Paper Info
Title
Material characterization and precise finite element analysis of fiber reinforced thermoplastic composites for 4D printing
Abstract
Four-dimensional (4D) printing, a new technology emerged from additive manufacturing (3D printing), is widely known for its capability of programming post-fabrication shape-changing into artifacts. Fused deposition modeling (FDM)-based 4D printing, in particular, uses thermoplastics to produce artifacts and requires computational analysis to assist the design processes of complex geometries. However, these artifacts are weak against structural loads, and the design quality can be limited by less accurate material models and numerical simulations. To address these issues, this paper propounds a composite structure design made of two materials – polylactic acid (PLA) and carbon fiber reinforced PLA (CFPLA) – to increase the structural strength of 4D printed artifacts and a workflow composed of several physical experiments and series of dynamic mechanical analysis (DMA) to characterize materials. We apply this workflow to 3D printed samples fabricated with different printed parameters to accurately characterize the materials and implement a sequential finite element analysis (FEA) to achieve accurate simulations. The accuracy of deformation induced by the triggering process is both computationally and experimentally verified with several creative design examples and is measured to be at least 95%, with a confidence interval of (0.972,0.985). We believe the presented workflow is essential to the combination of geometry, material mechanism and design, and has various potential applications.
Year
DOI
Venue
2020
10.1016/j.cad.2020.102817
Computer-Aided Design
Keywords
Field
DocType
4D printing,Design workflow,Material characterization,Fiber reinforcement,Finite element analysis
Size effect on structural strength,Dynamic mechanical analysis,Mathematical optimization,Mechanical engineering,Composite number,Finite element method,3D printing,Fused deposition modeling,Structural load,Workflow,Mathematics
Journal
Volume
ISSN
Citations 
122
0010-4485
0
PageRank 
References 
Authors
0.34
0
9
Name
Order
Citations
PageRank
Yuxuan Yu100.34
Haolin Liu2267.19
Kuanren Qian300.68
Humphrey Yang494.96
Matthew McGehee500.34
Jianzhe Gu6105.65
Danli Luo702.37
Lining Yao825131.54
Yongjie Zhang929334.45