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Title: Size-dependence of AM Ti–6Al–4V: Experimental characterization and applications in thin-walled structures simulations
Previous studies show that the properties of parts manufactured via additive manufacturing, such as selective laser melting, depend on local feature sizes like lattice wall thickness and strut diameter. Although size dependence has been studied extensively, it was not included in constitutive models for numerical simulations. In this work, flat dog-bone tensile specimens of different thicknesses were manufactured and tested under quasi-static conditions to characterize the size-dependent properties experimentally. It was observed that key mechanical properties decrease with specimen thickness. Through curve-fitting to experimental data, this work provides approximate analytical expressions for the material properties values as a function of specimen thickness, furnishing a phenomenological size-dependent constitutive model. The interpolating capability of the model is cross-validated with existing experimental data. Two numerical examples demonstrate the application of the size-dependent material model. The axial crushing of thin-walled lattices at varying wall thicknesses was simulated by the size-dependent material model and one that ignores size effects. Results show that ignoring size effects leads to overestimated peak crushing force and specific energy absorption. The two material models were also compared in the topology optimization of thin-walled structures. Results show that the size-dependent model leads to a more robust optimized design: having higher energy absorption and sustaining less material fracture.  more » « less
Award ID(s):
1926353
PAR ID:
10537698
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
Elsevier
Date Published:
Journal Name:
Thin-Walled Structures
Volume:
187
Issue:
C
ISSN:
0263-8231
Page Range / eLocation ID:
110722
Subject(s) / Keyword(s):
Size effects Selective laser melting Ti–6Al–4V Specific energy absorption Thin-walled lattice structures Topology optimization
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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