Convolution hierarchical deep-learning neural network tensor decomposition (C-HiDeNN-TD) for high-resolution topology optimization
High-resolution structural topology optimization is extremely challenging due to a large
number of degrees of freedom (DoFs). In this work, a Convolution-Hierarchical Deep …
number of degrees of freedom (DoFs). In this work, a Convolution-Hierarchical Deep …
Convolution Hierarchical Deep-learning Neural Networks (C-HiDeNN): finite elements, isogeometric analysis, tensor decomposition, and beyond
This paper presents a general Convolution Hierarchical Deep-learning Neural Networks (C-
HiDeNN) computational framework for solving partial differential equations. This is the first …
HiDeNN) computational framework for solving partial differential equations. This is the first …
RKPM2D: an open-source implementation of nodally integrated reproducing kernel particle method for solving partial differential equations
We present an open-source software RKPM2D for solving PDEs under the reproducing
kernel particle method (RKPM)-based meshfree computational framework. Compared to …
kernel particle method (RKPM)-based meshfree computational framework. Compared to …
Peridynamic analysis of dynamic fracture: influence of peridynamic horizon, dimensionality and specimen size
In peridynamic models for fracture, the dissipated fracture energy is regularized over a non-
local region denoted as the peridynamic horizon. This paper investigates the influence of …
local region denoted as the peridynamic horizon. This paper investigates the influence of …
Convolution finite element based digital image correlation for displacement and strain measurements
This work presents a novel global digital image correlation (DIC) method, based on a newly
developed convolution finite element (C-FE) approximation. The convolution approximation …
developed convolution finite element (C-FE) approximation. The convolution approximation …
[PDF][PDF] Nonlocal Operator Method for Solving Partial Differential Equations: State-of-the-Art Review and Future Perspectives.
The nonlocal operator method (NOM) is based on nonlocal theory and employs nonlocal
operators of integral form to replace the local partial differential operators. NOM naturally …
operators of integral form to replace the local partial differential operators. NOM naturally …
A variational multiscale immersed meshfree method for heterogeneous materials
We introduce an immersed meshfree formulation for modeling heterogeneous materials with
flexible non-body-fitted discretizations, approximations, and quadrature rules. The interfacial …
flexible non-body-fitted discretizations, approximations, and quadrature rules. The interfacial …
Convolution tensor decomposition for efficient high-resolution solutions to the Allen–Cahn equation
Y Lu, C Yuan, H Guo - Computer Methods in Applied Mechanics and …, 2025 - Elsevier
This paper presents a convolution tensor decomposition based model reduction method for
solving the Allen–Cahn equation. The Allen–Cahn equation is usually used to characterize …
solving the Allen–Cahn equation. The Allen–Cahn equation is usually used to characterize …
[HTML][HTML] Data-driven modeling of an unsaturated bentonite buffer model test under high temperatures using an enhanced axisymmetric reproducing kernel particle …
In deep geological repositories for high level nuclear waste with close canister spacings,
bentonite buffers can experience temperatures higher than 100° C. In this range of extreme …
bentonite buffers can experience temperatures higher than 100° C. In this range of extreme …
A stabilized quasi and bending consistent meshfree Galerkin formulation for Reissner–Mindlin plates
TH Huang, YL Wei - Computational Mechanics, 2022 - Springer
The state-of-the-art locking-free meshfree Galerkin formulation for modeling the Reissner–
Mindlin plate problems is plagued by the following issues:(1) the requirement of a large …
Mindlin plate problems is plagued by the following issues:(1) the requirement of a large …