Reducing computational effort in topology optimization considering the deformation in additive manufacturing

Integrating topology optimization and additive manufacturing (AM) technology can facilitate innovative product development. However, laser powder bed fusion, which is the predominant method in metal AM, can lead to issues such as residual stress and deformation. Recently, topology optimization methods considering these stresses and deformations have been proposed; however, they suffer from challenges caused by an increased computational cost. In this study, we propose a method for reducing computational cost in topology optimization considering the deformation in AM. An inherent strain method-based analytical model is presented for simulating the residual stress and deformation in the AM process. Subsequently, a constraint condition to suppress the deformation is formulated, and a method to reduce the computational cost of the adjoint analysis in deriving sensitivity is proposed. The minimum mean compliance problem considering AM deformation and self-support constraints can then be incorporated into the level set-based topology optimization framework. Finally, numerical examples are presented for validating the effectiveness of the proposed topology optimization method.