Morphable components topology optimization for additive manufacturing

This paper addresses the issue of minimizing support material in additive manufacturing (AM) during topology optimization (TO) in order to reduce material and post-processing costs. The TO method developed in this paper utilizes the moving morphable components (MMC) approach, where a structure is composed of several building blocks. This work introduces minimum build angle constraints to eliminate overhanging edges, supplementing these with penalty functions to ensure connectivity between building blocks, such that the TO output is printable. The MMC approach uses explicit geometric entities for the morphable components that are controlled by geometric parameters, such as length, thickness, and angle. These parameters are the design variables. Using this approach enables the formulation of geometric manufacturing constraints and the construction of CAD models, which are important advantages of the MMC method. Examples of a short cantilever beam and an MBB beam demonstrate the capabilities of the TO methods.

[1]  J. Sethian,et al.  FRONTS PROPAGATING WITH CURVATURE DEPENDENT SPEED: ALGORITHMS BASED ON HAMILTON-JACOB1 FORMULATIONS , 2003 .

[2]  Xiaoming Wang,et al.  A level set method for structural topology optimization , 2003 .

[3]  Takayuki Yamada,et al.  Matlab code for a level set-based topology optimization method using a reaction diffusion equation , 2014, Structural and Multidisciplinary Optimization.

[4]  Grégoire Allaire,et al.  Structural optimization under overhang constraints imposed by additive manufacturing technologies , 2017, J. Comput. Phys..

[5]  Matthijs Langelaar,et al.  An additive manufacturing filter for topology optimization of print-ready designs , 2016, Structural and Multidisciplinary Optimization.

[6]  K. Suresh,et al.  Multi-constrained 3D topology optimization via augmented topological level-set , 2016, ArXiv.

[7]  A. Clausen.  Topology Optimization for Additive Manufacturing , 2016 .

[8]  Julián A. Norato,et al.  A geometry projection method for the topology optimization of plate structures , 2016 .

[9]  Xu Guo,et al.  Doing Topology Optimization Explicitly and Geometrically—A New Moving Morphable Components Based Framework , 2014 .

[10]  Weihong Zhang,et al.  Feature-driven topology optimization method with signed distance function , 2016 .

[11]  Krishnan Suresh,et al.  Support structure constrained topology optimization for additive manufacturing , 2016, Comput. Aided Des..

[12]  Jian Zhang,et al.  A new topology optimization approach based on Moving Morphable Components (MMC) and the ersatz material model , 2016 .

[13]  Xiaoping Qian,et al.  Undercut and overhang angle control in topology optimization: A density gradient based integral approach , 2017 .

[14]  M. Bendsøe,et al.  Generating optimal topologies in structural design using a homogenization method , 1988 .

[15]  Ole Sigmund,et al.  A 99 line topology optimization code written in Matlab , 2001 .

[16]  Yongsheng Ma,et al.  3D level-set topology optimization: a machining feature-based approach , 2015 .

[17]  M. Bendsøe.  Optimal shape design as a material distribution problem , 1989 .

[18]  Martin Leary,et al.  Optimal topology for additive manufacture: A method for enabling additive manufacture of support-free optimal structures , 2014 .

[19]  K. Svanberg.  The method of moving asymptotes—a new method for structural optimization , 1987 .

[20]  Ying Liu,et al.  Self-supporting structure design in additive manufacturing through explicit topology optimization , 2017 .

[21]  James K. Guest,et al.  Topology optimization considering overhang constraints: Eliminating sacrificial support material in additive manufacturing through design , 2016 .