Composite material curing deformation prediction and reversible deformation compensation analysis method and system
By constructing the master curve of relaxation modulus and the genetic integral constitutive model, the problem of low prediction accuracy of curing deformation of composite materials was solved, efficient mold design compensation was achieved, manufacturing accuracy was improved and costs were reduced.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-04
- Publication Date
- 2026-04-03
AI Technical Summary
Existing composite material curing deformation prediction accuracy is low, making it difficult to achieve effective compensation. Traditional mold design relies on trial and error, resulting in long R&D cycles and high costs. Existing simulation technology cannot accurately describe the unsteady mechanical behavior of materials at high temperatures.
By collecting storage modulus data of resin-based composite materials, a master curve of relaxation modulus is constructed to obtain stiffness coefficient and characteristic relaxation time. Temperature and curing degree translation factors are obtained using WLF equation and empirical model. A constitutive model of genetic integral is established, and the stress matrix is solved by combining the finite element method to generate surface correction amount to reduce deformation deviation.
It improves the molding accuracy of composite material components, reduces the time cost and material loss of trial molding and mold repair, and achieves high-precision deformation prediction and compensation analysis.
Smart Images
Figure CN121789868A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of computer-aided design and simulation technology. More specifically, this invention relates to a method and system for predicting and compensating for the curing deformation of composite materials. Background Technology
[0002] Resin matrix composites (RMCs) have become an indispensable main load-bearing structural material in the aerospace and high-end equipment manufacturing fields due to their excellent properties such as lightweight, high strength and fatigue resistance. Their manufacturing process usually involves a complex autoclave curing process, which promotes the cross-linking polymerization reaction of the resin matrix under the action of a specific temperature and pressure field, thereby transforming the loose prepreg into an integral component with a specific geometry and mechanical properties.
[0003] However, during the high-temperature curing and subsequent cooling process, due to the severe chemical shrinkage of the resin matrix, the significant difference in the coefficient of thermal expansion between the fiber and the matrix, and the interaction between the mold and the component interface, complex residual stresses inevitably accumulate inside the composite component. These internal stresses are released and transformed into macroscopic warping or springback deformation after the component is demolded and the constraints are removed. This process-induced deformation severely reduces the geometric accuracy of the component, often leading to difficulties in subsequent assembly or even product scrapping.
[0004] To control curing deformation, traditional mold design mainly relies on experience-based trial and error, which involves iteratively manufacturing prototypes, measuring deviations, and correcting the mold to approximate design tolerances. Trial and error methods have long development cycles and high costs due to the expensive processing of large metal molds, making it difficult to meet the urgent needs of modern industry for short-cycle, low-cost manufacturing. Therefore, virtual manufacturing technology based on numerical simulation has gradually become the industry mainstream. Among them, the finite element method (FEM) is widely used to calculate the curing process of composite materials and assist in the pre-compensation design of molds.
[0005] Although existing simulation technologies have been applied in engineering, most commonly used calculation models are based on linear elastic assumptions or simplified transient constitutive theories, often neglecting the significant viscoelastic characteristics of polymer materials under high-temperature conditions. The stress state of a material depends not only on the current strain level but also on the loading history and stress relaxation process. Especially under complex working conditions with the coupling of variable temperature and variable curing degree, the relaxation time span of the material is huge and has a strong memory effect. Existing technologies cannot accurately describe this unsteady mechanical behavior, which often leads to biases in the assessment of stress levels. Consequently, the final deformation prediction accuracy cannot meet the stringent manufacturing requirements of high-precision components. Summary of the Invention
[0006] To address the technical problems of low accuracy in predicting curing deformation of composite materials and difficulty in achieving effective compensation in the prior art, the present invention provides solutions in the following aspects.
[0007] In a first aspect, the present invention provides a method for predicting and compensating for the curing deformation of composite materials, comprising: collecting storage modulus data of resin-based composite materials at different degrees of curing; constructing a master curve of relaxation modulus; extracting stiffness coefficient and characteristic relaxation time from the master curve of relaxation modulus; obtaining a temperature translation factor using the WLF equation; obtaining a degree of curing translation factor using an empirical model; obtaining a conversion time using the temperature translation factor and the degree of curing translation factor; obtaining a constitutive model based on the stiffness coefficient, characteristic relaxation time, and conversion time; obtaining a stress matrix using the constitutive model; solving the curing deformation field based on the stress matrix; and generating a surface correction amount based on the curing deformation field to complete the deformation prediction and compensation of the composite material.
[0008] This invention collects the storage modulus and curing exothermic data of resin-based composite materials and establishes a constitutive model that includes historical integral terms. It combines temperature translation factor and curing degree translation factor to obtain the conversion time, thereby evaluating the stress evolution and deformation during the curing process based on the material's viscoelastic memory effect, and generating a surface correction amount to reduce the curing deformation deviation of composite material components.
[0009] Preferably, the step of collecting storage modulus data of resin-based composite materials at different degrees of curing, constructing a relaxation modulus master curve, and extracting stiffness coefficient and characteristic relaxation time from the relaxation modulus master curve includes: performing dynamic thermomechanical analysis on standard samples of resin-based composite materials, collecting storage modulus data at multiple constant degrees of curing; using the time-temperature-degree-of-curing equivalence principle, stitching the storage modulus data under different states into a relaxation modulus master curve by horizontal shifting; and using the generalized Maxwell model theory, numerically fitting the relaxation modulus master curve using the nonlinear least squares method to extract the stiffness coefficient and characteristic relaxation time.
[0010] This invention utilizes dynamic thermomechanical analysis to obtain storage modulus data under multiple constant degrees of cure. Based on the time-temperature-degree-of-curvature equivalence principle, the data under different states are spliced together to form the main storage modulus curve and then converted into the main relaxation modulus curve. Thus, under limited testing conditions, material viscoelastic parameters covering a wide time and degree-of-curvature domain are obtained, providing complete basic data support for subsequent deformation prediction.
[0011] Preferably, the conversion time satisfies the expression: ;in, Indicates time The corresponding conversion time; Indicates time; Indicates time; Indicates time-based temperature A defined temperature translation factor; Indicates time-based curing degree Determined curing degree translation factor; Indicates the zero constant; This indicates the operation of finding the maximum value.
[0012] This invention uses an integral form to calculate the conversion time, transforming the actual physical time under non-constant temperature and non-constant curing rates into an equivalent time perceived by the material's internal environment. This maps the unsteady relaxation behavior in the complex temperature and curing process to a steady-state process under a reference state, reducing stress assessment errors caused by fluctuations in environmental conditions.
[0013] Preferably, the constitutive model satisfies the expression: ;in, Indicates time The stress matrix; Represents the relaxation modulus matrix; Indicates time Conversion time; Indicates time Conversion time; Represents the total strain matrix; This represents the non-mechanical strain matrix.
[0014] Preferably, the step of solving the curing deformation field based on the stress matrix and generating the surface correction amount based on the curing deformation field includes: writing the constitutive model based on genetic integrals into a user subroutine of the finite element software; updating the stress matrix using a recursive expression in each incremental step, and simulating the demolding process after the curing cycle ends to extract the nodal displacement solution of the component surface to obtain the curing deformation field; and reversing the data of the curing deformation field and superimposing it on the original mold surface to generate the surface correction amount.
[0015] This invention writes a constitutive model based on genetic integrals into a user subroutine of finite element software and updates the stress matrix using a recursive formula in the incremental step. It extracts the nodal displacement solution by simulating the demolding process after the curing cycle ends, thereby improving the computational efficiency of large-scale finite element solutions while ensuring computational accuracy, and realizing the rapid evaluation of the curing deformation field of large composite material components.
[0016] Preferably, the number of sets of characteristic relaxation times is 15.
[0017] Preferably, the curing degree translation factor is obtained as follows: based on the dynamic thermomechanical analysis test curves at different constant curing degrees, with a selected reference curing degree as the benchmark, the logarithmic time displacement required to horizontally shift and overlap the storage modulus curves at other curing degrees with the reference curve is measured; a linear regression analysis is performed with the curing degree difference as the abscissa and the corresponding displacement as the ordinate, and the slope of the fitted line is used as the curing retardation coefficient; an empirical model is established, which defines the logarithmic value of the curing degree translation factor as equal to the product of the curing retardation coefficient and the difference between the real-time curing degree and the reference curing degree; the empirical model calculates the corresponding curing degree translation factor at any time based on the real-time curing degree.
[0018] Preferably, the zero-prevention constant is .
[0019] Preferably, the relaxation modulus matrix is constructed from the stiffness coefficient and the characteristic relaxation time; the thermal expansion coefficient and chemical contraction coefficient in the non-mechanical strain matrix are obtained through thermomechanical analysis and PVT characteristic experimental measurement.
[0020] This invention obtains the coefficient of thermal expansion and the coefficient of chemical shrinkage, and removes the non-mechanical strain caused by temperature changes and curing reactions from the total strain, thereby more accurately assessing the elastic energy storage and viscous dissipation caused by mechanical loads and boundary constraints, and improving the ability to analyze the curing deformation mechanism of resin-based composite materials.
[0021] Secondly, the present invention provides a composite material curing deformation prediction and anti-deformation compensation analysis system, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-mentioned composite material curing deformation prediction and anti-deformation compensation analysis method is implemented.
[0022] By adopting the above technical solution, a computer program is generated from the above-mentioned method for predicting and compensating for the curing deformation of composite materials, and stored in a memory so that it can be loaded and executed by a processor. A terminal device can then be made based on the memory and the processor for convenient use.
[0023] The beneficial effects of this invention are as follows: The constitutive model based on genetic integral established in this invention can record and calculate the continuous influence of loading history on stress state. By introducing relaxation modulus matrix and conversion time, the stress relaxation characteristics and memory decay mechanism of resin-based composite materials during high-temperature curing are reflected in numerical calculation, reducing the overestimation of stress level and deformation by traditional linear elastic models.
[0024] This invention obtains the real-time temperature and curing history of the component through the coupled analysis of the curing kinetic model and the heat conduction equation, and transmits these state variables to the mechanical solution module in real time to update the viscoelastic parameters of the material. This realizes two-way data interaction between the thermal field, chemical field and mechanical field, and improves the accuracy of evaluating the curing differences inside the composite material component with thick cross section or complex shape.
[0025] This invention proposes a closed-loop compensation strategy based on the principle of anti-deformation. It uses the solidification deformation field data obtained by simulation calculation to directly generate a surface correction amount opposite to the deformation direction and superimpose it on the mold surface. This provides a digital correction basis for mold design, reduces the time cost and material loss caused by repeated mold trials and repairs, and improves the final molding accuracy of composite material components. Attached Figure Description
[0026] Figure 1 This is a flowchart illustrating a method for predicting and compensating for curing deformation of composite materials according to the present invention. Figure 2 This is a schematic diagram illustrating the changes in temperature shift factor and cure degree shift factor over process time; Figure 3 This is a schematic diagram illustrating the comparison between the linear elastic model and the viscoelastic constitutive model in calculating stress; Figure 4 This is a schematic diagram illustrating the curing deformation field and the amount of surface correction. Detailed Implementation
[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0028] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
[0029] This invention discloses a method for predicting curing deformation and analyzing inverse deformation of composite materials, referring to... Figure 1 This includes steps S1-S4: S1. Collect the storage modulus data of resin-based composite materials at different degrees of curing, construct the master curve of relaxation modulus, and extract the stiffness coefficient and characteristic relaxation time from the master curve of relaxation modulus.
[0030] It is important to note that the stress performance of resin-based composite materials is closely related to their history. To accurately calculate this, a standard must first be established to describe how the material releases stress at different curing stages. Because temperature and degree of curing affect the speed of molecular motion, leading to continuous changes in relaxation properties, we need to integrate scattered experimental data into a unified mathematical model.
[0031] Specifically, dynamic thermomechanical analysis was performed on standard samples of resin-based composite materials. The frequency scan range was set from 0.1 Hz to 100 Hz, and storage modulus data were collected at no fewer than five different constant degrees of cure. Utilizing the time-temperature-degree-of-curvature equivalence principle, a reference temperature and degree of cure were selected, and the storage modulus data from different states were stitched together to form a master curve of storage modulus in the frequency domain through horizontal shifting. The master curve of storage modulus in the frequency domain was converted to a master curve of relaxation modulus in the time domain using Prony series fitting transformation. Based on the generalized Maxwell model theory, the relaxation modulus master curve was numerically fitted using the nonlinear least squares method to identify and extract a set of stiffness coefficients. and the corresponding feature relaxation time Differential scanning calorimetry (DSC) was used to test the resin-based composite material, and exothermic curing reaction curves were collected at different heating rates. Based on the exothermic curves, the activation energy, reaction order, and pre-exponential factor were obtained. A curing kinetic model describing the relationship between curing rate, temperature, and real-time degree of cure was constructed. This curing kinetic model was used in subsequent analyses to calculate the real-time degree of cure of the material at any given time based on the temperature history.
[0032] It is necessary to further add the stiffness coefficient. and characteristic relaxation time These are inherent property parameters of the material, which do not change with operating conditions, and form the constant basis for subsequently constructing the genetic integral kernel. The number of groups extracted in this invention... An empirical value of 15 groups is recommended. Too few groups will not accurately fit the relaxation behavior over a wide frequency range; too many groups will increase the computational burden and may lead to overfitting. 15 groups of parameters can ensure both fitting accuracy and computational efficiency.
[0033] S2. Obtain the temperature shift factor using the WLF equation, and obtain the curing degree shift factor using the empirical model; obtain the conversion time using the temperature shift factor and the curing degree shift factor.
[0034] It should be noted that, in order to address the problem of stress relaxation under non-constant temperature and non-constant curing rates that existing technologies cannot handle, this invention calculates a conversion time, transforming the actual elapsed time into an equivalent time perceived internally by the material. During the curing process, high temperatures accelerate molecular motion, while cross-linking reactions freeze molecular motion, rendering clocks unsuitable for describing material behavior. Therefore, an internal clock controlled by state variables must be introduced.
[0035] Specifically, the Williams-Landel-Ferry equation (WLF equation) is a classic empirical formula based on free volume theory, primarily used to describe the dependence of relaxation time on temperature in polymers near the glass transition temperature. This invention utilizes the WLF equation to calculate the temperature shift factor: based on the construction process of the relaxation modulus master curve, the horizontal shift amount under different isothermal conditions is extracted; using a reference temperature as a benchmark, the relationship between the horizontal shift amount and the temperature difference is substituted into the WLF equation for nonlinear fitting, thereby identifying the material constants in the WLF equation. These material constants are used to calculate the corresponding temperature shift factor under arbitrary temperature variations.
[0036] An empirical model is used to obtain the curing degree translation factor: Based on the dynamic thermomechanical analysis test curves at different constant curing degrees, and using the selected reference curing degree as a benchmark, the logarithmic time displacement required to horizontally shift the modulus curves at other curing degrees to coincide with the reference curve is measured; linear regression analysis is performed with the curing degree difference as the abscissa and the corresponding displacement as the ordinate, and the slope of the fitted line is used as the curing retardation coefficient. The curing retardation coefficient objectively reflects the freezing effect of increased crosslinking density on molecular chain movement; an empirical model including the curing retardation coefficient is established. The empirical model defines that the logarithmic value of the curing degree translation factor is linearly related to the curing degree difference, that is, the logarithmic value of the curing degree translation factor is equal to the product of the curing retardation coefficient and the difference between the real-time curing degree and the reference curing degree, which can be used to calculate the corresponding curing degree translation factor based on the real-time curing degree at any time.
[0037] For each integration point within the component, based on its real-time temperature history and curing history, the time derivative is divided by the current comprehensive translation factor and then integrated cumulatively to obtain the current converted time.
[0038] The conversion time satisfies the expression:
[0039] in, Indicates time The corresponding conversion time; Indicates time; Indicates time; Indicates time-based temperature A defined temperature translation factor; Indicates time-based curing degree Determined curing degree translation factor; This represents the zero-prevention constant, with an empirical value of [value missing]. ; This indicates the operation of finding the maximum value.
[0040] In the formula, the temperature shift factor The value of [value] decreases with increasing temperature, reflecting that high temperatures accelerate relaxation; [curing degree translation factor] The value increases with increasing degree of curing, reflecting the relaxation of curing resistance. (Denominator term) This constitutes a comprehensive time scaling factor. When the degree of curing is extremely high... It becomes extremely large, causing the integrand to approach 0, which means that even time... As time passes, time is converted. The stress increase almost stops, the stress relaxation process of the material is frozen, and the historical stress is completely preserved. By mapping time to equivalent time, this invention equates the unsteady and complex curing process to a steady-state process under a reference state, making linear viscoelastic theory applicable to complex working conditions of variable temperature and variable curing.
[0041] For example, Figure 2 This diagram illustrates the changes in temperature shift factor and cure degree shift factor over process time, showing the evolution of these two key variables within a standard curing cycle. The temperature shift factor decreases with increasing temperature, reflecting the accelerating effect of the high-temperature environment on molecular chain segment movement. The cure degree shift factor exhibits a rapid, non-linear increase in the later stages of the reaction, reflecting the hindering effect of cross-linked network formation on molecular movement. These two factors together determine the cumulative rate of the calculated time.
[0042] S3. Obtain the constitutive model based on the stiffness coefficient, characteristic relaxation time, and reduction time; use the constitutive model to obtain the stress matrix.
[0043] It should be noted that the current stress of resin-based composite materials is not only related to the current strain, but also depends on the strain rate history at all past moments. Furthermore, recent strain has a greater impact than long-term strain, exhibiting memory decay characteristics. To overcome the shortcomings of transient snapshot models, this invention establishes a constitutive model that includes historical integral terms to accurately calculate the stress state at each moment.
[0044] Specifically, thermomechanical analysis and PVT (Potentially Transformed Variable Temperature) characteristic measurements are performed on standard samples of resin-based composite materials to obtain the coefficients of thermal expansion and chemical shrinkage. Based on these coefficients, and considering the temperature and degree of curing changes, the non-mechanical strain matrix caused by thermal expansion and chemical shrinkage is obtained. Based on the stiffness coefficient and characteristic relaxation time, and considering the reduced time, the stress matrix at each material integration point is obtained. The stress matrix satisfies the following expression:
[0045] In the formula, Indicates time The stress matrix; Represents the relaxation modulus matrix; Indicates time Conversion time; Indicates time Conversion time; Represents the total strain matrix; This represents the nonmechanical strain matrix caused by thermal expansion and chemical contraction.
[0046] In the formula, the expression uses a convolutional form to divide the entire loading history into countless tiny strain increments. Kernel function Indicates at time The resulting strain increment has passed through After this period of decay, at time... How much stiffness contribution remains? If the material is in a rubbery state, the kernel function decays rapidly, and historical stresses are forgotten; if the material is in a glassy state, the kernel function value remains high, and historical stresses are inherited. The stress matrix fully preserves the genetic influence of the loading path on the current stress state through integral calculation, which can accurately distinguish and evaluate the elastic energy storage and viscous dissipation during the curing process, and solves the problem of insufficient stress relaxation assessment in traditional models.
[0047] It is necessary to further add the non-mechanical strain matrix. The correlation coefficients, namely the coefficients of thermal expansion and chemical contraction, were obtained through thermomechanical analysis and PVT characteristic experiments; the relaxation modulus matrix... From stiffness coefficient and characteristic relaxation time Acquisition: Based on the extracted stiffness coefficients and characteristic relaxation times, a scalar relaxation modulus function varying with the conversion time is constructed. To convert the one-dimensional scalar modulus into a tensor matrix required for three-dimensional stress analysis, this embodiment is based on existing linear viscoelastic theory, assuming that the resin-based composite material is macroscopically isotropic or transversely isotropic, and introducing Poisson's ratio as an empirical constant. Using the elastic-viscoelastic correspondence principle, the scalar relaxation modulus function is combined with Poisson's ratio according to the generalized Hooke's law to calculate each component in the stiffness matrix, thereby constructing a complete relaxation modulus matrix.
[0048] For example, Figure 3 This diagram compares the stress calculations of the linear elastic model and the viscoelastic constitutive model, showing the evolution of internal stress throughout the curing cycle. The curves indicate that stress caused by thermal shrinkage accumulates rapidly during the cooling phase. Compared to the linear elastic model, the viscoelastic constitutive model based on genetic integrals calculates lower stress values and exhibits significant stress relaxation characteristics. This demonstrates that the viscoelastic constitutive model accurately captures the viscous dissipation behavior of resin-based composites at high temperatures, avoiding overestimation of stress levels.
[0049] S4. Solve the curing deformation field based on the stress matrix; generate the surface correction amount based on the curing deformation field to complete the deformation prediction and compensation of the composite material.
[0050] It should be noted that, for the ultimate industrial application, this invention is based on high-precision stress solutions to predict deformation and implement compensation. Since direct calculation involves integral operations, the computational load is enormous. In practical implementation, a recursive algorithm is typically used to transform the integral into an algebraic incremental form.
[0051] Specifically, based on the constructed curing kinetics model and the preset curing process temperature curve, a coupled analysis of heat conduction and curing reaction is performed on the composite material component. The heat conduction equation is solved using the finite element method to obtain the temperature history and degree of curing history of each node within the component throughout the entire curing cycle, and this data is passed as state variables to the user subroutine of the finite element software. A constitutive model based on genetic integrals is written as a user subroutine for the finite element software. In each incremental step, the stress state is updated using a recursive expression, and the demolding process is simulated after the curing cycle ends. The nodal displacement solutions on the component surface are extracted to obtain a high-precision curing deformation field. According to the inverse deformation principle, the data of the curing deformation field is reversed and superimposed onto the original mold surface to generate a new surface correction amount.
[0052] It should be further noted that the time step for finite element solutions is typically dynamically adjusted between 0.1 s and 60 s. If the step size is too large, stress relaxation details during the rapid reaction phase will be lost; if the step size is too small, the computational cost will be too high. Dynamically adjusting the step size allows for more detailed calculations during intense curing reactions and less detailed calculations during slower reactions, balancing accuracy and efficiency.
[0053] For example, Figure 4 This is a schematic diagram of the curing deformation field and the surface correction amount. The diagram shows the predicted displacement solution of the component surface and the generated compensation surface. For the asymmetric concave deformation shown in the diagram, the system generates a corresponding surface correction amount based on the principle of inverse deformation. The geometry of the surface correction amount is equal in magnitude and opposite in direction to the curing deformation field. It is used to superimpose onto the original mold surface to offset the non-uniform process deformation generated during the curing process.
[0054] This invention also discloses a composite material curing deformation prediction and inverse deformation compensation analysis system, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, a composite material curing deformation prediction and inverse deformation compensation analysis method according to the present invention is implemented.
[0055] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.
Claims
1. A method for predicting and compensating for curing deformation of composite materials, characterized in that, include: Storage modulus data of resin-based composite materials at different degrees of curing were collected, relaxation modulus master curves were constructed, and stiffness coefficients and characteristic relaxation times were extracted from the relaxation modulus master curves. The temperature shift factor is obtained using the WLF equation, and the curing degree shift factor is obtained using an empirical model; the conversion time is obtained using the temperature shift factor and the curing degree shift factor. The constitutive model is obtained based on the stiffness coefficient, characteristic relaxation time, and reduction time; the stress matrix is obtained using the constitutive model. Solving the solidification deformation field based on the stress matrix; Based on the surface correction amount generated by the solidification deformation field, the deformation prediction and compensation of the composite material are completed.
2. The method for predicting and compensating for curing deformation of composite materials according to claim 1, characterized in that, The process involves collecting storage modulus data of resin-based composite materials at different degrees of cure, constructing a master relaxation modulus curve, and extracting stiffness coefficients and characteristic relaxation times from the master relaxation modulus curve, including: Dynamic thermomechanical analysis was performed on standard samples of resin-based composite materials, and storage modulus data were collected at multiple constant degrees of cure. Using the time-temperature-degree-of-curing equivalence principle, the storage modulus data under different states were spliced into a relaxation modulus master curve by horizontal shifting. Based on the generalized Maxwell model theory, the relaxation modulus master curve was numerically fitted using the nonlinear least squares method to extract the stiffness coefficient and characteristic relaxation time.
3. The method for predicting and compensating for curing deformation of composite materials according to claim 1, characterized in that, The conversion time satisfies the expression: ； in, Indicates time The corresponding conversion time; Indicates time; Indicates time; Indicates time-based temperature A defined temperature translation factor; Indicates time-based curing degree Determined curing degree translation factor; Indicates the zero constant; This indicates the operation of finding the maximum value.
4. The method for predicting and compensating for curing deformation of composite materials according to claim 1, characterized in that, The constitutive model satisfies the expression: ； in, Indicates time The stress matrix; Represents the relaxation modulus matrix; Indicates time Conversion time; Indicates time Conversion time; Represents the total strain matrix; This represents the non-mechanical strain matrix.
5. The method for predicting and compensating for curing deformation of composite materials according to claim 1, characterized in that, The solidification deformation field is solved based on the stress matrix; The surface correction amount generated based on the solidification deformation field includes: The constitutive model based on genetic integrals is written as a user subroutine of the finite element software; the stress matrix is updated using a recursive expression in each incremental step, and the demolding process is simulated after the curing cycle to extract the nodal displacement solution of the component surface, thus obtaining the curing deformation field; the data of the curing deformation field is reversed and superimposed on the original mold surface to generate the surface correction amount.
6. The method for predicting and compensating for curing deformation of composite materials according to claim 2, characterized in that, The number of sets of the characteristic relaxation time is 15.
7. The method for predicting and compensating for curing deformation of composite materials according to claim 3, characterized in that, The curing degree translation factor is obtained as follows: Based on the dynamic thermomechanical analysis test curves at different constant degrees of curing, and with the selected reference degree of curing as the benchmark, the logarithmic time displacement required to make the storage modulus curves at other degrees of curing coincide with the reference curve by horizontal shift is measured. Linear regression analysis was performed with the difference in curing degree as the abscissa and the corresponding displacement as the ordinate. The slope of the fitted line was used as the curing resistance coefficient. An empirical model is established, in which the logarithm of the curing degree shift factor is defined as equal to the product of the curing retardation coefficient and the difference between the real-time curing degree and the reference curing degree. The empirical model calculates the corresponding curing degree shift factor based on the real-time curing degree at any given time.
8. The method for predicting and compensating for curing deformation of composite materials according to claim 3, characterized in that, The zero-prevention constant is: .
9. The method for predicting and compensating for curing deformation of composite materials according to claim 4, characterized in that, The relaxation modulus matrix is constructed from the stiffness coefficient and the characteristic relaxation time; the thermal expansion coefficient and chemical contraction coefficient in the non-mechanical strain matrix are obtained through thermomechanical analysis and PVT characteristic experimental measurement.
10. A composite material curing deformation prediction and inverse deformation compensation analysis system, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement a method for predicting and compensating for curing deformation of composite materials according to any one of claims 1-9.