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Prediction of anisotropic mechanical properties for lattice structures
File(s)
Author(s)
Munford, Max
Hossain, Umar
Ghouse, Shaaz
Jeffers, Jonathan
Type
Journal Article
Abstract
Additive manufacturing methods present opportunities for structures to have tailored mechanical anisotropy by integrating controlled lattice structures into their design. The ability to predict anisotropic mechanical properties of such lattice structures would help tailor anisotropy and ensure adequate off-axis strength at an early stage in the design process. A method is described for the development of a model to predict apparent modulus and strength based on structure density and fabric, taken from CAD data. The model utilises a tensorial form of well-founded power-law relationships for these variables and is fit to mechanical test data for properties in the principal directions of manufactured titanium stochastic lattices and nylon rhombic dodecahedron structures. The results are validated against mechanical testing across at least 7 additional off-axis directions. For stochastic structures, apparent modulus is predicted in 10 directions with a mean error of 13% and strength predicted with a mean error of 10%. For rhombic dodecahedron structures apparent modulus and strength are predicted in 15 directions with mean errors of 4.2% and 5.1% respectively. This model is the first to predict the anisotropic apparent modulus and strength of structures based on lattice density and fabric tensors and will be highly useful in the mechanical design of lattice structures.
Date Issued
2020-03-01
Date Acceptance
2020-01-04
Citation
Additive Manufacturing, 2020, 32
URI
DOI
ISSN
2214-8604
Publisher
Elsevier
Journal / Book Title
Additive Manufacturing
Volume
32
Copyright Statement
© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/).
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Wellcome Trust
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/K027549/1
208858/Z/17/Z
EP/R042721/1
Subjects
0910 Manufacturing Engineering
Publication Status
Published
Article Number
ARTN 101041
Date Publish Online
2020-01-23