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RESEARCH ARTICLE · Extreme Mechanics Letters · 2023

A Problem-Independent Machine Learning (PIML) enhanced substructure-based approach for large-scale structural analysis and topology optimization of linear elastic structures

Mengcheng Huang, Tianchen Cui, Chang Liu, Zongliang Du, Jiameng Zhang, Chuhui He, Xu Guo

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A Problem-Independent Machine Learning (PIML) enhanced substructure-based approach for large-scale structural analysis and topology optimization of linear elastic structuresOriginalMultiscale Topology Optimization Via Artificial Neural Networks and Displacement-Driven Topology-Optimized Microstructures0Real-Time Generative Design of Diverse, "Truly" Optimized Structures With Controllable Structural Complexities0Study on Coupling of Social and Ecological Dual Network Pattern in Gannan Prefecture Based on Complex Network Theory0Shell-infill composite structure design based on a hybrid explicit- implicit topology optimization method26Knowledge-dominated and data-driven rigid-flexible coupling dynamics for rotating flexible structure10Machine Learning in Biomaterials, Biomechanics/Mechanobiology, and Biofabrication: State of the Art and Perspective60PINN enhanced extended multiscale finite element method for fast mechanical analysis of heterogeneous materials22Stress-related discrete variable topology optimization with handling non-physical stress concentrations8Problem-independent machine learning-enhanced structural topology optimization of complex design domains based on isoparametric elements21Robust topology optimization of multi-material structures with overhang angle constraints using the material field series-expansion method3A mechanics-based data-free Problem Independent Machine Learning (PIML) model for large-scale structural analysis and design optimization35A multi-material topology optimization method based on implicit topology description functions10Sym-ML: A symplectic machine learning framework for stable dynamic prediction of mechanical system19Topology optimization for pressurized nonlinear structures using substructure and experimental studies2Data-driven reliability-based topology optimization by using the extended multi scale finite element method and neural network approach31Integrating neural networks with numerical schemes for dynamical systems: A review5Real-time generative design of diverse optimized structures with controllable structural complexities and high quality3Roadmap on metamaterial theory, modelling and design19A data-driven integrated optimization method of macroscopic topology and microscopic configuration for the graded functional cellular structures5Problem-Independent Machine Learning (PIML) enhanced 3D lattice composite structures optimization via moving morphable components approach11Developing artificial mechanics intuitions from extremely small data2Graph convolutional networks-driven multiscale topology optimization base on polygonal coarse-grid elements5Artificial Intelligence in Generative Design: A Structured Review of Trends and Opportunities in Techniques and Applications40Transformed Tensor Decomposition Method for Topology Optimization2Data-driven model order reduction with surrogate elements for transient simulations0Multiscale topology optimization using machine learning and displacement-driven microstructures3Learning the Solution Operator Family in Elastic Mechanics for Response Prediction Under Various Load Scenarios1Data-driven robust topology optimization using surrogate modeling, model reduction, and machine learning4Real-time generalizable structural topology generation via fourier and latent modulated neural networks informed by few prior designs2A Mechanistic Generative Framework for Sparse Data Dynamics in Engineering Systems0Design of 3D Shell-Graded Infill Structures Based on Moving Morphable Void and Triply Periodic Minimal Surfaces0Problem-Independent Transfer Learning (PITL) for Efficient 3D Topology Optimization on Complex Design Domains0A high-performance parallel algorithm based on problem independent machine learning (PIML) for large-scale topology optimization1A data-driven elastoplastic super element method for multiscale modeling of history-dependent responses in metamaterials3Systematic Mapping of Artificial Intelligence Applications in Finite-Element-Based Structural Engineering2A level-set-oriented and problem-independent robust topology optimization strategy based on convolutional neural networks and uncertainty clustering22High-Generalization AI-Enhanced mechanical analysis and topology optimization via cubic bézier interpolation of substructure boundary displacements3Exponentially convergent extended multiscale finite element method (EC-EMsFEM) for heterogeneous elasticity problems in irregular domains0A deep learning-accelerated nonlocal reduced-order model for brittle fracture simulation1Discrete variable topology optimization for large-scale high-order eigenvalue problems by high-frequency harmonic excitation response surrogate method0Hybrid finite element-deep learning method for deformation modeling of porous structures1A multi-grid, single-mesh online learning framework for efficient large-scale topology optimization0An adaptive online transfer learning framework for isogeometric topology optimization0Problem-independent transfer learning for complex-domain 3D topology optimization0The Adaptive Joint-Driven Moving Morphable Component Method for 3D Topology Optimization0Problem-independent machine learning-accelerated fail-safe topology optimization of 3D continuum structures0Mechanically consistent equivariant machine learning for substructural analysis0A machine learning enhanced substructure method for full scale topology optimization of piezoelectric graded lattice structure0AI-enhanced and data-driven mechanical analysis and structural topology optimization0

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  9. Problem-independent machine learning-enhanced structural topology optimization of complex design domains based on isoparametric elements

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  10. Robust topology optimization of multi-material structures with overhang angle constraints using the material field series-expansion method

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  11. A mechanics-based data-free Problem Independent Machine Learning (PIML) model for large-scale structural analysis and design optimization

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  13. Sym-ML: A symplectic machine learning framework for stable dynamic prediction of mechanical system

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  20. Problem-Independent Machine Learning (PIML) enhanced 3D lattice composite structures optimization via moving morphable components approach

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