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Application of physics-informed neural network in the analysis of hydrodynamic lubrication

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Bibliographic Details
Main Authors: Yang, Zhao, Liang, Guo, Patrick Pat Lam, Wong
Format: Book
Language:English
Published: Springer 2023
Subjects:
PINN
2D Reynolds equation
Online Access:https://link.springer.com/article/10.1007/s40544-022-0658-x
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7933
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spelling oai:localhost:PNK-79332023-04-14T03:55:54Z Application of physics-informed neural network in the analysis of hydrodynamic lubrication Yang, Zhao Liang, Guo Patrick Pat Lam, Wong PINN 2D Reynolds equation CC BY The last decade has witnessed a surge of interest in artificial neural network in many different areas of scientific research. Despite the rapid expansion in the application of neural networks, few efforts have been carried out to introduce such a powerful tool into lubrication studies. Thus, this work aims to apply the physics-informed neural network (PINN) to the hydrodynamic lubrication analysis. The 2D Reynolds equation is solved. The PINN is a meshless method and does not require big data for network training compared with classical methods. Our results are consistent with those obtained by experiments and the finite element method. Hence, we envision that the PINN method will have great application potential in lubrication and bearing research. 2023-04-14T03:55:53Z 2023-04-14T03:55:53Z 2022 Book https://link.springer.com/article/10.1007/s40544-022-0658-x https://dlib.phenikaa-uni.edu.vn/handle/PNK/7933 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic PINN
2D Reynolds equation
spellingShingle PINN
2D Reynolds equation
Yang, Zhao
Liang, Guo
Patrick Pat Lam, Wong
Application of physics-informed neural network in the analysis of hydrodynamic lubrication
description CC BY
format Book
author Yang, Zhao
Liang, Guo
Patrick Pat Lam, Wong
author_facet Yang, Zhao
Liang, Guo
Patrick Pat Lam, Wong
author_sort Yang, Zhao
title Application of physics-informed neural network in the analysis of hydrodynamic lubrication
title_short Application of physics-informed neural network in the analysis of hydrodynamic lubrication
title_full Application of physics-informed neural network in the analysis of hydrodynamic lubrication
title_fullStr Application of physics-informed neural network in the analysis of hydrodynamic lubrication
title_full_unstemmed Application of physics-informed neural network in the analysis of hydrodynamic lubrication
title_sort application of physics-informed neural network in the analysis of hydrodynamic lubrication
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s40544-022-0658-x
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7933
_version_ 1763180886127280128
score 8.891053

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