The application of multi-material topology optimization affords greater design flexibility compared to traditional single-material methods.However,density-based topology optimization methods encounter three unique cha...The application of multi-material topology optimization affords greater design flexibility compared to traditional single-material methods.However,density-based topology optimization methods encounter three unique challenges when inertial loads become dominant:non-monotonous behavior of the objective function,possible unconstrained characterization of the optimal solution,and parasitic effects.Herein,an improved Guide-Weight approach is introduced,which effectively addresses the structural topology optimization problem when subjected to inertial loads.Smooth and fast convergence of the compliance is achieved by the approach,while also maintaining the effectiveness of the volume constraints.The rational approximation of material properties model and smooth design are utilized to guarantee clear boundaries of the final structure,facilitating its seamless integration into manufacturing processes.The framework provided by the alternating active-phase algorithm is employed to decompose the multi-material topological problem under inertial loading into a set of sub-problems.The optimization of multi-material under inertial loads is accomplished through the effective resolution of these sub-problems using the improved Guide-Weight method.The effectiveness of the proposed approach is demonstrated through numerical examples involving two-phase and multi-phase materials.展开更多
The guide-weight method is introduced to solve two kinds of topology optimization problems with multiple loads in this paper.The guide-weight method and its Lagrange multipliers' solution methods are presented fir...The guide-weight method is introduced to solve two kinds of topology optimization problems with multiple loads in this paper.The guide-weight method and its Lagrange multipliers' solution methods are presented first,and the Lagrange multipliers' soution method of problems with multiple constraints is improved by the dual method.Then the iterative formulas of the guide-weight method for topology optimization problems of minimum compliance and minimum weight are derived and coresponding numerical examples are calculated.The results of the examples exhibits that when the guide-weight method is used to solve topology optimization problems with multiple loads,it works very well with simple iterative formulas,and has fast convergence and good solution.After comparison with the results calculated by the SCP method in Ansys,one can conclude that the guide-weight method is an effective method and it provides a new way for solving topology optimization problems.展开更多
The guide-weight method is introduced to solve the topology optimization problems of thermoelastic structures in this paper.First,the solid isotropic microstructure with penalization(SIMP)with different penalty factor...The guide-weight method is introduced to solve the topology optimization problems of thermoelastic structures in this paper.First,the solid isotropic microstructure with penalization(SIMP)with different penalty factors is selected as a material interpolation model for the thermal and mechanical fields.The general criteria of the guide-weight method is then presented.Two types of iteration formulas of the guide-weight method are applied to the topology optimization of thermoelastic structures,one of which is to minimize the mean compliance of the structure with material constraint,whereas the other one is to minimize the total weight with displacement constraint.For each type of problem,sensitivity analysis is conducted based on SIMP model.Finally,four classical 2-dimensional numerical examples and a 3-dimensional numerical example considering the thermal field are selected to perform calculation.The factors that affect the optimal topology are discussed,and the performance of the guide-weight method is tested.The results show that the guide-weight method has the advantages of simple iterative formula,fast convergence and relatively clear topology result.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52172356)the Hunan Provincial Natural Science Foundation of China(Grant No.2022JJ10012).
文摘The application of multi-material topology optimization affords greater design flexibility compared to traditional single-material methods.However,density-based topology optimization methods encounter three unique challenges when inertial loads become dominant:non-monotonous behavior of the objective function,possible unconstrained characterization of the optimal solution,and parasitic effects.Herein,an improved Guide-Weight approach is introduced,which effectively addresses the structural topology optimization problem when subjected to inertial loads.Smooth and fast convergence of the compliance is achieved by the approach,while also maintaining the effectiveness of the volume constraints.The rational approximation of material properties model and smooth design are utilized to guarantee clear boundaries of the final structure,facilitating its seamless integration into manufacturing processes.The framework provided by the alternating active-phase algorithm is employed to decompose the multi-material topological problem under inertial loading into a set of sub-problems.The optimization of multi-material under inertial loads is accomplished through the effective resolution of these sub-problems using the improved Guide-Weight method.The effectiveness of the proposed approach is demonstrated through numerical examples involving two-phase and multi-phase materials.
基金supported in part by the National Natural Science Founda-tion of China (Grant No 51075222)the Fund of State Key Laboratory of Tribology (Grant No SKLT10C02)the National Key Scientific and Technological Project (Grant No 2010ZX04004-116)
文摘The guide-weight method is introduced to solve two kinds of topology optimization problems with multiple loads in this paper.The guide-weight method and its Lagrange multipliers' solution methods are presented first,and the Lagrange multipliers' soution method of problems with multiple constraints is improved by the dual method.Then the iterative formulas of the guide-weight method for topology optimization problems of minimum compliance and minimum weight are derived and coresponding numerical examples are calculated.The results of the examples exhibits that when the guide-weight method is used to solve topology optimization problems with multiple loads,it works very well with simple iterative formulas,and has fast convergence and good solution.After comparison with the results calculated by the SCP method in Ansys,one can conclude that the guide-weight method is an effective method and it provides a new way for solving topology optimization problems.
基金supported by the National Natural Science Foundation of China(Grant No.51375251)the National Basic Research Program("973"Program)(Grant No.2013CB035400)of China
文摘The guide-weight method is introduced to solve the topology optimization problems of thermoelastic structures in this paper.First,the solid isotropic microstructure with penalization(SIMP)with different penalty factors is selected as a material interpolation model for the thermal and mechanical fields.The general criteria of the guide-weight method is then presented.Two types of iteration formulas of the guide-weight method are applied to the topology optimization of thermoelastic structures,one of which is to minimize the mean compliance of the structure with material constraint,whereas the other one is to minimize the total weight with displacement constraint.For each type of problem,sensitivity analysis is conducted based on SIMP model.Finally,four classical 2-dimensional numerical examples and a 3-dimensional numerical example considering the thermal field are selected to perform calculation.The factors that affect the optimal topology are discussed,and the performance of the guide-weight method is tested.The results show that the guide-weight method has the advantages of simple iterative formula,fast convergence and relatively clear topology result.
