Computational design and additive manufacturing of periodic conformal metasurfaces by synthesizing topology optimization with conformal mapping

2018 ◽  
Vol 328 ◽  
pp. 477-497 ◽  
Author(s):  
Panagiotis Vogiatzis ◽  
Ming Ma ◽  
Shikui Chen ◽  
Xianfeng David Gu
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Conformal Mapping ◽  
Computational Design

Computational Design and Additive Manufacturing of Conformal Metasurfaces by Combining Topology Optimization With Riemann Mapping Theorem

2017 ◽  
Author(s):  
Panagiotis Vogiatzis ◽  
Ming Ma ◽  
Shikui Chen ◽  
Xianfeng David Gu
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Conformal Mapping ◽  
Level Set ◽  
Computational Design ◽  
Unit Cell ◽  
Free Form ◽  
Computational Framework ◽  
Riemann Mapping Theorem ◽  
Free Form Surfaces

In this paper, we present a computational framework for computational design and additive manufacturing of spatial free-form periodic metasurfaces. The proposed scheme rests on the level-set based topology approach and the conformal mapping theory. A 2D unit cell of metamaterial with tailored effective properties is created using the level-set based topology optimization method. The achieved unit cell is further mapped to the 3D quad meshes on a free-form surface by applying the conformal mapping method which can preserve the local shape and angle when mapping the 2D design to a 3D surface. The proposed level-set based optimization methods not only can act as a motivator for design synthesis, but also can be seamlessly hooked with additive manufacturing with no need of CAD reconstructions. The proposed computational framework provides a solution to increasing applications involving innovative metamaterial designs on free-form surfaces in different fields of interest. The performance of the proposed scheme is illustrated through a benchmark example where a negative-Poisson’s-ratio unit cell pattern is mapped to a 3D human face and fabricated through additive manufacturing.

scholarly journals An Open Source Framework for Integrated Additive Manufacturing and Level-Set-Based Topology Optimization

2017 ◽  
Vol 17 (4) ◽  
Author(s):  
Panagiotis Vogiatzis ◽  
Shikui Chen ◽  
Chi Zhou
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
3D Printing ◽  
Open Source ◽  
Level Set ◽  
Optimization Procedure ◽  
Computational Design ◽  
Standard Format ◽  
Practical Algorithms ◽  
Open Source Framework

Topology optimization has been considered as a promising tool for conceptual design due to its capability of generating innovative design candidates without depending on the designer's intuition and experience. Various optimization methods have been developed through the years, and one of the promising options is the level-set-based topology optimization method. The benefit of this alternative method is that the design is characterized by its clear boundaries. This advantage can avoid postprocessing work in conventional topology optimization process to a large extent and realize direct integration between topology optimization and additive manufacturing (AM). In this paper, practical algorithms and a matlab-based open source framework are developed to seamlessly integrate the level-set-based topology optimization procedure with AM process by converting the design to STereoLithography (STL) files, which is the de facto standard format for three-dimensional (3D) printing. The proposed algorithm and code are evaluated by a proof-of-concept demonstration with 3D printing of both single and multimaterial topology optimization results. The algorithm and the open source framework proposed in this paper will be beneficial to the areas of computational design and AM.

scholarly journals A Shape Optimization Method for Part Design Derived from the Buildability Restrictions of the Directed Energy Deposition Additive Manufacturing Process

Designs ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 19
Author(s):  
Andreas K. Lianos ◽  
Harry Bikas ◽  
Panagiotis Stavropoulos
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Energy Deposition ◽  
Design Method ◽  
Current Trend ◽  
Internal Stresses ◽  
Material Distribution ◽  
Load Case ◽  
Design Elements ◽  
Industrial Sectors

The design methodologies and part shape algorithms for additive manufacturing (AM) are rapidly growing fields, proven to be of critical importance for the uptake of additive manufacturing of parts with enhanced performance in all major industrial sectors. The current trend for part design is a computationally driven approach where the parts are algorithmically morphed to meet the functional requirements with optimized performance in terms of material distribution. However, the manufacturability restrictions of AM processes are not considered at the primary design phases but at a later post-morphed stage of the part’s design. This paper proposes an AM design method to ensure: (1) optimized material distribution based on the load case and (2) the part’s manufacturability. The buildability restrictions from the direct energy deposition (DED) AM technology were used as input to the AM shaping algorithm to grant high AM manufacturability. The first step of this work was to define the term of AM manufacturability, its effect on AM production, and to propose a framework to estimate the quantified value of AM manufacturability for the given part design. Moreover, an AM design method is proposed, based on the developed internal stresses of the build volume for the load case. Stress tensors are used for the determination of the build orientation and as input for the part morphing. A top-down mesoscale geometric optimization is used to realize the AM part design. The DED Design for Additive Manufacturing (DfAM) rules are used to delimitate the morphing of the part, representing at the same time the freeform mindset of the AM technology. The morphed shape of the part is optimized in terms of topology and AM manufacturability. The topology optimization and AM manufacturability indicator (TMI) is introduced to screen the percentage of design elements that serve topology optimization and the ones that serve AM manufacturability. In the end, a case study for proof of concept is realized.

scholarly journals Topology Optimization for additive manufacturing with distortion constraints

2021 ◽  
Vol 386 ◽  
pp. 114095
Author(s):  
Grzegorz Misiun ◽  
Emiel van de Ven ◽  
Matthijs Langelaar ◽  
Hubert Geijselaers ◽  
Fred van Keulen ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing
Sign in / Sign up

Export Citation Format

Share Document