Physics-Informed Multifidelity Residual Neural Networks for Hydromechanical Modeling of Granular Soils and Foundation Considering Internal Erosion-Reference-Cited by-同舟云学术

Physics-Informed Multifidelity Residual Neural Networks for Hydromechanical Modeling of Granular Soils and Foundation Considering Internal Erosion

Published:2022-04 Issue:4 Volume:148 Page:
ISSN:0733-9399
Container-title:Journal of Engineering Mechanics
language:en
Short-container-title:J. Eng. Mech.

Author:

Zhang Pin¹,Yin Zhen-Yu²,Jin Yin-Fu³,Yang Jie⁴^ORCID,Sheil Brian⁵

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, The Hong Kong Polytechnic Univ., Hong Kong, China; Visiting Researcher, Dept. of Engineering Science, Univ. of Oxford, Oxford OX1 3PJ, UK.

2. Associate Professor, Dept. of Civil and Environmental Engineering, The Hong Kong Polytechnic Univ., Hong Kong, China (corresponding author).

3. Postdoctoral Fellow, Dept. of Civil and Environmental Engineering, The Hong Kong Polytechnic Univ., Hong Kong, China.

4. Postdoctoral Fellow, Dept. of Civil and Environmental Engineering, The Hong Kong Polytechnic Univ., Hong Kong, China. ORCID: .

5. Royal Academy of Engineering Research Fellow, Dept. of Engineering Science, Univ. of Oxford, Oxford, UK.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EM.1943-7889.0002094

Reference53 articles.

1. Alboresha R. 2016. “Evaluation of the impact of a cavity upon an earth dike (analytical and numerical approaches): Application to the Val d’Orléans area (France).” Ph.D. thesis Université de Lorraine. https://hal.univ-orraine.fr/tel-01752229/document.

2. Statistical Mechanics of Deep Learning

3. A finite element reduced‐order model based on adaptive mesh refinement and artificial neural networks

4. Automatic differentiation in machine learning: A survey;Baydin A. G.;J. Mach. Learn. Res.,2018

5. Prediction of maximum surface settlement caused by earth pressure balance (EPB) shield tunneling with ANN methods

Cited by 41 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-Fidelity Learned Emulator for Waves and Porous Coastal Structures Interaction Modelling;Computers and Geotechnics;2024-12

2. Physics-informed and data-driven machine learning of rock mass classification using prior geological knowledge and TBM operational data;Tunnelling and Underground Space Technology;2024-10

3. Multifidelity Data Fusion for the Estimation of Static Stiffness of Suction Caisson Foundations in Layered Soil;Journal of Geotechnical and Geoenvironmental Engineering;2024-08

4. A multi‐fidelity residual neural network based surrogate model for mechanical behaviour of structured sand;International Journal for Numerical and Analytical Methods in Geomechanics;2024-06-10

5. Tensor-based physics-encoded neural networks for modeling constitutive behavior of soil;Computers and Geotechnics;2024-06