Lightweight design method for thin-wall structure containing flow channel based on additive manufacturing

Abstract

The invention discloses a lightweight design method for a thin-wall structure containing a flow channel based on additive manufacturing, and belongs to the technical field of additive manufacturing, and the lightweight design method comprises the following steps: S100, analyzing functional requirements, and constructing a functional requirement model containing the flow channel; s200, a printing direction and additive manufacturing constraint conditions are set, topological optimization is executed on the function demand model, and a preliminary topological structure is obtained; s300, carrying out geometric reconstruction on a topological optimization result to obtain a three-dimensional model suitable for additive manufacturing; s400, carrying out parameter optimization design; s500, the section shape and size of the runner are optimized based on fluid performance requirements; and S600, additive manufacturing manufacturability inspection is conducted on the structure with the section shape and size optimized. And S700, the model obtained after additive manufacturing manufacturability optimization is analyzed and checked. The technical problems that in the prior art, the design requirement of a thin-wall structure containing a runner cannot be met, and the forming quality and the section shape of the inner surface of the runner are difficult to accurately control can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of additive manufacturing, and particularly to a lightweight design method for a thin-walled structure with a flow channel based on additive manufacturing. Background Art

[0002] In recent years, the rapid development of additive manufacturing technology has brought about a revolution in the design of complex structures. Additive manufacturing can achieve the layer-by-layer stacking construction of any complex geometric structure, and is particularly suitable for manufacturing thin-walled parts with complex internal cavities, lattice structures and flow channel networks, providing new technical support for lightweight and multi-functional integration. In particular, metal additive manufacturing technology has shown broad application prospects in aerospace engines, thermal management structures and high-precision equipment.

[0003] For the manufacturing of additive manufacturing thin-walled structures and complex flow channel parts, the patent with the patent number CN107321979A discloses a laser additive manufacturing method for a multi-support surface configuration for cavity thin-walled structural parts. The laser additive manufacturing technology is used to form a superalloy cavity thin-walled structural part, and the direction with the largest orthographic projection area of the structural part is selected as the additive manufacturing stacking direction; during the additive manufacturing process, the lower part of the cavity position of the part structure is manufactured by additive manufacturing. After the lower part of the cavity position is formed, a support structure of the same material is welded to the corresponding position of the formed part, and then, with this support structure as a support, additive manufacturing is continued on the outer surface of this support structure until the entire structural part is formed. The patent with the patent number CN119255544A discloses that an integrated thin-walled lattice cooling plate includes a hollow cold plate body. A cooling flow channel and a liquid inlet and a liquid outlet communicated with the inside of the cooling flow channel are arranged in the cold plate body. A hollow heat exchange body is filled in the cooling flow channel. By setting the position of the cold plate body except for the cooling flow channel as a hollow structure, the entire cold plate body can be made lightweight, and a hollow heat exchange body is arranged in the cooling flow channel, so that the contact surface between the coolant and the heat exchange body has a larger specific surface area, thereby making its heat exchange effect better.

[0004] However, the functional requirements of the thin-walled structure with complex flow channels are complex and there are many constraints. The above solutions only focus on the additive manufacturing process and the flow channel structure design respectively, and cannot meet the design requirements of the thin-walled structure with flow channels, and it is difficult to accurately control the forming quality and cross-sectional shape of the inner surface of the flow channel. Summary of the Invention

[0005] The present invention provides a lightweight design method for a thin-walled structure with a flow channel based on additive manufacturing, so as to solve the technical problems that the prior art cannot meet the design requirements of the thin-walled structure with a flow channel and it is difficult to accurately control the forming quality and cross-sectional shape of the inner surface of the flow channel.

[0006] According to one aspect of the present invention, a lightweight design method for a thin-walled structure with a flow channel based on additive manufacturing is provided, including the following steps: S100, functional requirement analysis, constructing a functional requirement model of the structure with a flow channel; S200, setting the printing direction and additive manufacturing constraint conditions, performing topology optimization on the functional requirement model to obtain a preliminary topological structure; S300, geometric reconstruction of the topology optimization result to obtain a three-dimensional model suitable for additive manufacturing; S400, parametric optimization design, taking the wall thickness, rib beam width, and rib beam thickness of the model obtained after geometric reconstruction as design variables, taking the minimum structural mass as the design goal, and taking the minimum compliance as the design constraint, and performing rib beam and wall thickness dimension optimization design on the topological thin-walled structure; S500, optimizing the cross-sectional shape and size of the flow channel based on fluid performance requirements, analyzing the influence of different flow channel cross-sectional shapes and different flow channel spacings on the coolant flow and heat dissipation efficiency through fluid mechanics simulation, and obtaining the optimal cross-sectional shape of the flow channel; S600, performing an additive manufacturing processability review on the structure with optimized cross-sectional shape and size, and performing additive manufacturing processability optimization according to the review results; S700, analyzing and checking the model after additive manufacturing processability optimization until the model meets all design performance indicators.

[0007] Optionally, step S200 includes the following steps: S210: Setting the printing direction and additive manufacturing process parameters, and setting the printing direction as the reference for overhang plane judgment according to the selected additive manufacturing equipment and part posture; S220: Introducing design constraints and process constraints, and performing topology optimization with design constraints and process constraints; S230, printing verification of characteristic parts, performing 3D printing tests on typical characteristic parts of the optimized structural design to verify process adaptability and printing effect.

[0008] Optionally, the design constraints in step S220 include maximum stress, maximum deformation, and natural frequency, and the process constraints include overhang angle constraint, maximum / minimum size constraint, and connectivity constraint.

[0009] Optionally, in step S220, the topology optimization for overhang angle constraint includes the following steps: S221, parameter initialization; S222, finite element analysis, performing mechanical simulation on the initial structure to obtain stress and deformation response results; S223, calculating compliance and sensitivity, calculating the compliance index of the structure, and obtaining the sensitivity information of each element to the objective function; S224, grid filtering, smooth the sensitivity distribution in topology optimization to eliminate local artifacts and numerical oscillations; S225, design variable solution, update the density variables of each grid cell according to the sensitivity information and optimization algorithm to complete one iteration; S226, determine whether the manufacturing constraint accuracy is satisfied. If not, return to S222. If satisfied, proceed to the next step; S227, overhang surface detection, analyze the surface normal angle of the current design result to identify the area with an angle less than the critical angle as a potential overhang surface; S228, explicit self-supporting processing, remove the shape of the potential overhang area through an explicit constraint method and perform filtering on the lower boundary identification; S229, determine whether the accuracy and performance indicators of the current structure meet the requirements after adding the overhang angle constraint. If not, return to S222. If satisfied, output the final design result.

[0010] Optionally, in step S500, for long holes or curved pipes with an aperture greater than φ8mm, the cross-sectional shape is optimized to a water droplet shape, and the optimization formula is as follows:

[0011] In the formula, R is the radius of the cross-sectional circle of the original flow channel, and R1 is the radius of the circle of the water droplet shape.

[0012] Optionally, in step S200, for functional regions in the structure that include flow channels, mounting platforms, assembly threaded holes, or mounting holes, a distributed topology optimization strategy or a step-by-step topology optimization strategy is adopted; The distributed topology optimization strategy divides the overall structure into multiple design sub-regions, extracts the loads and boundary conditions of each sub-region respectively, and performs independent topology optimization on each sub-region; The step-by-step topology optimization strategy divides the design goal into multiple gradient goals according to different degrees of optimization, starts from the lowest goal among the multiple gradient goals, and gradually iterates to the final global optimization goal to achieve hierarchical optimization control of complex structures.

[0013] Optionally, in step S300, when geometric reconstruction is performed on the structure after topology optimization, a reconstruction method based on PolyBURBS is used to convert the stl model into a continuously manufacturable three-dimensional model, and within the structure, according to the mechanical performance requirements and process constraints, the solid regions retained by the overhang angle limit are replaced with a lattice structure with a preset cell type and parameters to further reduce the structure weight while ensuring formability.

[0014] Optionally, step S100 includes the following steps: S110. Establish a functional requirement model based on the usage environment, load conditions, and functional requirements; S120. Conduct mechanical and thermal finite element analyses on the initial structure to identify key stress-bearing areas, stress distributions, stiffness distributions, and temperature distributions; S130. Conduct flow simulations for functional areas containing flow channels under different shapes, sizes, and layouts to obtain flow velocity, pressure, and heat transfer characteristic parameters; S140. Based on the structural and fluid analysis results, identify design areas driven by functions to provide a basis for subsequent structural optimization.

[0015] Optionally, step S600 includes the following steps: Identify removable support areas and non-removable support areas in the structure, and optimize the structure to reduce the existence of non-removable supports; Check whether there are closed or semi-closed cavities in the structure, determine whether they will cause powder to be unable to be discharged, and modify the corresponding areas of the structure to ensure cleanability.

[0016] Optionally, step S700 includes the following steps: S710. Re-check the functional simulation analysis of the model to verify whether its mechanical response, thermal stress, or flow performance under the target conditions meets the set indicators; S720. Manufacture test pieces with typical characteristics based on the structure, and apply equivalent loads or boundary conditions for performance test verification; S730. If the simulation results or test results do not meet the performance requirements, adjust the parameters and modify the structure of the optimized model according to the deviation results, and re-perform the verification until all design performance requirements are met.

[0017] In summary, the present application includes at least one of the following beneficial technical effects: In step S100 of the present invention, through the systematic analysis of the use environment, load conditions and functional requirements, a functional model is constructed that not only includes the thin-walled structure form but also incorporates the fluid performance requirements, providing a basic support for the subsequent collaborative optimization of the structure and the flow channel; in step S200, the printing direction and typical additive manufacturing process constraints are introduced and directly incorporated into the topology optimization process, so that the obtained preliminary structure can avoid generating difficult-to-manufacture morphological structures while meeting the mechanical objectives, making up for the shortcoming that the results of traditional topology optimization cannot be directly printed; in S300, high-quality surface modeling is performed on the STL results through geometric reconstruction methods, and combined with the characteristics of additive manufacturing, it is converted into a CAD model, improving the subsequent parametric controllability of the structure; in S400, optimization design is carried out for key parameters such as wall thickness and rib beams to achieve size-level lightweighting based on load and stress distribution; in S500, through the combination of various flow channel cross-sectional shapes and spacings for fluid simulation, the flow velocity distribution, pressure loss and heat transfer efficiency inside the flow channel are accurately obtained to ensure that the flow channel cross-section not only meets the functional requirements but also has good forming stability; in S600, a process review mechanism is further introduced to automatically identify uncleanable closed cavities and difficult-to-remove support structures, and the model is fine-tuned according to the results, thereby improving the practical manufacturability of the model; finally, in S700, a dual-path verification mechanism of simulation and experiment is used to ensure that the multi-objective performance of the final model meets the requirements, and feedback to the previous parameters for fine-tuning when necessary, forming an optimization closed-loop; the overall solution establishes a multi-round collaborative coupling optimization and review mechanism among the structure-channel-process, solving the bottleneck problems of the separation of structure and flow channel design, difficult fine control of the cross-sectional shape and poor process accessibility in the prior art, and improving the design reliability and manufacturing quality of thin-walled structures with complex flow channels in the additive manufacturing scenario.

[0018] In addition to the purposes, features and advantages described above, the present invention has other purposes, features and advantages. The present invention will be further described in detail below with reference to the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings forming a part of this application are used to provide a further understanding of the present invention. The schematic embodiments and descriptions thereof of the present invention are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: Figure 1 is a flowchart of the lightweight design method for a thin-walled structure with a flow channel based on additive manufacturing according to the present invention; Figure 2 is a flowchart of the topology optimization algorithm for the overhang angle constraint facing additive manufacturing according to the present invention; Figure 3 is a sectional topology model of the air intake casing; Figure 4 is a solid support filling lattice of the air intake casing; Figure 5For the comparison between the circular flow channel and the water droplet-shaped flow channel of the intake casing; Figure 6 It is a schematic diagram of the optimized flow channel of the intake casing. Specific implementation manners

[0020] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, the present invention can be implemented in many different ways defined and covered by the following.

[0021] The following combines the attached Figure 1-6 Further detailed description will be made on this application.

[0022] The embodiment of this application discloses a lightweight design method for a thin-walled structure with a flow channel based on additive manufacturing.

[0023] Referring to Figure 1 , the present invention proposes a lightweight design method for a thin-walled structure with a complex flow channel based on additive manufacturing. This method integrates structural topology optimization, lattice structure filling, fine design of the flow channel cross-section, adaptation of manufacturing process constraints, and closed-loop verification of simulation tests, and constructs a complete design-manufacturing integration process, significantly improving the forming performance and design freedom of the thin-walled structure with a flow channel.

[0024] The overall process of this method includes the following seven main steps: It includes the following steps: S100, Functional requirement analysis, constructing a functional requirement model with a flow channel; S200, Setting the printing direction and additive manufacturing constraint conditions, performing topology optimization on the functional requirement model, and obtaining a preliminary topological structure; S300, Geometric reconstruction of the topology optimization result to obtain a three-dimensional model suitable for additive manufacturing; S400, Parameter optimization design, taking the wall thickness, rib beam width, and rib beam thickness of the model obtained after geometric reconstruction as design variables, taking the minimum structural mass as the design goal, and taking the minimum compliance as the design constraint, and performing rib beam and wall thickness size optimization design on the topological thin-walled structure; S500, Optimizing the cross-section shape and size of the flow channel based on fluid performance requirements, analyzing the coolant flow and heat dissipation efficiency of different flow channel cross-section shapes and different flow channel spacings through fluid mechanics simulation, and obtaining the optimal cross-section shape of the flow channel; S600, Conducting an additive manufacturing processability review on the structure with optimized cross-section shape and size, and performing additive manufacturing processability optimization according to the review results; S700, Analyzing and checking the model after additive manufacturing processability optimization until the model meets all design performance indicators.

[0025] Through the complete design process from S100 to S700, the present invention gradually realizes the lightweight modeling, optimization and process adaptation of the thin-walled structure with a flow channel, and solves the problems in the prior art that it is difficult for the thin-walled structure to meet the complex flow channel integrated design and it is difficult to control the forming quality of the flow channel cross-section. Specifically, S100 constructs a functional requirement model with a flow channel through functional requirement analysis, clarifies the design objectives and structural functional areas, and provides a basis for subsequent optimization; S200 sets the printing direction and additive manufacturing constraint conditions, performs topology optimization on the functional model, and obtains a preliminary topological structure that takes into account both structural performance and manufacturing process feasibility; S300 performs geometric reconstruction on the basis of topology optimization, and converts the optimization result into a three-dimensional model suitable for additive manufacturing; S400 takes the minimum structural mass as the objective and the minimum flexibility as the constraint, and optimizes the parameters such as wall thickness, rib beam width and thickness in the geometric reconstruction model to further improve the lightweight effect; S500 optimizes the cross-sectional shape and size of the flow channel based on the fluid performance requirements, and analyzes the influence of different cross-sectional shapes and spacings on the coolant flow and heat dissipation efficiency through fluid simulation, so as to determine the optimal cross-sectional form; S600 conducts an additive manufacturing processability review on the optimized structure, and performs processability optimization according to the review results, and identifies and adjusts the structural areas that affect the printing quality; S700 analyzes and checks the model after processability optimization to ensure that the structure finally meets all design performance indicators. By sequentially executing the above steps, a lightweight design method for a thin-walled structure oriented to additive manufacturing and capable of effectively controlling the cross-sectional shape and inner surface quality of the flow channel is formed.

[0026] Step S100 includes the following steps: S110, establishing a functional requirement model based on the use environment, load conditions and functional requirements; S120, performing mechanical and thermal finite element analysis on the initial structure to identify the key stress-bearing areas, stress distribution, stiffness distribution and temperature distribution; S130, performing flow simulations under different shapes, sizes and layouts on the functional area including the flow channel to obtain flow velocity, pressure and heat transfer characteristic parameters; S140, based on the structural and fluid analysis results, identifying the design areas driven by functions to provide a basis for subsequent structural optimization.

[0027] As the starting link of the overall lightweight design process of the present invention, step S100 plays a role in converting the actual working conditions and functional requirements into a quantifiable and solvable design input model, and is the basis for realizing the collaborative design of structure-function-process. It specifically includes four sub-steps: In S110, information such as the structural usage environment, loading conditions, and functional requirements is collected and analyzed by the system to establish a functional requirements model. Among them, the usage environment includes, but is not limited to, temperature fields, pressure fields, fluid conditions, etc.; the loading conditions include conventional boundary conditions such as static loads, dynamic loads, and thermal loads; and the functional requirements cover target performance indicators such as overall stiffness, mass constraints, flow functions in specific regions, and heat conduction requirements. This model not only puts forward requirements for the structural shape but also makes restrictive definitions for functional regions such as flow channel arrangements, channel connectivity, and boundary interfaces, constituting the boundary framework for subsequent optimization.

[0028] In S120, a finite element analysis is performed on the initial structure to identify the key feature responses of the structure from two dimensions: mechanics and thermotics. Specifically, indicators such as stress distribution, stiffness distribution, and temperature distribution are obtained to find weak regions with high stress concentration, easily deformable parts with low structural stiffness, and potential thermal failure points with large thermal gradients. These analysis results help set reasonable design variable regions and non-design protected areas in the subsequent topology optimization process and assist in identifying whether it is necessary to set local size lower limits or stiffness enhancement requirements.

[0029] In S130, multi-scenario fluid simulations are performed on the structural regions containing internal flow channels to compare and evaluate the performance of different flow channel shapes, cross-sectional dimensions, and layout methods under key indicators such as flow velocity distribution, flow resistance change, and heat transfer efficiency. This step particularly focuses on the trade-off relationship between functional satisfaction and design adjustability of different flow channel schemes to ensure that the selected scheme has room for parametric design and optimization while meeting the performance requirements.

[0030] Finally, in S140, based on the structural mechanical responses and fluid performance results obtained in S120 and S130, a function-driven regional division of the entire design domain is carried out to identify the structural regions that need to be optimized, the functional interface regions that should be retained, and the designable regions. This division not only provides the basic geometric boundary for topology optimization but also lays a clear regional foundation for subsequent parameter optimization and flow channel refinement.

[0031] Step S200 includes the following steps: S210: Set the printing direction and additive manufacturing process parameters. According to the selected additive manufacturing equipment and part attitude, set the printing direction as the reference for overhang plane judgment; S220: Introduce design constraints and process constraints and perform topology optimization with design constraints and process constraints; S230: Verify the printing of characteristic parts. Conduct 3D printing tests on typical characteristic parts of the optimized structural design to verify the process adaptability and printing effect.

[0032] Step S200 is the core stage of structural optimization after the completion of the functional requirement model. Its purpose is to generate a preliminary topological structure with actual manufacturability while ensuring that the structure meets the usage functions by introducing additive manufacturing process conditions and structural performance constraints. This step includes three key subprocesses: printing direction setting, constraint embedding optimization process, and process verification of the results, ensuring close coordination between design and manufacturing capabilities.

[0033] In S210, according to the specific type of additive manufacturing equipment and the part installation posture, clarify the placement method of the component on the printing platform, and set the printing direction as the benchmark for overhang judgment. This operation directly determines the basic direction for subsequent overhang angle judgment, support structure generation strategy, and forming quality control. Since additive manufacturing is a layer-by-layer stacking process, the relationship between the printing direction and the structural inclination angle will affect whether additional support is required for local structures. Therefore, the printing direction must be solidified before the start of topology optimization to ensure the formation of self-supporting or supportable geometric shapes during the optimization process. In addition, this step also sets relevant process parameters, such as the allowable minimum feature size, support removable angle threshold, powder cleaning directivity, etc., to guide subsequent process constraint modeling.

[0034] In S220, based on the functional requirement model established in S100, construct the objective function and constraint conditions for topology optimization, and introduce the key process constraints in the additive manufacturing process. Design constraints include structural performance indicators such as maximum stress, maximum deformation, and natural frequency, ensuring that the results after topology optimization meet the expectations in terms of load-bearing capacity and structural stiffness. In terms of process constraints, they include overhang angle constraints, maximum / minimum structure size constraints, and structural connectivity constraints. The overhang angle constraint is used to avoid generating inclined surface structures that are difficult to self-support during the forming process, the maximum / minimum size constraint is used to prevent details from not being printable or large surfaces from collapsing, and the connectivity constraint is used to avoid generating suspended structures or closed cavities, thereby ensuring the complete manufacturability of the topological structure. During the topology optimization process, these structure-process hybrid constraints are embedded into the solution algorithm of the design variables, usually using SIMP, ESO, or sensitivity-based gradient optimization methods, dynamically adjusting the density distribution during the iteration process, and outputting a structural layout that takes into account both performance and printability.

[0035] In S230, to verify the adaptability of the topology-optimized structure in the actual manufacturing process, several representative structural feature sections are selected as feature parts for 3D printing tests. These feature parts usually include overhanging structures, connection interfaces, runner corners, or the thinnest regions of the structure, and are the key units reflecting the overall forming difficulty and printing quality. Through actual printing measurements, the influence of process parameters such as the surface quality, forming error, and boundary transition continuity of the structure on the actual printing quality can be visually verified, and it can be evaluated whether the support structure is reasonably set, whether the corners are clearly formed, and whether the dimensional accuracy meets the expected design requirements. If the printing results of the feature parts show problems such as severe support dependence, deteriorated lower surface quality, or insufficient structural accuracy, feedback can be made to S210 or S220 based on this to adjust the printing direction setting or constraint parameters, forming a front-to-back closed-loop design correction mechanism.

[0036] The design constraints in step S220 include maximum stress, maximum deformation, and natural frequency, and the process constraints include overhanging angle constraints, maximum / minimum size constraints, and connectivity constraints. The maximum stress, maximum deformation, and natural frequency in the design constraints control the strength, safety, and dynamic performance of the structure during use, preventing structural failure or insufficient stiffness caused by excessive material reduction; while the overhanging angle constraint in the process constraints is used to avoid generating structural surfaces that require a large amount of support or are difficult to form, the maximum / minimum size constraints prevent details from being too small to print or the structure from being too large and collapsing, and the connectivity constraints ensure that all parts of the structure remain integrally coherent during printing, without forming isolated islands or closed cavities, thereby improving the manufacturability and one-time forming success rate of the optimized structure.

[0037] In step S220, the topology optimization for overhanging angle constraints includes the following steps: S221, parameter initialization; S222, finite element analysis, performing mechanical simulation on the initial structure to obtain stress and deformation response results; S223, calculating compliance and sensitivity, calculating the compliance index of the structure, and obtaining the sensitivity information of each element to the objective function; S224, mesh filtering, smoothing the sensitivity distribution in the topology optimization to eliminate local artifacts and numerical oscillations; S225, solving design variables, updating the density variables of each mesh element according to the sensitivity information and the optimization algorithm to complete one iteration; S226, judging whether the manufacturing constraint accuracy is met. If not, return to S222. If so, proceed to the next step; S227, overhanging surface detection, analyzing the surface normal angle of the current design result to identify regions with an angle less than the critical angle as potential overhanging surfaces; S228, Explicit self - support processing, shape removal of potential overhanging regions through explicit constraint methods, and filtering for lower - boundary recognition; S229, Determine whether the accuracy and performance indicators of the current structure meet the requirements after adding overhanging - angle constraints. If not, return to S222; if so, output the final design result.

[0038] The topology - optimization process for overhanging - angle constraints in step S220 aims to actively identify and control the regions in additive manufacturing that are prone to forming overhanging structures during the optimization process, ensuring that the finally generated topology structure has good self - supportability and manufacturability. This process first performs parameter initialization in S221 to clarify the optimization objectives, boundary conditions, and process parameters. Subsequently, in S222, the stress and deformation responses of the initial structure under load are obtained through finite - element analysis, providing a basis for structural - performance evaluation. S223 calculates the structural compliance and sensitivity to identify the influence degree of each element on the objective function, serving as the basis for optimization adjustment. Then, S224 performs mesh filtering on the sensitivity - distribution results to remove numerical oscillations and artifacts, enhancing the stability and physical rationality of the optimization process. In S225, combined with sensitivity information and optimization algorithms, the design variables are solved to update the structural - density distribution, forming the result of one - time topology iteration. S226 determines whether the result of this round of iteration meets the basic accuracy requirements of manufacturing constraints. If not, return to S222 for re - iteration. Once the preliminary process - accuracy requirements are met, in S227, the normal - angle analysis of the structure surface is performed to detect whether there are overhanging regions with an angle less than the preset threshold (such as 45°) with the printing direction. In S228, through explicit self - support processing means, the morphology of these potential overhanging surfaces is adjusted or penalty - constrained, and combined with lower - boundary recognition technology to optimize the bottom - support connectivity of the structure, further improving the printing feasibility. Finally, in S229, it is evaluated whether the performance indicators and manufacturing accuracy of the structure meet the standards after adding overhanging - angle constraints. If they still do not meet the requirements, return to the previous steps for continued iteration; if they meet the requirements, output the final design result. This process realizes the deep integration of additive - manufacturing constraints and structural optimization by embedding the overhanging - angle limit into the main loop of topology optimization, avoiding the problem that traditional topology - optimized structures are difficult to manufacture due to excessive overhanging surfaces during the printing process from the source, and improving the practicality and manufacturability of the design results.

[0039] In step S200, for the functional regions in the structure that include flow channels, mounting platforms, assembly threaded holes or mounting holes, a distributed topology optimization strategy or a step-by-step topology optimization strategy is adopted; the distributed topology optimization strategy is to divide the overall structure into multiple design sub-regions, extract the loads and boundary conditions of each sub-region respectively, and perform independent topology optimization on each sub-region; the step-by-step topology optimization strategy is to divide the design objectives into multiple gradient objectives according to different degrees of optimization, start from the lowest objective among the multiple gradient objectives, and gradually iterate to the final global optimization objective to achieve hierarchical optimization control of complex structures.

[0040] In step S200, to solve the problems of unbalanced structural distribution, non-convergent optimization or non-manufacturable results that are prone to occur in the overall topology optimization of thin-walled structures with complex functional regions, the present invention introduces a distributed topology optimization strategy and a step-by-step topology optimization strategy to improve the optimization efficiency, structural rationality and directional adaptability of functional regions, and is particularly suitable for structural design tasks including multi-functional integrated parts such as flow channels, mounting platforms, assembly threaded holes or mounting holes.

[0041] Among them, the distributed topology optimization strategy is applicable to the situation where the structural morphology is complex and the distribution of functional regions is clear. This strategy divides the overall structure into several design sub-regions, and each sub-region independently extracts loads and boundary conditions according to its functional attributes. For example, the flow channel region is mainly based on the internal fluid pressure, the mounting platform focuses on structural stiffness and stability, and the area around the threaded hole pays attention to local strength and connection force transmission ability. Performing topology optimization on these sub-regions separately can avoid the phenomenon of performance target conflicts or local optimization being ignored during global unified optimization. At the same time, this strategy allows different constraint models or weight factors to be adopted in different sub-regions, so as to achieve spatial differential regulation of structural performance. After optimization, the results of each sub-region are geometrically patched and coordinated to form a complex structural topology that meets local functions and has overall performance.

[0042] The step-by-step topology optimization strategy aims at the problems of large span of optimization objectives, drastic morphological changes and difficulty in converging in one step. By decomposing the global design objectives into several gradient objectives (such as 20%, 50%, 80%, 90%, 100% objective levels), the topology optimization process is gradually advanced. In each stage, first perform topology optimization with low constraints or low-intensity objectives to obtain a preliminary feasible structural distribution, and then tighten the objectives or add more constraint conditions on this basis to gradually approach the global optimal solution. This strategy can effectively reduce the optimization search space, improve the stability and physical interpretability of structural evolution, and avoid problems such as structural collapse, connection fracture or morphological mutation during the direct optimization process, and is particularly suitable for dealing with scenarios where the fluid path coupling is significant and the structural support boundary is complex in thin-walled structures with flow channels.

[0043] In step S300, when geometric reconstruction is performed on the topologically optimized structure, a reconstruction method based on PolyBURBS is used to convert the stl model into a continuously manufacturable three-dimensional model. According to the mechanical property requirements and process constraints inside the structure, the solid regions retained due to the overhang angle limit are replaced with a lattice structure having a preset cell type and parameters, so as to further reduce the structure weight while ensuring formability.

[0044] Specifically, the topologically optimization process usually outputs a triangular mesh model (STL) generated based on a density field. This model has problems such as discontinuous surfaces, local roughness, and non-closed topologies, making it difficult to directly apply to subsequent process preparation and additive manufacturing path planning. Therefore, in S300, the PolyBURBS method is used for geometric reconstruction, and through a spatially continuous modeling method based on a local reconstruction function, the conversion from the STL mesh to a high-smoothness solid model is realized. The PolyBURBS method can quickly generate a surface structure that meets the requirements of engineering manufacturing while maintaining the morphological characteristics of the original optimized structure, improving the operability and precision control ability of the geometric model, and solving the problems of low reconstruction efficiency and unstable results in traditional CAD software.

[0045] After the geometric reconstruction is completed, for the solid regions retained due to process limitations in the topology optimization stage, the present invention further introduces a lattice structure filling strategy. Such retained regions generally do not bear the main structural loads, and their existence is mainly used to meet the processability requirements of self-supporting forming. If they continue to exist as solid structures, it will cause unnecessary material waste and weight increase. Therefore, in combination with the structural stress analysis results and the process forming path, the present invention uses a preset lattice structure for alternative filling in these non-critical stress-bearing regions. The selected lattice structure can be in the form of a tetrahedral lattice, honeycomb unit, or metamaterial structure, etc. Its parameters are differentially set according to the stress distribution and forming direction of different regions to achieve local adaptation of multi-objective performances such as load-bearing capacity, heat conduction, and formability. This treatment not only greatly reduces the structure weight, but also optimizes the internal space utilization rate, improves the heat conduction ability and powder cleaning efficiency without damaging the overall stiffness and manufacturing feasibility. Compared with the traditional fully solid structure model, this reconstruction-filling scheme better fits the advantages of additive manufacturing technology, can achieve the coordinated matching of complex morphologies and performance requirements, and significantly improves the structural lightweight level and printing success rate.

[0046] In step S400, after geometric reconstruction is completed, parametric optimization design is carried out to refine and optimize key geometric parameters such as wall thickness, rib beam width, and rib beam thickness in the model. The purpose is to further reduce the structural mass and improve local performance while maintaining the overall structural form unchanged. The specific approach is to set these parameters as design variables, with the minimization of structural mass as the optimization goal and the minimization of compliance as the design constraint. By combining parametric modeling and finite element simulation analysis, an optimization model is constructed and solved through multiple rounds of iteration to gradually adjust the local dimensions of the structure, ensuring the removal of redundant materials without reducing stiffness and load-bearing capacity, thereby achieving higher-precision lightweight control. This process effectively compensates for the deficiencies of topology optimization in detail control and improves the comprehensive performance and manufacturing feasibility of the structure.

[0047] For existing additive manufacturing processes, especially SLM, small abnormal lower surfaces will appear in φ8mm round holes, and the abnormal area on the lower surface of φ9 - 10mm horizontal holes is further enlarged. Therefore, in general, when the hole diameter is greater than φ8mm, supports need to be added to ensure the printing forming effect. However, for long holes or curved pipes, the internal supports are basically impossible to remove. In response to this situation, the shape of the flow channel needs to be designed as a teardrop-shaped hole, ellipse, or rhombus, and the corners inside the hole are chamfered to avoid stress concentration. In step S500, the cross-sectional shape of the flow channel of the air intake casing with a diameter greater than 8mm is optimized to a water droplet shape, increasing the degree of fluid turbulence and cross-sectional area while ensuring process feasibility, and improving the heat exchange efficiency. At the same time, the outer shape of the flow channel is adjusted to a conformal water droplet cross-section to ensure the wall thickness of the flow channel to meet the design requirements for pressure bearing inside the flow channel. Step S600 includes the following steps: identifying the support-removable areas and non-removable areas in the structure and optimizing the structure to reduce the presence of non-removable supports; checking whether there are closed or semi-closed cavities in the structure, judging whether they will cause powder discharge problems, and modifying the corresponding areas of the structure to ensure cleanability.

[0048] Step S600 mainly conducts an additive manufacturing processability review and structural adjustment on the structure after topology optimization and parametric optimization to ensure that the designed thin-walled structure has good manufacturability and cleanability during the actual printing process, thereby avoiding printing failures or functional defects caused by insufficient process adaptability. This step includes two core links, which analyze and optimize the removability of the support structure and the internal powder cleaning problem respectively.

[0049] First, in the process of identifying removable support areas and non-removable support areas, the system classifies and judges all areas that need support based on the printing direction and the local morphology of the structure. Removable support areas are usually located in external open areas or accessible positions, and their support structures can be removed mechanically or chemically after printing; while non-removable support areas include supports in deep cavities, long holes, bends or local confined spaces. Once formed, such structures are often difficult to remove, which can easily lead to structural defects, quality abnormalities or functional failures. Therefore, the present invention identifies the location of non-removable supports and combines the self-supporting design principles to fine-tune the structure, such as optimizing the overhang angle, adjusting the local wall thickness or changing the printing direction, so as to minimize the dependence on non-removable supports and improve the natural forming ability of the structure from the source.

[0050] Secondly, during the inspection and processing of closed or semi-closed cavities, the system performs a topological scan on the structural model to identify whether there are closed cavities that are not connected to the outside world or semi-closed areas with limited space. This type of structure is very likely to cause powder retention in powder bed additive manufacturing, which can seriously affect the patency of the flow channels inside the structure, the heat conduction capacity and the overall reliability. In order to avoid such problems, the present invention introduces a structural inspection and automatic repair mechanism in the model stage. When a closed cavity is detected, the structure can be adjusted by setting powder discharge holes, optimizing the shape of the inner cavity path, and opening auxiliary connecting holes without affecting the function, etc., to ensure that all internal spaces are powder-drainable after forming, meeting the requirements of post-processing and functional integration.

[0051] Step S700 includes the following steps: S710, performing functional simulation analysis and review on the model to verify whether its mechanical response, thermal stress or flow performance under the target working condition meets the set indicators; S720, manufacturing a test piece with typical characteristics based on the structure, applying equivalent loads or boundary conditions to perform performance test verification; S730, if the simulation results or test results do not meet the performance requirements, adjusting the parameters and modifying the structure of the optimization model according to the deviation results, and re-performing the verification until all design performance requirements are met.

[0052] Step S700 is the terminal link of the entire lightweight design process, which aims to conduct final performance confirmation and closed-loop correction of the model that has completed optimization and process adjustment to ensure the feasibility and reliability of the structure in practical applications. This step not only verifies whether the structural design meets the mechanical, thermal or fluid performance requirements under the target working conditions, but also evaluates the manufacturing adaptability and engineering effectiveness of the model through physical testing methods. It is a key verification node from theoretical design to engineering application.

[0053] In the S710 functional simulation analysis and review, the full model is simulated under all working conditions using finite element analysis or computational fluid dynamics methods. Based on the key performance indicators set in the initial design, a comprehensive assessment is made of the response of the structure under target loads, thermal boundary conditions, or fluid conditions. The simulation content includes but is not limited to: the positions of the maximum displacement and stress, the overall flexibility, the thermal stress distribution, the flow resistance and flow velocity distribution, the heat transfer efficiency, etc. This step can determine whether the optimized structure truly meets the comprehensive performance requirements of the initial functional requirement model at the performance level and detect whether the optimization process introduces risk factors such as new stress concentration points, weak stiffness areas, or flow discontinuities.

[0054] In the S720 typical feature part test verification, representative key geometric features are selected for trial production. The corresponding test parts are manufactured and boundary conditions consistent with the design working conditions are applied, and physical performance tests are carried out. By comparing the measured data with the simulation results, the accuracy of the simulation modeling and the manufacturing reliability of the model can be evaluated, such as whether there are problems such as warping deformation, unqualified surface roughness, uncleaned powder, or difficult removal of the support structure. This stage not only verifies the dimensional retention ability and forming quality of the structure during the printing process, but also evaluates its load-bearing capacity, fluid function, or thermal performance under physical tests, improving the accuracy of the process adaptability evaluation of the overall structure.

[0055] If the results of the S710 or S720 stage do not meet the design objectives, it enters the S730 feedback correction stage. According to the deviation information in the simulation and test results, the reasons for the unqualified performance are located, such as insufficient wall thickness resulting in poor stiffness, sharp corners in the flow channel causing excessive pressure loss, etc., and the model parameters or local structural forms are adjusted. The correction content includes fine-tuning of design variables, optimization of geometric transitions, elimination of structural interference, correction of flow path, etc. After correction, re-perform simulation analysis and necessary feature part verification to form a closed-loop control of "optimization - verification - re-optimization" to ensure that the final output structure model meets the target design indicators in all performance dimensions.

[0056] The following is an illustration of the lightweight design of a certain type of aero-engine inlet casing.

[0057] 1) Establish a structural function requirement model The aero-engine inlet casing is a key component of the engine, located at the front end, used to guide the airflow, protect the internal components, etc. It is generally composed of the inner and outer walls of the casing, inlet guide vanes, and front fairing cone, etc. In the center of the inlet casing, there are often the front support of the compressor rotor, as well as accessories such as the low-pressure rotor speed sensor and the total inlet pressure sensor. The structural shape is complex and has a large number of thin-walled structures. Its design needs to comprehensively consider multiple factors, and has extremely high requirements for the strength, stiffness of its thin-walled structures, and the heat exchange rate of the internal flow channel. Traditional methods are to optimize the structure through simulation and testing.

[0058] Using finite element analysis software, simulate the mechanical properties of the initial intake casing under different working conditions to determine its key stress-bearing parts and stress distribution. At the same time, use fluid analysis software to analyze the heat exchange efficiency and fluid flow characteristics under different flow channel design schemes. On the premise of ensuring that the heat exchange efficiency, maximum stress, and maximum displacement are increased by 10% compared with the original structure, achieve the design goal of reducing the weight by 10%. 2) Topological optimization and dimensional optimization Refer to Figure 3 , taking the minimum structural weight as the objective function, the strength, stiffness, and heat exchange efficiency of the thin-walled structure of the intake casing as functional constraint conditions, and the minimum size and overhang as process constraints, use the topological optimization algorithm for design. After multiple rounds of calculation and optimization, the topological shape of the thin-walled structure of the intake casing with a large amount of non-critical materials removed is obtained, and the material is reduced by 10% compared with the initial design. 3) Lattice structure filling Refer to Figure 4 , due to the complex functional structure requirements of the intake casing, there are many assembly areas and functional areas, resulting in a large number of solid supports generated to avoid overhangs in the model after topology based on additive manufacturing process constraints. This part of the support structure has a greater impact on the weight. Fill the tetrahedral lattice (grille) structure and porous structure with high load-bearing capacity in such areas of the intake casing. By filling the lattice structure, the unnecessary weight increase caused by process constraints is reduced (about 2%). 4) Refined design of the flow channel Refer to Figure 5 , according to the process constraints and fluid analysis results, optimize the cross-sectional shape of the flow channel in the intake casing with a diameter greater than 8 mm to a water droplet shape, increasing the turbulence degree and cross-sectional area of the fluid while ensuring process feasibility, and improving the heat exchange efficiency. At the same time, adjust the outer shape of the flow channel to a conformal water droplet cross-section to ensure the wall thickness of the flow channel to meet the design requirements of the internal pressure in the flow channel. Taking the example of changing the circular flow channel to a water droplet-shaped flow channel, the conversion process to ensure the cross-sectional area of the flow channel is as follows: Let the radius of the cross-sectional circle of the original flow channel be R, and the circular area S = πR2. Let the radius of the circle of the water droplet shape be R1. In the case where the diagonal line is tangent to the circle, it is easy to obtain the area of the water droplet shape: ; Let S = S1, and we get: ; After simplification, we get:

[0059] The height of the water droplet is: ; The center of the circle of the water droplet should be moved down by h compared with the center of the original circle: 。

[0060] Taking a circle with a diameter of 10 mm as an example, the center of the circle of the water droplet moves down by 1 mm, the diameter of the water droplet circle is 9.7 mm. According to the measurement results, the area of the water droplet shape is 78.9 mm2, which is close to π×52 = 78.5 mm2.

[0061] 5) Optimization of additive manufacturing processability Analyze the influence of the optimized model additive manufacturing process on the forming quality of thin-walled structures and runners in the specified printing direction, and further optimize the usage amount of the support structure. For complex runner structures, design special removable support structures to ensure the shape accuracy of the runners. According to the accuracy characteristics of the additive manufacturing equipment, perform dimensional compensation on the model to ensure the dimensional accuracy of the final part. 6) Model verification and optimization Refer to Figure 6 , use the finite element analysis method to verify the performance of the final design model under the specified service conditions. The simulation results show that under the temperature load, aerodynamic load and inertial load conditions of the intake casing, the maximum stress and deformation of the structure are within the allowable range, and the heat exchange efficiency reaches the design goal. Design and print typical additive manufacturing feature parts to verify the process feasibility. After further fine-tuning and optimization based on the additive manufacturing process constraints, a lightweight design scheme for the intake casing that meets all design requirements is finally determined. Through actual tests, all performance indicators are consistent with the simulation results, verifying the effectiveness of the design method of the present invention.

[0062] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A lightweight design method for a thin-walled structure with a flow channel based on additive manufacturing, characterized in that: It includes the following steps: S100, Functional requirement analysis, constructing a functional requirement model of the flow channel-containing structure; S200, Setting the printing direction and additive manufacturing constraint conditions, performing topology optimization on the functional requirement model to obtain a preliminary topological structure; S300, Geometric reconstruction of the topology optimization result to obtain a three-dimensional model suitable for additive manufacturing; S400, Parameter optimization design, taking the wall thickness, rib beam width, and rib beam thickness of the three-dimensional model obtained after geometric reconstruction as design variables, taking the minimum structural mass as the design goal, and taking the minimum flexibility as the design constraint, and performing rib beam and wall thickness dimension optimization design on the topological structure; S500, Based on the fluid performance requirements, optimize the cross-sectional shape and size of the flow channel, analyze the influence of different flow channel cross-sectional shapes and different flow channel spacings on the coolant flow and heat dissipation efficiency through fluid mechanics simulation, and obtain the optimal cross-sectional shape of the flow channel; S600, Conduct an additive manufacturing processability review on the structure after parameter and cross-sectional shape optimization, and perform additive manufacturing processability optimization according to the review results; S700, Analyze and check the model after additive manufacturing process optimization until the model meets the design performance indicators.

2. The lightweight design method for a thin-walled structure with a flow channel based on additive manufacturing according to claim 1, characterized in that: Step S200 includes the following steps: S210: Set the printing direction and additive manufacturing process parameters, and set the printing direction as the overhang plane judgment benchmark according to the selected additive manufacturing equipment and part attitude; S220: Introduce design constraints and process constraints, and perform topology optimization with design constraints and process constraints; S230, Characteristic part printing verification, perform 3D printing tests on typical characteristic parts of the optimized structural design to verify process adaptability and printing effect.

3. The lightweight design method for a thin-walled structure with a flow channel based on additive manufacturing according to claim 2, characterized in that: The design constraints in step S220 include maximum stress, maximum deformation, and natural frequency, and the process constraints include overhang angle constraint, maximum / minimum size constraint, and connectivity constraint.

4. The lightweight design method for a thin-walled structure with a flow channel based on additive manufacturing according to claim 3, characterized in that: In step S220, the topology optimization for overhang angle constraint includes the following steps: S221, Parameter initialization; S222, Finite element analysis, performing mechanical simulation on the initial structure to obtain stress and deformation response results; S223, Calculate flexibility and sensitivity, calculate the flexibility index of the structure, and obtain the sensitivity information of each unit to the objective function; S224, Mesh filtering, performing smoothing processing on the sensitivity distribution in topology optimization to eliminate local artifacts and numerical oscillations; S225, Solve the design variables, update the density variables of each mesh unit according to the sensitivity information and the optimization algorithm, and complete one iteration; S226, Judge whether the manufacturing constraint accuracy is met. If not, return to S222. If it is met, proceed to the next step; S227, Overhang surface detection, perform surface normal angle analysis on the current design result, and identify the area with an angle less than the critical angle as the potential overhang surface; S228, Explicit self - support processing, remove the shape of the potential overhang area through an explicit constraint method, and identify and filter the lower boundary; S229, Determine whether the accuracy and performance indicators of the current structure meet the requirements after adding the overhang angle constraint. If not, return to S222; if so, output the final design result.

5. The lightweight design method of the thin - walled structure with a flow channel based on additive manufacturing according to claim 1, wherein: In step S500, for the long hole or curved pipe with a hole diameter greater than φ8mm, the cross - sectional shape is optimized to a water - droplet shape, and the optimization formula is as follows: ； In the formula, R is the radius of the cross - sectional circle of the original flow channel, and R1 is the radius of the circle of the water - droplet shape.

6. The lightweight design method of the thin - walled structure with a flow channel based on additive manufacturing according to claim 1, wherein: In step S200, for the functional areas including flow channels, mounting platforms, assembly threaded holes or mounting holes in the structure, a distributed topology optimization strategy or a step - by - step topology optimization strategy is adopted; The distributed topology optimization strategy divides the overall structure into multiple design sub - regions, separately extracts the loads and boundary conditions of each sub - region, and performs independent topology optimization on each sub - region; The step - by - step topology optimization strategy divides the design goal into multiple gradient goals according to different degrees of optimization, starts from the lowest goal among multiple gradient goals, and gradually iterates to the final global optimization goal to achieve hierarchical optimization control of complex structures.

7. The lightweight design method of the thin - walled structure with a flow channel based on additive manufacturing according to claim 1, wherein: In step S300, when geometric reconstruction is performed on the structure after topology optimization, the stl model is converted into a continuously manufacturable three - dimensional model using the PolyBURBS - based reconstruction method, and the solid region retained by the overhang angle limit inside the structure is replaced with a lattice structure with a preset cell type and parameters according to the mechanical property requirements and process constraints to further reduce the structure weight while ensuring formability.

8. The lightweight design method of the thin - walled structure with a flow channel based on additive manufacturing according to claim 1, wherein: Step S100 includes the following steps: S110, Based on the use environment, load conditions and functional requirements, establish a functional requirements model; S120, Perform mechanical and thermal finite - element analysis on the initial structure to identify key stress - bearing areas, stress distribution, stiffness distribution and temperature distribution; S130, Perform flow simulations under different shapes, sizes and layouts on the functional areas including flow channels to obtain flow velocity, pressure and heat - transfer characteristic parameters; S140, Based on the structural and fluid analysis results, perform function - driven design area identification to provide a basis for subsequent structural optimization.

9. The lightweight design method of the thin - walled structure with a flow channel based on additive manufacturing according to claim 1, wherein: Step S600 includes the following steps: Identify the removable and non-removable support regions in the structure, and optimize the structure to reduce the presence of non-removable supports; Check whether there are closed or semi-closed cavities in the structure, determine whether they will cause powder discharge problems, and modify the corresponding regions of the structure to ensure cleanability.

10. The lightweight design method of the thin-walled structure with a flow channel based on additive manufacturing according to claim 1, wherein: Step S700 includes the following steps: S710, conduct a functional simulation analysis review of the model to verify whether its mechanical response, thermal stress, or flow performance under the target working conditions meets the set indicators; S720, manufacture a test piece with typical characteristics based on the structure, and apply equivalent loads or boundary conditions for performance test verification; S730, if the simulation results or test results do not meet the performance requirements, adjust the parameters and modify the structure of the optimized model according to the deviation results, and re-execute the verification until all design performance requirements are met.

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