A method, system and device for optimizing parameters of a honeycomb sandwich paperboard structure

Abstract

The present application relates to the technical field of unmanned aerial vehicle materials, and particularly relates to a method, system and device for optimizing structural parameters of a honeycomb sandwich paperboard, in order to solve the problem of parameter optimization of the honeycomb sandwich paperboard under a set constraint condition, the present application provides a method for optimizing structural parameters of the honeycomb sandwich paperboard, which takes minimizing the weight of the honeycomb sandwich paperboard per unit area as a target, establishes a target function, determines constraint conditions of the target function based on satisfying minimum mechanical parameters and design sizes of the honeycomb sandwich paperboard, and then constructs a structural parameter optimization model of the honeycomb sandwich paperboard, the structural parameter optimization model of the honeycomb sandwich paperboard is solved by an interior point method, and the optimized structural parameters are obtained; under the condition of satisfying the design stiffness constraint condition and the size variable constraint condition of the honeycomb sandwich paperboard, the panel thickness, the honeycomb core layer thickness, the honeycomb wall thickness and the honeycomb cell edge length under the condition of the lightest mass per unit area are obtained, and then the optimization of the unmanned aerial vehicle body structure is satisfied.

Description

Technical Field

[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) materials technology, specifically relating to a method, system, and equipment for optimizing the structural parameters of a honeycomb sandwich cardboard structure. Background Technology

[0002] Low-cost sandwich cardboard material is a novel material for unmanned aerial vehicles (UAVs) developed in response to the ever-increasing demand. Existing research on cardboard-based UAVs is abundant, with relevant flight tests and verification results already available. Compared to traditional UAV materials such as carbon fiber, aerospace aluminum alloy, and engineering plastics, sandwich cardboard material has significant advantages in the field of small and medium-sized consumable UAVs. First, it is inexpensive and can be mass-produced. Cardboard is a general-purpose civilian material with extremely low procurement and molding costs, eliminating the need for specialized precision aerospace manufacturing equipment. This significantly reduces the R&D and mass production costs of UAVs, making it suitable for large-scale deployment and high-frequency wear and tear applications. Second, it exhibits outstanding lightweight characteristics. The high porosity and low density of sandwich cardboard effectively reduce the overall weight of the UAV, decrease flight energy consumption, and improve endurance and flight maneuverability. Third, it has strong deployment adaptability. The cardboard fuselage can adopt a folding, modular assembly structure, resulting in a small storage volume, convenient transportation and storage, high efficiency for rapid field assembly, and excellent emergency deployment capabilities. Fourth, it offers good concealment and safety. The pure paper structure has a small radar cross-section, providing excellent concealment during low-altitude flight. Simultaneously, its lightweight and soft texture reduces the risk of crash damage during test flights and operations, resulting in higher operational safety. Fifth, it is green and biodegradable. The cardboard material is naturally biodegradable, requiring no special recycling after disposal or damage, making it suitable for the application positioning of disposable drones. However, sandwiched cardboard materials also have certain disadvantages in the drone field. One is insufficient mechanical stability. Cardboard has limited tensile, impact, and fatigue resistance, making it prone to cracking and deformation damage when facing high-altitude turbulence, flight bumps, and minor collisions, making it unsuitable for high-speed, long-endurance, and complex airspace flight requirements.

[0003] Low-cost sandwich paperboard is categorized into corrugated paperboard, honeycomb paperboard, and foam paperboard based on its core structure and materials. The application of honeycomb paperboard in drone manufacturing is becoming increasingly widespread. The airframe structure of a honeycomb paperboard drone is its skeleton, and the materials used in the airframe largely determine the drone's operating time and lifespan. Simultaneously, the mechanical properties of the selected materials significantly influence the structure's load-bearing capacity, thus affecting the drone's flight performance. Therefore, in the complex structural design of drones, redundancy in the use of honeycomb paperboard and structural design can increase the overall weight, shorten flight range, reduce thrust-to-weight ratio and flight stability, increase structural dynamic loads and exacerbate the risk of delamination and cracking, reduce mission payload capacity, and drive up manufacturing costs, directly negating the core advantages of lightweight and low-cost paperboard drones. Therefore, it is necessary to further improve the lightweight design of the airframe structure, using as much lightweight honeycomb paperboard as possible while meeting certain design conditions. Summary of the Invention

[0004] To address the problem in the prior art that requires optimizing the parameters of honeycomb sandwich paperboard under set constraints to obtain the optimal solution under those constraints, the present invention aims to provide a method, system, and device for optimizing the structural parameters of honeycomb sandwich paperboard. Specifically, through this optimization method, under the constraints of design stiffness and dimensional variables of honeycomb sandwich paperboard, the panel thickness, honeycomb core layer thickness, honeycomb wall thickness, and honeycomb cell side length with the lightest mass per unit area can be obtained, thereby achieving the optimization of the UAV airframe structure.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] The first objective of this invention is to provide a method for optimizing the structural parameters of a honeycomb sandwich paperboard, the optimization method comprising: An objective function is established to minimize the weight of honeycomb sandwich paperboard per unit area. Based on the minimum mechanical parameters and design dimensions of the honeycomb sandwich paperboard, the constraints of the objective function are determined, and then an optimization model for the structural parameters of the honeycomb sandwich paperboard is constructed. The optimized structural parameters of the honeycomb sandwich paperboard are obtained by solving the structural parameter optimization model using the interior point method. These optimized structural parameters are then used to manufacture the optimized honeycomb sandwich paperboard.

[0007] Furthermore, the objective function expression is: ; in, The weight per unit area of ​​honeycomb sandwich paperboard; For panel thickness; The thickness of the honeycomb core layer; The thickness of the honeycomb wall; The side length of the cell; The areal density of the colloid; This refers to the density of the honeycomb core layer.

[0008] Furthermore, the constraints of the objective function include a first constraint and a second constraint, wherein the first constraint includes bending stiffness and torsional stiffness, and the second constraint is a dimensional constraint.

[0009] Furthermore, the formula and constraint conditions for calculating the bending stiffness are as follows: ; in, The bending stiffness of the honeycomb sandwich paperboard. The elastic modulus of the panel material of the honeycomb sandwich paperboard. The minimum bending stiffness of the designed honeycomb sandwich paperboard.

[0010] Furthermore, the formula and constraint conditions for calculating the torsional stiffness are as follows: ; in, The torsional stiffness of the honeycomb sandwich paperboard. This refers to the shear modulus of the panel material of the honeycomb sandwich paperboard. This is the minimum torsional stiffness of the designed honeycomb sandwich paperboard.

[0011] A second objective of this invention is to provide an optimization system for the structural parameters of honeycomb sandwich paperboard, the optimization system being implemented based on the optimization method for the structural parameters of the honeycomb sandwich paperboard, the optimization system comprising: The objective function building module is used to establish an objective function with the goal of minimizing the weight of honeycomb sandwich paperboard per unit area. The optimization model building module determines the constraints of the objective function based on the minimum mechanical parameters and design dimensions that satisfy the honeycomb sandwich paperboard, and then constructs an optimization model for the structural parameters of the honeycomb sandwich paperboard. The output module is used to solve the structural parameter optimization model of the honeycomb sandwich paperboard using the interior point method to obtain the optimized structural parameters, which are then used to manufacture the optimized honeycomb sandwich paperboard.

[0012] A third objective of the present invention is to provide an electronic device for optimizing the structural parameters of a honeycomb sandwich paperboard, the device comprising: at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that are executed by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform a method for optimizing the structural parameters of the honeycomb sandwich paperboard.

[0013] The beneficial effects of this invention are: This invention discloses a method, system, and device for optimizing the structural parameters of honeycomb sandwich paperboard. Compared with the prior art, the improvement of this invention lies in: (1) This invention optimizes parameters such as panel thickness, core layer thickness, wall thickness, and cell side length of the honeycomb sandwich paperboard to maximize the lightness of the prepared honeycomb sandwich paperboard while meeting the design mechanical performance requirements. That is, under the same stiffness requirements, a thinner panel, a lighter core material, and a more reasonable combination of honeycomb cell structures can replace solid boards or overly conservative sandwich boards, thereby reducing the surface density of components such as the UAV fuselage shell, canopy, fairing, wing rib skin, and equipment bay partition. After the mass of the airframe structure is reduced, the cruise power consumption is reduced under the same battery and power system, or the saved mass can be converted into spare capacity for batteries, payloads, sensors, or communication equipment. Long-endurance UAVs especially rely on lightweight structures, and their high aspect ratio wings and large-area skins have a significant impact on the mass of the airframe. Meeting the design stiffness requirements helps to reduce skin dents, local bulges, and deformation under load, thereby maintaining the airfoil, fuselage shape, and control surface clearance, which helps with flight drag, attitude stability, and control accuracy.

[0014] (2) The method of this invention outputs parameters such as thickness, wall thickness, and side length, rather than complex free-form topology, making it easier to integrate with the cardboard supply chain, die-cutting process, gluing process, and batch inspection. For commercial drones, structural solutions must not only be lightweight but also inexpensive, replicable, and maintainable, which is more important than simply pursuing optimal simulation. Furthermore, the method of this invention can be embedded into a larger drone design process: the outer layer provides the fuselage load, aerodynamic shape, equipment layout, and safety factor, while the inner layer quickly outputs the parameters of the honeycomb sandwich cardboard. In this way, it can become a "lightweight panel parameter generator," serving for overall machine weight estimation, stiffness verification, and cost assessment. Attached Figure Description

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a flowchart of the optimization method provided in Embodiment 1 of the present invention; Figure 2 This is the original honeycomb sandwich cardboard model grid division diagram provided in Embodiment 2 of the present invention; Figure 3 This is the optimized honeycomb sandwich paperboard model mesh division diagram provided in Embodiment 2 of the present invention; Figure 4 This is a diagram showing the loading constraint conditions of the finite element model of the honeycomb sandwich paperboard provided in Embodiment 2 of the present invention; Figure 5This is the load definition diagram of the finite element model of the honeycomb sandwich paperboard provided in Embodiment 2 of the present invention; Figure 6 This is a parameter configuration displacement diagram of the original honeycomb sandwich paperboard under bending load provided in Embodiment 2 of the present invention; Figure 7 This is the optimized honeycomb sandwich paperboard parameter configuration displacement diagram under bending load provided in Embodiment 2 of the present invention; Figure 8 This is a structural parameter configuration displacement diagram of the original honeycomb sandwich paperboard structure under bending and torsional loads provided in Embodiment 2 of the present invention; Figure 9 This is the configuration displacement diagram of optimized honeycomb sandwich paperboard structure parameters under bending and torsional loads provided in Embodiment 2 of the present invention. Detailed Implementation

[0016] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0017] Example 1: Reference Figure 1 As shown in the figure, an embodiment of the present invention provides a method for optimizing the structural parameters of a honeycomb sandwich paperboard, the optimization method comprising: S1. Establish an objective function with the goal of minimizing the weight of honeycomb sandwich paperboard per unit area.

[0018] Specifically, the unit area can be arbitrarily selected, such as 60mm × 60mm. The process of establishing the objective function includes: S101. Construct a general objective function for minimizing the weight of sandwich paperboard per unit area.

[0019] The general expression for the weight minimization objective function of sandwich paperboard is: Formula (1) in, This refers to the weight of the cardboard layers. The thickness of the cardboard panel. This refers to the core layer thickness of the laminated cardboard. The areal density of the adhesive in the sandwich paperboard. This refers to the core layer density of the sandwich paperboard.

[0020] S102. The core layer density of the honeycomb sandwich paperboard. Substituting into formula (1), we obtain the objective function of the honeycomb sandwich paperboard per unit area, namely formula (2). The objective function aims to minimize the weight of the honeycomb sandwich paperboard per unit area. In the embodiments of this application, the core honeycomb structure of the honeycomb sandwich paperboard is a regular hexagonal honeycomb structure.

[0021] The objective function expression is: ;Formula (2) in, The weight of the honeycomb sandwich cardboard per unit area. For panel thickness, The thickness of the honeycomb core layer. For honeycomb wall thickness, The side length of the cell is the honeycomb cell. The surface density of the colloid. This refers to the density of the honeycomb core layer.

[0022] Core layer density of honeycomb sandwich paperboard The expression is: ;Formula (3) S2. Determine the structural parameters to be optimized for the honeycomb sandwich paperboard.

[0023] Specifically, in the embodiments of this application, the structural parameters to be optimized for the honeycomb sandwich paperboard include: individual panel thickness, honeycomb core layer thickness, honeycomb wall thickness, and honeycomb cell side length. That is, the corresponding honeycomb sandwich paperboard can be manufactured using the above parameters.

[0024] S3. Based on the minimum mechanical parameters and design dimensions of the honeycomb sandwich paperboard, determine the constraints of the objective function, and then construct an optimization model for the structural parameters of the honeycomb sandwich paperboard.

[0025] Specifically, the mechanical parameters of the honeycomb sandwich paperboard are bending stiffness and torsional stiffness. The constraints include a first constraint and a second constraint. The first constraint includes bending stiffness and torsional stiffness, while the second constraint is a dimensional constraint. The first constraint is a mechanical performance constraint on the honeycomb sandwich paperboard, ensuring that the honeycomb sandwich paperboard produced based on the optimized parameters meets the preset mechanical properties, i.e., meets the mechanical requirements of UAV materials. The second constraint is a dimensional constraint on the honeycomb sandwich paperboard structure per unit area, ensuring that the honeycomb sandwich paperboard produced based on the optimized parameters achieves optimal dimensions while meeting the preset mechanical properties. The dimensions of the honeycomb sandwich paperboard structure are: individual panel thickness, honeycomb core layer thickness, honeycomb wall thickness, and honeycomb cell side length.

[0026] The specific steps for constructing the optimization model for the structural parameters of honeycomb sandwich cardboard are as follows:

[0027] Where X is a 4-dimensional column vector of the dimensions of the honeycomb sandwich cardboard, and T is the matrix transpose; To minimize the weight of honeycomb sandwich paperboard, The bending stiffness of the honeycomb sandwich paperboard. The elastic modulus of the panel material of the honeycomb sandwich paperboard. To determine the minimum bending stiffness of the designed honeycomb sandwich paperboard, The torsional stiffness of the honeycomb sandwich paperboard. This refers to the shear modulus of the panel material of the honeycomb sandwich paperboard. To determine the minimum torsional stiffness of the designed honeycomb sandwich paperboard, The minimum panel thickness for the designed honeycomb sandwich cardboard. The maximum panel thickness of the designed honeycomb sandwich cardboard, The minimum honeycomb core layer thickness for the designed honeycomb sandwich paperboard. The maximum honeycomb core layer thickness of the designed honeycomb sandwich paperboard. The minimum cell side length for the designed honeycomb sandwich paperboard. The maximum cell side length of the designed honeycomb sandwich paperboard. The minimum honeycomb wall thickness for the designed honeycomb sandwich paperboard. The maximum cell wall thickness of the designed cell sandwich paperboard is defined by find, min means to minimize, and st is an abbreviation for subjectto, which represents all the constraints that the variable must satisfy.

[0028] S4. Based on the weight target, the structural parameters to be optimized, and the constraints, the optimized structural parameters of the honeycomb sandwich paperboard are obtained by solving the internal point method.

[0029] In this embodiment, the interior-point method is a numerical optimization algorithm for solving constrained optimization problems. Its core idea is to search within the feasible region, selecting an initial point and iteratively approximating the optimal solution. The interior-point method is particularly suitable for large-scale convex optimization problems and nonlinear optimization problems. The mathematical principle of the interior-point method is to introduce a barrier function to transform the constrained optimization problem into an unconstrained optimization problem. That is, the optimization function is transformed into the superposition of the objective function and the barrier function, and a positive barrier parameter is introduced. As the barrier parameter decreases continuously during the iteration process, the central path for the objective function to form the optimal solution is obtained. When the barrier parameter decreases to near zero, the optimization function approximates the objective function, and the obtained solution approximates the optimal solution. This application uses the interior-point method to solve for the optimal parameters in the lightweight design of honeycomb sandwich paperboard. Specifically, the interior-point method is used to solve the objective function based on satisfying the constraints, ultimately obtaining the optimized structural parameters. These optimized structural parameters can then be used to manufacture the corresponding honeycomb sandwich paperboard, which meets the mechanical performance and weight requirements for UAV manufacturing materials.

[0030] Example 2: This embodiment performs performance analysis on the optimized honeycomb sandwich paperboard obtained by the method of Embodiment 1 and the original honeycomb sandwich paperboard (the honeycomb sandwich paperboard before optimization), respectively, to further verify the effectiveness of the optimization method of Embodiment 1.

[0031] Specifically, in this embodiment, bending and torsional loads were applied to the optimized honeycomb sandwich paperboard and the original honeycomb sandwich paperboard using ABAQUS finite element software to verify the mechanical properties of the optimized honeycomb sandwich paperboard before and after optimization. Figures 2 to 9 As shown.

[0032] (1) First, establish an optimized honeycomb sandwich paperboard model and an original honeycomb sandwich paperboard model of the same size, and import the two models into ABAQUS software.

[0033] Specifically, both the optimized honeycomb sandwich paperboard model and the original honeycomb sandwich paperboard model were refined 3D models with dimensions of 40mm × 40mm. The material properties of the original honeycomb sandwich paperboard model were assigned using the material parameters of the original paper in Table 1, while the material properties of the optimized honeycomb sandwich paperboard model were assigned using the material parameters of the optimized honeycomb sandwich paperboard in Table 2. In ABAQUS software, when assigning material properties and meshing the honeycomb sandwich paperboard structure, to make the simulation results more accurate, twice the thickness of the honeycomb cell wall was used as the global mesh size, and eight-node linear hexahedral elements and reduced integral (C3D8R) were selected as the global mesh type. Figure 2 This is the mesh generation diagram for the original honeycomb sandwich cardboard model. Figure 3 To optimize the mesh generation diagram of the honeycomb sandwich cardboard model.

[0034] Table 1. Material parameters of the original honeycomb sandwich paperboard

[0035] Table 2 Optimized honeycomb sandwich paperboard material parameters

[0036] (2) Determine the application point RP in the original honeycomb sandwich paperboard model and the optimized honeycomb sandwich paperboard model respectively.

[0037] Using coupling constraints, the sides of the original and optimized cellular sandwich paperboard models are coupled to point RP at the center of the side, which serves as the application point for subsequent bending moment loads. Furthermore, binding constraints are created between the upper and lower layers of the cellular structure of the original and optimized cellular sandwich paperboard models and the core layer, respectively. Figure 4 Figure showing the loading constraint conditions for the finite element model of the honeycomb sandwich cardboard; Figure 5 Define the load for the finite element model of the honeycomb sandwich cardboard.

[0038] (3) Apply bending and torsional loads at the RP point in the original honeycomb sandwich paperboard model and the optimized honeycomb sandwich paperboard model respectively.

[0039] Specifically, at point RP in both the original and optimized honeycomb sandwich paperboard models, a force of 1 along the negative x-axis is applied. The bending load and 0.5 along the negative y-axis direction. To better compare the bending and torsional resistance of the simulation results, bending and torsional loads were applied stepwise using STEP-1 and STEP-2 respectively. After checking the constraints, loading conditions, and output variables, the deformation of the two structural parameters was calculated, followed by post-processing analysis. After 15 incremental steps of calculation convergence, the simulation results of the original and optimized honeycomb sandwich paperboard models under bending and torsional loads were obtained, and displacement and stress contour plots of the original and optimized honeycomb sandwich paperboards were obtained.

[0040] Since the bending load is applied in the negative x-axis direction, the structure can be considered to be subjected to an upward load in the positive z-axis direction. Therefore, the simulation results of the displacement along the U3 direction of the loaded end face along the z-axis are obtained, such as... Figures 6-7 As shown, this is a displacement diagram of the parameter configuration of the original and optimized honeycomb sandwich paperboard under bending load. Figure 6 This is a diagram showing the parameter configuration displacement of the original honeycomb sandwich paperboard under bending load. Figure 7 Optimize the configuration displacement diagram of honeycomb sandwich paperboard parameters under bending load. Figures 6-7 It can be seen that the maximum displacement in the U3 direction of the original honeycomb sandwich paperboard and the refined model established by optimizing the structural parameters of the honeycomb sandwich paperboard are 2.26 mm and 1.53 mm, respectively, under bending load.

[0041] like Figures 8-9 The figure shows the configuration displacement diagrams of the original and optimized honeycomb sandwich paperboard under bending and torsional loads. Figure 8 This is a configuration displacement diagram of the original honeycomb sandwich cardboard structure under bending and torsional loads. Figure 9 Optimize the configuration displacement diagram of honeycomb sandwich cardboard structure parameters under bending and torsional loads. Figures 8-9 It can be seen that the deformations of the original honeycomb sandwich paperboard and the refined model established by optimizing the structural parameters of the honeycomb sandwich paperboard in the U3 direction under bending load are 2.98 mm and 2.65 mm, respectively.

[0042] The optimization results show that under bending loads, the optimized honeycomb sandwich paperboard reduces deformation by 47.7% compared to the original honeycomb sandwich paperboard, and reduces deformation by 16.4% under bending and torsional loading, significantly improving the stiffness of the optimized honeycomb sandwich paperboard. This has been applied to the fuselage of a drone with a fuselage area of ​​0.32m². 2 The weight of the drone using the original honeycomb sandwich cardboard was calculated to be 188.16g, while the weight using the optimized honeycomb sandwich cardboard was 159.68g. The weight of the drone body after optimization was reduced by 15.1% compared to before optimization.

[0043] It should be understood that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Those skilled in the art can modify the technical solutions described in the above embodiments, or make equivalent substitutions for some of the technical features; and all such modifications and substitutions should fall within the protection scope of the appended claims of the present invention.

Claims

1. A method for optimizing the structural parameters of a honeycomb sandwich paperboard, characterized in that, The optimization method includes: An objective function is established to minimize the weight of honeycomb sandwich paperboard per unit area. Based on the minimum mechanical parameters and design dimensions of the honeycomb sandwich paperboard, the constraints of the objective function are determined, and then an optimization model for the structural parameters of the honeycomb sandwich paperboard is constructed. The optimized structural parameters of the honeycomb sandwich paperboard are obtained by solving the structural parameter optimization model using the interior point method. These optimized structural parameters are then used to manufacture the optimized honeycomb sandwich paperboard.

2. The method for optimizing the structural parameters of a honeycomb sandwich paperboard according to claim 1, characterized in that, The objective function expression is: ； in, This refers to the weight of the honeycomb sandwich paperboard per unit area. For panel thickness, The thickness of the honeycomb core layer. For honeycomb wall thickness, The side length of the cell is _____. The surface density of the colloid. This refers to the density of the honeycomb core layer.

3. The method for optimizing the structural parameters of a honeycomb sandwich paperboard according to claim 2, characterized in that, The constraints of the objective function include a first constraint and a second constraint, wherein the first constraint includes bending stiffness and torsional stiffness, and the second constraint is a dimensional constraint.

4. The method for optimizing the structural parameters of a honeycomb sandwich paperboard according to claim 3, characterized in that, The formula and constraints for calculating the bending stiffness are as follows: ； in, The bending stiffness of the honeycomb sandwich paperboard. The elastic modulus of the panel material of the honeycomb sandwich paperboard. The minimum bending stiffness of the designed honeycomb sandwich paperboard.

5. The method for optimizing the structural parameters of a honeycomb sandwich paperboard according to claim 4, characterized in that, The formula and constraints for calculating the torsional stiffness are as follows: ； in, The torsional stiffness of the honeycomb sandwich paperboard. This refers to the shear modulus of the panel material of the honeycomb sandwich paperboard. This is the minimum torsional stiffness of the designed honeycomb sandwich paperboard.

6. A system for optimizing the structural parameters of a honeycomb sandwich paperboard, said optimization system being implemented based on the optimization method for the structural parameters of a honeycomb sandwich paperboard according to any one of claims 1-5, characterized in that, The optimization system includes: The objective function building module is used to establish an objective function with the goal of minimizing the weight of honeycomb sandwich paperboard per unit area. The optimization model building module determines the constraints of the objective function based on the minimum mechanical parameters and design dimensions that satisfy the honeycomb sandwich paperboard, and then constructs an optimization model for the structural parameters of the honeycomb sandwich paperboard. The output module is used to solve the structural parameter optimization model of the honeycomb sandwich paperboard using the interior point method to obtain the optimized structural parameters, which are then used to manufacture the optimized honeycomb sandwich paperboard.

7. An electronic device for optimizing the structural parameters of a honeycomb sandwich cardboard structure, characterized in that, The device includes: At least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

Images