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Xiaonan Hou

Lancaster University

Lancaster LA1 4YX

United Kingdom

SCHOLARLY PAPERS

7

DOWNLOADS

387

TOTAL CITATIONS

3

Scholarly Papers (7)

Element-Wise Multiplication Based Deeper Physics-Informed Neural Networks

Number of pages: 13 Posted: 23 Oct 2024
Feilong Jiang, Xiaonan Hou, Jianqiao Ye and Min Xia
Lancaster University, Lancaster University, Lancaster University and Western University
Downloads 73 (863,736)

Abstract:

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Physics-informed neural network, AI for Science, Numerical methods for PDE

Element-Wise Multiplication Based Deeper Physics-Informed Neural Networks

Number of pages: 14 Posted: 20 Dec 2024
Feilong Jiang, Xiaonan Hou, Jianqiao Ye and Min Xia
Lancaster University, Lancaster University, Lancaster University and Western University
Downloads 53 (1,049,673)

Abstract:

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Physics-Informed Neural Networks, deep learning, Partial differential equations

Stress Field Prediction of Unidirectional Fibre-Reinforced Polymer Composites Using Convolutional Neural Network (Cnn) Trained on Physically Meaningful Data

Number of pages: 32 Posted: 31 May 2025
Siyu Zhao, Xiaoxuan Ding, Jianqiao Ye and Xiaonan Hou
Lancaster University, affiliation not provided to SSRN, Lancaster University and Lancaster University
Downloads 41 (1,196,631)

Abstract:

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Machine learning, Discrete Element method (DEM), Composite laminates, Stress field, physically meaningful data.

Stress Field Prediction of Unidirectional Fibre-Reinforced Polymer Composites Using Convolutional Neural Network (Cnn) Trained on Physically Meaningful Data

Number of pages: 32 Posted: 28 May 2025
Siyu Zhao, Xiaoxuan Ding, Jianqiao Ye and Xiaonan Hou
Lancaster University, affiliation not provided to SSRN, Lancaster University and Lancaster University
Downloads 18 (1,525,626)

Abstract:

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Machine learning, Discrete Element method (DEM), Composite laminates, Stress field, physically meaningful data.

Stress Field Prediction of Unidirectional Fibre-Reinforced Polymer Composites Using Convolutional Neural Network (Cnn) Trained on Physically Meaningful Data

Number of pages: 32 Posted: 28 May 2025
Siyu Zhao, Xiaoxuan Ding, Jianqiao Ye and Xiaonan Hou
Lancaster University, affiliation not provided to SSRN, Lancaster University and Lancaster University
Downloads 8 (1,621,812)

Abstract:

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Machine learning, Discrete Element method (DEM), Composite laminates, Stress field, physically meaningful data.

3.

Deeper-Pinns: Unlocking the Power of Deep Physics-Informed Neural Networks

Number of pages: 14 Posted: 27 May 2025
Feilong Jiang, Min Xia, Xiaonan Hou and Jianqiao Ye
Lancaster University, Western University, Lancaster University and Lancaster University
Downloads 58 (980,173)

Abstract:

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Physics-Informed Neural Networks, Deep learning, Partial differential equations

4.

Mask-PINNs: Mitigating Internal Covariate Shift in Physics-Informed Neural Networks

Number of pages: 18 Posted: 22 Oct 2025
Feilong Jiang, Xiaonan Hou, Jianqiao Ye and Min Xia
Lancaster University, Lancaster University, Lancaster University and Western University
Downloads 43 (1,157,785)

Abstract:

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Deep learning, Physics-informed neural networks, Partial differential equations, Scientific machine learning

5.

Effect of Microstructural Roughness on the Performance and Fracture Mechanism of Multi-Type Single Lap Joints

Number of pages: 44 Posted: 22 May 2024
Lancaster University, affiliation not provided to SSRN, Lancaster University, University of Warwick and Lancaster University
Downloads 34 (1,263,436)

Abstract:

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Microstructure, Surface roughness, Single lap joint, Discrete element method, Failure mechanism

6.

Spatio-Temporal Attention-Based Hidden Physics-Informed Neural Network for Remaining Useful Life Prediction

Number of pages: 14 Posted: 28 May 2024
Feilong Jiang, Xiaonan Hou and Min Xia
Lancaster University, Lancaster University and Western University
Downloads 33 (1,277,121)
Citation 3

Abstract:

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Remaining useful life (RUL), physics-informed machine learning, Feature fusion

7.

Physics-informed neural networks for predicting deformation and stress fields in asymmetric composite adhesive joints​

Number of pages: 29 Posted: 21 Mar 2026
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, University of Science and Technology Beijing, affiliation not provided to SSRN and Lancaster University
Downloads 26 (1,399,036)

Abstract:

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Composites adhesive joints, physical-information neural networks, Partial differential equations, Theoretical model, finite element analysis