Method for testing interface thermal resistance and effective fiber bridging length of fiber cement-based materials

Abstract

The application discloses a kind of fiber cement-based material interface thermal resistance and fiber effective lap length test method, comprising: preparing fiber random distribution's non-oriented group sample and fiber directional arrangement's oriented group sample, the effective thermal conductivity of two groups of samples is measured as measured value;Establish finite element heat transfer model, adjust interface thermal resistance value in model and simulate effective thermal conductivity, the simulated value of non-oriented group sample is compared with measured value, when simulated value approaches measured value, the interface thermal resistance between fiber and cement matrix is determined;For oriented group sample, increase fiber length in model and simulate effective thermal conductivity, when simulated value approaches measured value, the fiber length set at this time is effective lap length of fiber.This application can accurately obtain interface thermal resistance and fiber effective lap length by experiment and finite element simulation, overcome the problem that interface thermal resistance relies on experience in prior art, it is difficult to reflect the problem of fiber lap joint in simulation.

Description

Technical Field

[0001] This invention relates to the field of thermophysical property testing technology for composite materials, and in particular to a method for testing the interfacial thermal resistance and effective fiber overlap length of fiber-reinforced cementitious composite materials. Background Technology

[0002] Fiber-reinforced cementitious composites are widely used in construction, transportation, and energy fields due to their excellent mechanical properties and controllable functional characteristics. Thermal conductivity is a key parameter for evaluating their thermal performance. Carbon fibers, due to their high thermal conductivity, are often used as fillers to improve the thermal conductivity of cementitious materials. Studies have shown that the interfacial thermal resistance between the fiber and the matrix, as well as the fiber overlap state within the matrix, are the core factors determining the overall effective thermal conductivity of the composite material.

[0003] In existing technologies, the determination of interfacial thermal resistance largely relies on empirical values ​​or literature data. However, different fiber types, surface treatment states, and matrix formulations lead to significant differences in interfacial thermal resistance. Directly applying general empirical values ​​cannot accurately reflect the interfacial characteristics of actual material systems. For example, the thin metal layer on the surface of nickel-plated carbon fibers significantly improves interfacial contact, and using unmodified general empirical values ​​will introduce a large bias. Furthermore, in actual composite materials, fibers interlock to form a more efficient heat conduction network, but existing simulation methods cannot effectively reflect the contribution of fiber interlocking to thermal conductivity, and there is a lack of testing methods to quantify the effective fiber interlocking length.

[0004] Therefore, there is an urgent need for a test method that can accurately measure the thermal resistance at the fiber-cement matrix interface and quantify the effective overlap length of the fibers. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention proposes a method for testing the interfacial thermal resistance and effective fiber overlap length of fiber cement-based materials. By comparing experiments with finite element simulations, the interfacial thermal resistance and effective fiber overlap length can be accurately obtained, overcoming the problems in the prior art where the interfacial thermal resistance depends on empirical values ​​and the simulations fail to reflect the fiber overlap effect.

[0006] Firstly, a method for testing the interfacial thermal resistance of fiber cement-based materials includes: The thermal conductivity of the cement matrix and the fiber were measured separately. A set of non-oriented samples with randomly distributed fibers in a cement matrix and different fiber content were prepared. The effective thermal conductivity of each sample was measured to form the first benchmark measured dataset. A first finite element heat transfer model corresponding to the non-oriented sample group is established. In the first finite element heat transfer model, the fiber content of each sample is set, and the geometric parameters and orientation angle of the fiber are set according to the fiber distribution state of each non-oriented sample. At the same time, the measured thermal conductivity of the cement matrix and the fiber are set, and the initial value of the interface thermal resistance between the fiber and the cement matrix is ​​preset. Temperature boundary conditions are applied to the first finite element heat transfer model, the initial value of the interface thermal resistance is adjusted, and for each interface thermal resistance value, the effective thermal conductivity simulation value under each fiber doping is simulated to form the first effective thermal conductivity simulation dataset. The interfacial thermal resistance value corresponding to the first effective thermal conductivity simulation dataset when approximating the first benchmark measured dataset is determined as the interfacial thermal resistance value to be measured between the fiber and the cement matrix.

[0007] In one embodiment of the first aspect, the initial value of the interfacial thermal resistance ranges from 10. -4 K·m 2 / W~2×10 -4 K·m 2 / W, starting from the initial value of the interface thermal resistance, adjusts the interface thermal resistance value according to the preset step size.

[0008] In one embodiment of the first aspect, the orientation angle in the first finite element heat transfer model is randomly distributed within the range of 0° to 90°.

[0009] In one embodiment of the first aspect, the step of simulating the effective thermal conductivity at each fiber doping level for each interfacial thermal resistance value includes: For each fiber content, the first finite element heat transfer model is parametrically simulated with the fiber diameter as the variable. The initial value of the interface thermal resistance, the fiber content and other parameters in the model are kept unchanged. Several sets of different fiber diameter settings and their corresponding effective thermal conductivity simulation values ​​are obtained to form a scatter dataset. The scatter dataset was fitted using an exponential decay function; Using deterministic coefficients Evaluate the fitting effect; Substituting the actual fiber diameter of each sample into the exponential decay function, the simulated effective thermal conductivity value is calculated.

[0010] In one embodiment of the first aspect, the first effective thermal conductivity simulation dataset approximating the first benchmark measured dataset means that: Calculate the average relative error between the first effective thermal conductivity simulation dataset and the first benchmark measured dataset. With the goal of minimizing the average relative error, when the minimum value is less than a preset accuracy threshold, determine the interface thermal resistance value corresponding to the minimum value as the interface thermal resistance value to be measured.

[0011] Secondly, a method for testing the interfacial thermal resistance and effective fiber overlap length of fiber-cement based materials, wherein the interfacial thermal resistance value between the fiber and the cement matrix is ​​determined using the aforementioned method for testing the interfacial thermal resistance of fiber-cement based materials; further comprising: A set of oriented samples with different fiber contents and oriented fibers in a cement matrix were prepared. The effective thermal conductivity of each sample was measured to form a second benchmark measured dataset. A second finite element heat transfer model corresponding to the orientation group sample is established. In the second finite element heat transfer model, the fiber content of each sample is set, and the fiber is set to be parallel to the heat flow direction according to the fiber distribution state of each sample. At the same time, the measured thermal conductivity of cement matrix and fiber, the determined interfacial thermal resistance value between fiber and cement matrix, and the preset initial value of fiber length are set. Temperature boundary conditions are applied to the second finite element heat transfer model. The initial value of the fiber length is gradually increased while keeping the other geometric parameters of the fiber unchanged. The number of fibers is reduced accordingly to keep the fiber content constant. For each fiber length, the effective thermal conductivity simulation value under each fiber content is simulated to form the second effective thermal conductivity simulation dataset. The fiber length corresponding to the second effective thermal conductivity simulation dataset when approximating the second benchmark measured dataset is determined as the effective overlap length of the fiber in the cement matrix.

[0012] In one embodiment of the second aspect, an initial fiber length value is set according to different types of fibers; starting from the initial fiber length value, the fiber length is increased incrementally according to a preset step size.

[0013] In one embodiment of the second aspect, the second effective thermal conductivity simulation dataset approximating the second benchmark measured dataset means that: Calculate the average relative error between the simulated dataset of the second effective thermal conductivity and the measured dataset of the second benchmark. With the goal of minimizing the average relative error, when the minimum value is less than the preset accuracy threshold, the fiber length corresponding to the minimum value is determined as the effective overlap length to be measured.

[0014] In one embodiment of the second aspect, the thermal conductivity of the material and / or the effective thermal conductivity of the sample is measured using a steady-state method or a transient method.

[0015] In one embodiment of the second aspect, the fibers are set to be separated from each other in the second finite element heat transfer model.

[0016] Compared with existing methods, the present invention has the following advantages: 1. This invention does not rely on any pre-assumed interface thermal resistance value, but uses the measured effective thermal conductivity as a benchmark. It reverse-engineers the interface thermal resistance by approximating the simulated value with the measured value, transforming the traditional human subjective guess logic into a calibration logic. As long as the measured data is accurate, the reverse-engineered result is the true value, thereby fundamentally overcoming the deviation caused by relying on empirical values ​​or literature data.

[0017] 2. This invention, by increasing fiber length while simultaneously reducing the number of fibers, effectively eliminates the interference of material content variations on thermal conductivity while maintaining a constant fiber content. This allows for a separate examination of the contribution of additional thermally conductive pathways formed by fiber contact to the thermal conductivity of the composite material. Through this method, the key geometric parameter for effectively constructing a thermally conductive network—the effective overlap length—was successfully quantified, providing a new theoretical basis and evaluation index for the design and performance assessment of thermally conductive pathways in fiber-reinforced composites.

[0018] 3. This invention employs a step-by-step decoupling strategy, first calculating the interfacial thermal resistance and then the effective overlap length, avoiding ambiguity caused by parameter coupling and ensuring the uniqueness and accuracy of the results. This is based on the following: Non-oriented fibers are mostly in point contact, and their contact thermal resistance is negligible, allowing for independent inversion of the interfacial thermal resistance; oriented fibers have lateral contact, and both interfacial thermal resistance and overlap length affect heat transfer behavior. Therefore, the interfacial thermal resistance must be determined first, followed by the overlap length calculation, and this order cannot be reversed. Furthermore, in the oriented model, the fibers do not contact each other. By extending the fiber geometric length to equivalently simulate the overlap effect, the contribution of the overlap to heat conduction is accurately characterized while avoiding mesh distortion.

[0019] 4. This invention combines physical experiments with finite element simulation. By using measured data from multiple sets of samples with different fiber content, the simulation results are constrained and verified at multiple points. The average relative error is used as the evaluation index, which significantly improves the back-calculation accuracy of interfacial thermal resistance and effective overlap length. The interfacial thermal resistance and effective overlap length obtained by this invention can be used to guide the selection of fiber types, interfacial modification treatment, and optimization of fiber content, which helps to develop fiber-reinforced cementitious composite materials with higher thermal conductivity. Attached Figure Description

[0020] Figure 1 A flowchart illustrating a method for testing the interfacial thermal resistance of fiber cement-based materials, provided for an embodiment of the present invention. Figure 2 A flowchart illustrating a method for testing the effective overlap length of fibers provided in an embodiment of the present invention; Figure 3(a) is a schematic diagram of a non-oriented fiber model provided in an embodiment of the present invention; Figure 3(b) is a schematic diagram of an orientation fiber model provided by an embodiment of the present invention; Figure 4(a) shows the temperature field cloud map of the steady-state heat conduction simulation results of a non-oriented fiber model provided by an embodiment of the present invention. Figure 4(b) shows the temperature field cloud map of the steady-state heat conduction simulation results of an oriented fiber model provided by an embodiment of the present invention. Figure 5(a) is a comparison of the simulated and measured effective thermal conductivity values ​​of non-oriented samples under different interfacial thermal resistance values ​​provided by an embodiment of the present invention. Figure 5(b) is a comparison of the simulated and measured values ​​of the effective thermal conductivity of an orientation group sample with different fiber lengths provided by an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will now be described in further detail with reference to the accompanying drawings.

[0022] It should be understood that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0023] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0024] It should be understood that the term "and / or" used in this article is merely a description of the same field for related objects, indicating that three relationships can exist.

[0025] like Figure 1 As shown, the present invention provides a method for testing the interfacial thermal resistance of fiber cement-based materials, comprising the following steps: S100: The thermal conductivity of the cement matrix and fiber were measured separately and used as the basic input parameters for subsequent simulations; S200: Prepare a group of non-oriented samples with fibers randomly distributed in the cement matrix and different fiber contents, and measure the effective thermal conductivity of each sample in the non-oriented group to form the first benchmark measured data set; wherein, the fiber content refers to the volume fraction (vol%) or mass fraction (wt%) of the fiber in the cement matrix. S300: Establish a first finite element heat transfer model corresponding to the non-oriented sample group. In the first finite element heat transfer model, set the fiber content of each sample, and set the geometric parameters and orientation angle of the fiber according to the fiber distribution state of each non-oriented sample. At the same time, set the measured thermal conductivity of the cement matrix and the fiber, and preset the initial value of the interfacial thermal resistance between the fiber and the cement matrix. To ensure the consistency between simulation and experiment, the geometric parameters of the fiber (including but not limited to fiber diameter and fiber length) need to be set according to the actual size of the fiber. For example, it can be set according to the nominal size of the fiber. S400: Apply temperature boundary conditions to the first finite element heat transfer model, adjust the initial value of the interface thermal resistance, and for each interface thermal resistance, simulate the effective thermal conductivity output by the first finite element heat transfer model under each fiber content to form the first effective thermal conductivity simulation dataset. S500: The interfacial thermal resistance value corresponding to the first effective thermal conductivity simulation dataset when it approximates the first benchmark measured dataset is determined as the interfacial thermal resistance value to be measured between the fiber and the cement matrix.

[0026] In one possible implementation, the initial value of the interfacial thermal resistance is in the range of 10. -4 K·m 2 / W~2×10 -4 K·m 2 / W, adjust the interface thermal resistance value according to a preset step size; optionally, in increments of 5×10 -5 K·m 2 / W is the step size for adjusting the interface thermal resistance value to gradually approach the optimal value.

[0027] In one possible implementation, in the first finite element heat transfer model, the orientation angle of the fiber is randomly distributed in the range of 0° to 90°, that is, the angle between the fiber axis and the preset heat flow direction is uniformly and randomly distributed in the range of 0° to 90°.

[0028] In one possible implementation, step S400, for each interfacial thermal resistance value, simulates the effective thermal conductivity value output by the first finite element heat transfer model under each fiber doping level, specifically including the following: S410: For each fiber content, using the fiber diameter as a variable, perform a parametric steady-state simulation of the first finite element heat transfer model. Set an upper limit for the fiber diameter, keep the initial value of the interfacial thermal resistance and other parameters (fiber length, etc.) in the model unchanged, and obtain several sets of different fiber diameter settings and their corresponding simulated effective thermal conductivity values, forming a scatter dataset (d). i ,keff i ), where i is the index number of the data point in the scatter dataset, and d iSet the fiber diameter value, keff i This is the simulated value of the effective thermal conductivity; S420: The scatter dataset is fitted using an exponential decay function, the expression of which is: ; in, The effective thermal conductivity is the simulated value. The diameter of the fiber. , , These are the fitting coefficients; S430: Use deterministic coefficients To evaluate the fit, when the coefficients are determined... When the value is greater than the effective threshold, the exponential decay function is confirmed to be effective. S440: Substitute the actual fiber diameter of each sample into the exponential decay function to calculate the simulated value of the effective thermal conductivity. The effective threshold is preferably 0.95, i.e., the coefficient of determination. A value greater than 0.95 confirms the validity of the exponential decay function.

[0029] It should be noted that the above fitting process only applies to cases where the fiber diameter is greater than zero and not greater than its length. In this process, the finite element model uses the base model corresponding to the sample as a reference, keeping other parameters such as interfacial thermal resistance, fiber length, orientation angle, and fiber content constant. Only the fiber diameter is used as a variable for parametric scanning. Here, the change in fiber diameter equivalently simulates the effect of different fiber thicknesses on thermal conductivity, rather than changing the actual diameter of the sample. The purpose is to establish a rapid response relationship between fiber diameter and effective thermal conductivity, facilitating subsequent parametric analysis.

[0030] In one possible implementation, the simulated dataset of the first effective thermal conductivity described in step S500 approximates the first benchmark measured dataset, specifically as follows: Calculate the average relative error between the first effective thermal conductivity simulation dataset and the first benchmark measured dataset. With the goal of minimizing the average relative error, when the minimum value is less than a preset accuracy threshold, determine the interface thermal resistance value corresponding to the minimum value as the interface thermal resistance value to be measured.

[0031] like Figure 2 As shown, based on the same inventive concept, the present invention also provides a method for testing the effective overlap length of fibers. After determining the interfacial thermal resistance value between the fiber and the cement matrix using the above method, the method further includes the following steps: S600: Prepare a group of oriented samples with different fiber contents and oriented fibers in a cement matrix, and measure the effective thermal conductivity of each sample in the oriented sample group to form a second benchmark measured dataset. S700: Establish a second finite element heat transfer model corresponding to the orientation group sample. In the second finite element heat transfer model, set the fiber content of each sample, and set the fiber parallel to the heat flow direction according to the fiber distribution state of each sample. At the same time, set the measured thermal conductivity of cement matrix and fiber, the determined interfacial thermal resistance value between fiber and cement matrix, and the preset initial value of fiber length while ignoring the contact thermal resistance between fibers. It should be noted that the parallelism means that the angle between the fiber axis and the preset heat flow direction is 0°. Small deviations caused by the preparation process are allowed, and the deviation angle usually does not exceed ±10°. S800: Apply temperature boundary conditions to the second finite element heat transfer model, gradually increase the initial value of the fiber length, and keep the other geometric parameters of the fiber unchanged. Accordingly reduce the number of fibers under each fiber doping in the model to keep the fiber doping constant. For each fiber length, simulate the effective thermal conductivity output by the second finite element heat transfer model under each fiber doping, and form the second effective thermal conductivity simulation dataset. S900: The fiber length corresponding to the second effective thermal conductivity simulation dataset approximating the second benchmark measured dataset is determined as the effective overlap length of the fiber in the matrix.

[0032] In this invention, the effective overlap length is not the actual geometric contact length of the fiber, but an equivalent parameter; specifically, it refers to the length of a single fiber set in a heat transfer model with constant fiber content to achieve a thermal conductivity enhancement effect equivalent to the measured value. This parameter comprehensively characterizes the actual contribution of the heat conduction network formed by the overlap or close proximity between fibers to macroscopic heat conduction.

[0033] In one alternative implementation, the thermal conductivity of the material (cement matrix and / or fiber) and the effective thermal conductivity of the non-oriented and / or oriented groups of samples are measured using a steady-state or transient method.

[0034] In one possible implementation, the second effective thermal conductivity simulation dataset described in step S900 approximates the second benchmark measured dataset, specifically as follows: Calculate the average relative error between the simulated dataset of the second effective thermal conductivity and the measured dataset of the second benchmark. With the goal of minimizing the average relative error, when the minimum value is less than the preset accuracy threshold, the fiber length corresponding to the minimum value is determined as the effective overlap length to be measured.

[0035] The fibers include, but are not limited to, carbon fibers (such as PAN-based carbon fibers and pitch-based carbon fibers), low-carbon steel fibers, basalt fibers, glass fibers, and aramid fibers. The initial value of the fiber length and the adjustment step size are set according to different types of fibers. The initial value of the fiber length is adjusted according to the step size. If higher prediction accuracy is required, the set step size can be reduced accordingly.

[0036] In steps S400 and S800, for each fiber dosage, a single simulation or multiple simulations can be performed, and the average of the simulation results can be used as the simulated effective thermal conductivity value for that dosage. When performing a single simulation, the average relative error in steps S500 and S900 can be expressed as: ; Where N represents the number of fiber content types, i.e. the number of samples in the non-oriented group / oriented group, and j is the index number of fiber content, j∈[1,N]. This represents the measured effective thermal conductivity of the sample with the j-th fiber content. This represents the simulated effective thermal conductivity value output by the finite element model for the j-th fiber content.

[0037] Furthermore, based on curve fitting, point error verification is adopted: when the minimum value of the average relative error is less than the preset accuracy threshold, the relative error between the simulated effective thermal conductivity value and the benchmark measured value for each fiber content under the interface thermal resistance value / fiber length corresponding to the minimum value is calculated; if the relative errors of each group are less than the preset accuracy threshold, the interface thermal resistance value / fiber length is officially adopted.

[0038] In one optional implementation, the first finite element heat transfer model and / or the second finite element heat transfer model are constructed using representative volume elements (RVEs). The RVEs are used to characterize the microstructure of the fiber cementitious composite material, and their fiber distribution is consistent with the fiber distribution in the corresponding sample.

[0039] Furthermore, in one optional embodiment, based on the first finite element heat transfer model, the fiber orientation distribution is modified to be parallel to the heat flow direction to obtain the second finite element heat transfer model; in another optional embodiment, a new finite element heat transfer model is established for the orientation group sample, with the fiber orientation set to be parallel to the heat flow direction to obtain the second finite element heat transfer model.

[0040] Preferably, in the second finite element heat transfer model, the fibers are geometrically set to be separated from each other, that is, the distance between the fibers is greater than a preset allowable threshold, so as to avoid mesh distortion and calculation divergence caused by fiber contact. The overlapping effect between fibers is equivalently simulated by extending the geometric length of a single fiber.

[0041] The feasibility and effectiveness of the present invention will be explained in detail below by selecting a nickel-plated carbon fiber reinforced cementitious composite material as the test object.

[0042] Step 1: Determine the thermal conductivity of the material and prepare a sample; Nickel-plated carbon fiber with a length of 2 mm was selected as the reinforcing phase, and cement matrix was selected as the matrix phase. The thermal conductivity of the cement matrix was measured to be 2.4414 W / (m·K) and that of the nickel-plated carbon fiber was 200 W / (m·K) using the transient flat plate heat source method (e.g., a DRE-2C thermal conductivity meter).

[0043] Two groups of samples with different fiber content were prepared, expressed as mass fractions: 0.1 wt%, 0.2 wt%, 0.3 wt%, 0.4 wt%, 0.5 wt%, 0.6 wt%, and 0.7 wt%. Non-oriented group: The fibers are randomly distributed in the cement matrix, and the orientation angle is uniformly and randomly distributed between 0° and 90°; Orientation group: The fiber orientation is oriented parallel to the preset heat flow direction (sample axis) by magnetic field induction, with an included angle of 0°.

[0044] Step 2: Calculate the interfacial thermal resistance of the sample; Using the same transient flat plate heat source method, the effective thermal conductivity of non-oriented samples with different fiber content was measured to form the first benchmark measured data set.

[0045] As shown in Figure 4(a), a first finite element heat transfer model corresponding to the non-oriented group samples was established using COMSOL finite element software, and the temperature field distribution inside the model was solved using the steady-state thermal balance equation. In the model, the fiber content of each sample was set, and the geometric parameters of the fibers (fiber length 2 mm, fiber diameter 0.5 mm) and orientation angle (randomly distributed from 0° to 90°) were set according to the fiber distribution state of the non-oriented group samples. The measured thermal conductivity of the cement matrix and fibers was also set.

[0046] Set the interface thermal resistance to 10 respectively -4 K·m 2 / W, 5×10 -5 K·m 2 / W and 0K·m 2 / W is used for simulation calculations; where 0 K·m 2 / W represents the boundary condition for ideal heat conduction. For each interfacial thermal resistance value, the effective thermal conductivity is simulated for each fiber doping level, forming multiple sets of first effective thermal conductivity simulation datasets. Each set of simulation datasets corresponds to one interfacial thermal resistance value, as shown in Figure 5(a).

[0047] Each set of simulated datasets is compared with the first benchmark measured dataset, and the approximation degree between the simulated and measured values ​​is evaluated by calculating the average relative error between the two sets of data. In this embodiment, the interface thermal resistance value is 5×10⁻⁶. -5 K·m 2 The smallest average relative error corresponding to / W indicates that the simulated value and the measured value are in best agreement at this interface thermal resistance value. Therefore, the interface thermal resistance between the nickel-plated carbon fiber and the cement matrix is ​​determined to be 5×10. -5 K·m 2 / W.

[0048] Step 3: Calculate the effective fiber overlap length of the sample; Based on the first finite element heat transfer model, and according to the fiber distribution of the oriented sample, the fibers are set to be parallel to the heat flow direction. A predetermined interfacial thermal resistance (5 × 10⁻⁶) is used. -5 K·m 2 / W), establish a second finite element heat transfer model corresponding to the orientation group sample, and use the steady-state thermal balance equation to solve the temperature field distribution inside the model, as shown in Figure 5(b).

[0049] To avoid mesh distortion, the model sets a minimum allowable distance between fibers geometrically to separate the fibers from each other. To simulate the overlapping effect between fibers, an equivalent method of extending the geometric length of a single fiber is adopted: keeping the fiber content constant, the length of a single fiber in the model is gradually increased, and the number of fibers is reduced accordingly.

[0050] In this embodiment, carbon fiber is used, and the initial fiber length is set to 2 mm. Starting from the preset initial fiber length of 2.0 mm, the length is increased in increments of 1.0 mm to 4.0 mm, and the contact thermal resistance between fibers is ignored. This corresponds to three sets of finite element simulation data. While increasing the fiber length, the number of fibers in the model is reduced accordingly for each fiber doping level to keep the fiber doping level constant.

[0051] For each fiber length, the effective thermal conductivity is simulated for each fiber doping amount, forming multiple sets of second effective thermal conductivity simulation datasets. Each set of simulation datasets corresponds to a fiber length, as shown in Figure 5(b).

[0052] The simulated datasets for different fiber lengths were compared with the second benchmark measured dataset to calculate the average relative error; the average relative error was minimized when the fiber length was set to 3.0 mm. Based on this, the relative error between the simulated and measured effective thermal conductivity values ​​for each fiber dosage condition with a fiber length of 3.0 mm was calculated within the dosage range. All relative errors were less than the preset accuracy threshold, indicating that the simulated values ​​approximate the measured values. Therefore, under this material system and process conditions, the effective overlap length of the carbon fiber was determined to be 3.0 mm.

[0053] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. For those skilled in the art, various improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for testing the interfacial thermal resistance of fiber cement-based materials, characterized in that, include: The thermal conductivity of the cement matrix and the fiber were measured separately. A set of non-oriented samples with randomly distributed fibers in a cement matrix and different fiber content were prepared. The effective thermal conductivity of each sample was measured to form the first benchmark measured dataset. A first finite element heat transfer model corresponding to the non-oriented sample group is established. In the first finite element heat transfer model, the fiber content of each sample is set, and the geometric parameters and orientation angle of the fiber are set according to the fiber distribution state of each non-oriented sample. At the same time, the measured thermal conductivity of the cement matrix and the fiber are set, and the initial value of the interface thermal resistance between the fiber and the cement matrix is ​​preset. Temperature boundary conditions are applied to the first finite element heat transfer model, the initial value of the interface thermal resistance is adjusted, and for each interface thermal resistance value, the effective thermal conductivity simulation value under each fiber doping is simulated to form the first effective thermal conductivity simulation dataset. The interfacial thermal resistance value corresponding to the first effective thermal conductivity simulation dataset when approximating the first benchmark measured dataset is determined as the interfacial thermal resistance value to be measured between the fiber and the cement matrix.

2. The method for testing the interfacial thermal resistance of fiber cement-based materials according to claim 1, characterized in that, The initial value of the interface thermal resistance is in the range of 10. -4 K·m 2 / W~2×10 -4 K·m 2 / W, starting from the initial value of the interface thermal resistance, adjusts the interface thermal resistance value according to a preset step size.

3. The method for testing the interfacial thermal resistance of fiber cement-based materials according to claim 1, characterized in that, In the first finite element heat transfer model, the orientation angle is randomly distributed within the range of 0° to 90°.

4. The method for testing the interfacial thermal resistance of fiber cement-based materials according to claim 1, characterized in that, The simulation of the effective thermal conductivity under different fiber doping levels for each interfacial thermal resistance value includes: For each fiber content, the first finite element heat transfer model is parametrically simulated with the fiber diameter as the variable. The initial value of the interface thermal resistance, the fiber content and other parameters in the model are kept unchanged. Several sets of different fiber diameter settings and their corresponding effective thermal conductivity simulation values ​​are obtained to form a scatter dataset. The scatter dataset was fitted using an exponential decay function; Using deterministic coefficients Evaluate the fitting effect; Substituting the actual fiber diameter of each sample into the exponential decay function, the simulated effective thermal conductivity value is calculated.

5. The method for testing the interfacial thermal resistance of fiber cement-based materials according to claim 1, characterized in that, The first effective thermal conductivity simulation dataset approximates the first benchmark measured dataset in that: Calculate the average relative error between the first effective thermal conductivity simulation dataset and the first benchmark measured dataset. With the goal of minimizing the average relative error, when the minimum value is less than a preset accuracy threshold, determine the interface thermal resistance value corresponding to the minimum value as the interface thermal resistance value to be measured.

6. A method for testing the interfacial thermal resistance and effective fiber overlap length of fiber-cement based materials, characterized in that, The method described in any one of claims 1-5 is used to determine the interfacial thermal resistance between the fiber and the cement matrix; further comprising: A set of oriented samples with different fiber contents and oriented fibers in a cement matrix were prepared. The effective thermal conductivity of each sample was measured to form a second benchmark measured dataset. A second finite element heat transfer model corresponding to the orientation group sample is established. In the second finite element heat transfer model, the fiber content of each sample is set, and the fiber is set to be parallel to the heat flow direction according to the fiber distribution state of each sample. At the same time, the measured thermal conductivity of cement matrix and fiber, the determined interfacial thermal resistance value between fiber and cement matrix, and the preset initial value of fiber length are set. Temperature boundary conditions are applied to the second finite element heat transfer model. The initial value of the fiber length is gradually increased while keeping the other geometric parameters of the fiber unchanged. The number of fibers is reduced accordingly to keep the fiber content constant. For each fiber length, the effective thermal conductivity simulation value under each fiber content is simulated to form the second effective thermal conductivity simulation dataset. The fiber length corresponding to the second effective thermal conductivity simulation dataset when approximating the second benchmark measured dataset is determined as the effective overlap length of the fiber in the cement matrix.

7. The method for testing the interfacial thermal resistance and effective fiber overlap length of fiber-cement based materials according to claim 6, characterized in that, Set an initial fiber length value based on different fiber types; starting from the initial fiber length value, increase the fiber length incrementally according to the preset step size.

8. The method for testing the interfacial thermal resistance and effective fiber overlap length of fiber-cement based materials according to claim 6, characterized in that, The second effective thermal conductivity simulation dataset approximates the second benchmark measured dataset in that: Calculate the average relative error between the simulated dataset of the second effective thermal conductivity and the measured dataset of the second benchmark. With the goal of minimizing the average relative error, when the minimum value is less than the preset accuracy threshold, the fiber length corresponding to the minimum value is determined as the effective overlap length to be measured.

9. The method for testing the interfacial thermal resistance and effective fiber overlap length of fiber-cement based materials according to claim 6, characterized in that, The thermal conductivity of the material and / or the effective thermal conductivity of the sample are measured using steady-state or transient methods.

10. The method for testing the interfacial thermal resistance and effective fiber overlap length of fiber-cement based materials according to claim 6, characterized in that, In the second finite element heat transfer model, the fibers are set to be separated from each other.

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