Transfer learning for modeling pressure coefficient around cylinder using CNN
文献类型：会议论文
| 作者 | Ye SR(叶舒然); Wang YW(王一伟) ; Zhang Z(张珍); Huang CG(黄晨光)
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| 出版日期 | 2019 |
| 会议日期 | June 16, 2019 - June 21, 2019 |
| 会议地点 | Honolulu, HI, United states |
| 关键词 | Convolutional neural networks Flow field analysis Pressure prediction Transfer learning |
| 页码 | 966-969 |
| 英文摘要 | A data-driven method is developed in this article to predict the pressure coefficients from the velocity distribution in the wake flow. The convolutional layer processes velocity information in local region to output flow feature, which are gathered by the fully connected layer to obtain the pressure coefficients. When meeting different around body flow situation, a transfer learning method is adopted. Results show that this transfer learning method achieves nearly the same accuracy as the traditional one but with significantly lower time cost. The learning results have also demonstrated the active prospects of convolutional neural network in fluid mechanics. © 2019 by the International Society of Offshore and Polar Engineers (ISOPE). |
| 会议录 | Proceedings of the International Offshore and Polar Engineering Conference
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| 语种 | 英语 |
| ISBN号 | 9781880653852 |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/85104]  |
| 专题 | 力学研究所_流固耦合系统力学重点实验室(2012-) |
| 作者单位 | 1.School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China 2.Key Laboratory for Mechanics in Fluid Solid Coupling System, Institute of Mechanics, Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Ye SR,Wang YW,Zhang Z,et al. Transfer learning for modeling pressure coefficient around cylinder using CNN[C]. 见:. Honolulu, HI, United states. June 16, 2019 - June 21, 2019. |
入库方式： OAI收割
来源：力学研究所
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