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Takao Miki

Publications and source records attributed to Takao Miki.

5 recordsLinked to original sources

Elastoplastic inherent strain-based topology optimization for residual stress reduction in metal additive manufacturing

This paper proposes a topology optimization method for reducing the residual stress arising in the building process of metal additive manufacturing. First, a layer-by-layer process analysis model based on an elastoplastic inherent strain method is introduced. In this model, the incremental displacement is solved anew at each layer step, and the stress history is explicitly incorporated into the constitutive equation as the stress accumulated up to the previous step, which guarantees the stress continuity across layer interfaces without introducing activation strains. Next, the design sensitivity of this analysis model is derived based on the adjoint method. Taking the pair of the stress and the equivalent plastic strain as the state variables reduces the dependency between layer steps to a one-step recurrence, and the adjoint fields are constructed as a layer-by-layer reverse sweep that reuses the coefficient tensors obtained in the forward analysis. Consequently, the cost of the sensitivity analysis scales linearly with the number of layers and remains of the same order as that of the forward analysis. An optimization problem is then formulated based on the density method to minimize the P-norm of the residual stress at the completion of the building process under the volume and final-use compliance constraints, and the derived sensitivities are verified by comparison with central finite differences. Finally, the proposed method is demonstrated through two- and three-dimensional examples of residual stress minimization under a compliance constraint. The results clarify that, under the elastoplastic analysis, the maximum residual stress is bounded by the yield surface, and the optimization therefore reduces the extent of the yielded and plastic strain accumulating regions rather than the peak stress value.

cs.CE

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.

cs.CE

Self-support topology optimization considering distortion for metal additive manufacturing

This paper proposes a self-support topology optimization method that considers distortion to improve the manufacturability of additive manufacturing. First, a self-support constraint is proposed that combines an overhang angle constraint with an adjustable degree of the dripping effect and a thermal constraint for heat dissipation in the building process. Next, we introduce a mechanical model based on the inherent strain method in the building process and propose a constraint that can suppress distortion. An optimization problem is formulated to satisfy all constraints, and an optimization algorithm based on level-set-based topology optimization is constructed. Finally, two- and three-dimensional optimization examples are presented to validate the effectiveness of the proposed topology optimization method.

cs.CE

Topology optimization of the support structure for heat dissipation in additive manufacturing

A support structure is required to successfully create structural parts in the powder bed fusion process for additive manufacturing. In this study, we present the topology optimization of a support structure that improves the heat dissipation in the building process. First, we construct a numerical method that obtains the temperature field in the building process, represented by the transient heat conduction phenomenon with the volume heat flux. Next, we formulate an optimization problem for maximizing heat dissipation and develop an optimization algorithm that incorporates a level-set-based topology optimization. A sensitivity of the objective function is derived using the adjoint variable method. Finally, several numerical examples are provided to demonstrate the effectiveness and validity of the proposed method.

cs.CE

Topology optimization considering the distortion in additive manufacturing

Additive manufacturing is a free-form manufacturing technique in which parts are built in a layer-by-layer manner. Laser powder bed fusion is one of the popular techniques used to fabricate metal parts. However, it induces residual stress and distortion during fabrication that adversely affects the mechanical properties and dimensional accuracy of the manufactured parts. Therefore, predicting and avoiding the residual stress and distortion are critical issues. In this study, we propose a topology optimization method that accounts for the distortion. First, we propose a computationally inexpensive analytical model for additive manufacturing that uses laser powder bed fusion and formulated an optimization problem. Next, we approximate the topological derivative of the objective function using an adjoint variable method that is then utilized to update the level set function via a time evolutionary reaction-diffusion equation. Finally, the validity and effectiveness of the proposed optimization method was established using two-dimensional design examples.

cs.CE