Results 21 to 30 of about 12,488,537 (258)

Level set topology optimization for design-dependent pressure loads using the reproducing kernel particle method [PDF]

, 2020
This paper presents a level set topology optimization method in combination with the reproducing kernel particle method (RKPM) for the design of structures subjected to design-dependent pressure loads.
Chen, Jiun-Shyan, Kim, H. Alicia, Huang, Tsung-Hui, Neofytou, Andreas, Picelli, Renato   +4 more
core   +1 more source

Penyelesaian Numerik Advection Equation 1 Dimensi dengan EFG-DGM

Media Komunikasi Teknik Sipil, 2016
Differential equation can be used to model various phenomena in science and engineering. Numerical method is the most common method used in solving DE.
Kresno Wikan Sadono
doaj   +1 more source

A neural network‐enhanced reproducing kernel particle method for modeling strain localization

International Journal for Numerical Methods in Engineering, 2022
AbstractModeling the localized intensive deformation in a damaged solid requires highly refined discretization for accurate prediction, which significantly increases the computational cost. Although adaptive model refinement can be employed for enhanced effectiveness, it is cumbersome for the traditional mesh‐based methods to perform while modeling the
Jonghyuk Baek, Jiun-Shyan Chen, Kristen Susuki   +2 more
openaire   +3 more sources

A Quasi-Convex RKPM for 3D Steady-State Thermomechanical Coupling Problems

Mathematics
A meshless, quasi-convex reproducing kernel particle framework for three-dimensional steady-state thermomechanical coupling problems is presented in this paper.
Lin Zhang, D. M. Li, Cen-Ying Liao, Li-Rui Tian   +3 more
doaj   +1 more source

Interpolation-based reproducing kernel particle method

Computer Methods in Applied Mechanics and Engineering
Meshfree methods, including the reproducing kernel particle method (RKPM), have been widely used within the computational mechanics community to model physical phenomena in materials undergoing large deformations or extreme topology changes. RKPM shape functions and their derivatives cannot be accurately integrated with the Gauss-quadrature methods ...
Jennifer E. Fromm, John A. Evans, Jiun-Shyan Chen   +2 more
openaire   +3 more sources

Applying the possibilistic C-means algorithm in kernel-induced spaces [PDF]

, 2010
In this paper, we study a kernel extension of the classic possibilistic c-means. In the proposed extension, we implicitly map input patterns into a possibly high-dimensional space by means of positive semidefinite kernels. In this new space, we model the
Masulli, F., M. Filippone, Filippone, M., ROVETTA, STEFANO, MASULLI, FRANCESCO, Rovetta, S.   +5 more
core   +1 more source

Meshfree methods for computational fluid dynamics

EPJ Web of Conferences, 2013
The paper deals with the convergence problem of the SPH (Smoothed Particle Hydrodynamics) meshfree method for the solution of fluid dynamics tasks. In the introductory part, fundamental aspects of mesh- free methods, their definition, computational ...
Jícha M., Čermák L., Niedoba P.
doaj   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

An ultra-high-speed reproducing kernel particle method

Computational Mechanics
In this work, the fast-convolving reproducing kernel particle method (FC-RKPM) is introduced. This method is hundreds to millions of times faster than the traditional RKPM for 3D meshfree simulations. In this approach, the meshfree discretizations with RK approximation are expressed in terms of convolution sums.
Siavash Jafarzadeh, Michael Hillman
openaire   +3 more sources

Reproducing Kernel Particle Method for Radiative Heat Transfer in 1D Participating Media [PDF]

, 2020
The reproducing kernel particle method (RKPM), which is a Lagrangian meshless method, is employed for the calculation of radiative heat transfer in participating media. In the present method, for each discrete particle (i.e., spatial node) within a local
Zhi-Hong He, Lei Mu, Shi-Kui Dong
core