Deep learning in computational mechanics: a review
The rapid growth of deep learning research, including within the field of computational
mechanics, has resulted in an extensive and diverse body of literature. To help researchers …
mechanics, has resulted in an extensive and diverse body of literature. To help researchers …
What's the Situation With Intelligent Mesh Generation: A Survey and Perspectives
Intelligent Mesh Generation (IMG) represents a novel and promising field of research,
utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG …
utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG …
MGNet: a novel differential mesh generation method based on unsupervised neural networks
Mesh generation accounts for a large number of workloads in the numerical analysis. In this
paper, we introduce a novel differential method MGNet for structured mesh generation. The …
paper, we introduce a novel differential method MGNet for structured mesh generation. The …
Mesh optimization using an improved self-organizing mechanism
As more powerful computing hardware enables higher resolution simulations, a fast and
flexible mesh optimization method is becoming increasingly indispensable for …
flexible mesh optimization method is becoming increasingly indispensable for …
Meshing using neural networks for improving the efficiency of computer modelling
C Lock, O Hassan, R Sevilla, J Jones - Engineering with Computers, 2023 - Springer
This work presents a novel approach capable of predicting an appropriate spacing function
that can be used to generate a near-optimal mesh suitable for simulation. The main …
that can be used to generate a near-optimal mesh suitable for simulation. The main …
How to teach neural networks to mesh: Application on 2-D simplicial contours
A Papagiannopoulos, P Clausen, F Avellan - Neural Networks, 2021 - Elsevier
A machine learning meshing scheme for the generation of 2-D simplicial meshes is
proposed based on the predictions of neural networks. The data extracted from meshed …
proposed based on the predictions of neural networks. The data extracted from meshed …
Preliminary investigation on unstructured mesh generation technique based on advancing front method and machine learning methods
W Nianhua, L Peng, C **nghua… - Chinese Journal of …, 2021 - lxxb.cstam.org.cn
Mesh generation and adaptation are bottleneck problems restricting future development of
computational fluid dynamics (CFD). Automatic and intelligent mesh generation is still worth …
computational fluid dynamics (CFD). Automatic and intelligent mesh generation is still worth …
An overview of the ELFIN code for finite element research in electrical engineering
G Aiello, WS Alfonzetti, G Borzì… - WIT Transactions on …, 1999 - witpress.com
This paper gives a general overview of the basic features and latest enhancements of the
finite element code ELFIN, developed by the authors for research in the electrical …
finite element code ELFIN, developed by the authors for research in the electrical …
Parametric short-circuit force analysis of three-phase busbars-a fully automated finite element approach
DG Triantafyllidis, PS Dokopoulos… - IEEE Transactions on …, 2003 - ieeexplore.ieee.org
A three-phase busbar arrangement with straight rigid conductors carrying short-circuit
currents is investigated. Calculations are made assuming steady-state AC current with a …
currents is investigated. Calculations are made assuming steady-state AC current with a …
[HTML][HTML] Implicit geometry neural network for mesh generation
XU Ran, LYU Hongqiang, YU Jian, BAO Chenyu… - Chinese Journal of …, 2024 - Elsevier
The accuracy of numerical computation heavily relies on appropriate meshing, which serves
as the foundation for numerical computation. Although adaptive refinement methods are …
as the foundation for numerical computation. Although adaptive refinement methods are …