Determination of tensile behavior of hot-pressed Mg-TiO2 and Mg-ZrO2 nanocomposites using indentation test and a holistic inverse modeling technique

Rahmani, Kaveh, Nouri, Alireza, Wheatley, Greg, Malekmohammadi, Hossein, Bakhtiari, Hamed, and Yazdi, Vahid (2021) Determination of tensile behavior of hot-pressed Mg-TiO2 and Mg-ZrO2 nanocomposites using indentation test and a holistic inverse modeling technique. Journal of Materials Research and Technology, 14. pp. 2107-2114.

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Abstract

The present study aims to implement a non-destructive approach to determine the tensile properties of magnesium-based nanocomposites reinforced with ZrO2 and TiO2 nanoparticles. Micron-sized magnesium particles were blended with 0, 1.5, 3, and 5 volume percentage of ZrO2 and TiO2 nanoparticles and hot-pressed at 450 °C under the pressure of 600 MPa. Next, the spherical indentation test was performed on the produced composites to obtain the load–penetration curves. A finite element model of the indentation test was then developed using the Hollomon material model with randomly chosen materials constants. At the next stage, load–penetration curves were obtained for each composite using simulations. A Levenberg–Marquardt neural network was then trained and utilized to find the correct material constants by minimizing the differences between the experimental and simulated load–penetration curves. The results indicated that there is a linear relationship between the tensile strength and content of the reinforcement phase, while it is inversely proportional to the size of the reinforcing particles. Magnesium composites reinforced with 5 volume percentage of ZrO2 and TiO2 nanoparticles showed tensile strengths 2.5 and 2.1 times greater than that of unreinforced magnesium, respectively. It was shown that the proposed method is able to calculate the tensile properties of magnesium-based composites in an accurate and inexpensive manner.

Item ID: 68918
Item Type: Article (Research - C1)
ISSN: 2214-0697
Keywords: Mg-ZrO2 nanocomposites,Mg-TiO2 nanocomposites,Tensile properties,Indentation,Finite element,Neural networks
Copyright Information: © 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Date Deposited: 10 Aug 2021 02:52
FoR Codes: 40 ENGINEERING > 4001 Aerospace engineering > 400101 Aerospace materials @ 100%
SEO Codes: 24 MANUFACTURING > 2415 Transport equipment > 241501 Aerospace equipment @ 100%
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