A method for predicting thermal conductivity of composite materials based on vector separation method

Abstract

The present invention belongs to the technical field of insulating materials, and specifically discloses a method for predicting the thermal conductivity of composite materials based on a vector separation method, including: establishing a volume element model; calculating the contact probability of filler particles under different contact modes by an axis projection method; calculating the normal heat flux density of the contact surface under different contact modes according to a finite element method, obtaining the final overall contact probability of filler particles, comparing the change curves of the thermal conductivity and contact probability of composite materials measured under different filler particle sizes and volume fractions, obtaining a normalized numerical comparison diagram of the contact probability and the thermal conductivity, and obtaining the thermal conductivity of the composite material through the comparison diagram. The present invention calculates the contact probability of filler particles under different contact modes, introduces the heat flux density under different contact modes as a weight into the calculation of the contact probability of filler particles, takes into account the influence of the heat flux density of the heat conduction path under different filler contact modes on the overall thermal conductivity of the material, and improves the reliability of the prediction of the thermal conductivity of the composite material.

Description

Technical Field

[0001] The invention belongs to the technical field of insulating materials, and in particular relates to a method for predicting thermal conductivity of composite materials based on a vector separation method. Background Art

[0002] With the miniaturization and integration of high-voltage equipment and power electronic equipment, heat accumulation caused by overload operation or partial discharge directly affects the dielectric properties and service life of electrical equipment, endangering the safe and stable operation of the power grid. Polymer composites have excellent thermal conductivity and dielectric breakdown strength, and are very attractive electrical insulation materials. However, the improvement of thermal conductivity of polymer composites comes at the expense of electrical performance. With the continuous increase in voltage levels and output power, thermal breakdown occurs repeatedly. Therefore, it is very necessary to develop new dielectric materials with high thermal conductivity.

[0003] Silicone rubber, epoxy resin and other high molecular polymers commonly used in electrical insulation materials have low thermal conductivity and cannot dissipate heat well under high voltage drive. Excess heat accumulation inside the equipment will cause the temperature to rise, eventually destroying the insulation performance of the material and greatly reducing the reliability of the electrical equipment.

[0004] Although there is an obvious proportional relationship between the filling amount of filler and the overall thermal conductivity of the material, the increase in filler also reduces the insulation performance of the composite material, so it is necessary to develop an appropriate filling plan by establishing a predictive model. Foreign scholars have established relevant mathematical models to predict the thermal conductivity of composite materials under the influence of different filler sizes, contents, shapes and other factors to guide experimental preparation. Scholars established mathematical models such as the Maxwell model, Lewis-Nielsen model, and Agari model in the early days. The Maxwell model is only applicable to low filling content. To improve this, Agari took into account the connectivity of the polymer matrix and filler, improved the parallel and series models, and proposed an optimized version of the Agari model.

[0005] However, the above prediction models rarely take into account the influence of the heat flux density of the heat conduction path under different filler contact forms on the overall thermal conductivity of the material. In fact, for polyhedral fillers, such as SiC, the heat flux densities conducted under the two forms of filler face-to-face contact and face-to-edge contact are very different. If they are confused, it will have a great impact on the prediction accuracy of the model. Summary of the invention

[0006] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a method for predicting the thermal conductivity of composite materials based on the vector segregation method, so as to solve the problem that the existing prediction model cannot take into account the influence of the heat flux density of the heat conduction path under different filler contact modes on the overall thermal conductivity of the material.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] The present invention provides a method for predicting thermal conductivity of a composite material based on a vector separation method, comprising:

[0009] S1: Based on the SEM image of the composite material, a volume element model reflecting the overall morphology of the material is established;

[0010] S2: A pair of cubes representing filler particles are randomly selected in the volume element model for contact detection. The surface-to-surface contact probability and the surface-to-edge contact probability of the filler particles are calculated by the axial projection method.

[0011] S3: Based on the contact surface normal heat flux density in the face-to-face contact and face-to-edge contact modes calculated by the finite element method, the final overall contact probability of the filler particles is calculated through the face-to-face contact probability and face-to-edge contact probability of the filler particles obtained in S2, and the variation curves of the thermal conductivity and contact probability of the composite materials experimentally measured under multiple groups of different filler particle sizes and volume fractions are compared to obtain a normalized numerical comparison diagram of the contact probability and the thermal conductivity. The thermal conductivity of the composite material is obtained through the normalized numerical comparison diagram of the contact probability and the thermal conductivity.

[0012] Furthermore, the composite material in S1 consists of a polymer matrix and an inorganic filler.

[0013] Furthermore, in the volume element model in S1, a large cube is used to represent the polymer matrix, and small cubes that do not overlap each other are used to represent the inorganic filler. The side length and number of the small cubes are determined according to the actual filler particle size and volume fraction, and the center position of the filler is determined using the random function of Matlab to establish the volume element model:

[0014]

[0015] Where: N f represents the number of filler particles; V represents the total volume of the composite material; VOL f Indicates the filler volume fraction; V f is the volume of a single filler; D f is the side length of the cube filling.

[0016] Furthermore, the filler particle surface-to-surface contact probability and the surface-to-edge contact probability are calculated by the axis projection method in S2 as follows:

[0017] The vector segregation method of convex edge collision detection is applied to a cube in three-dimensional space. The segregation axis becomes a segregation plane. Two cubic filler particles are selected and projected on the vertical vector axis of the segregation plane. Whether the two filler particles are parallel is determined by the number of segregation planes. If they are parallel, the contact form is face-to-face contact; if they are not parallel, the contact form is face-edge contact. The projections of the vertical vector axis of the segregation plane of the two filler particles are calculated. If there is no overlapping part, the two filler particles are not in contact, otherwise the projections on the vertical vector axes of the remaining segregation planes will continue to be calculated. The filler particles are determined to be in contact if and only if the projections of the two filler particles on all the vertical vector axes of the segregation planes have overlapping parts. The next pair of filler particles is continuously detected to see if they are in contact until all the filler particle pairs in the volume element model are exhausted, thereby obtaining the logarithm of the face-to-face contact and face-edge contact of the filler particles.

[0018] Furthermore, the specific method for determining the contact form is as follows:

[0019] The two cubic filler particles are A and B, and the direction axes of A and B are defined as two vector groups OA[3] and OB[3], corresponding to two size arrays DA[3] and DB[3], PA and PB are the center points of the two filler particles; the elements of the OA[3] and OB[3] vector groups are the three axis vectors of the cubes A and B, respectively, and the elements of the DA[3] and DB[3] scalar groups are the lengths of the cubes A and B in the three axis directions, respectively;

[0020] Find the perpendicular vector axis of the segregation surface. The segregation surfaces of the two cubes are divided into two categories. One category is parallel to any face of the cube, and the other category's normal vector is obtained by cross-producting an axis vector of each of the two filler particles. The set of all perpendicular vector axial quantities of the segregation surfaces is called SA[j], where j is the number of perpendicular vector axis vectors. The number of perpendicular vector axes of the segregation surfaces is used to determine whether the two cubes are parallel. If the number is 3, they are parallel and the contact form is face-to-face contact. If the number is greater than 3, they are not parallel and the contact form is face-edge contact.

[0021] Furthermore, the method for determining the contact of filler particles is specifically as follows:

[0022] Calculate the projection of the vertical vector axis of the segregation surface of the two filler particles if the following inequality relationship exists:

[0023]

[0024] Then the two filler particles are not in contact, otherwise continue to calculate the projections on the vertical vector axes of the remaining segregation surfaces. If and only if the projections of the two filler particles on the vertical vector axes of all segregation surfaces have overlapping parts, the two filler particles are determined to be in contact.

[0025] Furthermore, the S2 further includes:

[0026] Continue to detect whether the next pair of filler particles in the volume element model are in contact, until all the filler particle pairs in the volume element model are exhausted, thereby obtaining the probability of surface-to-surface contact and surface-edge contact of the filler particles:

[0027]

[0028] Where: P S-S and P S-E Respectively represent the contact probabilities of surface-to-surface contact and surface-edge contact; N S-S and N S-E represents the effective contact pairs between filler particles in the face-to-face contact and face-to-edge contact modes respectively; N par and N int is the logarithm of parallel packing particles and non-parallel packing particles.

[0029] Furthermore, the contact surface normal heat flux density in the surface-to-surface contact and surface-to-edge contact modes calculated by S3 according to the finite element method is specifically:

[0030] The normal heat flux density of the contact surface under the ideal condition of the corresponding mode is calculated by the finite element method, and normalized to obtain the corresponding weight; two ideal conditions are selected to calculate the normal heat flux density between filler particles under the surface-to-surface contact and surface-to-edge contact modes;

[0031] According to Fourier's law of heat conduction, in steady state, the temperature inside the material system does not change with time, so:

[0032]

[0033] Where: q is the heat flux density, unit is W / m 2 ; T is temperature, unit is K;

[0034] Set boundary conditions: Set the initial temperatures of the upper and lower plates to 333.15K and 273.15K respectively, and the ambient temperature to 293.15K; the four surrounding surfaces of the model are thermally insulated; the thermal conductivity process is controlled by the above equation and constrained by the following equation:

[0035]

[0036] According to the above two formulas, when the filler particles just come into contact, the normal heat flux densities in the face-to-face contact mode and the face-to-edge contact mode are 3.08×10 6 W / m 2 and 7.56×10 5 W / m 2 .

[0037] Furthermore, the contact probability of the filler particles' surface-to-surface contact and surface-to-edge contact obtained in S2 is used to calculate the final filler particle overall contact probability:

[0038] The two contact modes, surface-to-surface contact and surface-to-edge contact, contribute differently to thermal conductivity, and different weights need to be introduced to more accurately predict thermal conductivity:

[0039]

[0040] Where: P represents the total contact probability; N tot represents the number of possible combinations between filler particles; ω1 and ω2 are the weights of the two contact modes, face-to-face contact and face-edge contact, respectively;

[0041] When the filler particles are just in contact, the corresponding weight is proportional to the normal heat flux density through the contact surface, and the corresponding ω1 and ω2 are 0.803 and 0.197 respectively; the contact probability of surface-to-surface contact and surface-to-edge contact obtained in S2 is used to obtain the final overall contact probability of the filler particles, as shown in the following formula:

[0042]

[0043] Furthermore, the S3 also includes:

[0044] The contact probability of multiple groups of filler particles with different filling volume fractions and different particle sizes was calculated. The filling volume fraction and particle size values ​​were in three groups or more, and the contact probability variation curve was obtained. It was compared with the thermal conductivity coefficient in different units. The normalized thermal conductivity error band was represented by a color block, and the filling point represented the normalized average contact probability value. A comparison diagram of the contact probability and the normalized thermal conductivity value was obtained. The thermal conductivity of the composite material was obtained based on the comparison diagram of the contact probability and the normalized thermal conductivity value, the contact probability of the composite material and the filler particle size.

[0045] The present invention has at least the following beneficial effects:

[0046] 1. The present invention calculates the contact probability of filler particles under different contact modes. By introducing the heat flux density under different contact modes as a weight into the calculation of the contact probability of filler particles, the influence of the heat flux density of the heat conduction path under different filler contact modes on the overall thermal conductivity of the material is taken into account, thereby improving the reliability of the prediction of the thermal conductivity of the composite material.

[0047] 2. The purpose of the present invention is to study the influence of the contact of polyhedral fillers on the thermal conductivity of composite materials, so as to improve the thermal conductivity of composite materials at a lower filler filling amount. The established prediction model can guide the preparation of corresponding materials. The prepared materials are expected to be used in high-voltage electrical equipment and integrated power electronic devices, solving the heat dissipation problem of electrical insulating materials while ensuring electrical performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0049] In the attached picture:

[0050] Figure 1 It is a flow chart of contact detection of composite materials;

[0051] Figure 2 It is a schematic diagram for determining the vertical vector axis of the first type of segregation surface;

[0052] Figure 3 It is a schematic diagram for determining the vertical vector axis of the second type of segregation surface;

[0053] Figure 4 It is a schematic diagram of the projection of the vertical vector axis of the segregation surface;

[0054] Figure 5 Schematic diagram of the surface-edge contact mode of composite fillers;

[0055] Figure 6 Schematic diagram of the surface-to-surface contact mode of composite fillers;

[0056] Figure 7 Set the boundary conditions for heat conduction;

[0057] Figure 8 Comparison diagram of normalized values ​​of contact probability and thermal conductivity. DETAILED DESCRIPTION

[0058] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

[0059] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present invention belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present invention.

[0060] like Figure 1 As shown, a method for predicting thermal conductivity of composite materials based on vector separation method comprises:

[0061] S1: Based on the SEM image of the composite material, a volume element model reflecting the overall morphology of the material is established. A large cube is used to represent the matrix, and a polyhedron of the corresponding filler shape is used to represent the filler particles, that is, a large cube is used to represent the polymer matrix, and small non-overlapping cubes are used to represent the inorganic filler. The side length and number of the small cubes are determined according to the actual filler particle size and volume fraction, as shown in the following formula. The random function of Matlab is used to determine the center position of the filler and establish the volume element model.

[0062]

[0063] Where N f represents the number of filler particles; V represents the total volume of the composite material; VOL f Indicates the filler volume fraction; V f is the volume of a single filler; D f is the side length of the cube filling.

[0064] Composite materials are composed of a polymer matrix with excellent insulation properties and an inorganic filler with high thermal conductivity, such as SiC / SR composite materials.

[0065] S2: A pair of cubes representing filler particles are randomly selected in the volume element model for contact detection. The probability of face-to-face contact and face-to-edge contact between filler particles are calculated by axis projection. The vector segregation method of convex edge collision detection is applied to cubes in three-dimensional space. Correspondingly, the segregation axis becomes a segregation surface. Two cube filler particles are selected and the two randomly selected filler particles are projected on the vertical vector axis of the segregation surface. First, the number of segregation surfaces is used to determine whether the two filler particles are parallel. If they are parallel, the contact form is face-to-face contact; if they are not parallel, the contact form is face-to-edge contact. Secondly, the projection of the vertical vector axis of the segregation surface of the two filler particles is calculated. If there is no overlap, the two filler particles are not in contact. Otherwise, the projection on the vertical vector axis of the remaining segregation surfaces will continue to be calculated. The filler particles are determined to be in contact if and only if the projections of the two filler particles on all the vertical vector axes of the segregation surfaces have overlapped parts. Taking this as an example, continue to detect whether the next pair of filler particles are in contact until all the filler particle pairs in the volume element model are exhausted, thereby obtaining the logarithm of the face-to-face contact and face-to-edge contact of the filler particles.

[0066] For the sake of convenience, let the two cubic filler particles be A and B, and define the direction axes of A and B as two vector groups OA[3] and OB[3], corresponding to two size arrays DA[3] and DB[3]. PA and PB are the center points of the two filler particles. The elements of the OA[3] and OB[3] vector groups are the three axis vectors of cubes A and B, respectively, and the elements of the DA[3] and DB[3] scalar groups are the lengths of cubes A and B in the three axis directions, respectively. The calculation process is explained using the separation axis L as an example, as shown in Figure 4As shown. First, find the perpendicular vector axis of the segregation surface. The segregation surfaces of the two cubes are divided into two categories. One category is parallel to any face of the cube, such as Figure 2 As shown, the other type of normal vector is obtained by cross-producting an axis vector of each of the two filler particles, as Figure 3 As shown, the set of all the vertical vector axes of the segregation surfaces is called SA[j], where j is the number of vertical vector axes. The number of vertical vector axes of the segregation surfaces is then used to determine whether the two cubes are parallel. If the number is 3, they are parallel and the contact form is face-to-face contact; if the number is greater than 3, they are not parallel and the contact form is face-edge contact. Next, calculate the projection of the vertical vector axes of the segregation surfaces of the two filler particles. If the following inequality relationship exists:

[0067]

[0068] If the two filler particles are not in contact, otherwise the projections on the remaining segregation planes' perpendicular vector axes will continue to be calculated. Finally, if and only if the projections of the two filler particles on all segregation planes' perpendicular vector axes have overlapping parts, the two filler particles are considered to be in contact.

[0069] Taking this as an example, we continue to detect whether the next pair of filler particles in the volume element model are in contact, until all the filler particle pairs in the volume element model are exhausted, thereby obtaining the probability of surface-to-surface contact and surface-edge contact of the filler particles:

[0070]

[0071] Where: P S-S and P S-E Respectively represent the contact probabilities of surface-to-surface contact and surface-edge contact; N S-S and N S-E represents the effective contact pairs between filler particles in the face-to-face contact and face-to-edge contact modes respectively; N par and N int is the logarithm of parallel packing particles and non-parallel packing particles.

[0072] S3: Since the two contact modes, surface-to-surface contact and surface-to-edge contact, contribute differently to thermal conductivity, different weights need to be introduced to more accurately predict thermal conductivity:

[0073]

[0074] Where: P represents the total contact probability; N tot It represents the number of possible combinations between filler particles; ω1 and ω2 are the weights of the two contact modes, face-to-face contact and face-edge contact, respectively.

[0075] Since the thermal conductivity of filler particles is fixed, the influence of the heat transfer path formed by the contact of filler particles on the overall thermal conductivity mainly depends on the normal heat flux density through the contact surface. To simplify the calculation, the finite element method is used to calculate the normal heat flux density of the contact surface under the ideal condition of the corresponding mode, and normalized to obtain the corresponding weight. Two ideal conditions are selected to calculate the normal phase heat flux density between filler particles under the surface contact and surface edge contact modes, such as Figure 5 and Figure 6 shown.

[0076] Since the model established in this paper uses solid heat conduction and there is no external heat source, the heat conduction method in the model is mainly conduction. According to Fourier's law of heat conduction, in a steady state, the temperature inside the material system does not change with time, and we get:

[0077]

[0078] Where: q is the heat flux density, unit is W / m 2 ; T is temperature, unit is K.

[0079] The boundary conditions are set as Figure 7 As shown. The initial temperatures of the upper and lower plates are set to 333.15K and 273.15K respectively, and the ambient temperature is 293.15K. The four surrounding surfaces of the model are thermally insulated to prevent the introduction of other heat transfer methods. The thermal conductivity process is controlled by the above equation and constrained by the following equation:

[0080]

[0081] According to the above two formulas, when the filler particles just come into contact, the normal heat flux densities in the face-to-face contact mode and the face-to-edge contact mode are 3.08×10 6 W / m 2 and 7.56×10 5 W / m 2 , when the filler particles are just in contact, the corresponding weight should be proportional to the normal heat flux density through the contact surface, so the corresponding ω1 and ω2 are 0.803 and 0.197 respectively. The final filler particle overall contact probability is obtained by the surface-to-surface contact probability and surface-to-edge contact probability obtained in S2, as shown in the following formula:

[0082]

[0083] The contact probability of filler particles with different filling volume fractions and different particle sizes is calculated, where the filling volume fraction and particle size values ​​are in three groups or more to ensure the credibility of the comparison results, thus obtaining the contact probability change curve as shown in Figure 8The filler volume fractions are 10 vol%, 20 vol%, and 30 vol%, respectively, and the filler particle sizes are 1.5 μm, 10 μm, 28 μm, and 40 μm, respectively.

[0084] In order to compare with thermal conductivity in different units, the calculated contact probability value and the experimental material thermal conductivity value are normalized, and the units of both are converted to unit 1 for comparison. The color block represents the normalized thermal conductivity error band, and the filling point represents the normalized average contact probability value. The contact probability and thermal conductivity normalized value comparison diagram is obtained; the thermal conductivity of the composite material is obtained based on the contact probability and thermal conductivity normalized value comparison diagram, the contact probability of the composite material and the filler particle size. It can be seen that all the filling points fall within the corresponding color block, which means that the contact probability of the filling particles is positively correlated with the thermal conductivity, further verifying the feasibility of the model.

[0085] It is known from common technical knowledge that the present invention can be implemented by other embodiments that do not deviate from its spirit or essential features. Therefore, the above disclosed embodiments are only illustrative in all respects and are not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are included in the present invention.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for predicting thermal conductivity of composite materials based on vector separation method, characterized in that: include: S1: Based on the SEM image of the composite material, a volume element model reflecting the overall morphology of the material is established; S2: A pair of cubes representing filler particles are randomly selected in the volume element model for contact detection. The surface-to-surface contact probability and the surface-to-edge contact probability of the filler particles are calculated by the axial projection method. S3: Based on the contact surface normal heat flux density in the face-to-face contact and face-to-edge contact modes calculated by the finite element method, the final filler particle overall contact probability is calculated through the filler particle face-to-face contact probability and face-to-edge contact probability obtained in S2, and the variation curves of the composite material thermal conductivity and contact probability experimentally measured under multiple groups of different filler particle sizes and volume fractions are compared to obtain a normalized numerical comparison diagram of contact probability and thermal conductivity. The thermal conductivity of the composite material is obtained through the normalized numerical comparison diagram of contact probability and thermal conductivity; In S2, the filler particle surface-to-surface contact probability and the surface-to-edge contact probability are calculated by the axis projection method respectively as follows: The vector segregation method of convex edge collision detection is applied to a cube in three-dimensional space, and the segregation axis becomes a segregation plane. Two cubic filler particles are selected, and the two filler particles are projected on the vertical vector axis of the segregation plane. Whether the two filler particles are parallel is determined by the number of segregation planes. If they are parallel, the contact form is face-to-face contact; if they are not parallel, the contact form is face-edge contact. The projections of the vertical vector axis of the segregation plane of the two filler particles are calculated. If there is no overlap, the two filler particles are not in contact, otherwise the projections on the vertical vector axes of the remaining segregation planes will continue to be calculated. The filler particles are determined to be in contact if and only if the projections of the two filler particles on all the vertical vector axes of the segregation planes have overlapped parts. Continue to detect whether the next pair of filler particles are in contact until all the filler particle pairs in the volume element model are exhausted, thereby obtaining the logarithm of the face-to-face contact and face-edge contact of the filler particles. The contact surface normal heat flux density in the surface-to-surface contact and surface-to-edge contact modes calculated by S3 according to the finite element method is specifically: The normal heat flux density of the contact surface under the ideal condition of the corresponding mode is calculated by the finite element method, and normalized to obtain the corresponding weight; two ideal conditions are selected to calculate the normal heat flux density between filler particles under the surface-to-surface contact and surface-to-edge contact modes; According to Fourier's law of heat conduction, in a steady state, the temperature inside the material system does not change with time, so: Where: q is the heat flux, unit is W / m 2 ; T is temperature, unit is K; Set boundary conditions: Set the initial temperatures of the upper and lower plates to 333.15K and 273.15K respectively, and the ambient temperature to 293.15K; the four surrounding surfaces of the model are thermally insulated; the thermal conductivity process is controlled by the above equation and constrained by the following equation: According to the above two formulas, when the filler particles just come into contact, the normal heat flux densities in the face-to-face contact mode and the face-to-edge contact mode are 3.08×10 6 W / m 2 and 7.56×10 5 W / m 2 .

2. The method for predicting thermal conductivity of composite materials based on vector separation method according to claim 1, characterized in that: The composite material in S1 is composed of a polymer matrix and an inorganic filler.

3. The method for predicting thermal conductivity of composite materials based on vector separation method according to claim 2, characterized in that: In the volume element model in S1, a large cube is used to represent the polymer matrix, and small non-overlapping cubes are used to represent the inorganic filler. The side length and number of the small cubes are determined according to the actual filler particle size and volume fraction, and the center position of the filler is determined using the random function of Matlab to establish the volume element model: Where: N f represents the number of filler particles; V represents the total volume of the composite material; VOL f Indicates the filler volume fraction; V f is the volume of a single filler; D f is the side length of the cube filling.

4. The method for predicting thermal conductivity of composite materials based on vector separation method according to claim 1, characterized in that: The specific method for determining the contact form is as follows: The two cubic filler particles are A and B, and the direction axes of A and B are defined as two vector groups OA[3] and OB[3], corresponding to two size arrays DA[3] and DB[3], PA and PB are the center points of the two filler particles; the elements of the OA[3] and OB[3] vector groups are the three axis vectors of the cubes A and B, respectively, and the elements of the DA[3] and DB[3] scalar groups are the lengths of the cubes A and B in the three axis directions, respectively; Find the perpendicular vector axis of the segregation surface. The segregation surfaces of the two cubes are divided into two categories. One category is parallel to any face of the cube, and the other category's normal vector is obtained by cross-producting an axis vector of each of the two filler particles. The set of all perpendicular vector axial quantities of the segregation surfaces is called SA[j], where j is the number of perpendicular vector axis vectors. The number of perpendicular vector axes of the segregation surfaces is used to determine whether the two cubes are parallel. If the number is 3, they are parallel and the contact form is face-to-face contact. If the number is greater than 3, they are not parallel and the contact form is face-edge contact.

5. The method for predicting thermal conductivity of composite materials based on vector separation method according to claim 1, characterized in that: The method for determining the contact of filler particles is specifically as follows: Calculate the projection of the vertical vector axis of the segregation surface of the two filler particles if the following inequality relationship exists: Then the two filler particles are not in contact, otherwise continue to calculate the projections on the vertical vector axes of the remaining segregation surfaces. If and only if the projections of the two filler particles on the vertical vector axes of all segregation surfaces have overlapping parts, the two filler particles are determined to be in contact.

6. The method for predicting thermal conductivity of composite materials based on vector separation method according to claim 5, characterized in that: The S2 further includes: Continue to detect whether the next pair of filler particles in the volume element model are in contact, until all the filler particle pairs in the volume element model are exhausted, thereby obtaining the probability of surface-to-surface contact and surface-edge contact of the filler particles: Where: P S-S and P S-E Respectively represent the contact probabilities of surface-to-surface contact and surface-to-edge contact; N S-S and N S-E represents the effective contact pairs between filler particles in the face-to-face contact and face-to-edge contact modes respectively; N par and N int is the logarithm of parallel packing particles and non-parallel packing particles.

7. The method for predicting thermal conductivity of composite materials based on vector separation method according to claim 1, characterized in that: The contact probability of the filler particles' surface-to-surface contact and surface-to-edge contact obtained in S2 is used to calculate the final filler particle overall contact probability: The two contact modes, surface-to-surface contact and surface-to-edge contact, contribute differently to thermal conductivity, and different weights need to be introduced to more accurately predict thermal conductivity: Where: P represents the total contact probability; N tot represents the number of possible combinations between filler particles; ω1 and ω2 are the weights of the two contact modes, face-to-face contact and face-edge contact, respectively; When the filler particles are just in contact, the corresponding weight is proportional to the normal heat flux density through the contact surface, and the corresponding ω1 and ω2 are 0.803 and 0.197 respectively; the contact probability of surface-to-surface contact and surface-to-edge contact obtained in S2 is used to obtain the final overall contact probability of the filler particles, as shown in the following formula:

8. The method for predicting thermal conductivity of composite materials based on vector separation method according to claim 7, characterized in that: The S3 further includes: The contact probability of multiple groups of filler particles with different filling volume fractions and different particle sizes was calculated. The filling volume fraction and particle size values ​​were in three groups or more, and the contact probability variation curve was obtained. It was compared with the thermal conductivity coefficient in different units. The normalized thermal conductivity error band was represented by a color block, and the filling point represented the normalized average contact probability value. A comparison diagram of the contact probability and the normalized thermal conductivity value was obtained. The thermal conductivity of the composite material was obtained based on the comparison diagram of the contact probability and the normalized thermal conductivity value, the contact probability of the composite material and the filler particle size.

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