A method for optimizing the thermal deformation of a carbon fiber parabolic reflector with a honeycomb sandwich structure

Abstract

This invention proposes a method for optimizing the thermal deformation of a carbon fiber parabolic reflector with a honeycomb sandwich structure. The steps are as follows: constructing a reflector model; determining the constraint range of the structural parameters of the reflector model; calculating the root mean square of the thermal deformation of the working surface of the reflector model under high and low temperature conditions; constructing an optimized reflector model and solving it based on the Antlion optimization algorithm. The parameterized model constructed in this invention reduces the time spent on remodeling during the optimization process, thus improving optimization efficiency; solving the reflector optimization model based on the Antlion optimization algorithm to obtain the optimal solution avoids the low optimization accuracy of existing technologies that obtain optimization results by changing a single structural parameter, performing multiple calculations, and then taking the minimum root mean square of thermal deformation, thus improving optimization accuracy; determining the constraint range of the structural parameters of the parameterized reflector model avoids the shortcomings of existing technologies where the optimization variable range is too large and the optimization accuracy is low, thus improving both optimization efficiency and accuracy.

Description

Technical Field

[0001] This invention belongs to the field of aerospace reflector technology and relates to a method for optimizing the thermal deformation of a carbon fiber parabolic reflector with a honeycomb sandwich structure, which can be applied to satellite antennas. Background Technology

[0002] With the continuous development of satellite communication technology, the precision requirements for spaceborne antennas are increasing daily in order to meet the needs of observation in farther and smaller spaces. However, as the demand for antenna precision increases, the aperture of optical telescopes becomes larger and larger, leading to a corresponding increase in size and weight. This results in significant deformation under external loads such as gravity, temperature, and radiation, further complicating the control of surface precision. In recent years, with the continuous development of materials science, carbon fiber composite materials, due to their high specific strength and high specific modulus, have been increasingly used in various aerospace satellites as high-precision antenna structures, particularly in the honeycomb sandwich structure of carbon fiber parabolic reflectors.

[0003] The carbon fiber parabolic reflector with a honeycomb sandwich structure is a high-precision solid-surface reflector. It comprises a honeycomb core composed of multiple honeycomb cells, a skin covering the inner and outer sides of the honeycomb core, and an adhesive film bonding the honeycomb core and the inner and outer skins. The skin material is typically a carbon fiber composite material, and the honeycomb core can be made of aluminum or carbon fiber. To meet the high-precision requirements of spaceborne antennas, researchers have conducted extensive studies on the thermal deformation optimization analysis of carbon fiber parabolic reflectors with a honeycomb sandwich structure.

[0004] The current technical approach for optimizing the thermal deformation of carbon fiber parabolic reflectors with honeycomb sandwich structures involves constructing a reflector model and optimizing its structural parameters to minimize the root mean square (RMS) thermal deformation of the reflector's working surface under high and low temperature conditions. Common methods for constructing the reflector model include directly modeling in finite element analysis (FEM) software or modeling in specialized software and then importing it into FEM analysis software. Subsequent analysis and calculations require meshing the model, setting loads and boundary conditions, and often selecting structural parameters such as the side length and height of the honeycomb core cells, the number of skin layers, and the layup angle as optimization variables. Optimization methods often involve changing a single structural parameter and conducting multiple sets of calculations, using the structural parameter with the optimal RMS thermal deformation as the optimization result. However, each change in structural parameters requires remodeling, resulting in low optimization efficiency. Furthermore, the lack of simultaneous optimization of multiple structural parameters and appropriate constraints on the value range of these variables negatively impacts both optimization accuracy and efficiency. Summary of the Invention

[0005] The purpose of this invention is to overcome the defects of the prior art and propose a method for optimizing the thermal deformation of a carbon fiber parabolic reflector with a honeycomb sandwich structure, which solves the technical problems of low optimization accuracy and efficiency in the prior art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention includes the following steps:

[0007] (1) Constructing a parametric model of the reflector:

[0008] A carbon fiber parabolic honeycomb sandwich structure consisting of an intermediate layer and skins bonded to the inner and outer surfaces of the intermediate layer by an adhesive film is constructed in a spatial rectangular coordinate system O-XYZ. The working surface is then meshed. The structural and mechanical parameters of multiple hexagonal carbon fiber honeycomb core cells that make up the intermediate layer and multiple layers that make up the inner and outer skins, as well as the coordinates of N working surface nodes after meshing, are compiled into an inp file format to form a parametric model of the reflector.

[0009] (2) Determine the constraint range of the structural parameters of the parametric model of the reflector:

[0010] Determine the upper limit of the side length l of the honeycomb core cell in the parametric model of the reflector under pressure P. uper and lower limit l lower The upper limit of height h under gravity conditions uper and lower limit h lower And the angles of the Q plies, ply = [ply1, ply2, ..., ply] q ,…,ply Q ], where ply q Let q be the ply angle of the q-th ply;

[0011] (3) Calculate the root mean square of the thermal deformation of the working surface of the parametric model of the reflector under high and low temperature conditions:

[0012] Calculate at high temperature T h Low temperature is T l Root mean square (RMS) of thermal deformation of the working surface of the parametric model of the reflector under operating conditions h and RMS l ;

[0013] (4) Constructing a reflector optimization model:

[0014] Construct the root mean square (RMS) of the thermal deformation of the working surface of the parametric model of the reflector under high and low temperature conditions. h and RMS l To optimize the objective, a reflector optimization model is developed with the structural parameters of the honeycomb sandwich structure as the optimization variables and the constraint interval determined in step (2) as the condition.

[0015] (5) Obtain the optimization results of the reflector optimization model:

[0016] The reflector optimization model was solved using the antlion optimization algorithm, and the minimum root mean square (RMS) of the thermal deformation of the working surface under high and low temperature conditions was obtained. hu and RMS lu Carbon fiber parabolic reflector.

[0017] Compared with the prior art, the present invention has the following advantages:

[0018] (1) The present invention constructs a parametric model of a reflector, which includes multiple regular hexagonal carbon fiber honeycomb core cells that make up the intermediate layer and multiple layers that make up the inner and outer skins, as well as the coordinates of the working surface nodes after meshing, and compiles them into an inp file format. By changing the input parameters of the inp file, the reflector model with different parameters can be quickly reconstructed, reducing the time for remodeling during the optimization process and effectively improving the optimization efficiency.

[0019] (2) The present invention solves the reflector optimization model based on the antlion optimization algorithm to obtain the optimal solution, avoiding the shortcomings of the existing technology, which obtains the optimization result by changing a single structural parameter, performing multiple calculations and then taking the minimum root mean square of thermal deformation, i.e., the low optimization accuracy caused by artificially given experimental values, and effectively improves the optimization accuracy.

[0020] (3) The present invention determines the constraint range of the structural parameters of the parametric model of the reflector by the solidification deformation and self-weight deformation of the parametric model of the reflector and the actual engineering situation, thereby narrowing the range of optimization variables and reducing the workload of optimization. At the same time, it avoids the defects of the existing technology that the range of optimization variables is too large and the optimization accuracy is not high, and further improves the efficiency and accuracy of optimization. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the implementation of the present invention.

[0022] Figure 2 The graph shows the maximum deformation of the skin of the reflector model constructed for this invention as a function of the side length of the honeycomb core cell under a curing pressure of 0.15 MPa.

[0023] Figure 3 The graph shows the root mean square deformation of the working surface under gravity of the reflector model constructed in this invention as a function of the height of the honeycomb core cell.

[0024] Figure 4 The graph shows the change in fitness of each ant with the number of iterations when the root mean square of thermal deformation of the reflector working surface is optimized using the antlion optimization algorithm of this invention. Detailed Implementation

[0025] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0026] Reference Figure 1 The present invention includes the following steps:

[0027] Step 1) Construct the reflector model:

[0028] A carbon fiber parabolic honeycomb sandwich structure, consisting of an intermediate layer and skins bonded to the inner and outer surfaces of the intermediate layer via an adhesive film, was constructed and its working surfaces were meshed. The structural and mechanical parameters of the multiple hexagonal carbon fiber honeycomb core cells constituting the intermediate layer and the multiple layups constituting the inner and outer skins, along with the coordinates of the N working surface nodes after meshing, were then compiled into an inp file using Python to form a parametric model of the reflector. The structural parameters include the side length *l* and height *h* of the honeycomb core cells, the number of layups *Q* and the layup angle *ply* in the inner and outer skins; the mechanical parameters include the density *ρ* of the honeycomb core cells. core and the density ρ of the inner and outer skin sheet .

[0029] This embodiment:

[0030] A parabolic honeycomb sandwich structure of carbon fiber, consisting of an intermediate layer and skins bonded to the inner and outer surfaces of the intermediate layer via an adhesive film, was constructed and distributed in a spatial rectangular coordinate system O-XYZ. The working surfaces were meshed using tetrahedral meshes. The structural and mechanical parameters of the multiple hexagonal carbon fiber honeycomb core cells constituting the intermediate layer and the multiple layups constituting the inner and outer skins, along with the coordinates of the N working surface nodes after meshing, were then compiled into an inp file using Python to form a parametric model of the reflector. The structural parameters include the side length l and height h of the honeycomb core cells, the number of layups Q and the layup angle ply in the inner and outer skins; the mechanical parameters include the density ρ of the honeycomb core cells. core and the density ρ of the inner and outer skin sheet The inp file can quickly reconstruct reflector models with different parameters by changing the input parameters.

[0031] Step 2) Determine the constraint range of the reflector model structural parameters:

[0032] Determine the upper limit of the side length l of the honeycomb core cell in the parametric model of the reflector under pressure P. uper and lower limit l lower The upper limit of height h under gravity conditions uper and lower limit h lower And the angles of the Q plies, ply = [ply1, ply2, ..., ply] q ,…,ply Q ], where plyq Let q be the ply angle of the q-th ply. The inner and outer skins are designed with symmetrical ply angles, meaning the 2Q ply angles of the inner and outer skins are [ply1, ply2, ..., ply]. q ,…,ply Q ,ply Q ,…,ply q [,…ply2,ply1];

[0033] Using the finite element method Abaqus 6.14, the J side lengths l = [l1, l2, ..., l] of the honeycomb core cells in the parametric model of the reflector were calculated in sequence under the pressure P. j ,…,l J The corresponding maximum deformation of the skin is Δu = [Δu1, Δu2Ω, Δu] j ,…,Δu J [Then, a line graph of Δu as a function of l is plotted, and the minimum side length l1 is used as the lower limit l.] lower The side length l of the cell when Δu increases sharply in the line graph uper As the upper limit, where Δu j Indicate l j The corresponding maximum deformation of the skin.

[0034] The K heights h = [h1, h2Ω, h2Ω] of the honeycomb core cells in the parametric model of the reflector under gravity conditions were calculated using finite element method software. k ,…,h K The corresponding root mean square (RMS) of the working face's self-weight deformation. z =[RMS z1 RMS z2 Ω,RMS zk ,…,RMS zK ], and plotted RMS z A line graph showing the change of h1, then the RMS value in the line graph. z Equal to the surface test requirement RMS cl The height value h of the honeycomb core cell lower As the lower limit, the upper limit of the working surface density design index ρ is used. ZBsurface The calculated maximum height is used as the upper limit h. uper RMS zk h k The corresponding root mean square of the working surface deformation due to its own weight, h uper The calculation formula is:

[0035] h uper =max(h)

[0036]

[0037] M = ρZBsurface ·S

[0038]

[0039] V sheet =0.52·Q·t m ·10 7

[0040] Where M and S are the weight and aperture area of ​​the reflector, respectively, and V sheet ρ is the total volume of the inner and outer skins. * V represents the equivalent density of the honeycomb core cells. core Let t be the envelope volume of the honeycomb core cell, and t be the wall thickness of the honeycomb core cell. m The thickness of each layer of the skin.

[0041] Q ply angles, where the ply angle for each q ply is... q The value is determined through the principles of quasi-isotropic layup design and actual engineering manufacturing.

[0042] This embodiment:

[0043] The maximum skin deformation Δu = [Δu1, Δu2, Δu3, Δu4, Δu5, Δu6] corresponding to the six successively increasing side lengths l = [5, 11, 17, 23, 29, 34] (mm) of the honeycomb core cell in the parametric model of the reflector under a pressure of 0.15 MPa was calculated using the finite element software Abaqus 6.14. A line graph showing Δu as a function of l was then plotted. Figure 2 Then, the minimum side length of 5mm is used as the lower limit. lower 5mm is the minimum side length of a honeycomb cell in practical engineering applications. The side length of the honeycomb cell, 20mm, when Δu increases sharply in the line graph, is taken as the upper limit. uper .

[0044] The root mean square (RMS) of the self-weight deformation of the working surface in the parametric model of the reflector under gravity conditions was calculated using the finite element software Abaqus 6.14 for six successively increasing heights h = [15, 25, 35, 45, 55, 65] (mm) of the honeycomb core cells. z =[RMS z1 RMS z2 RMS z3 RMS z4 RMS z5 RMS z6 ], and plotted RMS z Line graph showing the variation of h as follows Figure 3 Then, in the line chart, the RMS z Equal to surface test requirements (RMS) clWhen the thickness is 2.1 μm, the height of the honeycomb core cell is 45 mm as the lower limit h. lower The maximum height calculated using the upper limit of the areal density design index is used as the upper limit h. uper =197.4mm, h uper The calculation formula is:

[0045] h uper =max(h)

[0046]

[0047] M = ρ ZBsurface ·S

[0048]

[0049] V sheet =0.52·Q·t m ·10 7

[0050] Substitute the specific value t m =0.1mm, Q=8, t=0.4mm, 5mm≤l≤20mm, ρ ZBsurface =10kg / m 2 S = 2.591m 2 , ρ sheet =1.7*10 -9 t / mm 3 , ρ core =1.58*10 -9 t / mm 3 When l is 20mm, h is at its maximum, i.e., h uper =max(h) = 197.4 mm; Finally, the upper limit of the side length l of the honeycomb core cell in the parametric model of the reflector under the working condition of 0.15 MPa was determined. uper =20mm and lower limit l lower =5mm, the upper limit of height h under gravity conditions uper =148.3mm and lower limit h lower =45mm.

[0051] The angles of Q plies are ply = [ply1, ply2, ..., ply] q ,…,ply Q ], where the ply angle of each q ply qThe value is determined through the quasi-isotropic ply design principle and engineering manufacturing practice. Quasi-isotropy means that the material is isotropic only in a certain plane, that is, the material strength and stiffness are equal in all directions in the plane of the part, but there may be differences in the vertical plane. In order to achieve quasi-isotropy, the ply angle is often taken as 0°, 90°, +45° and -45°. The 0° layer provides axial strength and stiffness, the + / -45° layer provides shear and torsional strength and stiffness, and the 90° layer provides lateral strength and stiffness. At the same time, the number of skin ply layers and angles of the parametric model of the reflector are limited by the following in combination with engineering manufacturing practice:

[0052] The angle of the two plies is ply = [ply1, ply2] = [0, 90].

[0053] The angles of the three plies are ply = [ply1, ply2, ply3] = [0, 60, -60].

[0054] The angles of the four plies are ply = [ply1, ply2, ply3, ply4] = [0, 45, -45, 90].

[0055] The angles of the 5 plies are ply = [ply1, ply2, ply3, ply4, ply5] = [45, -45, 0, -45, 45].

[0056] The angles of the 6 plies are ply = [ply1, ply2, ply3, ply4, ply5, ply6] = [0, 60, -60, -60, 60, 0].

[0057] The angles of the 7 plies are ply = [ply1, ply2, ply3, ply4, ply5, ply6, ply7] = [0, 60, -60, 0, -60, 60, 0].

[0058] The angles of the 8 plies are ply = [ply1, ply2, ply3, ply4, ply5, ply6, ply7, ply8] = [0, 45, -45, 90, 90, -45, 45, 0]. The inner and outer skins are symmetrically plyed. For example, when both the inner and outer skins are 3-layer plies, the angles of the 6 plies are [ply1, ply2, ply3, ply3, ply2, ply1] = [0, 60, -60, -60, 60, 0].

[0059] Step 3) Calculate the root mean square of the thermal deformation of the working surface of the parametric model of the reflector under high and low temperature conditions:

[0060] Calculate at high temperature T h Low temperature is T l Root mean square (RMS) of thermal deformation of the working surface of the reflector model under operating conditionsh and RMS l ;Calculations were performed using the finite element software Abaqus 6.14 at a high temperature of T h Low temperature is T l The nodal coordinates of the working surface of the parametric model of the reflector before and after thermal deformation are obtained under working conditions. Least squares focal length fitting is performed on the nodal coordinates of each nodal surface before and after thermal deformation. Then, the focal length is determined by using a high temperature T... h Low temperature is T l The normal distance d from the nth node of the working surface of the parametric model of the reflector after thermal deformation under working conditions to the best-fit surface. hn and d ln Calculate the root mean square (RMS) of the thermal deformation of the working surface of the parametric model of the reflector under high and low temperature conditions. h and RMS l :

[0061]

[0062] Step 4) Construct the reflector optimization model:

[0063] Construct the root mean square (RMS) of the thermal deformation of the working surface of the parametric model of the reflector under high and low temperature conditions. h and RMS l To optimize the objective, the reflector optimization model is formulated with the structural parameters of the honeycomb sandwich structure as optimization variables and the constraint interval determined in step (2) as the condition. Its expression is as follows:

[0064]

[0065] Step 5) Obtain the optimization results of the reflector optimization model:

[0066] The reflector optimization model was solved using the antlion optimization algorithm, and the minimum root mean square (RMS) of the thermal deformation of the working surface under high and low temperature conditions was obtained. hu and RMS lu Carbon fiber parabolic reflector.

[0067] The positions of the ants and antlions are initialized, and four variables are assigned to the ants and antlions in the antlion algorithm: the structural parameters l, h, Q, and ply from the inp file. The structural parameters l, h, Q, and ply in the inp file are updated using the four variable values ​​of the antlion's position parameters after initialization. In each iteration, the structural parameters l, h, Q, and ply of the honeycomb sandwich structure in the inp file are updated using the four variable values ​​of each ant's position parameters. Then, the root mean square (RMS) of the working surface thermal deformation of the reflector parameterized model under high and low temperature conditions is calculated using the updated structural parameters in each iteration until the maximum number of iterations is reached. The minimum RMS of the working surface thermal deformation under high and low temperature conditions is obtained. hu and RMSlu A carbon fiber parabolic reflector. The antlion optimization algorithm optimizes the reflector's working surface thermal deformation root mean square, and the fitness of each ant changes with the number of iterations, as shown below. Figure 4 During the iteration process, the fitness of each ant is calculated based on its position. It can be seen that as optimization progresses, the positions of all ants gradually converge, and the ants' activity range continuously decreases, indicating the convergence of the antlion algorithm. In each iteration, the position of the ant with the highest fitness is used to update the position of the elite antlion. Finally, the positions of all individuals gradually converge, thus obtaining the optimal solution to the objective function.

Claims

1. A method for optimizing the thermal deformation of a carbon fiber parabolic reflector with a honeycomb sandwich structure, characterized in that, Includes the following steps: (1) Constructing a parametric model of the reflector: A carbon fiber parabolic honeycomb sandwich structure consisting of an intermediate layer and skins bonded to the inner and outer surfaces of the intermediate layer by an adhesive film is constructed in a spatial rectangular coordinate system O-XYZ. The working surface is then meshed. The structural and mechanical parameters of multiple hexagonal carbon fiber honeycomb core cells that make up the intermediate layer and multiple layers that make up the inner and outer skins, as well as the coordinates of N working surface nodes after meshing, are compiled into an inp file format to form a parametric model of the reflector. (2) Determine the constraint range of the structural parameters of the parametric model of the reflector: Determine the upper limit of the side length l of the honeycomb core cell in the parametric model of the reflector under pressure P. uper and lower limit l lower The upper limit of height h under gravity conditions uper and lower limit h lower And the angles of the Q plies, ply = [ply1, ply2, ..., ply] q ,…,ply Q ], where ply q Let q be the ply angle of the q-th ply; (3) Calculate the root mean square of the thermal deformation of the working surface of the parametric model of the reflector under high and low temperature conditions: Calculate at a high temperature of T h Low temperature is T l Root mean square (RMS) of thermal deformation of the working surface of the parametric model of the reflector under operating conditions h and RMS l ; (4) Constructing a reflector optimization model: Construct the root mean square (RMS) of the thermal deformation of the working surface of the parametric model of the reflector under high and low temperature conditions. h and RMS l To optimize the objective, a reflector optimization model is developed with the structural parameters of the honeycomb sandwich structure as the optimization variables and the constraint interval determined in step (2) as the condition. (5) Obtain the optimization results of the reflector optimization model: The reflector optimization model was solved using the antlion optimization algorithm, and the minimum root mean square (RMS) of the thermal deformation of the working surface under high and low temperature conditions was obtained. hu and RMS lu Carbon fiber parabolic reflector.

2. The method according to claim 1, characterized in that, The structural and mechanical parameters mentioned in step (1) include the structural parameters such as the side length l and height h of the honeycomb core cell, the number of layers Q and the layup angle ply in the inner and outer skins; and the mechanical parameters such as the density ρ of the honeycomb core cell. core and the density ρ of the inner and outer skin sheet .

3. The method according to claim 2, characterized in that, The upper limit of the side length l of the honeycomb core cell described in step (2) under the working condition of pressure P. uper and lower limit l lower The method for determining this is as follows: Using finite element method (FEM) software, the J side lengths l = [l1, l2, ..., l] of the honeycomb core cells in the parametric model of the reflector, which increase sequentially under pressure P, were calculated. j ,…,l J The maximum deformation of the corresponding skin is Δu = [Δu1, Δu2, ..., Δu] j ,…,Δu J [The text appears to be incomplete and contains several errors. A more accurate translation would require the full context.] lower The side length l of the cell when Δu increases sharply in the line graph uper As the upper limit, where Δu j Indicate l j The corresponding maximum deformation of the skin.

4. The method according to claim 2, characterized in that, The upper limit h of the height h under gravity conditions mentioned in step (2) uper and lower limit h lower The method for determining this is as follows: The K heights h = [h1, h2, ..., h] of the honeycomb core cells in the parametric model of the reflector under gravity conditions were calculated using finite element method software. k ,…,h K The corresponding root mean square (RMS) of the working face's self-weight deformation. z =[RMS z1 RMS z2 …,RMS zk ,…,RMS zK ], and plotted RMS z A line graph showing the change of h1, then the RMS value in the line graph. z Equal to the surface test requirement RMS cl The height value h of the honeycomb core cell lower As the lower limit, the upper limit of the working surface density design index ρ is used. ZBsurface The calculated maximum height is used as the upper limit h. uper RMS zk h k The corresponding root mean square of the working surface deformation due to its own weight, h uper The calculation formula is: h uper =max(h) M=ρ ZBsurface ·S V sheet =0.52·Q·t m ·10 7 Where M and S are the weight and aperture area of ​​the reflector, respectively, and V sheet ρ is the total volume of the inner and outer skins. * V represents the equivalent density of the honeycomb core cells. core Let t be the envelope volume of the honeycomb core cell, and t be the wall thickness of the honeycomb core cell. m The thickness of each layer of the skin.

5. The method according to claim 2, characterized in that, The Q ply angles mentioned in step (2), wherein the ply angle for each q ply is ply q The value is determined through the principles of quasi-isotropic layup design and actual engineering manufacturing.

6. The method according to claim 2, characterized in that, The calculation described in step (3) is performed at a high temperature of T. h Low temperature is T l Root mean square (RMS) of thermal deformation of the working surface of the parametric model of the reflector under operating conditions h and RMS l The calculation method is as follows: Calculations were performed using finite element software at a high temperature of T. h Low temperature is T l The nodal coordinates of the working surface of the parametric model of the reflector before and after thermal deformation are obtained under working conditions. Least squares focal length fitting is performed on the nodal coordinates of each nodal surface before and after thermal deformation. Then, the focal length is determined by using a high temperature T... h Low temperature is T l The normal distance d from the nth node of the working surface of the parametric model of the reflector after thermal deformation under working conditions to the best-fit surface. hn and d ln Calculate the root mean square (RMS) of the thermal deformation of the working surface of the parametric model of the reflector under high and low temperature conditions. h and RMS l :

7. The method according to claim 6, characterized in that, The reflector optimization model described in step (4) is expressed as follows: min:RMS h ,RMS l Find: l, h, Q, ply.

8. The method according to claim 7, characterized in that, The specific method for solving the reflector optimization model based on the antlion optimization algorithm in step (5) is as follows: The positions of the ants and antlions are initialized. Four variables are assigned to the ants and antlions in the antlion algorithm: the structural parameters l, h, Q, and ply from the .inp file. The position parameters of the antlions after initialization are used to update the structural parameters l, h, Q, and ply in the .inp file. In each iteration, the position parameters of each ant are used to update the structural parameters l, h, Q, and ply of the honeycomb sandwich structure in the .inp file. Then, the root mean square (RMS) of the thermal deformation of the reflector parameterized model under high and low temperature conditions is calculated using the updated structural parameters in each iteration until the maximum number of iterations is reached. The minimum RMS of the thermal deformation of the working surface under high and low temperature conditions is obtained. hu and RMS lu Carbon fiber parabolic reflector.

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