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Advances in Mechanical Problems of Functionally Graded Materials and Structures / Le Van Lich, Indra Vir Singh, Tiantang Yu, Tinh Quoc Bui
| Advances in Mechanical Problems of Functionally Graded Materials and Structures / Le Van Lich, Indra Vir Singh, Tiantang Yu, Tinh Quoc Bui |
| Autore | Lich Le Van |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (262 p.) |
| Soggetto non controllato |
power-law distribution
evanescent wave flow theory of plasticity free vibration characteristics neural networks geometrically nonlinear analysis finite element method stress concentration factor inhomogeneous composite materials circular plate porous materials minimum module approximation method ANFIS electroelastic solution functionally graded piezoelectric materials Love wave polynomial approach stepped FG paraboloidal shell material design damping coefficient spring stiffness technique Lamb wave pure bending general edge conditions residual stress graded finite elements large strain non-linear buckling analysis orthogonal stiffener combined mechanical loads functionally graded piezoelectric-piezomagnetic material functionally graded beams attenuation failure and damage analytical solution functionally graded materials elastoplastic analysis elastic foundation hollow disc different moduli in tension and compression external pressure functional graded saturated material bimodulus fuzzy logic truncated conical sandwich shell quadratic solid–shell elements functionally graded viscoelastic material finite element analysis residual strain neutral layer elliptical hole thin structures functionally graded plate inhomogeneity clustering metal foam core layer robotics and contact wear dispersion high order shear deformation theory finite elements |
| ISBN |
9783039216598
3039216597 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367749803321 |
Lich Le Van
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics / Felix Fritzen, David Ryckelynck
| Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics / Felix Fritzen, David Ryckelynck |
| Autore | Fritzen Felix |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (254 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
supervised machine learning
proper orthogonal decomposition (POD) PGD compression stabilization nonlinear reduced order model gappy POD symplectic model order reduction neural network snapshot proper orthogonal decomposition 3D reconstruction microstructure property linkage nonlinear material behaviour proper orthogonal decomposition reduced basis ECSW geometric nonlinearity POD model order reduction elasto-viscoplasticity sampling surrogate modeling model reduction enhanced POD archive modal analysis low-rank approximation computational homogenization artificial neural networks unsupervised machine learning large strain reduced-order model proper generalised decomposition (PGD) a priori enrichment elastoviscoplastic behavior error indicator computational homogenisation empirical cubature method nonlinear structural mechanics reduced integration domain model order reduction (MOR) structure preservation of symplecticity heterogeneous data reduced order modeling (ROM) parameter-dependent model data science Hencky strain dynamic extrapolation tensor-train decomposition hyper-reduction empirical cubature randomised SVD machine learning inverse problem plasticity proper symplectic decomposition (PSD) finite deformation Hamiltonian system DEIM GNAT |
| ISBN |
9783039214105
3039214101 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367759403321 |
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Fritzen Felix
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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