solving the problem that the prior art cannot effectively predict the thermal conductivity parameters of resin-based heat-resistant materials at different stages of the pyrolysis process.

[0005] In order to solve the above technical problems, the present invention discloses an ablation heat transfer simulation method for resin-based materials considering microstructure evolution, comprising:

[0006] Step 1, cutting material samples at different positions of the resin-based heat-resistant material after the ground wind tunnel test to obtain material samples with different degrees of pyrolysis under aerodynamic heating conditions, which are numbered A1 to A6 in sequence; measuring the weight and size of each material sample to obtain the density of each material sample; wherein the material samples A1 to A6 correspond to the A1 to A6 layers of the resin-based heat-resistant material after the ground wind tunnel test; the A1 layer is the surface layer, which is a completely carbonized layer; and the A6 layer is the original layer;

[0007] Step 2, according to the density of each material sample, the thermal decomposition degree of each material sample is calculated; and according to the thermal decomposition degree of each material sample, in combination with the parallel model, the thermal conductivity of the resin matrix in each material sample is calculated;

[0008] Step 3, performing microstructure scanning observation on each material sample to obtain a microstructure image of each material sample;

[0009] Step 4, according to the microstructure image of each material sample, the nanoscale pores, micron-scale pores, and fiber sizes are statistically analyzed to obtain the nanoscale porosity, nanoscale pore size distribution law, micron-scale porosity, micron-scale pore size distribution law, and fiber size distribution law of each material sample;

[0010] Step 5, determining the size of the control body according to the range of nanoscale pores, microscale pore sizes and fiber sizes; wherein the control body is used to simulate the resin-based heat-resistant material;

[0011] Step 6, according to the nanoscale porosity, nanoscale pore size distribution law, microscale porosity, microscale pore size distribution law and fiber size distribution law of each material sample, combined with the thermal conductivity of the resin matrix in each material sample, a finite element model is established at different positions in the control body;

[0012] Step 7, dividing the volume mesh according to the finite element model established in step 6;

[0013] Step 8, applying temperature gradient boundary conditions and periodic boundary conditions to the finite element model after the volume meshing in step 7, and performing post-processing to obtain the equivalent thermal conductivity of the control volume A1 to A6 layers;

[0014] Step 9, according to the thermal decomposition degree obtained in step 2 and the equivalent thermal conductivity of the control body A1 to A6 layers obtained in step 8, fitting is performed to obtain a relationship between the thermal conductivity of the resin-based heat-resistant material and the thermal decomposition degree;

[0015] Step 10, using the relationship between the thermal conductivity of the resin-based heat-resistant material and the degree of pyrolysis obtained by fitting in step 9 to replace the modified linear interpolation method used in the original ablation heat transfer calculation, thereby obtaining an ablation heat transfer simulation scheme for the resin-based material taking into account the microstructure evolution;

[0016] Step 11, based on the ablation heat transfer simulation scheme of the resin-based material considering the microstructure evolution obtained in step 10, carry out the ablation heat transfer simulation of the resin-based material considering the microstructure evolution, and obtain the thermal conductivity of the resin-based heat-resistant material at different stages of the pyrolysis process.

[0017] In the above-mentioned ablation heat transfer simulation method of resin-based materials considering microstructure evolution, according to the nanoscale porosity, nanoscale pore size distribution law, micronscale porosity, micronscale pore size distribution law and fiber size distribution law of each material sample, combined with the thermal conductivity of each material sample, a finite element model is established at different positions in the control body, including: according to the nanoscale porosity, nanoscale pore size distribution law, micronscale porosity, micronscale pore size distribution law and fiber size distribution law of each material sample, at different positions in the control body, according to the nanoscale pore size distribution law, a microstructure component a corresponding to the nanoscale pore size distribution law is generated, and the microstructure component a is used to simulate the nanoscale pores to obtain a nanoscale pore finite element model; according to the microscale pore size distribution law, a microstructure component b corresponding to the microscale pore size distribution law is generated, and the microstructure component b is used to simulate the microscale pores to obtain a microscale pore finite element model; according to the fiber size distribution law, a microstructure component c corresponding to the fiber size distribution law is generated, and the microstructure component c is used to simulate the fiber to obtain a fiber finite element model.

[0018] In the ablation heat transfer simulation method considering the microstructure evolution of the above-mentioned resin-based material, when generating a microstructure component, nanoscale pores are generated in the nanoscale control body, and micrometer-scale pores and fibers are generated in the micrometer-scale control body, and the porosity of the generated nanoscale pores, the porosity of the micrometer-scale pores and the fiber volume fraction are consistent with the statistical results of step 4.

[0019] In the above-mentioned ablation heat transfer simulation method of resin-based materials considering microstructure evolution, the grid size of the microstructure component is equal to 1 / 50 to 1 / 30 times the diameter of the spherical pore; the control body is a cube, and the side length of the cube is more than twenty times the pore diameter.

[0020] In the above-mentioned ablation heat transfer simulation method of resin-based materials considering microstructure evolution, material samples at different positions of the resin-based heat-resistant material after the ground wind tunnel test are cut to obtain material samples with different degrees of pyrolysis under aerodynamic heating conditions, which are numbered A1 to A6 in sequence; the weight and size of each material sample are measured to obtain the density of each material sample, including:

[0021] The resin-based heat-resistant material that has passed the ground wind tunnel test was cut by wire cutting to obtain an initial sample with a length and width of 15 mm.

[0022] Starting from the surface layer of the initial sample, 6 slices with a thickness of 1 mm were cut in sequence and numbered A1 to A6, thus obtaining material samples A1 to A6;

[0023] The obtained material samples A1-A6 were placed in a drying oven and set at a temperature of 70°C. After keeping warm for 24 hours, the actual size and weight of each material sample were measured, and the densities ρ1-ρ6 of the material samples A1-A6 were calculated.

[0024] In the ablation heat transfer simulation method of the resin-based material considering the microstructure evolution, the pyrolysis degree of each material sample is calculated according to the density of each material sample; and according to the pyrolysis degree of each material sample, combined with the parallel model, the thermal conductivity of the resin matrix in each material sample is calculated, including:

[0025] According to the density of each material sample, the thermal decomposition degree χ of each material sample is calculated. i :

[0026]

[0027] Among them, material sample A1 corresponds to the completely carbonized layer, and the pyrolysis degree χ1 of material sample A1 is 1; material sample A6 corresponds to the original layer, and the pyrolysis degree χ6 of material sample A6 is 0; ρ i represents the density of material sample Ai; ρ p represents the density of the original unpyrolyzed material, ρ p =ρ6;ρ c Indicates the density of the material after complete pyrolysis, ρ c =ρ1;

[0028] Combined with the parallel model, the thermal conductivity k of the resin matrix in each material sample is calculated. i :

[0029] k i =(1-χ i ) mp +χ i k mc

[0030] Among them, k mp represents the thermal conductivity of the original unpyrolyzed resin matrix, k mc It indicates the thermal conductivity of the resin matrix after complete pyrolysis.

[0031] In the ablation heat transfer simulation method for the above-mentioned resin-based material considering the microstructure evolution, the microstructure image of each material sample is obtained in the following manner: the material sample is placed on a gold spraying instrument for gold spraying; the gold-sprayed material sample is placed on a scanning electron microscope for observation, and the position of the material sample under the lens is adjusted to obtain a microstructure image of the material sample.

[0032] In the above-mentioned ablation heat transfer simulation method considering microstructural evolution of resin-based materials, when applying temperature gradient boundary conditions and periodic boundary conditions, temperature gradient boundary conditions are applied along the heat transfer direction from the inner surface to the outer surface of the control body, and periodic boundary conditions are applied on the other four sides of the control body.

[0033] In the ablation heat transfer simulation method considering the microstructure evolution of the above-mentioned resin-based material, when the equivalent thermal conductivity of the control body A1 to A6 layers is obtained in the post-processing, the finite element models established for different layers are solved to obtain the heat flux along the heat transfer direction, and the equivalent thermal conductivity of the control body A1 to A6 layers is calculated using Fourier's law.

[0034] In the above-mentioned ablation heat transfer simulation method of resin-based materials considering microstructure evolution, the fitted relationship between the thermal conductivity of the resin-based heat-resistant material and the degree of pyrolysis is expressed as follows:

[0035] k p =[k m +α(k c -k m )]×[-7.2913α 3 +11.977α 2 -4.7492α+1.0651]

[0036] Among them, α represents the degree of thermal decomposition, k m represents the thermal conductivity of the original material layer, k p represents the thermal conductivity of a given material, k c It indicates the thermal conductivity of the carbonized layer formed after the material is completely pyrolyzed.

[0037] The present invention has the following advantages:

[0038] In the current ablation heat transfer calculation model for resin-based heat-resistant materials, the thermophysical parameters at different stages of pyrolysis can only be calculated using a modified linear interpolation method. The modified parameters are semi-empirical parameters, and it is impossible to effectively predict the thermophysical parameters at different stages of the pyrolysis process. Based on this, the present invention combines material sample preparation, density measurement and pyrolysis degree calculation, microscopic microstructure observation and statistical analysis with finite element modeling to predict the thermal conductivity of resin-based heat-resistant materials at different stages of the pyrolysis process. The relationship between the change of thermal conductivity and pyrolysis degree is fitted based on the prediction results, and the modified linear interpolation formula in the original ablation heat transfer model is replaced, which solves the problem that the existing technology cannot effectively predict the thermal conductivity parameters at different stages of the pyrolysis process of resin-based heat-resistant materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1is a flowchart of the steps of a method for simulating ablation heat transfer of a resin-based material taking into account microstructure evolution in an embodiment of the present invention;

[0040] Figure 2 is a schematic diagram of material samples at different positions in an embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram of the variation of density of a material with pyrolysis degree in an embodiment of the present invention;

[0042] Figure 4 is a schematic diagram of a surface microstructure image of a material sample A1 in an embodiment of the present invention;

[0043] Figure 5 This is a schematic diagram of a surface microstructure image of a material sample A6 in an embodiment of the present invention;

[0044] Figure 6 It is a schematic diagram of a nanoscale pore image and pore marking diagram and pore size distribution result on the back side of a material sample A1 in an embodiment of the present invention;

[0045] Figure 7 It is a micrometer-scale pore image and pore marking diagram of the back side of a material sample A1 in an embodiment of the present invention and a schematic diagram of pore size distribution results;

[0046] Figure 8 1 is a schematic diagram of a fiber image on the back side and a fiber length size distribution result of a material sample A1 in an embodiment of the present invention;

[0047] Fig. 9 1 is a schematic diagram of a fiber image on the back side and a fiber diameter size distribution result of a material sample A1 in an embodiment of the present invention;

[0048] Fig.10 is a schematic diagram of the change of thermal conductivity of a material with pyrolysis degree in an embodiment of the present invention;

[0049] Fig.11 It is a temperature cloud map and heat flow vector map of nanoscale pore distribution calculation in the embodiment of the present invention;

[0050] Fig.12 It is a temperature cloud map and heat flow vector map of micron-scale pore distribution calculation in the embodiment of the present invention;

[0051] Fig.13 is a schematic diagram of the change of nanoscale equivalent thermal conductivity with the degree of pyrolysis in an embodiment of the present invention;

[0052] Fig.14 This is a schematic diagram of the change of micrometer-scale equivalent thermal conductivity with the degree of pyrolysis in an embodiment of the present invention;

[0053] Fig.15It is a schematic diagram comparing the back surface temperature rise calculation results and ground test results before and after the improvement of an ablation heat transfer model in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments disclosed in the present invention will be further described in detail below with reference to the accompanying drawings.

[0055] One of the core ideas of the present invention is: according to the application requirements and current status of resin-based heat-shielding materials, in view of the shortcomings of the current method for determining the thermal conductivity at different stages of the pyrolysis process in the calculation of the heat transfer characteristics of resin-based heat-shielding materials, combined with the microscopic microstructural characteristics of heat-shielding materials, the present invention proposes an improved method for simulating the ablation heat transfer of resin-based materials that takes into account the influence of microstructural evolution on thermal conductivity. The object of analysis of the present invention is a resin-based heat-shielding material, the inner surface of which is fixedly mounted on the aircraft skin, the outer surface is in contact with the atmosphere, the inner surface and the outer surface are made of resin material, and the resin material contains nanoscale pores, micrometer-scale pores and fibers. Firstly, for a given resin-based heat-resistant material, a thin slice of 1 mm was cut from the surface to the inside by wire cutting, and the slices were placed in a drying oven for drying. The size and weight of each sample were measured to obtain the density of the material, and the pyrolysis degree of the material of each slice was calculated. Then, the microstructure of the material at different positions was detected, and the statistical analysis of the microstructure size and distribution was performed based on the detection results. Then, a finite element model for heat transfer characteristic analysis was established based on the microstructure observation and statistical results. Finally, the loading boundary conditions of the constructed model were solved, and the obtained results were processed to obtain the analysis results of the heat transfer characteristics of the resin heat-resistant material at different stages of pyrolysis. According to the obtained results of the change of thermal conductivity with the pyrolysis degree, the relationship between the change of thermal conductivity with the pyrolysis degree was fitted to replace the modified linear interpolation formula used to describe the thermal conductivity at different stages of the pyrolysis process in the ablation heat transfer calculation model of the resin-based material.

[0056] Reference Figure 1 In this embodiment, the ablation heat transfer simulation method of the resin-based material considering the microstructure evolution includes:

[0057] Step 1: Cut material samples at different positions of the resin-based heat-resistant material after the ground wind tunnel test to obtain material samples with different degrees of pyrolysis under aerodynamic heating conditions, which are numbered A1 to A6; measure the weight and size of each material sample to obtain the density of each material sample.

[0058] In this embodiment, material samples A1 to A6 correspond to the A1 to A6 layers of the resin-based heat-resistant material after the ground wind tunnel test, that is, the samples of the A1 to A6 layers of the resin-based heat-resistant material. Among them, the A1 layer is the surface layer, that is, the completely carbonized layer, and its pyrolysis degree is 1; the A6 layer is the original layer, and its pyrolysis degree is 0.

[0059] Preferably, the specific implementation of step 1 is as follows: first, the resin-based heat-resistant material after the ground wind tunnel test is cut by wire cutting to obtain an initial sample with a length and width of 15 mm; then, starting from the surface layer of the initial sample, 6 thin slices with a thickness of 1 mm are cut in sequence, numbered A1 to A6 in sequence, to obtain material samples A1 to A6, such as Figure 2 As shown; the obtained material samples A1~A6 are placed in a drying oven, set at 70℃, and after 24 hours of heat preservation, the actual size and weight of each material sample are measured, and the density ρ1~ρ6 of the material samples A1~A6 is calculated. Among them, ρ1 is the density of the completely carbonized layer, that is, the density of the completely carbonized material; ρ6 is the density of the original layer, which is very close to the density of the original material, that is, the density of the original non-pyrolyzed material.

[0060] Step 2: Calculate the thermal decomposition degree of each material sample according to the density of each material sample; and calculate the thermal conductivity of the resin matrix in each material sample according to the thermal decomposition degree of each material sample in combination with the parallel model.

[0061] In this embodiment, as mentioned above, the A1 layer is the surface layer, that is, the completely carbonized layer, and its pyrolysis degree χ1 is 1; the A6 layer is the original layer, and its pyrolysis degree χ6 is 0. Based on this, the pyrolysis degree χ of the resin matrix in each material sample can be calculated by the following formula: i :

[0062]

[0063] Among them, ρ i represents the density of material sample Ai; ρ p represents the density of the original unpyrolyzed material, ρ p =ρ6;ρ c Indicates the density of the material after complete pyrolysis, ρ c =ρ1. The variation of material density with pyrolysis degree is as follows Figure 3 shown.

[0064] Furthermore, combined with the parallel model, the thermal conductivity k of the resin matrix in each material sample was calculated. i :

[0065] k i =(1-χ i ) mp +χ i k mc

[0066] Among them, k mp represents the thermal conductivity of the unpyrolyzed resin matrix, k mc It indicates the thermal conductivity of the resin matrix after complete pyrolysis. The change law of the thermal conductivity of the material with the degree of pyrolysis is as follows: Fig.10 shown.

[0067] Step 3: Perform microstructure scanning observation on each material sample to obtain a microstructure image of each material sample.

[0068] In this embodiment, the microstructure image of each material sample can be obtained in the following manner: the material sample is placed on a gold spraying instrument for gold spraying; the gold sprayed material sample is placed on a scanning electron microscope for observation, and the position of the material sample under the lens is adjusted to obtain the microstructure image of the material sample. Among them, the microstructure image of material sample A1 is as follows: Figure 4 As shown, the microstructure image of material sample A6 is as follows Figure 5 shown.

[0069] Step 4, based on the microstructure images of each material sample, statistics are performed on the nanoscale pores, micronscale pores, and fiber sizes to obtain the nanoscale porosity, nanoscale pore size distribution law, micronscale porosity, micronscale pore size distribution law, and fiber size distribution law of each material sample.

[0070] In this embodiment, based on the microstructure images of each material sample obtained in step 3, software can be used to perform statistics on nanoscale pores, nanoscale pore size distribution, micronscale pores, micronscale pore size distribution and fiber size to obtain the nanoscale porosity, nanoscale pore size distribution law, micronscale porosity, micronscale pore size distribution law and fiber size distribution law of each material sample.

[0071] like Figure 6 , which are the nanopore images, pore marking diagrams and pore size distribution results of the A1 layer. Several images were taken for testing to obtain the average value of the nanoscale porosity.

[0072] like Figure 7 , which are the micron pore images, pore marking diagrams and pore size distribution results of the A1 layer. Several images were taken for testing to obtain the average value of the micron-scale porosity.

[0073] like Figure 8 , which is the A1 layer fiber marking image and fiber length size distribution results. Take several more images for testing to get the average value of the fiber length size.

[0074] like Fig. 9 , which is the fiber marking image and fiber size distribution result of the A1 layer. Take several more images for testing to obtain the average value of the fiber diameter size.

[0075] Step 5, determining the size of the control body according to the range of nanoscale pores, microscale pore sizes and fiber sizes.

[0076] In this embodiment, the control body is used to simulate the resin-based heat-resistant material. The control body is a cube, and the side length of the cube is more than twenty times the diameter of the pore.

[0077] Step 6, according to the nanoscale porosity, nanoscale pore size distribution law, micronscale porosity, micronscale pore size distribution law and fiber size distribution law of each material sample, combined with the thermal conductivity of the resin matrix in each material sample, a finite element model is established at different positions in the control body.

[0078] In this embodiment, the specific implementation method of step 6 is as follows: according to the nanoscale porosity, nanoscale pore size distribution law, micronscale porosity, micronscale pore size distribution law and fiber size distribution law of each material sample, at different positions in the control body, according to the nanoscale pore size distribution law, generate a microstructure component a corresponding to the nanoscale pore size distribution law, use the microstructure component a to simulate the nanoscale pores, and obtain a nanoscale pore finite element model; according to the micronscale pore size distribution law, generate a microstructure component b corresponding to the micronscale pore size distribution law, use the microstructure component b to simulate the micronscale pores, and obtain a microscale pore finite element model; according to the fiber size distribution law, generate a microstructure component c corresponding to the fiber size distribution law, use the microstructure component c to simulate the fiber, and obtain a fiber finite element model.

[0079] Preferably, when generating a microstructure component, nanoscale pores are generated in a nanoscale control body, and microscale pores and fibers are generated in a micrometer scale control body, and the porosity of the generated nanoscale pores, the porosity of the micrometer scale pores and the fiber volume fraction are consistent with the statistical results of step 4.

[0080] Preferably, the mesh size of the microstructure component is equal to 1 / 50 to 1 / 30 times the diameter of the spherical pore.

[0081] Preferably, for the nanoscale pore finite element model: the surface layer is a completely carbonized structure, so the resin matrix is ​​completely converted into residual carbon. According to the above statistics, the nanoscale porosity is 27.79%, and the average pore diameter distribution is in the range of 0 to 20 nm, which accounts for the majority. The pores are irregular structures, which are considered as spherical pores here. The control body is taken as 100 nanometers, spherical pores are randomly generated, a grid is drawn, periodic boundary conditions and temperature boundary conditions are applied, and the solution is performed. The temperature cloud map and heat flow vector diagram are shown in Figure 11.

[0082] Preferably, for the micron-scale pore finite element model: at the micron scale, according to the above statistics, the porosity is 31.9%, the average pore diameter distribution is in the range of 1 to 5 microns, and the pores are irregular structures, which are considered as spherical pores here. The control body is taken as 100 microns, and spherical pores are randomly generated. From the fiber statistical results, it can be seen that the fiber diameters are not much different, so the average value is 7 microns. The fiber volume fraction is calculated to be 13.6% based on the material physical property parameters. Fibers are generated according to this ratio, Boolean operations are performed, grids are drawn, periodic boundary conditions and temperature boundary conditions are applied, and calculations are performed to obtain the heat flow through the heat transfer direction, and the thermal conductivity prediction results are calculated using Fourier's law. The temperature cloud map and heat flow vector diagram are shown in Figure 12.

[0083] Preferably, for the change of nanoscale thermal conductivity with pyrolysis degree: Based on the above method, the nanoscale thermal conductivity at different pyrolysis degrees is calculated, and the obtained results are as follows: Fig.13 As shown, it can be seen that the equivalent thermal conductivity at the nanoscale increases with the degree of pyrolysis.

[0084] Preferably, for the change of microscale thermal conductivity with pyrolysis degree: Based on the above method, the microscale thermal conductivity at different pyrolysis degrees is calculated, and the obtained results are as follows: Fig.14 As shown, it can be seen that the equivalent thermal conductivity at the micron scale increases with the degree of pyrolysis.

[0085] Step 7, dividing the volume mesh according to the finite element model established in step 6.

[0086] Step 8, applying temperature gradient boundary conditions and periodic boundary conditions to the finite element model after the volume meshing in step 7, and performing post-processing to obtain the equivalent thermal conductivity and thermal decomposition degree of the control volume A1 to A6 layers.

[0087] In this embodiment, when applying temperature gradient boundary conditions and periodic boundary conditions, temperature gradient boundary conditions are applied along the heat transfer direction from the inner surface to the outer surface of the control body (different temperature boundary conditions are applied to the grid nodes along the upper and lower surfaces); periodic boundary conditions are applied to the remaining four side surfaces of the control body to make the temperatures of the grid nodes at corresponding positions on both sides consistent.

[0088] Preferably, when the equivalent thermal conductivity of the control body A1 to A6 layers is obtained by post-processing, the finite element models established for different layers are solved to obtain the heat flux along the heat transfer direction, and the equivalent thermal conductivity of the control body A1 to A6 layers is calculated using Fourier's law.

[0089] Step 9, according to the thermal decomposition degree obtained in step 2 and the equivalent thermal conductivity of the control body A1 to A6 layers obtained in step 8, a fitting equation of the change of thermal conductivity of the resin-based heat-resistant material with the thermal decomposition degree is obtained.

[0090] In this embodiment, the change of thermal conductivity with pyrolysis degree in the ablation heat transfer calculation is generally estimated using a modified linear difference method, and the formula is:

[0091] k p =[k m +α(k c -k m )]×[1-4α(1-α)(1-C α )]

[0092] Among them, α represents the degree of thermal decomposition, k m represents the thermal conductivity of the original material layer, k p represents the thermal conductivity of a given material, k c Indicates the thermal conductivity of the carbonized layer formed after the material is completely pyrolyzed. α It represents the empirical correction coefficient deduced from the test data, and its value range is 0.3 to 1.3.

[0093] Preferably, the relationship between the thermal conductivity of the resin-based heat-proof material obtained by fitting according to the present invention and the degree of pyrolysis is expressed as follows:

[0094] k p =[k m +α(k c -k m )]×[-7.2913α 3 +11.977α 2 -4.7492α+1.0651]

[0095] Step 10, using the relationship between the thermal conductivity of the resin-based heat-resistant material and the degree of pyrolysis obtained by fitting in step 9, to replace the modified linear interpolation method used in the original ablation heat transfer calculation, thereby obtaining an ablation heat transfer simulation scheme for the resin-based material taking into account the microstructure evolution.

[0096] Step 11, based on the ablation heat transfer simulation scheme of the resin-based material considering the microstructure evolution obtained in step 10, carry out the ablation heat transfer simulation of the resin-based material considering the microstructure evolution, and obtain the thermal conductivity of the resin-based heat-resistant material at different stages of the pyrolysis process.

[0097] In this embodiment, the original ablation heat transfer calculation model and the improved scheme of the present invention are used to calculate the ground wind tunnel test state, and the calculated back temperature response is compared with the experimental test. Fig.15 shown.

[0098] Although the present invention has been disclosed as above in the form of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications to the technical solution of the present invention by using the methods and technical contents disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

[0099] The contents not described in detail in the specification of the present invention belong to the common knowledge of the professionals in this field.

Claims

1. A method for simulating ablation heat transfer of resin-based materials considering microstructural evolution, characterized in that: include: Step 1, cutting material samples at different positions of the resin-based heat-resistant material after the ground wind tunnel test to obtain material samples with different degrees of pyrolysis under aerodynamic heating conditions, which are numbered A1 to A6 in sequence; measuring the weight and size of each material sample to obtain the density of each material sample; wherein the material samples A1 to A6 correspond to the A1 to A6 layers of the resin-based heat-resistant material after the ground wind tunnel test; the A1 layer is the surface layer, which is a completely carbonized layer; and the A6 layer is the original layer; Step 2, according to the density of each material sample, the thermal decomposition degree of each material sample is calculated; and according to the thermal decomposition degree of each material sample, in combination with the parallel model, the thermal conductivity of the resin matrix in each material sample is calculated; Step 3, performing microstructure scanning observation on each material sample to obtain a microstructure image of each material sample; Step 4, according to the microstructure image of each material sample, the nanoscale pores, micron-scale pores, and fiber sizes are statistically analyzed to obtain the nanoscale porosity, nanoscale pore size distribution law, micron-scale porosity, micron-scale pore size distribution law, and fiber size distribution law of each material sample; Step 5, determining the size of the control body according to the range of nanoscale pores, microscale pore sizes and fiber sizes; wherein the control body is used to simulate the resin-based heat-resistant material; Step 6, according to the nanoscale porosity, nanoscale pore size distribution law, microscale porosity, microscale pore size distribution law and fiber size distribution law of each material sample, combined with the thermal conductivity of the resin matrix in each material sample, a finite element model is established at different positions in the control body; Step 7, dividing the volume mesh according to the finite element model established in step 6; Step 8, applying temperature gradient boundary conditions and periodic boundary conditions to the finite element model after the volume meshing in step 7, and performing post-processing to obtain the equivalent thermal conductivity of the control volume A1 to A6 layers; Step 9, according to the thermal decomposition degree obtained in step 2 and the equivalent thermal conductivity of the control body A1 to A6 layers obtained in step 8, fitting is performed to obtain a relationship between the thermal conductivity of the resin-based heat-resistant material and the thermal decomposition degree; Step 10, using the relationship between the thermal conductivity of the resin-based heat-resistant material and the degree of pyrolysis obtained by fitting in step 9 to replace the modified linear interpolation method used in the original ablation heat transfer calculation, thereby obtaining an ablation heat transfer simulation scheme for the resin-based material taking into account the microstructure evolution; Step 11, based on the ablation heat transfer simulation scheme of the resin-based material considering the microstructure evolution obtained in step 10, carry out the ablation heat transfer simulation of the resin-based material considering the microstructure evolution, and obtain the thermal conductivity of the resin-based heat-resistant material at different stages of the pyrolysis process.

2. The ablation heat transfer simulation method for resin-based materials considering microstructure evolution according to claim 1, characterized in that: According to the nanoscale porosity, nanoscale pore size distribution law, micronscale porosity, micronscale pore size distribution law and fiber size distribution law of each material sample, combined with the thermal conductivity of each material sample, a finite element model is established at different positions in the control body, including: according to the nanoscale porosity, nanoscale pore size distribution law, micronscale porosity, micronscale pore size distribution law and fiber size distribution law of each material sample, at different positions in the control body, according to the nanoscale pore size distribution law, a microstructure component a corresponding to the nanoscale pore size distribution law is generated, and the microstructure component a is used to simulate the nanoscale pores to obtain a nanoscale pore finite element model; according to the microscale pore size distribution law, a microstructure component b corresponding to the microscale pore size distribution law is generated, and the microstructure component b is used to simulate the microscale pores to obtain a microscale pore finite element model; according to the fiber size distribution law, a microstructure component c corresponding to the fiber size distribution law is generated, and the microstructure component c is used to simulate the fiber to obtain a fiber finite element model.

3. The ablation heat transfer simulation method for resin-based materials considering microstructure evolution according to claim 2, characterized in that: When generating a microstructure component, nanoscale pores are generated in the nanoscale control body, and microscale pores and fibers are generated in the microscale control body, and the porosity of the generated nanoscale pores, the porosity of the microscale pores and the fiber volume fraction are consistent with the statistical results of step 4.

4. The ablation heat transfer simulation method for resin-based materials considering microstructure evolution according to claim 3, characterized in that: The grid size of the microstructure component is equal to 1 / 50 to 1 / 30 times the diameter of the spherical pore; the control body is a cube, and the side length of the cube is more than twenty times the diameter of the pore.

5. The ablation heat transfer simulation method for resin-based materials considering microstructure evolution according to claim 1, characterized in that: Material samples at different positions of the resin-based heat-resistant material after the ground wind tunnel test were cut to obtain material samples with different degrees of pyrolysis under aerodynamic heating conditions, which were numbered A1 to A6; The weight and size of each material sample are measured to obtain the density of each material sample, including: The resin-based heat-resistant material that has passed the ground wind tunnel test was cut by wire cutting to obtain an initial sample with a length and width of 15 mm. Starting from the surface layer of the initial sample, 6 slices with a thickness of 1 mm were cut in sequence and numbered A1 to A6, thus obtaining material samples A1 to A6; The obtained material samples A1-A6 were placed in a drying oven and set at a temperature of 70°C. After keeping warm for 24 hours, the actual size and weight of each material sample were measured, and the densities ρ1-ρ6 of the material samples A1-A6 were calculated.

6. The ablation heat transfer simulation method for resin-based materials considering microstructure evolution according to claim 5, characterized in that: According to the density of each material sample, the thermal decomposition degree of each material sample is calculated; According to the pyrolysis degree of each material sample, combined with the parallel model, the thermal conductivity of the resin matrix in each material sample is calculated, including: According to the density of each material sample, the thermal decomposition degree χ of each material sample is calculated. i : Among them, material sample A1 corresponds to the completely carbonized layer, and the pyrolysis degree χ1 of material sample A1 is 1; material sample A6 corresponds to the original layer, and the pyrolysis degree χ6 of material sample A6 is 0; ρ i represents the density of material sample Ai; ρ p represents the density of the original unpyrolyzed material, ρ p =ρ6;ρ c Indicates the density of the material after complete pyrolysis, ρ c =ρ1; Combined with the parallel model, the thermal conductivity k of the resin matrix in each material sample is calculated. i : k i =(1-x i )k mp +x i k mc Among them, k mp represents the thermal conductivity of the original unpyrolyzed resin matrix, k mc It indicates the thermal conductivity of the resin matrix after complete pyrolysis.

7. The ablation heat transfer simulation method for resin-based materials considering microstructure evolution according to claim 1, characterized in that: The microstructure image of each material sample is obtained in the following manner: the material sample is placed on a gold spraying instrument for gold spraying; the gold-sprayed material sample is placed on a scanning electron microscope for observation, and the position of the material sample under the lens is adjusted to obtain the microstructure image of the material sample.

8. The ablation heat transfer simulation method for resin-based materials considering microstructure evolution according to claim 1, characterized in that: When applying temperature gradient boundary conditions and periodic boundary conditions, temperature gradient boundary conditions are applied along the heat transfer direction from the inner surface to the outer surface of the control body, and periodic boundary conditions are applied on the other four sides of the control body.

9. The ablation heat transfer simulation method for resin-based materials considering microstructure evolution according to claim 1, characterized in that: When the equivalent thermal conductivity of the control body A1 to A6 layers is obtained in the post-processing, the finite element models established for different layers are solved to obtain the heat flux along the heat transfer direction, and the equivalent thermal conductivity of the control body A1 to A6 layers is calculated using Fourier's law.

10. The ablation heat transfer simulation method for resin-based materials considering microstructure evolution according to claim 1, characterized in that: The fitted relationship between the thermal conductivity of the resin-based heat-resistant material and the degree of pyrolysis is expressed as follows: k p =[k m +α(k c -k m )]×[-7.2913a 3 +11.977a 2 -4.7492a+1.0651] Among them, α represents the degree of thermal decomposition, k m represents the thermal conductivity of the original material layer, k p represents the thermal conductivity of a given material, k c It indicates the thermal conductivity of the carbonized layer formed after the material is completely pyrolyzed.

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