Determination of tensile behavior of hot-pressed Mg–TiO2 and Mg–ZrO2 nanocomposites using indentation test and a holistic inverse modeling technique
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 h...
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doaj-bc2fb62da75d410fba3763dc339934582021-09-25T05:07:15ZengElsevierJournal of Materials Research and Technology2238-78542021-09-011421072114Determination of tensile behavior of hot-pressed Mg–TiO2 and Mg–ZrO2 nanocomposites using indentation test and a holistic inverse modeling techniqueKaveh Rahmani0Alireza Nouri1Greg Wheatley2Hossein Malekmohammadi3Hamed Bakhtiari4Vahid Yazdi5Department of Mechanical Engineering, Bu-Ali Sina University, Hamedan, Iran; Corresponding author.School of Engineering, RMIT University, Melbourne, VIC, Australia; Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), Tehran, IranCollege of Science & Engineering, James Cook University, James Cook Dr, Douglas, QLD 4811, AustraliaDepartment of Mechanical Engineering, Bu-Ali Sina University, Hamedan, IranDepartment of Mechanical Engineering, Bu-Ali Sina University, Hamedan, IranDepartment of Mechanical Engineering, Kar Higher Education Institute of Qazvin, Qazvin, IranThe 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.http://www.sciencedirect.com/science/article/pii/S2238785421007523Mg–ZrO2 nanocompositesMg–TiO2 nanocompositesTensile propertiesIndentationFinite elementNeural networks |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kaveh Rahmani Alireza Nouri Greg Wheatley Hossein Malekmohammadi Hamed Bakhtiari Vahid Yazdi |
spellingShingle |
Kaveh Rahmani Alireza Nouri Greg Wheatley Hossein Malekmohammadi Hamed Bakhtiari Vahid Yazdi 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 Mg–ZrO2 nanocomposites Mg–TiO2 nanocomposites Tensile properties Indentation Finite element Neural networks |
author_facet |
Kaveh Rahmani Alireza Nouri Greg Wheatley Hossein Malekmohammadi Hamed Bakhtiari Vahid Yazdi |
author_sort |
Kaveh Rahmani |
title |
Determination of tensile behavior of hot-pressed Mg–TiO2 and Mg–ZrO2 nanocomposites using indentation test and a holistic inverse modeling technique |
title_short |
Determination of tensile behavior of hot-pressed Mg–TiO2 and Mg–ZrO2 nanocomposites using indentation test and a holistic inverse modeling technique |
title_full |
Determination of tensile behavior of hot-pressed Mg–TiO2 and Mg–ZrO2 nanocomposites using indentation test and a holistic inverse modeling technique |
title_fullStr |
Determination of tensile behavior of hot-pressed Mg–TiO2 and Mg–ZrO2 nanocomposites using indentation test and a holistic inverse modeling technique |
title_full_unstemmed |
Determination of tensile behavior of hot-pressed Mg–TiO2 and Mg–ZrO2 nanocomposites using indentation test and a holistic inverse modeling technique |
title_sort |
determination of tensile behavior of hot-pressed mg–tio2 and mg–zro2 nanocomposites using indentation test and a holistic inverse modeling technique |
publisher |
Elsevier |
series |
Journal of Materials Research and Technology |
issn |
2238-7854 |
publishDate |
2021-09-01 |
description |
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. |
topic |
Mg–ZrO2 nanocomposites Mg–TiO2 nanocomposites Tensile properties Indentation Finite element Neural networks |
url |
http://www.sciencedirect.com/science/article/pii/S2238785421007523 |
work_keys_str_mv |
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