An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural Network
Over the past few years, natural fiber composites have been a strategy of rapid growth. The computational methods have become a significant tool for many researchers to design and analyze the mechanical properties of these composites. The mechanical properties such as rigidity, effects, bending, and...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/5450935 |
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| author | Govindaraj Ramkumar Satyajeet Sahoo G. Anitha S. Ramesh P. Nirmala M. Tamilselvi Ram Subbiah S. Rajkumar |
| author_facet | Govindaraj Ramkumar Satyajeet Sahoo G. Anitha S. Ramesh P. Nirmala M. Tamilselvi Ram Subbiah S. Rajkumar |
| author_sort | Govindaraj Ramkumar |
| collection | DOAJ |
| description | Over the past few years, natural fiber composites have been a strategy of rapid growth. The computational methods have become a significant tool for many researchers to design and analyze the mechanical properties of these composites. The mechanical properties such as rigidity, effects, bending, and tensile testing are carried out on natural fiber composites. The natural fiber composites were modeled by using some of the computation techniques. The developed convolutional neural network (CNN) is used to accurately predict the mechanical properties of these composites. The ground-truth information is used for the training process attained from the finite element analyses below the plane stress statement. After completion of the training process, the developed design is authorized using the invisible data through the training. The optimum microstructural model is identified by a developed model embedded with a genetic algorithm (GA) optimizer. The optimizer converges to conformations with highly enhanced properties. The GA optimizer is used to improve the mechanical properties to have the soft elements in the area adjacent to the tip of the crack. |
| format | Article |
| id | doaj-art-f5e0de790460468288cfa60285ac1624 |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-f5e0de790460468288cfa60285ac16242025-02-03T07:23:58ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422021-01-01202110.1155/2021/54509355450935An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural NetworkGovindaraj Ramkumar0Satyajeet Sahoo1G. Anitha2S. Ramesh3P. Nirmala4M. Tamilselvi5Ram Subbiah6S. Rajkumar7Department of Electronics and Communication Engineering, Saveetha School of Engineering,SIMATS, Chennai 602105, Tamil Nadu, IndiaDepartment of Electronics and Communication Engineering,Vignan’s Foundation for Science, Technology and Research (Deemed to be University), Vadlamudi, Guntur, Andhra Pradesh 522213, IndiaDepartment of Electronics and Communication Engineering, Saveetha School of Engineering,SIMATS, Chennai 602105, Tamil Nadu, IndiaDepartment of Electronics and Communication Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore-641062, Tamil Nadu, IndiaDepartment of Electronics and Communication Engineering, Saveetha School of Engineering,SIMATS, Chennai 602105, Tamil Nadu, IndiaDepartment of Mechatronics Engineering, T.S. Srinivasan Centre For Polytechnic College and Advanced Training, Chennai, Tamil Nadu, IndiaDepartment of Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Nizampet, Hyderabad, IndiaDepartment of Mechanical Engineering, Faculty of Manufacturing, Institute of Technology, Hawassa University, Awasa, EthiopiaOver the past few years, natural fiber composites have been a strategy of rapid growth. The computational methods have become a significant tool for many researchers to design and analyze the mechanical properties of these composites. The mechanical properties such as rigidity, effects, bending, and tensile testing are carried out on natural fiber composites. The natural fiber composites were modeled by using some of the computation techniques. The developed convolutional neural network (CNN) is used to accurately predict the mechanical properties of these composites. The ground-truth information is used for the training process attained from the finite element analyses below the plane stress statement. After completion of the training process, the developed design is authorized using the invisible data through the training. The optimum microstructural model is identified by a developed model embedded with a genetic algorithm (GA) optimizer. The optimizer converges to conformations with highly enhanced properties. The GA optimizer is used to improve the mechanical properties to have the soft elements in the area adjacent to the tip of the crack.http://dx.doi.org/10.1155/2021/5450935 |
| spellingShingle | Govindaraj Ramkumar Satyajeet Sahoo G. Anitha S. Ramesh P. Nirmala M. Tamilselvi Ram Subbiah S. Rajkumar An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural Network Advances in Materials Science and Engineering |
| title | An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural Network |
| title_full | An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural Network |
| title_fullStr | An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural Network |
| title_full_unstemmed | An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural Network |
| title_short | An Unconventional Approach for Analyzing the Mechanical Properties of Natural Fiber Composite Using Convolutional Neural Network |
| title_sort | unconventional approach for analyzing the mechanical properties of natural fiber composite using convolutional neural network |
| url | http://dx.doi.org/10.1155/2021/5450935 |
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