A Method for Damp Heat Cycling Test and Performance Degradation Prediction of Resin-Based Composite Materials

Abstract

This invention discloses a method for hydrothermal cycling testing and performance degradation prediction of resin-based composite materials. The method first constructs a standard hydrothermal cycling test system for resin-based composite materials; secondly, it simultaneously acquires the glass transition temperature (GTH) and macroscopic mechanical property parameters of the material at different aging cycles using this system; then, it establishes a degradation function relationship between the GTH and hydrothermal environmental conditions (temperature, relative humidity, number of cycles); further, it constructs a quantitative mapping model between the GTH and key macroscopic mechanical properties (such as modulus and strength); finally, it integrates the above models to achieve quantitative prediction of the composite material's performance degradation process based on a known environmental spectrum. This invention connects the process from environmental excitation to microscopic evolution and then to macroscopic failure, providing accurate performance degradation prediction and offering a scientific basis for the engineering application of resin-based composite materials under different hydrothermal cycling conditions.

Description

Technical Field

[0001] This invention belongs to the field of service behavior and life assessment technology of resin-based composite materials. Specifically, it relates to a test method and performance degradation prediction method for resin-based composite materials in humid and hot cycling environments. In particular, it relates to a modeling technique for obtaining glass transition temperature and mechanical parameters through macroscopic and microscopic joint experiments, and establishing a quantitative relationship between humid and hot environmental conditions and mechanical property degradation laws. Background Technology

[0002] Resin-based composite materials are widely used in aerospace, shipbuilding, and transportation equipment, but they are often subjected to humid and hot cycling environments with alternating temperature and humidity during service. The resin matrix is ​​prone to moisture absorption and softening, and interfacial bonding strength decreases, leading to a continuous degradation of the macroscopic mechanical properties of the laminate, such as elastic modulus and strength, affecting structural reliability. Therefore, accurately characterizing and predicting the degradation of material properties under humid and hot cycling conditions is of significant engineering importance. Existing research mostly employs isothermal and humidity control or long-term exposure tests, primarily focusing on changes in macroscopic tensile, compressive, and shear mechanical properties, lacking research on the glass transition temperature (GCT). Systematic analysis of microscopic thermal performance parameters such as temperature, humidity, and cycle number is required. However, environmental factors such as temperature, humidity, and cycle number are often treated separately, and a multi-factor coupled degradation model suitable for damp-heat cycling conditions has not yet been developed. Therefore, it is necessary to propose a modeling method that combines damp-heat cycling experiments, microscopic thermal analysis, and macroscopic mechanical testing to construct a model. The functional relationship between environmental conditions and the number of cycles is established, and a framework is built. A mapping model to mechanical properties is used to accurately predict the performance degradation of resin-based composite materials. Summary of the Invention

[0003] The purpose of this invention is to address the problems of parameter dispersion, insufficient mechanism correlation, and limited predictive ability in existing studies on the damp heat aging of resin-based composite materials, and to propose a method for damp heat cycling testing and performance degradation prediction of resin-based composite materials. This method establishes a unified damp heat cycling test system, combines microscopic thermal analysis and macroscopic mechanical testing, establishes a functional relationship between the glass transition temperature and temperature, humidity, and number of cycles, and further establishes a mapping model between the glass transition temperature and the macroscopic mechanical parameters of the composite material, thereby achieving quantitative prediction of the evolution of material properties with damp heat cycling.

[0004] To achieve the above objectives, the present invention provides the following technical solution, comprising the following steps: Step 1: Design and Construction of the Damp Heat Cycling Test System Based on the typical service environment of resin-based composite materials and the requirements for model parameter solution accuracy and experimental cost, representative temperature and humidity cycling conditions were established with reference to relevant clauses on damp heat testing in environmental testing standards (such as the damp heat method in MIL-STD-810H). Using the daily cycle as the basic time unit, the alternation range of temperature and relative humidity was reasonably set, and various gradient temperature and humidity cycling load spectra were constructed through combinations of heating, isothermal and drying stages. The damp heat cycling conditions included at least three representative types of temperature and humidity alternation, used to simulate extreme high-temperature and high-humidity conditions, typical tropical / subtropical diurnal alternation conditions, and high-humidity absorption followed by high-temperature and low-humidity drying conditions. Each condition introduced temperature and humidity gradients and cyclic stress field changes through alternating high-temperature and high-humidity stages with lower temperature or lower humidity stages to comprehensively characterize the impact of different types of damp heat cycles on material properties and failure mechanisms. A gradual change process was set during the temperature and humidity switching stage to reduce the unexpected damage to the samples caused by transient temperature and humidity shocks, more closely approximating the rate of change in the actual service environment. According to subsequent tests, resin-based composite unidirectional laminate samples were prepared according to standard processes and divided into an unaged control group and test groups with different numbers of damp heat cycles.

[0005] Step Two: Macro- and Micro-performance testing Under different humid heat cycle conditions set in Step 1, at a predetermined number of cycles (e.g., a number of typical cycle steps) , , After the completion of the tests, microscopic thermal analysis and macroscopic mechanical property tests were conducted on the resin-based composite material samples to obtain the glass transition temperature. And the mechanical property parameters of unidirectional laminates.

[0006] At the microscopic level, differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) are preferred thermal analysis methods to test samples after undergoing different numbers of hygrothermal cycles and obtain the glass transition temperature at each cycle number. By studying the same material system under different combinations of temperature, humidity, and cycle counts... The measurement results were organized and constructed. The basic dataset showing how aging varies with the degree of aging under wet and hot cycling provides a foundation for subsequent development of... This provides a basis for the aging kinetic model of the driving variables.

[0007] At the macroscopic mechanical level, standard mechanical tests are performed on the batches of unidirectional laminated plate samples corresponding to the microscopic thermal analysis, including but not limited to tensile tests, compression tests, and shear tests, to obtain the elastic modulus and strength parameters of the material under different hygrothermal cycles. The macroscopic mechanical parameters may include the elastic modulus in the fiber direction and transverse direction. , shear modulus Fiber direction tensile strength Compressive strength And so on. By statistically analyzing and summarizing the test results under different wet and hot cycle conditions and cycles, a macro-micro one-to-one correspondence database is formed, so that each wet and hot cycle state simultaneously has... With a set of macroscopic mechanical performance parameters.

[0008] Step 3: Establishment of a damp-heat cycle aging model In step three, the glass transition temperature is determined based on the different temperatures, humidity levels, and number of damp-heat cycles obtained in step two. Data, building upon A kinetic model of humid heat aging with the driving variable is used to characterize the degree of aging and its evolution of resin-based composite materials in alternating humid heat environments.

[0009] In polymer material aging studies, the Arrhenius model is widely used to characterize the accelerating effect of temperature on chemical degradation processes such as hydrolysis, oxidation, and chain breakage. Its standard form is: (1) in, The reaction rate constant is determined by temperature. The frequency factor represents the rate of reaction without the influence of temperature. For activation energy, The gas constant is 8.314. ), For temperature, Represented by natural constant An exponential function with base , i.e. (in ).

[0010] Considering the effect of humidity, and referring to the Peck model, relative humidity is used as a power-law acceleration factor: (2) in, The reaction rate constant is the effect of relative humidity. Relative humidity, Humidity is an influencing factor. This indicates that higher humidity leads to faster reactions (e.g., water-catalyzed hydrolysis). The combined approach yields a physically sound Peck-Arrhenius type thermo-hygroscopic accelerated aging model to describe the coupling effect of temperature and humidity on the aging rate. (3) in, Let be the reaction rate constant influenced by both temperature and relative humidity. To account for the alternating changes in temperature and humidity over time in a cyclic humid environment, a cumulative dose variable is introduced. Characterizes the cumulative effect of aging. Aging dose per cycle. Defined as: (4) in, The total time of one cycle. The time for aging under damp heat. for The corresponding ambient relative humidity, for The corresponding ambient temperature. Since each cycle in the experiment contains multiple isothermal and humidity-controlled platforms and linear transition sections, the integral can be discretized into several intervals.

[0011] (1) For the constant temperature and humidity platform section (constant temperature and humidity): (5) in, , , and The first The aging dosage, time, relative humidity, and temperature under the segmented damp heat cycle conditions (for example, if the test sets up three damp heat cycle conditions, then...) ).

[0012] (2) For the temperature and humidity transition section (linear temperature and humidity change), the Gauss-Legendre five-point integral approximation is adopted: (6) In the formula, , representing the fifth point in the Gauss-Legend quadrature. A quadrature node, and These represent the position of the dimensionless integration point and the weight coefficient corresponding to that node. , These are the starting and ending temperatures of the transition section. , The relative humidity at the beginning and end of the transition section.

[0013] This will give us the [number]. Aging dosage under humid and hot cycling conditions The cumulative dose is: (7) in, This represents the number of iterations for the corresponding stage.

[0014] The macroscopic manifestation of polymer performance degradation typically follows an exponential saturation law, with the glass transition temperature... Sensitive to the movement of resin molecular chains, it directly reflects the structural relaxation and chemical degradation of the resin phase, and is one of the most intuitive and stable thermodynamic parameters characterizing the degree of damp heat aging. As a representative performance indicator characterizing the aging degree of the resin matrix composite material, a material... The following relationship exists between the cumulative dose and the cumulative dose: (8) in, ,yes The relative change This is the initial value of the glass transition temperature in the dry state. for The maximum change value represents the maximum possible change in the glass transition temperature of the resin-based composite material under extreme humid and hot conditions. This parameter can be determined through long-term aging test results or empirical values ​​from references. Another method is to... Set as initial value To account for the most extreme aging scenarios.

[0015] This led to the establishment of the glass transition temperature. With temperature relative humidity and damp heat aging time (Number of loops) The functional relationship is determined by obtaining the results of hydrothermal cycling experiments for different numbers of cycles. Substitute the measured data into the equation and adjust the model parameters. , and After identification, the result is as follows: The kinetic model for wet heat aging with the driving variable is as follows: (9) in, For cumulative dose variable The corresponding time.

[0016] Step Four: Construction of a correlation model with mechanical properties The degradation of the mechanical properties of the component materials is the core of the aging process of composite materials in humid and hot environments. In order to quantitatively describe this degradation process, it is first necessary to construct a model of the mechanical property degradation of the component materials.

[0017] Introducing dimensionless temperature Its expression is as follows: (10) In the formula, The glass transition temperature. For the test temperature, This is the initial value of the glass transition temperature in the dry state. This refers to the reference temperature or room temperature.

[0018] The main consideration is the impact of cyclic humid and hot environments on the properties of composite matrix. Therefore, the elastic modulus of the resin-based composite matrix is ​​established. and shear modulus and The functional relationship between the two is used to describe the degradation of mechanical properties during the damp heat aging process, using dimensionless temperature. The power function can be used to approximate it as: (11) In the formula, , These represent the elastic modulus and shear modulus of the resin-based composite matrix in its initial room temperature dry state, respectively. and Let be the material's damp heat degradation constant, taken from the Composite Materials Handbook. .

[0019] To derive the mechanical properties of a single-layer plate from the mechanical properties of its constituent materials, a quantitative relationship between microscopic and macroscopic mechanical parameters was established using the blending ratio method. This was applied to the elastic modulus of unidirectional laminates. , have (12) (13) Shear modulus for unidirectional laminates have: (14) Longitudinal tensile strength of unidirectional laminates and longitudinal compressive strength have: (15) (16) In equations (12)-(16) , , , , These are the volume fraction, elastic modulus, shear modulus, tensile strength, and compressive strength of the composite fiber, respectively. , , These represent the volume fraction, elastic modulus, and shear modulus of the composite matrix, respectively.

[0020] Established through step four The mapping relationship model between microscopic thermal properties and macroscopic mechanical properties realizes the quantitative correlation between microscopic thermal properties and macroscopic mechanical properties.

[0021] Step 5: Performance Prediction Validation and Application In step five, based on the macroscopic performance prediction model completed in step four, the model is validated and applied in practice. The goal of this step is to ensure the accuracy and applicability of the prediction model and to apply it to actual engineering projects for performance degradation assessment and lifetime prediction.

[0022] To verify the accuracy of the macroscopic performance prediction model established in step four, the prediction results are compared with the actual experimental values ​​obtained in step two to evaluate the accuracy of the prediction. The prediction accuracy of the model is quantified by calculating the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). Assume that... Group 1 experimental data, for the first Group data ( ), This represents the actual experimental measurement value. The specific formulas for RMSE, MAE, and MAPE, representing the model's predicted values, are as follows: (17) (18) (19) If the predicted value and the measured value are within an acceptable range of engineering error (e.g., the error is less than ±15% and the trend is consistent), it indicates that the established performance degradation function model has good accuracy, reliability and a certain extrapolation ability.

[0023] Once the model has been validated, it can be applied to practical engineering projects to assess the performance degradation and predict the lifespan of resin-based composite materials, ensuring the long-term safety and reliability of engineering structures in complex environments.

[0024] The advantages and beneficial effects of this invention are as follows: by constructing a standardized wet heat cycling test system for resin-based composite materials, the glass transition temperature of different aging cycles can be obtained simultaneously within the same test framework. Compared with macroscopic mechanical performance parameters, it significantly reduces parameter dispersion and improves data comparability; As a key bridge connecting humid and hot environmental excitation and macroscopic mechanical degradation, establish The degradation function relationship between temperature, humidity, and cycle number was established, and further construction was performed. A quantitative mapping model between the mechanical properties and key mechanical properties such as modulus and strength is established, thereby enabling continuous and quantifiable prediction of mechanical performance parameters from environmental spectrum input. The method has a clear model structure, and the parameters can be calibrated by limited experimental data. It has good portability and engineering applicability, and can provide a reliable basis for performance evaluation, life management and safety margin decision-making of resin-based composite materials under different humid heat cycling conditions. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the overall process of the method of the present invention.

[0026] Figure 2 Diagram showing setup for damp heat cycling test. Detailed Implementation

[0027] To further clarify the technical solution of the present invention, the present invention will be described below with reference to a typical embodiment, but it should not be construed as a limitation on the scope of protection of the present invention.

[0028] This embodiment discloses a method for wet heat cycling testing and performance degradation prediction of resin-based composite materials, the flowchart of which is shown below. Figure 1 As shown, the main steps include: Step 1: Design and Construction of the Damp Heat Cycling Test System This implementation focuses on a certain type of carbon fiber / epoxy resin composite material, and sets the temperature and humidity for a damp heat cycling test according to Method 507.5 (Damp Heat Test) in the MIL-STD-810H standard. Each cycle is 24 hours, and the temperature and humidity in the test chamber are adjusted and varied according to the standard test conditions. To comprehensively characterize the effects of temperature and humidity cycling on the performance and microscopic failure mechanism of the resin-based composite material, three temperature and humidity cycling conditions were designed, covering the harsh natural environment described in Section 2.6.3 of Method 507.5 in the MIL-STD-810H standard, and considering a certain acceleration effect. The three temperature and humidity cycling environmental conditions are shown in Table 1, and the test cycle damp heat settings are as follows. Figure 2As shown. Specifically, the damp heat cycle-1 used alternating conditions of 80℃ and 95%RH (high temperature and high humidity) and 60℃ and 75%RH (low temperature and low humidity) to simulate the service state of materials under extreme high temperature and high humidity conditions, and introduced a temperature and humidity gradient to cause cyclical changes in the internal stress field of the material; the damp heat cycle-2 used alternating conditions of 60℃ and 95%RH (high temperature and high humidity) and 30℃ and 75%RH (low temperature and low humidity), which is closer to the diurnal temperature variation in real tropical and subtropical natural environments; the damp heat cycle-3 was set to an alternating cycle of 30℃ and 95%RH (low temperature and high humidity) and 60℃ and 20%RH (high temperature and low humidity) to simulate the rapid high temperature drying process of materials after experiencing a high humidity environment, and focused on investigating the moisture migration, desorption behavior and potential interface damage mechanism of composite materials under high temperature and low humidity conditions.

[0029] Table 1 Test conditions for damp heat test

[0030] To avoid inducing temperature and humidity shock effects, a 2-hour gradual change phase was designed during temperature and humidity switching, which more closely approximates the rate of change in the real environment. Following subsequent testing, carbon fiber / epoxy resin composite unidirectional laminate samples of this model were prepared according to standard procedures and divided into an unaged control group and test groups with different numbers of damp heat cycles. The tests were conducted in a pre-set damp heat test chamber.

[0031] Step Two: Macro- and Micro-performance testing After the damp heat cycling test, resin-based composite material samples with different cycle periods (30 days, 50 days, and 80 days) were taken out for macroscopic and microscopic performance testing. The specific testing steps are as follows: (1) Microscopic thermal analysis test ( Measurement) The glass transition temperature of resin-based composite materials under different damp heat cycling conditions was measured using differential scanning calorimetry (DSC). Specifically, 5-10 mg of pre- and post-aging powder or small sample pieces are accurately weighed and placed in a sealed DSC sample crucible. The temperature is then heated at a rate of 10 °C / min, ranging from 30 °C to 300 °C. Measurements are taken under different numbers of damp heat cycles. , obtain The experimental data, which vary with the number of wet and hot cycles, are shown in Table 2 in this example.

[0032] Table 2 Glass transition temperature of a certain type of carbon fiber / epoxy resin composite material ( ) Measured value

[0033] (2) Macroscopic mechanical property testing Standard mechanical tests, including tensile, compression, and shear tests, were performed on unidirectional laminate specimens after hydrothermal cycling to obtain various macroscopic mechanical property parameters. This example primarily focuses on tensile and compression tests, with the following test conditions: a. Tensile test: Performed according to ASTM D3039, testing the longitudinal modulus of elasticity of the specimen. transverse elastic modulus and tensile strength ; b. Compression test: Performed according to ASTM D3410 standard, testing the compressive strength of the sample. ; c. Shear test: Performed according to ASTM D7078 standard, testing the shear modulus of the sample. .

[0034] The measured values ​​of this embodiment are shown in Table 3.

[0035] Table 3 Measured values ​​of macroscopic properties of a certain type of carbon fiber / epoxy resin

[0036] Through the above macroscopic and microscopic performance tests, the material's properties under different damp heat cycling conditions were obtained. The data on changes in macroscopic mechanical performance parameters provide experimental basis for subsequent modeling of performance degradation functions.

[0037] Step 3: Establishment of a damp-heat cycle aging model In step three, based on the information obtained in step two... Data, building upon A kinetic model of wet-heat aging with the driving variable as the driving variable. For the given equation, the activation energy of the model needs to be determined. Humidity influencing factors With frequency factor Perform parameter identification. Substitute the specific humid and hot conditions and time from step one, and the different cycle numbers from step two. Actual measurement data will Set as initial value To account for the most extreme aging conditions, the parameters obtained through nonfitting are shown in Table 4 below.

[0038] Table 4. Parameters of the mechanical property degradation model for resin materials under damp heat cycling.

[0039] Therefore, the kinetic model for wet heat aging can be obtained as follows: (20) Step Four: Construction of a correlation model with mechanical properties The kinetic model of damp heat aging obtained in step three can be used to determine the glass transition temperature of resin-based composite materials under arbitrary damp heat cycling conditions. To make predictions, a dimensionless temperature is introduced. Its expression is as follows: (twenty one) In the formula, the test temperature Standard laboratory temperature, i.e. Glass transition temperature of resin in the dry state Reference temperature The results obtained from equations (20) and (21) are shown in Table 5.

[0040] Table 5. Calculation results of glass transition temperature of carbon fiber / epoxy resin composites under different cycle periods.

[0041] In this example, a certain type of carbon fiber / epoxy resin composite material has a fiber volume fraction of 60%. The component material performance parameters under standard laboratory conditions are shown in Table 6 below: Table 6 Material performance parameters of carbon fiber / epoxy resin composite components

[0042] According to equation (11), we can obtain (twenty two) This allows us to determine the elastic modulus of the resin. With shear modulus The changes in the epoxy resin modulus parameters with the number of cycles were predicted and calculated, as shown in Table 7.

[0043] Table 7. Variation of epoxy resin modulus parameters with number of cycles

[0044] To derive the mechanical properties of a single-layer plate from the mechanical properties of its constituent materials, the blending ratio method is used to establish a quantitative relationship between microscopic and macroscopic mechanical parameters. This example considers solving for the elastic modulus of a unidirectional laminate. , shear modulus Tensile strength With compressive strength ,have (twenty three) (twenty four) (25) (26) (27) The macroscopic properties of this type of carbon fiber / epoxy resin composite material can be predicted by equations (23)-(27), and the results are shown in Table 8.

[0045] Table 8. Performance parameters of carbon fiber / epoxy resin composite single-layer plates as a function of cycle number.

[0046] Step 5: Performance Prediction Validation and Application In step five, based on the macroscopic performance prediction model completed in step four, the model is validated and applied in practice. The goal of this step is to ensure the accuracy and applicability of the prediction model and to apply it to actual engineering projects for performance degradation assessment and lifetime prediction.

[0047] To verify the accuracy of the macroscopic performance prediction model established in step four, the prediction results are compared with the actual experimental values ​​obtained in step two to evaluate the accuracy of the prediction. The elastic modulus of the unidirectional laminate is calculated according to equations (17)-(19). , shear modulus Tensile strength With compressive strength The statistical indicators such as root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) between the predicted and experimental macroscopic performance values ​​are shown in Table 9 below.

[0048] Table 9 Statistical Indicators of Macroscopic Property Prediction Results for Carbon Fiber / Epoxy Resin Composites

[0049] As shown in the table above, the root mean square error (RMSE) of the overall error and the mean absolute error (MAE) reflecting the average deviation are on the same order of magnitude and are generally low. The mean absolute percentage error (MAPE) of all five performance parameters is far below the engineering allowable threshold of ±15%, indicating that the established performance degradation function model has good accuracy, reliability and a certain extrapolation ability.

[0050] Once the model has been validated, it can be applied to practical engineering projects to assess the performance degradation and predict the lifespan of resin-based composite materials, ensuring the long-term safety and reliability of engineering structures in complex environments.

Claims

1. A method for wet heat cycling testing and performance degradation prediction of resin-based composite materials, characterized in that: The steps include the following: Step 1: Design and Construction of the Damp Heat Cycling Test System Based on the typical service environment of resin-based composite materials and the requirements for model parameter solution accuracy and test cost, and referring to the clauses on damp heat testing in environmental testing standards, representative temperature and humidity cycling conditions are established. Step Two: Macro- and Micro-performance testing Under different humid heat cycling conditions set in Step 1, after the predetermined number of cycles, microscopic thermal analysis and macroscopic mechanical property tests were carried out on the resin-based composite material samples to obtain the glass transition temperature. And the mechanical property parameters of unidirectional laminates; Step 3: Establishment of a damp-heat cycle aging model In step three, the glass transition temperature is determined based on the different temperatures, humidity levels, and number of damp-heat cycles obtained in step two. Data, building upon A kinetic model of humid heat aging with the driving variable is used to characterize the aging degree and evolution law of resin-based composite materials in alternating humid heat environment. Step Four: Construction of a correlation model with mechanical properties Construct a mechanical property degradation model for component materials; introduce dimensionless temperature. The expression is as follows: (10) In the formula, The glass transition temperature. For the test temperature, This is the initial value of the glass transition temperature in the dry state. Reference temperature or room temperature; Step 5: Performance Prediction Validation and Application In step five, the macroscopic performance prediction model is validated and applied in practice to ensure its accuracy and applicability, and it is then applied to actual engineering projects for performance degradation assessment and lifespan prediction.

2. The method for wet heat cycling test and performance degradation prediction of resin-based composite materials according to claim 1, characterized in that: In step one, the damp heat cycling conditions include at least three representative types of temperature and humidity alternation, used to simulate extreme high temperature and high humidity conditions, typical tropical / subtropical day-night alternation conditions, and high humidity absorption followed by high temperature and low humidity drying conditions. Each condition introduces temperature and humidity gradients and cyclic stress field changes by alternating between high temperature and high humidity stages and low temperature or low humidity stages, comprehensively characterizing the impact of different types of damp heat cycles on material properties and failure mechanisms. A gradual change process is set in the temperature and humidity switching stage to reduce the unexpected damage of transient temperature and humidity shocks to the samples. According to the subsequent test experiments, resin-based composite unidirectional laminate samples are prepared according to standard processes and divided into an unaged control group and test groups with different numbers of damp heat cycles.

3. The method for wet heat cycling test and performance degradation prediction of resin-based composite materials according to claim 1, characterized in that: In step two, at the microscopic level, differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) are used to test the samples after different numbers of hygrothermal cycles to obtain the glass transition temperature at each cycle number. By studying the same material system under different combinations of temperature, humidity, and cycle counts... The measurement results were organized and constructed. The basic dataset varies with the degree of aging under wet and hot cycling.

4. The method for wet heat cycling test and performance degradation prediction of resin-based composite materials according to claim 1 or 3, characterized in that: In step two, at the macroscopic mechanical level, standard mechanical tests are conducted on the batch of unidirectional laminate samples corresponding to the microscopic thermal analysis, including tensile, compression, and shear tests, to obtain the elastic modulus and strength parameters of the material under different hygrothermal cycles; the macroscopic mechanical parameters include the elastic modulus in the fiber direction and transverse direction. , shear modulus Fiber direction tensile strength Compressive strength By statistically analyzing and summarizing test results under different wet and hot cycling conditions and cycles, a macro-micro one-to-one correspondence database is formed, enabling each wet and hot cycling state to simultaneously possess... With a set of macroscopic mechanical performance parameters.

5. The method for wet heat cycling test and performance degradation prediction of resin-based composite materials according to claim 1, characterized in that: In step three, the model takes the following form: (1) in, The reaction rate constant is determined by temperature. The frequency factor represents the rate of reaction without the influence of temperature. For activation energy, The gas constant is 8.

314. ), For temperature, Represented by natural constant An exponential function with base , i.e. ,in, ; Considering the effect of humidity, and referring to the Peck model, relative humidity is used as a power-law acceleration factor: (2) in, The reaction rate constant is the effect of relative humidity. Relative humidity, Humidity is an influencing factor. This indicates that the higher the humidity, the faster the reaction; the combined result is a Peck-Arrhenius type thermo-hygroscopic accelerated aging model to describe the coupling effect of temperature and humidity on the aging rate: (3) in, The reaction rate constant is determined by the combined effects of temperature and relative humidity. To account for the alternating changes in temperature and humidity over time in a cyclic humid and hot environment, a cumulative dose variable is introduced. Characterizing the cumulative effect of aging; aging dose per cycle. Defined as: (4) in, The total time of one cycle. The time for aging under damp heat. for The corresponding ambient relative humidity, for The corresponding ambient temperature.

6. The method for wet heat cycling test and performance degradation prediction of resin-based composite materials according to claim 5, characterized in that: Since each cycle in the experiment contains multiple isothermal and humidity platforms and linear transition sections, the integral is discretized into several intervals. (1) For the constant temperature and humidity platform section: (5) in, , , and The first Aging dosage, time, relative humidity, and temperature under humid and hot cycling conditions; (2) For the temperature and humidity transition section, the Gauss-Legendre five-point integral approximation is adopted: (6) In the formula, , representing the fifth point in the Gauss-Legend quadrature. A quadrature node, and These represent the position of the dimensionless integration point and the weight coefficient corresponding to that node. , The starting and ending temperatures of the transition section. , The relative humidity at the beginning and end of the transition section; Get the first Aging dosage under humid and hot cycling conditions The cumulative dose is: (7) in, This represents the number of iterations for the corresponding stage.

7. The method for wet heat cycling test and performance degradation prediction of resin-based composite materials according to claim 6, characterized in that: choose As a representative performance indicator characterizing the aging degree of the resin matrix composite material, a material... The following relationship exists between the cumulative dose and the cumulative dose: (8) in, ,yes The relative change This is the initial value of the glass transition temperature in the dry state. for The maximum change value represents the maximum possible change in the glass transition temperature of the resin-based composite material under extreme humid and hot conditions. The glass transition temperature was established. With temperature relative humidity and damp heat aging time The functional relationship; where it is necessary to obtain the results at different numbers of cycles through damp heat cycling experiments. Substitute the measured data into the equation and adjust the model parameters. , and After identification, the result is as follows: The kinetic model for wet heat aging with the driving variable is as follows: (9) in, For cumulative dose variable The corresponding time.

8. The method for wet heat cycling test and performance degradation prediction of resin-based composite materials according to claim 1, characterized in that: In step four, the elastic modulus of the resin-based composite matrix is ​​established. and shear modulus and The functional relationship between the two is used to describe the degradation of mechanical properties during the damp heat aging process, using dimensionless temperature. The power function can be used to approximate it as: (11) In the formula, , These represent the elastic modulus and shear modulus of the resin-based composite matrix in its initial room temperature dry state, respectively. and denoted as the material's hydrothermal degradation constant.

9. A method for wet heat cycling test and performance degradation prediction of resin-based composite materials according to claim 1 or 8, characterized in that: A quantitative relationship between microscopic and macroscopic mechanical parameters was established using the admixture method; the elastic modulus of unidirectional laminates was then analyzed. , have (12) (13) Shear modulus for unidirectional laminates have: (14) Longitudinal tensile strength of unidirectional laminates and longitudinal compressive strength have: (15) (16) In equations (12)-(16) , , , , These are the volume fraction, elastic modulus, shear modulus, tensile strength, and compressive strength of the composite fiber, respectively. , , These represent the volume fraction, elastic modulus, and shear modulus of the composite matrix, respectively.

10. A method for wet heat cycling test and performance degradation prediction of resin-based composite materials according to claim 1 or 4, characterized in that: In step five, the prediction accuracy of the model is quantified by calculating the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE); Let's assume... Group 1 experimental data, for the first Group data, , This represents the actual experimental measurement value. The specific formulas for RMSE, MAE, and MAPE, representing the model predictions, are as follows: (17) (18) (19)。

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