Works matching IS 01787675 AND DT 2023 AND VI 71 AND IP 5
Results: 11
POD-based reduced order model for the prediction of global and local elastic responses of fibre-reinforced polymer considering varying fibre distribution.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 1041, doi. 10.1007/s00466-023-02286-y
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- Article
An enriched phase-field method for the efficient simulation of fracture processes.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 1015, doi. 10.1007/s00466-023-02285-z
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A Hu–Washizu variational approach to self-stabilized virtual elements: 2D linear elastostatics.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 935, doi. 10.1007/s00466-023-02282-2
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- Article
An improved formulation for reduced quadrature in computational solid mechanics.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 867, doi. 10.1007/s00466-023-02280-4
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- Article
Incompressible rubber thermoelasticity: a neural network approach.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 895, doi. 10.1007/s00466-023-02278-y
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- Article
Influence of flow–fiber coupling during mold-filling on the stress field in short-fiber reinforced composites.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 991, doi. 10.1007/s00466-023-02277-z
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- Article
Reduced representations of assumed fields for Hu–Washizu solid-shell element.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 957, doi. 10.1007/s00466-023-02275-1
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Efficient GPU-accelerated thermomechanical solver for residual stress prediction in additive manufacturing.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 879, doi. 10.1007/s00466-023-02273-3
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- Article
A fully implicit and thermodynamically consistent finite element framework for bone remodeling simulations.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 853, doi. 10.1007/s00466-022-02263-x
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- Article
FEANN: an efficient data-driven multiscale approach based on physics-constrained neural networks and automated data mining.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 827, doi. 10.1007/s00466-022-02260-0
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- Article
A new computational scheme for structural static stochastic analysis based on Karhunen–Loève expansion and modified perturbation stochastic finite element method.
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- Computational Mechanics, 2023, v. 71, n. 5, p. 917, doi. 10.1007/s00466-022-02259-7
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- Article