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Multi-Material Composition Optimization vs Software-Based Single-Material Topology Optimization of a Rectangular Sample under Flexural Load for Fused Deposition Modeling Process

Hassani, Vahid, Ahmad Mehrabi, Hamid, Gregg, Carl, O'Brien, Roger William, Ituarte, Inigo Flores and Tjahjowidodo, Tegoeh (2021) Multi-Material Composition Optimization vs Software-Based Single-Material Topology Optimization of a Rectangular Sample under Flexural Load for Fused Deposition Modeling Process. Materials Science Forum, 1042. pp. 23-44. ISSN 1662-9752

Item Type: Article

Abstract

Additive manufacturing (AM) technologies have been evolved over the last decade, enabling engineers and researchers to improve functionalities of parts by introducing a growing technology known as multi-material AM. In this context, fused deposition modeling (FDM) process has been modified to create multi-material 3D printed objects with higher functionality. The new technology enables it to combine several types of polymers with hard and soft constituents to make a 3D printed part with improved mechanical properties and functionalities. Knowing this capability, this paper aims to present a parametric optimization method using a genetic algorithm (GA) to find the optimum composition of hard polymer as polylactic acid (PLA) and soft polymer as thermoplastic polyurethane (TPU 95A) used in Ultimaker 3D printer for making a rectangular sample under flexural load in order to minimize the von Mises stress as an objective function. These samples are initially presented in four deferent forms in terms of composition of hard and soft polymers and then, after the optimization process, the final ratio of each type of material will be achieved. Based on the volume fraction of soft polymers in each sample, the equivalent topologically-optimized samples will be obtained that are solely made of single-material PLA as hard polymer under the same flexural load as applied to multi-material samples. Finally, the structural results and manufacturability in terms of the generated support structures, as key element of some AM processes, will be compared for the resultant samples created by two methods of optimization.

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More Information

Additional Information: ** Article version: VoR ** From Crossref journal articles via Jisc Publications Router ** History: epub 10-08-2021; issued 10-08-2021. ** Licence for VoR version of this article starting on 10-08-2021: https://www.scientific.net/PolicyAndEthics/PublishingPolicies
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Identifiers

Item ID: 13863
Identification Number: https://doi.org/10.4028/www.scientific.net/msf.1042.23
ISSN: 1662-9752
URI: http://sure.sunderland.ac.uk/id/eprint/13863
Official URL: https://www.scientific.net/MSF.1042.23

Users with ORCIDS

ORCID for Vahid Hassani: ORCID iD orcid.org/0000-0001-6724-2520
ORCID for Hamid Ahmad Mehrabi: ORCID iD orcid.org/0000-0003-0510-4055
ORCID for Carl Gregg: ORCID iD orcid.org/0000-0002-6033-4104

Catalogue record

Date Deposited: 13 Sep 2021 15:33
Last Modified: 24 Apr 2024 12:17

Contributors

Author: Vahid Hassani ORCID iD
Author: Hamid Ahmad Mehrabi ORCID iD
Author: Carl Gregg ORCID iD
Author: Roger William O'Brien
Author: Inigo Flores Ituarte
Author: Tegoeh Tjahjowidodo

University Divisions

Faculty of Health Sciences and Wellbeing > School of Nursing and Health Sciences

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