Prediction of Deformation Response of Target Plate in Underwater Explosion Based on Deep Learning Neural Network
The deformation of a target plate in underwater explosion is manifested as a complex nonlinear coupling interaction between the structure and the fluid under the impact of shock waves. In this paper, a deep learning neural network is designed and optimized to predict the dynamic deformation displace...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Science Press (China)
2024-12-01
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| Series: | 水下无人系统学报 |
| Subjects: | |
| Online Access: | https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2024-0069 |
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| _version_ | 1841557016817958912 |
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| author | Zhiguo LI Feng MA Wei ZHU Xiyu JIA Yifan LI Lei CHEN |
| author_facet | Zhiguo LI Feng MA Wei ZHU Xiyu JIA Yifan LI Lei CHEN |
| author_sort | Zhiguo LI |
| collection | DOAJ |
| description | The deformation of a target plate in underwater explosion is manifested as a complex nonlinear coupling interaction between the structure and the fluid under the impact of shock waves. In this paper, a deep learning neural network is designed and optimized to predict the dynamic deformation displacement data of the target plate under different conditions of target plate thickness, shock factor, explosive dosage, and explosion distance. The coefficient of determination and accuracy of prediction on the test set reach 0.99 and 0.95, respectively. Compared with 25 simulation conditions, the explosion deformation response analysis graph formed by 9 261 working conditions based on the prediction model can cover a more detailed range of characteristic parameters and the trend of maximum deformation variation, providing important reference for underwater weapon design and underwater protection applications. |
| format | Article |
| id | doaj-art-61b31d397aeb4c1ab88c7a8161e0b9ab |
| institution | Kabale University |
| issn | 2096-3920 |
| language | zho |
| publishDate | 2024-12-01 |
| publisher | Science Press (China) |
| record_format | Article |
| series | 水下无人系统学报 |
| spelling | doaj-art-61b31d397aeb4c1ab88c7a8161e0b9ab2025-01-07T02:42:15ZzhoScience Press (China)水下无人系统学报2096-39202024-12-013261045105210.11993/j.issn.2096-3920.2024-00692024-0069Prediction of Deformation Response of Target Plate in Underwater Explosion Based on Deep Learning Neural NetworkZhiguo LI0Feng MA1Wei ZHU2Xiyu JIA3Yifan LI4Lei CHEN5State Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, ChinaThe deformation of a target plate in underwater explosion is manifested as a complex nonlinear coupling interaction between the structure and the fluid under the impact of shock waves. In this paper, a deep learning neural network is designed and optimized to predict the dynamic deformation displacement data of the target plate under different conditions of target plate thickness, shock factor, explosive dosage, and explosion distance. The coefficient of determination and accuracy of prediction on the test set reach 0.99 and 0.95, respectively. Compared with 25 simulation conditions, the explosion deformation response analysis graph formed by 9 261 working conditions based on the prediction model can cover a more detailed range of characteristic parameters and the trend of maximum deformation variation, providing important reference for underwater weapon design and underwater protection applications.https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2024-0069underwater explosiondeep learningneural networkdeformation responsetarget plate |
| spellingShingle | Zhiguo LI Feng MA Wei ZHU Xiyu JIA Yifan LI Lei CHEN Prediction of Deformation Response of Target Plate in Underwater Explosion Based on Deep Learning Neural Network 水下无人系统学报 underwater explosion deep learning neural network deformation response target plate |
| title | Prediction of Deformation Response of Target Plate in Underwater Explosion Based on Deep Learning Neural Network |
| title_full | Prediction of Deformation Response of Target Plate in Underwater Explosion Based on Deep Learning Neural Network |
| title_fullStr | Prediction of Deformation Response of Target Plate in Underwater Explosion Based on Deep Learning Neural Network |
| title_full_unstemmed | Prediction of Deformation Response of Target Plate in Underwater Explosion Based on Deep Learning Neural Network |
| title_short | Prediction of Deformation Response of Target Plate in Underwater Explosion Based on Deep Learning Neural Network |
| title_sort | prediction of deformation response of target plate in underwater explosion based on deep learning neural network |
| topic | underwater explosion deep learning neural network deformation response target plate |
| url | https://sxwrxtxb.xml-journal.net/cn/article/doi/10.11993/j.issn.2096-3920.2024-0069 |
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