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Abstract
In this paper, considering the porosity defects of Additive Manufacturing (AM), a level set topology optimization method for AM with porosity constraints is proposed. The concept of topological sensitivity is used to formulate a global porosity constraint function in the proposed method, and a level set topology optimization model considering porosity defects is obtained. To improve the robustness of the algorithm, the topology optimization model is solved in two phases. At first, the classical level set method without the porosity constraint is used to initially optimize the structure. During this process, the hole nucleation method combining bi-directional evolutionary structural optimization (BESO) and the topological sensitivity is used. Secondly, the topology optimization considering the effects of porosity is implemented on the preliminary optimization results. After performing the two-step optimization, a robust structure that alleviates the harmful impact of porosity defects is obtained. Finally, the robustness and effectiveness of the proposed method are validated by several two-dimensional numerical examples.
Highlights
Topology optimization is a calculation method that achieves the optimal material configuration in the design domain according to the given boundary conditions and the load conditions
Wreidthuocuetthcoenisniflduereinncgetohfeppoorroossiittyy, tchoensptorareinsta, re the maximum porosity constraint value appears near the reentrant corner of the optimization result shown in Figure 12c, while the porosity constraint value in other areas is almost zero
Considering the robustness of the algorithm, the topology optimization considering the porosity constraint is performed by two steps
Summary
Topology optimization is a calculation method that achieves the optimal material configuration in the design domain according to the given boundary conditions and the load conditions. The level set method is introduced as an alternative new method in the structural optimization field. This method uses a higher-dimensional level set function to implicitly represent the structural boundary (zero level set) and obtains the updated structural boundary via the evolution of the level set function during the optimization process. This implicit expression can avoid the relaxation of design variables and numerical instability. The level set topology optimization is recognized by many researchers
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