Topology optimization based on moving deformable components: A new computational framework

Abstract

In the present work, a new computational framework for structural topology optimization based on the concept of moving deformable components is proposed. Compared with the traditional pixel or node point-based solution framework, the proposed solution paradigm can incorporate more geometry and mechanical information into topology optimization directly and therefore render the solution process more flexible. It also has the great potential to reduce the computational burden associated with topology optimization substantially. Some representative examples are presented to illustrate the effectiveness of the proposed approach.

46 pages, 22 figures

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• Systematic design and realization of double-negative acoustic metamaterials by topology optimization
• An efficient Moving Morphable Component (MMC)-based approach for multi-resolution topology optimization
• Multi-material Topology Optimization of Lattice Structures using Geometry Projection
• SEMDOT: Smooth-Edged Material Distribution for Optimizing Topology Algorithm
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• Data-driven topology design using a deep generative model
• Adaptive Mesh Refinement for Topology Optimization with Discrete Geometric Components
• Optimal design of shell-graded-infill structures by a hybrid MMC-MMV approach
• Topologically robust CAD model generation for structural optimisation
• Generation of smoothly-varying infill configurations from a continuous menu of cell patterns and the asymptotic analysis of its mechanical behaviour
• Topology optimization of micro-structured materials featured with the specific mechanical properties
• Topology optimization on complex surfaces based on the moving morphable component (MMC) method and computational conformal mapping (CCM)
• Cellular Topology Optimization on Differentiable Voronoi Diagrams
• Lagrangian-Eulerian Multi-Density Topology Optimization with the Material Point Method
• Topology Optimization Design of Stretchable Metamaterials with Bezier Skeleton Explicit Density (BSED) Representation Algorithm
• Topology optimization on two-dimensional manifolds
• A novel explicit design method for complex thin-walled structures based on embedded solid moving morphable components
• Optimisation of spatially varying orthotropic porous structures based on conformal mapping
• Efficient Design of Helical Higher-Order Topological Insulators in 3D Elastic Medium
• Mixed projection- and density-based topology optimization with applications to structural assemblies
• On Topology optimization with elliptical masks and honeycomb tessellation with explicit length scale constraints
• An improved Material Mask Overlay Strategy for the desired discreteness of pressure-loaded optimized topologies
• A mechanistic-based data-driven approach to accelerate structural topology optimization through finite element convolutional neural network (FE-CNN)
• Data-driven topology design based on principal component analysis for 3D structural design problems
• Neural topology optimization: the good, the bad, and the ugly
• Topology Optimization under Uncertainty using a Stochastic Gradient-based Approach
• On smooth or 0/1 designs of the fixed-mesh element-based topology optimization
• A Parametric Level Set Method for Topology Optimization based on Deep Neural Network (DNN)
• An efficient evolutionary structural optimization method for multi-resolution designs
• Enhanced Data-driven Topology Design Methodology with Multi-level Mesh and Correlation-based Mutation for Stress-related Multi-objective Optimization
• Stress-constrained topology optimization of lattice-like structures using component-wise reduced order models
• Isogeometric Configuration Design Optimization of Three-dimensional Curved Beam Structures for Maximal Fundamental Frequency
• On speeding up an asymptotic-analysis-based homogenisation scheme for designing gradient porous structured materials using a zoning strategy
• Miura-ori tube metamaterial with tunable dynamic property
• Machine Learning based parameter tuning strategy for MMC based topology optimization
• Accelerating gradient-based topology optimization design with dual-model neural networks
• Topology optimization of pentamode metamaterials for underwater acoustics
• Projection-based Implicit Modeling Method (PIMM) for Functionally Graded Lattice Optimization
• Design of a specimen to train path-dependent deep learning material models from a single uniaxial test: eliciting strain diversity via automatically differentiable elastoplastic topology optimization
• IRA assisted MMC-based topology optimization method