Simulation method for curing deformation of large-size composite stiffened panel

Abstract

The application discloses a simulation method for curing deformation of large-size composite stiffened panels, and relates to the field of composite forming simulation.The method comprises the following steps: providing a finite element grid unit system matched with multi-physical field coupling, supporting dynamic coupling analysis of a composite temperature field, a curing degree field and a stress deformation field; integrating a user subroutine in time sequence in finite element simulation, and dynamically regulating and controlling material properties and boundary conditions; based on a deformation quantization algorithm of spatial matching optimization, extracting normal deformation of an outer surface of a panel and eliminating inertial offset errors; verifying model reliability through point cloud data mapping and full-field error distribution analysis; and the finite element grid unit system is matched with curved surface profiles and variable-thickness geometric characteristics, and a mapping relationship of topological continuity of a longeron and a panel interface is established.The application can significantly improve the precision and reliability of curing deformation prediction under complex geometric structures.

Description

Technical Field

[0001] This invention relates to the field of composite material molding simulation, and in particular to a simulation method for curing deformation of large-size composite reinforced wall panels. Background Technology

[0002] Composite reinforced panels, due to their high specific strength, designability, and fatigue resistance, have become core components of aerospace main load-bearing structures. However, during the curing process, residual stress accumulates due to material anisotropy, geometric irregularities, and mold interactions. Deformation caused by stress release after curing not only reduces geometric accuracy but also weakens mechanical properties and affects assembly tolerances. As panel dimensions increase, deformation problems become increasingly nonlinear, necessitating high-precision prediction methods to guide process optimization. Traditional experimental methods are costly, have poor repeatability, and struggle to comprehensively quantify the coupled effects of multiple factors. Finite element simulation technology, through multi-field coupled analysis of temperature, curing, and stress, provides an effective approach for predicting residual stress distribution and deformation behavior.

[0003] Existing methods, such as patent CN110197008A, have achieved temperature, curing, and stress coupling simulation of composite material plates, but they still have significant limitations: 1. They are only applicable to simple plate structures and cannot effectively handle the curved contours, variable thickness characteristics, and complex mesh mapping problems of large-size stiffened panels, resulting in limited model accuracy; 2. They do not consider the interference of manufacturing factors such as hole-making processes on residual stress release, and lack a mechanism to dynamically correct local material properties in the simulation to eliminate process influences; 3. They lack systematic deformation quantification and verification methods, cannot eliminate inertial offset errors through best-fit alignment algorithms, and have not established a quantitative comparison process between simulation and experiment based on laser scanning point cloud data, making it difficult to guarantee model reliability. Therefore, based on the above problems, this invention proposes a simulation method for the curing deformation of large-size composite material stiffened panels. Summary of the Invention

[0004] Purpose of the invention

[0005] To address the aforementioned issues, the present invention aims to provide a simulation method for the curing deformation of large-size composite reinforced wall panels. This method aims to overcome the limitations of existing technologies in adapting to complex geometric structures, eliminate the interference of manufacturing factors such as hole-opening processes on residual stress release, and establish a quantitative verification mechanism based on point cloud data alignment. Ultimately, it achieves high-precision, engineering-oriented simulation prediction of curing deformation, providing a reliable basis for process optimization.

[0006] Technical solution

[0007] To achieve the above objectives, this invention provides a simulation method for the curing deformation of large-size composite reinforced wall panels. This method simplifies the long stringer membrane surface into a right-angle transition structure by geometrically removing non-critical features while retaining the variable thickness contour line. Mesh mapping enables shared node connections between the long stringer and the wall panel membrane surface. Based on actual layup parameters, layered, continuously numbered three-dimensional solid elements are generated, and spatial vector relationships are used to automatically orient the element layup direction. A step-by-step analysis process is designed, integrating user subroutines to dynamically adjust material properties. During the stress release stage, the elastic modulus of the opening region is corrected to the stress isolation threshold to eliminate process interference. Simultaneously, heat conduction, curing degree evolution, and thermal expansion effect calculations are coupled. Furthermore, the coordinates of nodes on the outer surface of the wall panel are extracted, and the opening region is filtered. An optimal fitting spatial alignment algorithm is used to eliminate inertial offset and extract the normal deformation. The deformation at the same characteristic location is compared between the simulation and experiment via a laser scanning point cloud data interface, and a full-field quantitative error analysis is performed.

[0008] In a first aspect, the present invention provides a simulation method for the curing deformation of large-size composite reinforced wall panels, comprising:

[0009] A finite element mesh system with multi-physics coupling adaptation is provided, supporting dynamic coupling analysis of temperature field, curing degree field and stress deformation field of composite materials; the system retains surface contour and variable thickness features through geometric simplification, and realizes the topological continuity of complex geometric structures based on mesh mapping and layered solid element continuous numbering mechanism;

[0010] In finite element simulation, user subroutines are integrated with the timing process, and material properties and boundary conditions can be dynamically adjusted. By timing the elastic modulus of the opening region to the stress isolation threshold, the interference of the manufacturing process on the release of residual stress can be accurately eliminated.

[0011] The deformation quantization algorithm based on spatial matching optimization extracts the normal deformation of the outer surface of the wall panel and eliminates the inertial offset error. By optimizing the spatial matching relationship of the nodes before and after curing, the rigid body displacement error caused by residual stress release is automatically eliminated.

[0012] Based on the mapping interface between laser scanning point cloud data and simulation nodes, and combined with full-field interpolation smoothing and feature position comparison analysis, a quantitative error evaluation standard is formed to verify the reliability of the model.

[0013] The finite element mesh system described herein adapts to curved surface profiles and variable thickness geometry, and establishes a topological continuity mapping relationship between the girder and panel interfaces.

[0014] Furthermore, the multi-field coupling analysis is achieved through staged stress evolution simulation. In the first analysis step, the outer surface of the wall panel is fixed and a temperature load is applied to simulate stress accumulation. In the second analysis step, the boundary constraints are removed to simulate stress release deformation, thereby achieving high-fidelity simulation of the residual stress evolution and release process.

[0015] Furthermore, the construction of the finite element mesh system includes:

[0016] Mapping the mesh of the stringer and the membrane surface of the wall panel to form a common node connection ensures the continuity of the stress transfer path;

[0017] Generates sequentially numbered layered solid units based on actual ply parameters, adapting to curved surfaces and variable thickness geometries.

[0018] By controlling the automatic orientation of the ply direction using spatial vector relationships, the problem of ply orientation inaccuracy under complex geometries can be solved.

[0019] Furthermore, the automated orientation calculates the basic orientation based on the spatial vector relationship between the centroid of the solid unit and the preset reference point, and assigns the actual orientation through the orientation function of the finite element software in combination with the ply angle parameters.

[0020] Furthermore, the user subroutine includes a material property timing control module, used to correct the elastic modulus of the open-pore region to the stress isolation threshold during the curing stress release stage. The open-pore region of the composite material is prone to localized stress concentration and fiber distortion during curing, resulting in an actual elastic modulus in this region that is lower than the theoretical value. The correction aims to reflect the true degradation of the mechanical properties in this region.

[0021] Furthermore, the stress isolation threshold is the critical value at which the elastic modulus of the material in the pore area decreases to the point where residual stress cannot be transmitted. The mechanical vibration energy caused by the dense pore process is converted into internal heat energy of the material, which intensifies the movement of molecular chain segments in the pore area and dissipates residual stress through microscopic plastic deformation. Unlike the traditional sacrificial layer process, this method directly creates pores in the product body area. The pore matrix forms a physical barrier to cut off the residual stress transmission path, causing the elastic modulus of the pore area to drop to a critical level where stress waves cannot propagate effectively.

[0022] Furthermore, the deformation quantization algorithm includes filtering the node coordinates of the opening area, using the best-fit spatial alignment algorithm to eliminate the inertial offset of the solidified deformation data, solving the problem of misalignment of the layup direction under complex geometry, and extracting the change in normal coordinates as the deformation quantization index to ensure that the deformation data strictly reflects the intrinsic deformation of the material.

[0023] Furthermore, the deformation quantization algorithm assigns corresponding weights to nodes participating in spatial alignment based on the spatial distribution of structural geometric features, and calculates spatial transformation relationships based on the weights using a weighted optimization algorithm.

[0024] Furthermore, in the process of verifying the accuracy of the model, the deformation data of simulation and experiment were compared at the same topological location, and quantitative error convergence analysis was performed through the full-field deformation distribution map to establish the model reliability criterion.

[0025] Secondly, the present invention also provides a simulation system for the curing deformation of large-size composite reinforced wall panels, the system comprising, according to the method described in the first aspect above:

[0026] A geometry processing module is used to preserve variable thickness contours and simplify non-critical features;

[0027] The mesh coupling module performs mesh mapping and sequential numbering of layered solid elements for the stringers and wall panel membrane surfaces.

[0028] The multiphysics solution module integrates user subroutines to realize time-coupled calculations of temperature, curing and stress deformation;

[0029] The verification and analysis module outputs a comparison of the deformation amounts in simulation and experiment based on the spatial alignment algorithm.

[0030] Furthermore, the verification and analysis module includes a three-dimensional scanning data interface and an inertial offset correction unit, achieving millimeter-level matching accuracy between laser point cloud data and simulation nodes; the spatial alignment algorithm achieves accurate extraction of deformation by optimizing the spatial matching relationship of nodes.

[0031] This invention simplifies the stringer membrane surface into a right-angle transition structure by geometrically removing non-critical features of the wall panel while retaining the variable thickness contour line. Mesh mapping enables shared-node connections between the stringer and the wall panel membrane surface. Based on actual layup parameters, layered, continuously numbered 3D solid elements are generated using offset and bottom-up methods. Spatial vector relationships are used to automatically orient the element layup direction. A step-by-step analysis process is designed: the first step applies a temperature load to the outer surface of the wall panel to simulate stress accumulation; the second step removes constraints to simulate stress release. User subroutines are integrated to dynamically adjust material properties. During the stress release stage, the elastic modulus of the opening area is corrected to the stress isolation threshold to eliminate process interference, while simultaneously coupling calculations of heat conduction, curing degree evolution, and thermal expansion effects. Node coordinate data of the outer surface of the wall panel is extracted and the opening area is filtered. An optimal fitting spatial alignment algorithm is used to eliminate inertial offset caused by residual stress release, and the change in normal coordinates is extracted as deformation. The deformation at the same feature location is compared between simulation and experiment via a laser scanning point cloud data interface, and quantitative error analysis is performed using full-field interpolation smoothing.

[0032] This scheme significantly improves the accuracy and reliability of curing deformation prediction under complex geometries. Mesh mapping and layered solid element generation mechanisms effectively support curved surface profiles and variable thickness features, overcoming the limitations of existing technologies for flat plate structures and improving model fidelity. The dynamic elastic modulus correction mechanism isolates the influence of the opening process during stress release, avoiding overall prediction deviations caused by local stress disturbances. The spatial alignment algorithm eliminates inertial offset by optimizing node matching relationships, ensuring that the extracted deformation strictly reflects the intrinsic deformation of the material, with the maximum error controlled within an acceptable engineering range. Quantitative comparison and full-field error analysis based on point cloud data form a reliability assessment standard, providing a high-confidence basis for process compensation design and expanding the application scenarios of composite material curing deformation simulation in aerospace main load-bearing structures.

[0033] Beneficial effects

[0034] By implementing the simulation method for curing deformation of large-size composite reinforced wall panels provided by the present invention, the following technical effects are achieved:

[0035] (1) By combining geometric simplification and mesh mapping techniques with a hierarchical solid element sequential numbering mechanism, a topological continuous mesh system supporting curved surface profiles and variable thickness features was constructed. This method overcomes the limitations of existing techniques for simple flat plate structures, significantly improves the structural fidelity of large-size stiffened panel finite element models, and provides a geometric basis for multi-field coupling analysis.

[0036] (2) During the curing stress release stage, the elastic modulus of the material in the opening area is dynamically corrected to the stress isolation threshold through a user subroutine, eliminating the influence of local stress disturbances caused by the opening process on the overall deformation. This mechanism realizes the coupled simulation of manufacturing process and residual stress release, overcoming the prediction bias problem caused by neglecting process interference in traditional methods.

[0037] (3) The best-fit spatial alignment algorithm is used to process the node coordinate data. By optimizing the spatial matching relationship of the node sets before and after solidification, the rigid body displacement error caused by residual stress release is automatically eliminated. This algorithm ensures that the extracted deformation strictly reflects the intrinsic deformation of the material, solves the quantitative distortion problem caused by inertial offset in the existing technology, and improves the physical authenticity of the deformation data.

[0038] (4) A mapping interface between laser scanning point cloud data and simulation nodes was constructed, and a quantitative error evaluation standard was formed by combining full-field interpolation smoothing and feature position comparison analysis. This system realizes the systematic verification of the simulation results of solidification deformation under complex geometric structures, establishes the model reliability criteria, and provides high-confidence data support for process optimization. Attached Figure Description

[0039] To make the simulation method for curing deformation of large-size composite reinforced wall panels of the present invention more obvious and understandable, the drawings used in the specific embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating the method described in this application;

[0041] Figure 2 This diagram illustrates the mesh construction effect on the corresponding connecting surfaces of the strut membrane surface and the wall panel membrane surface.

[0042] Figure 3 This represents the generated effect of a 3D solid element;

[0043] Figure 4 A schematic diagram showing the basic orientation of each entity unit in the global coordinate system;

[0044] Figure 5 A schematic diagram showing the solidification deformation field;

[0045] Figure 6 This diagram illustrates the comparison of curing deformation at a series of identical characteristic locations between simulation and experimental results. Detailed Implementation

[0046] Example 1:

[0047] A simulation method for curing deformation of large-size composite reinforced wall panels is provided, the method comprising the following steps:

[0048] Step 1: In the finite element preprocessing software, the geometric model of the large-size composite stiffened panel is simplified. Two-dimensional meshes are generated for the membrane surfaces of the stringers and panels, and common nodes are processed for the connecting surfaces. Based on the two-dimensional mesh, a solid mesh is generated with reference to the actual layup conditions. In the finite element simulation software, the solid mesh is divided into layups, and each mesh is assigned a layup direction, forming a finite element mesh system that supports coupled analysis of composite material temperature, curing, and stress-deformation.

[0049] Step 2: Set process boundary conditions and analysis steps in the finite element mesh system, and introduce user subroutines for calculating composite material temperature, curing and stress deformation. In the subroutines, the influence of the panel opening process is considered in advance to form a numerical model that simulates the internal stress accumulation during the curing process of the composite material reinforced panel and the internal stress release after curing, resulting in curing deformation. Then, simulation calculations are performed.

[0050] Step 3: Post-process the simulation model, extract the coordinate data of relevant nodes on the outer surface of the wall panel before and after curing, align the two sets of data to obtain the deformation of the outer surface of the wall panel after curing. Compare the simulation results with the actual experimental results to verify the accuracy of the simulation model.

[0051] The construction process of the finite element mesh system in step one specifically includes the following steps:

[0052] The geometric model of large-size composite stiffened wall panels is simplified by converting rounded transitions in the model into right-angle transitions and removing all dividing lines on the model surface, retaining only the outline.

[0053] The simplified stringer model's film-coating surface is divided into regular rectangular two-dimensional meshes. These meshes are then mapped onto the film-coating surface of the wall panel, forming the mesh on the connection surface between the wall panel and the stringer. Shared nodes are then applied to the mesh nodes on the contact surface between the stringer and the wall panel. The remaining portion of the wall panel's film-coating surface is filled with a regular rectangular mesh.

[0054] For the 2D mesh of the stringer membrane surface, generate 3D solid elements using the offset method, with the number of element layers equal to the number of plies in the stringer. For the 2D mesh of the wall panel membrane surface, generate 3D solid elements from the bottom up, with the number of element layers equal to the number of plies at the position with the maximum number of layers. Organize the numbering of all solid elements to ensure that all solid mesh numbers representing each ply are consecutive.

[0055] The 3D solid elements are imported into the finite element simulation software ABAQUS. A script is used to retrieve the element numbers for each layer of the girder and siding, and the solid elements are grouped according to the actual ply information, recorded in the element grouping. Since the siding and girder have complex geometries, the script automatically calculates the base orientation of each solid element within each layer and records it in the discrete field. Using ABAQUS's orientation setting function, the actual orientation of each element is set based on its base orientation and ply angle.

[0056] In step two, the impact of the panel perforation process is considered in advance. This is achieved by adjusting the elastic modulus of the material in the perforation area within the UMAT subroutine while the resin is in a viscoelastic state before the curing reaction is complete. In actual operation, the perforation process occurs after the curing process and before the residual stress is released. Therefore, at the corresponding moment in the simulation, the elastic modulus of the material in the perforation area is changed from a normal value to a small value close to 0, ensuring that the perforation area does not affect the deformation of other areas during the internal stress release process.

[0057] The post-processing and model validation process in step three specifically includes the following steps:

[0058] The script extracts the coordinate data of nodes on the outer surface of the wall panel in the original model before curing, and then extracts the coordinate data of the same nodes on the outer surface of the wall panel in the model obtained after simulation calculation after curing deformation. During the extraction process, nodes in the opening area are filtered by the script to simulate the surface shape of the wall panel after opening in reality.

[0059] To eliminate the influence of inertial offset caused by residual stress release on the node coordinates, a best-fit alignment algorithm was used to align the cured and deformed nodes with the uncured nodes using the two sets of extracted coordinate data. The change in the node coordinates in the Z direction after curing and deformation compared to before curing was calculated and recorded as the curing deformation amount on the outer surface of the panel.

[0060] For the actual test specimen, a laser scanner was used to record the node coordinate data on the outer surface of the wall panel before and after curing deformation. The same best-fit alignment algorithm was used to align the nodes after curing deformation to the nodes before curing, and the amount of curing deformation on the outer surface of the wall panel was calculated. The accuracy of the simulation model was quantitatively verified by comparing the curing deformation amounts at a series of identical feature locations with the simulation results.

[0061] Example 2:

[0062] Based on the aforementioned embodiments, the working mechanism of the simulation method for curing deformation of large-size composite reinforced wall panels is further explained.

[0063] The method flow is as follows: Figure 1 As shown, the curing deformation prediction applied to 3*1 meter composite reinforced wall panels specifically includes the following steps:

[0064] The digital model of the stiffened panel was imported into the finite element preprocessing software. All dividing lines on the panel surface were removed, while the outline of the panel model was retained to maintain the variable thickness characteristics of the panel. Due to the more complex geometry of the stringer, all surfaces of the stringer except the film-coated surface were removed, and all rounded transitions on the film-coated surface were simplified to right-angle transitions.

[0065] The simplified girder model's membrane surface is divided into regular rectangular 2D meshes. These meshes are then mapped onto the wall panel's membrane surface, forming the meshes on the connection surfaces between the wall panel and the girder. Shared nodes are treated for the mesh nodes on the contact surfaces of the girder and wall panel. Meshes are created for the eight girder membrane surfaces, and corresponding meshes are created on the connection surfaces of the wall panel membrane surfaces, resulting in the following construction effect: Figure 2 As shown. Fill the remaining portion of the wall panel film surface with a neat rectangular grid.

[0066] For the 2D mesh of the stringer membrane surface, 3D solid elements are generated using the offset method based on the actual number of layers for each stringer. The number of layers in each element ranges from 14 to 34, corresponding to a thickness of 2.61 to 6.35 mm. For the 2D mesh of the wall panel membrane surface, 3D solid elements are generated from the bottom up based on the maximum number of layers in the wall panel. The number of layers in each element ranges from 93, with a thickness of 6.13 to 17.35 mm. The numbering of all solid elements is then organized to ensure that all solid mesh numbers representing each layer are consecutive. The effect after generating the 3D solid elements is as follows. Figure 3 As shown.

[0067] Import the 3D solid elements into the finite element simulation software ABAQUS. Use a script to retrieve the element numbers for each layer of the girder and siding, and group the solid elements according to the actual ply information, recording the groupings. Since the siding and girder have complex geometries, the script automatically calculates the base orientation of each solid element in each layer in the global coordinate system. The determination method is as follows: Figure 4 As shown, the X-direction of the basic orientation is represented by a vector formed by the centroids of the surfaces determined by the nodes numbered 2, 3, 6, and 7 in each element. Similarly, the Y-direction of the basic orientation is represented by a vector formed by the centroids of the surfaces determined by the nodes numbered 3, 4, 7, and 8 in each element. Both vectors are recorded in the discrete field. Using the orientation setting function of the ABAQUS software, the actual orientation of each element is set based on its basic orientation and ply angle.

[0068] In the finite element mesh system, process boundary conditions and analysis steps were set, with the initial degree of curing set to a small value approaching 0 and the initial temperature set to 20 degrees Celsius. The simulation task was divided into two analysis steps. The first step was a temperature and displacement coupled analysis step, fixing the outer surface of the panel and applying the curing process temperature curve to simulate the internal stress accumulation during the panel's curing process. The second step was a static and general analysis step, keeping only two nodes fixed and removing other fixed boundary conditions to simulate the curing deformation caused by the release of internal stress in the panel. Five subroutines—HETVAL, USDFLD, DISP, UMAT, and UEXPAN—were introduced to support coupled simulation calculations of temperature, curing, and stress-deformation of the composite material. In the UMAT subroutine, nodes within the opening region were identified and marked using spatial coordinates. After the first analysis step and before the second analysis step began, the elastic modulus of the material in the opening region was changed from a normal value to a small value approaching 0 to ensure that the opening region would not affect the deformation of other regions during the release of internal stress. Simulation calculations were performed based on the above settings.

[0069] The script extracts the coordinate data of nodes on the outer surface of the wall panel in the original model before curing. The node coordinates on the outer surface are determined by the coordinates of nodes numbered 5, 6, 7, and 8 on the outermost solid element of the finite element model. The node positions are determined by... Figure 3 As shown. The same method was used to extract the coordinate data of the same nodes on the outer surface of the wall panel after solidification deformation in the model obtained after simulation calculation. During the extraction process, the nodes in the opening area were filtered by the script to simulate the surface shape of the wall panel after opening in reality.

[0070] For the two sets of extracted coordinate data, the best-fit alignment algorithm is used to align the nodes after curing deformation to the nodes before curing, so as to eliminate the influence of inertial offset caused by residual stress release on the node coordinates. The change in node coordinates in the Z direction after curing deformation compared with before curing is calculated and recorded as the curing deformation amount of the outer surface of the panel, thus obtaining the point cloud data of the XY axis coordinates and the curing deformation amount in the Z direction of the outer surface of the panel in the simulation.

[0071] For the actual test specimen, a laser scanner was used to record the node coordinate data on the outer surface of the wall panel after curing and deformation. The same best-fit alignment algorithm was used to align the cured and deformed nodes to the uncured nodes, and the curing deformation amount on the outer surface of the wall panel was calculated, obtaining point cloud data of the XY-axis coordinates and Z-direction curing deformation amount on the outer surface of the wall panel during the experiment. Interpolation and smoothing were performed on the point cloud data obtained from both the simulation and experiment, resulting in the curing deformation field as shown below. Figure 5 As shown. The simulation results and experimental results were compared at a series of identical feature locations to quantitatively verify the accuracy of the simulation model. The results are as follows. Figure 6 As shown in the figure. The results demonstrate that the accuracy of the finite element model established using this method can be verified by experimental results.

[0072] This invention establishes a finite element mesh system that supports coupled analysis of temperature, curing, and stress-deformation of composite materials by co-designing simulation preprocessing, solving, and post-processing methods. It extends the coupled analysis method to the curing deformation simulation of large-size stiffened panels with complex geometric features such as curvature and varying thickness. By extracting and processing the deformation data of the outer surface of the panel in the simulation model, the accuracy of the model is quantitatively verified based on experimental results, proving that the method is suitable for predicting the curing deformation of large-size stiffened panels.

[0073] Example 3:

[0074] Building upon the aforementioned embodiments, a curing degree feedback mechanism is introduced into the user subroutine to achieve real-time dynamic correction of the elastic modulus of the pore region. Traditional methods only statically correct the elastic modulus during the stress release stage, while this method adjusts the elastic modulus correction coefficient in real time based on the evolution of local curing degree, more accurately simulating the time-varying impact of the pore-opening process on material properties. Its core lies in establishing a functional relationship between the elastic modulus and the curing degree, dynamically adjusting the elastic modulus by calculating the local curing degree in real time, thereby more realistically reflecting the degradation of mechanical properties in the pore region during the curing process.

[0075] In finite element simulation, the curing degree data of each integration point in the opening area is collected in real time through a user subroutine.

[0076] The formula for correcting the elastic modulus is:

[0077]

[0078] In the formula, This is the corrected elastic modulus; This is the initial elastic modulus of the material; Real-time curing degree; This is the curing degree threshold, which is typically 0.6.

[0079] When the degree of curing exceeds the threshold, the elastic modulus of the pore area is dynamically calculated and updated according to the formula.

[0080] During the stress release phase, the elastic modulus is further adjusted to the stress isolation threshold based on the above correction results to ensure that the opening area does not affect the overall deformation behavior.

[0081] Verification shows that, while achieving a similar average error to the above embodiments, this method reduces the deformation prediction error of the opening area from 15% to less than 5% compared to the traditional static correction method, and improves the overall panel deformation prediction accuracy by approximately 12%. The results demonstrate that this method, by responding in real-time to changes in the local curing state, significantly improves the fidelity of simulating the mechanical behavior of the opening area during the stress release stage. It also significantly improves the accuracy of predicting stress distortion and local deformation introduced by the opening process, resulting in a higher degree of agreement between the simulation results of the overall deformation field and physical experiments. This effectively confirms the core role of this method in isolating manufacturing process interference and improving the reliability of model predictions.

[0082] Example 4:

[0083] Building upon the aforementioned embodiments, this paper optimizes the accuracy of the spatial alignment algorithm when handling complex geometric structures by introducing a local reference frame and a weighted fitting strategy. Traditional best-fit algorithms treat all nodes equally, while this method assigns weights to nodes based on their importance within the geometric structure, prioritizing matching accuracy in high-curvature and key feature regions. Its core lies in calculating weights based on node curvature and prioritizing the matching of high-weight nodes during spatial alignment, thereby more accurately eliminating inertial offset errors.

[0084] The coordinate data of the nodes on the outer surface of the wall panel are extracted, and the local curvature of each node is calculated. .

[0085] The formula for assigning node weights is:

[0086]

[0087] In the formula, Node weights; For node curvature; The maximum curvature among all nodes; This is the baseline weight, typically 0.1.

[0088] Spatial alignment is performed using weighted least squares, and the objective function is optimized as follows:

[0089]

[0090] In the formula, This is the spatial transformation matrix; These are the node coordinates before solidification; These are the node coordinates after solidification.

[0091] The optimal transformation matrix is ​​obtained through iterative calculation, and the normal deformation is extracted as a quantification index.

[0092] Verification shows that, while achieving a similar average error to the aforementioned embodiments, this method reduces the inertial migration error to below 0.1 mm, improving accuracy by approximately 20% compared to traditional algorithms. Simultaneously, the convergence speed of the full-field deformation distribution map is improved by 15%, providing higher-confidence data support for model validation. The results demonstrate that this algorithm effectively addresses the inertial migration error generated by traditional best-fit algorithms in complex surfaces and variable-thickness regions by assigning higher weights to nodes in high-curvature and key feature regions. The extracted normal deformation more purely reflects the intrinsic deformation of the material itself caused by curing shrinkage, rather than spurious signals introduced by numerical calculations. This significantly improves the consistency between simulation and experimental data in spatial comparison, providing a solid and reliable data foundation for accurate model validation.

Claims

1. A method of simulating cure distortion of a large composite stiffened panel, characterized by, The system comprises: a finite element mesh cell system adapted for multi-physics coupling, supporting dynamic coupling analysis of composite temperature field, curing degree field and stress deformation field; a time sequence integrated user subroutine in finite element simulation, which can dynamically regulate material properties and boundary conditions; a deformation quantization algorithm based on spatial matching optimization, which extracts the normal deformation of the outer surface of the wallboard and eliminates inertial offset errors; wherein the deformation quantization algorithm includes filtering the node coordinates of the open hole area, using the best fitting spatial alignment algorithm to eliminate the inertial offset of the curing deformation data, and extracting the normal coordinate change as the deformation quantization index; the model reliability is verified by point cloud data mapping and full-field error distribution analysis; wherein the finite element mesh cell system is adapted to curved surface profile and variable thickness geometric features, and establishes a topological continuity mapping relationship between the stringer and the wallboard.

2. The method of claim 1, wherein: the dynamic coupling analysis of multi-physics coupling is realized by stress evolution simulation in stages, the first analysis step fixes the outer surface of the wallboard and applies temperature load to simulate stress accumulation, and the second analysis step removes the boundary constraint to simulate stress release deformation.

3. The method of claim 1, wherein: the construction of the finite element mesh cell system comprises: mapping the stringer and the wallboard film surface grid to form a common node connection; generating continuous numbered layered solid elements based on actual layup parameters; controlling the automatic orientation of the layup direction through spatial vector relationship.

4. The method of claim 3, wherein: the automatic orientation calculates the basic orientation according to the spatial vector relationship between the solid element centroid and the preset reference point, and gives the actual orientation by combining the layup angle parameter through the orientation function of the finite element software.

5. The method of claim 1, wherein: the user subroutine includes a material property time sequence regulation module, which is used to dynamically calculate and correct the material mechanics property parameters of the specified area based on the local curing state of the composite structure.

6. The method of claim 1, wherein: the deformation quantization algorithm assigns corresponding weights to the nodes participating in spatial alignment according to the spatial distribution of the structure geometric features, and calculates the spatial transformation relationship based on the weights using a weighted optimization algorithm.

7. The method of claim 1, wherein: in the process of verifying the accuracy of the model, the deformation data of simulation and test are compared at the same topological position, and quantitative error convergence analysis is carried out through the full-field deformation distribution map.

8. A system for simulating cure distortion of large composite stiffened panels, comprising: a computer; and a software program stored on the computer and configured to: receive a plurality of input parameters; generate a plurality of output parameters; and output the plurality of output parameters. The system is realized based on the method of any one of claims 1-7, comprising: a geometry processing module for retaining variable thickness profiles and simplifying non-critical features; a mesh coupling module for performing stringer and wallboard film surface grid mapping and layered solid element continuous numbering; a multi-physics solving module for integrating user subroutines to realize time sequence coupling calculation of temperature, curing and stress deformation; a verification analysis module for outputting the deformation comparison results of simulation and test based on the spatial alignment algorithm.

9. The system of claim 8, wherein: The verification analysis module comprises a three-dimensional scanning data interface and an inertial offset correction unit; the spatial alignment algorithm realizes accurate extraction of deformation by optimizing spatial matching relationship of nodes.

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