Pages that link to "Item:Q2309199"
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The following pages link to Self-consistent clustering analysis: an efficient multi-scale scheme for inelastic heterogeneous materials (Q2309199):
Displaying 33 items.
- Virtual clustering analysis for long fiber reinforced composites (Q6101637) (← links)
- An enhanced data-driven constitutive model for predicting strain-rate and temperature dependent mechanical response of elastoplastic materials (Q6105206) (← links)
- Deep learning discrete calculus (DLDC): a family of discrete numerical methods by universal approximation for STEM education to frontier research (Q6109277) (← links)
- On the micromechanics of deep material networks (Q6115410) (← links)
- A reduced order model for geometrically parameterized two-scale simulations of elasto-plastic microstructures under large deformations (Q6118519) (← links)
- Fast construction of cluster interaction matrix for data-driven cluster-based reduced-order model and prediction of elastoplastic stress-strain curves and yield surface (Q6118535) (← links)
- A monolithic hyper ROM \(\mathrm{FE}^2\) method with clustered training at finite deformations (Q6118589) (← links)
- Extended tensor decomposition model reduction methods: training, prediction, and design under uncertainty (Q6120135) (← links)
- Concurrent multiscale simulations of nonlinear random materials using probabilistic learning (Q6125499) (← links)
- Modelling of damage and plasticity phenomena in 3D printed materials via a multiscale approach (Q6141078) (← links)
- A clustering-enhanced potential-based reduced order homogenization framework for nonlinear heterogeneous materials (Q6141162) (← links)
- FEM-CM as a hybrid approach for multiscale modeling and simulation of ferroelectric boundary value problems (Q6145125) (← links)
- A micromechanical mean‐field homogenization surrogate for the stochastic multiscale analysis of composite materials failure (Q6148530) (← links)
- Adaptive spatiotemporal dimension reduction in concurrent multiscale damage analysis (Q6159317) (← links)
- An introduction to kernel and operator learning methods for homogenization by self-consistent clustering analysis (Q6159333) (← links)
- Three-scale bridging for woven composites using homogenization techniques (Q6162956) (← links)
- Convolution hierarchical deep-learning neural network (C-HiDeNN) with graphics processing unit (GPU) acceleration (Q6164268) (← links)
- Deep learning framework for multiscale finite element analysis based on data-driven mechanics and data augmentation (Q6171158) (← links)
- On-the-fly construction of surrogate constitutive models for concurrent multiscale mechanical analysis through probabilistic machine learning (Q6186258) (← links)
- Clustering dimensionless learning for multiple-physical-regime systems (Q6194199) (← links)
- A framework for self-evolving computational material models inspired by deep learning (Q6495609) (← links)
- Accelerating crack growth simulations through adaptive model order reduction (Q6497769) (← links)
- Approximation of periodic Green's operator in real space using numerical integration and its use in fast Fourier transform-based micromechanical models (Q6554071) (← links)
- Cluster based nonuniform transformation field analysis: an efficient homogenization for inelastic heterogeneous materials (Q6554081) (← links)
- N-adaptive Ritz method: a neural network enriched partition of unity for boundary value problems (Q6566038) (← links)
- Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity (Q6584871) (← links)
- Virtual clustering analysis for phase field model of quasi-static brittle fracture (Q6630925) (← links)
- Unsupervised machine learning classification for accelerating \(\mathrm{FE}^2\) multiscale fracture simulations (Q6641844) (← links)
- A reduced order variational spectral method for efficient construction of eigenstrain-based reduced order homogenization models (Q6648529) (← links)
- A FEM cluster-based basis reduction method for shakedown analysis of heterogeneous materials (Q6661932) (← links)
- Clustering-enhanced lattice discrete particle modeling for quasi-brittle fracture and fragmentation analysis (Q6661951) (← links)
- Convolution tensor decomposition for efficient high-resolution solutions to the Allen-Cahn equation (Q6663325) (← links)
- A composite Bayesian optimisation framework for material and structural design (Q6669038) (← links)
