Abstract
This article falls within the scope of topology optimization for Additive Manufacturing processes and proposes an alternative strategy to prevent the phenomenon known as the Dripping Effect. The Dripping Effect is when an overhang constraint is imposed on topology optimization processes for Additive Manufacturing and is defined as the formation of oscillatory contour trends within the prescribed threshold angle. Although these drop-like formations constitute local minimizers of the constraint function, they do not provide a printable feature, and, therefore, they neither eliminate the need to form temporary support structures. So far, there has been no general agreement on how to prevent the Dripping Effect, so this work aims to introduce a strategy that effectively prevents it, and that at the same time may be easy to extrapolate to other types of geometric overhang restrictions. This paper provides a study of the origin of the Dripping Effect and gives detailed instructions on how the proposed prevention strategy is applied. In addition, several benchmark examples where the Dripping Effect is prevented are shown.
Highlights
Additive Manufacturing (AM) is the process of joining material to make objects from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies, such as traditional machining (ASTM International 2012). The input of these manufacturing techniques is constituted by a Computer-Aided Design (CAD) model, usually supplied under the form of a surface mesh that after a slicing process is converted into a series of two-dimensional layers
The present paper introduces a novel strategy to deal with the Dripping Effect generated when geometric overhang constraints are introduced within topology optimization algorithms
It is in the early stages of the optimization process that the algorithm is more prone to generate thin support members, especially if the overhang is evaluated in very small neighborhoods
Summary
Additive Manufacturing (AM) is the process of joining material to make objects from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies, such as traditional machining (ASTM International 2012). The different strategies that address the overhang issue during the topology optimization problem can be classified into additive manufacturing filters (Zhang et al 2019; Gaynor and Guest 2016; Langelaar 2017, 2016; Zou et al 2021; van de Ven et al 2018) and geometric overhang constraints (Qian 2017; Garaigordobil et al 2019, 2018; Garaigordobil and Ansola 2019; Garaigordobil 2018; Allaire et al 2017) The former group of methods analyses layer by layer whether the solid elements have enough support material underneath, while the latter explores the design domain looking for the contours of the structure, analyzing their inclination, and correcting those who are below a threshold overhang angle.
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