No abstract

The potential of topology optimization to amplify the benefits of additive manufacturing (AM), by fully exploiting the vast design space that AM allows, is widely recognized. However, existing topology optimization approaches do not consider AM-specific limitations during the design process, resulting in designs that are not self-supporting. This leads to additional effort and costs in postprocessing and use of sacrificial support structures. To overcome this difficulty, this paper presents a topology optimization formulation that includes a simplified AM fabrication model implemented as a layerwise filtering procedure.Unprintable geometries are effectively excluded from the design space, resulting in fully self-supporting optimized designs. The procedure is demonstrated on numerical examples involving compliance minimization, eigenfrequency maximization and compliant mechanism design. Despite the applied restrictions, in suitable orientations fully printable AM-restrained designs matched the performance of reference designs obtained by conventional topology optimization.

Additive manufacturing (AM) offers exciting opportunities to manufacture parts of unprecedented complexity. Topology optimization is essential to fully exploit this capability. However, AM processes have specific limitations as well. When these are not considered during design optimization, modifications are generally needed in post-processing, which add costs and reduce the optimized performance. This paper presents a filter that incorporates the main characteristics of a generic AM process, and that can easily be included in conventional density-based topology optimization procedures. Use of this filter ensures that optimized designs comply with typical geometrical AM restrictions. Its performance is illustrated on compliance minimization problems, and a 2D Matlab implementation is provided.

In various applications, design problems involving structures and compliant mechanisms experience fluidic pressure loads. During topology optimization of such design problems, these loads adapt their direction and location with the evolution of the design, which poses various challenges. A new density-based topology optimization approach using Darcy's law in conjunction with a drainage term is presented to provide a continuous and consistent treatment of design-dependent fluidic pressure loads. The porosity of each finite element and its drainage term are related to its density variable using a Heaviside function, yielding a smooth transition between the solid and void phases. A design-dependent pressure field is established using Darcy's law and the associated PDE is solved using the finite element method. Further, the obtained pressure field is used to determine the consistent nodal loads. The approach provides a computationally inexpensive evaluation of load sensitivities using the adjoint-variable method. To show the efficacy and robustness of the proposed method, numerical examples related to fluidic pressure loaded stiff structures and small-deformation compliant mechanisms are solved. For the structures, compliance is minimized, whereas for the mechanisms a multi-criteria objective is minimized with given resource constraints.

SUMMARYThis article presents a detailed study on the potential and limitations of performing higher-order multiresolution topology optimization with the finite cell method. To circumvent stiffness overestimation in high-contrast topologies, a length-scale is applied on the solution using filter methods. The relations between stiffness overestimation, the analysis system, and the applied length-scale are examined, while a highresolution topology is maintained. The computational cost associated with nested topology optimization is reduced significantly compared with the use of first-order finite elements. This reduction is caused by exploiting the decoupling of density and analysis mesh, and by condensing the higher-order modes out of the stiffness matrix.

Document VersionAbstract In this paper, we propose a unified aggregation and relaxation approach for topology optimization with stress constraints. Following this approach, we first reformulate the original optimization problem with a design-dependent set of constraints into an equivalent optimization problem with a fixed design-independent set of constraints. The next step is to perform constraint aggregation over the reformulated local constraints using a lower bound aggregation function. We demonstrate that this approach concurrently aggregates the constraints and relaxes the feasible domain, thereby making singular optima accessible. The main advantage is that no separate constraint relaxation techniques are necessary, which reduces the parameter dependence of the problem. Furthermore, there is a clear relationship between the original feasible domain and the perturbed feasible domain via this aggregation parameter.

Additive manufacturing (AM) enables the fabrication of parts of unprecedented complexity. Dedicated topology optimization approaches, that account for specific AM restrictions, are instrumental in fully exploiting this capability. In popular powder-bed-based AM processes, the critical overhang angle of downward facing surfaces limits printability of parts. This can be addressed by changing build orientation, part adaptation, or addition of sacrificial support structures. Thus far, each of these measures have been studied separately and applied sequentially, which leads to suboptimal solutions or excessive computation cost. This paper presents and studies, based on 2D test problems, an approach enabling simultaneous optimization of part geometry, support layout and build orientation. This allows designers to find a rational tradeoff between manufacturing cost and part performance. The relative computational cost of the approach is modest, and in numerical tests it consistently obtains high quality solutions.

No abstract