Method for establishing prediction model of R-angle region wrinkles in autoclave forming process
By establishing a predictive model for the autoclave molding process, the problem of fiber wrinkles in the R-corner area was solved, achieving efficient and accurate process optimization and quality control, and reducing production costs and time.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-23
- Publication Date
- 2026-04-03
AI Technical Summary
In the autoclave molding process, fiber wrinkles are prone to occur in the radius (R) area, which leads to a decrease in the mechanical properties of the component and poor dimensional accuracy. Existing methods mainly rely on post-inspection, which is time-consuming, resource-intensive, and difficult to effectively predict and avoid the occurrence of wrinkles.
A predictive model is established by measuring thickness changes and fiber slippage distance, and combining process parameters to construct an empirical equation to predict whether wrinkles will occur in the R-corner region, and to optimize process parameters to avoid wrinkle formation.
It enables the prediction of wrinkle risks during the process design stage, reduces material waste, shortens the R&D cycle, improves the first-pass yield and quality consistency of products, and reduces costs.
Smart Images
Figure CN121787095A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of autoclave molding process for resin-based composite materials, and specifically to a method for establishing a predictive model for wrinkles in the R-corner region during autoclave molding process. Background Technology
[0002] Carbon fiber reinforced resin matrix composites have become one of the key materials for high-end equipment manufacturing in aerospace and other fields due to their lightweight, high strength, strong designability, and excellent resistance to extreme environments. Among various composite material molding processes, autoclave molding technology shows broad application prospects in the manufacturing of aerospace composite components due to its advantages such as uniform molding temperature and pressure, stable and reliable process, low porosity, high mechanical consistency, and high dimensional accuracy of the molded components.
[0003] However, autoclave molding still faces a series of challenges in practical applications, especially in the molding of components with complex geometries (such as C-shaped, L-shaped, and other components with rounded corners), where defects such as fiber wrinkles are prone to occur in the rounded corner areas. This is usually related to process parameters (such as temperature, pressure, and time), the interaction between the mold and the prepreg, and the friction and deformation characteristics of the prepreg itself. These factors often have an impact during the compaction stage, causing excess fiber length to be generated due to path changes when the fiber layer transitions from areas with higher curvature to rounded corners with lower curvature. If the interlayer slip resistance is too high, the fibers cannot slip sufficiently to release stress, which can easily lead to fiber accumulation, buckling, and wrinkles. This reduces the mechanical properties and dimensional accuracy of the component, affects the consistency of the final product quality, and may even lead to component scrapping, increasing manufacturing costs and cycle time.
[0004] Therefore, predicting fiber wrinkles in the radius (R-angle) region has become a key step in improving the quality of autoclave-molded composite components. Establishing an effective wrinkle prediction method not only helps identify and mitigate defect risks during the process design stage, but also reduces the traditional trial-and-error-based parameter optimization cycle, providing technical support for high-quality and high-efficiency molding of composite materials.
[0005] Currently, in the production of advanced composite materials, wrinkles formed in the curing stage of prepregs have been a key factor restricting component quality and production efficiency. Existing research mainly uses equipment such as metallographic microscopes and scanning electron microscopes to directly observe and analyze wrinkles formed in the cured material, and has found that process parameters such as curing temperature and heating rate affect wrinkle formation. Although these studies have revealed some influencing factors from an experimental perspective, the overall method still mainly relies on post-testing of molded components. This analytical method has certain limitations: once wrinkles form, they usually lead to a decline in the mechanical properties of the component, making it difficult to meet usage requirements, resulting in material waste and increased production costs; in addition, relying on experimental trial and error to optimize process parameters is time-consuming and resource-intensive, affecting the development of high-efficiency, high-quality composite material components.
[0006] To address the aforementioned issues, a method is needed to predict the likelihood of wrinkles occurring under different process conditions before actual curing. By systematically integrating existing process parameters and corresponding wrinkle state data, a quantifiable and transferable predictive model can be established. This model can assess the wrinkle risk in advance for process combinations that have not yet been experimentally verified, thereby selecting a more optimal process window before actual production. This method not only helps reduce the wrinkle incidence rate during component molding and improve the first-pass yield, but also shortens the process development cycle, reduces the number of experiments and resource investment, and provides technical support for the high-quality and high-efficiency manufacturing of composite materials. Summary of the Invention
[0007] The purpose of this invention is to provide a method for predicting wrinkles in the R-corner area during autoclave molding, which can assess the wrinkle risk in advance, improve the first-pass yield of products, and provide technical support for shortening the process development cycle, reducing the number of tests and resource input, and achieving high-quality and high-efficiency actual production and manufacturing.
[0008] To address the aforementioned technical problems, this invention provides a method for establishing a predictive model for wrinkles in the R-corner region during autoclave forming, comprising the following steps: The prepreg is cured to obtain cured prepreg, and the thickness change is measured. The length of excess fibers generated in the R-corner section is calculated based on the thickness variation; Obtain the edge slip angle of the cured prepreg, and then calculate the actual fiber slip distance based on the excess fiber length generated in the R-angle portion; By changing the process parameters of the prepreg curing process, several thickness variations and actual fiber slippage distances were obtained. An empirical equation is obtained by fitting the process parameters, thickness variation, and actual fiber slip distance. The process parameters to be measured are input into the empirical equation to obtain the prediction results.
[0009] Preferably, the prepreg is cured to obtain a cured prepreg, and the thickness change is measured, specifically including the following steps: The prepreg is laid on an L-shaped mold and pre-compacted using a vacuum bag pressing method. The thickness of the prepreg before curing is measured. ; According to the process parameters, the curing method involves first maintaining the temperature at room temperature and then raising the temperature to cure the prepreg. The thickness of the prepreg after curing is then measured. ; Based on the thickness of the prepreg before curing and the thickness of the cured prepreg The thickness change was calculated.
[0010] Preferably, the formula for calculating the thickness change is: In the formula: This represents the change in thickness.
[0011] Preferably, the formula for calculating the excess fiber length generated by the R-angle portion is: In the formula: This represents the length of excess fibers generated in the R-angle portion.
[0012] Preferably, the process of obtaining the edge slip angle is as follows: Take a photograph of the edge of the cured prepreg and then measure the edge slip angle using ImageJ.
[0013] Preferably, the formula for calculating the actual slip distance of the fiber is: In the formula: α' represents the actual fiber slip distance; α' represents the edge slip angle.
[0014] Preferably, the process parameters include the curing temperature, heating rate, and pressure.
[0015] Preferably, an empirical equation is obtained by fitting process parameters, thickness variation, and actual fiber slippage distance, specifically including the following steps: Establish separately , Empirical equations relating heat preservation temperature T, heating rate K, and pressure P n =g(T, K, P) ' n =f(T, K, P); Where: A, B, a, b, c, d, e, and f all represent parameters; n This represents the nth thickness change; ' n This represents the actual sliding distance of the nth fiber; Solving for the parameters A, B, a, b, c, d, e, and f, we obtain: In the formula: This represents the excess fiber length generated by the nth R-angle portion.
[0016] Preferably, the process parameters to be measured are input into an empirical equation to obtain the prediction results, specifically including the following steps: The process parameters to be measured are input into the empirical equation to calculate the excess fiber length generated by the nth R-angle portion corresponding to the process parameters to be measured. n The nth thickness change and the actual sliding distance of the nth fiber ; Compare the length of excess fibers generated in the nth R-angle portion. n The actual sliding distance of the nth fiber ' n The size of the value is used to obtain the prediction result.
[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention establishes the relationship between process parameters (temperature, heating rate, pressure) and compaction strain and slip distance, constructing an empirical equation model capable of predicting wrinkle formation in composite materials during the curing process on complex curved surfaces. This model solves the problem of directly measuring slip distance in actual processes and can predict slip distance under other unexperimented parameters. Furthermore, by comparing it with slip distance caused by thickness variations, it can predict whether wrinkles will occur in the cured component under those process parameters. This empirical equation enables process optimization and defect prevention, to some extent avoiding the high cost and long cycle associated with traditional process development, which relies heavily on engineers' experience and numerous repetitive experiments. In addition, the model can screen a large number of parameter combinations, shortening the R&D cycle and reducing material and energy costs. It reduces material waste caused by wrinkles at the source, improves the first-pass yield and quality consistency of products, and provides technical support for the efficient, robust, and digital manufacturing of composite material components. Attached Figure Description
[0018] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.
[0019] Figure 1 This represents the ideal sliding condition for L-shaped mold curing (no wrinkles are generated); Figure 2 This is the actual sliding condition of the L-shaped mold during curing (wrinkles are produced); Figure 3 The empirical equations predicted that wrinkles would occur, and wrinkles did indeed occur in reality. Figure 4 The empirical equation predicts no wrinkles will be produced, but in reality no wrinkles will be produced. Figure 5 This is a flowchart illustrating a method for establishing a prediction model for wrinkles in the R-corner region during the autoclave forming process of this invention. Detailed Implementation
[0020] Numerous specific details are set forth in the following description to provide a full understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.
[0021] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.
[0022] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."
[0023] The present invention will now be described in further detail with reference to the accompanying drawings: This invention provides a method for establishing a predictive model for wrinkles in the radius (R) corner region during autoclave molding. The technical solution of this invention compares the excess fiber length caused by changes in layup thickness before and after curing of the R-corner component under different process parameters with the interlayer slip distance of the fibers after curing to determine whether wrinkles occur in the layup structure. A model is established by combining existing theoretical and experimental results to predict wrinkles. The specific method is as follows: A. For the laid prepreg, seal it with sealing strips in the following order: mold - release agent - release cloth - prepreg - release cloth - non-porous release film - breathable felt - vacuum bag. After vacuuming, put it into an autoclave for curing.
[0024] B. Measure the thickness of the prepreg before curing using a digital thickness gauge. Thickness after curing And calculate the thickness change H, based on the calculated length of excess fibers generated in the R-angle portion. L: Where: θ is the mold angle. H represents the change in prepreg thickness before and after curing.
[0025] C. Observe the edge of the cured prepreg using a metallographic microscope, measure the edge slip angle α' using Image J, and calculate the actual fiber slip distance using the following formula. : D. By comparison Determine whether wrinkles have occurred and verify with the actual occurrence of wrinkles.
[0026] E. By changing different process parameters (temperature, heating rate, pressure), a series of... H and and the temperature, heating rate, pressure and H and The fitting process yields an empirical equation, which is used to predict process parameters that have not been experimentally determined. H and and will With calculation Compare and predict the occurrence of wrinkles.
[0027] To better illustrate the technical effects of the present invention, the present invention provides the following specific embodiments to illustrate the above technical process: Example 1: The prepreg is laid on an L-shaped mold, and the prepreg is pre-compacted by vacuum bag pressing, and the thickness of the prepreg layer is measured. Then, it was cured according to the curing method (125℃ for 30 min, then increased to 180℃ at a rate of 2℃ / min and held for 120 min; pressure 600 kPa). After cooling, it was demolded and the thickness was measured. Calculate thickness variation The results were calculated based on the geometric relationship of the composite material in the bending region. ,like Figure 1 The edge slip angle α of the cured composite material was obtained using a metallographic microscope and ImageJ, and then calculated. ',like Figure 2 .
[0028] like( If ') > 0, then theoretically wrinkles will occur. Comparing this result with actual observations further confirms the accuracy of the method. Furthermore, The larger the value of '), the more severe the wrinkling phenomenon is theoretically.
[0029] By changing the holding temperature (105℃, 115℃, 125℃, 135℃…), the heating rate (1℃ / min, 1.5℃ / min, 2℃ / min, 2.5℃ / min…), and the pressure (585KPa, 590KPa, 595Kpa, 600KPa…), a series of… results were obtained using the same method. 1. 2. 3... n and 1. 2 3... n And calculate , , ... Then establish separately n , n Empirical equations relating temperature T, heating rate K, and pressure P n =g(T, K, P) ' n =f(T, K, P).
[0030] And due to the relationship between temperature T and resin viscosity Follow the following relationship: Furthermore, the sliding resistance is directly proportional to the resin viscosity, while the sliding distance is inversely proportional to the sliding resistance. Therefore... and It is directly proportional (where a is the fitting factor), while the heating rate affects the material's slip time. With K -b Proportional relationship; In addition, the sliding resistance is also related to the pressure; the greater the pressure, the greater the sliding resistance, resulting in a shorter sliding distance. Therefore, we get: Correspondingly: Solve for A, B, a, b, c, d, e, and f; The calculations were then completed. Substituting the process parameters that were not tested into the equation, the calculation was obtained. and and compare and Size is used to determine the occurrence of wrinkles in untested process parameters.
[0031] Example 2: The prepreg was laid on an L-shaped mold and pre-compacted using a vacuum bag pressing method. Then, it was cured according to the following method (110℃ for 30 min, then increased to 180℃ at a rate of 1.5℃ / min and held for 120 min; pressure 600 kPa). Substituting the parameters into an empirical equation yielded the desired results. n =2.57mm> ' n =2.36mm Wrinkles were determined through model analysis, and subsequent observation of the cured sample using a metallographic microscope revealed significant wrinkling in the material. Figure 3 .
[0032] Example 3: The prepreg was laid on an L-shaped mold and pre-compacted using a vacuum bag pressing method. Then, it was cured according to the following method (130℃ for 30 min, then increased to 180℃ at a rate of 1.5℃ / min and held for 120 min; pressure 600 kPa). Substituting the parameters into an empirical equation yielded the desired results. n=2.59mm is close to With n=2.56mm, the model indicated that virtually no wrinkles would form. Subsequent observation of the cured sample using a metallographic microscope revealed no significant wrinkles. Figure 4 .
[0033] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions within the technical scope disclosed in the present invention should be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.
Claims
1. A method for establishing a predictive model for wrinkles in the R-corner region during autoclave forming process, characterized in that, Includes the following steps: The prepreg is cured to obtain cured prepreg, and the thickness change is measured. The length of excess fibers generated in the R-corner section is calculated based on the thickness variation; Obtain the edge slip angle of the cured prepreg, and then calculate the actual fiber slip distance based on the excess fiber length generated in the R-angle portion; By changing the process parameters of the prepreg curing process, several thickness variations and actual fiber slippage distances were obtained. An empirical equation was obtained by fitting the process parameters, thickness variation, and actual fiber slip distance. The process parameters to be measured are input into the empirical equation to obtain the prediction results.
2. The method for establishing a prediction model for wrinkles in the R-corner region during the autoclave forming process according to claim 1, characterized in that, The prepreg is cured to obtain cured prepreg, and the thickness change is measured. The specific steps include: The prepreg is laid on an L-shaped mold and pre-compacted using a vacuum bag pressing method. The thickness of the prepreg before curing is measured. ; According to the process parameters, the curing method involves first maintaining the temperature at room temperature and then raising the temperature to cure the prepreg. The thickness of the prepreg after curing is then measured. ; Based on the thickness of the prepreg before curing and the thickness of the cured prepreg The thickness change was calculated.
3. The method for establishing a prediction model for wrinkles in the R-corner region during the autoclave forming process according to claim 2, characterized in that, The formula for calculating the thickness change is: In the formula: This represents the change in thickness.
4. The method for establishing a prediction model for wrinkles in the R-corner region during the autoclave forming process according to claim 3, characterized in that, The formula for calculating the excess fiber length generated by the R-angle portion is: In the formula: This represents the length of excess fibers generated in the R-angle portion.
5. The method for establishing a prediction model for wrinkles in the R-corner region during the autoclave forming process according to claim 4, characterized in that, The process of obtaining the edge slip angle is as follows: Take a photograph of the edge of the cured prepreg and then measure the edge slip angle using ImageJ.
6. The method for establishing a prediction model for wrinkles in the R-corner region during the autoclave forming process according to claim 5, characterized in that, The formula for calculating the actual slip distance of the fiber is: In the formula: α' represents the actual fiber slip distance; α' represents the edge slip angle.
7. The method for establishing a prediction model for wrinkles in the R-corner region during the autoclave forming process according to claim 6, characterized in that: The process parameters include the curing temperature, heating rate, and pressure.
8. The method for establishing a prediction model for wrinkles in the R-corner region during the autoclave forming process according to claim 7, characterized in that, An empirical equation is obtained by fitting process parameters, thickness variations, and actual fiber slippage distance. The specific steps include: Establish separately , Empirical equations relating heat preservation temperature T, heating rate K, and pressure P n =g(T, K, P) ' n =f(T, K, P); Where: A, B, a, b, c, d, e, and f all represent parameters; n This represents the nth thickness change; ' n This represents the actual sliding distance of the nth fiber; Solving for the parameters A, B, a, b, c, d, e, and f, we obtain: In the formula: This represents the excess fiber length generated in the nth R-angle section.
9. The method for establishing a prediction model for wrinkles in the R-corner region during the autoclave forming process according to claim 8, characterized in that, The process parameters to be measured are input into the empirical equation to obtain the prediction results, which specifically includes the following steps: The process parameters to be measured are input into the empirical equation to calculate the excess fiber length generated by the nth R-angle portion corresponding to the process parameters to be measured. n The nth thickness change and the actual sliding distance of the nth fiber ; Compare the lengths of excess fibers generated at the nth R-angle. n Actual slip distance of the nth fiber ' n The size of the value is used to obtain the prediction result.