Data-driven modeling of an unsaturated bentonite buffer model test under high temperatures using an enhanced axisymmetric reproducing kernel particle method-Reference-Cited by-同舟云学术

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Data-driven modeling of an unsaturated bentonite buffer model test under high temperatures using an enhanced axisymmetric reproducing kernel particle method

Published:2024-04 Issue: Volume:168 Page:106133
ISSN:0266-352X
Container-title:Computers and Geotechnics
language:en
Short-container-title:Computers and Geotechnics

Author:

Baek Jonghyuk,Wang Yanran,He Xiaolong,Lu Yu^ORCID,McCartney John S.,Chen Jiun-Shyan^ORCID

Funder

Nuclear Energy University Programs

Publisher

Elsevier BV

Reference86 articles.

1. A neural network-based enrichment of reproducing kernel approximation for modeling brittle fracture;Baek;Comput. Methods Appl. Mech. Eng.,2024

2. A Neural Network-enhanced Reproducing Kernel Particle Method for Modeling Strain localization;Baek;IJNME,2022

3. Distance-preserving manifold denoising for data-driven mechanics;Bahmani;Comput. Methods Appl. Mech. Eng.,2023

4. Automatic differentiation in machine learning: a survey;Baydin;Journal of Marchine Learning Research,2018

5. Nodal integration of the element-free Galerkin Method;Beissel;Comput. Methods Appl. Mech. Eng.,1996

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