Ajit Panesar
Design framework for multifunctional additive manufacturing: coupled optimization strategy for structures with embedded functional systems
Panesar, Ajit; Ashcroft, Ian; Brackett, David; Wildman, Ricky D.; Hague, Richard
Authors
Professor Ian Ashcroft IAN.ASHCROFT@NOTTINGHAM.AC.UK
PROFESSOR OF MECHANICS OF SOLIDS
David Brackett
Ricky D. Wildman
Professor RICHARD HAGUE RICHARD.HAGUE@NOTTINGHAM.AC.UK
Professor of Additive Manufacturing
Abstract
The driver for this research is the development of multi-material additive manufacturing processes that provide the potential for multi-functional parts to be manufactured in a single operation. In order to exploit the potential benefits of this emergent technology, new design, analysis and optimization methods are needed. This paper presents a method that enables in the optimization of a multifunctional part by coupling both the system and structural design aspects. This is achieved by incorporating the effects of a system, comprised of a number of connected functional components, on the structural response of a part within a structural topology optimization procedure. The potential of the proposed method is demonstrated by performing a coupled optimization on a cantilever plate with integrated components and circuitry. The results demonstrate that the method is capable of designing an optimized multifunctional part in which both the structural and system requirements are considered.
Citation
Panesar, A., Ashcroft, I., Brackett, D., Wildman, R. D., & Hague, R. (2017). Design framework for multifunctional additive manufacturing: coupled optimization strategy for structures with embedded functional systems. Additive Manufacturing, 16, https://doi.org/10.1016/j.addma.2017.05.009
Journal Article Type | Article |
---|---|
Acceptance Date | May 21, 2017 |
Online Publication Date | May 23, 2017 |
Publication Date | Aug 1, 2017 |
Deposit Date | Jun 15, 2017 |
Publicly Available Date | Jun 15, 2017 |
Journal | Additive Manufacturing |
Print ISSN | 2214-7810 |
Electronic ISSN | 2214-8604 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 16 |
DOI | https://doi.org/10.1016/j.addma.2017.05.009 |
Keywords | Optimization; Additive manufacturing; Multi-functional; Computational methods |
Public URL | https://nottingham-repository.worktribe.com/output/967599 |
Publisher URL | http://www.sciencedirect.com/science/article/pii/S2214860416302998 |
Contract Date | Jun 15, 2017 |
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0
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