Pages that link to "Item:Q597632"

The following pages link to Accurate cyclic plastic analysis using a neural network material model (Q597632):

Displaying 15 items.

• Multiscale topology optimization using neural network surrogate models (Q1986944) (← links)
• Recurrent neural networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step (Q2072735) (← links)
• Mechanistically informed data-driven modeling of cyclic plasticity via artificial neural networks (Q2138793) (← links)
• A recurrent neural network-accelerated multi-scale model for elasto-plastic heterogeneous materials subjected to random cyclic and non-proportional loading paths (Q2236174) (← links)
• Self-learning simulation method for inverse nonlinear modeling of cyclic behavior of connections (Q2638009) (← links)
• Surrogate-assisted Bayesian inference inverse material identification method and application to advanced high strength steel (Q2831841) (← links)
• Artificial neural network modeling of creep behavior in a rotating composite disc (Q3055828) (← links)
• Stochastic identification of elastic constants for anisotropic materials (Q3549848) (← links)
• Extracting inelastic metal behaviour through inverse analysis: a shift in focus from material models to material behaviour (Q3612707) (← links)
• A new neural network-based model for hysteretic behavior of materials (Q3623126) (← links)
• Advances in Neural Networks – ISNN 2005 (Q5707481) (← links)
• A neural network tool for identifying the material parameters of a finite deformation viscoplasticity model with static recovery (Q5956800) (← links)
• Optimal parameters selection of back propagation algorithm in the feedforward neural network (Q6158709) (← links)
• A framework for neural network based constitutive modelling of inelastic materials (Q6194141) (← links)
• Data-driven physics-constrained recurrent neural networks for multiscale damage modeling of metallic alloys with process-induced porosity (Q6584871) (← links)