35 results about "Topology optimization problem" patented technology

The invention discloses a density evolution topological optimization method for a continuum structure with a smooth boundary. The method comprises the following steps: establishing a geometric initialdesign domain of the continuum structure; establishing a finite element model of a geometric initial design domain based on a material interpolation model without a penalty function; establishing a continuum structure topological optimization problem mathematical model; calculating the sensitivity of the optimization target and the constraint condition to the design variable, and conducting filtering; updating a design variable according to the sensitivity by adopting an optimization algorithm, and carrying out graded filtering on the density to achieve convergence and constraint conditions so as to obtain a finite element model of an optimized structure; and constructing a node strain energy level set, and processing a boundary unit to obtain a structure topological optimization model ofa smooth boundary displayed based on the node density or the node strain energy level set. According to the method, a penalty-function-free material interpolation model and a density grading filtering method are provided, a structure boundary unit is processed, an optimization result with a smooth boundary is obtained, and the topological optimization problem is efficiently solved.

The invention discloses a variable density method-based stress and strain energy double-constraint topological optimization method. Based on a variable density method and an SIMP material interpolation model, a finite element method is utilized to calculate the strain energy of a structure and the Mises stress of a unit, the minimal structure volume is taken as an objective function, the structurewhole is taken as a constraint, a P norm method condenses the unit stress of the structure into a global stress constraint; a topological optimization model containing stress and strain energy doubleconstraints is constructed, the sensitivity of an objective function and a constraint function relative to a design variable is calculated, a topological optimization problem is solved by using a moving asymptotic line method, iteration is repeated until a convergence condition is met, and an optimal topological structure is obtained. The stress and strain energy double-constraint topological optimization method is used for topological optimization of the structure, the problem that a topological structure obtained through a traditional topological optimization method cannot meet the strengthor rigidity condition is solved, and the topological structure obtained through topological optimization meets the preset structural static strength and rigidity condition.

The invention discloses a structure topology optimization method based on material field reduction series expansion, and solves the problem of low calculation efficiency caused by too many design variables and need of relative density or sensitivity filtering measures in traditional density method topology optimization. The method comprises the following steps: a bounded material field consideringcorrelation is defined; a spectral decomposition method is adopted to perform transform to obtain a linear combination of a series of undetermined coefficients, the undetermined coefficients are usedas design variables, an optimization model is constructed based on a unit density interpolation model, a gradient class or non-gradient class optimization algorithm is adopted to solve a topologicaloptimization problem, and then a topological configuration with a clear boundary is obtained efficiently. According to the method, the number of design variables in density method topology optimization can be greatly reduced, and meanwhile, the method has the natural advantage of completely avoiding grid dependence and chessboard format problems. The method also inherits the advantages of simple density method form, convenience in engineering popularization and the like, the optimization solving speed is high, and the research and development efficiency of the innovative topological design ofthe complex equipment structure can be ensured.

The invention provides a multi-DOF (degree of freedom) topological optimization method for a compliant parallel mechanism. The method comprises the following steps in sequence: arranging a kinematic chain of the compliant parallel mechanism to be a design domain of the topological optimization problem; building a compliant matrix for each kinematic chain, and assembling all the compliant matrixes to be a rigid matrix of the compliant parallel mechanism; deriving the rigidity and kinematic transmission relation of input/ output points according to the rigidity matrix of the mechanism; creating a topological optimization model to optimize the kinematic chain. The method can be applied to a comprehensive plane 1-3 degrees of freedom, spatial 2-6 degrees of freedom, redundant driving and other compliant parallel mechanisms; the topology with the optimal performance can be obtained according to the design problem without referring to the existing rigid mechanism; in addition, the topology is unique and novel, and the topology type of the compliant parallel mechanism is enriched.

The invention provides a structure non-gradient topological optimization method based on a sequence Kriging proxy model, and belongs to the field of structure and multidisciplinary optimization design. The method mainly comprises three parts of reduction series expansion of a design domain material field, establishment of the non-gradient topological optimization model and solution of a sequence Kriging proxy model algorithm. According to the method, the topological optimization problem design variables are effectively reduced through reduced series expansion of the material field function, and the topological optimization problem described by the material field within 50 design variables can be effectively solved by using a sequence Kriging agent model algorithm with an adaptive design space adjustment strategy. The method does not need a performance function to design sensitivity information, and is suitable for solving complex multi-field coupling, multidisciplinary and high-nonlinearity topological optimization problems. The method not only inherits the simple form of density method topological optimization, but also enables the boundary of the topological structure to be clearand smooth, facilitates the integration of various commercial and self-developed finite element software, and is a topological optimization method convenient for popularization and engineering application.

The invention relates to a multiple-working-condition adaptivity topological optimization method of an automotive transmission case. A compromise programming method in mathematics is applied to a multiple-working-condition topological optimization design of the automotive transmission case. The method does not adopt a traditional method, i.e. a linear weighting method, used for solving multiple-working-condition topological optimization problems, instead, a target function extreme value is obtained under each working condition, a target function of a multiple-working-condition topological optimization model is reconstructed, then, topological optimization calculation is carried out, and an obtained topological structure can simultaneously satisfy various working conditions. While the obtained topological structure satisfies various working conditions, a situation that the linear weighting method can not solve feasible region is a non convex set can be avoided, and therefore, a multiple-working-condition topological optimization result is more accurate.

The invention discloses a macro-micro integrated structure topology optimization method considering stress constraints. According to the method, for the topology optimization problem of a structure with a macroscopic solid material and a micro-truss at the same time, the micro-truss is equivalently expressed as a mean material by adopting a representative volume element method; for the solid material, a stress comprehensive function is used for representing the stress level of the solid material; then an adjoint vector method is adopted for solving the stress comprehensive function and a partial derivative value of a displacement to a design variable; and finally, the macro-micro integrated structure topology optimization considering the stress constraint is solved by building a double-level optimization model, wherein an inner layer is solved by adopting a moving asymptotic line method, the displacement constraint of the structure and the stress constraint of the solid material are achieved, and an outer layer adopts a univariate function zero solving algorithm to realize the stress constraint of the micro-truss. The provided topology optimization method can effectively control the stress level of the macro-micro integrated structure to realize the topological optimization of the macro-micro integrated structure under the stress constraint.

The invention belongs to the technical field related to structure optimization design, and discloses a topological optimization design method for generating a bracing structure in additive manufacturing. The method comprises the following steps: (1) reading a three-dimension model of a product to obtain information such as geometric construction of the model; (2) generating a design region of a support structure according to parameters of product arrangement, and manufacturing equipment and a base plate to generate a design region of the support structure; (3) setting relevant material parameters, dividing grid, taking the material filling rate as a design variable, and setting objective functions and constrain conditions for topological optimization; and (4) performing topological optimization on the design region of the support structure by utilizing a topological optimization method and finally providing the optimal structure design scheme and related data. According to the method,generation of the support structure is taken as a topological optimization problem, and generation of the support structure can be performed according to the geometric structure and material performances of the product, thus reducing the possibilities of deformation and cracking caused during product manufacture and increasing the manufacture success rate.

The invention provides a structural topology optimization solving method based on resampling particle swarm optimization, which can realize the topology optimization of structural topology optimization problem and has higher solving efficiency. The method comprises the main steps of 1 establishing the optimization model of the topology optimization problem; 2 establihsing the fitness function of the topology optimization problem; 3 utilzing the resample particle swarm optimization to solve that problem accord to the fitness function; 4 obtaining the optimal value of the objective function according to the optimal solution. The method can effectively solve the structural topology optimization problem. For that same topology optimization problem, after comparing with the traditional particleswarm optimization and the genetic optimization, the method of the invention can prove that the method in the invention can obtain a better optimization result, has high solving efficiency, and has advantages in stability of the result of multiple solving. The method is simple, practical and easy to implement, and has the value of popularization and application.

The invention discloses a mobile robot path planning method based on a parameterized level set. The method comprises: enabling a mobile robot path planning problem to be equivalent to a topology optimization problem of a heat conduction path; establishing a finite element calculation model of a base structure; and with the heat dissipation weakness as an objective function, determining a growth direction of each step of cooling channel based on a topology optimization method expressed by a parameterized level set, and acquiring a planned path based on continuous growth of the cooling channel.Therefore, a problem of falling into local optimum is solved fundamentally. The generated path is one with the low energy consumption by using the heat dissipation weakness as the objective function;the generated path is formed by a series of explicit geometric points and can be applied to navigation of the mobile robot directly; on the basis of combination of the growth conception, the high computing load in one operation is avoided and the planning quality is improved; and since the growth direction is not limited by the underlying mesh, searching is performed freely to obtain an optimal path that is better than that in the traditional method.

The invention discloses a network topology optimization method. The method comprises the following steps: acquiring a first network topology and a traffic model of a target network; according to the first network topology and a flow model, determining a first topology evaluation value corresponding to the first network topology through target topology evaluation predetermined based on a graph neural network and/or artificial topology evaluation; and if the first topology evaluation value does not meet the first preset condition, determining a second network topology according to the first network topology, wherein a second topology evaluation value corresponding to the second network topology meets the first preset condition, and the second network topology is used for adjusting the network topology of the target network, so that the network topology of the target network is adjusted to the second network topology. According to the technical scheme, the topology optimization problem of the network is converted into a mathematical optimization problem taking topology evaluation as a target function, so that the topology optimization result is easy to quantify and evaluate, the calculation complexity in the topology optimization process is remarkably reduced, and the network topology optimization problem is systematically solved.

The invention discloses a compliant mechanism topological optimization method based on static strength and fatigue constraint. The compliant mechanism topological optimization method comprises the following steps: evaluating the static strength and fatigue strength of a compliant mechanism; converting static strength and fatigue constraints of the mechanism into different stress constraints, and aggregating various stress constraints of the unit into different global stress constraints; constructing a compliant mechanism topological optimization model based on static strength and fatigue constraints by taking output displacement maximization as a target function and taking static strength, fatigue and volume as constraints; carrying out sensitivity analysis correcting the sensitivity through mapping filtering, solving the topological optimization problem, carrying out iteration till the convergence criterion is met, and obtaining the optimal compliant mechanism topological structure. According to the method, the von Mises with symbols and the corrected Goodman fatigue criterion are used for carrying out topological optimization on the compliant mechanism based on static strength and fatigue constraint, the obtained compliant mechanism can meet the requirements for static strength and fatigue strength, and a hinge-like structure is effectively avoided.

The invention discloses a continuum displacement and frequency constraint topological optimization design method considering damage-safety conditions. The method comprises the steps: establishing a finite element model according to a continuum-based structure; determining a damage working condition number, and inputting an initial damage area center coordinate value and a damage area parameter; inputting displacement and frequency constraint optimization parameters to form an optimization model; carrying out static analysis on the damage-safety structure containing the damage working conditionin sequence, and constructing explicit expression of displacement constraints; carrying out modal analysis of the damage-safety structure, and constructing an explicit expression of frequency constraint; establishing an approximate continuous mathematical optimization column formula of a topological optimization model considering displacement and frequency constraints under damage-safety conditions, and solving the optimization model; and performing inversion processing on the optimal topological configuration to obtain the optimal topological configuration and displacement and fundamental frequency of each structure damage condition. According to the invention, a reference is provided for considering the damage-safety topological optimization problem in the field of statics and dynamics.

The invention discloses a continuum frequency constraint topological optimization design method considering damage-safety. The continuum frequency constraint topological optimization design method comprises the following steps: firstly, establishing a finite element model based on a continuum-based structure; determining a damage working condition number, and inputting an initial damage area center coordinate value and a damage area parameter; inputting frequency constraint optimization parameters to form a frequency constraint optimization model considering damage-safety conditions; sequentially carrying out modal analysis on the damage-safety structure containing the damage working condition, and extracting a modal analysis result of the damage condition of each structure; establishing an approximate continuous mathematical optimization column formula of the topological optimization model considering the frequency constraint under the damage-safety condition; solving the optimizationmodel by adopting a mathematical programming algorithm; and performing inversion processing on the optimal topological configuration to obtain the optimal topological configuration and the fundamental frequency of the optimal configuration. According to the method, the redundancy of the structure can be obviously improved, and a reference is provided for considering the topological optimization problem of damage-safety in the field of dynamics.

According to the topological optimization method for maximizing the fundamental frequency of the mechanical structure, topological optimization of maximizing the fundamental frequency of the mechanical structure under the quality constraint condition can be achieved, and higher calculation efficiency is achieved. The method comprises the following specific steps: 1, establishing a topological optimization mathematical model of a mechanical structure; 2, deriving an iterative calculation formula of a design variable; 3, controlling a topological optimization iterative solution process; and 4, obtaining the optimal topological form of the mechanical structure according to the optimal solution of the unit relative density. According to the method, the problem of mechanical structure dynamicstopology optimization can be efficiently solved, a clear structure topology form can be obtained in the first several steps of optimization iteration, and the method has the advantages of being high in convergence speed, high in calculation efficiency and the like and can be popularized and applied to structural design of complex mechanical equipment.

The invention provides a mechanical structure topological optimization method based on a multi-population genetic algorithm, which can realize topological design for minimizing structural flexibilityunder a volume constraint condition. The method comprises the following specific steps: 1, dividing finite element grids, and establishing an optimization model of a topological optimization problem;2, setting operation parameters of a multi-population genetic algorithm; 3, solving the topological optimization model, and drawing a topological optimization result. According to the method, the probability of searching for a topological optimization global optimal solution can be improved, and a stable topological optimization result is obtained; the method has the advantages of being fast in iterative convergence, clear and stable in optimization result and the like and can be popularized and applied to structural design of complex mechanical equipment.

The invention provides a multi-material manipulator. The multi-material manipulator comprises a soft material part obtained in an integrated injection molding mode and a hard material part obtained ina 3D mode. The hard material part is hollow, the soft material is arranged in the hollow part of the hard material part in a matched mode, and the hard material part obtained in a 3D mode comprises the following steps that initialization of a topological optimization problem is conducted, specifically, a design domain, design variables and constraint conditions of a hollow cuboid of the hard material part are given; sensitivity analysis is carried out on the topological optimization problem; solving a topological optimization problem by adopting a fastest descent method and obtaining an optimization result; outputting an optimization result as an stl file; and importing the stl file into a 3D printer to finish machining of the hard material part. Compared with the prior art, the soft material part obtained in an integrated injection molding mode and the hard material part obtained in a 3D mode of the multi-material manipulator have the advantages of being sufficient in flexibility andrigidity, capable of meeting the strength requirement and low in cost.

In various embodiments, a topology optimization application solves a topology optimization problem associated with designing a three-dimensional (“3D”) object. The topology optimization application coverts a first shape having a first resolution and representing the 3D object to a coarse shape having a second resolution that is lower than the first resolution. Subsequently, the topology optimization application computes coarse structural analysis data based on the coarse shape. The topology optimization application then uses a trained machine learning model to generate a second shape having the first resolution and representing the 3D object based on the first shape and the coarse structural analysis data. The trained machine learning model modifies a portion of a shape having the first resolution based on structural analysis data having the second resolution. Advantageously, generating the second shape based on structural analysis data having a lower resolution reduces computational complexity relative to prior art techniques.