A structure topology optimization design method for block-oriented additive manufacturing

Abstract

The application discloses a kind of structure topology optimization design techniques for block additive manufacturing, preliminary block to topological configuration, each block is defined based on level set function φ, and each block is mapped by step function to step mapping, the overlapping area of each block after step mapping is excluded to obtain each topological configuration block based on the given topological configuration description function γ, the structure topological configuration physical density is obtained by density filtering and step function mapping, and based on topological configuration block and initial printing direction b, topological configuration physical density constructs auxiliary support control constraint;Cooperative optimization topological configuration description function γ, level set function φ and the control angle θ of printing direction b of each block i , iterative design is carried out using moving asymptote method until optimal design variable set is obtained. The multiple equipment processing of the optimized structure can be realized, and the manufacturing cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of modular additive manufacturing, and more specifically to a structural topology optimization design method for modular additive manufacturing. Background Technology

[0002] The design and manufacturing of high-end equipment is crucial for enhancing a nation's core competitiveness, and high-end manufacturing requires the support of advanced product design theories and manufacturing technologies. Topology optimization, as an optimization design method, can discover innovative structural forms within a design region under given constraints, playing a significant role in achieving lightweight, multifunctional, and high-performance structures. However, the geometric configurations of topology optimization results are complex and difficult to fabricate using traditional manufacturing processes. Designers often need to perform secondary design based on manufacturing technology and experience to meet manufacturability requirements, which often compromises the optimality of the structure.

[0003] Additive manufacturing (also known as 3D printing), as an advanced manufacturing technology, can create complex structures of arbitrary geometry by depositing material layer by layer onto a printing plane. Combining topology optimization and additive manufacturing allows for the integrated design and processing of complex industrial products. This technology has been widely used in the design and manufacturing of high-end components such as aero engines and aircraft antenna supports, and has enormous industrial application prospects, making it a current cutting-edge research hotspot internationally.

[0004] However, the processing speed and sized limits of existing single additive manufacturing equipment restrict the application of additive manufacturing technology in the overall manufacturing of large components and large industrial equipment, especially in the aerospace field. With the development of the Industrial Internet and network-based collaborative manufacturing, collaborative processing by multiple additive manufacturing equipment or robots is an effective way to manufacture large components. For example, Relativity Space in the United States plans to use Stargate, currently the world's largest metal 3D printer, to manufacture an entire rocket in 60 days. Stargate uses three printing robots to process components collaboratively to shorten the processing time. Each additive manufacturing equipment only needs to print component blocks that meet its size limitations, without increasing the size of the printing equipment to process large components. Multiple additive manufacturing equipment can also work simultaneously to reduce manufacturing time. This emerging modular additive manufacturing approach for large components poses challenges to design methodologies. It is necessary to consider the characteristics of multi-device collaborative additive manufacturing in the topology optimization design stage to achieve integrated design and processing of large components where "design is product". However, directly using traditional topology optimization structures without considering process constraints for modular additive manufacturing will lead to difficulties in modularization and difficulty in quantifying and controlling the auxiliary support for each block, thus requiring iterative design and increasing design and processing costs. Existing additive manufacturing modularization methods are mainly for simple structural forms. Such structures can be modularized with the help of the designer's experience and observation, but it is difficult to extend them to modular additive manufacturing of innovative configurations. Summary of the Invention

[0005] The purpose of this invention is to overcome the aforementioned defects or problems in the prior art and to provide a structural topology optimization design method for modular additive manufacturing.

[0006] To achieve the above objectives, the present invention and its preferred embodiments employ the following technical solutions, but the embodiments are not limited to the following solutions: Option 1, a structural topology optimization design method for modular additive manufacturing, includes the following steps: The topology is initially divided into blocks based on level set functions. Define each block and apply a step function to each block. Perform a step mapping, and exclude overlapping regions of each block after the step mapping to obtain each topological configuration block. ; Based on the given topological configuration description function The physical density of the structural topology is obtained through density filtering and step function mapping. And based on topological configuration, it is divided into blocks. and the initial printing direction For topological physical density Construct auxiliary support control constraints; topology configuration description function Used to describe the relative density of structures within the design area; Collaborative optimization topology description function Level set function and the printing direction of each block control angle The moving asymptote method is used for iterative design until the optimal set of design variables is obtained.

[0007] Option 2, based on Option 1, is based on the level set function. Defining each block involves the following steps: describing the block as a level set function. The contour lines, and the corresponding parameterized level set function Defined as:

[0008] in,

[0009]

[0010] in The coordinates are after the blocks are rotated. It is a level set function The center's position coordinates; These are the x-axis and y-axis side lengths of the zero level set; It's the tilt angle. The parameter p is the radius parameter of the ellipse-like shape, and p is an even number greater than or equal to 2.

[0011] Option 3, based on Option 2, applies a step function to each block. Performing a step mapping includes the following steps: based on the parameterized level set function Apply step mapping to the blocks, step function Defined as:

[0012] in, It is a parameter that controls the degree of step.

[0013] Option 4, based on Option 3, excludes overlapping regions of each block after step mapping to obtain each topological configuration block. Includes the following steps: Record For the first i The identification function for each block, for a given first to the second... i There are several blocks, including:

[0014]

[0015]

[0016]

[0017] .

[0018] Option 5, based on Option 4, is based on the given topology description function or design variables. The physical density of the structural topology is obtained through density filtering and step function mapping. And based on topological configuration, it is divided into blocks. and the initial printing direction For topological physical density The steps for constructing auxiliary support control constraints include: Obtain the topology description function To describe the relative density of structures within the design area; right The physical density of the structural topology is obtained through density filtering and step function mapping. ; The control constraints for the segmented auxiliary support are:

[0019] in, Given the critical value of the suspension angle, For printing direction, Physical density function of topological configuration The gradient; Defined as:

[0020] Where step function Defined as

[0021] Control the steepness of the step function near the critical value.

[0022] Option 6, based on Option 5, collaboratively optimizes the topology description function. Level set function and the printing direction of each block control angle The iterative design using the moving asymptote method until the optimal set of design variables is obtained includes the following steps: For the initialization structure configuration description function Blocking method and printing direction of each block The simulation analyzes the overall structural performance and the auxiliary support constraints of each block. Then, sensitivity analysis is performed, and the structural performance and the block auxiliary support constraints are calculated in relation to the topological configuration description function. The derivative of the algorithm is used to solve the optimization problem using the moving asymptote method, and the design variables are updated until the optimization algorithm converges.

[0023] Option 7, based on Option 3, Take 0.001.

[0024] Option 8, based on Option 5, the aforementioned ; =10.

[0025] As can be seen from the above description of the present invention and its preferred embodiments, compared with the prior art, the technical solution of the present invention and its preferred embodiments have the following beneficial effects due to the adoption of the following technical means: 1. Compared with existing technologies, this solution proposes a structural topology optimization design method for modular additive manufacturing, which initially divides the topology into blocks based on level set functions. Define each block and apply a step function to each block. Perform a step mapping, and exclude overlapping regions of each block after the step mapping to obtain each topological configuration block. Based on the given topology description function or design variables The physical density of the structural topology is obtained through density filtering and step function mapping. And based on topological configuration, it is divided into blocks. and the initial printing direction For topological physical density Construct auxiliary support control constraints; collaboratively optimize the configuration description function. Level set function and the printing direction of each block control angle The moving asymptote method is used for iterative design until the optimal set of design variables is obtained.

[0026] This scheme proposes a block description method based on parameterized level sets, which enables block-based topology configuration with a small number of parameters during optimization. It constructs block-based auxiliary support quantification and control constraints based on parameterized level sets and density gradients, enabling control over the amount of auxiliary support used and optimization of the printing direction during optimization. Combining the advantages of variable density methods and parameterized level set methods, it can collaboratively optimize structural topology configuration, block-based configuration, and printing direction.

[0027] In summary, this solution considers the modular approach and the amount of auxiliary support required during the modular additive manufacturing process in the design phase, fully leveraging the advantages of multi-equipment collaborative additive manufacturing. It enables multi-equipment collaborative processing of optimized structures, reducing the additive manufacturing cost of complex optimized structures. Attached Figure Description

[0028] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. 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.

[0029] Figure 1 This embodiment uses a topology-optimized structure with multi-device modular additive manufacturing. Figure 2 This is a parameterized description of the two-dimensional structure blocks in this embodiment; Figure 3 This embodiment, the level set function, and the corresponding block description; Figure 4 This is a description of the overall components and the block-based approach based on the level set function in this embodiment. Figure 5 In this embodiment, the block-based density gradient requires auxiliary support for identifying the overhanging surface; Figure 6 This is the topology optimization process for modular additive manufacturing in this embodiment; Figure 7 This describes the iterative process of optimizing the two-dimensional MBB beam in this embodiment. Figure 8 The optimization results for the two-dimensional MBB beam in this embodiment are as follows: segmentation, printing direction, and non-self-supporting surface; Figure 9 For the design of the three-dimensional cantilever beam in this embodiment: topology configuration, block division, and printing direction are optimized collaboratively. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are preferred embodiments of the present invention and should not be considered as excluding other embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0031] Unless otherwise expressly defined, the use of terms such as "first," "second," or "third" in the claims, description, and accompanying drawings of this invention is for distinguishing different objects and not for describing a specific order.

[0032] Unless otherwise expressly defined, in the claims, description, and accompanying drawings of this invention, the use of directional terms such as "center," "lateral," "longitudinal," "horizontal," "vertical," "top," "bottom," "inner," "outer," "upper," "lower," "front," "rear," "left," "right," "clockwise," and "counterclockwise" to indicate orientation or positional relationships is based on the orientation and positional relationships shown in the accompanying drawings and is only for the convenience of describing the invention and simplifying the description, and is not intended to indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore should not be construed as limiting the specific scope of protection of this invention.

[0033] Unless otherwise expressly defined, the terms "fixed connection" or "fixed connection" used in the claims, description and drawings of this invention should be interpreted broadly to refer to any connection in which there is no displacement or relative rotation relationship between the two parties, including non-removable fixed connection, detachable fixed connection, integral connection and fixed connection by other means or components.

[0034] In the claims, description and accompanying drawings of this invention, the terms "comprising," "having," and variations thereof are used to mean "including but not limited to."

[0035] See Figure 1 , Figure 1 As shown.

[0036] A structural topology optimization design method for modular additive manufacturing includes the following steps: The topology is initially divided into blocks based on level set functions. Define each block. Specifically, five design parameters can be used in two-dimensional problems ( This describes each block, thereby controlling its position, size, and orientation. Blocks are described as level set functions. The contour lines, and the corresponding parameterized level set function Defined as:

[0037] in,

[0038]

[0039] in The coordinates are after the blocks are rotated. It is a level set function The center's position coordinates; These are the x-axis and y-axis side lengths of the zero level set; It's the tilt angle, set. The parameter p is the radius parameter of the ellipse-like shape, which can control the realization of different block shapes. To ensure that the shape is closed, p is an even number greater than or equal to 2. yes The function whose center ( The point at () is the minimum value of the function, on the curve. Within the enclosed region, the function The value is negative outside the region and positive outside the region. Therefore, the partitioning can be described as a level set function. Regions exceeding a certain critical value, such as Figure 3 As shown.

[0040] Based on level set function The block boundary can be implicitly described as a high-dimensional level set function. The contour lines. By parameterizing the level set, the position, size, and orientation of the blocks can be controlled with a few parameters, which facilitates subsequent calculations.

[0041] In order to make the level set function Mapping to 0 / 1 achieves clear block boundaries and guarantees differentiability; each block is processed through a step function. Performing a step mapping specifically includes the following steps: based on the parameterized level set function Apply step mapping to the blocks, step function Defined as:

[0042] in, It is a parameter that controls the degree of step change, during the experiment. A value of 0.001 is acceptable. Based on parameterized level set functions. The blocks obtained by step mapping are as follows Figure 3 As shown.

[0043] Description functions for multiple blocks of the topological configuration Therefore, it is necessary to consider the overlap between each block to avoid repeatedly considering overlapping areas in structural performance design and fabrication. To describe the block range after excluding block overlap, let's denote... For the first i The identification function for each block. Assuming the block segmentation process is ordered, for a given block number from the first to the second... i There are several blocks, including:

[0044]

[0045]

[0046]

[0047] .

[0048] This process eliminates overlapping regions in the blocks after step mapping to obtain the topological configuration blocks. ; Figure 4 The paper demonstrates a parameterized level set function. The two-dimensional topological configuration is divided into blocks. It can be seen that there is no overlap between the blocks, and the union of the blocks constitutes the entire topological configuration.

[0049] Many additive manufacturing processes require the generation of support structures to assist in the fabrication of parts, preventing them from collapsing under their own weight during polymer additive manufacturing; or, in metal additive manufacturing, to avoid burning due to high-intensity laser power or bending due to residual thermal stress during material deposition. This embodiment proposes a block-based assisted support quantization control method based on parametric level sets and density gradients, which can collaboratively optimize the printing direction of individual blocks. .

[0050] Specifically, obtain the topology description function. Topological configuration description function Defined as the relative physical density of each finite element or node in the optimized structure, i.e., describing the relative density of the structure within the design region; based on a given topological configuration description function. The physical density of the structural topology is obtained through density filtering and step function mapping. Density filtering is used to improve the continuity and smoothness of variable distributions, thereby enhancing optimization results. The basic idea behind density filtering is to introduce a filter or smoothing function that maps the initial variables to a smooth, continuous domain, eliminating discontinuities. These smoothing functions are typically local; they determine the smoothness of the variables based on their relative position and distance from each cell.

[0051] And based on the initial printing orientation and topological configuration blocks For topological physical density Construct auxiliary support control constraints, with the block-based auxiliary support control constraints as follows:

[0052] in, Given a critical value for the suspension angle, in this embodiment, ; For printing direction, Physical density function of topological configuration The gradient; , It is mainly used to map non-self-supporting overhanging surfaces in structural topology design to 1, so that self-supporting overhanging surfaces can be obtained by constraining the upper limit of the integral after integration. Defined as:

[0053] Where step function Defined as

[0054] Controlling the steepness of the step function near the critical value, =10. Regions that do not meet the overhang angle constraint are marked as 1, and these are compared with the block identification function. Density gradient projection Multiply, and in the design area Integral within the inner boundary, the integral obtained This approximates the projected length of the overhanging surface to be supported within the printed plane. Therefore, through... The upper bound of the constraint integral can eliminate the need for supported overhangs within the block.

[0055] like Figure 5 As shown, based on the proposed auxiliary support quantification formula, a given printing direction can be identified. Define the overhanging surfaces required for each block. By integrating the overhanging surfaces across the entire area and controlling their maximum value, it can be ensured that each block can be printed without support.

[0056] Based on the proposed topology partitioning technology and modular additive manufacturing auxiliary support quantization control technology, this embodiment conducts topology optimization design for modular additive manufacturing. The optimization flowchart is as follows: Figure 6 As shown, the collaborative optimization topology description function in this embodiment Level set function Control parameters and printing direction of each block control angle The design is iteratively performed using the moving asymptote method until the optimal set of design variables is obtained. In this implementation, the objective function is to maximize the structural stiffness, while also considering material volume constraints and auxiliary support constraints for each block. The volume constraint refers to the ratio of material usage to the volume of the optimization region.

[0057] Specifically, for the initialization structure configuration description function Blocking method and printing direction of each block The simulation analyzes the overall structural performance and the auxiliary support constraints of each block. Then, sensitivity analysis is performed, and the structural performance and the block auxiliary support constraints are calculated in relation to the topological configuration description function. The derivative of the algorithm is used to solve the optimization problem using the moving asymptote method, and the design variables are updated until the optimization algorithm converges.

[0058] The iterative process of optimizing the structure of a two-dimensional MBB beam is as follows: Figure 7 As shown, this technique can optimize and converge to a 0 / 1 solution, finding a suitable printing direction for each block. Print direction here The lower segment's overhang surface is greater than a given critical value. ( Figure 8 This eliminates the need for auxiliary supports in additive manufacturing.

[0059] The optimization results of the three-dimensional cantilever beam are as follows: Figure 9 As shown. In 3D structural optimization design, this is used to describe the block division and printing direction. The design variables will increase accordingly. It can be seen that the optimized structure is divided into three blocks, each corresponding to a different printing direction. Print direction here The lower segment can be manufactured using supportless additive manufacturing.

[0060] The optimization results demonstrate that the proposed technique can automatically divide the topology into blocks and find the optimal printing direction for each block. The realization of modular, unsupported additive manufacturing can reduce the overall structural processing cost and has important application prospects in the lightweight and high-performance design of future advanced equipment.

[0061] This embodiment proposes a block description method based on parameterized level sets, which enables block-based topology configuration with a small number of parameters during optimization. A block-based auxiliary support quantization and control constraint based on parameterized level sets and density gradients is constructed, which can control the amount of block-based auxiliary support used and optimize the printing direction during optimization. Combining the advantages of the variable density method and the parameterized level set method, it can collaboratively optimize the structural topology configuration, block-based configuration, and printing direction.

[0062] In summary, this solution considers the modular approach and the amount of auxiliary support required during the modular additive manufacturing process in the design phase, fully leveraging the advantages of multi-equipment collaborative additive manufacturing. It enables multi-equipment collaborative processing of optimized structures, reducing the additive manufacturing cost of complex optimized structures.

[0063] The foregoing description of the specifications and embodiments is intended to explain the scope of protection of this invention, but does not constitute a limitation on the scope of protection of this invention. Modifications, equivalent substitutions, or other improvements to the embodiments of this invention or a portion thereof that can be obtained by those skilled in the art through logical analysis, reasoning, or limited experimentation, based on the teachings of this invention or the foregoing embodiments, in conjunction with common knowledge, general technical knowledge, and / or existing technology, should all be included within the scope of protection of this invention.

Claims

1. A structural topology optimization design method for modular additive manufacturing, characterized in that: The topology is initially divided into blocks based on level set functions. Define each block and apply a step function to each block. Perform a step mapping, and exclude overlapping regions of each block after the step mapping to obtain each topological configuration block. ; Based on the given topological configuration description function The physical density of the structural topology is obtained through density filtering and step function mapping. And based on topological configuration, it is divided into blocks. and the initial printing direction For topological physical density Construct auxiliary support control constraints; topology configuration description function Used to describe the relative density of structures within the design area; Collaborative optimization topology description function Level set function and the printing direction of each block control angle The moving asymptote method is used for iterative design until the optimal set of design variables is obtained.

2. The structural topology optimization design method for modular additive manufacturing as described in claim 1, characterized in that: Based on level set function Defining each block involves the following steps: describing the block as a level set function. The contour lines, and the corresponding parameterized level set function Defined as: in, in The coordinates are after the blocks are rotated. It is a level set function The center's position coordinates; These are the x-axis and y-axis side lengths of the zero level set; It's the tilt angle. The parameter p is the radius parameter of the ellipse-like shape, and p is an even number greater than or equal to 2.

3. The structural topology optimization design method for modular additive manufacturing as described in claim 2, characterized in that: And for each block, a step function is applied. Performing a step mapping includes the following steps: based on the parameterized level set function Apply step mapping to the blocks, step function Defined as: in, It is a parameter that controls the degree of step.

4. The structural topology optimization design method for modular additive manufacturing as described in claim 3, characterized in that: The overlapping regions of each block after step mapping are excluded to obtain each topological configuration block. Includes the following steps: Record For the first i The identification function for each block, for a given first to the second... i There are several blocks, including: 。 5. The structural topology optimization design method for modular additive manufacturing as described in claim 4, characterized in that: Based on the given topological configuration description function The physical density of the structural topology is obtained through density filtering and step function mapping. And based on topological configuration, it is divided into blocks. and the initial printing direction For topological physical density The steps for constructing auxiliary support control constraints include: Obtain the topology description function To describe the relative density of structures within the design area; right The physical density of the structural topology is obtained through density filtering and step function mapping. ; The control constraints for the segmented auxiliary support are: in, Given the critical value of the suspension angle, For printing direction, Physical density function of topological configuration The gradient; Used to constrain the upper bound of the integral; Defined as: Where step function Defined as Control the steepness of the step function near the critical value.

6. The structural topology optimization design method for modular additive manufacturing as described in claim 5, characterized in that: Collaborative optimization topology description function Level set function and the printing direction of each block control angle The iterative design using the moving asymptote method until the optimal set of design variables is obtained includes the following steps: For the initialization structure configuration description function Blocking method and printing direction of each block The simulation analyzes the overall structural performance and the auxiliary support constraints of each block. Then, sensitivity analysis is performed, and the structural performance and the block auxiliary support constraints are calculated using finite element analysis to describe the topological configuration. The derivative is then used to solve the optimization problem based on the moving asymptote method, and the topology description function is updated. Continue until the optimization algorithm converges.

7. The structural topology optimization design method for modular additive manufacturing as described in claim 3, characterized in that: Take 0.

001.

8. The structural topology optimization design method for modular additive manufacturing as described in claim 5, characterized in that: The ; =10.

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