Level set topology optimization with nodally integrated reproducing kernel particle method
Journal
Computer Methods in Applied Mechanics and Engineering
Journal Volume
385
Start Page
114016
ISSN
00457825
Date Issued
2021
Author(s)
Neofytou, Andreas
Kambampati, Sandilya
Picelli, Renato
Chen, Jiunshyan
Kim, Hyunsun Alicia
Abstract
A level set topology optimization (LSTO) using the stabilized nodally integrated reproducing kernel particle method (RKPM) to solve the governing equations is introduced in this paper. This methodology allows for an exact geometry description of a structure at each iteration without remeshing and without any interpolation scheme. Moreover, useful characteristics of the RKPM such as the easily controlled order of continuity and the ability to freely place particles in a design domain wherever needed are illustrated through stress based and design-dependent surface loading examples. The numerical results illustrate the effectiveness and robustness of the methodology with good optimization convergence behavior and ability to handle large topological changes. Furthermore, it is shown that different particle distributions can be used to increase efficiency without additional complexity.
Subjects
Design-depended
Level Set Topology Optimization
Naturally Stabilized Nodal Integration
Reproducing Kernel Particle Method
Stress-based
Iterative Methods
Shape Optimization
Stress Analysis
Design-depended
Exact Geometry
Governing Equations
Level Set
Level Set Topology Optimization
Naturally Stabilized Nodal Integration
Remeshing
Reproducing Kernel Particle Method
Stress-based
Topology Optimisation
Topology
Publisher
Elsevier B.V.
Type
journal article