A Data Assimilation Methodology to Analyze the Unsaturated Seepage of an Earth–Rockfill Dam Using Physics-Informed Neural Networks Based on Hybrid Constraints

A Data Assimilation Methodology to Analyze the Unsaturated Seepage of an Earth–Rockfill Dam Using Physics-Informed Neural Networks Based on Hybrid Constraints

Data assimilation for unconfined seepage analysis has faced significant challenges due to hybrid causes, such as sparse measurements, heterogeneity of porous media, and computationally expensive forward models. To address these bottlenecks, this paper introduces a physics-informed neural network (PI...

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Bibliographic Details
Main Authors: Qianwei Dai, Wei Zhou, Run He, Junsheng Yang, Bin Zhang, Yi Lei
Format: Article
Language:English
Published: MDPI AG 2024-04-01
Series:Water
Subjects:
data assimilation
unsaturated seepage
physics-informed neural networks
deep learning
earth–rock dams
Online Access:https://www.mdpi.com/2073-4441/16/7/1041

Internet

https://www.mdpi.com/2073-4441/16/7/1041

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