Non-destructive simulation of node defects in additively manufactured lattice structures

Lozanovski, Bill; Downing, David; Tino, Rance; du Plessis, Anton; Tran, Phuong; Jakeman, John; Shidid, Darpan; Emmelmann, Claus; Qian, Ma; Choong, Peter; Brandt, Milan; Leary, Martin

doi:10.1016/j.addma.2020.101593

Non-destructive simulation of node defects in additively manufactured lattice structures

Journal Article · Sat Sep 12 00:00:00 EDT 2020 · Additive Manufacturing

DOI:https://doi.org/10.1016/j.addma.2020.101593· OSTI ID:1667431

^[1]; Downing, David ^[1]; ^[2]; ^[3]; ^[4]; Jakeman, John ^[5]; ^[6]; Emmelmann, Claus ^[7]; Qian, Ma ^[6]; Choong, Peter ^[8]; ^[1]; Leary, Martin ^[1]

RMIT Univ., Melbourne (Australia). RMIT Centre for Additive Manufacture and ARC Training Centre in Additive Biomanufacturing
RMIT Univ., Melbourne (Australia). RMIT Centre for Additive Manufacture and ARC Training Centre in Additive Biomanufacturing; Peter MacCallum Cancer Centre, Melbourne (Australia)
Stellenbosch Univ. (South Africa). Research Group 3DInnovation; Nelson Mandela Univ., Port Elizabeth (South Africa). Dept. of Mechanical Engineering
RMIT Univ., Melbourne (Australia). Dept. of Civil & Infrastructure Engineering
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Center for Computing Research
RMIT Univ., Melbourne (Australia). RMIT Centre for Additive Manufacture
Fraunhofer Research Inst. for Additive Manufacturing Technologies IAPT, Hamburg (Germany)
RMIT Univ., Melbourne (Australia). ARC Training Centre in Additive Biomanufacturing; St. Vincent’s Hospital, Melbourne (Australia). Dept. of Surgery

Additive Manufacturing (AM), commonly referred to as 3D printing, offers the ability to not only fabricate geometrically complex lattice structures but parts in which lattice topologies in-fill volumes bounded by complex surface geometries. However, current AM processes produce defects on the strut and node elements which make up the lattice structure. This creates an inherent difference between the as-designed and as-fabricated geometries, which negatively affects predictions (via numerical simulation) of the lattice’s mechanical performance. Although experimental and numerical analysis of an AM lattice’s bulk structure, unit cell and struts have been performed, there exists almost no research data on the mechanical response of the individual as-manufactured lattice node elements. Here we propose a methodology that, for the first time, allows non-destructive quantification of the mechanical response of node elements within an as-manufactured lattice structure. A custom-developed tool is used to extract and classify each individual node geometry from micro-computed tomography scans of an AM fabricated lattice. Voxel-based finite element meshes are generated for numerical simulation and the mechanical response distribution is compared to that of the idealised computer-aided design model. The method demonstrates compatibility with Uncertainty Quantification methods that provide opportunities for efficient prediction of a population of nodal responses from sampled data. Overall, the non-destructive and automated nature of the node extraction and response evaluation is promising for its application in qualification and certification of additively manufactured lattice structures.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); Australian Research Council; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC04-94AL85000; NA0003525

OSTI ID:: 1667431

Report Number(s):: SAND--2020-9747J; 690617

Journal Information:: Additive Manufacturing, Journal Name: Additive Manufacturing Vol. 36; ISSN 2214-8604

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Non-destructive simulation of node defects in additively manufactured lattice structures

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