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David González
David González
Professor, Universidad de Zaragoza, AMB Applied Mechanics and BioEngineering
Verified email at unizar.es - Homepage
Title
Cited by
Cited by
Year
A review of motion planning techniques for automated vehicles
D González, J Pérez, V Milanés, F Nashashibi
IEEE Transactions on intelligent transportation systems 17 (4), 1135-1145, 2015
13102015
PGD-based computational vademecum for efficient design, optimization and control
F Chinesta, A Leygue, F Bordeu, JV Aguado, E Cueto, D González, ...
Archives of Computational methods in Engineering 20 (1), 31-59, 2013
3702013
A manifold learning approach to data-driven computational elasticity and inelasticity
R Ibanez, E Abisset-Chavanne, JV Aguado, D Gonzalez, E Cueto, ...
Archives of Computational Methods in Engineering 25, 47-57, 2018
1932018
Recent advances on the use of separated representations
D González, A Ammar, F Chinesta, E Cueto
International Journal for Numerical Methods in Engineering 81 (5), 637-659, 2010
1632010
Numerically explicit potentials for the homogenization of nonlinear elastic heterogeneous materials
J Yvonnet, D Gonzalez, QC He
Computer Methods in Applied Mechanics and Engineering 198 (33-36), 2723-2737, 2009
1432009
Real‐time simulation of biological soft tissues: a PGD approach
S Niroomandi, D González, I Alfaro, F Bordeu, A Leygue, E Cueto, ...
International journal for numerical methods in biomedical engineering 29 (5 …, 2013
1042013
Non incremental strategies based on separated representations: applications in computational rheology
A Ammar, M Normandin, F Daim, D Gonzalez, E Cueto, F Chinesta
972010
Thermodynamically consistent data-driven computational mechanics
D González, F Chinesta, E Cueto
Continuum Mechanics and Thermodynamics 31, 239-253, 2019
862019
Real‐time simulation of surgery by reduced‐order modeling and X‐FEM techniques
S Niroomandi, I Alfaro, D Gonzalez, E Cueto, F Chinesta
International journal for numerical methods in biomedical engineering 28 (5 …, 2012
832012
Proper generalized decomposition based dynamic data driven inverse identification
D González, F Masson, F Poulhaon, A Leygue, E Cueto, F Chinesta
Mathematics and Computers in Simulation 82 (9), 1677-1695, 2012
812012
Numerical integration in natural neighbour Galerkin methods
D Gonzalez, E Cueto, MA Martinez, M Doblaré
International journal for numerical methods in engineering 60 (12), 2077-2104, 2004
802004
Hybrid constitutive modeling: data-driven learning of corrections to plasticity models
R Ibáñez, E Abisset-Chavanne, D González, JL Duval, E Cueto, ...
International Journal of Material Forming 12, 717-725, 2019
762019
A multidimensional data-driven sparse identification technique: the sparse proper generalized decomposition
R Ibáñez, E Abisset-Chavanne, A Ammar, D González, E Cueto, A Huerta, ...
Complexity 2018, 2018
712018
A natural element updated Lagrangian strategy for free-surface fluid dynamics
D González, E Cueto, F Chinesta, M Doblaré
Journal of computational physics 223 (1), 127-150, 2007
692007
A manifold learning approach for integrated computational materials engineering
E Lopez, D Gonzalez, JV Aguado, E Abisset-Chavanne, E Cueto, ...
Archives of Computational Methods in Engineering 25 (1), 59-68, 2018
652018
Learning corrections for hyperelastic models from data
D González, F Chinesta, E Cueto
Frontiers in Materials 6, 14, 2019
642019
Proper generalized decompositions: an introduction to computer implementation with Matlab
E Cueto, D González, I Alfaro
Springer, 2016
592016
Model order reduction in hyperelasticity: a proper generalized decomposition approach
S Niroomandi, I Alfaro, D González, E Cueto, F Chinesta
International Journal for Numerical Methods in Engineering 96 (3), 129-149, 2013
542013
Real‐time direct integration of reduced solid dynamics equations
D González, E Cueto, F Chinesta
International Journal for Numerical Methods in Engineering 99 (9), 633-653, 2014
532014
Deep learning of thermodynamics-aware reduced-order models from data
Q Hernandez, A Badias, D Gonzalez, F Chinesta, E Cueto
Computer Methods in Applied Mechanics and Engineering 379, 113763, 2021
522021
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