Determination Method for Heat Transfer Characteristics of Resin Matrix Materials Considering Physical Properties and Microstructure Evolution

Abstract

The present invention relates to a method for determining the heat transfer characteristics of a resin-based material considering physical properties and microstructural evolution. Material samples are cut from different positions of the material after aerodynamic heating to obtain the values of the material density, and thus the pyrolysis degrees of the samples at different positions are calculated. Based on the pyrolysis degrees, the matrix physical properties at different pyrolysis degrees are calculated. At the same time, the microstructures of the material samples at different positions are observed to obtain the microstructure morphology, the overlapping relationship between microstructure components, and the mutual position relationship. Through the statistical results of the sizes of the microstructures, including nano-porosity, micro-porosity, fiber diameter, and fiber length, the evolution law of the microstructure during the aerodynamic heating process is obtained. And from the statistical results and the physical property results varying with the pyrolysis degree, combined with the morphological observation results of the microstructure, a cross-scale finite element model is established, and the boundary conditions are loaded and solved to obtain the prediction results of the equivalent thermal conductivity of the material corresponding to different pyrolysis degrees.

Description

Technical Field

[0001] The present invention relates to a method for determining the heat transfer characteristics considering the physical properties and microstructure evolution of resin-based thermal protection materials under pneumatic heating conditions, belonging to the technical field of aircraft thermal protection. Background Technique

[0002] The development of aircraft thermal protection technology has gone through several processes. Initially, it was heat sink thermal protection, using the heat sink of metal to absorb heat and block heat. However, with the severity of pneumatic heating, it can no longer meet the requirements. Later, ablative thermal protection methods were developed, using the evaporation, melting, sublimation, and chemical reactions of materials to absorb heat. Ablative thermal protection has been widely used in reentry satellites, spacecraft, etc. due to its high-efficiency thermal protection effect. Ablative thermal protection is still widely used in aircraft such as return satellites and spacecraft because of its simple form, good heat protection effect, and high reliability. In order to improve the heat insulation effect while taking into account the heat protection efficiency, currently, nano-resin-based thermal protection materials have been developed, mainly with nano-scale pores in the resin matrix, which significantly reduce the thermal conductivity and density of the material without affecting the heat protection effect and mechanical strength, and then compounded with fibers to obtain resin-based thermal protection materials with nano-scale pores removed.

[0003] For the design and processing of thermal protection materials, most are currently continuously tried from the process perspective. For thermal protection material samples produced by different processes, their heat insulation and heat protection performances are tested through experimental methods. This exploration is a very effective way, but the production cycle is long, the cost is high, and the uncertainty during the process exploration and material performance testing is high. Therefore, it is particularly important to explore the heat insulation and heat protection performances of materials from the simulation perspective.

[0004] Currently, the research on the ablation and heat transfer mechanisms of homogeneous materials is relatively mature. Using the macroscopic thermochemical ablation theory, heat transfer control equations, surface energy conservation and mass conservation equations, and loading boundary conditions, the heat response mechanism of the material changing with time is solved, including the internal temperature distribution, ablation recession, and the change of the carbonized layer thickness with time, etc. However, there is less research on the heat response mechanism of resin-based thermal protection materials with nano-pores. The current research mostly combines process exploration and experimental testing, lacking an accurate prediction of the heat transfer performance of thermal protection materials.

[0005] During different stages of the pyrolysis process of materials, significant changes will occur in the physical properties and microstructure of the materials. For the testing of physical property parameters such as the thermal conductivity of materials during the pyrolysis process, there are lack of effective experimental means, and there is also less simulation research. Most tests still focus on the physical property parameters after complete carbonization and of the original materials, and there is lack of effective means for the change of the thermal conductivity of materials during different stages of the pyrolysis process. Summary of the Invention

[0006] The object of the present invention is to overcome the deficiencies of the prior art and propose a method for determining the heat transfer characteristics considering the physical properties and microstructure evolution of resin-based thermal protection materials under aerodynamic heating conditions, solving the problem in the prior art that the physical property parameters in different stages of the pyrolysis process of resin-based thermal protection materials cannot be effectively predicted.

[0007] The technical solution of the present invention is as follows:

[0008] A method for determining the heat transfer characteristics of a resin-based material considering physical properties and microstructure evolution, comprising the following steps:

[0009] 1) Cut material samples at different positions from the resin-based thermal protection material after ground wind tunnel tests, numbered A1 to A6 respectively, to obtain material samples with different degrees of pyrolysis under aerodynamic heating conditions, measure the weight and size, and obtain the density results of the material.

[0010] 2) According to the density results obtained from the surface layer A1 and the density results of the original material layer of the material, obtain the pyrolysis degree values of the materials at different cut positions.

[0011] 3) Perform microstructure scanning observations on different positions A1 to A6 of the resin-based thermal protection material to obtain the microstructure images of the thermal protection materials corresponding to different positions;

[0012] 4) According to the microstructure images obtained in step 3), respectively count the nano-scale pores, micro-scale pores, and fiber sizes, and obtain the nano-scale porosity, pore size distribution, micro-scale porosity, pore size distribution, and fiber size statistical results of the slices at different positions;

[0013] 5) Determine the size of the control volume according to the ranges of the pore sizes at the nano and micro scales and the fiber size; the control volume is used to simulate the resin-based thermal protection material;

[0014] 6) At different positions within the control volume, according to the distribution law of the nano-scale pore sizes, generate microstructure components corresponding to the nano-scale pore size distribution law, use the microstructure components to simulate the nano-scale pores, and obtain a finite element model; according to the distribution law of the micro-scale pore sizes, generate microstructure components corresponding to the micro-scale pore size distribution law, use the microstructure components to simulate the micro-scale pores, and obtain a finite element model; according to the distribution law of the fiber sizes, generate microstructure components corresponding to the fiber size distribution law, use the microstructure components to simulate the nano-fibers, and obtain a finite element model;

[0015] 7) According to the finite element model established in step 6), perform the division of the volume mesh;

[0016] 8) Apply temperature boundary conditions and periodic boundary conditions to the finite element model after the volume mesh division obtained in step 7).

[0017] 9) Solve to obtain the equivalent thermal conductivity of the control volume.

[0018] Furthermore, for the step 1) of obtaining material samples with different degrees of pyrolysis, performing weight and size measurements, and calculating the degree of pyrolysis of the material, specifically:

[0019] 1.1) Cut samples with a length and width of 15 mm each using wire cutting, and then cut thin slices with a thickness of 1 mm starting from the surface carbonized layer, numbered A1 to A6 respectively.

[0020] 1.2) Place the cut samples in a drying oven, set the temperature to 70 °C, and keep them moist for 24 hours.

[0021] 1.3) Measure the actual size and weight of each thin slice, and calculate the density values ρ1 to ρ6. ρ1 is the density of the fully carbonized material, ρ6 is very close to the density of the original material, and take ρ6 as the density value of the original material.

[0022] Furthermore, for step 2), calculate the degree of pyrolysis value based on the density results of each layer, specifically:

[0023] 2.1) Define the internal pyrolysis rate of the material as:

[0024]

[0025] where ρ is the current density of the material; ρ c is the density after the material is fully pyrolyzed; ρ p is the density of the original unpyrolyzed material. According to this formula and the physical properties of A1 being the carbonized material and A6 being the original material, the degree of pyrolysis of A2 to A4 can be calculated.

[0026] 2.2) The thermal conductivity during the resin pyrolysis process can be expressed as a function of the pyrolysis rate χ:

[0027] k = (1 - χ)k p + χk c

[0028] where k p is the thermal conductivity of the original unpyrolyzed material; k c is the thermal conductivity after the material is fully pyrolyzed.

[0029] Furthermore, for the step 3) of performing microstructure scanning and observation, specifically:

[0030] 3.1) Place the material sample on a sputtering coater for sputtering treatment;

[0031] 3.2) Place the sputter-coated material sample in a scanning electron microscope for observation, and adjust the position of the material sample under the lens to obtain an image of the material microstructure;

[0032] 3.3) Repeat step 3.2) multiple times to obtain the microstructure images of the thermal insulation materials corresponding to A1 - A6.

[0033] Further, step 4) obtains the statistical results of the nano-scale porosity, pore size distribution, micro-scale porosity, pore size distribution, and the size of the fibers, specifically:

[0034] Based on the microstructure images obtained in step 3), use software to perform statistics on the nano-scale porosity, pore size distribution, micro-scale porosity, pore size distribution, and the size of the fibers, and obtain the values of the porosity and the distribution of the microstructure sizes.

[0035] Further, the control volume in step 5) is a cube, and the side length of the cube is more than twenty times the pore diameter.

[0036] Further, the method for generating microstructure components corresponding to the distribution laws of the pore size and fiber size in step 6) is specifically:

[0037] According to the statistical results, generate nano-pores in the nano-scale control volume, and according to the statistical results, generate micro-pores and fibers in the micro-scale control volume. The porosity and the fiber volume fraction are consistent with the statistical results.

[0038] Further, in step 7): the grid size of the microstructure components is equal to 1 / 5 - 1 / 20 times the diameter of the spherical pores.

[0039] Further, the method for applying the temperature boundary condition and the periodic boundary condition in step 8) is specifically:

[0040] 8.1) Apply a temperature gradient boundary condition on the grid nodes of the upper and lower surfaces along the heat transfer direction from the inner surface to the outer surface of the control volume.

[0041] 8.2) Apply a periodic boundary condition on the other four sides to make the temperatures of the corresponding grid nodes on the two pairs of opposite surfaces consistent.

[0042] Step 10) Solve and post-process, specifically:

[0043] Perform the solution to obtain the heat flux along the heat transfer direction, and calculate the equivalent thermal conductivity of the control volume using Fourier's law.

[0044] Furthermore, the present invention also proposes a heat transfer characteristic determination system for the physical properties and microstructural evolution of resin-based thermal protection materials under pneumatic heating conditions, including: a sample preparation and observation module, a microstructure statistics module, a model generation module, a mesh generation module, a loading boundary condition module, and a solution and post-processing module;

[0045] Sample preparation and observation module: Take materials at different pyrolysis degrees for sectioning, drying, weighing, and measuring dimensions to obtain density values and calculate the corresponding pyrolysis degree values; perform microstructure scanning observations on different positions of the thermal protection material to obtain microstructure images of the thermal protection material corresponding to different positions;

[0046] Microstructure statistics module: Statistically analyze the nano-scale porosity, pore size distribution, micro-scale porosity, pore size distribution, and fiber size based on the microstructure images to obtain the distribution law of microstructure sizes;

[0047] Model generation module: Determine the size of the control volume according to the nano-scale pores, micro-scale pores, and fiber size ranges; the control volume is used to simulate the thermal protection material; at different positions within the control volume, generate microstructure components corresponding to the pore size distribution law according to the pore size distribution law, and use the microstructure components to simulate pores and fibers to obtain a finite element model;

[0048] Mesh generation module: Perform volume mesh generation on the finite element model; the mesh size of the microstructure components is equal to 1 / 5 to 1 / 20 times the pore diameter;

[0049] Loading boundary condition module: Apply a temperature gradient boundary condition along the heat transfer direction from the inner surface to the outer surface of the control volume, and apply periodic boundary conditions on the other four sides;

[0050] Solution and post-processing module: Solve to obtain the heat flux along the heat transfer direction, and calculate the equivalent thermal conductivity of the control volume using Fourier's law.

[0051] Advantages of the present invention compared with the prior art:

[0052] (1) Currently, for resin-based thermal protection materials, most only test the material property parameters of the fully carbonized layer and the original material layer for finite element prediction. For the thermal property parameters at different pyrolysis stages, only linear interpolation or empirical interpolation methods can be used, and it is impossible to effectively predict the thermal property parameters at different stages of the pyrolysis process. Based on this, the present invention combines material sample preparation, density measurement, pyrolysis degree calculation, mesoscopic microstructure observation and statistical analysis with finite element modeling to predict the heat transfer characteristics of resin-based thermal protection materials at different stages of the pyrolysis process.

[0053] (2) Compared with the existing methods for testing or predicting the physical properties of resin-based heat-resistant materials, the method of the present invention has low cost, fast calculation, high accuracy, good versatility, and the ability to analyze the heat transfer characteristics of heat-resistant materials at different stages of the pyrolysis process. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 Flow chart of the method of the present invention;

[0055] Figure 2 Schematic diagram of photos of material samples at different positions;

[0056] Figure 3 Schematic diagram of the variation law of material density with pyrolysis degree;

[0057] Figure 4 Surface microstructure image of Model A1;

[0058] Figure 5 Surface microstructure image of Model A6;

[0059] Figure 6 Schematic diagram of the nano-scale pore image, pore marking map and pore size distribution results on the back surface of Layer A1;

[0060] Figure 7 Schematic diagram of the micro-scale pore image, pore marking map and pore size distribution results on the back surface of Layer A1;

[0061] Figure 8 Schematic diagram of the fiber image and fiber length size distribution results on the back surface of Layer A1;

[0062] Figure 9 Schematic diagram of the fiber image and fiber diameter size distribution results on the back surface of Layer A1;

[0063] Figure 10 Schematic diagram of the variation of the thermal conductivity of the phenolic resin matrix with pyrolysis degree;

[0064] Figure 11 Calculated temperature contour map and heat flux vector map of nano-scale pore distribution;

[0065] Figure 12 Calculated temperature contour map and heat flux vector map of micro-scale;

[0066] Figure 13 Schematic diagram of the variation of nano-scale equivalent thermal conductivity with pyrolysis degree;

[0067] Figure 14 Schematic diagram of the variation of micro-scale equivalent thermal conductivity with pyrolysis degree;

[0068] Figure 15 Schematic diagram of the influence law of nano-pore size on nano-scale thermal conductivity;

[0069] Figure 16 Schematic diagram of the influence law of nanoporosity on thermal conductivity at the nanoscale;

[0070] Figure 17 Schematic diagram of the influence law of the bottom diameter of the fiber on thermal conductivity at the microscale;

[0071] Figure 18 Schematic diagram of the influence law of the angle between the fiber and the heat transfer equation on thermal conductivity. Specific implementation mode

[0072] According to the application requirements and current situation of resin-based thermal protection materials, aiming at the deficiencies of the current determination methods for the heat transfer characteristics of resin-based thermal protection materials, and combining with the mesoscopic microstructure characteristics of thermal protection materials, the present invention proposes a method for determining the heat transfer characteristics considering the physical properties and microstructure evolution of resin-based thermal protection materials under aerodynamic heating conditions. The analysis object of the present invention is a resin-based thermal protection material, the inner surface of which is fixedly installed on the aircraft skin, the outer surface is in contact with the atmosphere, the inner surface and the outer surface are resin materials, and there are nanoscale pores, microscale pores and fibers in the resin material.

[0073] First, for a given resin-based thermal protection material, use wire cutting to cut thin slices from the surface to the inside every 1 mm, put them into a drying oven for drying, measure the size and weight of each sample, obtain the density of the material, and calculate the pyrolysis degree of the material for each slice; then, perform microstructure detection on the materials at different positions, and conduct statistical analysis on the microstructure size and distribution according to the detection results; then, establish a finite element model for heat transfer characteristics analysis based on the microstructure observation and statistical results; finally, solve the established model by applying boundary conditions, process the obtained results, and obtain the analysis results of the heat transfer characteristics at different pyrolysis stages of the resin thermal protection material. At the same time, the influence law of mesoscopic structure parameters can be studied, such as changing the content, size distribution and position distribution of different microstructure components, etc., to obtain the influence law of microstructure parameters on heat transfer characteristics, so as to provide a reference for the formulation of material processes.

[0074] Specifically, as Figure 1 shown, a method for determining the heat transfer characteristics considering the physical properties and microstructure evolution of resin-based thermal protection materials under aerodynamic heating conditions proposed by the present invention includes the following steps:

[0075] (1) Cut material samples at different positions from the resin-based thermal protection material after ground wind tunnel tests to obtain material samples with different pyrolysis degrees under aerodynamic heating conditions, measure the weight and size, and obtain the density results of the material; specifically:

[0076] (1.1) Use wire cutting to cut samples with a length and width of 15 mm, and then cut thin slices with a thickness of 1 mm starting from the surface carbonized layer, numbered A1 to A6 respectively;

[0077] (1.2) Place the cut sample in an oven, set the temperature to 70 °C, and maintain the humidity for 24 hours;

[0078] (1.3) Measure the actual sizes and weights of the thin slices A1 to A6, and calculate the density values ρ1 to ρ6. ρ1 is the density of the fully carbonized material, ρ6 is close to the density of the original material, and take ρ6 as the density value ρ of the original material. p .

[0079] (2) Obtain the pyrolysis degree values of the materials at different cut positions based on the density results of the material sample surface layer and the density results of the original material layer of the material, and calculate the resin thermal conductivity values corresponding to different pyrolysis degrees using a parallel model; specifically:

[0080] (2.1) The internal pyrolysis rate of the material is:

[0081]

[0082] where ρ is the current density of the material; ρ c is the density of the material after complete pyrolysis; ρ p is the density value of the original material; according to this formula and the physical properties of layer A1 being carbonized material and layer A6 being the original material, calculate the pyrolysis degrees of layers A2 to A4;

[0083] (2.2) The thermal conductivity during the resin pyrolysis process is expressed as a function of the pyrolysis rate χ:

[0084] k = (1 - χ)k p + χk c

[0085] where k p is the thermal conductivity of the original unpyrolyzed material; k c is the thermal conductivity of the material after complete pyrolysis.

[0086] (3) Conduct microstructure scanning observations on the material samples at different positions of the resin-based thermal protection material to obtain the microstructure images of the thermal protection material corresponding to different positions; specifically:

[0087] (3.1) Place the material sample on a sputtering coater for sputtering treatment;

[0088] (3.2) Place the sputtered material sample in a scanning electron microscope for observation, adjust the position of the material sample under the lens to obtain the material microstructure image;

[0089] (3.3) Repeat step (3.2) multiple times to obtain the microstructure images of the thermal protection material corresponding to layers A1 to A6.

[0090] (4) Based on the microstructure images obtained in step (3), statistically analyze the nano-scale pores, micro-scale pores, and fiber sizes respectively to obtain the nano-scale porosity, pore size distribution, micro-scale porosity, pore size distribution, and fiber size statistical results of different position slices;

[0091] (5) Determine the size of the control volume according to the ranges of nano-scale and micro-scale pore sizes and fiber sizes; the control volume is used to simulate the resin-based thermal protection material;

[0092] The control volume includes a nano-scale control volume and a micro-scale control volume, both of which are cubic structures, and the side length of the cube is more than twenty times the corresponding pore diameter.

[0093] (6) At different positions within the control volume, generate microstructure components corresponding to the nano-scale pore size distribution law according to the nano-scale pore size distribution law, use the microstructure components to simulate the nano-scale pores, and obtain a finite element model;

[0094] Generate microstructure components corresponding to the micro-scale pore size distribution law according to the micro-scale pore size distribution law, use the microstructure components to simulate the micro-scale pores, and obtain a finite element model;

[0095] Generate microstructure components corresponding to the fiber size distribution law according to the fiber size distribution law, use the microstructure components to simulate the nanofibers, and obtain a finite element model;

[0096] Generate nano-pores within the nano-scale control volume according to the statistical results, and generate micro-pores and fibers within the micro-scale control volume according to the statistical results; the porosity and fiber volume fraction are consistent with the statistical results.

[0097] (7) Perform volume mesh division on the finite element model established in step (6); the mesh size of the microstructure components is equal to 1 / 5 to 1 / 20 times the diameter of the spherical pores.

[0098] (8) Apply temperature boundary conditions and periodic boundary conditions to the finite element model obtained in step (7) after volume mesh division; specifically:

[0099] (8.1) Apply a temperature gradient boundary condition along the heat transfer direction from the inner surface to the outer surface of the control volume, and apply different temperature boundary conditions to the grid nodes on the upper and lower surfaces of the thermal protection material;

[0100] (8.2) Apply periodic boundary conditions on the other four sides to make the temperatures of the grid nodes at corresponding positions on the two pairs of opposite faces consistent.

[0101] (9) Solve to obtain the equivalent thermal conductivity of the control volume. Specifically: Solve to obtain the heat flux along the heat transfer direction, and use Fourier's law to calculate the equivalent thermal conductivity of the control volume.

[0102] Example

[0103] As Figure 1 shown, the specific steps are as follows:

[0104] 1) Cut material samples at different positions from the resin-based heat protection material after the ground wind tunnel test. The samples are numbered A1 to A6 respectively, to obtain material samples with different degrees of pyrolysis under aerodynamic heating conditions, and measure the weight and size to obtain the density results of the material. Specifically:

[0105] The samples cut at different positions are as Figure 2 shown.

[0106] 2) According to the density results obtained from the surface layer A1 and the density results of the original material layer of the material, obtain the pyrolysis degree values of the materials cut at different positions. Specifically:

[0107] 2.1) Define the internal pyrolysis rate of the material as:

[0108]

[0109] where ρ is the current density of the material; ρ c is the density of the material after complete pyrolysis; ρ p is the density of the original unpyrolyzed material. According to this formula and the physical properties of A1 being carbonized material and A6 being the original material, the pyrolysis degrees of A2 to A4 can be calculated.

[0110] 2.2) The thermal conductivity during the resin pyrolysis process can be expressed as a function of the pyrolysis rate χ:

[0111] k = (1 - χ)k p + χk c

[0112] where k p is the thermal conductivity of the original unpyrolyzed material; k c is the thermal conductivity of the material after complete pyrolysis.

[0113] The variation law of the material density with the pyrolysis degree is calculated as shown in Figure 3 shown.

[0114] 3) Conduct microstructure scanning observations on different positions A1 to A6 of the resin-based heat protection material to obtain the microstructure images of the heat protection material corresponding to different positions; as Figure 4 and Figure 5 are the microstructure images of layers A1 and A6 respectively.

[0115] 4) Based on the microstructure images obtained in step 3), the nano-scale pores, micro-scale pores, and fiber sizes are respectively statistically analyzed to obtain the nano-scale porosity, pore size distribution, micro-scale porosity, pore size distribution, and fiber size statistical results of different position slices, specifically as follows:

[0116] 4.1) Figure 6 It is the nano-pore image, pore marking map, and pore size distribution result of layer A1. Take several images for testing to obtain the average value of the nano-scale porosity.

[0117] 4.2) Figure 7 It is the micro-pore image, pore marking map, and pore size distribution result of layer A1. Take several images for testing to obtain the average value of the micro-scale porosity.

[0118] 4.3) Figure 8 It is the fiber marking map and fiber length size distribution result of layer A1. Take several images for testing to obtain the average value of the fiber length size.

[0119] 4.4) Figure 9 It is the fiber marking map and fiber size distribution result of layer A1. Take several images for testing to obtain the average value of the fiber diameter size.

[0120] 5) Determine the size of the control volume according to the ranges of the pore sizes at the nano- and micro-scales and the fiber size; the control volume is used to simulate the resin-based thermal protection material;

[0121] 6) At different positions within the control volume, according to the distribution law of the nano-scale pore sizes, generate microstructure components corresponding to the nano-scale pore size distribution law, use the microstructure components to simulate the nano-scale pores, and obtain a finite element model; according to the distribution law of the micro-scale pore sizes, generate microstructure components corresponding to the micro-scale pore size distribution law, use the microstructure components to simulate the micro-scale pores, and obtain a finite element model; according to the distribution law of the fiber sizes, generate microstructure components corresponding to the fiber size distribution law, use the microstructure components to simulate the nano-fibers, and obtain a finite element model; perform mesh division, apply humidity boundary conditions and periodic boundary conditions, and solve to obtain the value of the equivalent thermal conductivity, as Figure 10 shown.

[0122] 6.1) Finite element model of nano-pore scale

[0123] The surface layer has a completely carbonized structure, so the resin matrix is completely converted into residual carbon. From the aforementioned statistics, the porosity at the nanoscale is 27.79%. Most of the pore average diameters are distributed in the range of 0 - 20 nm, and the pores are of irregular structure. Here, they are considered as spherical pores. A control volume of 100 nanometers is taken, spherical pores are randomly generated, meshed, and periodic boundary conditions and temperature boundary conditions are applied for solution. The temperature contour and heat flux vector diagram are as Figure 11 shown.

[0124] 6.2) Finite element model at the microscale

[0125] At the microscale, from the aforementioned statistics, the porosity is 31.9%. Most of the pore average diameters are distributed in the range of 1 - 5 microns, and the pores are of irregular structure. Here, they are considered as spherical pores. A control volume of 100 microns is taken, spherical pores are randomly generated. From the fiber statistical results, the fiber diameters do not vary much, so the average value of 7 microns is taken. The fiber volume fraction is calculated to be 13.6% from the material physical property parameters. Fibers are generated according to this ratio, Boolean operations are performed, meshed, periodic boundary conditions and temperature boundary conditions are applied for calculation, the heat flux through the heat transfer direction is obtained, and the predicted result of the thermal conductivity is calculated using Fourier's law. The temperature contour and heat flux vector diagram are as Figure 12 shown.

[0126] 6.3) Results of the change of nanoscale thermal conductivity with the degree of pyrolysis

[0127] Using a method similar to that in the previous section, the nanoscale thermal conductivity at different degrees of pyrolysis is calculated, and the results are as Figure 13 shown. It can be seen that the equivalent thermal conductivity at the nanoscale increases with the increase in the degree of pyrolysis.

[0128] 64) Results of the change of nanoscale thermal conductivity with the degree of pyrolysis

[0129] The microscale thermal conductivity at different degrees of pyrolysis is calculated, and the results are as Figure 14 shown. It can be seen that the equivalent thermal conductivity at the microscale increases with the increase in the degree of pyrolysis.

[0130] 6.5) Influence law of nanoscale pores

[0131] With the same porosity, the influence law of the change in pore size on the nanoscale thermal conductivity is explored, as Figure 15 shown. Since the model is randomly distributed, the method of taking the average value through multiple calculations is adopted. It can be seen that under a certain volume fraction, the nanoscale pore size has little effect on the nanoscale thermal conductivity.

[0132] For different nanoscale porosities, the influence of porosity on the nanoscale thermal conductivity is calculated, as Figure 16As shown, it can be seen that the thermal conductivity at the nanoscale decreases with the increase in porosity. This is because the thermal conductivity of air is relatively low, and a larger porosity will reduce the thermal conductivity of the material.

[0133] 6.6) Influence law of fiber size

[0134] Next, the influence of the fineness of the fiber on the thermal conductivity at the microscale is discussed. With a certain fiber volume fraction, for different bottom diameters of the fiber, the equivalent thermal conductivity at the fiber scale is calculated, as Figure 17 shown. It can be seen that the influence of the fiber diameter on the equivalent thermal conductivity at the microscale is not significant.

[0135] 6.7) Influence law of fiber distribution

[0136] The influence of the different angles between the fiber orientation and the heat transfer direction on the equivalent thermal conductivity is as Figure 18 shown. It can be seen that the fiber orientation has a greater influence on the equivalent thermal conductivity. When the fiber is along the heat transfer direction, the thermal conductivity is the largest, and when the fiber is perpendicular to the heat transfer direction, the thermal conductivity is the smallest.

[0137] Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can 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 decorations 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 all fall within the protection scope of the technical solution of the present invention.

[0138] The content not described in detail in the specification of the present invention belongs to the well-known technology of those skilled in the art.

Claims

1. A method for determining the heat transfer characteristics of a resin-based material considering physical properties and microstructure evolution, characterized in that Including: (1) Taking material samples at different positions from the resin-based heat protection material after ground wind tunnel tests to obtain material samples with different degrees of pyrolysis under aerodynamic heating conditions, measuring the weight and size, and obtaining the density results of the material; (2) According to the density results of the material samples on the surface layer and the density results of the original material layer of the material, obtaining the pyrolysis degree values of the materials at different cut positions, and calculating the resin thermal conductivity values corresponding to different pyrolysis degrees using a parallel model; (3) Conducting microstructure scanning observations on material samples at different positions of the resin-based heat protection material to obtain microstructure images of the heat protection material corresponding to different positions; (4) According to the microstructure images obtained in step (3), respectively counting the nano-scale pores, micro-scale pores, and fiber sizes, and obtaining the nano-scale porosity, pore size distribution, micro-scale porosity, pore size distribution, and fiber size statistical results of the slices at different positions; (5) Determining the size of the control volume according to the ranges of the nano-scale and micro-scale pore sizes and fiber sizes; the control volume is used to simulate the resin-based heat protection material; (6) At different positions within the control volume, according to the distribution law of the nano-scale pore sizes, generating microstructure components corresponding to the nano-scale pore size distribution law, using the microstructure components to simulate the nano-scale pores, and obtaining a finite element model; According to the distribution law of the micro-scale pore sizes, generating microstructure components corresponding to the micro-scale pore size distribution law, using the microstructure components to simulate the micro-scale pores, and obtaining a finite element model; According to the distribution law of the fiber sizes, generating microstructure components corresponding to the fiber size distribution law, using the microstructure components to simulate the nano-fibers, and obtaining a finite element model; (7) Conducting volume mesh division according to the finite element model established in step (6); (8) Applying temperature boundary conditions and periodic boundary conditions to the finite element model obtained in step (7) after volume mesh division; (9) Solving to obtain the equivalent thermal conductivity of the control volume.

2. The method for determining the heat transfer characteristics of a resin-based material considering physical properties and microstructure evolution according to claim 1, characterized in that (1) The obtaining of the material samples with different degrees of pyrolysis in step (1), conducting weight and size measurements, and calculating the density results of the material is specifically as follows: (1.1) Using wire cutting to cut samples with a length and width of 15 mm, and then starting from the surface carbonized layer, cutting thin slices with a thickness of 1 mm, numbered A1 to A6 respectively; (1.2) Placing the cut samples in a drying oven, setting the temperature at 70 °C, and maintaining humidity for 24 hours; (1.3) Measure the actual dimensions and weights of each of the thin slices A1 to A6, and calculate the density values ρ1 to ρ6. ρ1 is the density of the material after complete carbonization, and ρ6 is close to the density of the original material. Take ρ6 as the density value ρ of the original material p .

3. The method for determining the heat transfer characteristics by considering the physical properties and microstructure evolution of a resin-based material according to claim 2, wherein (2) According to the density results of each layer, calculating the pyrolysis degree values and the corresponding resin thermal conductivity, specifically as follows: (2.1) The internal pyrolysis rate of the material is: where ρ is the current density of the material; ρ c is the density after the material is completely pyrolyzed; ρ p is the density value of the raw material; according to this formula and the physical properties of the A1 layer being carbonized material and the A6 layer being raw material, the degree of pyrolysis of the A2 - A5 layers is calculated; (2.2) The thermal conductivity during the resin pyrolysis process is expressed as a function of the pyrolysis rate χ: k = (1 - χ)k p + χk c where k p is the thermal conductivity of the original unpyrolyzed material; k c is the thermal conductivity of the material after complete pyrolysis.

4. A method for determining the heat transfer characteristics of a resin-based material considering physical properties and microstructure evolution according to claim 1, characterized in that (3) The conducting of microstructure scanning observations in step (3) is specifically as follows: (3.1) Placing the material sample on a sputtering coater for sputtering treatment; (3.2) Placing the sputtered material sample in a scanning electron microscope for observation, adjusting the position of the material sample under the lens, and obtaining the material microstructure image; (3.3) Repeating step (3.2) multiple times to obtain the microstructure images of the heat protection material corresponding to layers A1 to A6.

5. The method for determining the heat transfer characteristics of a resin-based material considering physical properties and microstructure evolution according to claim 1, characterized in that: The control volume includes a nano-scale control volume and a micro-scale control volume, both of which are cubic structures, and the side length of the cube is more than twenty times the corresponding pore diameter.

6. The method for determining the heat transfer characteristics of a resin-based material considering physical properties and microstructure evolution according to claim 1, characterized in that: The method for generating microstructure components corresponding to the distribution laws of pore sizes and fiber sizes in step (6) is specifically as follows: According to the statistical results, nano-pores are generated in the nano-scale control volume, and micro-pores and fibers are generated in the micro-scale control volume according to the statistical results; the porosity and fiber volume fraction are consistent with the statistical results.

7. A method for determining the heat transfer characteristics of a resin-based material considering physical properties and microstructure evolution according to claim 6, characterized in that: The grid size of the microstructure components is equal to 1 / 5 to 1 / 20 times the diameter of the spherical pores.

8. A method for determining the heat transfer characteristics of a resin-based material considering physical properties and microstructure evolution according to claim 1, characterized in that The method for applying temperature boundary conditions and periodic boundary conditions in step (8) is specifically as follows: (8.1) Apply a temperature gradient boundary condition along the heat transfer direction from the inner surface to the outer surface of the control volume, and apply different temperature boundary conditions to the grid nodes on the upper and lower surfaces of the heat insulation material; (8.2) Apply periodic boundary conditions on the other four sides to make the temperatures of the grid nodes at corresponding positions on the two pairs of opposite sides consistent.

9. The method for determining the heat transfer characteristics by considering the physical properties and the microstructure evolution of a resin-based material according to claim 1, characterized in that: The step (9) of solving to obtain the equivalent thermal conductivity of the control volume is specifically as follows: Solve to obtain the heat flux along the heat transfer direction, and calculate the equivalent thermal conductivity of the control volume using Fourier's law.

10. A heat transfer characteristic determination system for a resin-based material considering physical properties and microstructure evolution, characterized in that It includes: A sample preparation and observation module, a microstructure statistics module, a model generation module, a grid division module, a loading boundary condition module, and a solution and post-processing module; Sample preparation and observation module: Take materials at different pyrolysis degrees for sectioning, drying, weighing and measuring dimensions to obtain density values, and calculate the corresponding pyrolysis degree values; conduct microstructure scanning and observation on different positions of the heat insulation material to obtain microstructure images of the heat insulation material corresponding to different positions; Microstructure statistics module: Statistically analyze the nano-scale porosity, pore size distribution, micro-scale porosity, pore size distribution, and fiber size based on the microstructure images to obtain the distribution laws of microstructure sizes; Model generation module: Determine the size of the control volume according to the nano-scale pores, micro-scale pores, and fiber size ranges; the control volume is used to simulate the heat insulation material; at different positions in the control volume, generate microstructure components corresponding to the distribution law of pore sizes according to the distribution law of pore sizes, and use the microstructure components to simulate pores and fibers to obtain a finite element model; Grid division module: Divide the volume grid of the finite element model; the grid size of the microstructure components is equal to 1 / 5 to 1 / 20 times the pore diameter; Loading boundary condition module: Apply a temperature gradient boundary condition along the heat transfer direction from the inner surface to the outer surface of the control volume, and apply periodic boundary conditions on the other four sides; Solution and post-processing module: Solve to obtain the heat flux along the heat transfer direction, and calculate the equivalent thermal conductivity of the control volume using Fourier's law.

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