206 results about "Design domain" patented technology

The invention provides a multi-sealing method and system for a high-vacuum die-casting die based on topological optimization, and relates to the technical field of die structures.The multi-sealing method comprises the steps that a sealing structure parameterized model is established, geometric parameters and boundary conditions of a cavity wall face are obtained, an initial design domain is constructed, and grid units are divided; carrying out topological optimization calculation based on a multi-objective function considering contact stress distribution, and iteratively optimizing the relative density of grid cells by adopting an SIMP method; and according to the obtained topological configuration of the sealing structure, multiple sealing structure design is carried out, a three-dimensional entity model is constructed, and the sealing performance is verified through finite element analysis.

The invention belongs to the technical field of material structure optimization, and discloses an enhanced structure design method and system for a three-period minimal curved surface, and the method comprises the steps: modeling a geometric model of the three-period minimal curved surface, and exporting the model; expanding a design domain of the geometric model to obtain a corresponding expanded design space of the three-period minimal curved surface; a design space file is converted into an analysis data structure, a general expression mode is constructed for the three-period minimum curved surface, an equal geometric element stiffness matrix is solved by using a Gaussian integral method and the elastic performance of each point in a design domain and assembled into a global stiffness matrix, and the structural response of the model is solved; constructing a local density distribution function in the Bayesian unit, and assembling all LDDFs to obtain a global density distribution function for presenting structural topology; and constructing a stiffness maximization topological optimization mathematical model for the TPMS, calculating an objective function and analyzing sensitivity, and carrying out iterative updating on design variables in the optimization model based on an optimal criterion method to obtain a reinforced structure configuration.

The invention discloses a circuit EMI suppression-oriented multi-knowledge collaborative distillation and optimization method and system, and the method comprises the steps: constructing a basic large language model based on the circuit design of the electronic industry as a student model, and carrying out the adaptive optimization of the circuit design field. Thirdly, integrating the formalized EMI rule base, the simulation data / model base and the expert experience case base, constructing a multi-source heterogeneous teacher knowledge system, and generating a comprehensive guidance signal G; then, candidate circuit design generated by a student model is evaluated through the system, and a multi-objective loss function including basic distillation, rule conformity, performance fitting and expert experience consistency is constructed; according to the method, the universality is reserved by quantifying differences, compliance is ensured through punishment, the performance difference is reduced, dynamic weight adjustment is introduced, and the model performance reaches a preset target through iterative distillation. The model can understand and process terminologies and design rules in the field of circuit design, and the defect that a general AI model lacks domain knowledge is overcome.

The invention provides a topology and morphology integrated optimization design method for a thin-walled structure. The method comprises the steps that 1, a finite element model is established according to design requirements; 2, extracting a thin-wall structure morphology distribution field # imgabs0 # through two-step partial differential equation filtering and Heavide projection operation; 3, constructing a material attribute rational approximation model in combination with the thin-wall morphology distribution field # imgabs1 # and the topological density field v obtained in the step 2, thereby obtaining an elastic modulus E and mass rho in a design domain; 4, performing finite element analysis in combination with the material interpolation model, and calculating the flexibility of the structure; 5, solving to obtain the sensitivity of the structure flexibility and the quality relative to the design variables; step 6, updating the morphology design variable mu and the topology design variable v of the thin plate by adopting a moving asymptote method; and step 7, when a convergence condition is satisfied, stopping optimization iteration and outputting an optimization result. According to the method, the maximum forming angle of the thin-wall structure is controlled by adjusting the filtering radius of the anisotropic filter, and the stamping forming process is met.

The invention relates to the technical field of topological optimization, and discloses a thermal coupling multi-scale parallel topological optimization method for additive manufacturing, and the method comprises the steps: dividing a macroscopic design domain into a plurality of macroscopic sub-design domains through a fuzzy C clustering method, and mapping the information of the macroscopic sub-design domains on the microcosmic level as the constraint condition of microcosmic optimization; performing equivalent static conversion on the transient temperature load, and introducing an equivalent thermal load into the multi-scale topological optimization model; macroscopic and microscopic thermal coupling finite element analysis is carried out according to the thermal coupling control equation, and a displacement vector matrix is solved by using an HHT-alpha method; sensitivity analysis is carried out on macro and micro objective functions and constraint conditions, and a moving asymptote MMA method is used as a solver for macro and micro design variable updating; and filling the microstructure into the macroscopic configuration to obtain an overall configuration, judging a convergence condition, and if the condition is met, outputting an optimal material distribution structure and an optimal microscopic configuration. The method can better reflect the real working state of the workpiece.

The invention belongs to the related technical field of structure optimization, and discloses a full-scale topological optimization method of a structure under dynamic load, which comprises the following steps of: (1) constructing local volume constraints to represent the allowable maximum material volume in each grid neighborhood of the structure to be optimized, and aggregating all the local volume constraints in a design domain into a total constraint; (2) dispersing the duration of the dynamic load, performing dynamic finite element analysis in each time step, taking a continuous density field of the structure as a design variable, minimizing the dynamic flexibility of the structure as a target function, taking a dynamic balance equation of the structure as a control equation, and constructing a constraint function based on global volume constraint and local volume constraint obtained by aggregation, so as to obtain a dynamic load; further constructing a full-scale topological optimization model under the dynamic load; and (3) solving the control equation, carrying out dynamic finite element analysis on the to-be-optimized structure, and solving the full-scale topological optimization model to obtain the optimal density distribution of the structure. The method considers the influence of the dynamic load.

The invention relates to the technical field of vehicle frame structure optimization, and discloses a vehicle frame structure optimization method and system based on an SIMP-PLSM fusion method, and the method comprises the steps: building a vehicle frame geometric model, and defining a design domain of the vehicle frame geometric model and a plurality of preset first boundary conditions under different working conditions; topological optimization software is adopted to carry out topological optimization calculation on the geometric model of the vehicle frame under each working condition by utilizing an SIMP-PLSM fusion method, and a first topological optimization model under each working condition is obtained; carrying out rigidity analysis on the first topological optimization model under each working condition by adopting finite element analysis software, and obtaining a weight value of each working condition according to a rigidity analysis result; and performing weighted average processing on the topological optimization target of each working condition by adopting topological optimization software according to the weight value of each working condition, and performing topological optimization on the geometric model of the frame again by utilizing an SIMP-PLSM fusion method to obtain a topological optimized frame model under multiple working conditions. The optimization efficiency is high, the optimization result is good, and the manufacturability and practicability of the optimized structure are high.

The invention belongs to the field of intelligent manufacturing and engineering design, and particularly relates to an industrial fan structure optimization design method and system based on AI assistance. According to the method, structural components of an industrial fan are modeled into a multi-node topological structure, a dual-channel performance prediction model is constructed, and the mapping relation between the structure and the performance is accurately established. On the basis, a comprehensive objective function is constructed, a boundary penalty mechanism is introduced, a virtual input parameter space is constructed in combination with a structure disturbance sample, a strategy gradient optimization method is adopted to carry out structure search and iterative optimization, and finally a structure scheme meeting boundary conditions and optimal performance is screened out through simulation verification. The system module comprises structure modeling, model training, objective function construction, disturbance generation, optimization execution, simulation verification and result output, and has the advantages of high structure identification precision, high optimization efficiency, strong engineering adaptability and the like.

The invention relates to the technical field of lattice structure topological optimization, and discloses a multi-scale hybrid lattice structure double-variable topological optimization method, which comprises the steps of defining double variables, including a first design variable as a scaling scale and a second design variable as a relative density; determining a basic unit cell of the hybrid lattice structure and obtaining a corresponding unit cell size, wherein the second design variable is determined based on the unit cell size; obtaining a first filling unit cell and a second filling unit cell; determining a design domain, and filling the first filling unit cells and the second filling unit cells into the design domain by taking the flexibility minimization of the hybrid lattice structure as a target and the volume fraction as a constraint; and optimizing the filling process based on a moving asymptote optimization algorithm so as to carry out topological optimization of the hybrid lattice structure based on double variables, and outputting an optimized multi-scale hybrid lattice structure. According to the industrial bearing structure, higher structural specific stiffness, specific strength and energy absorption efficiency are achieved, and the requirements for light weight, self-adaption and high performance in an existing industrial bearing structure can be met.

The invention belongs to the technical field of impact load attenuation and topological optimization, and particularly relates to an anti-impact super structure optimization method based on explicit topological description, which comprises the following steps: S1, constructing a two-dimensional unit cell library based on explicit topological description; c4v symmetry is adopted for unit cells under the topology description method, two-dimensional unit cells are generated by dividing an original square design domain, and the coordinates of randomly generated control points and width information of an initial component are used for obtaining the two-dimensional unit cells of various different configurations; s2, impact environment description based on an impact response spectrum; s3, carrying out modeling analysis through the ABAQUS of the Python interface; s4, verifying whether the unit cell configuration can attenuate the impact or not; and S5, optimizing the process. The method can utilize an explicit topology description method to detailedly describe the geometric characteristics of the structure through the clear geometric boundary of the explicit topology description method.

The present application discloses a method and device for modeling and topological optimization design of a reinforced flat plate with an embedded acoustic black hole. The method includes: dividing the design domain into units based on design variables to construct a collaborative optimization model; dividing the reinforced area with solid units and the flat plate area with variable thickness shell units to simulate acoustic black holes; coupling the variable thickness shell units with the solid units and determining the stiffness matrix; introducing maximum size constraints and / or geometric non-interference constraints and / or geometric-topological non-interference constraints and / or draft constraints in the design process; solving the sensitivity of the design variables based on the optimization target combined with the stiffness matrix to obtain the optimization result; if the optimization result does not meet the convergence condition, redefine the design variables based on the sensitivity. It solves the problem that the existing vibration reduction means are difficult to efficiently realize the lightweight vibration reduction design of thin-walled structures. It takes into account the structural stiffness and the vibration and noise reduction characteristics of the medium and high frequencies, realizes the structure-function integrated design, and reduces the dynamic response of the thin-walled structure.

The invention discloses a meshless EFGM and style migration-based multi-material structure topological optimization method, which comprises the following steps of: (1) inputting material attributes such as Young modulus, shear modulus and Poisson's ratio of a structure, and discretizing a design domain by using meshless nodes; (2) transforming the designed meshless density field to obtain a physical density field, and performing length scale filtering; (3) an alternating active phase algorithm is executed, and the displacement field, the system flexibility and the related sensitivity of the structure are solved based on the meshless EFGM; (4) executing a neural style migration program to calculate the difference between the current topological structure and the reference style image, and calculating the derivative of the physical density field of the topological structure to the network parameter; and (5) updating a design variable by using a moving asymptote algorithm, and judging whether an optimization loop is converged or not. According to the method, based on meshless EFGM and style migration multi-material structure topological optimization, topological structures with different artistic styles can be designed, and the method has engineering application value.

The invention discloses a thin-wall structure topological optimization design method, device and system, and a storage medium. The method comprises the following steps: calculating any unit density in a design domain according to a structure topological optimization model; calculating a displacement vector according to the density of any unit in the design domain, the total stiffness matrix and the external load vector; calculating the structural flexibility according to the element stiffness matrix and the displacement vector; according to the unit density and the structural flexibility, obtaining the sensitivity of the target function and the constraint function to design variables; establishing a topological optimization model by taking the minimum structural flexibility as a target function, taking the welding spot area as a constraint condition and taking a design variable as a normalized height; and according to the sensitivity of the target function and the constraint function to the design variables and the topological optimization model, performing updating iteration on the design variables by utilizing an MMA algorithm to obtain an optimized structure. By the adoption of the technical scheme, on the premise that the technological constraint of the superplastic forming technology is met, the structure with the excellent mechanical property is obtained.

The invention discloses a connectable multi-configuration lattice structure topological optimization method, system and device based on transition unit cells and a storage medium. The method comprises the steps that interpolation is conducted on rod diameters of M kinds of basic unit cells to obtain the transition unit cells; respectively calculating equivalent elastic matrixes of the M basic unit cells and the transition unit cells by adopting a homogenization method; according to the relative densities and the equivalent elastic matrixes of the basic unit cells and the transition unit cells, respectively calculating the relative densities and the elastic matrixes of the units by utilizing a multi-material interpolation formula; constructing a topological optimization model of the connectable multi-configuration lattice structure based on the transition unit cell, and optimizing the sensitivity of the target function and the volume constraint to the design variables in the design domain based on the topological optimization model until the topological optimization model converges; in the optimization process, a moving asymptote method is adopted to update design variables; and obtaining an optimized structure according to a design variable corresponding to the converged topological optimization model. According to the invention, the problem of connectivity between microstructures is solved by using the transition unit cells, the geometric configuration of the basic unit cells does not need to be limited, and the mechanical potential of the structure is improved.

A method includes defining a design domain for a meta-element configured to be attached to an edge of thin wall structure with an arbitrary boundary condition, and executing a topological optimization process on the design domain and providing a topology optimized shape for the meta-element. The topological optimization process includes an objective function that minimizes a reflection coefficient of flexural waves in the audible frequency range propagating towards and impinging the meta-element.

Apparatus and method achieve topology optimization with bidirectional mesh adaptation. A mesh engine generates a mesh for a geometry of a computer aided design model of a design domain. A multi-physics simulator derives of physical field variables on the mesh based on material properties and boundary conditions of the design domain. An adjoint sensitivity is determined based on a given cost function and sensitivity formulation to drive a design variable lower or higher, the design variable defining a density of the design domain. An optimizer determines an optimization yielding a new set of design variables based on the adjoint sensitivity. A bidirectional mesh adaptation is performed on regions of the mesh by coarsening or refining the mesh element size. The multi-physics simulation, optimization and mesh adaptation are iteratively performed until optimized convergence criteria are met.

The invention discloses a topological optimization design method for a bearing structure of a wall-mounted box, which relates to structural design and comprises the following steps of: determining specification parameters of a box according to a use scene and a purpose of a required bearing structure, and establishing a required maximum envelope model of the box according to the specification parameters; the maximum envelope model of the box body is used as a topological optimization object, and a design domain and a non-design domain of the maximum envelope model are configured to be discrete into finite element models; carrying out topological optimization analysis on the finite element model of the box body by adopting a variable density method; main material layout features are extracted according to the optimization result, so that a box body main force bearing path meeting the machining requirement is determined, and structural model reconstruction is carried out; and on the basis of the reconstructed topological configuration, local strength is checked through structural mechanical simulation analysis, and local structural features are adjusted, so that the overall mechanical property of the box structure meets the requirements. The invention provides a wall-mounted box body structure force bearing optimization checking means, and the performance of the box body structure under the severe working condition is improved.

The invention provides a topological optimization method for a tension / compression structure. The method is based on a three-phase material model formed by pure tension, pure compression and empty attribute materials. According to the method, the discrete design domain of the mixed stress unit is adopted, the unit tension / pressure state judgment criterion based on the principal stress value and the tension / pressure tolerance is formulated, the tension / pressure state of the unit can be more accurately determined, and therefore material distribution based on the unit stress state is achieved. And finally, deriving the sensitivity of the target function to the design variable, and filtering the sensitivity by using a three-field filtering technology.

The invention provides a failure safety topology optimization design method under a dynamic load. The method comprises the following steps: step 1, defining a design domain and design parameters of a structure; 2, performing transient dynamic analysis on the structure; 3, calculating to obtain an equivalent static load of the dynamic load; 4, performing failure safety topological optimization design on the model under the equivalent static load; the maximum flexibility of the minimization structure under the local failure condition is taken as an optimization target; carrying out optimization iteration on the design variable unit density by using a moving asymptote method until the internal loop failure safety topological optimization process is finished; and 5, according to the design variable updated after the failure safety topological optimization, judging whether an outer circulation convergence condition is met or not. According to the method, the possible local failure condition of the structure is fully considered in the design process, and the performance of the structure under the local failure condition is improved; the dynamic load under the original working condition is converted into the static load through the equivalent static load method, and the calculation efficiency of the optimization process is effectively improved.

The invention relates to the technical field of fluid pressure loads, in particular to a fluid pressure load floating projection topological optimization method based on mworks. According to the technical scheme, the method comprises the following six steps: step 1, defining a design domain and load boundary conditions in MWorks, and dividing grids; the method comprises the following steps of: (1) carrying out iteration convergence and defining initial optimization parameters at the same time, (2) carrying out finite element analysis and calculating a target function, a constraint function and the sensitivity of a corresponding unit, (3) updating design variables in MWorks by adopting a floating projection method, (4) carrying out smooth design on the structure if iteration convergence is carried out, and (5) repeating the steps (2)-(3) if iteration convergence is not carried out. And step 5, judging whether the smooth solution is convergent or not, and if not, repeating the steps 2-4 until the program is strictly convergent. According to the method, a floating projection topological optimization method is adopted, the design is gradually pushed to 0 / 1 through beta iteration, all penalty coefficients are replaced with one parameter, the model is greatly simplified, and the workload is reduced for optimization design.

The present invention discloses a multi-objective thermal-fluid topological design optimization method for the cooling element of a precision gear grinding machine tool, comprising the following steps: Step 1: Define the design domain: Expand the cooling element into a plane, define a two-dimensional design domain representing the cooling element's geometric structure, and discretize it using the finite element method; Step 2: Numerical modeling: Model the cooling element as a porous medium; Under the conditions of laminar incompressible flow, the fluid dynamics are governed by the dimensionless forms of the continuity equation and the momentum equation; The fluid-solid coupled heat transfer model is governed by the dimensionless energy conservation equation; Step 3: Construct an objective function: The optimization objective is defined as a weighted function of heat transfer and fluid dissipated power, and a fluid-solid heat transfer topological optimization model is constructed; Step 4: Solve the objective function; Step 5: Restore the shape and structure of the cooling element. The present invention also discloses a precision gear grinding machine tool and a cooling element.

This invention discloses an optimized design method for support structures to control thermal stress in metal additive manufacturing, relating to the field of metal additive manufacturing. The method includes the following steps: defining a design domain and a non-design domain; initializing design variables; converting design variables into physical variables through density filtering and projection; establishing an interpolation model between the physical variables and the overall structural stiffness; performing finite element simulation on the layer-by-layer additive manufacturing process of the overall structure to obtain the thermal deformation of the overall structure; and calculating the maximum thermal stress σ of the structure. pn The proposed method involves calculating the volume fraction V of the supporting structure and the suspension angle constraint response G; determining the sensitivity; updating the design variables to solve the optimization model; determining whether convergence has occurred; and post-processing the optimization results. The structure designed by this method ensures that the thermal stress of the overall structure is controllable after additive manufacturing, avoiding cracking and delamination caused by excessive thermal stress.

The invention relates to the field of computer-aided engineering and intelligent manufacturing, and provides a topological optimization design method integrating subjective preferences. The method comprises the following steps: initializing material density distribution in a design domain, and intelligently recommending an initial density distribution scheme according to a subjective preference type selected by a user; calculating an objective response value and sensitivity thereof; calling a pre-trained subjective preference scoring model to subjectively evaluate the current material density distribution, outputting a subjective evaluation value, and calculating the sensitivity of the subjective evaluation value based on a numerical perturbation method; the objective response value, the sensitivity of the objective response value, the subjective evaluation value and the sensitivity of the subjective evaluation value are input into an MMA optimizer for iterative calculation, and material density distribution is dynamically updated to balance subjective preference and objective constraint; and judging whether the updated material density distribution meets a convergence condition set by a user, if so, performing post-processing visualization on the optimized material density distribution, and outputting a final topological configuration, otherwise, returning to a new round of iteration.

The invention relates to the technical field of lattice structure optimization, and discloses a topological optimization-based lattice structure, a design method and application, a topological optimization model is constructed, and physical parameters and optimization parameters of the topological optimization model are initialized; defining a structural design domain, a load and a boundary condition corresponding to the topological optimization model, and establishing a finite element model; the defined load and boundary conditions are applied to the topological optimization model, finite element analysis is carried out, displacement response of each node on a design domain is obtained, and sensitivity of structural flexibility and volume about design variables is analyzed; filtering the sensitivity, and filtering the material density represented by the design variable by adopting a projection method based on a Heaviside function so as to inhibit a checkerboard phenomenon; updating a design variable according to the filtered sensitivity and material density; and checking whether the current iteration result meets a convergence condition, if so, outputting the result, and if not, returning to continue iteration.

The invention belongs to the field of structure optimization design, and particularly discloses a multi-model topological optimization method and system for a complex geometric model, and the method comprises the steps: building a corresponding finite element model according to a geometric model of a wing corrugated structure; dividing a design domain for the geometric model, and establishing a topological model corresponding to the finite element model; geometric mapping is carried out on the shared design domain through manufacturing constraints with repeated modes, a mapping relation of a local coordinate system for processing a large deformation area is established, a topology model capable of being synchronously optimized is formed, and an output file of the topology model is exported; and carrying out synchronous loop optimization on the plurality of topology models by utilizing a parallel computing interface, and judging optimization results of the topology models according to a convergence criterion until the topology models reach the convergence criterion, so as to obtain a final optimization model. According to the method, the geometric mapping effect and the multi-working-condition synchronous optimization effect of the complex geometric model can be improved.

The invention relates to the field of model design, and provides an aircraft multi-objective optimization design method and system based on semanteme in order to improve the calculation efficiency of multi-objective balance. Firstly, original design parameters and design rules are obtained, obtained data are converted into semantic vectors through a semantic embedding function, and adjacency matrixes are obtained; generating a semantic gene map based on the semantic vector and the adjacent matrix, constructing a comprehensive objective function, and performing optimization solution based on the semantic gene map; and creating a target mapping function, and mapping an optimized result into a specific engineering target based on the target mapping function. By introducing a semantic modeling and cognitive enhancement mechanism, aircraft structure optimization is improved from traditional numerical drive to semantic drive, a prediction and search process is accelerated by using semantic space and cognitive reasoning, and global optimization and traceability are realized in combination with crowd intelligence evolution and a cross-domain hypernetwork; not only are efficiency and robustness improved, but also engineering feasibility and compliance credibility of a design result are ensured.

The invention discloses a method for optimizing manufacturability of a welding topological optimization structure, which belongs to the technical field of computer aided design and comprises the following steps: acquiring boundary conditions of a design domain and a geometric model in the design domain; performing initial layout on the geometric model in the design domain through the quadrilateral component; the overlapped quadrilateral assemblies are operated, and segmented and recombined convex polygon assemblies are obtained; acquiring a position relationship between the network nodes in the design domain and the convex polygon component, and converting the position relationship into a unit density field; establishing a topological optimization model according to the unit density field; updating control parameters of the quadrilateral component according to the sensitivity of the target function and the sensitivity of the constraint function; and outputting the layout of the convex polygon component in the design domain after the control parameters are optimized as an optimization result until the topological optimization model converges. According to the optimization method for the manufacturability of the welding topological optimization structure, the problems that existing welding topological optimization is poor in manufacturability and complex in structure post-processing are solved.

The invention provides a neural network multi-objective optimization and FPGA hardware acceleration collaborative design method, and belongs to the field of deep learning model compression and hardware collaborative design. The method comprises the following steps: constructing a joint optimization space containing a neural network compression parameter and an FPGA hardware design parameter; a multi-target Bayesian optimization search strategy is adopted, iterative search is carried out in the joint optimization space, model precision, FPGA resource occupation and reasoning delay are synchronously optimized, and optimal candidate configuration is obtained; matching the compressed network structure with the FPGA parallel architecture by using a hardware-perceived pruning and quantification strategy; a multi-task performance prediction model is adopted to quickly predict the precision, resource occupation and delay of the optimal candidate configuration so as to accelerate the search process; according to the optimal configuration, a hardware accelerator code facing the target FPGA is automatically generated, and integration and implementation are completed. According to the method, collaborative optimization of neural network compression and hardware design is achieved, FPGA resource occupation can be remarkably reduced, the reasoning speed can be increased, and meanwhile the model precision is kept.

The invention provides a concurrent vulnerability detection method based on a code concurrent attribute graph. The method comprises the following steps: adopting a vulnerability detection tool CONCODEQL; the method comprises the following steps: S1, initializing a code attribute graph and identifying key nodes according to source codes; s2, traversing the initial graph to construct a concurrency relationship; and S3, detecting concurrent violation according to the designed domain specific language. According to the method, by introducing the CCPG, various relations and features in the concurrent program source code can be comprehensively expressed, and the defect that an existing static code detection method based on structured representation is difficult to recognize complex concurrent vulnerabilities is overcome. And on the basis of a CCPG domain-specific language, detection for different types of concurrent vulnerabilities is supported, and the expansibility of the tool is improved. By combining the capability of the CCPG, the false report rate and the missing report rate of a traditional data race detection method are effectively reduced, and the detection capability of complex concurrency problems is enhanced.

The invention discloses a structural topology optimization design method for additive manufacturing and a related device, which can be used in the field of structural design, in the method, based on the shape of a structural design domain and a parameterized density field function including the structural design domain, a structural density field is determined, and a suspension angle constraint function at a structural boundary is constructed; constructing a boundary gradient constraint function based on a normal vector pointing to the interior of the structural design domain on the boundary of the structural design domain; discretizing the structural design domain into a plurality of finite element units, and constructing a material stiffness matrix to calculate an overall stiffness matrix; and constructing a topological optimization mathematical model according to the finite element balance constraint, the volume constraint, the suspension angle constraint function and the boundary gradient constraint function based on the overall stiffness matrix, and solving to obtain a structural topological optimization result. Therefore, through multi-constraint collaborative optimization, the conflict problem of suspended constraint and material anisotropy on the forming direction is solved, and a structural topological optimization result considering manufacturability and structural performance is obtained.