Lightweight design method for thin-walled structures with flow channels based on additive manufacturing

Abstract

The present invention discloses a lightweight design method for a thin-walled structure containing flow channels based on additive manufacturing, which belongs to the field of additive manufacturing technology. The method includes S100, functional requirement analysis, and construction of a functional requirement model containing flow channels; S200, setting the printing direction and additive manufacturing constraints, performing topological optimization on the functional requirement model, and obtaining a preliminary topological structure; S300, geometrically reconstructing the preliminary topological structure to obtain a three-dimensional model suitable for additive manufacturing; S400, parameter optimization design; S500, optimizing the cross-sectional shape and size of the flow channel based on fluid performance requirements, S600, conducting an additive manufacturing processability review on the structure after the cross-sectional shape and size are optimized; S700, analyzing and verifying the model after the additive manufacturing processability optimization. The present application can solve the technical problem that the existing technology cannot meet the design requirements of thin-walled structures containing flow channels, and it is difficult to accurately control the forming quality and cross-sectional shape of the inner surface of the flow channel.

Description

Technical Field

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

[0002] In recent years, the rapid development of additive manufacturing technology has revolutionized the design of complex structures. Enabling the layer-by-layer construction of arbitrarily complex geometries, AM is particularly well-suited for the fabrication of thin-walled components with complex internal cavities, lattice structures, and flow channel networks, providing new technical support for lightweighting and multifunctional integration. Metal additive manufacturing, in particular, has demonstrated broad application prospects in aerospace engines, thermal management structures, and high-precision equipment.

[0003] For the additive manufacturing of thin-walled structures and complex flow channel parts, patent number CN107321979A discloses a laser additive manufacturing method with a multi-support surface configuration for cavity thin-walled structural parts. Laser additive manufacturing technology is used to form high-temperature alloy cavity thin-walled structural parts, and the direction with the largest positive projection area of ​​the structural part is selected as the additive manufacturing stacking direction; during the additive preparation process, the lower part of the cavity position of the part structure is additively manufactured. 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 the support structure is used as a support and additive manufacturing is continued on the outer surface of the support structure until the entire structural part is formed. Patent No. CN119255544A discloses an integrated thin-walled lattice cooling plate including a hollow cold plate body, a cooling channel and a liquid inlet and a liquid outlet connected to the cooling channel are provided in the cold plate body, and the cooling channel is filled with a hollow heat exchanger. By setting the position of the cold plate body except the cooling channel as a hollow structure, the entire cold plate body can be lightweight, and the hollow heat exchanger is set in the cooling channel, so that the contact point between the coolant and the heat exchanger has a larger specific surface area, thereby improving the heat exchange effect.

[0004] However, the functional requirements of thin-walled structures with complex flow channels are complex and there are many constraints. The above solutions only focus on additive manufacturing process and flow channel structure design respectively, which cannot meet the design requirements of thin-walled structures 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 thin-walled structures containing flow channels based on additive manufacturing to solve the technical problems that the existing technology cannot meet the design requirements of thin-walled structures containing flow channels 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 containing a flow channel based on additive manufacturing is provided, comprising the following steps:

[0007] S100, functional requirement analysis, building a functional requirement model including flow channels;

[0008] S200, setting the printing direction and additive manufacturing constraints, performing topology optimization on the functional requirement model, and obtaining a preliminary topological structure;

[0009] S300, geometrically reconstructing the preliminary topological structure to obtain a three-dimensional model suitable for additive manufacturing;

[0010] S400, parameter optimization design, uses the wall thickness, rib width, and rib thickness of the model obtained after geometric reconstruction as design variables, minimizes the structural mass as the design goal, and minimizes the flexibility as the design constraint to optimize the rib and wall thickness dimensions of the topological thin-walled structure;

[0011] S500 optimizes the cross-sectional shape and size of the flow channel based on fluid performance requirements. Through fluid mechanics simulation, it analyzes the effects of different flow channel cross-sectional shapes and different flow channel spacing on coolant flow and heat dissipation efficiency, and obtains the optimal flow channel cross-sectional shape.

[0012] S600: Conduct an additive manufacturing process review on the structure after cross-sectional shape and size optimization, and optimize the additive manufacturing process based on the review results;

[0013] S700: Analyze and verify the model after additive manufacturing process optimization until the model meets all design performance indicators.

[0014] Optionally, step S200 includes the following steps:

[0015] S210: Setting the printing direction and additive manufacturing process parameters, and setting the printing direction as a reference for determining the overhang surface according to the selected additive manufacturing equipment and the part posture;

[0016] S220: Introduce design constraints and process constraints, and perform topology optimization with design constraints and process constraints;

[0017] S230, feature part printing verification, conducts 3D printing tests on typical feature parts of the optimized structural design to verify process adaptability and printing effects.

[0018] Optionally, in step S220 , the design constraints include maximum stress, maximum deformation, and natural frequency, and the process constraints include overhang angle constraints, maximum / minimum size constraints, and connectivity constraints.

[0019] Optionally, in step S220, the topology optimization for overhang angle constraint includes the following steps:

[0020] S221, parameter initialization;

[0021] S222, finite element analysis, performs mechanical simulation on the initial structure to obtain stress and deformation response results;

[0022] S223, calculating flexibility and sensitivity, calculating the flexibility index of the structure, and obtaining sensitivity information of each unit to the objective function;

[0023] S224, mesh filtering, smoothes the sensitivity distribution in topology optimization to eliminate local artifacts and numerical oscillations;

[0024] S225, solving the design variables, updating the density variables of each grid cell according to the sensitivity information and the optimization algorithm, and completing one iteration;

[0025] S226, determine whether the manufacturing constraint accuracy is met, if not, return to S222, if yes, proceed to the next step;

[0026] S227, overhang surface detection, analyzes the surface normal angle of the current design result and identifies areas with a smaller than critical angle as potential overhang surfaces;

[0027] S228, explicit self-support processing, uses explicit constraint methods to remove the shape of potential overhanging areas and identify and filter the lower boundary;

[0028] S229, judging whether the accuracy and performance index of the current structure after adding the cantilever angle constraint meet the requirements, if not, returning to S222, if satisfied, outputting the final design result.

[0029] Optionally, in step S500, for a long hole or a curved pipe with a hole diameter greater than φ8 mm, the cross-sectional shape is optimized to a teardrop shape, and the optimization formula is as follows:

[0030]

[0031] Where R is the cross-sectional radius of the original flow channel, and R1 is the radius of the teardrop-shaped circle.

[0032] Optionally, in step S200, a distributed topology optimization strategy or a step-by-step topology optimization strategy is adopted for functional areas of the structure including flow channels, mounting platforms, assembly threaded holes, or mounting holes;

[0033] The distributed topology optimization strategy is to divide the overall structure into multiple design sub-areas, extract the loads and boundary conditions of each sub-area, and perform independent topology optimization on each sub-area.

[0034] The step-by-step topology optimization strategy is to divide the design objectives into multiple gradient objectives according to different degrees of optimization, starting from the lowest objective among the multiple gradient objectives, and gradually iterating to the final global optimization objective to achieve hierarchical optimization control of complex structures.

[0035] Optionally, in step S300, when geometrically reconstructing the structure after topology optimization, a reconstruction method based on PolyBURBS is used to convert the STL format model into a continuously manufacturable three-dimensional model, and inside the structure, according to the mechanical performance requirements and process constraints, the solid area retained by the overhang angle limitation is replaced with a lattice structure with preset cell types and parameters, so as to further reduce the weight of the structure while ensuring formability.

[0036] Optionally, step S100 includes the following steps:

[0037] S110, establish a functional requirement model based on the use environment, load conditions and functional requirements;

[0038] S120, perform mechanical and thermal finite element analysis on the initial structure to identify key stress areas, stress distribution, stiffness distribution, and temperature distribution;

[0039] S130, performing flow simulation on the functional area including the flow channel under different shapes, sizes, and layouts to obtain flow velocity, pressure, and heat transfer characteristic parameters;

[0040] S140, based on the structural and fluid analysis results, performs function-driven design area identification to provide a basis for subsequent structural optimization.

[0041] Optionally, step S600 includes the following steps:

[0042] Identify removable and non-removable support areas in the structure and optimize the structure to reduce the presence of non-removable supports;

[0043] Check the structure for closed or semi-closed cavities to determine if they will prevent powder from being discharged, and make structural modifications to the corresponding areas to ensure cleanability.

[0044] Optionally, step S700 includes the following steps:

[0045] S710, performing functional simulation analysis and review on the model to verify whether its mechanical response, thermal stress or flow performance under target working conditions meets the set indicators;

[0046] S720, manufacturing a test piece with typical characteristics based on the structure, applying equivalent loads or boundary conditions to perform performance tests and verification;

[0047] S730, if the simulation results or test results do not meet the performance requirements, the optimization model is parameter adjusted and the structure modified according to the deviation results, and verification is re-performed until all design performance requirements are met.

[0048] In summary, this application includes at least one of the following beneficial technical effects:

[0049] In step S100 of the present invention, a functional model that includes both thin-walled structural morphology and flow performance requirements is constructed through a systematic analysis of the use environment, load conditions and functional requirements, providing basic support for the subsequent coordinated optimization of structure and flow channel; step S200 introduces the printing direction and typical process constraints of additive manufacturing and directly integrates them into the topology optimization process, so that the obtained preliminary structure avoids the generation of difficult-to-manufacture morphological structures while meeting the mechanical goals, making up for the shortcoming that traditional topology optimization structures cannot be directly printed; S300 uses a geometric reconstruction method to perform high-quality surface modeling on the STL results, and converts them into a CAD model in combination with the characteristics of additive manufacturing, thereby improving the subsequent parametric controllability of the structure; S400 optimizes the design of key parameters such as wall thickness and rib beams to achieve size-level lightweighting based on load and stress distribution; in S500, through a variety of flow channel cross-sectional shapes and spacing combinations, The S600 system combines fluid simulation to accurately obtain the flow velocity distribution, pressure loss and heat transfer efficiency inside the flow channel, ensuring that the flow channel cross-section not only meets functional requirements but also has good forming stability. The S600 system further introduces a processability review mechanism to automatically identify uncleanable closed cavities and difficult-to-remove support structures, and fine-tune the model based on the results, thereby improving the actual manufacturing feasibility of the model. Finally, the S700 system uses a dual-path verification mechanism of simulation and experiment to ensure that the multi-objective performance of the final model meets the requirements, and when necessary, it feeds back to the early parameters for fine-tuning to form an optimization closed loop. The overall solution establishes a multi-round collaborative coupling optimization and review mechanism among structure, flow channel and process, which solves the bottleneck problems of the existing technology such as the separation of structure and flow channel design, the difficulty in fine-tuning the cross-sectional shape and the poor process accessibility, and improves the design reliability and manufacturing quality of thin-walled structures with complex flow channels in additive manufacturing scenarios.

[0050] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0052] Figure 1 This is a flow chart of a lightweight design method for a thin-walled structure containing flow channels based on additive manufacturing according to the present invention;

[0053] Figure 2 This is a flow chart of the topology optimization algorithm for additive manufacturing overhang angle constraints of the present invention;

[0054] Figure 3 It is the topological model of the air intake casing partition;

[0055] Figure 4 Fill the dot matrix for the solid support of the air intake casing;

[0056] Figure 5 Comparison between the circular flow channel and the teardrop-shaped flow channel of the air intake casing;

[0057] Figure 6 Schematic diagram of the optimized flow path after the air intake casing. DETAILED DESCRIPTION

[0058] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. However, the present invention can be implemented in many different ways as defined and covered below.

[0059] The following is combined with Figure 1-6 This application is described in further detail.

[0060] The embodiments of the present application disclose a lightweight design method for a thin-walled structure containing a flow channel based on additive manufacturing.

[0061] Reference Figure 1 The present invention proposes a lightweight design method for thin-walled structures with complex flow channels based on additive manufacturing. The method integrates structural topology optimization, lattice structure filling, fine design of flow channel sections, manufacturing process constraint adaptation and closed-loop verification of simulation tests to construct a complete design-manufacturing integrated process, which significantly improves the forming performance and design freedom of thin-walled structures with flow channels.

[0062] The overall process of this method includes the following seven main steps:

[0063] The steps include:

[0064] S100, functional requirement analysis, building a functional requirement model including flow channels;

[0065] S200, setting the printing direction and additive manufacturing constraints, performing topology optimization on the functional requirement model, and obtaining a preliminary topological structure;

[0066] S300, geometrically reconstructing the preliminary topological structure to obtain a three-dimensional model suitable for additive manufacturing;

[0067] S400, parameter optimization design, uses the wall thickness, rib width, and rib thickness of the model obtained after geometric reconstruction as design variables, minimizes the structural mass as the design goal, and minimizes the flexibility as the design constraint to optimize the rib and wall thickness dimensions of the topological thin-walled structure;

[0068] S500 optimizes the cross-sectional shape and size of the flow channel based on fluid performance requirements. Through fluid mechanics simulation, it analyzes the effects of different flow channel cross-sectional shapes and different flow channel spacing on coolant flow and heat dissipation efficiency, and determines the optimal flow channel cross-sectional shape.

[0069] S600: Conduct an additive manufacturing process review on the structure after cross-sectional shape and size optimization, and optimize the additive manufacturing process based on the review results;

[0070] S700: Analyze and verify the model after additive manufacturing process optimization until the model meets all design performance indicators.

[0071] Through the complete design process from S100 to S700, the present invention gradually realizes the lightweight modeling, optimization and process adaptation of thin-walled structures containing flow channels, solving the problems in the existing technology that thin-walled structures are difficult to meet the requirements of complex flow channel integration design and the flow channel cross-section forming quality is difficult to control. Specifically, S100 constructs a functional requirement model including flow channels through functional requirement analysis, clarifying design objectives and structural functional areas, providing a foundation for subsequent optimization. S200 sets the printing direction and additive manufacturing constraints, performs topology optimization on the functional model, and obtains a preliminary topology structure that balances structural performance and manufacturing process feasibility. S300 performs geometric reconstruction based on topology optimization, converting the optimization results into a 3D model suitable for additive manufacturing. S400 optimizes parameters such as wall thickness, rib width, and thickness in the geometrically reconstructed model with the goal of minimizing structural mass and the constraint of minimizing flexibility, further enhancing the lightweighting effect. S500 optimizes the cross-sectional shape and size of the flow channels based on fluid performance requirements, and uses fluid simulation to analyze the effects of different cross-sectional shapes and spacing on coolant flow and heat dissipation efficiency to determine the optimal cross-sectional form. S600 conducts an additive manufacturing process review of the optimized structure and, based on the review results, performs process optimization to identify and adjust structural areas that affect printing quality. S700 analyzes and verifies the process-optimized model to ensure that the structure ultimately meets all design performance indicators. By sequentially executing the above steps, a lightweight design method for thin-walled structures that is oriented to additive manufacturing and can effectively control the flow channel cross-sectional shape and inner surface quality is formed.

[0072] 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 key stress areas, stress distribution, stiffness distribution and temperature distribution; S130, performing flow simulation on the functional areas including the flow channels under different shapes, sizes and layouts to obtain flow velocity, pressure and heat transfer characteristic parameters; S140, performing function-driven design area identification based on the structural and fluid analysis results to provide a basis for subsequent structural optimization.

[0073] Step S100, as the starting point of the overall lightweight design process of the present invention, is responsible for converting actual working conditions and functional requirements into a quantifiable and solvable design input model, and is the basis for achieving structure-function-process collaborative design. It specifically includes four sub-steps:

[0074] In S110, the system collects and analyzes information such as the structural environment, load conditions, and functional requirements to establish a functional requirements model. The environment includes, but is not limited to, temperature fields, pressure fields, and fluid conditions. Load conditions include conventional boundary conditions such as static, dynamic, and thermal loads. Functional requirements encompass target performance indicators such as overall stiffness, mass constraints, flow function in specific areas, and thermal conductivity requirements. This model not only imposes requirements on the structural shape but also defines restrictions on functional areas such as flow path layout, channel connectivity, and boundary interfaces, forming the boundary framework for subsequent optimization.

[0075] In S120, a finite element analysis is performed on the initial structure to identify key structural responses from both mechanical and thermal perspectives. Specifically, this involves obtaining metrics such as stress distribution, stiffness distribution, and temperature distribution to identify weak areas with high stress concentrations, areas prone to deformation due to low structural stiffness, and potential thermal failure points with large thermal gradients. These analysis results facilitate the subsequent establishment of appropriate design variable regions and non-design protection zones during topology optimization, and assist in identifying the need for local minimum size limits or stiffness enhancements.

[0076] In S130, multiple flow simulation scenarios are performed on the structural area containing internal flow channels, comparing and evaluating the performance of different flow channel shapes, cross-sectional dimensions, and layouts in terms of key indicators such as flow velocity distribution, flow resistance variation, and heat transfer efficiency. This step specifically focuses on the trade-off between functional satisfaction and design adjustability among different flow channel solutions, ensuring that the selected solution meets performance requirements while also allowing for parameterized design and optimization.

[0077] Finally, in S140, based on the structural mechanics response and fluid performance results obtained in S120 and S130, the entire design domain is partitioned into function-driven regions, identifying structural areas requiring optimization, functional interface areas to be retained, and designable areas. This partitioning not only provides the basic geometric boundaries for topology optimization but also lays a clear foundation for subsequent parameter optimization and flow channel refinement.

[0078] 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 judging the overhanging surface based on 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, feature part printing verification, performing 3D printing tests on typical feature parts of the optimized structural design to verify process adaptability and printing effects.

[0079] Step S200 is the core stage of structural optimization after the functional requirements model is constructed. Its purpose is to generate a preliminary topology that is practically manufacturable while ensuring the structure meets its intended function by introducing additive manufacturing process conditions and structural performance constraints. This step includes three key sub-processes: setting the print direction, embedding constraints into the optimization process, and verifying the process results, ensuring close coordination between design and manufacturing capabilities.

[0080] In S210, according to the specific type of additive manufacturing equipment and the installation posture of the parts, the placement of the components on the printing platform is clarified, and the printing direction is set as the basis for overhang judgment. This operation directly determines the basic direction of 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 the structure requires additional support locally. Therefore, the printing direction must be solidified before the topology optimization begins to ensure that a self-supporting or supportable geometric morphology is formed during the optimization process. In addition, this step also sets relevant process parameters, such as the minimum allowable feature size, support removable angle threshold, powder cleaning directionality, etc., to guide subsequent process constraint modeling.

[0081] In S220, based on the functional requirement model established in S100, the objective function and constraints for topology optimization are constructed, and key process constraints for additive manufacturing are introduced. Design constraints include structural performance indicators such as maximum stress, maximum deformation, and natural frequency to ensure that the results of topology optimization meet expectations in terms of load-bearing capacity and structural stiffness. Process constraints include overhang angle constraints, maximum / minimum structural size constraints, and structural connectivity constraints. Overhang angle constraints are used to avoid the generation of inclined structures that are difficult to self-support during the forming process. Maximum / minimum size constraints are used to prevent details from being unable to print or large surface collapse. Connectivity constraints are used to avoid the generation of suspended structures or closed cavities, thereby ensuring that the topology structure has complete manufacturability. During the topology optimization process, these structural-process hybrid constraints are embedded in the solution algorithm for the design variables. SIMP, ESO, or sensitivity-based gradient optimization methods are usually used to dynamically adjust the density distribution during the iteration process to output a structural layout that balances performance and printability.

[0082] In S230, in order to verify the adaptability of the topology optimization 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, flow channel corners or the thinnest areas of the structure, and are key units reflecting the overall forming difficulty and printing quality. Through actual printing measurements, the influence of process parameters such as structural surface quality, forming errors, and boundary transition continuity on the actual printing quality can be intuitively verified, and it can be evaluated whether the support structure settings are reasonable, whether the edges and corners are clearly formed, and whether the dimensional accuracy meets the expected design requirements. If the feature part printing results show that there are serious support dependence, deterioration of the lower surface quality or insufficient structural accuracy, this can be fed back to S210 or S220 to adjust the printing direction settings or constraint parameters to form a front-to-back closed-loop design correction mechanism.

[0083] In step S220, the design constraints include maximum stress, maximum deformation, and natural frequency, while the process constraints include overhang angle constraints, maximum / minimum size constraints, and connectivity constraints. The maximum stress, maximum deformation, and natural frequency constraints control the strength, safety, and dynamic performance of the structure during use, preventing structural damage or insufficient rigidity due to excessive material reduction. The overhang angle constraint, a process constraint, avoids the creation of structural surfaces that require extensive support or are difficult to form. Maximum / minimum size constraints prevent details that are too small to print or structures that are too large to collapse. Connectivity constraints ensure that all parts of the structure remain coherent during printing, avoiding the formation of isolated islands or closed cavities, thereby improving the manufacturability and first-time success rate of the optimized structure.

[0084] In step S220, the topology optimization for overhang angle constraint includes the following steps:

[0085] S221, parameter initialization;

[0086] S222, finite element analysis, performs mechanical simulation on the initial structure to obtain stress and deformation response results;

[0087] S223, calculating flexibility and sensitivity, calculating the flexibility index of the structure, and obtaining sensitivity information of each unit to the objective function;

[0088] S224, mesh filtering, smoothes the sensitivity distribution in topology optimization to eliminate local artifacts and numerical oscillations;

[0089] S225, solving the design variables, updating the density variables of each grid cell according to the sensitivity information and the optimization algorithm, and completing one iteration;

[0090] S226, determine whether the manufacturing constraint accuracy is met, if not, return to S222, if yes, proceed to the next step;

[0091] S227, overhang surface detection, analyzes the surface normal angle of the current design result and identifies areas with a smaller than critical angle as potential overhang surfaces;

[0092] S228, explicit self-support processing, uses explicit constraint methods to remove the shape of potential overhanging areas and identify and filter the lower boundary;

[0093] S229, judging whether the accuracy and performance index of the current structure after adding the cantilever angle constraint meet the requirements, if not, returning to S222, if satisfied, outputting the final design result.

[0094] The overhang angle constraint-oriented topology optimization process in step S220 aims to proactively identify and control areas prone to overhang formation during additive manufacturing, ensuring the resulting topology is both self-supporting and manufacturable. The process begins with parameter initialization in step S221 to define the optimization objectives, boundary conditions, and process parameters. Subsequently, in step S222, finite element analysis is performed to obtain the stress and deformation responses of the initial structure under load, providing a basis for structural performance evaluation. In step S223, structural flexibility and sensitivity are calculated to identify the influence of each element on the objective function, which serves as a basis for optimization adjustments. Next, in step S224, grid filtering is performed on the sensitivity distribution results to remove numerical oscillations and artifacts, enhancing the stability and physical rationality of the optimization process. In step S225, the sensitivity information is combined with the optimization algorithm to solve for the design variables, update the structural density distribution, and generate the topology iteration results. In step S226, a determination is made as to whether the results of this iteration meet the basic accuracy requirements of the manufacturing constraints. If not, the process returns to step S222 and iterates again. Once the preliminary process accuracy requirements are met, the normal angle analysis of the structure surface is performed in S227 to detect whether there are overhanging areas with an angle with the printing direction less than a preset threshold (such as 45°). In S228, these potential overhanging surfaces are morphologically adjusted or penalized through explicit self-support processing methods, and the bottom support connectivity of the structure is optimized in combination with the lower boundary recognition technology to further improve the feasibility of printing. Finally, in S229, the performance indicators and manufacturing accuracy of the structure after adding the overhang angle constraint are evaluated to see if they meet the standards. If they still do not meet the standards, return to the previous steps to continue iterating. If they meet the standards, the final design results are output. This process achieves a deep integration of additive manufacturing constraints and structural optimization by embedding the overhang angle constraint into the main loop of topology optimization, avoiding the problem of traditional topology optimization structures being difficult to manufacture due to too many overhanging surfaces during the printing process from the source, and improving the practicality and manufacturability of the design results.

[0095] In step S200, a distributed topology optimization strategy or a step-by-step topology optimization strategy is adopted for functional areas of the structure including flow channels, mounting platforms, assembly threaded holes or mounting holes; the distributed topology optimization strategy is to divide the overall structure into multiple design sub-areas, extract the load and boundary conditions of each sub-area respectively, and perform independent topology optimization on each sub-area; the step-by-step topology optimization strategy is to divide the design goal into multiple gradient goals according to different degrees of optimization, start from the lowest goal among the multiple gradient goals, and gradually iterate to the final global optimization goal to achieve hierarchical optimization control of complex structures.

[0096] In step S200, in order to solve the problems of structural distribution imbalance, non-convergence of optimization or unmanufacturability of results in the overall topology optimization process of thin-walled structures with complex functional areas, 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 areas. It is particularly suitable for structural design tasks involving multifunctional integrated parts such as flow channels, mounting platforms, assembly threaded holes or mounting holes.

[0097] Among them, the distributed topology optimization strategy is suitable for situations where the structural morphology is complex and the functional area distribution is clear. This strategy divides the overall structure into several design sub-areas, and each sub-area independently extracts loads and boundary conditions according to its functional properties. For example, the flow channel area is mainly based on internal fluid pressure, the installation platform focuses on structural stiffness and stability, and the area around the threaded hole focuses on local strength and connection force transmission capacity. Topological optimization of these sub-areas 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 used in different sub-areas, thereby realizing spatially differentiated regulation of structural performance. After optimization, the results of each sub-area are geometrically spliced ​​and coordinated to form a complex structural topology that meets local functions while having overall performance.

[0098] The step-by-step topology optimization strategy addresses the problems of large optimization target spans, drastic morphological changes, and difficulty in achieving convergence in one step. By decomposing the global design target into several gradient targets (such as 20%, 50%, 80%, 90%, and 100% target levels), the topology optimization process is gradually advanced. In each stage, the topology optimization is first run with low constraints or low-intensity targets to obtain a preliminary feasible structural distribution. On this basis, the target is tightened or more constraints are added 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 breakage, or morphological mutations during the direct optimization process. It is particularly suitable for dealing with scenarios where fluid path coupling is significant and structural support boundaries are complex in thin-walled structures containing flow channels.

[0099] In step S300, when geometrically reconstructing the structure after topology optimization, a PolyBURBS-based reconstruction method is used to convert the STL format model into a continuously manufacturable three-dimensional model. Inside the structure, the solid area retained by the overhang angle limitation is replaced with a lattice structure with preset cell types and parameters based on the mechanical performance requirements and process constraints, so as to further reduce the weight of the structure while ensuring formability.

[0100] Specifically, the topology optimization process usually outputs a triangular mesh model (STL) generated based on the density field. This model has problems such as surface discontinuity, local roughness, and non-closed topology, making it difficult to directly apply to subsequent process preparation and additive manufacturing path planning. Therefore, the PolyBURBS method is used in S300 for geometric reconstruction. Through a spatial continuous modeling method based on local reconstruction functions, the conversion from STL mesh to a highly smooth solid model is achieved. While maintaining the morphological characteristics of the original optimized structure, the PolyBURBS method can quickly generate a surface structure that meets the requirements of engineering manufacturing, improve the operability and precision control capabilities of the geometric model, and solve the problems of low reconstruction efficiency and unstable results in traditional CAD software.

[0101] After the geometric reconstruction is completed, the present invention further introduces a lattice structure filling strategy for the solid areas retained due to process limitations in the topology optimization stage. Such retained areas usually do not bear the main structural loads. Their existence is mainly to meet the process requirements of self-supporting forming. If they continue to exist as solid structures, it will cause unnecessary material waste and weight increase. Therefore, combining the results of structural stress analysis and the process forming path, the present invention uses a preset lattice structure as an alternative filling in these non-critical stress-bearing areas. The selected lattice structure can be in the form of a tetrahedral lattice, honeycomb unit or metamaterial structure, and its parameters are differentiated according to the stress distribution and forming direction of different regions to achieve local adaptation of multiple target performances such as load-bearing capacity, thermal conductivity, and formability. This process not only significantly reduces the weight of the structure, but also optimizes the internal space utilization without compromising the overall stiffness and manufacturing feasibility, and improves the thermal conductivity and powder cleaning efficiency. Compared with the traditional full-solid structure model, this reconstruction-filling scheme is more in line with the advantages of additive manufacturing technology, can achieve a coordinated match between complex morphology and performance requirements, and significantly improves the lightweight level of the structure and the printing success rate.

[0102] In step S400, parameter optimization design is to refine and optimize key geometric parameters such as wall thickness, rib width and rib thickness in the model after completing geometric reconstruction. Its purpose is to further reduce the structural mass and improve local performance while keeping the overall structural form unchanged. The specific approach is to set these parameters as design variables, with minimizing the structural mass as the optimization goal, and minimizing flexibility as the design constraint. By combining parametric modeling with finite element simulation analysis, an optimization model is constructed and multiple rounds of iterative solutions are performed to gradually adjust the local dimensions of the structure to ensure that redundant materials are removed without reducing stiffness and load-bearing capacity, thereby achieving higher-precision lightweight control. This process effectively makes up for the shortcomings of topology optimization in detail control and improves the comprehensive performance and manufacturing feasibility of the structure.

[0103] For existing additive manufacturing processes, especially SLM, a circular hole of φ8mm will have a small lower surface anomaly, and the lower surface anomaly area of ​​a horizontal hole of φ9-10mm will be further expanded. Therefore, in general, when the hole diameter is larger than φ8mm, it is necessary to add support to ensure the printing forming effect, but for long holes or curved pipes, the internal support is basically impossible to remove. In this case, it is necessary to design the flow channel shape into a teardrop-shaped hole, an ellipse or a diamond, and chamfer the corners in the hole to avoid stress concentration. In step S500, the cross-sectional shape of the air intake casing flow channel with a diameter greater than 8mm is optimized to a water drop shape, which increases the turbulence and cross-sectional area of ​​the fluid while ensuring the feasibility of the process, thereby improving the heat exchange efficiency. At the same time, the flow channel shape is adjusted to a conformal water drop cross-section to ensure the flow channel wall thickness to meet the design requirements of the pressure in the flow channel.

[0104] Step S600 includes the following steps: identifying removable support areas and non-removable support areas in the structure, optimizing the structure to reduce the presence of non-removable supports; checking whether the structure has closed or semi-closed cavities to determine whether they will prevent powder from being discharged, and modifying the structure of the corresponding areas to ensure cleanability.

[0105] Step S600 primarily conducts an AM process review and structural adjustments for the structure after topology and parameter optimization. This ensures the designed thin-walled structure is manufacturable and cleanable during the actual printing process, thereby avoiding printing failures or functional defects caused by insufficient process adaptability. This step includes two core components: analyzing and optimizing support structure removability and internal powder cleaning.

[0106] First, in the process of identifying removable support areas and non-removable support areas, the system classifies and judges all areas that require 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 fine-tunes the structure in combination with the self-supporting design principle, such as optimizing the overhang angle, adjusting the local wall thickness or changing the printing direction, so as to minimize dependence on non-removable supports and improve the natural forming ability of the structure from the source.

[0107] 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 flow channel patency, heat conduction capacity and overall reliability inside the structure. 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.

[0108] 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 conditions meet 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.

[0109] Step S700, the final step in the lightweight design process, aims to conduct final performance verification and closed-loop correction of the optimized and process-adjusted model 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, and fluid performance requirements under the target operating conditions, but also evaluates the model's manufacturability and engineering effectiveness through physical testing. It is a key verification node in the transition from theoretical design to engineering application.

[0110] During the S710 functional simulation analysis review, the complete model is simulated under all operating conditions using finite element analysis or computational fluid dynamics methods. Based on the key performance indicators set at the initial design stage, a comprehensive assessment of the structure's response to target loads, thermal boundary conditions, or fluid conditions is conducted. Simulation content includes, but is not limited to, maximum displacement and stress location, overall compliance, thermal stress distribution, flow resistance and velocity distribution, and heat transfer efficiency. This step determines whether the optimized structure truly meets the comprehensive performance requirements of the initial functional requirement model in terms of performance, and detects whether the optimization process has introduced new risk factors such as stress concentration points, weak stiffness areas, or flow discontinuities.

[0111] During the S720's typical feature part testing and verification, representative key geometric features were selected for trial production. Corresponding test pieces were manufactured, and boundary conditions consistent with the design operating conditions were applied to conduct physical performance testing. 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. For example, issues such as warping, surface roughness that does not meet requirements, powder not being cleaned up properly, or support structure removal difficulties can be assessed. This stage not only verifies the structure's dimensional retention and forming quality during the printing process, but also evaluates its load-bearing capacity, fluid function, or thermal performance under physical testing, thereby improving the accuracy of the overall structure's process adaptability evaluation.

[0112] If the results of the S710 or S720 stages do not meet the design goals, the feedback and correction stage S730 will be entered. Based on the deviation information in the simulation and test results, the reasons for the unsatisfactory performance are identified, such as insufficient wall thickness leading to poor stiffness, sharp flow channel corners leading to excessive pressure loss, etc., and the model parameters or local structural morphology are adjusted. The correction content includes fine-tuning of design variables, optimization of geometric transitions, elimination of structural interference, correction of flow channel paths, etc. After the correction, the simulation analysis and necessary feature parts verification are carried out again to form a closed-loop control of "optimization-verification-re-optimization" to ensure that the final output structural model meets the target design indicators in all performance dimensions.

[0113] The following describes the lightweight design of a certain type of aircraft engine air intake casing.

[0114] 1) Establish a structural function requirement model

[0115] The aircraft engine intake case is a critical component, located at the front end, responsible for guiding airflow and protecting internal components. It typically consists of the inner and outer casing walls, inlet guide vanes, and a front straightening cone. The center of the intake case often houses the front bearing of the compressor rotor, as well as accessories such as the low-pressure rotor speed sensor and the intake total pressure sensor. Its complex structure and numerous thin-walled structures require comprehensive design considerations, placing extremely high demands on the strength and rigidity of the thin-walled structures, as well as the heat exchange efficiency of the internal flow channels. Traditionally, structural optimization has been achieved through simulation and testing.

[0116] Finite element analysis software was used to simulate the mechanical properties of the original intake casing under different operating conditions, identifying key stress points and stress distribution. Fluid analysis software was also used to analyze the heat exchange efficiency and fluid flow characteristics of different flow channel design options. The design goal of a 10% weight reduction was clearly established, while ensuring a 10% improvement in heat exchange efficiency, maximum stress, and maximum displacement compared to the original structure.

[0117] 2) Topology optimization and size optimization

[0118] Reference Figure 3A topology optimization algorithm was used for the design, with minimizing structural weight as the objective function, the strength, stiffness, and heat exchange efficiency of the thin-walled intake casing structure as functional constraints, and minimum size and overhang as process constraints. After multiple rounds of calculations and optimization, the resulting topology of the thin-walled intake casing was eliminated, eliminating a significant amount of non-critical material. This resulted in a 10% reduction in material compared to the initial design.

[0119] 3) Lattice structure filling

[0120] Reference Figure 4 Due to the complex functional structure of the air intake casing and the large number of assembly and functional areas, the model, based on the topology constraints of the additive manufacturing process, contains a large number of solid supports generated to avoid overhangs. These support structures have a significant impact on weight. These areas of the air intake casing are filled with a tetrahedral lattice (grid) structure and a porous structure with high load-bearing capacity. By filling with the lattice structure, the unnecessary weight increase caused by process constraints is reduced (approximately 2%).

[0121] 4) Flow channel refinement design

[0122] Reference Figure 5 Based on process constraints and fluid analysis results, the cross-sectional shape of the intake casing flow passages with a diameter greater than 8mm was optimized to a teardrop shape. This increased the fluid turbulence and cross-sectional area while ensuring process feasibility, improving heat exchange efficiency. Simultaneously, the flow passage shape was adjusted to a conformal teardrop cross-section to ensure the passage wall thickness met the design requirements for pressure within the passage.

[0123] Taking the conversion of a circular flow channel to a teardrop-shaped flow channel as an example, in order to ensure the cross-sectional area of ​​the flow channel, the conversion process is as follows:

[0124] Let the radius of the original cross-section of the flow channel be R, and the area of ​​the circle S = πR2. Let the radius of the teardrop-shaped circle be R1. When the oblique line is tangent to the circle, the area of ​​the teardrop-shaped circle can be easily obtained:

[0125]

[0126] Let S = S1, we get:

[0127]

[0128] After simplification, we get:

[0129]

[0130] The height of the water drop is:

[0131]

[0132] The center of the water droplet should be shifted downward by h compared to the original center of the circle:

[0133]

[0134] Taking a circle with a diameter of 10mm as an example, the center of the water droplet moves down 1mm, and the diameter of the water droplet circle is 9.7mm. According to the measurement results, the area of ​​the water droplet is 78.9mm2, which is close to π×52=78.5mm2.

[0135] 5) Additive manufacturing process optimization

[0136] The impact of thin-wall structures and runner formation quality during additive manufacturing of optimized models with a specified print orientation was analyzed to further optimize the use of support structures. For complex runner structures, special removable support structures were designed to ensure runner shape accuracy. Based on the precision characteristics of the additive manufacturing equipment, dimensional compensation was applied to the model to ensure the dimensional accuracy of the final part.

[0137] 6) Model verification and optimization

[0138] Reference Figure 6 , using the finite element analysis method, the performance of the final design model was verified under the specified service conditions. The simulation results show that under the temperature load, aerodynamic load and inertial load conditions, the maximum stress and deformation of the structure of the air intake casing are within the allowable range, and the heat exchange efficiency has reached the design target. The typical characteristic parts of additive manufacturing were designed and printed to verify the feasibility of the process. After further fine-tuning and optimization based on the constraints of the additive manufacturing process, a lightweight design scheme for the air intake casing that meets all design requirements was finally determined. After actual testing, various performance indicators were consistent with the simulation results, verifying the effectiveness of the design method of the present invention.

[0139] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A lightweight design method for thin-walled structures containing flow channels based on additive manufacturing, characterized by: The steps include: S100, functional requirement analysis, building a functional requirement model including flow channels; S200, setting the printing direction and additive manufacturing constraints, performing topology optimization on the functional requirement model, and obtaining a preliminary topological structure; S300, geometrically reconstructing the preliminary topological structure to obtain a three-dimensional model suitable for additive manufacturing; S400, parameter optimization design, uses the wall thickness, rib width, and rib thickness of the 3D model obtained after geometric reconstruction as design variables, minimizes structural mass as the design goal, and minimizes flexibility as the design constraint to optimize the rib and wall thickness dimensions of the topologically reconstructed structure; S500 optimizes the cross-sectional shape and size of the flow channel based on fluid performance requirements. Through fluid mechanics simulation, it analyzes the effects of different flow channel cross-sectional shapes and different flow channel spacing on coolant flow and heat dissipation efficiency, and obtains the optimal flow channel cross-sectional shape. S600: Conduct an additive manufacturing process review on the structure after parameter and cross-sectional shape optimization, and optimize the additive manufacturing process based on the review results; S700: Analyze and verify the model after the additive manufacturing process optimization until the model meets the design performance indicators.

2. The lightweight design method for a thin-walled structure containing flow channels based on additive manufacturing according to claim 1, characterized in that: Step S200 includes the following steps: S210: Setting the printing direction and additive manufacturing process parameters, and setting the printing direction as a reference for determining the overhang surface according to the selected additive manufacturing equipment and the part posture; S220: Introduce design constraints and process constraints, and perform topology optimization with design constraints and process constraints; S230, feature part printing verification, conducts 3D printing tests on typical feature parts of the optimized structural design to verify process adaptability and printing effects.

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

4. The lightweight design method for a thin-walled structure containing flow channels 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, performs mechanical simulation on the initial structure to obtain stress and deformation response results; S223, calculating flexibility and sensitivity, calculating the flexibility index of the structure, and obtaining sensitivity information of each unit to the objective function; S224, mesh filtering, smoothes the sensitivity distribution in topology optimization to eliminate local artifacts and numerical oscillations; S225, solving the design variables, updating the density variables of each grid cell according to the sensitivity information and the optimization algorithm, and completing one iteration; S226, determine whether the manufacturing constraint accuracy is met, if not, return to S222, if yes, proceed to the next step; S227, overhang surface detection, analyzes the surface normal angle of the current design result and identifies areas with a smaller than critical angle as potential overhang surfaces; S228, explicit self-support processing, uses explicit constraint methods to remove the shape of potential overhanging areas and identify and filter the lower boundary; S229, judging whether the accuracy and performance index of the current structure after adding the cantilever angle constraint meet the requirements, if not, returning to S222, if satisfied, outputting the final design result.

5. The lightweight design method for a thin-walled structure containing flow channels based on additive manufacturing according to claim 1, characterized in that: In step S500, for a long hole or a curved pipe with a hole diameter greater than φ8 mm, the cross-sectional shape is optimized to a teardrop shape. The optimization formula is as follows: Where R is the cross-sectional radius of the original flow channel, and R1 is the radius of the teardrop-shaped circle.

6. The lightweight design method of a thin-walled structure containing flow channels based on additive manufacturing according to claim 1, characterized in that: In step S200, a distributed topology optimization strategy or a step-by-step topology optimization strategy is adopted for functional areas of the structure including flow channels, mounting platforms, assembly threaded holes or mounting holes; The distributed topology optimization strategy is to divide the overall structure into multiple design sub-areas, extract the loads and boundary conditions of each sub-area, and perform independent topology optimization on each sub-area. The step-by-step topology optimization strategy is to divide the design objectives into multiple gradient objectives according to different degrees of optimization, starting from the lowest objective among the multiple gradient objectives, and gradually iterating to the final global optimization objective to achieve hierarchical optimization control of complex structures.

7. The lightweight design method for a thin-walled structure containing flow channels based on additive manufacturing according to claim 1, characterized in that: In step S300, when geometrically reconstructing the structure after topology optimization, a PolyBURBS-based reconstruction method is used to convert the STL format model into a continuously manufacturable three-dimensional model. Inside the structure, the solid area retained by the overhang angle limitation is replaced with a lattice structure with preset cell types and parameters based on the mechanical performance requirements and process constraints, so as to further reduce the weight of the structure while ensuring formability.

8. The lightweight design method for a thin-walled structure containing flow channels based on additive manufacturing according to claim 1, characterized in that: Step S100 includes the following steps: S110, establish a functional requirement model based on the use environment, load conditions and functional requirements; S120, perform mechanical and thermal finite element analysis on the initial structure to identify key stress areas, stress distribution, stiffness distribution, and temperature distribution; S130, performing flow simulation on the functional area including the flow channel 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, performs function-driven design area identification to provide a basis for subsequent structural optimization.

9. The lightweight design method for a thin-walled structure containing flow channels based on additive manufacturing according to claim 1, characterized in that: Step S600 includes the following steps: Identify removable and non-removable support areas in the structure, and optimize the structure to reduce the presence of non-removable supports; check whether the structure has closed or semi-closed cavities to determine whether they will prevent powder from being discharged, and modify the structure of the corresponding areas to ensure cleanability.

10. The lightweight design method of a thin-walled structure containing flow channels based on additive manufacturing according to claim 1, characterized in that: 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 target working conditions 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 tests and verification; S730, if the simulation results or test results do not meet the performance requirements, the optimization model is parameter adjusted and the structure modified according to the deviation results, and verification is re-performed until all design performance requirements are met.

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