Pages that link to "Item:Q2179181"
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The following pages link to An inverse modeling approach for predicting filled rubber performance (Q2179181):
Displaying 7 items.
- Rheological model optimization using advanced evolutionary computation for the analysis of the influence of recycled rubber on rubber blend dynamical behaviour (Q400285) (← links)
- Hierarchical deep learning neural network (HiDeNN): an artificial intelligence (AI) framework for computational science and engineering (Q2020738) (← links)
- Concurrent \(n\)-scale modeling for non-orthogonal woven composite (Q2086043) (← links)
- A mixed FFT-Galerkin approach for incompressible or slightly compressible hyperelastic solids under finite deformation (Q2156780) (← links)
- A review of nonlinear FFT-based computational homogenization methods (Q2234259) (← links)
- Recurrent neural networks (RNNs) learn the constitutive law of viscoelasticity (Q2241874) (← links)
- Advances in Numerical Prediction of Extrusion Tools used for Fabrication of Rubber Profiles (Q4582394) (← links)