Overhang control in topology optimization: a comparison of continuous front propagation-based and discrete layer-by-layer overhang control

Although additive manufacturing (AM) allows for a large design freedom, there are some manufacturing limitations that have to be taken into consideration. One of the most restricting design rules is the minimum allowable overhang angle. To make topology optimization suitable for AM, several algorithms have been published to enforce a minimum overhang angle. In this work, the layer-by-layer overhang filter proposed by Langelaar (Struct Multidiscip Optim 55(3):871–883, 2017), and the continuous, front propagation-based, overhang filter proposed by van de Ven et al. (Struct Multidiscipl Optim 57(5):2075–2091, 2018) are compared in detail. First, it is shown that the discrete layer-by-layer filter can be formulated in a continuous setting using front propagation. Then, a comparison is made in which the advantages and disadvantages of both methods are highlighted. Finally, the continuous overhang filter is improved by incorporating complementary aspects of the layer-by-layer filter: continuation of the overhang filter and a parameter that had to be user-defined are no longer required. An implementation of the improved continuous overhang filter is provided.

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

[2]  J. Petersson,et al.  Numerical instabilities in topology optimization: A survey on procedures dealing with checkerboards, mesh-dependencies and local minima , 1998 .

[3]  Guido A.O. Adam,et al.  Design for Additive Manufacturing—Element transitions and aggregated structures , 2014 .

[4]  Boyan Stefanov Lazarov,et al.  Topology optimization using PETSc: An easy-to-use, fully parallel, open source topology optimization framework , 2015 .

[5]  Robert Maas,et al.  Continuous front propagation-based overhang control for topology optimization with additive manufacturing , 2018 .

[6]  Matthijs Langelaar,et al.  Towards design for precision additive manufacturing : A simplified approach for detecting heat accumulation , 2018 .

[7]  Yongqiang Yang,et al.  Research on the fabricating quality optimization of the overhanging surface in SLM process , 2013 .

[8]  Robert Maas,et al.  A PDE-Based Approach to Constrain the Minimum Overhang Angle in Topology Optimization for Additive Manufacturing , 2017 .

[9]  Barry F. Smith,et al.  PETSc Users Manual , 2019 .

[10]  Vipin Kumar,et al.  A Parallel Algorithm for Multilevel Graph Partitioning and Sparse Matrix Ordering , 1998, J. Parallel Distributed Comput..

[11]  Joel W. Barlow,et al.  The Prediction of the Emissivity and Thermal Conductivity of Powder Beds , 2004 .

[12]  Christophe Geuzaine,et al.  Gmsh: A 3‐D finite element mesh generator with built‐in pre‐ and post‐processing facilities , 2009 .

[13]  Matthijs Langelaar,et al.  Topology optimization of 3D self-supporting structures for additive manufacturing , 2016 .

[14]  C. C. Law,et al.  ParaView: An End-User Tool for Large-Data Visualization , 2005, The Visualization Handbook.

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

[16]  Anders Clausen,et al.  Efficient topology optimization in MATLAB using 88 lines of code , 2011 .

[17]  William Gropp,et al.  Efficient Management of Parallelism in Object-Oriented Numerical Software Libraries , 1997, SciTools.

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

[19]  Alexander Vladimirsky,et al.  Ordered Upwind Methods for Static Hamilton-Jacobi Equations: Theory and Algorithms , 2003, SIAM J. Numer. Anal..

[20]  Matthijs Langelaar,et al.  Combined optimization of part topology, support structure layout and build orientation for additive manufacturing , 2018, Structural and Multidisciplinary Optimization.

[21]  Oded Amir,et al.  Topology optimization for staged construction , 2018 .

[22]  Dirk Herzog,et al.  Design guidelines for laser additive manufacturing of lightweight structures in TiAl6V4 , 2015 .

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

[24]  M. Bendsøe,et al.  Material interpolation schemes in topology optimization , 1999 .

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

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

[27]  B. Lazarov,et al.  Parallel framework for topology optimization using the method of moving asymptotes , 2013, Structural and Multidisciplinary Optimization.

[28]  Kaiqing Zhang,et al.  Topology optimization considering overhang constraint in additive manufacturing , 2019, Computers & Structures.

[29]  J. Kruth,et al.  Residual stresses in selective laser sintering and selective laser melting , 2006 .

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

[31]  T. E. Bruns,et al.  Topology optimization of non-linear elastic structures and compliant mechanisms , 2001 .

[32]  Charlie C. L. Wang,et al.  Current and future trends in topology optimization for additive manufacturing , 2018 .

[33]  Ray Y. Zhong,et al.  Investigation of printable threshold overhang angle in extrusion-based additive manufacturing for reducing support waste , 2018, Int. J. Comput. Integr. Manuf..