5 papers
A Unified Phase-Field Fourier Neural Network Framework for Topology Optimization
Jing Li, Xindi Hu, Helin Gong +2
We propose Alternating Phase-Field Fourier Neural Networks (APF-FNNs) as a unified and physics-based framework for topology optimization. The approach decouples the design problem…
Convergence Analysis of an Adaptive Nonconforming FEM for Phase-Field Dependent Topology Optimization in Stokes Flow
Bangti Jin, Jing Li, Yifeng Xu +1
In this work, we develop an adaptive nonconforming finite element algorithm for the numerical approximation of phase-field parameterized topology optimization governed by the Stoke…
On the Crouzeix-Raviart Finite Element Approximation of Phase-Field Dependent Topology Optimization in Stokes Flow
Bangti Jin, Jing Li, Yifeng Xu +1
In this work, we investigate a nonconforming finite element approximation of phase-field parameterized topology optimization governed by the Stokes flow. The phase field, the veloc…
Adaptive finite element approximations of the first eigenpair associated with -Laplacian
Guanglian Li, Jing Li, Julie Merten +2
In this paper, we propose an adaptive finite element method for computing the first eigenpair of the -Laplacian problem. We prove that starting from a fine initial mesh our prop…
Adaptive Computation of Elliptic Eigenvalue Topology Optimization with a Phase-Field Approach
Jing Li, Yifeng Xu, Shengfeng Zhu
In this paper, we discuss adaptive approximations of an elliptic eigenvalue optimization problem in a phase-field setting by a conforming finite element method. An adaptive algorit…