Uncertainty Quantification of Vibroacoustics with Deep Neural Networks and Catmull–Clark Subdivision Surfaces
This study proposes an uncertainty quantification method based on deep neural networks and Catmull–Clark subdivision surfaces for vibroacoustic problems. The deep neural networks are utilized as a surrogate model to efficiently generate samples for stochastic analysis. The training data are obtained...
Main Authors: | Zhongbin Zhou, Yunfei Gao, Yu Cheng, Yujing Ma, Xin Wen, Pengfei Sun, Peng Yu, Zhongming Hu |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2024-01-01
|
Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2024/7926619 |
Similar Items
-
Subdivision Shading for Catmull-Clark and Loop Subdivision Surfaces with Semi-Sharp Creases
by: Jun Zhou, et al.
Published: (2023-04-01) -
HSS-progressive interpolation for Loop and Catmull–Clark Subdivision Surfaces
by: Yusuf Fatihu Hamza, et al.
Published: (2024-03-01) -
Cloth simulation using an enhanced Catmull-Clark subdivision scheme and collision detection in a virtual environment
by: Tulasii Sivaraja, et al.
Published: (2019) -
Subdivisi permukaan menggunakan teknik Catmull-Clark /
by: 514957 Mohd. Fadzil Hilmi Abdul Rahman, et al.
Published: (2010) -
Subdivisi permukaan menggunakan teknik Catmull-Clark [electronic resource] /
by: 514957 Mohd. Fadzil Hilmi Abdul Rahman
Published: (2010)