TY - JOUR
T1 - Characterization of Anisotropy in Additively Manufactured Materials through Instrumented Indentation Testing
AU - Cai, Zhuoshao
AU - Yang, Zhiwei
AU - Meng, Liang
AU - Lin, Kaijie
AU - Hou, Yuliang
AU - Sapanathan, Thaneshan
AU - Zhu, Jihong
AU - Zhang, Weihong
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - The accurate characterization of anisotropy for additively manufactured materials is of vital importance for both high-performance structural design and printing processing optimization. To avoid the repetitive and redundant tensile testing on specimens prepared along diverse directions, this study proposes an instrumented indentation-based inverse identification method for the efficient characterization of additively manufactured materials. In the present work, a 3D finite element model of indentation test is first established for the printed material, for which an anisotropic material constitutive model is incorporated. We have demonstrated that the indentation responses are information-rich, and material anisotropy along different directions can be interpreted by a single indentation imprint. Subsequently, an inverse identification framework is built, in which an Euclidean error norm between simulated and experimental indentation responses is minimized via optimization algorithms such as the Globally Convergent Method of Moving Asymptotes (GCMMA). The developed method has been verified on diverse printed materials referring to either the indentation curve or the residual imprint, and the superiority of this latter over the former is confirmed by a better and faster convergence of inverse identification. Experimental validations on 3D printed materials (including stainless steel 316L, aluminum alloy AlSi10Mg, and titanium alloy TC4) reveal that the developed method is both accurate and reliable when compared with material constitutive behaviors obtained from uni-axial tensile tests, regardless of the degree of anisotropy among different materials.
AB - The accurate characterization of anisotropy for additively manufactured materials is of vital importance for both high-performance structural design and printing processing optimization. To avoid the repetitive and redundant tensile testing on specimens prepared along diverse directions, this study proposes an instrumented indentation-based inverse identification method for the efficient characterization of additively manufactured materials. In the present work, a 3D finite element model of indentation test is first established for the printed material, for which an anisotropic material constitutive model is incorporated. We have demonstrated that the indentation responses are information-rich, and material anisotropy along different directions can be interpreted by a single indentation imprint. Subsequently, an inverse identification framework is built, in which an Euclidean error norm between simulated and experimental indentation responses is minimized via optimization algorithms such as the Globally Convergent Method of Moving Asymptotes (GCMMA). The developed method has been verified on diverse printed materials referring to either the indentation curve or the residual imprint, and the superiority of this latter over the former is confirmed by a better and faster convergence of inverse identification. Experimental validations on 3D printed materials (including stainless steel 316L, aluminum alloy AlSi10Mg, and titanium alloy TC4) reveal that the developed method is both accurate and reliable when compared with material constitutive behaviors obtained from uni-axial tensile tests, regardless of the degree of anisotropy among different materials.
KW - Additive manufacturing
KW - Anisotropy property
KW - Indentation test
KW - Inverse identification
UR - http://www.scopus.com/inward/record.url?scp=85218420221&partnerID=8YFLogxK
U2 - 10.1186/s10033-024-01174-7
DO - 10.1186/s10033-024-01174-7
M3 - 文章
AN - SCOPUS:85218420221
SN - 1000-9345
VL - 38
JO - Chinese Journal of Mechanical Engineering (English Edition)
JF - Chinese Journal of Mechanical Engineering (English Edition)
IS - 1
M1 - 13
ER -