David González. Publications

Books

  • Teoría de Estructuras para arquitectos. Elías Cueto, Beatriz Moya y David González. Prensas de la Universidad de Zaragoza. Order here!
  • An Introduction to Structural Mechanics for Architects.
  • Resistencia de materiales para arquitectos. David González y Elías Cueto. Prensas de la Universidad de Zaragoza.
  • Guía rápida de MATLAB. Claves para la certificación. David González. Prensas de la Universidad de Zaragoza.portadaguiamatlab
  • Proper Generalized Decompositions. An introduction to computer implementation with matlab. E. Cueto, D. González, I. Alfaro. Springer Briefs in Applied Sciences and Technology.
    pgd

Book chapters

  1. Aguado , J. V., Borzacchiello , D., Lopez , E., Abisset-Chavanne , E., Gonzalez , D., Cueto , E. and Chinesta , F. (2017) New Trends in Computational Mechanics: Model Order Reduction, Manifold Learning and Data-Driven, in From Microstructure Investigations to Multiscale Modeling: Bridging the Gap (eds D. Brancherie, P. Feissel, S. Bouvier and A. Ibrahimbegović), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781119476757.ch9
  2. PGD-Based Model Reduction for Surgery Simulation: Solid Dynamics and Contact Detection. C. Quesada, I. Alfaro, D. Gonzalez, E. Cueto and F. Chinesta. Lecture Notes in Computational Science and Engineering. Biomedical Simulation, Springer-Verlag, pp. 193-202, 2015.
  3. Vademecums for Real-Time Computational Surgery. D. Gonzalez, I. Alfaro, C. Quesada, E. Cueto and F. Chinesta. Computational Biomechanics for Medicine, Springer-Verlag, pp. 3-15, 2015. DOI- 10.1007/978-3-319-15503-6
  4. The alpha-shape based Natural Element Method in Solid and Fluid Mechanics. D. Gonzalez, I. Alfaro, E. Cueto, M. Doblare and F. Chinesta. Lecture Notes in Computational Science and Engineering. Meshfree Methods for Partial Differential Equations II, Michael Griebel and Marc A. Schweitzer, Ed., Springer-Verlag, pp. 55-70, 2005.
  5. Contributions la methode des lments naturels bass sur les formes alpha. E. Cueto, D. Gonzalez, M. Doblare and F. Chinesta. In Extensions et alternatives la methode des elments finis, Piotr Breitkopf, Ed. Hermes-Science publications, Paris, 2006. In french. ISBN 2-7462-1170-X.
  6. Towards an isogeometric meshless method. D. González, E. Cueto, M. Doblare. In Progress on Meshless methods. Ferreira, Kansa, Fasshauer and Leitao, Eds. p. 237-258. Springer, 2008.

Refereed Journal Publications

  1. A Gentle Short Introduction on Data Learning Model Order Reduction and Twining Methodologies and Techniques. Francisco Chinesta, Elias Cueto, Victor Champaney, Chady Ghnatios, Amine Ammar, Nicolas Hascoet, David Gonzalez, Iciar Alfaro, Daniele Di Lorenzo, Angelo Pasquale and Dominique Baillargeat. Submitted, 2024.
  2. Structure-preserving formulations for the data-driven analysis of coupled multi-physics systems. Alba Muixí, David González, Francisco Chinesta, Elías Cueto. Submitted, 2023.
  3. Computational sensing, understanding, and reasoning: an artificial intelligence approach to physics-informed world modeling. Beatriz Moya, Alberto Badias, David Gonzalez, Francisco Chinesta, Elias Cueto. Archives of Computational Methods in Engineering, accepted for publication, 2023. [Download PDF of draft]
  4. An open-source development based on photogrammetry for a real-time IORT treatment planning system. S. Lozares, C. Bermejo, A. Badías, R. Ibáñez, L. Ligorred, J.M. Ponce, V. González, A. Gandía, J.A. Font, O. Blas, D. González. Physica Medica 112 (2023) 10262,  https://doi.org/10.1016/j.ejmp.2023.102622
  5. Physics perception in sloshing scenes with guaranteed thermodynamic consistency. Moya B., Badías A., González D., Chinesta F., Cueto E. IEEE Transactions in Pattern Analysis and Machine Intelligence. 2022. https://arxiv.org/abs/2106.13301
  6. Physics-informed Reinforcement Learning for Perception and Reasoning about Fluids. Moya B., Badías A., González D., Chinesta F.,  Cueto E. Submitted 2022 https://arxiv.org/pdf/2203.05775.pdf
  7. Learning data-driven reduced elastic and inelastic models of spot-welded patches. Agathe Reille, Victor Champaney, Fatima Daim, Yves Tourbier, Nicolas Hascoet, David Gonzalez, Elias Cueto, Jean Louis Duval, Francisco Chinesta. Mechanics and industry. Accepted for publication, 2021.
  8. MORPH-DSLAM: Model Order Reduction for PHysics-based Deformable SLAM. A. Badias, I. Alfaro, D. Gonzalez, F. Chinesta, E. Cueto. Accepted for publication, Transactions on Pattern Analysis and Machine Intelligence, 2021. [arXiv preprint]
  9. Deep learning of thermodynamics-aware reduced-order models from data. Quercus Hernandez, Alberto Badias, David Gonzalez, Francisco Chinesta, Elias Cueto. Computer Methods in Applied Mechanics and Engineering, accepted for publication, 2021. , arXiv:2007.03758, 2020.
  10. Structure-preserving neural networks. Q. Hernandez, A. Badias, D. Gonzalez, F. Chinesta, E. Cueto. Journal of Computational Physics, accepted for publication, 2020. [Arxiv preprint]
  11. Physically sound, self-learning digital twins for sloshing fluids. Beatriz Moya, Iciar Alfaro, David González, Francisco Chinesta and Elias Cueto. Plos One, accepted for publication, 2020.
  12. Learning non-Markovian physics from data. D. Gonzalez, F. Chinesta, E. Cueto. Journal of Computational Physics, in press, 2019. [Download PDF of draft]
  13. Data-driven GENERIC modeling of poroviscoelastic materials. Chady Ghnatios, Iciar Alfaro, Rok Simik, Christian Mathis, David González, Francisco Chinesta, Elías Cueto. Entropy 2019, 21, 1165; doi:10.3390/e21121165
  14. A data-driven learning method for constitutive modeling: application to vascular hyperelastic soft tissues. D. Gonzalez, A. Garcia-Gonzalez, F. Chinesta, E. Cueto. Materials 2020, 13, 2319; doi:10.3390/ma13102319
  15. Real-time interaction of virtual and physical objects in Mixed Reality applications. A. Badias, I. Alfaro, D. Gonzalez, F. Chinesta, E. Cueto. International Journal for Numerical Methods in Engineering, accepted for publication, 2020.
  16. An Augmented Reality platform for interactive aerodynamic design and analysis. A. Badias, S. Curtit, D. Gonzalez, I. Alfaro, F. Chinesta, E. Cueto. International Journal for Numerical Methods in Engineering, accepted for publication, 2019.
  17. Learning slosh dynamics by means of data. Beatriz Moya, David González, Iciar Alfaro, Francisco Chinesta and Elías Cueto. Computational Mechanics, accepted for publication, 2019.
  18. Learning Corrections for Hyperelastic Models From Data. González D., Chinesta F. and Cueto E. Front. Mater. 6:14. (2019). doi: 10.3389/fmats.2019.00014
  19. Hybrid Contitutive Modeling: Data-driven learning of corrections to plasticity models. R. Ibañez, E. Abisset-Chavanne,  D. González, J. L. Duval, E. Cueto and F. Chinesta. International Journal of Material Forming (2018). https://doi.org/10.1007/s12289-018-1448-x
  20. A multi-dimensional data-driven sparse identification technique: the sparse Proper Generalized Decomposition. R. Ibañez, E. Abisset-Chavanne, A. Ammar, D. González, E. Cueto, A. Huerta, J. L. Duval and F. Chinesta. Complexity, vol. 2018, Article ID 5608286, 2018. https://doi.org/10.1155/2018/5608286.
  21. Reduced order modeling for physically-based augmented reality. Alberto Badías, Iciar Alfaro, David González, Francisco Chinesta, Elías Cueto. Comput. Method Appl. Mech. Engrg. Accepted for Publication, 2018.
  22. Thermodynamically consistent data-driven computational mechanics. David González, Francisco Chinesta, Elías Cueto. Continuum Mech. Thermodyn.  https://doi.org/10.1007/s00161-018-0677-z  (2018) [Download pdf].
  23. Reduced-order modelling of soft robots. Chenevier J, González D, Aguado JV, Chinesta F, Cueto E (2018)  PLoS ONE 13(2): e0192052. https://doi.org/10.1371/journal.pone.0192052 [Download pdf]
  24. Model order reduction for real-time data assimilation through Extended Kalman Filters. David González, Alberto Badías, Icíar Alfaro, Francisco Chinesta, Elías Cueto. Computer Methods in Applied Mechanics and Engineering, 326, 679-693, 2017. https://doi.org/10.1016/j.cma.2017.08.041  [Download pdf of draft].
  25. Oxidative stress prediction: a preliminary approach using a response surface based technique. M. Sierra, L. Bragg-Gonzalo, J. Grasa, M.J. Muñoz, D. González, F.J. Miana-Mena. Toxicology in Vitro, 46 (2018) 273-283. DOI: 10.1016/j.tiv.2017.10.016
  26. Local Proper Generalized Decomposition. A. Badías, D. González, I. Alfaro, F. Chinesta, E. Cueto. International Journal for Numerical Methods in Engineering, 112:12,1715–1732, 2017. [Download pdf of draft]
  27. Haptic simulation of tissue tearing during surgery. C. Quesada, I. Alfaro, D. Gonzalez, F. Chinesta, E. Cueto. International Journal for Numerical Methods in Biomedical Engineering, 34 (3), e2926. 2018 [Download pdf of draft]
  28. A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity. R. Ibañez, E. Abisset-Chavanne, J. V. Aguado, D. González, E. Cueto, F. Chinesta. Arch Computat Methods Eng (2018). 25:59-68 doi:10.1007/s11831-016-9172-5 [Download pdf of draft].
  29. Predicting muscle fatigue. A response surface approximation based on proper generalized decomposition technique. M. Sierra, J. Grasa, M.J. Muñoz, F.J. Miana-Mena, D. González. Biomech Model Mechanobiol (2017) 16: 625. doi:10.1007/s10237-016-0841-y
  30. A PGD-based Multiscale Formulation for Non-Linear Solid Mechanics Under Small Deformations. F. El Halabi, D.González, J.A. Sanz-Herrera and M. Doblaré. Comput. Method Appl. Mech. Engrg., – (), 2016. DOI: 10.1016/j.cma.2016.03.039.
  31. kPCA-based Parametric Solutions within the PGD Framework. D. González, J.V. Aguado, E. Cueto, E. Abisset-Chavanne, F. Chinesta. Archives of Computational Methods in Engineering (2018), 25: 69-86. DOI: 10.1007/s11831-016-9173-4  [Download pdf of draft]
  32. A manifold learning approach for Integrated Computational Materials Engineering. E. Lopez, D. Gonzalez, J.V. Aguado, E. Abisset-Chavanne, F. Lebel, R. Upadhyay, E. Cueto, C. Binetruy, F. Chinesta. Archives of Computational Methods in Engineering (2018), 25:47-57. DOI: 10.1007/s11831-016-9197-9 [Download pdf of draft]
  33. Computational vademecums for real-time simulation of surgical cutting in haptic environments. C. Quesada, D. Gonzalez, I. Alfaro, E. Cueto and F. Chinesta. International Journal for Numerical Methods in Engineering. 108 (10), 1230-1247, 2016. [Download pdf of draft]
  34. Vademecum-based GFEM (V-GFEM): Optimal Enrichment for transient problems. D. Canales, A. Leygue, F. Chinesta, D. Gonzalez, E. Cueto, E. Feulvarch, J.-M. Bergheau, A. Huerta. International Journal for Numerical Methods in Engineering, 108(9), 971-989, 2016. [Download pdf of draft]
  35. An error estimator for real-time simulators based on model order reduction. Iciar Alfaro, David Gonzalez, Sergio Zlotnik, Pedro Diez, Elias Cueto, and Francisco Chinesta. Advanced Modeling and Simulation in Engineering Sciences (AMSES), 2:30, 2015. [Download pdf of draft]
  36. In-plane-out-of-plane separated representations of updated-Lagrangian descriptions of thermomechanical models defined in plate domains. D. Canales, A. Leygue, F. Chinesta, I. Alfaro, D. González, E. Cueto, E. Feulvarch, J.M. Bergheau. C.R. Mecanique (2016) http://dx.doi.org/10.1016/j.crme.2015.12.006 [Download pdf of draft]
  37. On the use of α-shapes for the measurement of 3D bubbles in fluidized beds from Two-Fluid Model simulations. Ignacio Julián, David González, Javier Herguido, Miguel Menéndez. Powder Technology (2016), pp. 409-421. DOI: 10.1016/j.powtec.2015.11.035
  38. Effect of the separated approximation of input data in the accuracy of the resulting PGD solution. Sergio Zlotnik, Pedro Diez, Elias Cueto, David Gonzalez and Antonio Huerta. Advanced Modeling and Simulation in Engineering Sciences, 2015. DOI 10.1186/s40323-015-0052-6 [Download pdf of draft]
  39. Towards a pancreatic surgery simulator based on model order reduction. Andres Mena, David Bel, Iciar Alfaro, David Gonzalez, Elias Cueto, and Francisco Chinesta. Advanced Modeling and Simulation in Engineering Sciences, 2015. DOI 10.1186/s40323-015-0049-1 [Download pdf of draft]
  40. Computational patient avatars for surgery planning. David Gonzalez, Elias Cueto and Francisco Chinesta. Annals of Biomedical Engineering (ABME), 2015-06-23. DOI: 10.1007/s10439-015-1362-z [Download pdf of draft]
  41. Real-time simulation techniques for augmented learning in science and engineering. C. Quesada, D. Gonzalez, I. Alfaro, E. Cueto, A. Huerta, F. Chinesta. The Visual Computer, 2015. DOI 10.1007/s00371-015-1134-7 [Download pdf of draft]
  42. Computational vademecums for the real-time simulation of haptic collision between nonlinear solids. D. Gonzalez, I. Alfaro, C. Quesada, E. Cueto, F. Chinesta. Comput. Method Appl. Mech. Engrg., (283), 210-223, 2015. DOI: 10.1016/j.cma.2014.09.029
  43. Un método de Descomposición Propia Generalizada para operadores diferenciales de alto orden C. Quesada, G. Xu, D. Gonzalez, I. Alfaro, A. Leygue, M. Visonneau, E. Cueto, F. Chinesta. Revista Internacional de Metodos Numericos para Calculo y Diseno en Ingenieria, 31 (3), 188–197 (2015). DOI:10.1016/j.rimni.2014.09.001
  44. Real-time direct integration of reduced solid dynamics equations. David Gonzalez, Elias Cueto, Francisco Chinesta. International Journal for Numerical Methods in Engineering, 99(9), 633-653, 2014. DOI: 10.1002/nme.4691
  45. Model order reduction in hyperelasticity: a Proper Generalized Decomposition approach. S. Niroomandi, I. Alfaro, D. Gonzalez, E. Cueto, F. Chinesta. International Journal for Numerical Methods in Engineering, 96, 3, 129-149. 2013.
  46. Real-time in silico experiments on gene regulatory networks and surgery simulation on handheld devices. I. Alfaro, D. Gonzalez, F. Bordeu, A. Leygue, A. Ammar, E. Cueto, F. Chinesta. Computational Surgery., 1, 1-1 (Open access). (2014)
  47. PGD-based computational vademecum for efficient design, optimization and control. F. Chinesta, A. Leygue, F. Bordeu, J.V. Aguado, E. Cueto, D. Gonzalez, I. Alfaro, A. Ammar, A. Huerta. Archives of Computational Methods in Engineering, 20(1), 31-59, 2013.
  48. FE2 Multiscale in Linear Elasticity Based on Parametrized Microscale Models Using Proper Generalized Decomposition. F. El Halabi, D. González, M. Doblare. Comput. Method Appl. Mech. Engrg. 257 (2013) 183–202.
  49. Real-time simulation of biological soft tissues: a PGD approach. S. Niroomandi, D. Gonzalez, I. Alfaro, F. Bordeu, A. Leygue, E. Cueto, F. Chinesta. International Journal for Numerical Methods in Biomedical Engineering, 29(5), 586-600, 2013.
  50. SUPG-based stabilization of Proper Generalized Decompositions for high-dimensional Advection-Diffusion Equations. D. Gonzalez, E. Cueto, F. Chinesta, P. Diez, A. Huerta. International Journal for Numerical Methods in Engineering, 94(13), 1216-1232, 2013.
  51. Una estrategia basada en la descomposición propia generalizada para aplicaciones gobernadas por datos dinámicos. F. Masson, D. González, E. Cueto, F. Chinesta. Revista Internacional de Metodos Numericos para Calculo y Diseno en Ingenieria, 29(2), 2013.
  52. Multiparametric Response Surface Construction by means of Proper Generalized Decomposition: An extension of the PARAFAC procedure. F. El Halabi, D. González, M. Doblare. Comput. Method Appl. Mech. Engrg. 253, 543-557, 2013.
  53. A natural neighbour Lagrange-Galerkin method for the simulation of Newtonian and Oldroyd-B free-surface flows. A. Galavis, D. Gonzalez, E. Cueto. International Journal for Numerical Methods in Fluids, 70(7), 860-885. 2012. [Download pdf of draft]
  54. Real-time simulation of surgery by reduced order modelling and X-FEM techniques. S. Niroomandi, I. Alfaro, D. Gonzalez, E. Cueto, F. Chinesta. International Journal for Numerical Methods in Biomedical Engineering, 28(5), 574-588, 2012. [Download pdf of draft]
  55. Proper Generalized Decomposition based Dynamic Data Driven Inverse Identification. D. Gonzalez, F. Masson, F. Poulhaon, E. Cueto, F. Chinesta. Mathematics and Computers in Simulation, 82, p. 1677-1695, 2012.
  56. A comparative study on the performance of meshless approximations and their integration. W. Quak, A.H. van den Boogaard, D. González, Elías Cueto. Computational Mechanics, 48, pp 121-137, 2011.
  57. Recent advances on the use of separated representations. David Gonzalez, Amine Ammar, Francisco Chinesta and Elias Cueto. International Journal for Numerical Methods in Engineering, 81(5), 637-659, 2010. [download pdf of draft]
  58. A higher-order method based on local maximum entropy approximation. David Gonzalez, Elias Cueto, Manuel Doblare. International Journal for Numerical Methods in Engineering, 83, pp. 741-764, 2010.[download pdf of draft]
  59. Non Incremental Strategies Based on Separated Representations: Applications in Computational Rheology. A. Ammar, M. Normandin F. Daim, D. Gonzalez, E. Cueto, F. Chinesta. Communications in Mathematical Sciences, 8(3), 671-695, 2010.
  60. NSUPG-Based stabilization using a separated representations approach. D. Gonzalez, L. Debeugny, E. Cueto, F. Chinesta, P. Diez, A. Huerta.  International Journal of Material Forming,, Vol. 3 Suppl 1:883– 886, 2010.
  61. Numerically explicit potentials for the homogenization of nonlinear elastic heterogeneous materials. J. Yvonnet, D. Gonzalez, Q.C. He. Comput. Method Appl. Mech., 198, 2723-2737, 2009.
  62. A High Order Method Using Max-Ent Approximation Schemes. D. Gonzalez, E. Cueto and M. Doblare. International Journal of Material Forming,Vol. 2 Suppl 1:577–580 2009.
  63. Improved domain tracking in meshless simulations of free-surface flows. A. Galavis, D. Gonzalez, I. Alfaro, E. Cueto. Computational Mechanics, vol. 42:467-479, 2008. [download pdf of draft]
  64. Higher-order Natural Element Methods: towards an isogeometric meshless method. David Gonzalez, Elias Cueto, Manuel Doblare. International Journal for Numerical Methods in Engineering, 74 (13), pp.1928-1954, 2008. [download pdf of draft]
  65. Towards a high-resolution numerical strategy based on separated representations. D. Gonzalez, A. Ammar, E. Cueto, F. Chinesta. International Journal of Material Forming Vol. 1, Suppl 1:1099 –1102 2008.
  66. A Natural Element updated Lagrangian strategy for free-surface Fluid Dynamics. D. Gonzalez, E. Cueto, F. Chinesta, M. Doblare. Journal of Computational Physics, 223(1), pp.127-150, 2007. [download pdf of draft]
  67. A Natural Element updated Lagrangian approach for modelling Fluid-Structure interactions. A. Galavis, D. Gonzalez, E. Cueto, F. Chinesta, M. Doblare. European Journal of Computational Mechanics, 16(3-4), pp. 323-336, 2007.
  68. Natural Neighbour strategies for the simulation of laser surface coating processes. D. Gonzalez, D. Bel, E. Cueto, F. Chinesta, M. Doblare. International Journal of Forming Processes. Vol 10/1, pp.89-108, 2007. [download pdf of draft]
  69. Recent advances in the meshless simulation of aluminium extrusion and other related forming processes. I. Alfaro, D. Gonzalez, D. Bel, E. Cueto, M. Doblare, F. Chinesta. Archives of Computational Methods in Engineering, vol 13(1) pp. 3-44. 2007 [download pdf of draft]
  70. Volumetric locking in Natural Neighbour Galerkin methods. D. Gonzalez, E. Cueto and M. Doblare. International Journal for Numerical Methods in Engineering, vol. 61(4) pp. 611-632, 2004. [download from IJNME]
  71. Numerical integration in Natural Neighbour Galerkin methods. D. Gonzalez, E. Cueto, M. A. Martinez and M. Doblare. International Journal for Numerical Methods in Engineering, 60(12):2077-2104, 2004[download from IJNME]