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A Convolutional Level-Set Based Topology Optimization Framework for General Multiphysics Problems

https://doi.org/10.2139/ssrn.5956854
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An explicit level set approach for generalized shape optimization of fluids with the lattice Boltzmann method
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Radial basis functions and level set method for structural topology optimization
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A level set‐based topology optimization method targeting metallic waveguide design problems
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Explicit level‐set‐based topology optimization using an exact Heaviside function and consistent sensitivity analysis
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Level Set Methods for Optimization Problems Involving Geometry and Constraints
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Optimal shape design as a material distribution problem
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A parametric level-set approach for topology optimization of flow domains
inferredcites →https://doi.org/10.1007/s00158-012-0782-8openalex-snapshot
Levelset based fluid topology optimization using the extended finite element method
inferredcites →https://doi.org/10.1007/s00158-013-0912-yopenalex-snapshot
Level-set methods for structural topology optimization: a review
inferredcites →https://doi.org/10.1007/s00158-016-1467-5openalex-snapshot
An immersed boundary approach for shape and topology optimization of stationary fluid-structure interaction problems
inferredcites →https://doi.org/10.1007/s00158-016-1640-xopenalex-snapshot
On shape sensitivities with heaviside-enriched XFEM
inferredcites →https://doi.org/10.1007/s00158-018-2101-5openalex-snapshot
Deep learning for determining a near-optimal topological design without any iteration
inferredcites →https://doi.org/10.1007/s00158-020-02545-zopenalex-snapshot
Accelerated topology optimization by means of deep learning
inferredcites →https://doi.org/10.1007/s00158-020-02584-6openalex-snapshot
Adaptive level set topology optimization using hierarchical B-splines
inferredcites →https://doi.org/10.1007/s00158-020-02748-4openalex-snapshot
TOuNN: Topology Optimization using Neural Networks
inferredcites →https://doi.org/10.1007/s00158-022-03347-1openalex-snapshot
On the use of artificial neural networks in topology optimisation
inferredcites →https://doi.org/10.1007/s001580050176openalex-snapshot
A 99 line topology optimization code written in Matlab
inferredcites →https://doi.org/10.1007/s00211-015-0744-3openalex-snapshot
Cut finite element methods for coupled bulk–surface problems
inferredcites →https://doi.org/10.1007/s00466-020-01859-5openalex-snapshot
Topology optimization based on deep representation learning (DRL) for compliance and stress-constrained design
inferredcites →https://doi.org/10.1007/s00466-022-02200-yopenalex-snapshot
XIGA: An eXtended IsoGeometric analysis approach for multi-material problems
inferredcites →https://doi.org/10.1007/s10409-010-0395-7openalex-snapshot
Recent development in structural design and optimization
inferredcites →https://doi.org/10.1007/s11081-011-9159-xopenalex-snapshot
Topology optimization using the finite cell method
inferredcites →https://doi.org/10.1007/s11831-023-09913-0openalex-snapshot
Stability and Conditioning of Immersed Finite Element Methods: Analysis and Remedies
inferredcites →https://doi.org/10.1016/0021-9991(88)90002-2openalex-snapshot
Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
inferredcites →https://doi.org/10.1016/0045-7949(95)00048-lopenalex-snapshot
A neural dynamics model for structural optimization—Theory
inferredcites →https://doi.org/10.1016/j.advengsoft.2004.06.004openalex-snapshot
A level set method for structural topology optimization and its applications
inferredcites →https://doi.org/10.1016/j.cad.2019.05.038openalex-snapshot
Non-iterative structural topology optimization using deep learning
inferredcites →https://doi.org/10.1016/j.camwa.2022.09.027openalex-snapshot
Robust high-order unfitted finite elements by interpolation-based discrete extension
inferredcites →https://doi.org/10.1016/j.cma.2014.05.021openalex-snapshot
Stress-based topology optimization method for steady-state fluid–structure interaction problems
inferredcites →https://doi.org/10.1016/j.cma.2017.03.007openalex-snapshot
CutFEM topology optimization of 3D laminar incompressible flow problems
inferredcites →https://doi.org/10.1016/j.cma.2017.09.005openalex-snapshot
Shape optimization using the cut finite element method
inferredcites →https://doi.org/10.1016/j.cma.2018.03.022openalex-snapshot
The aggregated unfitted finite element method for elliptic problems
inferredcites →https://doi.org/10.1016/j.cma.2018.09.036openalex-snapshot
Shape and topology optimization considering anisotropic features induced by additive manufacturing processes
inferredcites →https://doi.org/10.1016/j.cma.2019.02.026openalex-snapshot
Cellular level set in B-splines (CLIBS): A method for modeling and topology optimization of cellular structures
inferredcites →https://doi.org/10.1016/j.cma.2021.114083openalex-snapshot
TONR: An exploration for a novel way combining neural network with topology optimization
inferredcites →https://doi.org/10.1016/j.cma.2021.114232openalex-snapshot
Linking ghost penalty and aggregated unfitted methods
inferredcites →https://doi.org/10.1016/j.cma.2023.116505openalex-snapshot
Finite element interpolated neural networks for solving forward and inverse problems
inferredcites →https://doi.org/10.1016/j.compstruc.2007.05.025openalex-snapshot
Level set based topological shape optimization of geometrically nonlinear structures using unstructured mesh
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2018.01.114openalex-snapshot
On the non-optimality of tree structures for heat conduction
inferredcites →https://doi.org/10.1016/j.jcp.2003.09.032openalex-snapshot
Structural optimization using sensitivity analysis and a level-set method
inferredcites →https://doi.org/10.1016/j.jcp.2020.109252openalex-snapshot
Reactive fluid flow topology optimization with the multi-relaxation time lattice Boltzmann method and a level-set function
inferredcites →https://doi.org/10.1016/j.tws.2020.107263openalex-snapshot
Generating three-dimensional structural topologies via a U-Net convolutional neural network
inferredcites →https://doi.org/10.1023/a:1022650905902openalex-snapshot
Approximation and Estimation Bounds for Artificial Neural Networks
inferredcites →https://doi.org/10.1109/access.2021.3125014openalex-snapshot
Unit Module-Based Convergence Acceleration for Topology Optimization Using the Spatiotemporal Deep Neural Network
inferredcites →https://doi.org/10.1109/tim.2019.2921441openalex-snapshot
Nonstationary Shape Estimation in Electrical Impedance Tomography Using a Parametric Level Set-Based Extended Kalman Filter Approach
inferredcites →https://doi.org/10.1137/18m1185624openalex-snapshot
Mixed Aggregated Finite Element Methods for the Unfitted Discretization of the Stokes Problem
inferredcites →https://doi.org/10.3389/fradi.2023.1175473openalex-snapshot
Selecting the best optimizers for deep learning–based medical image segmentation
inferredcites →https://doi.org/10.3390/fluids5010029openalex-snapshot
A Review of Topology Optimisation for Fluid-Based Problems
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