Composite material L-shaped beam lightweight design method based on Double-Double layering mode

Abstract

The invention belongs to the technical field of composite material weight reduction optimization design, and discloses a composite material L-shaped beam lightweight design method based on a Double-Double layering mode. The method solves the problem of low search efficiency when a heuristic algorithm is adopted to carry out structure optimization in the design of the discrete layering sequence of the variable-thickness structure in the traditional carbon fiber reinforced resin matrix composite material technology. Once the sub-ply of the DD ply composite material structure is determined, only the number of times of repetition of the sub-ply needs to be changed, so that the problems of internal layer loss and symmetry do not need to be considered, the number missing condition is greatly reduced, and the optimization efficiency of the optimization search algorithm is remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of weight reduction optimization design of composite materials in aerospace manufacturing, and specifically relates to a lightweight design method for a composite L-beam based on a Double-Double laying method. Background Art

[0002] In the fields of aerospace, lightweight design is an important method to reduce costs in the structural design process. At present, carbon fiber reinforced resin-based composite materials are widely used in aircraft manufacturing due to their high specific strength, high specific stiffness, and strong corrosion resistance. For large aircraft, the overall fuselage, wall panels and other structural parts must be designed with variable thickness and lightweight according to the overall weight reduction and structural aerodynamic requirements. However, since the traditional carbon fiber reinforced resin-based composite material laying method is limited to the constraints of four angles of 0°, ±45°, and 90°, the heuristic algorithm used for structural optimization in the design of discrete laying sequences of variable thickness structures will result in low search efficiency.

[0003] In order to break through the limitation of fiber angle on the performance of composite materials, Tsai proposed a new composite material laying method: Double-Double (DD). The DD laying method is in the form of [±Φ / ±Ψ] rT , where r represents the number of sub-ply repetitions, and the values ​​of Φ and Ψ range from 90°–90°. DD-ply composite structures do not require constraints such as mid-plane symmetry and four angle restrictions, and have the advantage of homogenization. Therefore, the search efficiency is higher when using heuristic algorithms for lightweight structural layer drop design, and it can show great application potential. However, the research on lightweight design of DD-ply composite structures using heuristic algorithms is still in its infancy. The invention patent with patent number CN117910323A involves a variable thickness optimization method for C-beams of DD-ply composite materials. This method uses an exhaustive method to obtain all feasible solutions in the feasible domain. This method has good optimization results, but low search efficiency.

[0004] Therefore, the present invention performs lightweight design on DD laminated composite material structural parts and proposes a lightweight design method for L-shaped beams of DD laminated composite materials. Under the premise of ensuring the design requirements such as stiffness and strength, the volumetric load-bearing efficiency of the composite material structural parts is maximized to achieve the enhanced variable thickness design of the L-shaped beam of DD laminated composite materials. Summary of the invention

[0005] The present invention proposes a lightweight design method for a DD-laminated composite L-shaped beam, which realizes a strengthened variable thickness design of a DD-laminated composite L-shaped beam while ensuring the design requirements of stiffness, strength, etc., with the goal of maximizing the volumetric load-bearing efficiency of composite structural parts.

[0006] In order to achieve the above invention objectives, the technical solutions adopted in this application are as follows:

[0007] A lightweight design method for a composite L-beam based on a Double-Double layup method, the steps of which are as follows:

[0008] Step 1: Determine the initial layup sequence of DD-laminated composite structural parts.

[0009] At present, carbon fiber reinforced resin-based composite structural parts generally adopt the traditional layup method, that is, the four angles of 0°, ±45°, and 90° are designed according to specific rules. For composite structural parts with known traditional layup sequences, the layup sequence must first be converted into DD layup. The conversion process is as follows:

[0010] First, the components of the in-plane stiffness matrix [A] for the conventionally laid composite laminate are calculated using the following equations:

[0011]

[0012] In the formula, Q ij is the eccentric stiffness, and U1, U2 and U3 are stiffness invariants.

[0013] Then, the stiffness components are normalized:

[0014]

[0015] In the formula, h is the thickness of the composite laminate;

[0016] The solution is:

[0017]

[0018] Similarly, for DD laminate composite materials, it can be obtained:

[0019]

[0020] Finally, according to the stiffness matrix coefficient A of the traditional ply and the DD ply 11 Equal, formula (3) and formula (4) are solved together to obtain:

[0021]

[0022] The ply angle of the obtained DD ply composite structure is [Φ / -Ψ / -Φ / Ψ] rT . Approximate values ​​can be obtained for special cases.

[0023] Step 2: Pre-process the composite structure according to the structural characteristics to achieve regional division, and divide the structural parts into i regions. The number of sub-plies of the DD ply in different regions is used as a variable. Limited area division is performed according to the structural characteristics of the composite material, and special areas (such as corners) are divided separately. For structures with high requirements for lightweight design, the number of regional divisions and the number of sub-plies can be extracted as subsequent optimization variables at the same time.

[0024] Step 3: Use parametric modeling to complete the construction of the finite element model of the DD laminate composite structure. Determine the geometry, material properties, laminate angle, boundary conditions, load mode, mesh division, etc., modify and test the script, and complete the finite element simulation.

[0025] The parametric modeling process is as follows: First, a standardized L-beam three-point bending load model is built in the Abaqus / CAE software environment. During the modeling process, the script generated by the pre-processing is saved as an initial Python script named code.py. The script contains all the commands and parameters required to create the model.

[0026] Then, optimize the code.py initial script. Specifically, carefully review each line of code in the script and delete the invalid code that is automatically generated during the graphical interface operation. These invalid codes are usually related to operations such as scaling, rotating, and moving the view, and have no actual contribution to the parametric modeling of the model, so they need to be eliminated.

[0027] After cleaning invalid code, key parameters need to be set in the script, including the number of regions, the number of sub-plies in each region, etc. These parameters should be defined as strings and called directly in the script as keywords. In this way, the modification of key parameters will become easy without having to delve into other parts of the script. The modified script will be saved as a new code.py file for subsequent automated modeling.

[0028] Then, in Abaqus / CAE software, the script is executed through the "run script" function. If errors occur during execution, the erroneous code needs to be tested and corrected to ensure that the script can run smoothly and generate the correct model.

[0029] Finally, a post-processing script needs to be written. The main task of this script is to process and extract the required data and save the data to the specified file. At the same time, the preset variable key parameters need to be stored, and the code.py script file needs to be run to read the data. Through Python processing, Abaqus / CAE is used for pre-processing to generate an inp file. Then, the Abaqus / Standard module is used to solve the model and obtain the ODB file. Finally, the code.py script is used again to process the data in the result file to extract the unit volume bearing capacity of the DD ply structure. These data will lay the foundation for data processing in the subsequent optimization process and ensure the effective implementation of structural optimization and performance analysis.

[0030] Step 4: Considering both mechanical and economic benefits, taking the maximum unit volume bearing capacity as the optimization design goal, and taking the DD homogenization requirements, stiffness and strength requirements as constraints, a mathematical model for lightweight design of DD laminated composite L-beams is constructed.

[0031]

[0032] In the formula, r i represents the number of sub-ply repetitions in the ith region. To meet the homogenization requirements, set the constraint r i ≥4. μ is the bearing capacity per unit volume, F max Indicates the maximum load capacity, V i (r i ) is the volume of the ith block area, F0 is the design bearing capacity, and K0 is the design minimum stiffness. The single-sided layer loss design method is used in the lightweight design process.

[0033] Step 5: In the lightweight design process of DD laminate composite materials, the particle swarm optimization algorithm is used to optimize the number of sub-plies in different areas. This method integrates parametric modeling technology to achieve a more efficient optimization process. Specifically, the optimization process can be described as follows:

[0034] In the initial stage, a series of parameters need to be set, including local and global learning factors, maximum number of iterations, population size, particle speed and position range, etc. By initializing these parameters, the initial population is constructed. Subsequently, a fitness function is defined, using the unit volume carrying capacity as the evaluation criterion to evaluate the performance of each individual. The initial position of each particle is regarded as the individual extreme value, and its fitness value is calculated accordingly.

[0035] During the evaluation process, the global extreme value is selected from many local optimal solutions, which represents the individual with the best performance in the current population. Then, under the constraints of particle update speed and position range, the state of each particle in the population is updated. The update process includes adjusting the speed and position of the particle in order to find a better solution.

[0036] Finally, it is necessary to determine whether the number of iterations has reached the preset maximum value G. If it has, the individual with the best fitness value will be output as the final optimization result. If not, the above evaluation and update steps will be repeated, and the iteration will continue until the preset number of iterations is met. This method can ensure that the optimal performance sub-ply number configuration is found, thereby achieving the lightweight design of DD laminate composite materials.

[0037] Compared with the prior art, the beneficial effects of this application are:

[0038] 1. The present invention adopts a heuristic algorithm based on the DD laying method to achieve lightweight design of composite material structural parts, avoiding the problem of exponential increase and combinatorial explosion in the variable space of the laying order under the traditional four laying angles, and at the same time avoiding problems such as intra-layer interruption and resin aggregation area that occur during the layer dropping design process.

[0039] 2. In the present invention, once the sub-layers of the DD-laminated composite material structure are determined, it is only necessary to change the number of sub-layer repetitions, so there is no need to consider internal layer loss and symmetry problems, which greatly reduces the number of missing conditions and significantly improves the optimization efficiency of the optimization search algorithm.

[0040] 3. The method of the present invention can be widely used in the lightweight design of carbon fiber reinforced resin-based composite material structural parts.

[0041] The present application is further described below in conjunction with the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0043] In the attached picture:

[0044] Figure 1 This is a schematic diagram of the area division of the L-beam lightweight design of the present invention;

[0045] Figure 2 This is a structural diagram of the L-shaped beam before lightweight design optimization of the present invention;

[0046] Figure 3 A schematic diagram of a single-sided layer-dropping lightweight design method of the present invention;

[0047] Figure 4 This is a flow chart of the optimization algorithm for the L-shaped beam of the DD-laminated composite material of the present invention;

[0048] Figure 5 This is a schematic diagram of the optimization results of 12 iterations after the lightweight design optimization of the L-shaped beam of the present invention;

[0049] Figure 6 This is the optimal structural diagram for the lightweight design of the L-beam of the present invention. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0051] The L-shaped beam made of carbon fiber reinforced resin-based composite material is taken as the optimization object, and the lightweight design is completed according to its design requirements.

[0052] Step 1: Determine the initial layup sequence of DD-laminated composite structural parts.

[0053] For known composite structural parts, the traditional layup sequence is [03 / 45 / 902 / -45 / 03] 2s , thickness h = 6mm material properties are shown in Table 1. Substituting into the formula, the DD ply angle is: [0 / -45 / 0 / 45] 10T .

[0054] The calculation results for traditional plies are as follows:

[0055] A 11 =371.59GPa, A 22 =132.76GPa, A 16 =13.27GPa, A 66 =37.97GPa.

[0056] After transformation, DD laminate composite material is obtained [0 / -45 / 0 / 45] 10T The calculation results are compared as follows:

[0057] A 11 =375.36GPa, A 22 =82.25GPa, A 16 =0GPa, A 66 =76.60GPa.

[0058] The two are relatively close, achieving an approximate conversion from traditional ply to DD ply, sacrificing some A during this conversion process. 22 performance value.

[0059] Table 1T800 / AC531 unidirectional prepreg material properties

[0060]

[0061] Step 2: In this embodiment, the L-shaped beam is divided into regions, and n regions are obtained after the division, namely r i =[r1,r2,...,r n ], where i represents the i-th region, r i Indicates the number of sub-ply repetitions in each i-th region.

[0062] Step 3: Use parametric modeling to complete the construction of the finite element model of the DD laminate composite structure. Determine the geometry, material properties, laminate angle, boundary conditions, load mode, mesh division, etc., modify and test the script, and complete the finite element simulation.

[0063] In this example, the model is constructed with the help of ABAQUS software. The geometric shape of the model is an L-shaped beam. Figure 1 The material properties are shown in Table 1 below, and the ply angle is [0 / -45 / 0 / 45] 10T , boundary conditions and loading modes simulate the actual loading form of three-point bending. The redundant useless codes in the script can be deleted, and the obtained codes are tested. After the test is correct, the simulation results under the initial state are obtained.

[0064] The steps of parametric modeling are as follows: (1) Use Abaqus / CAE modeling to establish a standardized L-beam three-point bending load model, and save the script in the pre-processing process as the code.py initial script; (2) Delete the invalid code in the code.py initial script, such as the code generated when operating in the graphical interface to reflect the view scaling, rotation, movement and other operations; (3) Set the key parameters that need to be modified (number of regions, number of sub-ply layers in each region, etc.) as strings in the script as keywords and call it directly to obtain the modified code.py script; (4) Run it in Abaqus / CAE The script function runs the modified code.py script to test and correct the erroneous code; (5) write a post-processing script to extract the required data into the specified file after processing, store the preset variable key parameters and run the code.py script file to read the data, process it with Python, use Abaqus / CAE for pre-processing, obtain the inp file, use Abaqus / Standard to solve and obtain the ODB file, use the code.py script to process and extract the data in the result file to obtain the unit volume bearing capacity of the DD laminate structure, and prepare for the data processing in the subsequent optimization process.

[0065] Step 4: Considering both mechanical and economic benefits, taking the maximum unit volume bearing capacity as the optimization design goal, and taking DD homogenization requirements, stiffness and strength requirements as constraints, a mathematical model for lightweight design of DD laminated composite structural parts is constructed.

[0066]

[0067] In the formula, r i represents the number of sub-ply repetitions in the ith region. To meet the homogenization requirements, set the constraint r i ≥4. μ is the bearing capacity per unit volume, F max Indicates the maximum load capacity, V i (r i ) is the volume of the i-th block area, F0 is the design bearing capacity, and K0 is the design minimum stiffness. The single-sided layer loss design method is used in the lightweight design process, such as Figure 2 shown.

[0068] Step 5: Use the particle swarm optimization algorithm to optimize the number of sub-plies in different areas of the DD laminate composite material, and complete the lightweight design in combination with parameterized modeling. Figure 3 As shown. The optimization process is briefly described as follows: First, initialize the population by setting parameters (such as local and global learning factors, maximum number of iterations, population size, particle speed and position range). Next, use the fitness function (i.e., unit volume carrying capacity) to evaluate each individual, regard the initial position of the particle as the individual extreme value, and calculate its fitness value. Subsequently, select the global extreme value from many local optimal solutions. Under the constraints of particle update speed and position range, use the relevant formula to update the particle state. Finally, determine whether the number of iterations reaches the preset maximum value G. If reached, the individual with the optimal fitness value is output as the final solution; if not, repeat the above evaluation and update steps until the conditions are met.

[0069] According to the constraint optimization conditions, the initial value of the sub-layer repetition number is 10. To ensure the homogenization of the DD layer, its minimum value is set to 4, so the theoretical maximum weight reduction effect is 60%. The particle swarm algorithm is used to generate the number of sub-layer repetitions in different areas. The initial population is set to 20. The load displacement curve of the L-beam is calculated in the imported script to determine whether the required load value and stiffness value meet the design requirements. After iteratively updating the swarm information, the optimization result is obtained after 12 generations. The optimization design process is as follows Figure 4As shown. In order to avoid the situation where a larger value swallows up a smaller value during the unit volume bearing capacity processing, the load is magnified 20 times and then divided by the volume during the data processing, and the result is normalized and compared with the corresponding data of a 40-layer DD-ply composite L-shaped beam with equal thickness. The results are shown in Table 2. The number of plies in each generation area is shown in Table 3. Due to its left-right symmetry, the L-shaped beam only needs to display 16 areas. The schematic diagram of the structure after weight reduction is shown in Figure 6 shown.

[0070] Table 2 Comparison of ultimate load, mass and normalized volume bearing capacity of optimized L-beam

[0071]

[0072] Table 3 Number of plies in each generation area

[0073]

[0074]

[0075] So far, the purpose of the present invention has been achieved.

[0076] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A lightweight design method for composite L-shaped beams based on Double-Double layup, characterized in that: The steps include: Convert the traditional layup sequence of composite L-beam into DD layup sequence; The L-shaped beam after equivalent conversion is divided into regions according to its structural characteristics; The finite element model of the L-shaped beam of DD laminated composite material is constructed by parametric modeling; Taking into account both mechanical and economic benefits, taking the maximum unit volume bearing capacity of the L-beam as the optimization design goal, and taking the DD homogenization requirements, stiffness and strength requirements as constraints, a mathematical model for lightweight design of L-beams with DD laminate composite materials was constructed. According to the above finite element model and mathematical model, the lightweight design optimization of the DD laminate composite L-shaped beam is carried out, and the particle swarm optimization algorithm is used to find the sub-ply number configuration with optimal performance in different areas, so as to realize the lightweight design of the DD laminate composite L-shaped beam.

2. The lightweight design method of composite L-shaped beam based on Double-Double layup method according to claim 1, characterized in that: The equivalent conversion process is as follows: First, the components of the in-plane stiffness matrix [A] for the conventionally laid composite laminate are calculated using the following equations: In the formula, Q ij is the eccentric stiffness, U1, U2 and U3 are stiffness invariants; Then, the stiffness components are normalized: In the formula, h is the thickness of the composite laminate, The solution is: Similarly, for DD laminate composite materials, it can be obtained: Finally, according to the stiffness matrix coefficient A of the traditional ply and the DD ply 11 Equal, formula (3) and formula (4) are solved together to obtain: The ply angle of the obtained DD-ply composite L-beam is [Φ / -Ψ / -Φ / Ψ] rT , approximate values ​​can be obtained for special cases.

3. The lightweight design method of composite L-shaped beam based on Double-Double layup method according to claim 1, characterized in that: According to the structural characteristics of the composite L-beam, a limited area is divided, and the special area is divided separately, a total of i areas are divided, and the number of sub-plies of the DD ply in different areas is used as a variable.

4. The lightweight design method of composite L-shaped beam based on Double-Double layup method according to claim 1, characterized in that: The parametric modeling process is as follows: Firstly, a standardized L-beam three-point bending loading model is constructed in the Abaqus / CAE software environment; During the modeling process, the script generated by the pre-processing is saved as an initial Python script named code.py, which contains all the commands and parameters required to create the model; Then, optimize the code.py initial script; Specifically, it is necessary to carefully review each line of code in the script and delete the invalid codes that are automatically generated during the operation of the graphical interface. These invalid codes are usually related to operations such as scaling, rotating, and moving the view, and have no actual contribution to the parametric modeling of the model, so they need to be eliminated; After cleaning invalid codes, key parameters need to be set in the script, including the number of regions, the number of sub-layers in each region, etc. These parameters should be defined as strings and directly called in the script as keywords. In this way, the modification of key parameters will become simple without going into other parts of the script. The modified script will be saved as a new code.py file for subsequent automated modeling. Then, in Abaqus / CAE software, execute the script through the "run script" function; If an error occurs during execution, the erroneous code needs to be tested and corrected to ensure that the script can run smoothly and generate the correct model; Finally, a post-processing script needs to be written; the main task of this script is to process and extract the required data and save the data to the specified file; at the same time, the preset variable key parameters need to be stored, and the code.py script file needs to be run to read the data; through Python processing, Abaqus / CAE is used for pre-processing to generate an inp file; then, the Abaqus / Standard module is used to solve the model and obtain the ODB file; finally, the code.py script is used again to process the data in the result file to extract the unit volume bearing capacity of the DD ply structure; These data will lay the foundation for data processing in the subsequent optimization process and ensure the effective implementation of structural optimization and performance analysis.

5. The lightweight design method of composite L-shaped beam based on Double-Double layup method according to claim 3, characterized in that: The mathematical model is as follows: In the formula, r i represents the number of sub-ply repetitions in the ith region. To meet the homogenization requirements, set the constraint r i ≥4; μ is the bearing capacity per unit volume, F max Indicates the maximum load capacity, V i (r i ) is the volume of the ith area, F0 is the design bearing capacity, and K0 is the design minimum stiffness.

6. The lightweight design method of composite L-shaped beam based on Double-Double layup method according to claim 5, characterized in that: In the lightweight design process, a single-sided layer-dropping design method is adopted.

7. The lightweight design method of composite L-shaped beam based on Double-Double layup method according to claim 1, characterized in that: The particle swarm optimization algorithm mainly optimizes the number of sub-layers in different areas. The specific process is as follows: In the initial stage, a series of parameters need to be set, including local and global learning factors, maximum number of iterations, population size, particle speed and position range, etc. Through the initialization of these parameters, the initial population is constructed. Then, a fitness function is defined, with the unit volume carrying capacity as the evaluation criterion to evaluate the performance of each individual. The initial position of each particle is regarded as the individual extreme value, and its fitness value is calculated accordingly. During the evaluation process, the global extreme value is selected from many local optimal solutions. This extreme value represents the individual with the best performance in the current population. Then, under the constraints of particle update speed and position range, the state of each particle in the population is updated. The update process includes adjusting the speed and position of the particle in order to find a better solution. Finally, it is necessary to determine whether the number of iterations has reached the preset maximum value G; if it has, the individual with the optimal fitness value will be output as the final optimization result; If not, the above evaluation and update steps will be repeated and iterated continuously until the preset number of iterations is met to ensure that the sub-ply number configuration with the best performance is found.

8. The lightweight design method of composite L-shaped beam based on Double-Double layup method according to claim 3, characterized in that: For structures with high requirements for lightweight design, the number of area divisions and the number of sub-plies can be extracted as subsequent optimization variables at the same time.

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