Composite material service life prediction method and device, electronic equipment and storage medium

Abstract

The invention provides a composite material service life prediction method. The method comprises the following steps: constructing a material moisture absorption model according to preset composite material moisture absorption data; and constructing a material life prediction model according to the material moisture absorption model and preset mechanical data of the composite material. And predicting the service life of the composite material according to the material service life prediction model. Therefore, prediction of the storage life of the composite material under the moisture absorption condition is realized.

Description

Technical Field

[0001] This application relates to the field of materials performance analysis technology, and in particular to a method for predicting the life of composite materials. Background Technology

[0002] As modern warfare shifts towards information-based, multi-layered, and all-encompassing three-dimensional warfare, the complex interplay of land, sea, air, space, cyber, and electromagnetic environments places increasingly higher demands on the integration of advanced technologies and the adaptability to complex environments in weaponry. Weapon systems are developing towards higher speeds, greater mobility, and longer ranges, and the increasing demand for lightweight new equipment has led to the widespread application of composite materials with low density, high specific strength, and high specific modulus.

[0003] Since missile equipment spends most of its lifespan in storage or non-operation, characterized by "long-term storage, single-use," storage period is a crucial combat technical indicator for missile equipment. In the storage environment, composite materials are subjected to stresses from temperature, humidity, and mechanical loads. High temperature and high humidity can cause chemical reactions in the composite material, such as hydrolysis, oxidation, degradation, and cross-linking, leading to damage to the matrix material itself and the creation of internal voids and defects. This directly results in interfacial delamination and a decline in overall performance of the composite material. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a method, apparatus, electronic device and storage medium for predicting the life of composite materials.

[0005] To achieve the above objectives, this application provides a method for predicting the lifespan of composite materials, comprising: constructing a material moisture absorption model based on preset composite material moisture absorption data; constructing a material lifespan prediction model based on the material moisture absorption model and preset composite material mechanical data; and predicting the lifespan of the composite material based on the material lifespan prediction model.

[0006] In some embodiments, a material moisture absorption model is constructed based on preset composite material moisture absorption data, specifically including: curve fitting the composite material moisture absorption data to obtain a diffusion coefficient curve; calculating the diffusion coefficient of the composite material based on the diffusion coefficient curve; calculating the saturated moisture absorption rate of the composite material based on the diffusion coefficient; and inputting the diffusion coefficient and saturated moisture absorption rate into a preset moisture absorption calculation model to obtain the material moisture absorption model. The moisture absorption calculation model is represented by the following formula: .in, Indicates the moisture absorption rate of the composite material. Indicates the moisture absorption time of the composite material. This indicates the end time of the initial linear phase of the moisture absorption curve of the composite material. This indicates the maximum moisture absorption capacity. This represents the slope of the initial linear phase of the moisture absorption curve of the composite material. Indicates the diffusion coefficient. This indicates the thickness of the composite material.

[0007] In some embodiments, the diffusion coefficient is expressed by the following formula: .in, This represents the moisture absorption rate of the composite material at any given time. Indicates the initial moisture absorption rate of the composite material. Indicates the thickness of the composite material. Used to calculate the slope of the initial linear phase of the moisture absorption curve of the composite material. .

[0008] In some embodiments, a material life prediction model is constructed based on a material moisture absorption model and preset composite material mechanical data. Specifically, this includes: curve fitting the composite material mechanical data to obtain mechanical property curves; calculating the composite material degradation rate based on the material moisture absorption model and mechanical property curves; and constructing a material life prediction model based on a preset material life model and material degradation rate. The material degradation rate is calculated using the following formula: .in, This represents the degradation rate under temperature stress T and relative humidity stress %RH. E is a constant, representing the material activation energy of the composite material. is the gas constant, equal to 8.314. , It is a power exponent.

[0009] In some embodiments, a material lifetime prediction model is constructed based on a preset material lifetime model and a material degradation rate, specifically including: constructing a composite material mechanical property model based on mechanical property curves and material degradation rates; calculating the degradation mechanical properties of the composite material at a specific time based on the composite material mechanical property model; and constructing a material lifetime prediction model based on the ratio of the degradation mechanical properties to the initial mechanical properties of the composite material. The composite material mechanical property model is expressed by the following formula: .in, Indicates composite materials in Mechanical properties at time, Indicates initial mechanical properties. This represents the model correction factor.

[0010] This application also provides a composite material life prediction device, comprising: a first model building module for building a material moisture absorption model based on preset composite material moisture absorption data; a second model building module for building a material life prediction model based on the material moisture absorption model and preset composite material mechanical data; and a prediction module for predicting the life of the composite material based on the material life prediction model.

[0011] In some embodiments, the first model construction module includes: a first fitting module, used to perform curve fitting on the moisture absorption data of the composite material to obtain a diffusion coefficient curve; calculate the diffusion coefficient of the composite material based on the diffusion coefficient curve; calculate the saturated moisture absorption rate of the composite material based on the diffusion coefficient; and input the diffusion coefficient and the saturated moisture absorption rate into a preset moisture absorption calculation model to obtain a material moisture absorption model. The moisture absorption calculation model is represented by the following formula: .in, Indicates the moisture absorption rate of the composite material. Indicates the moisture absorption time of the composite material. This indicates the end time of the initial linear phase of the moisture absorption curve of the composite material. This indicates the maximum moisture absorption capacity. This represents the slope of the initial linear phase of the moisture absorption curve of the composite material. Indicates the diffusion coefficient. This indicates the thickness of the composite material.

[0012] In some embodiments, the second model construction module includes: a second fitting module, used to perform curve fitting on the mechanical data of the composite material to obtain a mechanical property curve; calculating the degradation rate of the composite material based on the material moisture absorption model and the mechanical property curve; and constructing a material life prediction model based on a preset material life model and the material degradation rate. The material degradation rate is calculated by the following formula: .in, This represents the degradation rate under temperature stress T and relative humidity stress %RH. E is a constant, representing the material activation energy of the composite material. is the gas constant, equal to 8.314. , It is a power exponent.

[0013] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as described in any of the preceding descriptions.

[0014] A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform any of the methods described above.

[0015] As can be seen from the above, the composite material life prediction method provided in this application establishes a composite material moisture absorption model and constructs a material life prediction model based on the composite material moisture absorption model and composite material mechanical data, thereby enabling the prediction of the life of composite materials stored under temperature and humidity stress, and allowing the selection of appropriate storage temperature and humidity based on the prediction results, thereby extending the service life of composite materials. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A schematic flowchart illustrating a composite material life prediction method provided in an embodiment of this application; Figure 2 The moisture absorption rate curves of four composite materials under different humid and hot environments are shown in an optional embodiment of this application. Figure 3 The Fick diffusion curve (left) and the modified curve (right) of the T800 / S0506 composite material in an optional embodiment of this application are shown. Figure 4 This is a fitting curve of the diffusion coefficient of a carbon-based composite material at different temperatures in an optional embodiment of this application; Figure 5 The fitted curves of saturated moisture absorption rate of S0506 (left) and DS1211 (right) composite materials at different temperatures in an optional embodiment of this application are shown. Figure 6 This is a performance curve fitting diagram of a carbon-based composite material in an optional embodiment of this application; Figure 7 This is a schematic diagram of the structure of a composite material life prediction device provided in an embodiment of this application; Figure 8 This is a schematic diagram of a more specific electronic device hardware structure provided in an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0019] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0020] As modern warfare shifts towards information-based, multi-layered, and all-encompassing three-dimensional warfare, the complex interplay of land, sea, air, space, cyber, and electromagnetic environments places increasingly higher demands on the integration of advanced technologies and the adaptability to complex environments in weaponry. Weapon systems are developing towards high speed, high mobility, and long range, and the increasing demand for lightweight new equipment has led to the widespread application of composite materials with low density, high specific strength, and high specific modulus. Carbon fiber reinforced composites are made by using carbon fiber as a reinforcing skeleton and thermosetting or thermoplastic organic polymers as fillers, processed through special processes such as autoclaving, lamination, compression molding, filament winding, pultrusion, continuous sheet molding, and resin transfer molding. Carbon fiber reinforced composites possess characteristics such as low density, high specific strength and stiffness, high specific modulus, and fatigue resistance, playing an increasingly important role in the performance generation and development of weaponry.

[0021] Because missile equipment spends most of its lifespan in storage or non-operation, characterized by "long-term storage, single-use," storage period is a crucial combat technical indicator for missile equipment. In the storage environment, composite materials are subjected to stresses from temperature, humidity, and mechanical loads. Due to the significant differences in thermophysical and mechanical properties between the reinforcing fibers and the polymer resin matrix, the effects of temperature, humidity, and mechanical loads can easily cause deformation mismatch between the two, leading to residual stress and localized stress concentration at the material interfaces. Furthermore, the resin matrix, under prolonged high temperature and humidity, easily absorbs moisture, resulting in a swelling effect that reduces the adhesion of the matrix to the fibers or causes direct interface delamination and separation. Simultaneously, high temperature and humidity can cause chemical reactions in the composite material, such as hydrolysis, oxidation, degradation, and cross-linking, leading to damage to the matrix material itself and the creation of internal voids and defects, directly causing interfacial delamination and overall performance degradation. These performance degradations caused by the physical and chemical aging of composite materials will ultimately lead to the failure of the load-bearing functions of critical components in the missile equipment, posing significant quality and safety risks to combat missions.

[0022] Carbon fiber reinforced composites are a new type of material that emerged in the 1960s and is currently experiencing rapid development. They are widely used in aerospace, construction, machinery, and bioengineering. They possess a variety of superior properties, including high specific strength and specific stiffness, customizable performance, and ease of processing and molding. As a structural material, they are 20%-50% lighter than traditional materials. They can also be used as functional materials. In the past decade, advanced composite materials have grown at an annual rate of 30%, demonstrating that a composite materials era, comparable to the space age and the information age, is emerging in the development of science and technology.

[0023] With the application and promotion of carbon-based composite materials in the aerospace field, research on the damage of carbon-based composite materials under environmental and mechanical loads has also been carried out, especially in the case of humid and hot environments. Humid and hot environments will have physical or chemical effects on the resin matrix, fibers and fiber / resin interfaces in composite materials, thereby affecting their mechanical properties. Since different types of composite materials use resins and fibers with different properties, different humid and hot aging mechanisms may occur. In general, the following changes will mainly occur: (1) Changes in the matrix: Water molecules enter the resin matrix, causing it to swell or plasticize, which is a reversible physical change; at the same time, water molecules in the humid and hot environment may cause the resin matrix to undergo chemical changes such as hydrolysis, which is irreversible. (2) Changes in fibers: The performance of carbon fibers is less affected by the humid and hot environment, and its effect on the humid and hot aging of resin-based composite materials can be basically ignored. (3) Changes in the interface: Due to the different moisture absorption rates of resin and fiber, internal stress will be generated at the interface, which will then promote the debonding and cracking of the interface. During the humid and hot aging process, heating will accelerate the diffusion rate of water molecules and promote the moisture absorption effect of composite materials. Composite materials are subject to the combined effects of humidity and temperature in humid and hot environments. Therefore, simulating different humid and hot environments at multiple scales to study their complex aging mechanisms is of great significance for the development and modification of materials.

[0024] The gradual failure of carbon-based composites under external loads is a process of elastoplastic deformation. During the preparation process, the difference between curing temperature and room temperature can lead to numerous defects. These defects are prone to initiation of damage under external loads, resulting in stiffness degradation of the carbon-based composite. Simultaneously, due to stress concentration, the matrix material undergoes irreversible plastic deformation. Therefore, the mechanical properties of carbon-based composites depend on both damage and plasticity. While research on the elasticity of composites is quite comprehensive, there are still many shortcomings in predicting the plastic deformation of composites. Furthermore, FEM and FFT methods are high-resolution, high-precision calculation methods, especially for the nonlinear solution of elastoplastic damage, which inevitably leads to a large computational load, affecting computational efficiency and hindering reliability assessment. In addition, existing research shows that the plastic deformation of the resin matrix has a significant nonlinear effect on carbon-based composites, and is simultaneously controlled by damage and plasticity; one factor cannot be considered alone. Therefore, how to develop a reduced analytical model for rapidly and accurately solving the elastoplastic damage behavior of carbon-based composites and apply it to the mechanical property analysis of carbon-based composites remains an unsolved scientific problem.

[0025] like Figure 1 As shown, this application provides a method for predicting the lifespan of composite materials, including: Step S1: Construct a material moisture absorption model based on preset composite material moisture absorption data.

[0026] Step S2: Construct a material life prediction model based on the material moisture absorption model and the preset composite material mechanical data.

[0027] Step S3: Predict the lifespan of the composite material based on the material lifespan prediction model.

[0028] In this embodiment, the moisture absorption data of the composite material is obtained by testing the moisture absorption rate of the composite material for which lifespan prediction is required. Specifically, the composite material to be tested can be stored in an environment with corresponding temperature and humidity, and the moisture absorption rate of the composite material can be tested periodically to obtain the corresponding moisture absorption data. Similarly, the mechanical data of the composite material can also be obtained by periodically testing the mechanical properties of the composite material stored under corresponding temperature and humidity conditions.

[0029] As an exemplary embodiment, this application provides a method for preparing longitudinal tensile specimens using a unidirectional prepreg layup of T800 carbon fiber and SO506 bismaleimide resin via an autoclave molding process, wherein the layup angle and number of layers of the prepreg are [0°]. 10 The test method for storage testing of carbon fiber composite materials. Among them, the curing regime of S0506 bismaleimide resin prepreg is 125℃ for 30 min, 185℃ for 2 h, 230℃ for 2 h, and 250℃ for 4 h, with a heating rate not exceeding 2℃ / min.

[0030] Specifically, the experimental procedure is as follows: Step S100: Set the number of stress levels for the accelerated storage test. Specifically, set three temperature points (70℃, 80℃, 90℃) and two relative humidity points (75%RH, 85%RH), and conduct four stress environment tests at 70℃ / 75%RH, 80℃ / 75%RH, 90℃ / 75%RH, and 80℃ / 85%RH.

[0031] Step S200: Select the damp heat aging test cycle. In this embodiment, 7 test cycles are selected, namely t1, t2...t7.

[0032] Step S300: In each stress environment test, prepare 5 composite material specimens for moisture absorption and mechanical property testing, and prepare an additional specimen for internal defect detection, infrared spectroscopy, Raman spectroscopy analysis, microstructure analysis, and glass transition temperature testing.

[0033] Environmental testing Step S400: Place the carbon-based composite material samples into the damp heat aging test chamber. A total of 42 samples of each type of carbon fiber composite material are placed (6 samples per group, 7 cycles). The temperature and humidity are increased to the required temperature and humidity at a rate of 1~3℃ / min, and the aging time is recorded.

[0034] Step S500: When the aging test time reaches the predetermined cycle, take the samples out of the damp heat aging test chamber. For each material, take out 1 set (6 pieces) each time under each test condition and place them in a standard laboratory environment for one day.

[0035] Step S600: Of the 6 samples taken out, 5 are used for moisture absorption rate and mechanical property tests, and the average value of these 5 samples is taken as the test value for each test cycle; 1 sample is used for other performance tests in this cycle, including infrared spectroscopy test, Raman spectroscopy test, internal defect test, microstructure test and glass transition temperature test.

[0036] In step S600, since moisture absorption rate testing is a non-destructive test, it can share a batch of samples with mechanical properties testing. To avoid measurement errors caused by sample differences, the samples from the last cycle are selected for moisture absorption rate testing, and measurements are repeated after each cycle of damp heat aging test. In the last cycle, these five samples undergo moisture absorption rate testing first, followed by mechanical property testing. After the mechanical property testing, fractured samples can be taken for fracture morphology observation.

[0037] Meanwhile, internal defect detection, infrared spectroscopy, and Raman spectroscopy are non-destructive testing methods. Therefore, internal defect detection, infrared spectroscopy, and Raman spectroscopy tests are carried out first. Subsequently, microstructure analysis and glass transition temperature samples are taken from the sample.

[0038] Step S700: The next sampling and testing cycle will repeat steps S500 and S600 until the test termination condition is met.

[0039] In some embodiments, step S1 specifically includes: Step S11: Perform curve fitting on the moisture absorption data of the composite material to obtain the diffusion coefficient curve.

[0040] Step S12: Calculate the diffusion coefficient of the composite material based on the diffusion coefficient curve.

[0041] Step S13: Calculate the saturated moisture absorption rate of the composite material based on the diffusion coefficient.

[0042] Step S14: Input the diffusion coefficient and saturated moisture absorption rate into the preset moisture absorption calculation model to obtain the material moisture absorption model.

[0043] The moisture absorption calculation model is represented by the following formula: .

[0044] in, Indicates the moisture absorption rate of the composite material. Indicates the moisture absorption time of the composite material. This indicates the end time of the initial linear phase of the moisture absorption curve of the composite material. This indicates the maximum moisture absorption capacity. This represents the slope of the initial linear phase of the moisture absorption curve of the composite material. Indicates the diffusion coefficient. This indicates the thickness of the composite material.

[0045] In some embodiments, the diffusion coefficient is expressed by the following formula: .

[0046] in, This represents the moisture absorption rate of the composite material at any given time. Indicates the initial moisture absorption rate of the composite material. Indicates the thickness of the composite material. Used to calculate the slope of the initial linear phase of the moisture absorption curve of the composite material. .

[0047] In this embodiment, the change in moisture absorption rate during the accelerated aging test of the composite material under damp heat (e.g.) Figure 2 Analysis of the composite material (as shown) reveals that its moisture absorption process conforms to Fick's Law, expressed by the following formula: ; in, This indicates the concentration of water molecules in the material; Indicates diffusion time; This represents the diffusion mass flux density of water molecules; This represents the diffusion coefficient of water molecules in a material.

[0048] Assuming the diffusion coefficient does not change with time, i.e. At this point, the above formula can be simplified to: ; Therefore, the fundamental equation for the change of the moisture concentration field inside the material due to hygroscopic absorption over time can be expressed as: ; In this equation, the thickness of the composite material must be known. Before testing, the composite material must be thoroughly dried and placed in a constant temperature and humidity environment for 24 hours. During the diffusion process, the water molecules on the sample surface should remain in a uniform state. When the composite material finally reaches equilibrium with the surrounding environment, the weight increase at any given time should be considered. It is the balance of moisture content The function.

[0049] At this point, the expression for the moisture absorption of the composite material at any given time is as follows: ; in, This represents the moisture absorption rate of a material at any given time. Indicates the saturated moisture absorption rate of the material; Indicates the diffusion coefficient; Indicates diffusion time; This indicates the thickness of the sample.

[0050] By separating variables in the above equation, we can obtain: ; in, This indicates the initial moisture absorption rate of the material.

[0051] At this point, since the initial moisture absorption rate of the composite material sample is 0, the diffusion coefficient in this embodiment can be obtained. The expression: .

[0052] In some alternative embodiments, the moisture saturation rate and diffusion coefficient of the composite material samples at different temperatures can be calculated based on the data obtained from the damp heat aging test. Taking the data of T800 / S0506 composite material as an example, Table 1 shows the moisture saturation rate and diffusion coefficient of T800 / S0506 composite material under different environmental conditions.

[0053] Table 1. Moisture saturation rate and diffusion coefficient of T800 / S0506 composite material

[0054] For the hygroscopic sample of the composite material, it is assumed that the concentration on both the upper and lower surfaces is the same and is... The concentration inside the composite material is The thickness of the composite material sample is The boundary conditions are: ; In the above formula, for from arrive Integrals, due to We can obtain: ; In the above formula, ,when Then, the moisture absorption and diffusion model of composite materials derived from Fick's law can be obtained as follows: .

[0055] By using the saturated moisture absorption rate in Table 1 and diffusion coefficient Substituting these values ​​into the above equation, we can obtain the Fick diffusion curve of the T800 / S0506 composite material, as shown below. Figure 3 As shown.

[0056] The Fick diffusion model curve shows a high degree of overlap with the experimental data, with a slight error occurring near the saturation stage of moisture absorption. Since the moisture absorption process of the composite material involves two stages, in the first stage, the moisture absorption rate is linearly related to time. However, the formula derived from Fick's second law can only predict the moisture absorption pattern in the second stage relatively well. Therefore, the curve for the initial stage of moisture absorption was modified to have a slope of [missing information]. The time corresponding to the intersection of the straight line and the Fick diffusion curve is . ,like Figure 3 As shown in the right figure, the expression for the moisture absorption rate model in the above embodiments can be obtained as follows: ; To obtain the diffusion coefficient of the composite material at different temperatures and moisture saturation Without considering the effect of thickness, experimental data at 70℃, 80℃, and 90℃ were fitted. After trying multiple function types, the exponential function with the highest goodness of fit was selected. The diffusion coefficients at different temperatures are shown below. Figure 4 As shown, the diffusion coefficients of the four different composite material samples are basically the same under the same humid heat conditions, and the fitted curves are consistent. The value is 0.90, indicating a good fit. Therefore, after fitting the experimental data, the diffusion coefficient is... The expression is: ; The main factor affecting the moisture absorption properties of composite materials is the material matrix. Therefore, curve fitting can be used to obtain the moisture absorption rate of two composite materials with different resin matrices as a function of temperature under a relative humidity of 75%. The exponential function with the highest goodness of fit is selected, and the final fitted curve is shown below. Figure 5 As shown in the figure, the fitted curve The value was 0.91, indicating a good fit.

[0057] After fitting the experimental data, the saturated moisture absorption rate of the S0506 resin-based composite material was determined. The expression is: ; So, the saturated moisture absorption rate of DS1211 resin-based composite materials The expression is: .

[0058] The diffusion coefficient D and the saturated moisture absorption rate of the S0506 resin-based composite material are considered. DS1211 resin-based composite material saturated moisture absorption rate Substituting the expression into the moisture absorption rate model expression, we get: ; .

[0059] In some embodiments, step S2 specifically includes: Step S21: Perform curve fitting on the mechanical data of the composite material to obtain the mechanical property curve.

[0060] Step S22: Calculate the degradation rate of the composite material based on the material moisture absorption model and mechanical property curve.

[0061] Step S23: Construct a material life prediction model based on the preset material life model and material degradation rate.

[0062] The material degradation rate is calculated using the following formula: .

[0063] in, This represents the degradation rate under temperature stress T and relative humidity stress %RH. E is a constant, representing the material activation energy of the composite material. is the gas constant, equal to 8.314. , It is a power exponent.

[0064] In some embodiments, step S23 specifically includes: Step S231: Construct a mechanical property model for the composite material based on the mechanical property curves and the material degradation rate.

[0065] Step S232: Calculate the degradation mechanical properties of the composite material at a specific time based on the composite material mechanical property model.

[0066] Step S233: Construct a material life prediction model based on the ratio of degraded mechanical properties to the initial mechanical properties of the composite material.

[0067] The mechanical property model of composite materials is represented by the following formula: .

[0068] in, Indicates composite materials in Mechanical properties at time, Indicates initial mechanical properties. This represents the model correction factor.

[0069] In this embodiment, the composite material mechanical property model is constructed based on the principle that the change of composite material properties with acceleration time follows an exponential law. Using this model, the tensile strength of the T800 / S0506 composite material under test conditions of 90℃ / 75%RH, 80℃ / 75%RH, 70℃ / 75%RH, and 80℃ / 85%RH is fitted with the curves of change with test time. This yields the fitting equations and performance degradation rates for the four temperature and humidity conditions, as shown below. Figure 6 As shown in Table 2: Table 2. Fitting equations for tensile strength and test time of composite materials

[0070] In a humid and hot environment, the Peck accelerated model with temperature and humidity dual stresses is used to model the life prediction of carbon-based composite materials, as shown in the following equation:

[0071] In the formula, This represents the degradation rate under temperature stress of T (in K) and relative humidity stress of %RH. Represents a constant; E represents the material activation energy, which is material-dependent; This represents the gas constant, which is equal to 8.314. ; It represents the power exponent.

[0072] Linearizing the model to facilitate fitting and extrapolation during use yields the following equation: ; Substituting the degradation rates under the four humid and hot environmental conditions into the above formula, the humid and hot aging model of carbon-based composite materials can be obtained as follows: ; Taking 25℃ / 60%RH as the humid and hot environmental condition, substituting into the above formula and combining it with the degradation rate calculation formula, we can obtain the fitting equation for tensile strength versus aging time under the 25℃ / 60%RH condition: ; Using the tensile strength dropping to 80% of the initial performance as the failure criterion, the storage life of T800 / S0506 composite material under 25℃ / 60%RH conditions can be calculated to be 44.9 years according to the above formula.

[0073] As can be seen from the above embodiments of this application, this application establishes a moisture absorption model for composite materials and constructs a material life prediction model based on the moisture absorption model and mechanical data of composite materials. This enables the prediction of the life of composite materials stored under temperature and humidity stress, and allows the selection of appropriate storage temperature and humidity based on the prediction results, thereby extending the service life of composite materials.

[0074] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0075] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0076] Based on the same inventive concept, corresponding to any of the above embodiments, this application also provides a composite material life prediction device.

[0077] refer to Figure 7 A composite material life prediction device, comprising: The first model building module 10 is used to build a material moisture absorption model based on preset composite material moisture absorption data.

[0078] The second model construction module 20 is used to construct a material life prediction model based on the material moisture absorption model and preset composite material mechanical data.

[0079] The prediction module 30 is used to predict the life of composite materials based on the material life prediction model.

[0080] In some embodiments, the first model building module includes: The first fitting module is used to perform curve fitting on the moisture absorption data of composite materials to obtain the diffusion coefficient curve.

[0081] The diffusion coefficient of the composite material is calculated based on the diffusion coefficient curve.

[0082] The saturated moisture absorption rate of the composite material is calculated based on the diffusion coefficient.

[0083] The diffusion coefficient and saturated moisture absorption rate are input into the preset moisture absorption calculation model to obtain the material moisture absorption model.

[0084] The moisture absorption calculation model is represented by the following formula: .

[0085] in, Indicates the moisture absorption rate of the composite material. Indicates the moisture absorption time of the composite material. This indicates the end time of the initial linear phase of the moisture absorption curve of the composite material. This indicates the maximum moisture absorption capacity. This represents the slope of the initial linear phase of the moisture absorption curve of the composite material. Indicates the diffusion coefficient. This indicates the thickness of the composite material.

[0086] In some embodiments, the second model building module includes: The second fitting module is used to perform curve fitting on the mechanical data of composite materials to obtain mechanical property curves.

[0087] The degradation rate of composite materials was calculated based on the material's moisture absorption model and mechanical property curves.

[0088] A material life prediction model is constructed based on a pre-defined material life model and material degradation rate.

[0089] The material degradation rate is calculated using the following formula: .

[0090] in, This represents the degradation rate under temperature stress T and relative humidity stress %RH. E is a constant, representing the material activation energy of the composite material. is the gas constant, equal to 8.314. , It is a power exponent.

[0091] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing this application, the functions of each module can be implemented in one or more software and / or hardware.

[0092] The apparatus described above is used to implement the corresponding composite material life prediction method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0093] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the composite material life prediction method described in any of the above embodiments.

[0094] Figure 8 This embodiment illustrates a more specific hardware structure of an electronic device. The device may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0095] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0096] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0097] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0098] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0099] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0100] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0101] The electronic devices described in the above embodiments are used to implement the corresponding composite material life prediction methods in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0102] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the composite material life prediction method as described in any of the above embodiments.

[0103] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0104] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the composite material life prediction method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0105] It should be noted that the embodiments of this application can also be further described in the following ways: A method for predicting the lifespan of composite materials, comprising: A material moisture absorption model is constructed based on the preset moisture absorption data of the composite material; A material life prediction model is constructed based on the material moisture absorption model and the preset composite material mechanical data; The lifespan of the composite material is predicted based on the material lifespan prediction model.

[0106] Optionally, the step of constructing a material moisture absorption model based on preset composite material moisture absorption data specifically includes: The diffusion coefficient curve was obtained by curve fitting of the moisture absorption data of the composite material; The diffusion coefficient of the composite material is calculated based on the diffusion coefficient curve. The saturated moisture absorption rate of the composite material is calculated based on the diffusion coefficient. The diffusion coefficient and the saturated moisture absorption rate are input into a preset moisture absorption calculation model to obtain the material moisture absorption model; The moisture absorption calculation model is represented by the following formula: ; in, Indicates the moisture absorption rate of the composite material. Indicates the moisture absorption time of the composite material. This indicates the end time of the initial linear phase of the moisture absorption curve of the composite material. This indicates the maximum moisture absorption capacity. This represents the slope of the initial linear phase of the moisture absorption curve of the composite material. This represents the diffusion coefficient. This indicates the thickness of the composite material.

[0107] Optionally, the diffusion coefficient is expressed by the following formula: ; in, This represents the moisture absorption rate of the composite material at any given time. Indicates the initial moisture absorption rate of the composite material. Indicates the thickness of the composite material. Used to calculate the slope of the initial linear phase of the moisture absorption curve of the composite material. .

[0108] Optionally, the step of constructing a material life prediction model based on the material moisture absorption model and preset composite material mechanical data specifically includes: Curve fitting was performed on the mechanical data of the composite material to obtain the mechanical property curves; The degradation rate of the composite material was calculated based on the material's moisture absorption model and mechanical property curves. The material life prediction model is constructed based on the preset material life model and the material degradation rate; The material degradation rate is calculated using the following formula: ; in, This represents the degradation rate under temperature stress T and relative humidity stress %RH. E is a constant, representing the material activation energy of the composite material. is the gas constant, equal to 8.314. , It is a power exponent.

[0109] Optionally, the step of constructing the material lifetime prediction model based on the preset material lifetime model and the material degradation rate specifically includes: Based on the mechanical property curves and the material degradation rate, a mechanical property model of the composite material is constructed. The degradation mechanical properties of the composite material at a specific time are calculated based on the composite material mechanical property model. The material life prediction model is constructed based on the ratio of the degraded mechanical properties to the initial mechanical properties of the composite material. The mechanical property model of the composite material is represented by the following formula: ; in, Indicates composite materials in Mechanical properties at time, This indicates the initial mechanical properties. This represents the model correction factor.

[0110] A composite material life prediction device, comprising: The first model building module is used to build a material moisture absorption model based on preset composite material moisture absorption data; The second model building module is used to build a material life prediction model based on the material moisture absorption model and preset composite material mechanical data. The prediction module is used to predict the lifespan of the composite material based on the material lifespan prediction model.

[0111] Optionally, the first model building module includes: The first fitting module is used to perform curve fitting on the moisture absorption data of the composite material to obtain the diffusion coefficient curve. The diffusion coefficient of the composite material is calculated based on the diffusion coefficient curve. The saturated moisture absorption rate of the composite material is calculated based on the diffusion coefficient. The diffusion coefficient and the saturated moisture absorption rate are input into a preset moisture absorption calculation model to obtain the material moisture absorption model; The moisture absorption calculation model is represented by the following formula: ; in, Indicates the moisture absorption rate of the composite material. Indicates the moisture absorption time of the composite material. This indicates the end time of the initial linear phase of the moisture absorption curve of the composite material. This indicates the maximum moisture absorption capacity. This represents the slope of the initial linear phase of the moisture absorption curve of the composite material. This represents the diffusion coefficient. This indicates the thickness of the composite material.

[0112] Optionally, the second model building module includes: The second fitting module is used to perform curve fitting on the mechanical data of the composite material to obtain the mechanical property curve. The degradation rate of the composite material was calculated based on the material's moisture absorption model and mechanical property curves. The material life prediction model is constructed based on the preset material life model and the material degradation rate; The material degradation rate is calculated using the following formula: ; in, This represents the degradation rate under temperature stress T and relative humidity stress %RH. E is a constant, representing the material activation energy of the composite material. is the gas constant, equal to 8.314. , It is a power exponent.

[0113] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as described in any of the preceding descriptions.

[0114] A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform any of the methods described above.

[0115] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0116] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0117] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0118] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

Claims

1. A composite material life prediction method, comprising: constructing a material moisture absorption model according to preset composite material moisture absorption data; constructing a material life prediction model according to the material moisture absorption model and preset composite material mechanical data; predicting the life of the composite material according to the material life prediction model.

2. The composite life prediction method of claim 1, wherein, The construction of the material moisture absorption model according to the preset composite material moisture absorption data specifically comprises: curve fitting the composite material moisture absorption data to obtain a diffusion coefficient curve; calculating the diffusion coefficient of the composite material according to the diffusion coefficient curve; calculating the saturated moisture absorption rate of the composite material according to the diffusion coefficient; inputting the diffusion coefficient and the saturated moisture absorption rate into a preset moisture absorption calculation model to obtain the material moisture absorption model; wherein the moisture absorption calculation model is represented by the following formula: ； wherein, represents the moisture uptake of the composite material, represents the moisture uptake time of the composite material, represents the end time of the initial linear phase of the moisture uptake curve of the composite material, represents the maximum moisture uptake, represents the slope of the initial linear phase of the moisture uptake curve of the composite material, represents the diffusion coefficient, represents the thickness of the composite material. 3.The composite material life prediction method of claim 2, wherein, the diffusion coefficient is represented by the following formula: ； wherein, represents the moisture uptake of the composite material at any time, represents the initial moisture uptake of the composite material, represents the thickness of the composite material, for calculating the slope of the initial linear phase of the moisture uptake curve of the composite material .

4. The composite life prediction method of claim 1, wherein, The construction of the material life prediction model according to the material moisture absorption model and the preset composite material mechanical data specifically comprises: curve fitting the composite material mechanical data to obtain a mechanical property curve; calculating the material degradation rate according to the material moisture absorption model and the mechanical property curve; constructing the material life prediction model according to the preset material life model and the material degradation rate; the material degradation rate is calculated by the following formula: ； wherein, represents the degradation rate under temperature stress T and relative humidity stress %RH, is a constant, E represents the material activation energy of the composite material, is the gas constant, equal to 8.314 , is the power index.

5. The composite life prediction method of claim 4, wherein, The construction of the material life prediction model according to the preset material life model and the material degradation rate specifically comprises: constructing a composite material mechanical property model according to the mechanical property curve and the material degradation rate; calculating the degraded mechanical property of the composite material at a specific time according to the composite material mechanical property model; constructing the material life prediction model according to the ratio of the degraded mechanical property to the initial mechanical property of the composite material; the composite material mechanical property model is represented by the following formula: ； wherein, represents the mechanical properties of the composite material at the time instant, represents the initial mechanical properties, represents a model correction factor. 6.A composite material life prediction device, comprising: a first model construction module configured to construct a material moisture absorption model according to preset composite material moisture absorption data; a second model construction module configured to construct a material life prediction model according to the material moisture absorption model and preset composite material mechanical data; a prediction module configured to predict the life of the composite material according to the material life prediction model.

7. The composite life prediction apparatus according to claim 6, wherein The first model construction module comprises: a first fitting module configured to curve fit the composite material moisture absorption data to obtain a diffusion coefficient curve; calculating the diffusion coefficient of the composite material according to the diffusion coefficient curve; calculating the saturated moisture absorption rate of the composite material according to the diffusion coefficient; inputting the diffusion coefficient and the saturated moisture absorption rate into a preset moisture absorption calculation model to obtain the material moisture absorption model; wherein the moisture absorption calculation model is represented by the following formula: ； wherein, represents the moisture uptake of the composite material, represents the moisture uptake time of the composite material, represents the end time of the initial linear phase of the moisture uptake curve of the composite material, represents the maximum moisture uptake, represents the slope of the initial linear phase of the moisture uptake curve of the composite material, represents the diffusion coefficient, represents the thickness of the composite material.

8. The composite life prediction apparatus according to claim 6, wherein The second model construction module comprises: a second fitting module configured to curve fit the composite material mechanical data to obtain a mechanical property curve; calculating the material degradation rate according to the material moisture absorption model and the mechanical property curve; constructing the material life prediction model according to the preset material life model and the material degradation rate; The material degradation rate is calculated by the following equation: ； wherein, represents the degradation rate under temperature stress T and relative humidity stress %RH, is a constant, E represents the material activation energy of the composite material, is the gas constant, equal to 8.314 , is the power index.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and loadable on the processor, the processor implementing the method of any one of claims 1 to 5 when executing the program.

10. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1 to 5.

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