Different analytical and numerical models are often used to predict the elastic properties of composite materials. However, accurate predictions and quick elasticity of composite materials in micro-scale is still more of challenging. In this study, the application of different analytical models such as: Rule of Mixture, Halphin-Tsai, Chamis are presented to predict the mechanical properties of composite materials. Then, finite element analysis (FEA) is used to verify the results obtained through Square RVE and hexagonal RVE models. This study focuses on evaluating the elastic properties of composite materials with the polymer background reinforced by the fiber distributed cyclically in a certain direction at a different volume fraction of fiber. We proceed to predict the mechanical properties of materials with a volume fraction of fiber from 10% to 70% using a microscale approach. In addition, this combination also provides a convenient platform for optimizing material design and composite geometry with different algorithms to solve a variety of problems in predicting the complex mechanical properties of composite materials. Finally, a computational software was developed to quick predict and efficient the mechanical properties of this complex materials. Compared with other studies, this study shows the possibility of high application in order to predict more accurate for composite complex materials.
Published in | Science Development (Volume 2, Issue 4) |
DOI | 10.11648/j.scidev.20210204.11 |
Page(s) | 62-70 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2021. Published by Science Publishing Group |
RVE, Composite Structure, Micro-scale RVE, Predict Mechanical Properties
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APA Style
Nguyen Duc Hai, Nguyen Ngoc Dam, Vu Hoa Ky. (2021). A New Develop Model for Predict Micro Mechanical Properties of Composite Materials. Science Development, 2(4), 62-70. https://doi.org/10.11648/j.scidev.20210204.11
ACS Style
Nguyen Duc Hai; Nguyen Ngoc Dam; Vu Hoa Ky. A New Develop Model for Predict Micro Mechanical Properties of Composite Materials. Sci. Dev. 2021, 2(4), 62-70. doi: 10.11648/j.scidev.20210204.11
@article{10.11648/j.scidev.20210204.11, author = {Nguyen Duc Hai and Nguyen Ngoc Dam and Vu Hoa Ky}, title = {A New Develop Model for Predict Micro Mechanical Properties of Composite Materials}, journal = {Science Development}, volume = {2}, number = {4}, pages = {62-70}, doi = {10.11648/j.scidev.20210204.11}, url = {https://doi.org/10.11648/j.scidev.20210204.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.scidev.20210204.11}, abstract = {Different analytical and numerical models are often used to predict the elastic properties of composite materials. However, accurate predictions and quick elasticity of composite materials in micro-scale is still more of challenging. In this study, the application of different analytical models such as: Rule of Mixture, Halphin-Tsai, Chamis are presented to predict the mechanical properties of composite materials. Then, finite element analysis (FEA) is used to verify the results obtained through Square RVE and hexagonal RVE models. This study focuses on evaluating the elastic properties of composite materials with the polymer background reinforced by the fiber distributed cyclically in a certain direction at a different volume fraction of fiber. We proceed to predict the mechanical properties of materials with a volume fraction of fiber from 10% to 70% using a microscale approach. In addition, this combination also provides a convenient platform for optimizing material design and composite geometry with different algorithms to solve a variety of problems in predicting the complex mechanical properties of composite materials. Finally, a computational software was developed to quick predict and efficient the mechanical properties of this complex materials. Compared with other studies, this study shows the possibility of high application in order to predict more accurate for composite complex materials.}, year = {2021} }
TY - JOUR T1 - A New Develop Model for Predict Micro Mechanical Properties of Composite Materials AU - Nguyen Duc Hai AU - Nguyen Ngoc Dam AU - Vu Hoa Ky Y1 - 2021/11/23 PY - 2021 N1 - https://doi.org/10.11648/j.scidev.20210204.11 DO - 10.11648/j.scidev.20210204.11 T2 - Science Development JF - Science Development JO - Science Development SP - 62 EP - 70 PB - Science Publishing Group SN - 2994-7154 UR - https://doi.org/10.11648/j.scidev.20210204.11 AB - Different analytical and numerical models are often used to predict the elastic properties of composite materials. However, accurate predictions and quick elasticity of composite materials in micro-scale is still more of challenging. In this study, the application of different analytical models such as: Rule of Mixture, Halphin-Tsai, Chamis are presented to predict the mechanical properties of composite materials. Then, finite element analysis (FEA) is used to verify the results obtained through Square RVE and hexagonal RVE models. This study focuses on evaluating the elastic properties of composite materials with the polymer background reinforced by the fiber distributed cyclically in a certain direction at a different volume fraction of fiber. We proceed to predict the mechanical properties of materials with a volume fraction of fiber from 10% to 70% using a microscale approach. In addition, this combination also provides a convenient platform for optimizing material design and composite geometry with different algorithms to solve a variety of problems in predicting the complex mechanical properties of composite materials. Finally, a computational software was developed to quick predict and efficient the mechanical properties of this complex materials. Compared with other studies, this study shows the possibility of high application in order to predict more accurate for composite complex materials. VL - 2 IS - 4 ER -