Finite element analysis-based carbon fiber reinforced composite material design method

Abstract

The invention relates to the technical field of computer-aided engineering design, and discloses a carbon fiber reinforced composite material design method based on finite element analysis, which comprises the following steps: constructing a finite element model of a carbon fiber reinforced composite material, randomly generating a mixing proportion scheme of carbon fibers and a matrix, generating a constraint condition of a mixing proportion scheme based on design parameters of the finite element model, generating axial tensile strength of the carbon fiber reinforced composite material based on the mixing proportion scheme, generating a damage variable of the carbon fiber reinforced composite material based on the finite element model and the mixing proportion scheme, and determining the damage variable of the carbon fiber reinforced composite material based on the axial tensile strength, the damage variable and the constraint condition. According to the method, the damage ultimate tension of the carbon fiber reinforced composite material is generated, the dynamic response prediction precision is improved by introducing the temperature change rate parameter, the influence of the damage ultimate tension and the temperature change rate on the real-time strength of the carbon fiber reinforced composite material is considered, and the strength performance of the material under the actual working condition can be reflected more accurately.

Description

Technical Field

[0001] The invention relates to the technical field of computer-aided engineering design, and in particular to a carbon fiber reinforced composite material design method based on finite element analysis. Background Art

[0002] Carbon fiber reinforced composites have been widely used in aerospace, automobile, sports equipment and other fields due to their excellent properties such as high specific strength, high specific modulus, and corrosion resistance. However, the performance of carbon fiber reinforced composites is affected by many factors such as fiber orientation, ply sequence, and fiber volume fraction, and its design process is relatively complicated.

[0003] The design of traditional carbon fiber reinforced composite materials is mainly based on actual testing of material properties (such as tension, compression, wet heat aging, etc.), relying on manual experience, requiring a lot of trial and error, and lacking efficient data analysis models and algorithms. This not only leads to high costs and long R&D cycles, but also makes it difficult to fully tap the performance potential of materials. With the development of computer technology, finite element analysis methods have gradually been applied to the field of composite material design. However, finite element models have significant defects in simulating the damage evolution law and temperature effects of materials. Finite element models cannot accurately simulate the damage evolution law under complex environments (such as high temperatures), and the coupling effect of fiber fracture and matrix cracking is not fully considered, resulting in insufficient performance prediction accuracy and incomplete design results. Summary of the invention

[0004] The present invention provides a carbon fiber reinforced composite material design method based on finite element analysis, the main purpose of which is to solve the problems that the finite element model cannot accurately simulate the damage evolution law under complex environment (such as high temperature), the coupling effect of fiber fracture and matrix cracking is not fully considered, resulting in insufficient performance prediction accuracy and incomplete design results.

[0005] To achieve the above object, the present invention provides a carbon fiber reinforced composite material design method based on finite element analysis, comprising:

[0006] S1: Construct finite element model of carbon fiber reinforced composites;

[0007] S2: Randomly generate a mixing ratio of carbon fiber and matrix;

[0008] S3: generating constraint conditions of the mixing ratio scheme based on the design parameters of the finite element model;

[0009] S4: generating the axial tensile strength of the carbon fiber reinforced composite material based on the mixing ratio scheme;

[0010] S5: generating damage variables of the carbon fiber reinforced composite material based on the finite element model and the mixing ratio scheme;

[0011] S6: Based on the axial tensile strength, the damage variable and the constraint condition, generating a damage limit tensile force of the carbon fiber reinforced composite material:

[0012] S7: Based on a preset hybrid algorithm, the damage limit tension and the temperature change rate of the carbon fiber reinforced composite material, the real-time strength of the carbon fiber reinforced composite material is generated, wherein the hybrid algorithm is:

[0013]

[0014] Where: is the real-time intensity, is the damage limit tensile force, It is the tensile strength that carbon fiber can withstand at the maximum temperature. is the real-time temperature, is the reference temperature, is the reference temperature The maximum tensile strength of the carbon fiber is is the thermal stability coefficient of carbon fiber, It is the tensile strength that carbon fiber can withstand at the maximum temperature. is the rate of temperature change;

[0015] S8: sorting the real-time strengths to obtain a strength sequence of the carbon fiber reinforced composite material, and generating the carbon fiber reinforced composite material according to a target mixing ratio determined by the strength sequence.

[0016] Optionally, the design parameters of the finite element model include:

[0017] is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the carbon fiber volume fraction, is the matrix volume fraction, is the tensile strength of carbon fiber, is the tensile strength of the matrix.

[0018] Optionally, the randomly generated mixing ratio of carbon fiber and matrix includes:

[0019] Randomly generate a number between 0 and 1 as the carbon fiber volume fraction;

[0020] The matrix volume fraction in the carbon fiber reinforced composite material is calculated according to the carbon fiber volume fraction, wherein the calculation formula of the matrix volume fraction is as follows:

[0021]

[0022] Where: is the carbon fiber volume fraction, is the matrix volume fraction;

[0023] A mixing ratio of the carbon fiber to the matrix is ​​determined based on the carbon fiber volume fraction and the matrix volume fraction.

[0024] Optionally, the constraint condition is:

[0025]

[0026] Where: is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the carbon fiber volume fraction, is the matrix volume fraction.

[0027] Optionally, the calculation formula of the axial tensile strength is:

[0028]

[0029] Where: is the axial tensile strength, is the tensile strength of carbon fiber, is the tensile strength of the matrix, is the carbon fiber volume fraction, is the matrix volume fraction, is the contribution of carbon fiber to the axial tensile strength of the composite material, It is the contribution of the matrix material to the axial tensile strength of the composite material.

[0030] Optionally, the calculation formula of the damage variable is:

[0031]

[0032] Where: is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the damage variable.

[0033] Optionally, the damage limit tensile force calculation formula is:

[0034]

[0035] Where: is the damage variable, is the axial tensile strength, is the damage limit tensile force, is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the carbon fiber volume fraction, is the matrix volume fraction, is the tensile strength of carbon fiber, is the tensile strength of the matrix.

[0036] Optionally, the constraint condition further includes: the real-time strength is within a preset predicted tension range.

[0037] Optionally, the step of sorting the real-time strength to obtain a strength sequence of the carbon fiber reinforced composite material comprises: determining an array of real-time strengths to be sorted;

[0038] Sorting the array to be sorted in descending order to obtain an ordered array of the real-time strength;

[0039] The ordered array is screened according to a preset predicted tension range to obtain a strength sequence within the predicted tension range.

[0040] Optionally, generating a carbon fiber reinforced composite material according to a target mixing ratio determined according to the strength sequence includes:

[0041] Filter out a target mixing ratio in the mixing ratio scheme according to the sorted real-time intensities;

[0042] The carbon fiber and the matrix are synthesized based on the target mixing ratio to obtain a carbon fiber reinforced composite material.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] Through the real-time strength calculation formula, multiple groups of carbon fiber volume fractions and matrix volume fractions are input into the real-time strength calculation formula to obtain different real-time strengths, and then the real-time strength of carbon fiber composites with different specifications at a certain temperature is analyzed, and the most suitable carbon fiber volume fraction and matrix volume fraction under a certain temperature condition are obtained. By adjusting the temperature change rate, the influence of temperature on different proportions of carbon fiber volume fractions and matrix volume fractions is analyzed. The dynamic response prediction accuracy is improved by introducing the temperature change rate parameter, and the influence of the damage limit tension and temperature change rate on the real-time strength of carbon fiber reinforced composites is considered, which can more accurately reflect the strength performance of the material under actual working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic flow chart of a carbon fiber reinforced composite material design method based on finite element analysis provided by one embodiment of the present invention; DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments belong to a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms of "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0048] As used herein, the words “if” or “if” may be interpreted as “at the time of” or “when” or “in response to determining” or “in response to detecting”, depending on the context. Similarly, the phrases “if it is determined” or “if (stated condition or event) is detected” may be interpreted as “when it is determined” or “in response to determining” or “when detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0049] The embodiment of the present application provides a carbon fiber reinforced composite material design method based on finite element analysis. The execution subject of the carbon fiber reinforced composite material design method based on finite element analysis includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided in the embodiment of the present application. In other words, the carbon fiber reinforced composite material design method based on finite element analysis can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0050] like Figure 1 FIG. 1 is a flow chart of a method for designing a carbon fiber reinforced composite material based on finite element analysis of the present invention. In this embodiment, the method for designing a carbon fiber reinforced composite material based on finite element analysis includes:

[0051] S1: Construct finite element models of carbon fiber reinforced composites.

[0052] In an embodiment of the present invention, the design parameters of the finite element model include:

[0053] is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the carbon fiber volume fraction, is the matrix volume fraction, is the tensile strength of carbon fiber, is the tensile strength of the matrix.

[0054] In detail, first perform feature screening and simplification to retain key features, retain the main structure according to the load transfer path, such as the edge of the laminate, the reinforced structure, the connecting hole, etc., remove chamfers, bosses, non-load-bearing small holes with a size of less than 0.5 mm, reduce the calculation complexity, and use CATIA, SolidWorks or ABAQUS / CAE to draw a three-dimensional solid or surface model to ensure the continuity of the surface (curvature radius > 1 mm). Before importing an external model (such as an STL file), use a geometry cleaning tool (such as HyperMesh's GeomCleanup) to repair broken surfaces and short edges.

[0055] Specifically, when importing, you need to determine the coordinate system and define the global coordinate system settings first. Usually, the geometric center of the model or the load application point (such as the symmetry center of the laminate) is selected. The coordinate axis directions must include: X-axis: along the main direction of the fiber (such as the fiber direction of the 0° ply), Y-axis: perpendicular to the fiber direction (within the plane of the laminate), Z-axis: perpendicular to the plane of the laminate (thickness direction), and then the local material coordinate system is allocated. One axis of the material coordinate system of each layer is aligned with the fiber direction (such as the angle between the fiber direction of the ±45° ply and the X-axis is ±45°). If there is reinforcement or complex connection, the fiber direction needs to be adjusted in the local coordinate system to match the actual ply.

[0056] After completing the above operations, it is necessary to carry out layer design and section definition. First, it is necessary to define the layer sequence according to the actual process. The single layer thickness is usually 0.125-0.25mm. Then determine the carbon fiber volume fraction. Through the carbon fiber volume fraction (such as 60%), calculate the matrix volume fraction (1-60%=40%), and then calculate the equivalent density of the carbon fiber and the matrix, so as to obtain the tensile strength of the carbon fiber and the tensile strength of the matrix.

[0057] S2: Randomly generate a mixing ratio of carbon fiber and matrix.

[0058] In an embodiment of the present invention, the randomly generated mixing ratio of carbon fiber and matrix includes:

[0059] Randomly generate a number between 0 and 1 as the carbon fiber volume fraction;

[0060] The matrix volume fraction in the carbon fiber reinforced composite material is calculated according to the carbon fiber volume fraction, wherein the calculation formula of the matrix volume fraction is as follows:

[0061]

[0062] Where: is the carbon fiber volume fraction, is the matrix volume fraction;

[0063] A mixing ratio of the carbon fiber to the matrix is ​​determined based on the carbon fiber volume fraction and the matrix volume fraction.

[0064] In detail, first determine the mixing ratio range. The carbon fiber volume fraction is usually set in the range of 30%-70%. The calculation formula of the matrix volume fraction is 100%-carbon fiber volume fraction. For example: if the carbon fiber volume fraction = 50%, then the matrix volume fraction = 50%;

[0065] Use a uniformly distributed random number generator (0-100) to generate the mixing ratio scheme:

[0066] Step 1: Set the seed value to ensure repeatability (e.g., seed = 20250310) and generate 10 sets of independent random numbers as candidate carbon fiber volume fraction values.

[0067] Step 2: Check whether the carbon fiber volume fraction is within the range of 30%-70%, and exclude abnormal values ​​outside the range (if the generated value is <30%, regenerate it).

[0068] In detail, randomly generated ratio schemes can help researchers explore previously unconsidered combinations of carbon fiber and matrix, thereby discovering new performance characteristics or performance improvement points. Through randomness, a large number of different ratio schemes can be generated, which together constitute a broad design space from which the optimal or suboptimal design can be screened. Among the large number of randomly generated schemes, there may be certain ratio combinations that can significantly improve the performance of composite materials. Through screening, one or more more cost-effective carbon fiber and matrix combinations may be found, thereby reducing production costs while ensuring performance.

[0069] S3: Generate constraints of the mixing ratio scheme based on the design parameters of the finite element model.

[0070] In the embodiment of the present invention, the constraint condition is:

[0071]

[0072] Where: is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the carbon fiber volume fraction, is the matrix volume fraction.

[0073] In detail, the current axial strain means the strain value actually borne by the carbon fiber reinforced composite material, the damage initiation axial strain means the strain when microcracks begin to appear in the carbon fiber reinforced composite material or the matrix cracks 0, the axial strain at fiber breakage means the ultimate strain when the carbon fiber reinforced composite material completely fails, the carbon fiber volume fraction means the volume percentage of carbon fiber in the carbon fiber reinforced composite material, and the matrix volume fraction means the volume percentage of the matrix in the carbon fiber reinforced composite material.

[0074] S4: generating the axial tensile strength of the carbon fiber reinforced composite material based on the mixing ratio scheme.

[0075] In an embodiment of the present invention, the calculation formula of the axial tensile strength is:

[0076]

[0077] Where: is the axial tensile strength, is the tensile strength of carbon fiber, is the tensile strength of the matrix, is the carbon fiber volume fraction, is the matrix volume fraction, is the contribution of carbon fiber to the axial tensile strength of the composite material, is the contribution of the matrix material to the axial tensile strength of the composite;

[0078] In detail, the formula shows that the total strength of carbon fiber composites is the sum of the contributions of the fiber and the matrix.

[0079] S5: Generate damage variables of the carbon fiber reinforced composite material based on the finite element model and the mixing ratio scheme.

[0080] In the embodiment of the present invention, the calculation formula of the damage variable is:

[0081]

[0082] Where: is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the damage variable.

[0083] In detail, the current axial strain represents the actual deformation of the material under axial load, which is obtained through experimental testing or finite element calculation, reflects the current stress state of the CFRP, and is the driving parameter of damage evolution.

[0084] In detail, the damage initiation axial strain represents the critical strain value when the carbon fiber reinforced composite material begins to show micro damage (such as fiber micro cracks and matrix cracking). It is predicted through tensile tests or theoretical models based on the fatigue life of materials, marking the turning point of the carbon fiber reinforced composite material from the elastic deformation stage to the damage accumulation stage.

[0085] In detail, the axial strain at fiber fracture indicates the maximum strain value when the carbon fiber reinforced composite material is completely fractured, which corresponds to the ultimate bearing capacity of the material. When the carbon fiber reinforced composite material is subjected to external force until the critical point of complete fracture, the strain value of its fiber along the force direction (i.e. axial direction) occurs. This strain value is actually a quantitative description of the deformation capacity of the material under the limit state, which is directly related to the maximum deformation degree that the composite material can achieve when subjected to external force.

[0086] More importantly, the axial strain at fiber fracture is closely related to the ultimate bearing capacity of the material. In composite materials, carbon fiber, as a reinforcing phase, undertakes the main load transfer task. When the external force gradually increases to a certain critical value, the carbon fiber will begin to fracture, and the corresponding axial strain at this time is the ultimate strain of the material. This ultimate strain value not only reflects the maximum deformation that the material can withstand before fracture, but also indirectly reflects the ultimate bearing capacity of the material - that is, the maximum external force that the material can withstand before fracture.

[0087] Therefore, for carbon fiber reinforced composite materials, the axial strain at fiber fracture is an important indicator to measure its mechanical properties, especially its load-bearing capacity. At the same time, this parameter also provides an important data basis for the reliability assessment, safety analysis and service life prediction of composite materials.

[0088] In detail, the damage variable shows a linear growth with strain, reflecting the progressive process of CFRP fracture and matrix damage. The formula adopts the linear damage evolution assumption and is applicable to the brittle fracture behavior dominated by CFRP.

[0089] S6: generating a damage limit tensile force of the carbon fiber reinforced composite material based on the axial tensile strength, the damage variable and the constraint condition.

[0090] In the embodiment of the present invention, the damage limit tensile force calculation formula is:

[0091]

[0092] Where: is the damage variable, is the axial tensile strength, is the damage limit tensile force, is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the carbon fiber volume fraction, is the matrix volume fraction, is the tensile strength of carbon fiber, is the tensile strength of the matrix.

[0093] In detail, by inputting a large amount of data, tensile tests are carried out on different batches of carbon fiber reinforced composites, and various strain data during the experiment and information such as the final breaking strength are recorded. By collecting a large amount of experimental data, the statistical reliability of the results can be significantly improved. A large sample size can reduce the impact of accidental errors and make the experimental results closer to the actual situation. Through data analysis, the key factors affecting material properties can be discovered, thereby guiding material improvements and optimization of production processes. At the same time, a large amount of experimental data is an important input for machine learning and predictive models. By establishing a data-based model, the performance of CFRP under different conditions can be predicted, providing strong support for design and production.

[0094] In detail, the finite element software is used to simulate and analyze the carbon fiber reinforced composite structure to obtain stress and strain data under different working conditions. At the same time, after the data is input, it is necessary to organize and clean the data, check the integrity of the data, and remove missing values ​​or abnormal values. For example, if the damage variable of a sample is greater than 1 or less than 0, then the data may be wrong and needs to be corrected or eliminated.

[0095] Sorting and cleaning data can ensure the accuracy and consistency of the data and reduce analytical biases caused by data errors or inconsistencies. The cleaned data is purer and can more accurately reflect the true performance of carbon fiber reinforced composites, thereby improving the reliability of the analysis results. At the same time, through data cleaning, invalid or low-quality data can be identified and eliminated, thereby avoiding wasting computing resources and time in subsequent analysis. Cleaned data helps to build a more robust and accurate prediction model, improve the generalization ability and prediction accuracy of the model, and eliminate missing values ​​and outliers. It can reduce errors in the analysis process and make the prediction results of statistical analysis and machine learning models more accurate.

[0096] In detail, statistical analysis is performed on the calculated damage limit tensile force, and histograms, box plots, etc. are drawn to understand the distribution of the data. For example, to see if there is an obvious central trend or a large degree of dispersion. Histograms and box plots can intuitively display the distribution of data, including central trends (such as mean or median) and dispersion (such as standard deviation or interquartile range). Through box plots, outliers or extreme values ​​in the data can be easily identified. These values ​​may have a significant impact on the statistical analysis results and need to be eliminated.

[0097] Secondly, histograms and box plots are helpful to evaluate whether the damage limit tensile force data obtained from different batches or under different conditions are consistent, so as to judge the stability and reliability of the production process. By comparing the histograms and box plots under different conditions, the performance differences of carbon fiber reinforced composites under different batches, different formulas or different production processes can be intuitively compared.

[0098] After understanding the distribution of the data, we can more specifically select useful information from the data, formulate material designs more scientifically based on statistical analysis results and visual charts, and improve the accuracy and effectiveness of decision-making.

[0099] Statistical analysis methods include:

[0100] Step 1: Correlation analysis, analyze the correlation between the damage limit tension and other parameters (such as carbon fiber volume fraction, damage variable, etc.). The Pearson correlation coefficient and other methods can be used for calculation. If a strong positive correlation is found, it means that increasing the carbon fiber volume fraction helps to increase the damage limit tension. By calculating the Pearson correlation coefficient, the strength and direction of the linear relationship between the damage limit tension and parameters such as carbon fiber volume fraction and damage variable can be quantified. A positive correlation means that an increase in one parameter is accompanied by an increase in another parameter, while a negative correlation means that an increase in one parameter is accompanied by a decrease in another parameter. If the analysis results show that there is a strong positive correlation between the carbon fiber volume fraction and the damage limit tension, then this can provide clear guidance for material design, that is, increasing the volume fraction of carbon fiber within a certain range is expected to increase the damage limit tension of the material.

[0101] After understanding the correlation between parameters, the performance of the material can be predicted and optimized by adjusting these parameters. For example, in the design of carbon fiber reinforced composite materials, the carbon fiber content can be adjusted to achieve the required mechanical properties based on the relationship between the carbon fiber volume fraction and the damage limit tensile force. Correlation analysis can also help identify the key factors that affect material performance, thereby developing more effective quality control strategies. By monitoring these key factors, it is possible to ensure that the produced materials have consistent performance.

[0102] Step 2: Comparative analysis, compare the calculated results with the design requirements or previous experimental data. If the calculated damage limit tensile force is lower than the design requirements, further analysis of the reasons is required, which may be due to poor material performance, process problems, or unreasonable design parameters. By comparing the calculation results with the design requirements, the rationality of the design can be verified. If the calculation results meet or exceed the design requirements, it means that the design parameters and material selection are reasonable, and subsequent production and application can be further promoted, and problems can be discovered and solved in a timely manner. If the calculated damage limit tensile force is lower than the design requirements, this means that the product may not meet the predetermined performance standards. At this time, timely discovery of problems and in-depth analysis can avoid waste and potential quality problems in subsequent production.

[0103] At the same time, the comparison results can reflect the gap between the actual performance of the material and the design expectations. If the material performance is not good, it may be necessary to replace the material or adjust the material formula to increase the damage limit tensile force. Moreover, through comparative analysis, the weak links in the process can be identified and targeted improvements can be made, such as optimizing production process parameters and improving production accuracy.

[0104] Unreasonable design parameters may also lead to substandard calculation results. At this time, according to the results of comparative analysis, the design parameters are adjusted, such as changing the volume fraction of carbon fiber, optimizing the ply structure, etc., to improve the mechanical properties of the material. In the process of comparative analysis, some new phenomena or laws may be discovered, which will help promote the innovation and development of materials science and engineering technology.

[0105] Step 3: Feedback on the design and optimization of material selection. For example, when the carbon fiber volume fraction increases to a certain level, the damage limit tensile force does not increase significantly, and it may be necessary to find a higher strength carbon fiber material, or to redistribute a more appropriate carbon fiber volume fraction and matrix volume fraction.

[0106] The damage limit tensile force calculation formula can directly reflect the maximum limit tensile force of various carbon fiber reinforced composite materials and is applicable to carbon fiber reinforced composite materials of different specifications.

[0107] S7: Based on a preset hybrid algorithm, the damage limit tension and the temperature change rate of the carbon fiber reinforced composite material, generating the real-time strength of the carbon fiber reinforced composite material, wherein the hybrid algorithm is.

[0108]

[0109] Where: is the real-time intensity, is the damage limit tensile force, It is the tensile strength that carbon fiber can withstand at the maximum temperature. is the real-time temperature, is the reference temperature, is the reference temperature The maximum tensile strength of the carbon fiber is is the thermal stability coefficient of carbon fiber, It is the tensile strength that carbon fiber can withstand at the maximum temperature. It is the temperature change rate, which refers to the difference between the real-time temperature and the reference temperature.

[0110] In detail, by considering the temperature change rate in the test, it is possible to ensure that carbon fiber reinforced composite materials have higher reliability in practical applications. This helps to reduce failures and accidents caused by material performance not meeting expectations. The mechanical properties of carbon fiber reinforced composite materials are significantly affected by temperature. By considering the temperature change rate, the stress conditions of the material in actual application can be simulated more accurately, thereby improving the accuracy of the test.

[0111] In the embodiment of the present invention, the constraint condition further includes: the real-time strength is within a preset predicted tension range.

[0112] Specifically, the tensile strength value of carbon fiber at the maximum temperature is the maximum tensile strength that a certain carbon fiber reinforced composite material can withstand.

[0113] The thermal stability coefficient of carbon fiber characterizes the stability of the mechanical properties of carbon fiber materials in temperature field changes, and specifically reflects the ability of the material to maintain its initial tensile strength in a high temperature environment. Experimental data show that when the temperature exceeds the glass transition temperature, the interfacial bonding strength between the carbon fiber and the resin matrix will decay exponentially with a proportional coefficient.

[0114] At the same time, the thermal stability coefficient of carbon fiber in different carbon fiber reinforced composites is different, which will change with the change of the ratio of the carbon fiber volume fraction to the matrix volume fraction. At this time, the damage limit tensile force will also change accordingly.

[0115] By correlating the tensile force that the carbon fiber can withstand at the maximum temperature with the damage limit tensile force, the real-time strength of carbon fiber composites of different specifications at a certain temperature is obtained. By inputting multiple sets of data, multiple sets of real-time strengths are obtained, and then the most suitable carbon fiber volume fraction and matrix volume fraction under a certain temperature condition are analyzed.

[0116] This formula takes into account the influence of damage limit tension and temperature change rate on the real-time strength of carbon fiber reinforced composite materials, and can more accurately reflect the strength performance of the material under actual working conditions.

[0117] S8: sorting the real-time strengths to obtain a strength sequence of the carbon fiber reinforced composite material, and generating the carbon fiber reinforced composite material according to a target mixing ratio determined by the strength sequence.

[0118] In an embodiment of the present invention, the step of sorting the real-time strength to obtain a strength sequence of the carbon fiber reinforced composite material includes:

[0119] Determine the array to be sorted of the real-time strength;

[0120] Sorting the array to be sorted in descending order to obtain an ordered array of the real-time strength;

[0121] The ordered array is screened according to a preset predicted tension range to obtain a strength sequence within the predicted tension range.

[0122] In detail, the to-be-sorted array means the unsorted real-time strength array, the ordered array means the sorted real-time strength array, and the predicted tension range pair means the force range set in advance to obtain a qualified strength sequence.

[0123] Specifically, the expression formula is: ~ ,in = ;

[0124] Where: Indicates that in the interval The uniform distribution on Take interval Any value in is equally likely;

[0125] based on The carbon fiber volume fraction and matrix volume fraction are obtained.

[0126] In an embodiment of the present invention, generating a carbon fiber reinforced composite material according to the target mixing ratio determined according to the strength sequence includes:

[0127] Filter out a target mixing ratio in the mixing ratio scheme according to the sorted real-time intensities;

[0128] The carbon fiber and the matrix are synthesized based on the target mixing ratio to obtain a carbon fiber reinforced composite material.

[0129] In detail, let the array to be sorted be ,

[0130] For each round i , j( )

[0131] After N rounds of sorting, the first N elements of the array are already in order (in descending order), and an ordered array is obtained. ;

[0132] For adjacent elements in the array to be sorted and For comparison, When and The value of , the exchange operation can be expressed as:

[0133]

[0134] Where: is the array to be sorted, To predict the real-time strength of the material to be sorted within the tensile range , is an ordered array, To predict the real-time strength of the sorted tensile range , t is a temporary variable.

[0135] In the several embodiments provided by the present invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0136] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0137] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0138] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0139] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0140] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A carbon fiber reinforced composite material design method based on finite element analysis, characterized in that: include: S1: Construct finite element model of carbon fiber reinforced composites; S2: Randomly generate a mixing ratio of carbon fiber and matrix; S3: generating constraint conditions of the mixing ratio scheme based on the design parameters of the finite element model; S4: generating the axial tensile strength of the carbon fiber reinforced composite material based on the mixing ratio scheme; S5: generating damage variables of the carbon fiber reinforced composite material based on the finite element model and the mixing ratio scheme; S6: Based on the axial tensile strength, the damage variable and the constraint condition, generating a damage limit tensile force of the carbon fiber reinforced composite material: S7: Based on a preset hybrid algorithm, the damage limit tension and the temperature change rate of the carbon fiber reinforced composite material, the real-time strength of the carbon fiber reinforced composite material is generated, wherein the hybrid algorithm is: Where: is the real-time intensity, is the damage limit tensile force, It is the tensile strength that carbon fiber can withstand at the maximum temperature. is the real-time temperature, is the reference temperature, is the reference temperature The maximum tensile strength of the carbon fiber is is the thermal stability coefficient of carbon fiber, It is the tensile strength that carbon fiber can withstand at the maximum temperature. is the rate of temperature change; S8: sorting the real-time strengths to obtain a strength sequence of the carbon fiber reinforced composite material, and generating the carbon fiber reinforced composite material according to a target mixing ratio determined by the strength sequence.

2. The carbon fiber reinforced composite material design method based on finite element analysis according to claim 1, characterized in that: The design parameters of the finite element model include: is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the carbon fiber volume fraction, is the matrix volume fraction, is the tensile strength of carbon fiber, is the tensile strength of the matrix.

3. The carbon fiber reinforced composite material design method based on finite element analysis according to claim 2, characterized in that: The randomly generated mixing ratio of carbon fiber and matrix includes: Randomly generate a number between 0 and 1 as the carbon fiber volume fraction; The matrix volume fraction in the carbon fiber reinforced composite material is calculated according to the carbon fiber volume fraction, wherein the calculation formula of the matrix volume fraction is as follows: Where: is the carbon fiber volume fraction, is the matrix volume fraction; A mixing ratio of the carbon fiber to the matrix is ​​determined based on the carbon fiber volume fraction and the matrix volume fraction.

4. The carbon fiber reinforced composite material design method based on finite element analysis according to claim 2, characterized in that: The constraints are: Where: is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the carbon fiber volume fraction, is the matrix volume fraction.

5. The carbon fiber reinforced composite material design method based on finite element analysis according to claim 2, characterized in that: The calculation formula of the axial tensile strength is: Where: is the axial tensile strength, is the tensile strength of carbon fiber, is the tensile strength of the matrix, is the carbon fiber volume fraction, is the matrix volume fraction, is the contribution of carbon fiber to the axial tensile strength of the composite material, It is the contribution of the matrix material to the axial tensile strength of the composite material.

6. The carbon fiber reinforced composite material design method based on finite element analysis according to claim 1, characterized in that: The calculation formula of the damage variable is: Where: is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the damage variable.

7. The carbon fiber reinforced composite material design method based on finite element analysis according to claim 6, characterized in that: The damage limit tensile force calculation formula is: Where: is the damage variable, is the axial tensile strength, is the damage limit tensile force, is the current axial strain, is the damage initiation axial strain, is the axial strain at fiber rupture, is the carbon fiber volume fraction, is the matrix volume fraction, is the tensile strength of carbon fiber, is the tensile strength of the matrix.

8. The carbon fiber reinforced composite material design method based on finite element analysis according to claim 4, characterized in that: The constraint condition also includes: the real-time strength is within a preset predicted tension range.

9. The carbon fiber reinforced composite material design method based on finite element analysis according to claim 8, characterized in that: The step of sorting the real-time strength to obtain a strength sequence of the carbon fiber reinforced composite material comprises: determining an array of real-time strengths to be sorted; Sorting the array to be sorted in descending order to obtain an ordered array of the real-time strength; The ordered array is screened according to a preset predicted tension range to obtain a strength sequence within the predicted tension range.

10. The carbon fiber reinforced composite material design method based on finite element analysis according to claim 9, characterized in that: The step of generating a carbon fiber reinforced composite material according to the target mixing ratio determined according to the strength sequence comprises: Filter out a target mixing ratio in the mixing ratio scheme according to the sorted real-time intensities; The carbon fiber and the matrix are synthesized based on the target mixing ratio to obtain a carbon fiber reinforced composite material.

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