Computer-aided optimization design method and device for double-layer skin lattice mirror seat

Abstract

The application discloses a computer-aided optimization design method and device for a double-skin lattice mirror seat. The method comprises the following steps: firstly, obtaining a mirror seat structure and performing regional division processing to distinguish a non-design domain and a lattice filling design domain; performing finite element grid discrete processing on the lattice filling design domain by fusing geometric boundary constraints and additive manufacturing process constraints to obtain a grid framework model; performing lattice mapping and reconstruction processing on the grid framework model based on an isoparametric transformation rule to obtain a conformal lattice structure model; constructing a lattice parameterized model and optimizing the lattice parameterized model to obtain a lattice rod diameter optimization parameter set; and after three-dimensional solidification, assembly verification, additive manufacturing preprocessing and forming post-processing, the double-skin lattice mirror seat is prepared. The application significantly improves the lightweight rate and thermal stability of the mirror seat, and can be widely applied to the design of mirror seats of high-precision optical systems.

Description

Technical Field

[0001] This application relates to the field of optomechanical structure design technology for precision optical systems, and in particular to a computer-aided optimization design method and apparatus for a double-layer skin array lens mount. Background Technology

[0002] With the rapid development of high-precision optical technologies such as deep space exploration, space laser communication, and airborne aiming and tracking, the performance requirements of optical mounts, as core functional components of optomechanical systems, are continuously increasing. Optical mounts play a crucial role in supporting and protecting mirrors, adjusting and controlling the optical axis orientation, and isolating external environmental interference. Their lightweight design and thermal stability directly determine the imaging accuracy and service reliability of the optical system.

[0003] Currently, the design of mirror mount structures in high-precision optical systems generally adopts a purely solid structure design. This typically involves reinforcing the structure within the design envelope and creating weight-reducing holes to achieve lightweighting. Some designs also utilize topology optimization techniques to divide the design and non-design spaces, further enhancing the lightweighting effect. However, this type of solid structure design has significant technical drawbacks: On the one hand, lightweight materials such as aluminum alloys and titanium alloys are often chosen to meet lightweight requirements, but their coefficients of linear thermal expansion differ by two orders of magnitude from those of ultra-low expansion materials such as microcrystalline glass commonly used in mirrors. This mismatch in thermal deformation under extreme environments makes it difficult to maintain the mirror's surface accuracy, severely impacting the performance of the optical system and becoming an industry challenge for the athermal design of precision optical systems. On the other hand, using low-thermal-expansion Invar alloys to improve thermal stability is limited by their high-density characteristics, making them unsuitable for applications in airborne and other highly mass-sensitive scenarios, thus making it difficult to achieve a balance between lightweighting and low thermal expansion performance. On the other hand, existing design ideas are limited to the scope of solid structures and do not introduce lattice microstructures to achieve ultimate lightweight design. At the same time, traditional machining processes are difficult to manufacture complex internal topological configurations and closed internal cavity microstructures. The design space is limited to simple regular weight reduction grooves, and it is impossible to perform fine performance optimization for the mirror base structure. Even if lattice structures are introduced, problems such as loss of boundary integrity, failure of node connection, and poor manufacturability are likely to occur when the array is filled.

[0004] Therefore, how to balance lightweight efficiency and low thermal expansion stability while ensuring the mechanical performance of the lens mount, and at the same time improve the boundary adaptability and manufacturability of the lattice structure filling, is a technical problem that urgently needs to be solved in the field of precision optical lens mount design. Summary of the Invention

[0005] In view of this, the computer-aided optimization design method and apparatus for a double-layer skin dot matrix lens mount provided in this application embodiment can, while ensuring the mechanical performance of the lens mount, balance lightweight structural efficiency and low thermal expansion stability, and simultaneously improve the boundary adaptability and manufacturability of the dot matrix structure filling. The computer-aided optimization design method and apparatus for a double-layer skin dot matrix lens mount provided in this application embodiment is implemented as follows: This application provides a computer-aided optimization design method for a double-layer skin dot matrix lens mount, comprising: Obtain the mirror base structure, and perform region division processing on the mirror base structure to obtain the non-design domain and the lattice-filled design domain; The lattice-filled design domain is discretized using finite element meshing based on geometric boundary constraints and additive manufacturing process constraints to obtain a mesh frame model. Based on the isoparametric transformation rule, the mesh frame model is subjected to lattice mapping and reconstruction to obtain a conformal lattice structure model. A lattice parameterized model is constructed, and the geometric information of the conformal lattice structure model and the mesh frame model is extracted respectively. The geometric information is then input into the lattice parameterized model to obtain the lattice rod diameter optimization parameter set. The topological information of the lattice rod diameter optimization parameter set and the conformal lattice structure model are obtained respectively, and the topological information is processed into a three-dimensional solid model to obtain a lattice solid model that can be used for additive manufacturing. The lattice solid model, double-layer skin solid model and flange reinforcing block solid model available for additive manufacturing are assembled and verified to obtain the three-dimensional model of the mirror base. The three-dimensional model of the lens mount is preprocessed for additive manufacturing to obtain a process control document. The lens mount is then subjected to additive manufacturing and post-processing according to the process control document to obtain a double-layer skin dot matrix lens mount.

[0006] In some embodiments, the construction of the lattice parameterized model involves extracting the geometric information of the conformal lattice structure model and the mesh frame model, respectively, and inputting the geometric information into the lattice parameterized model to obtain a set of lattice rod diameter optimization parameters, including: The node coordinate information, rod topology connection information, and element geometric information of the conformal lattice structure model are extracted and processed to obtain the lattice structure geometric information; The geometric information of the lattice structure is encoded and converted to obtain a standardized parameter dataset; The model was constructed by using the diameter of the lattice rod as the design variable and the mechanical properties, thermal stability and lightweight index of the mirror mount as the optimization objectives, resulting in a parametric lattice model. The standardized parameter dataset is input into the lattice parameterized model for iterative optimization and solution to obtain the lattice rod diameter optimization parameter set.

[0007] In some embodiments, the step of performing lattice mapping and reconstruction processing on the mesh frame model based on isoparametric transformation rules to obtain a conformal lattice structure model includes: The spatial coordinates of the basic vertices in the mesh frame model are extracted by traversal to obtain a three-dimensional spatial coordinate array; A unit topology connection matrix is ​​established based on the three-dimensional spatial coordinate array. The unit topology connection matrix is ​​used to record vertex index attribution, unit adjacency relationship and node connection rules. Based on the unit topology connection matrix, the basic vertices shared by adjacent units are topologically connected to obtain a set of conformal boundary rods. The three-dimensional spatial coordinate array is subjected to spatial parameterization interpolation to obtain virtual nodes; Based on the preset lattice unit cell topology logic and the unit topology connection matrix, the virtual node and the basic vertex of the corresponding unit are topologically connected to obtain the core load-bearing rod. The conformal boundary member set and the core load-bearing member are topologically integrated to obtain a complete lattice unit cell topology. Based on the unit topology connection matrix, the complete lattice unit cell topology is seamlessly spliced ​​across the entire domain through the shared nodes of adjacent grid units to obtain a conformal lattice structure model.

[0008] In some embodiments, the step of performing finite element mesh discretization on the lattice-filled design domain based on geometric boundary constraints and additive manufacturing process constraints to obtain a mesh frame model includes: The topology type, number of normal layers, and element aspect ratio of the finite element mesh are locked to obtain the mesh topology constraint rules; Based on the process constraints of the maximum printing span of additive manufacturing, the critical safety angle of self-support, and the range of rod diameters that can be formed by lattice rods, the upper limit of the size, the lower limit of the size, and the aspect ratio threshold of the finite element mesh are set to obtain the mesh size constraint rules. Based on the mesh topology constraint rules, the mesh size constraint rules, and the geometric boundary constraints of the lattice-filled design domain, the lattice-filled design domain is meshed to obtain an initial mesh model. The initial mesh model is subjected to boundary fit and manufacturability verification and optimization processing to obtain the mesh frame model.

[0009] In some embodiments, the step of acquiring the topological information of the lattice rod diameter optimization parameter set and the conformal lattice structure model, and performing three-dimensional solidification processing on the topological information to obtain a lattice solid model suitable for additive manufacturing includes: The topological information of the conformal lattice structure model is analyzed and processed based on the lattice rod diameter optimization parameter set to obtain the lattice rod topology dataset; The node spatial coordinate matrix is ​​processed by topological connection based on the unit topological connection matrix to obtain the directed central axis. Using the optimized rod diameter of the corresponding rod in the lattice rod diameter optimization parameter set as the cross-sectional feature, the directed central axis is subjected to three-dimensional sweeping processing to obtain a three-dimensional cylindrical solid model of a single rod. A 3D Boolean union operation is performed on the 3D cylindrical solid model at the intersection of multiple rods to obtain a lattice solid model; The surface mesh of the lattice solid model is discretized to obtain a lattice solid model suitable for additive manufacturing.

[0010] In some embodiments, the assembly and verification process of the additively manufactured lattice solid model, the double-layer skin solid, and the flange reinforcing block solid to obtain a mirror mount three-dimensional model includes: The lattice solid model, double-layer skin solid model and flange reinforcing block solid model available for additive manufacturing are imported into the same design space and matched with the reference to obtain the initial assembly positioning model. The initial assembly positioning model is subjected to global entity assembly fusion processing to obtain the initial assembly entity model; The initial assembly entity model is subjected to geometric continuity, boundary closure, and structural integrity verification processes to obtain a defect identification dataset; The defect identification dataset is corrected to obtain the assembly entity model; The assembly entity model is subjected to a global closed-loop verification process to obtain the overall three-dimensional model of the mirror mount.

[0011] In some embodiments, the diameter of the lattice rod is in the range of 0.65~0.85mm.

[0012] This application provides a computer-aided optimization design device for a double-layer skin dot matrix lens mount, comprising: The acquisition module is used to acquire the mirror base structure, perform region division processing on the mirror base structure, and obtain the non-design domain and the lattice-filled design domain. The processing module is used to perform finite element mesh discretization on the lattice-filled design domain based on geometric boundary constraints and additive manufacturing process constraints to obtain a mesh frame model. The processing module is also used to perform lattice mapping and reconstruction processing on the mesh frame model based on isoparametric transformation rules to obtain a conformal lattice structure model. A construction module is used to construct a lattice parameterized model, extract the geometric information of the conformal lattice structure model and the mesh frame model respectively, and input the geometric information into the lattice parameterized model to obtain a set of lattice rod diameter optimization parameters; The acquisition module is also used to acquire the topological information of the lattice rod diameter optimization parameter set and the conformal lattice structure model respectively, and to perform three-dimensional solidification processing on the topological information to obtain a lattice solid model that can be used for additive manufacturing. The processing module is also used to assemble and verify the lattice solid model, double-layer skin solid and flange reinforcing block solid that can be used for additive manufacturing, to obtain a three-dimensional model of the mirror base. The processing module is also used to perform additive manufacturing preprocessing on the three-dimensional model of the lens mount to obtain a process control file, and to perform additive manufacturing and post-processing on the lens mount according to the process control file to obtain a double-layer skin dot matrix lens mount.

[0013] The computer device provided in this application includes a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the program, it implements the method described in this application.

[0014] The computer-readable storage medium provided in this application embodiment stores a computer program thereon, which, when executed by a processor, implements the method provided in this application embodiment.

[0015] This application provides a computer-aided optimization design method and apparatus for a double-layer skin dot matrix lens mount. The method involves first acquiring the lens mount structure and dividing it into regions, distinguishing between the non-design domain and the dot matrix-filled design domain. Then, it integrates geometric boundary constraints and additive manufacturing process constraints to perform finite element mesh discretization on the dot matrix-filled design domain, obtaining a mesh frame model. Based on isoparametric transformation rules, it performs dot matrix mapping and reconstruction on the mesh frame model to obtain a conformal dot matrix structure model. Finally, it constructs a parameterized dot matrix model and optimizes it to obtain a set of optimized dot matrix rod diameter parameters. After three-dimensional solidification, assembly verification, additive manufacturing preprocessing, and post-forming processing, a double-layer skin dot matrix lens mount is obtained. This significantly improves the lightweight ratio and thermal stability of the lens mount, making it widely applicable to the lens mount design of high-precision optical systems and solving the technical problems mentioned in the background art. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A schematic diagram illustrating the implementation process of a computer-aided optimization design method for a double-layer skin dot matrix lens mount provided in this application embodiment; Figure 2 A schematic diagram illustrating the implementation process of obtaining a set of optimized parameters for lattice rod diameters, provided in an embodiment of this application; Figure 3 A schematic diagram of the structure of a computer-aided optimization design device for a double-layer skin dot matrix lens mount provided in an embodiment of this application; Figure 4 This is a schematic diagram of the original design domain of the mirror mount structure provided in the embodiments of this application; Figure 5 A schematic diagram of the layering of the double-layer skin dot matrix sandwich mirror mount provided in the embodiments of this application; Figure 6 This is a schematic diagram of the lattice domain and the non-design domain provided in the embodiments of this application; Figure 7 This is a schematic diagram of finite element discretization in the lattice domain provided in an embodiment of this application; Figure 8 A schematic diagram illustrating the correspondence between finite element meshes and lattice structures when the virtual node is body-centered, as provided in the embodiments of this application. Figure 9 A visual schematic diagram of the lattice parametric finite element analysis-optimization model provided in the embodiments of this application; Figure 10 This is a schematic diagram of a dot matrix STL file provided in an embodiment of this application; Figure 11 A complete rendering of the lightweight, low-expansion double-layer skin matrix lens mount provided for the embodiments of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0019] The following description of some technologies involved in the embodiments of this application is provided to aid understanding and should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, some descriptions of well-known functions and structures are omitted in the following description.

[0020] Figure 1 This is a schematic flowchart illustrating the implementation of a computer-aided optimization design method for a double-layer skin dot matrix lens mount provided in this application embodiment, including steps 101 to 107. Wherein, Figure 1 This is merely one execution order shown in the embodiments of this application, and does not represent the only execution order of a computer-aided optimization design method for a double-layer skin dot matrix mirror mount. Where the final result can be achieved, Figure 1 The steps shown can be performed in parallel or in reverse order.

[0021] Step 101: Obtain the mirror base structure, and perform region division processing on the mirror base structure to obtain the non-design domain and the lattice-filled design domain.

[0022] In this embodiment of the application, the original design model of the lens mount structure is obtained, that is, the initial design domain model of the precision optical lens mount to be designed (e.g., Figure 4 As shown, Figure 4 (This is a schematic diagram of the original design domain of the lens mount structure provided in the embodiments of this application). Based on the design dimensions, interface parameters and functional requirements of the given optical model, the lens mount structure is divided into regions to obtain the non-design domain and the lattice-filled design domain.

[0023] First, the inner wall envelope of the mirror mount is extracted as the absolute non-design domain based on optical path constraints. Then, the flange bolt holes and the outer wall of the mating surface are extracted as interference non-design domains based on assembly tolerances. Simultaneously, for the bottom flange bolt holes, a pre-placed reinforcing block is used as the non-design domain, centered on the bolt holes, to ensure the connection strength around the bolt holes. Based on the partitioning results, a double-layer skin-lattice sandwich structure model is established. The overall space of the mirror mount structure is divided into an inner skin layer, a lattice sandwich layer, and an outer skin layer. The inner skin layer, outer skin layer, and flange reinforcing block are all classified as non-design domains. The lattice sandwich layer between the two skin layers is a specific layer of the lattice-filled design domain. The results are as follows: Figure 5 As shown, Figure 5 This is a schematic diagram of the layering of a double-layer skin dot matrix sandwich mirror mount provided in an embodiment of this application.

[0024] For a precision lens mount with a main body wall thickness of 6mm, this embodiment divides the space into a 1mm thick inner skin layer, a 4mm thick dot matrix sandwich layer, and a 1mm thick outer skin layer. The dot matrix sandwich layer is filled with only a single layer of dot matrix. Simultaneously, a 2mm undesigned space is reserved in the top area of ​​the lens mount to ensure a rigid connection between the lens mount and the frame, preventing damage to the dot matrix area during assembly. Similarly, the bottom flange area is divided into upper and lower skin layers of 1mm thickness and a 4mm thick dot matrix sandwich layer. A 4mm thick reinforcing block undesigned area is pre-placed centered on the bolt holes to prevent insufficient strength at the flange bolt holes due to excessive dot matrix porosity. Details of the division of the dot matrix area and undesigned area in the bottom flange area are as follows: Figure 6 As shown, Figure 6 This is a schematic diagram of the lattice domain and the non-design domain provided in the embodiments of this application.

[0025] Step 102: Based on geometric boundary constraints and additive manufacturing process constraints, the lattice-filled design domain is discretized using finite element mesh to obtain a mesh frame model.

[0026] In this embodiment, for the lattice-filled design domain, a mesh generation strategy that integrates geometric boundary constraints and additive manufacturing process constraints is adopted. The generation rules for micro-lattices are moved forward to the macro-mesh generation stage. The finite element discretization effect of the lattice-filled design domain is as follows: Figure 7 As shown, Figure 7 This is a schematic diagram of finite element discretization of a lattice domain provided in an embodiment of this application. First, the topology type, number of normal layers, and aspect ratio of the finite element mesh are forcibly locked to ensure that the spatial characteristics of the mesh are highly coordinated with the preset spatial characteristics of the lattice unit cell. At the same time, the setting of the mesh size and aspect ratio fully incorporates the process limit constraints of additive manufacturing, including the maximum printing span, the self-supporting critical safety angle, and the maximum and minimum formable rod diameters of the lattice structure.

[0027] For a 4mm thick lattice sandwich layer, this embodiment sets the mesh layer number constraint operator to 1 and sets a limit on the element aspect ratio to ensure that the topology of the finite element unit is highly compatible with the preset lattice unit cell space ratio. This drives the discretization algorithm to generate a mesh structure dominated by hexahedral meshes and compatible with some tetrahedral meshes within the lattice filling design domain. The upper limit of the feature size of the hexahedral mesh is set to 4mm, with a maximum of 4.5mm, thereby limiting the maximum spatial span of a single lattice rod and avoiding molten pool collapse caused by excessively long suspended lattice rods in the selective laser melting process. The height-to-width ratio of the mesh is set to meet the following requirements. The self-supporting critical safety angle requirement is set at 45° in this embodiment. Aspect ratio control prevents the generation of excessively flat meshes in the gently sloping area of ​​the mirror mount, thus preventing the introduction of internal supports that cannot be removed. Simultaneously, a minimum mesh size greater than four times the maximum design rod diameter is set; in this embodiment, the minimum mesh size is 3.2mm. This ensures sufficient mesh space to accommodate the maximum design rod diameter, guaranteeing the porosity and lightweight efficiency of the lattice structure. Furthermore, it avoids excessive mesh density, preventing the optimized mapped lattice rod diameter from falling below the printer's minimum formable limit, thus avoiding rod breakage or weak connections during printing. Finally, the mesh generation is completed through these constraints, resulting in a mesh frame model adapted to the preset lattice unit cell topological features.

[0028] Step 103: Perform lattice mapping and reconstruction on the mesh frame model based on the isoparametric transformation rules to obtain the conformal lattice structure model.

[0029] In this embodiment, the solid cutting logic under the global coordinate system is abandoned. Instead, the geometric spatial information of the finite element mesh is used as the local constraint domain. The preset standard lattice unit cell topology is mapped from the natural coordinate system to each mesh cell in the physical space through a spatial interpolation function. First, the spatial physical coordinates of the basic vertices of each cell in the mesh frame model are extracted. Taking a hexahedral cell as an example, the spatial coordinates of the eight basic vertices of each hexahedral cell are extracted. A cell topology connection matrix is ​​established, the connection order of the nodes is defined, and adjacent basic vertices sharing the same physical boundary are automatically connected to generate a set of conformal boundary rods that fit the inner and outer skins. Then, a virtual node injection enhancement mechanism is introduced inside the cell. The three-dimensional shape function of the cell is used to perform spatial parameterized interpolation on the eight basic vertices to calculate the precise spatial body center coordinates of each mesh cell as virtual nodes. When the virtual nodes are body centers, the correspondence between the finite element mesh and the lattice structure is as follows: Figure 8As shown; then, based on the preset body-centered cubic lattice unit cell topology logic, cross connections are established between the body-centered virtual nodes and the corresponding unit's peripheral foundation vertices to generate the core load-bearing members inside the unit; since adjacent finite element meshes naturally share common surfaces and common nodes, through the unit-based local mapping reconstruction strategy, the seamless splicing of lattice units is automatically completed within the entire lattice filling design domain, ultimately generating a conformal lattice structure model that is completely fitted to the skin boundary, physically connected to the entire node domain, and has a continuous force transmission path.

[0030] It should be noted that, in addition to body-centered lattices, this embodiment can also modify the topological connection matrix of the basic nodes and the selection logic of virtual nodes according to actual design requirements to generate different types of lattice structures such as face-centered and centroid-centered lattice structures.

[0031] Step 104: Construct a lattice parameterized model, extract the geometric information of the conformal lattice structure model and the mesh frame model respectively, and input the geometric information into the lattice parameterized model to obtain the lattice rod diameter optimization parameter set.

[0032] In this embodiment, the node coordinate information, member topology connection information, and element geometry information of the conformal lattice structure model are extracted. Using a dedicated attribute encoding script, the discretized lattice network information is converted into a finite element input format recognizable by CAE (Computer Aided Engineering) software, including but not limited to mainstream finite element numerical analysis input formats such as .fem, .inp, and .dat. The visualization effect of the lattice parametric finite element analysis-optimization model constructed in this embodiment is shown below. Figure 9 As shown, the script automatically captures the 3D coordinate array of all nodes, assigns a unique index number to each node, and constructs the node data required by the CAE solver; it traverses the member mapping logic within each element, serializes the connection relationship of the beam element into a topological connection matrix, and constructs the element data required by the CAE solver; at the same time, it extracts the surface mesh information of the finite element model. The surface mesh is consistent with the beam element nodes and naturally has connectivity, so it can be directly used as skin in the finite element solution.

[0033] The beam element diameter parameters are set as an open design variable interface. With the mechanical properties, thermal stability, and lightweighting of the mirror mount as optimization objectives, and considering structural stress distribution, weight constraints, and geometric interference constraints, a lattice parametric finite element analysis and optimization model is constructed. The sensitivity information of the beam diameter to structural compliance and weight is obtained through the finite difference method. A gradient algorithm is used for multiple iterative solutions to finally obtain a converged set of optimized lattice beam diameter parameters. In this embodiment, the diameter range of the optimized lattice beams is controlled between 0.65mm and 0.85mm. This parametric model supports rapid updates; parameters can be adjusted without remodeling, enabling rapid iteration of design-simulation-optimization.

[0034] Step 105: Obtain the topology information of the lattice rod diameter optimization parameter set and the conformal lattice structure model, respectively, and perform three-dimensional solidification processing on the topology information to obtain a lattice solid model that can be used for additive manufacturing.

[0035] In this embodiment, the optimization parameter set of lattice rod diameters and the topological information of the conformal lattice structure model are analyzed to obtain the three-dimensional coordinate matrix of the node space, the element topological connection matrix, and the converged rod diameter distribution dataset. A three-dimensional solidification process is then performed using a beam element geometric reconstruction algorithm. Guided by the connection relationships in the topological connection matrix, directed central axes are generated between the corresponding spatial node endpoints. The optimized rod diameter of the corresponding rod is used as a cross-sectional feature, and a three-dimensional sweep calculation is performed along the central axis to transform the one-dimensional beam element topological network into a spatial cylindrical array entity with real physical boundaries. At the nodes where multiple lattice rods intersect in space, a three-dimensional Boolean union operation is performed to automatically calculate and eliminate the internal overlapping redundant volume at the intersection, ensuring the entity continuity and structural integrity at the intersection nodes. The merged continuous geometric entity undergoes surface mesh discretization processing, transforming the continuous three-dimensional surface into a polyhedral network composed of spatial triangular facets. Finally, it is exported as a three-dimensional printable solid model in standard STL format. The lattice domain STL file obtained after solidification is shown below. Figure 10 As shown, it can be directly used for subsequent layer slicing and printing.

[0036] Step 106: Assemble and verify the lattice solid model, double-layer skin solid model, and flange reinforcing block solid model available for additive manufacturing to obtain the three-dimensional model of the mirror mount.

[0037] In this embodiment, the lattice solid model available for additive manufacturing is imported into the same three-dimensional design space along with the double-layer skin solid and flange reinforcement block solid pre-separated and extracted during the region division stage. Spatial alignment is achieved through reference origin or feature surface matching to complete solid assembly and fusion. During the assembly process, the integrity of the model is verified to ensure that the skin, flange reinforcement block and internal lattice structure are tightly connected. The geometric continuity and boundary closure of the model are detected to eliminate cracks, isolated surfaces and overlapping surfaces in the model, and finally, a complete three-dimensional model of the mirror mount with a completely closed surface and a continuous and complete structure is obtained.

[0038] Step 107: Perform additive manufacturing preprocessing on the 3D model of the mirror mount to obtain the process control file. Based on the process control file, perform additive manufacturing and post-processing on the mirror mount to obtain a double-layer skin dot matrix mirror mount.

[0039] In this embodiment, the verified overall 3D model of the lens mount is imported into the additive manufacturing data preparation system for layered slicing. A support structure is generated based on the constraints of the metal printing process, and the laser scanning path is planned. A process control file that can be directly input into the metal additive manufacturing equipment is then output. In this embodiment, selective laser melting equipment is used for additive manufacturing, and 4J36 Invar alloy powder is selected as the forming material. This material has a coefficient of thermal expansion of 1×10^-6 / K, exhibiting excellent low thermal expansion performance. After the formed part is printed and exits the chamber, post-processing steps such as powder cleaning, stress-relieving annealing, and support removal are performed sequentially. Finally, a lightweight, low-expansion double-layer skin dot matrix lens mount that meets the design requirements is obtained. The final effect of the complete lightweight, low-expansion double-layer skin dot matrix lens mount is as follows: Figure 11 As shown.

[0040] This application's embodiments, through a double-layer skin + lattice core structure design and a fully adaptive additive manufacturing method, utilize Invar alloy with low thermal expansion as the forming material, while maintaining a weight comparable to that of a solid aluminum alloy lens mount. This significantly reduces thermal deformation during lens mount service, substantially improving thermal stability and fundamentally solving the problem of excessive surface accuracy caused by mismatch between optical components and lens mount deformation. It abandons the traditional global solid cutting logic of array lattice filling, achieving complete fit between the lattice structure and the complex curved surface boundary of the lens mount through an integrated design process of mesh discretization-lattice mapping. This fundamentally avoids problems such as incomplete unit cells, node connection failures, and poor boundary fit, ensuring the integrity and uniformity of mechanical properties of the lattice structure. The entire process integrates additive manufacturing process constraints, considering manufacturability requirements in advance at every stage from mesh generation, lattice design, parameter optimization to solidification. This effectively avoids printing defects such as melt pool collapse, inability to remove internal supports, and broken rods, achieving seamless integration of lens mount design and manufacturing. A closed-loop process of design-simulation-optimization-manufacturing has been established. Parametric design has significantly shortened the development cycle of the lens mount. It can flexibly adapt to the design requirements of precision optical lens mounts of different specifications and service scenarios, and has strong engineering practicality and versatility.

[0041] In the above Figure 1 Based on the above, this application embodiment also provides a schematic diagram of the implementation process for obtaining the lattice rod diameter optimization parameter set. For example... Figure 2 As shown, steps 201 to 204 are included: Step 201: Extract the node coordinate information, rod topology connection information, and element geometric information of the conformal lattice structure model to obtain the lattice structure geometric information.

[0042] In this embodiment of the application, the node coordinate information, rod topology connection information, and element geometric information of the conformal lattice structure model are extracted and processed to obtain the lattice structure geometric information.

[0043] A dedicated attribute encoding script automatically extracts all node data from the conformal lattice structure model, including the 3D spatial coordinate arrays of the basic vertices and virtual nodes constituting the lattice members. Each node is assigned a globally unique index number, ensuring that the same physical node shared by adjacent mesh elements uses a unified index identifier, avoiding duplicate nodes and member breakage issues during subsequent analysis. Simultaneously, the topological connection matrix recording the member connection relationships is extracted from the conformal lattice structure model, obtaining the two endpoint node indices and spatial orientation information for each lattice member, i.e., the member topological connection information. Furthermore, element geometric information such as type, size parameters, adjacency relationships, and boundary fit states of each element in the mesh frame model is extracted. Integrating these three types of information yields complete lattice structure geometric information. The surface mesh information of the mesh frame model is also extracted concurrently. This surface mesh is consistent with the beam element nodes of the lattice structure, naturally possessing geometric connectivity, and can be directly used as a skin structure in subsequent finite element analysis.

[0044] Step 202: Encode and convert the geometric information of the lattice structure to obtain a standardized parameter dataset.

[0045] In this embodiment, a dedicated attribute encoding script is used to perform full parametric encoding conversion on the geometric information of the lattice structure. This converts the discrete, non-standardized geometric information into a finite element input format recognizable by CAE software. Optional formats include, but are not limited to, mainstream finite element numerical analysis input formats such as .fem, .inp, and .dat. During the encoding conversion process, the three-dimensional spatial coordinate array of nodes is converted into node data that can be directly read by the finite element solver; the topological connection matrix of the members is converted into element constraint data for finite element analysis; and the diameter parameters of the lattice members are converted into editable and optimizable design variable data. Finally, a standardized parameter dataset with a unified format and complete data is obtained, achieving seamless migration of the geometric information of the lattice structure to the finite element analysis environment.

[0046] Step 203: Using the diameter of the lattice rod as the design variable and the mechanical properties, thermal stability, and lightweight indicators of the mirror mount as optimization objectives and constraints, an optimization model is constructed to obtain the lattice parameterized optimization model.

[0047] In this embodiment, the rod diameter parameters of the lattice members in the standardized parameter dataset are set as an open variable interface, serving as the sole design variable for the optimization model. Simultaneously, the quantitative dimensions of the optimization objectives are clearly defined. Mechanical performance is quantified by the stiffness and strength of the mirror mount structure; thermal stability by the thermal deformation of the mirror mount under extreme temperature conditions; and lightweighting by the overall weight and structural lightweighting rate. Combining the structural stress distribution, weight limits, and geometric interference constraints between the rods and non-design domains under actual service conditions, a multi-objective coupled lattice parameterized finite element analysis and optimization model is constructed. This model enables rapid adjustment of the rod diameter parameters and real-time solution of corresponding performance indicators without requiring re-geometric modeling, supporting rapid iteration of mirror mount design, simulation, and optimization.

[0048] Step 204: Input the standardized parameter dataset into the lattice parameterized model for iterative optimization and solution processing to obtain the lattice rod diameter optimization parameter set.

[0049] In this embodiment, the standardized parameter dataset is completely imported into the lattice parameterized model, and a size optimization algorithm is introduced to perform multi-round iterative optimization. During the solution process, the sensitivity information of different rod diameter parameters to the compliance and overall weight of the mirror mount structure is first calculated using the finite difference method to clarify the influence weight of the rod diameter parameters on each optimization objective. Then, an iterative optimization is performed using a gradient algorithm. During the iteration process, it is simultaneously verified whether the rod diameter parameters meet the constraints of the formable rod diameter range and geometric interference constraints of additive manufacturing, until the optimization objective reaches the preset design threshold and the change in design variables is less than the convergence threshold. The iterative solution is then completed, and finally, a globally convergent lattice rod diameter optimization parameter set that satisfies all constraints is obtained. In this embodiment, after iterative optimization, the diameter range of the lattice rods is limited to between 0.65mm and 0.85mm. This parameter set can achieve a globally optimal balance between mirror mount stiffness, thermal stability, and lightweight performance.

[0050] This application's embodiments solve the problems of data loss and format incompatibility between the design model and the analysis model by fully extracting and standardizing the encoding and conversion of node coordinates, rod topology connections, and element geometric information, significantly improving the accuracy and efficiency of simulation analysis. A parametric optimization model with the rod diameter of the lattice rods as the core design variable and coupled with multiple performance objectives is constructed, achieving a globally optimal balance between the mechanical performance, thermal stability, and lightweight performance of the mirror mount, avoiding performance shortcomings caused by traditional empirical design. The rod diameter parameters obtained through iterative optimization simultaneously meet the mechanical load-bearing requirements and the additive manufacturing formability constraints, ensuring the load-bearing capacity of the lattice structure while avoiding printing defects caused by rod diameters exceeding the range. The optimized rod diameter range of 0.65mm to 0.85mm achieves a precise balance between structural performance and manufacturability. The constructed parametric model supports rapid adjustment and updating of rod diameter parameters without the need for re-geometric modeling, significantly improving the iteration efficiency of the design scheme and reducing the R&D design cost of the mirror mount.

[0051] In some embodiments, the mesh frame model is subjected to lattice mapping and reconstruction based on isoparametric transformation rules to obtain a conformal lattice structure model, including: traversing and extracting the spatial coordinates of the basic vertices in the mesh frame model to obtain a three-dimensional spatial coordinate array.

[0052] Specifically, for finite element elements in the mesh framework model that are mainly hexahedral and compatible with some tetrahedral transitions, the spatial physical coordinates of all basic vertices are extracted element by element through a traversal algorithm. Specifically, the three-axis coordinates of 8 basic vertices are extracted for hexahedral elements, and the three-axis coordinates of 4 basic vertices are extracted for tetrahedral transition elements. At the same time, a globally unique index number is assigned to each extracted basic vertex to ensure that the same physical vertex shared by adjacent mesh elements uses a completely consistent index identifier. This avoids the problem of duplicate nodes and broken members in subsequent topological connections from the data source. Finally, all the coordinates of basic vertices with unique indexes are integrated to form a three-dimensional spatial coordinate array covering the entire lattice filling design domain.

[0053] Furthermore, a cell topology connection matrix is ​​established based on a three-dimensional spatial coordinate array. The cell topology connection matrix is ​​used to record vertex index attribution, cell adjacency relationship and node connection rules.

[0054] Specifically, using a three-dimensional spatial coordinate array as the data foundation, the unit number corresponding to each basic vertex index is recorded unit by unit to form the vertex index belonging relationship; the correspondence between common surfaces and shared vertices between adjacent units is identified and recorded to form unit adjacency relationship; at the same time, the connection order between nodes inside the unit and boundary nodes and the connection rules of shared nodes between adjacent units are preset. Finally, the above information is integrated to establish a unit topology connection matrix. This matrix provides a unique data basis for all subsequent topology connection operations, ensuring the accuracy and consistency of node connection during the lattice mapping process.

[0055] Furthermore, based on the element topology connection matrix, the basic vertices shared by adjacent elements are topologically connected to obtain a set of conformal boundary rods.

[0056] Specifically, based on the unit adjacency relationships and node connection rules recorded in the unit topology connection matrix, the basic vertices of the mesh units that fit the inner and outer skin boundaries of the mirror mount are automatically identified. The same boundary vertices shared by adjacent mesh units are topologically connected to generate rods that extend continuously along the skin boundary. Through the unified constraints of the unit topology connection matrix, it is ensured that the boundary rods are free from breaks, repetitions, and misalignments, and completely fit the complex curved surface contour of the mirror mount skin, ultimately forming a set of conformal boundary rods that cover the entire lattice-filled design domain boundary.

[0057] Furthermore, spatial parameterization interpolation is performed on the three-dimensional spatial coordinate array to obtain virtual nodes.

[0058] Specifically, based on the isoparametric transformation rules of the unit's local coordinate system, the three-dimensional shape function of the unit is used to perform spatial parameterized interpolation on the three-dimensional spatial coordinate array corresponding to each mesh unit to calculate the coordinates of the virtual nodes inside the unit. In this embodiment, the precise spatial body center coordinates of each hexahedral mesh unit are calculated by interpolation as virtual nodes. At the same time, the interpolation logic can be adjusted to calculate the virtual nodes at the face center, centroid, and other positions of the unit according to actual design requirements, adapting to different types of lattice unit cell topology designs.

[0059] Furthermore, based on the preset lattice unit cell topology logic and the unit topology connection matrix, the virtual nodes and the basic vertices of the corresponding units are topologically connected to obtain the core load-bearing rods.

[0060] Specifically, this embodiment pre-defines the topological logic of the body-centered cubic lattice unit cell. Based on the vertex index belonging relationship recorded in the unit topological connection matrix, it locks the unit to which the virtual node belongs and only establishes cross-topological connections between the virtual node and all the basic vertices of the unit to avoid incorrect connections across units. This generates oblique core load-bearing members inside the unit. These members can significantly improve the shear stiffness and structural stability of the lattice structure, ultimately forming a core load-bearing member system covering all grid units.

[0061] Furthermore, the conformal boundary member set and the core load-bearing member are topologically integrated to obtain a complete lattice unit cell topology.

[0062] Specifically, taking a single grid cell as the unit, the conformal boundary members of the corresponding cell are topologically integrated with the internal core load-bearing members to eliminate duplicate nodes and redundant connections, forming a complete lattice unit cell topology structure that corresponds one-to-one with a single grid cell. Each complete lattice unit cell has preset topological logic and mechanical load-bearing capacity, providing standardized topological units for subsequent global splicing.

[0063] Furthermore, based on the unit topology connection matrix, the complete lattice unit cell topology is seamlessly spliced ​​across the entire domain through the shared nodes of adjacent grid units to obtain a conformal lattice structure model.

[0064] Specifically, based on the unit adjacency relationship and shared node information recorded in the unit topology connection matrix, the complete lattice unit cells corresponding to adjacent units are precisely connected through the shared vertices of adjacent grid units, so that adjacent unit cells are completely connected at the shared nodes, without cracks, misalignments, or redundant members, and the entire lattice filling design domain is seamlessly spliced. It abandons the global coordinate system solid cutting logic used in traditional array lattice filling, fundamentally avoiding the problems of incomplete unit cells and node connection failures at complex curved surface boundaries, and finally generates a conformal lattice structure model that is completely fitted to the mirror base skin boundary, physically connected to the entire node domain, and has a continuous force transmission path.

[0065] This application's embodiments utilize isoparametric transformation rules based on the element's local coordinate system to map and reconstruct lattice unit cells on a per-mesh-element basis. This eliminates the traditional solid cutting logic under the global coordinate system, fundamentally solving the industry pain points of incomplete unit cells and poor boundary fit at complex curved surface boundaries, achieving complete adaptation between the lattice structure and the mirror mount skin boundary. By establishing an element topology connection matrix, the rules for vertex index assignment, element adjacency, and node connection are standardized, providing a unique data basis for the entire process of topology connection operations. This effectively avoids problems such as duplicate nodes, broken members, and incorrect cross-element connections, ensuring the accuracy and consistency of node connections in the lattice structure. Virtual nodes are generated through three-dimensional shape function space interpolation, and core load-bearing members are constructed within the element, significantly improving the shear stiffness and structural stability of the lattice structure. Simultaneously, the interpolation logic of the virtual nodes can be flexibly adjusted to adapt to various types of lattice unit cell topologies, such as body-centered, face-centered, and centroid-centered, providing extremely high design flexibility. The seamless splicing process based on shared nodes enables complete connectivity of lattice unit cells within the entire lattice filling design domain, ensuring the continuity and integrity of the structural force transmission path, avoiding mechanical performance degradation caused by splicing misalignment, and improving the overall structural reliability of the mirror mount.

[0066] In some embodiments, the lattice-filled design domain is discretized using finite element mesh based on geometric boundary constraints and additive manufacturing process constraints to obtain a mesh frame model, including: locking the topology type, number of normal layers, and aspect ratio of the element mesh to obtain mesh topology constraint rules.

[0067] Specifically, to overcome the boundary integrity loss problem that easily occurs in traditional array-type lattice filling, this embodiment moves the generation rules of the micro-level lattice to the macro-level mesh generation stage, first locking the core topological parameters of the finite element mesh. First, the topological type of the mesh is locked, determining that a hexahedral mesh is the core, compatible with a small number of tetrahedral meshes as transition units at complex curved surfaces, ensuring that the mesh unit configuration matches the topological logic of the preset lattice unit cell. Then, for the design parameters of a 6mm wall thickness for the mirror mount and a 4mm thickness for the lattice core layer, the mesh layer constraint operator N=1 is set, meaning only one layer of mesh is divided along the normal wall thickness direction of the lattice core layer, perfectly matching the design requirement that the lattice core layer is only filled with a single layer of lattice. Finally, the aspect ratio range of the mesh units is locked, ensuring that the spatial configuration of the mesh units is highly coordinated with the spatial size ratio of the preset body-centered cubic lattice unit cell, eliminating the risk of configuration distortion during subsequent lattice mapping from the geometric source. Integrating the above locked parameter requirements, the mesh topological constraint rules are obtained.

[0068] Furthermore, based on the process constraints of the maximum printing span of additive manufacturing, the critical safety angle of self-support, and the range of formable rod diameters of lattice rods, the upper limit, lower limit, and aspect ratio threshold of the finite element mesh are set to obtain the mesh size constraint rules.

[0069] Specifically, in this embodiment, selective laser melting is used to complete the additive manufacturing of the mirror mount, and the mesh size constraint is set by combining the limiting parameters of this process. First, based on the maximum printing span allowed by the process, the upper limit of the feature size of the grid unit is set to 4mm, with a maximum of 4.5mm. This limits the maximum spatial span of the single lattice rods generated by subsequent mapping, avoiding the defect of melt pool collapse due to excessively long suspended lattice rods during printing. Second, based on the self-supporting critical safety angle of the process, which is 45° in this embodiment, the height-to-width ratio threshold of the grid unit is set to ≥tan45°, i.e., the ratio ≥1. This avoids generating excessively flat grid units in the gentle slope area of ​​the mirror base, preventing the tilt angle of the lattice rods generated by subsequent mapping from being too small, introducing internal supports that cannot be removed. Finally, combined with the range of formable rod diameters of the lattice rods, the minimum size of the grid unit is set to be greater than 4 times the maximum design rod diameter. In this embodiment, the minimum grid size is set to 3.2mm. On the one hand, this ensures that the internal space of the grid is sufficient to accommodate the maximum design rod diameter, ensuring the porosity and lightweight efficiency of the lattice structure. On the other hand, it avoids excessively dense grids, preventing the lattice rod diameter generated after optimization from being lower than the minimum formable limit of the printer, avoiding problems such as rod breakage and weak connections during printing. Integrating the above parameter setting requirements, the grid size constraint rules are obtained.

[0070] Furthermore, based on the mesh topology constraint rules, mesh size constraint rules, and geometric boundary constraints of the lattice-filled design domain, the lattice-filled design domain is meshed to obtain the initial mesh model.

[0071] Specifically, taking the inner and outer skin geometric contours of the mirror mount lattice-filled design domain as the core boundary constraints, and strictly following the mesh topology constraint rules and mesh size constraint rules, the entire lattice-filled design domain is automatically meshed. During the meshing process, it is ensured that the mesh boundary nodes completely fit the geometric contours of the lattice-filled design domain, without any boundary deviation or node misalignment. Finally, an initial mesh model covering the entire lattice-filled design domain is generated.

[0072] Furthermore, the initial mesh model is optimized for boundary fit and manufacturability to obtain the mesh frame model.

[0073] Specifically, the initial mesh model is first subjected to boundary fit verification. The fit between the mesh boundary nodes and the geometric contour of the lattice-filled design domain is checked element by element. Abnormal mesh elements with boundary deviation or warping are removed. The positions of the mesh nodes at the boundaries are locally optimized and adjusted to ensure that all boundary meshes completely fit the skin geometry. Next, the initial mesh model is subjected to manufacturability verification. The mesh is checked element by element to see if it conforms to the mesh topology constraint rules and mesh size constraint rules. Abnormal mesh elements with excessive size, aspect ratio that does not meet the threshold, or mismatched topology type are screened out. The local area where the abnormal mesh is located is subjected to mesh re-partitioning optimization until all mesh elements meet the preset constraint requirements. Finally, after multiple rounds of verification and optimization, a mesh frame model is obtained that is fully adapted to the preset lattice unit cell topology features, completely fits the geometric boundary of the design domain, and fully meets the requirements of additive manufacturing process.

[0074] This application embodiment locks the mesh topology type, normal layer number, and element aspect ratio, ensuring a high degree of coordination between the spatial configuration of the mesh elements and the topological logic and size ratio of the preset lattice unit cells. This eliminates the risk of configuration distortion during subsequent lattice mapping from the geometric source, laying a core foundation for the generation of high-quality lattice structures. Mesh size constraints fully integrate the technological limits of additive manufacturing, limiting the mesh size boundaries from three core dimensions: maximum printing span, self-supporting critical safety angle, and the range of formable rod diameters. This avoids problems such as excessively long suspended rods, excessively small tilt angles, and rod diameters exceeding the range in subsequently mapped lattice components, mitigating printing defects such as melt pool collapse, inability to remove internal supports, and broken rods from the source, significantly improving the manufacturability of the lattice structure. Mesh generation is completed strictly following the geometric boundary constraints of the design domain, and optimization is performed through dual-dimensional verification of boundary fit and manufacturability. This ensures complete fit between the mesh boundary and the mirror mount skin contour, and guarantees that all mesh elements meet the preset constraint requirements, achieving boundary consistency and full-domain compliance in subsequent lattice mapping.

[0075] In some embodiments, the topological information of the lattice rod diameter optimization parameter set and the conformal lattice structure model are obtained respectively, and the topological information is processed into a three-dimensional solid model to obtain a lattice solid model that can be used for additive manufacturing. This includes: parsing the topological information of the conformal lattice structure model based on the lattice rod diameter optimization parameter set to obtain a lattice rod topology dataset.

[0076] Specifically, firstly, the optimized parameter set of the lattice rod diameter, which has been converged through iterative optimization, is analyzed to obtain the unique index number and optimized rod diameter parameter for each lattice rod. Then, the topological information of the conformal lattice structure model is analyzed, extracting the three-dimensional coordinate matrix of the node space covering the entire lattice filling design domain and the unit topological connection matrix recording the connection relationships of the rod endpoints. The three-dimensional coordinate matrix of the node space contains the three-axis spatial coordinates of all basic vertices and virtual nodes with unique indices, while the unit topological connection matrix records the two endpoint node indices and the unit information corresponding to each rod. Finally, the optimized rod diameter parameters are matched and bound one-to-one with the topological information of the corresponding rods, integrating them to obtain a lattice rod topology dataset containing node coordinates, rod connection relationships, and corresponding optimized rod diameter parameters, providing a complete data foundation for subsequent materialization processing.

[0077] Furthermore, based on the unit topology connection matrix, the node spatial coordinate matrix is ​​processed by topology connection to obtain the directed central axis.

[0078] Specifically, using the unit topology connection matrix as the sole data basis, the two endpoint node indices corresponding to each lattice member are identified one by one. The three-dimensional spatial coordinates of the corresponding endpoints are retrieved from the node spatial coordinate matrix. Taking the two endpoints as the start and end points, a continuous straight-line directed central axis is generated in space. This axis is the path reference for subsequent solidification sweep. Through the unified constraints of the unit topology connection matrix, it is ensured that all directed central axes are unbroken, misaligned, and intersecting, and are completely consistent with the topological logic of the conformal lattice structure model. Finally, a directed central axis system covering all lattice members is generated.

[0079] Furthermore, using the optimized rod diameter corresponding to the rod in the lattice rod diameter optimization parameter set as the cross-sectional feature, a three-dimensional sweep process is performed on the oriented central axis to obtain a three-dimensional cylindrical solid model of a single rod.

[0080] Specifically, the optimized rod diameter for each rod corresponding to the directional central axis is retrieved from the lattice rod diameter optimization parameter set. Using this optimized rod diameter as the diameter, a circular cross-sectional profile perpendicular to the directional central axis is generated. Using the directional central axis as the sweep path, the circular cross-sectional profile is swept along the path with equal cross-section throughout, transforming the one-dimensional axis into a three-dimensional solid with real physical thickness, thus obtaining a three-dimensional cylindrical solid model of a single rod. The sweeping process of all lattice rods is completed one by one, forming a spatial cylindrical array solid that corresponds one-to-one with the conformal lattice structure model.

[0081] Furthermore, a three-dimensional Boolean union operation is performed on the three-dimensional cylindrical solid model at the intersection of multiple rods to obtain a lattice solid model.

[0082] Specifically, based on the unit topology connection matrix, the node positions where all multiple lattice members intersect are identified, including the positions of basic vertices and virtual nodes. At each intersection node, a three-dimensional Boolean union operation is performed on the three-dimensional cylindrical solid models of all intersecting members. During the operation, the internal overlapping redundant volumes of multiple cylindrical solids at the intersection position are automatically calculated and eliminated, so that the multiple intersecting members are merged into a continuous and complete solid structure, avoiding problems such as solid interference, internal voids, and node breakage, and ensuring that the nodes of the entire lattice structure are continuous and the force transmission path is complete. After completing the Boolean operation of all nodes, a lattice solid model with overall continuity and no redundancy defects is obtained.

[0083] Furthermore, the surface mesh of the lattice solid model is discretized to obtain a lattice solid model suitable for additive manufacturing.

[0084] Specifically, the outer surface of the lattice solid model after Boolean operations is discretized into a mesh. The continuous three-dimensional surface of the solid model is discretized into a polyhedral mesh composed of a large number of uniformly sized and topologically continuous spatial triangular facets. This ensures that the discretized surface mesh has no broken surfaces, cracks, or reverse normal defects, and fully meets the reading requirements of additive manufacturing equipment. Finally, the discretized solid model is exported into the standard STL format to obtain a lattice solid model that can be directly used for subsequent layer slicing and additive manufacturing.

[0085] This application embodiment obtains a complete lattice member topology dataset by matching and analyzing the lattice topology information with the optimized rod diameter parameters. This ensures a one-to-one correspondence between the optimized rod diameter parameters and the topology information for each member, resolving the solidification deviation problem caused by parameter mismatch and ensuring complete consistency between the final solid model and the optimized design scheme. A directed central axis is generated based on the unit topology connection matrix, and the three-dimensional solidification of the members is completed through equal-section sweeping processing, accurately restoring the design form of the lattice structure and ensuring complete matching between the solid members and the design topology logic. Through three-dimensional Boolean union operations at the member intersection nodes, overlapping redundant volumes at the intersection positions are eliminated, allowing multiple members to merge into a continuous and complete solid structure. This ensures the global continuity of nodes and the integrity of the force transmission path in the entire lattice structure, avoiding structural performance degradation and printing defects caused by solid interference and node breakage. The solid model undergoes surface mesh discretization processing, and a standard STL format three-dimensional solid model is finally exported. This model can be directly adapted to the reading requirements of additive manufacturing equipment without secondary model repair, achieving seamless connection from the design model to the manufacturing model and significantly improving production efficiency.

[0086] In some embodiments, the lattice solid model, double-layer skin solid model, and flange reinforcing block solid model available for additive manufacturing are assembled and verified to obtain a three-dimensional model of the mirror mount. This includes: importing the lattice solid model, double-layer skin solid model, and flange reinforcing block solid model available for additive manufacturing into the same design space and performing benchmark matching to obtain an initial assembly positioning model.

[0087] Specifically, the lattice solid model available for additive manufacturing, along with the double-layer skin solid and flange reinforcement block solid pre-separated and extracted during the region division stage, are simultaneously imported into the same three-dimensional design workspace. Using the design datum origin of the mirror mount, the flange installation mating surface, and the inner and outer contour datum surfaces of the skin as matching datums, the three types of solids are precisely aligned in space to ensure that the outer boundary of the lattice solid is completely fitted with the inner wall mating surface of the double-layer skin solid, and that the non-design domain position of the flange reinforcement block corresponds completely with the non-design domain position of the mirror mount flange area, without any positional misalignment or excessive mating clearance. After completing the datum matching, an initial assembly positioning model with precise spatial alignment is obtained.

[0088] Furthermore, the initial assembly positioning model is subjected to global entity assembly fusion processing to obtain the initial assembly entity model.

[0089] Specifically, based on the benchmark matching results of the initial assembly positioning model, the entire model is subjected to full-domain solid assembly fusion processing, so that the boundary rods of the lattice entity are tightly fitted with the inner wall of the double-layer skin entity without gaps, and the flange reinforcement block is completely integrated with the flange area of ​​the double-layer skin entity. This ensures that the connection nodes of the three types of entities correspond one-to-one and fit tightly, without any problems of solid interference or misalignment, and finally integrates to form a complete initial assembly solid model.

[0090] Furthermore, the initial assembly entity model is subjected to geometric continuity, boundary closure, and structural integrity verification processes to obtain a defect identification dataset.

[0091] Specifically, three core verifications are performed on the initial assembly solid model: First, geometric continuity verification, which involves checking the connection positions of the lattice solids, double-layer skin solids, and flange reinforcement blocks segment by segment to identify defects such as misalignment, broken members, and discontinuous fit; second, boundary closure verification, which involves a full-area inspection of the entire outer surface of the model to identify closure defects such as surface cracks, open boundaries, and broken surfaces; and third, structural integrity verification, which involves a comprehensive scan of the model to identify integrity defects such as isolated facets, overlapping solids, and missing structures. All identified defects are classified and recorded according to type, location, and severity to form a complete defect identification dataset.

[0092] Furthermore, the defect identification dataset is corrected to obtain the assembly entity model.

[0093] Specifically, based on the defect information recorded in the defect identification dataset, each defect is individually corrected: for closed defects such as cracks and broken surfaces, surface patching is performed; for integrity defects such as overlapping surfaces, redundant entities, and isolated facets, cleanup and deletion are performed; for continuous defects such as misaligned connections and discontinuous bonding, position adjustment and bonding fusion are performed. After all defects are corrected, the model is initially verified to ensure that all identified defects have been corrected, resulting in an assembly entity model without obvious design or modeling defects.

[0094] Furthermore, the assembly entity model is subjected to a full-domain closed-loop verification process to obtain the overall three-dimensional model of the mirror mount.

[0095] Specifically, a full-scale review of the revised assembly entity model is conducted to re-verify the geometric continuity, boundary closure, and structural integrity of the model. The compliance of defect repair locations is carefully reviewed to ensure that the outer surface of the entire model is strictly closed, without any residual defects, and that the structure is continuous and complete. The connection between the lattice entity, the double-layer skin entity, and the flange reinforcement block is tight, fully meeting the design requirements and additive manufacturing model specifications. Finally, a complete 3D model of the mirror mount with a completely closed surface and a continuous and complete structure is obtained.

[0096] This application's embodiments, through unified design space import and benchmark matching processing, ensure precise spatial alignment of the lattice entities, double-layer skin entities, and flange reinforcing block entities, resolving issues of assembly misalignment and excessive fit clearances, and ensuring consistency between the mirror mount assembly accuracy and design requirements. Through full-domain entity assembly fusion processing, tight fit between the lattice entities and skin entities, and complete fusion of the flange reinforcing block and skin structure are achieved, ensuring reliable connections between mirror mount components and avoiding issues such as reduced structural stiffness and vibration / noise caused by connection gaps. Through multi-dimensional verification of geometric continuity, boundary closure, and structural integrity, various defects in the assembly model are comprehensively identified, and all defects are eliminated through targeted correction processing, avoiding printing failures and substandard product performance caused by modeling defects. Through full-domain closure verification processing, the final mirror mount overall 3D model has a completely closed surface and a continuous and complete structure, fully meeting the model specifications for additive manufacturing. It can be directly used for subsequent slicing and printing without secondary repair processing, ensuring the quality and design accuracy of the final product.

[0097] While this application provides the method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive labor. The order of steps listed in this embodiment is merely one possible execution order among many and does not represent the only execution order. In actual device or client product execution, the methods shown in this embodiment or the accompanying drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0098] like Figure 3 As shown in the illustration, this application also provides a computer-aided optimization design device 300 for a double-layer skin dot matrix lens mount. The device includes: The acquisition module 301 is used to acquire the mirror base structure, perform region division processing on the mirror base structure, and obtain the non-design domain and the lattice-filled design domain.

[0099] The processing module 302 is used to perform finite element mesh discretization on the lattice-filled design domain based on geometric boundary constraints and additive manufacturing process constraints to obtain a mesh frame model.

[0100] The processing module 302 is also used to perform lattice mapping and reconstruction processing on the mesh frame model based on the isoparametric transformation rules to obtain the conformal lattice structure model.

[0101] Module 303 is used to construct a lattice parameterized model. It extracts the geometric information of the conformal lattice structure model and the mesh frame model, respectively, and inputs the geometric information into the lattice parameterized model to obtain the lattice rod diameter optimization parameter set.

[0102] The acquisition module 301 is also used to acquire the topological information of the lattice rod diameter optimization parameter set and the conformal lattice structure model, respectively, and to perform three-dimensional solidification processing on the topological information to obtain a lattice solid model that can be used for additive manufacturing.

[0103] The processing module 302 is also used to assemble and verify the lattice solid model, double-layer skin solid and flange reinforcing block solid that can be used for additive manufacturing, to obtain the three-dimensional model of the mirror base.

[0104] The processing module 302 is also used to perform additive manufacturing preprocessing on the three-dimensional model of the mirror mount to obtain a process control file, and to perform additive manufacturing and post-processing on the mirror mount according to the process control file to obtain a double-layer skin dot matrix mirror mount.

[0105] Some modules in the apparatus described in this application can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0106] The apparatus or module described in the above embodiments can be implemented by a computer chip or physical entity, or by a product with a certain function. For ease of description, the above apparatus is described by dividing it into various modules according to their functions. When implementing the embodiments of this application, the functions of each module can be implemented in one or more software and / or hardware. Of course, a module that implements a certain function can also be implemented by combining multiple sub-modules or sub-units.

[0107] The methods, apparatus, or modules described in this application can be implemented in a computer-readable program code manner. The controller can be implemented in any suitable manner, such as a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of a memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code manner, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included within it for implementing various functions can also be considered as structures within the hardware component. Alternatively, the device used to implement various functions can be viewed as either a software module that implements the method or a structure within a hardware component.

[0108] This application also provides an apparatus, the apparatus comprising: a processor; a memory for storing processor-executable instructions; wherein, when the processor executes the executable instructions, it implements the method described in this application.

[0109] This application also provides a non-volatile computer-readable storage medium storing a computer program or instructions thereon, which, when executed, enables the method described in this application embodiment to be implemented.

[0110] Furthermore, in the various embodiments of the present invention, each functional module can be integrated into a processing module, or each module can exist independently, or two or more modules can be integrated into a single module.

[0111] The aforementioned storage media include, but are not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), Cache, Hard Disk Drive (HDD), or Memory Card. The memory can be used to store computer program instructions.

[0112] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary hardware. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, or it can be embodied in the process of data migration. The computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0113] The various embodiments described in this specification are presented in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. All or part of this application can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, mobile communication terminals, multiprocessor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0114] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of this application.

Claims

1. A computer-aided optimization design method for a double-layer skin dot matrix lens mount, characterized in that, include: Obtain the mirror base structure, and perform region division processing on the mirror base structure to obtain the non-design domain and the lattice-filled design domain; The lattice-filled design domain is discretized using finite element meshing based on geometric boundary constraints and additive manufacturing process constraints to obtain a mesh frame model. Based on the isoparametric transformation rule, the mesh frame model is subjected to lattice mapping and reconstruction to obtain a conformal lattice structure model. A lattice parameterized model is constructed, and the geometric information of the conformal lattice structure model and the mesh frame model is extracted respectively. The geometric information is then input into the lattice parameterized model to obtain the lattice rod diameter optimization parameter set. The topological information of the lattice rod diameter optimization parameter set and the conformal lattice structure model are obtained respectively, and the topological information is processed into a three-dimensional solid model to obtain a lattice solid model that can be used for additive manufacturing. The lattice solid model, double-layer skin solid model and flange reinforcing block solid model available for additive manufacturing are assembled and verified to obtain the three-dimensional model of the mirror base. The three-dimensional model of the lens mount is preprocessed for additive manufacturing to obtain a process control document. The lens mount is then subjected to additive manufacturing and post-processing according to the process control document to obtain a double-layer skin dot matrix lens mount.

2. The method according to claim 1, characterized in that, The construction of the lattice parameterized model involves extracting the geometric information of the conformal lattice structure model and the mesh frame model, respectively, and inputting the geometric information into the lattice parameterized model to obtain a set of lattice rod diameter optimization parameters, including: The node coordinate information, rod topology connection information, and element geometric information of the conformal lattice structure model are extracted and processed to obtain the lattice structure geometric information; The geometric information of the lattice structure is encoded and converted to obtain a standardized parameter dataset; The model was constructed by using the diameter of the lattice rod as the design variable and the mechanical properties, thermal stability and lightweight index of the mirror mount as the optimization objectives, resulting in a parametric lattice model. The standardized parameter dataset is input into the lattice parameterized model for iterative optimization and solution to obtain the lattice rod diameter optimization parameter set.

3. The method according to claim 1, characterized in that, The process of performing lattice mapping and reconstruction on the mesh frame model based on isoparametric transformation rules to obtain a conformal lattice structure model includes: The spatial coordinates of the basic vertices in the mesh frame model are extracted by traversal to obtain a three-dimensional spatial coordinate array; A unit topology connection matrix is ​​established based on the three-dimensional spatial coordinate array. The unit topology connection matrix is ​​used to record vertex index attribution, unit adjacency relationship and node connection rules. Based on the unit topology connection matrix, the basic vertices shared by adjacent units are topologically connected to obtain a set of conformal boundary rods. The three-dimensional spatial coordinate array is subjected to spatial parameterization interpolation to obtain virtual nodes; Based on the preset lattice unit cell topology logic and the unit topology connection matrix, the virtual node and the basic vertex of the corresponding unit are topologically connected to obtain the core load-bearing rod. The conformal boundary member set and the core load-bearing member are topologically integrated to obtain a complete lattice unit cell topology. Based on the unit topology connection matrix, the complete lattice unit cell topology is seamlessly spliced ​​across the entire domain through the shared nodes of adjacent grid units to obtain a conformal lattice structure model.

4. The method according to claim 1, characterized in that, The finite element mesh discretization of the lattice-filled design domain based on geometric boundary constraints and additive manufacturing process constraints yields a mesh frame model, including: The topology type, number of normal layers, and element aspect ratio of the finite element mesh are locked to obtain the mesh topology constraint rules; Based on the process constraints of the maximum printing span of additive manufacturing, the critical safety angle of self-support, and the range of rod diameters that can be formed by lattice rods, the upper limit of the size, the lower limit of the size, and the aspect ratio threshold of the finite element mesh are set to obtain the mesh size constraint rules. Based on the mesh topology constraint rules, the mesh size constraint rules, and the geometric boundary constraints of the lattice-filled design domain, the lattice-filled design domain is meshed to obtain an initial mesh model. The initial mesh model is subjected to boundary fit and manufacturability verification and optimization processing to obtain the mesh frame model.

5. The method according to claim 1, characterized in that, The process of acquiring the topological information of the lattice rod diameter optimization parameter set and the conformal lattice structure model, and performing three-dimensional solidification processing on the topological information to obtain a lattice solid model suitable for additive manufacturing includes: The topological information of the conformal lattice structure model is analyzed and processed based on the lattice rod diameter optimization parameter set to obtain the lattice rod topology dataset; The node spatial coordinate matrix is ​​processed by topological connection based on the unit topological connection matrix to obtain the directed central axis. Using the optimized rod diameter of the corresponding rod in the lattice rod diameter optimization parameter set as the cross-sectional feature, the directed central axis is subjected to three-dimensional sweeping processing to obtain a three-dimensional cylindrical solid model of a single rod. A 3D Boolean union operation is performed on the 3D cylindrical solid model at the intersection of multiple rods to obtain a lattice solid model; The surface mesh of the lattice solid model is discretized to obtain a lattice model suitable for additive manufacturing.

6. The method according to claim 1, characterized in that, The lattice model, double-layer skin solid, and flange reinforcing block solid available for additive manufacturing are assembled and verified to obtain a three-dimensional model of the mirror mount, including: The lattice solid model, double-layer skin solid model and flange reinforcing block solid model available for additive manufacturing are imported into the same design space and matched with the reference to obtain the initial assembly positioning model. The initial assembly positioning model is subjected to global entity assembly fusion processing to obtain the initial assembly entity model; The initial assembly entity model is subjected to geometric continuity, boundary closure, and structural integrity verification processes to obtain a defect identification dataset; The defect identification dataset is corrected to obtain the assembly entity model; The assembly entity model is subjected to a global closed-loop verification process to obtain the overall three-dimensional model of the mirror mount.

7. The method according to claim 2, characterized in that, The diameter of the lattice rods ranges from 0.65 to 0.85 mm.

8. A computer-aided optimization design device for a double-layer skin dot matrix lens mount, characterized in that, include: The acquisition module is used to acquire the mirror base structure, perform region division processing on the mirror base structure, and obtain the non-design domain and the lattice-filled design domain. The processing module is used to perform finite element mesh discretization on the lattice-filled design domain based on geometric boundary constraints and additive manufacturing process constraints to obtain a mesh frame model. The processing module is also used to perform lattice mapping and reconstruction processing on the mesh frame model based on isoparametric transformation rules to obtain a conformal lattice structure model. A construction module is used to construct a lattice parameterized model, extract the geometric information of the conformal lattice structure model and the mesh frame model respectively, and input the geometric information into the lattice parameterized model to obtain a set of lattice rod diameter optimization parameters; The acquisition module is also used to acquire the topological information of the lattice rod diameter optimization parameter set and the conformal lattice structure model respectively, and to perform three-dimensional solidification processing on the topological information to obtain a lattice solid model that can be used for additive manufacturing. The processing module is also used to assemble and verify the lattice solid model, double-layer skin solid and flange reinforcing block solid that can be used for additive manufacturing, to obtain a three-dimensional model of the mirror base. The processing module is also used to perform additive manufacturing preprocessing on the three-dimensional model of the lens mount to obtain a process control file, and to perform additive manufacturing and post-processing on the lens mount according to the process control file to obtain a double-layer skin dot matrix lens mount.

9. A computer device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 7.

Images