Quantitative relations between curing processes and local properties within thick composites based on simulation and machine learning
Overheating is almost inevitable during the curing of thick polymer matrix composite parts, which always induces degradation of the mechanical properties. To explore the relationship between the local process variables and the property distribution of interlaminar shear strengths and compression str...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-02-01
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| Series: | Materials & Design |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0264127523001016 |
| _version_ | 1811158437550096384 |
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| author | Yubo Zhou Min Li Qiao Cheng Shaokai Wang Yizhuo Gu Xiangbao Chen |
| author_facet | Yubo Zhou Min Li Qiao Cheng Shaokai Wang Yizhuo Gu Xiangbao Chen |
| author_sort | Yubo Zhou |
| collection | DOAJ |
| description | Overheating is almost inevitable during the curing of thick polymer matrix composite parts, which always induces degradation of the mechanical properties. To explore the relationship between the local process variables and the property distribution of interlaminar shear strengths and compression strengths inside thick composites, experiments and relative simulations were conducted herein. Based on machine learning techniques, a convolutional autoencoder (CAE) was used to evaluate the spatial distributions of temperature, cure degree, and stress during autoclave curing process of thick composites. The results demonstrate a strong linear relationship between the spatial distribution of stress with the property values of interlaminar shear strengths and compressive strengths. This indicates that the stress distribution history strongly impacts the mechanical properties of thick laminates, which is usually neglected in previous studies that only concerns the stress magnitude. |
| first_indexed | 2024-04-10T05:24:41Z |
| format | Article |
| id | doaj.art-584552c6de8c4b61b10bc8245723a4b8 |
| institution | Directory Open Access Journal |
| issn | 0264-1275 |
| language | English |
| last_indexed | 2024-04-10T05:24:41Z |
| publishDate | 2023-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Materials & Design |
| spelling | doaj.art-584552c6de8c4b61b10bc8245723a4b82023-03-08T04:13:52ZengElsevierMaterials & Design0264-12752023-02-01226111686Quantitative relations between curing processes and local properties within thick composites based on simulation and machine learningYubo Zhou0Min Li1Qiao Cheng2Shaokai Wang3Yizhuo Gu4Xiangbao Chen5School of Materials Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, ChinaSchool of Materials Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China; Ningbo Institute of Technology, Beihang University, Beilun District, Ningbo 315800, China; Corresponding author at: School of Materials Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China.School of Materials Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, ChinaSchool of Materials Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China; Ningbo Institute of Technology, Beihang University, Beilun District, Ningbo 315800, ChinaResearch Institute of Frontier Science, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, ChinaBejing Institute of Aeronautical Materials, Aero Engine Corporation of China, No.8, Hangcai Avenue, Haidian District, Beijing 100095, ChinaOverheating is almost inevitable during the curing of thick polymer matrix composite parts, which always induces degradation of the mechanical properties. To explore the relationship between the local process variables and the property distribution of interlaminar shear strengths and compression strengths inside thick composites, experiments and relative simulations were conducted herein. Based on machine learning techniques, a convolutional autoencoder (CAE) was used to evaluate the spatial distributions of temperature, cure degree, and stress during autoclave curing process of thick composites. The results demonstrate a strong linear relationship between the spatial distribution of stress with the property values of interlaminar shear strengths and compressive strengths. This indicates that the stress distribution history strongly impacts the mechanical properties of thick laminates, which is usually neglected in previous studies that only concerns the stress magnitude.http://www.sciencedirect.com/science/article/pii/S0264127523001016Machine learningAutoclave process simulationThick compositesMechanical propertiesStress distribution |
| spellingShingle | Yubo Zhou Min Li Qiao Cheng Shaokai Wang Yizhuo Gu Xiangbao Chen Quantitative relations between curing processes and local properties within thick composites based on simulation and machine learning Materials & Design Machine learning Autoclave process simulation Thick composites Mechanical properties Stress distribution |
| title | Quantitative relations between curing processes and local properties within thick composites based on simulation and machine learning |
| title_full | Quantitative relations between curing processes and local properties within thick composites based on simulation and machine learning |
| title_fullStr | Quantitative relations between curing processes and local properties within thick composites based on simulation and machine learning |
| title_full_unstemmed | Quantitative relations between curing processes and local properties within thick composites based on simulation and machine learning |
| title_short | Quantitative relations between curing processes and local properties within thick composites based on simulation and machine learning |
| title_sort | quantitative relations between curing processes and local properties within thick composites based on simulation and machine learning |
| topic | Machine learning Autoclave process simulation Thick composites Mechanical properties Stress distribution |
| url | http://www.sciencedirect.com/science/article/pii/S0264127523001016 |
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