Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/114220
Title: Modelling methodologies for Finite Element Analysis of material extrusion 3D printed scaffolds
Authors: Vega Rodríguez, Gisela Del Carmen 
Paz Hernández, Rubén 
Monzón Verona, Mario Domingo 
Gledall, Andy
UNESCO Clasification: 3312 Tecnología de materiales
3314 Tecnología médica
Keywords: Tissue engineering
Scaffold
Material extrusion additive manufacturing
3D geometry modelling
Finite element analysis, et al
Issue Date: 2021
Project: Biomaterials and Additive Manufacturing: Osteochondral Scaffold innovation applied to osteoarthritis 
Conference: BrainIT-Brain Revealed: Innovative Technologies in Neurosurgery Study
Abstract: The material extrusion additive manufacturing (AM) results in porous structures, which are desired in tissue engineering. Most scaffolds are 3D printed, but there are several methodologies to model these printed parts and to estimate their mechanical behaviour by finite element analysis (FEA). In this work, two different approaches are defined and compared in terms of computational efficiency, dimensional accuracy, and mechanical behaviour prediction of printed parts: geometry-based and voxel-based modelling techniques. Both methodologies are applied in a real scaffold, starting from the manufacturing G-code file, and FEA was applied to the resulting models. The results of the compression tests and dimensional measurements were compared with experimental and theoretical data. Moreover, the time and CPU requirements were also studied to determine which methodology is more suitable for each application. In terms of scaffolds manufacturing, the geometry-based modelling methodology is a more efficient process for simple parts, such as rectilinear patterned scaffolds, while the voxel-based one is more advantageous for complex geometries, such as gyroids. The whole process, modelling and simulation, is useful to optimise parts before printing.
URI: http://hdl.handle.net/10553/114220
Appears in Collections:Ponencias
Show full item record

Page view(s)

100
checked on Oct 12, 2024

Google ScholarTM

Check


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.