| Vertical cracks characterization using lock-in thermography: I infinite cracks NW Pech-May, A Oleaga, A Mendioroz, AJ Omella, R Celorrio, A Salazar Measurement Science and Technology 25 (11), 115601, 2014 | 57 | 2014 |
| Supervised deep learning with finite element simulations for damage identification in bridges A Fernandez-Navamuel, D Zamora-Sánchez, ÁJ Omella, D Pardo, ... Engineering Structures 257, 114016, 2022 | 55 | 2022 |
| On quadrature rules for solving partial differential equations using neural networks JA Rivera, JM Taylor, ÁJ Omella, D Pardo Computer Methods in Applied Mechanics and Engineering 393, 114710, 2022 | 34 | 2022 |
| A finite element based deep learning solver for parametric PDEs C Uriarte, D Pardo, ÁJ Omella Computer Methods in Applied Mechanics and Engineering 391, 114562, 2022 | 33 | 2022 |
| Vertical cracks characterization using lock-in thermography: II finite cracks R Celorrio, AJ Omella, NW Pech-May, A Oleaga, A Mendioroz, A Salazar Measurement Science and Technology 25 (11), 115602, 2014 | 33 | 2014 |
| Deep learning enhanced principal component analysis for structural health monitoring A Fernandez-Navamuel, F Magalhaes, D Zamora-Sánchez, AJ Omella, ... Structural Health Monitoring 21 (4), 1710-1722, 2022 | 32 | 2022 |
| Modeling extra-deep electromagnetic logs using a deep neural network S Alyaev, M Shahriari, D Pardo, ÁJ Omella, DS Larsen, N Jahani, E Suter Geophysics 86 (3), E269-E281, 2021 | 30 | 2021 |
| Bridge damage identification under varying environmental and operational conditions combining Deep Learning and numerical simulations A Fernandez-Navamuel, D Pardo, F Magalhães, D Zamora-Sánchez, ... Mechanical Systems and Signal Processing 200, 110471, 2023 | 17 | 2023 |
| Advances in crack characterization by lock-in infrared thermography R Celorrio, AJ Omella, A Mendioroz, A Oleaga, A Salazar International Journal of Thermophysics 36, 1202-1207, 2015 | 14 | 2015 |
| Sensitivity and uncertainty analysis by discontinuous Galerkin of lock-in thermography for crack characterization AJ Omella, R Celorrio, D Pardo Computer Methods in Applied Mechanics and Engineering 373, 113523, 2021 | 8 | 2021 |
| Modeling extra-deep EM logs using a deep neural network S Alyaev, M Shahriari, D Pardo, AJ Omella, DS Larsen, N Jahani, E Suter arXiv preprint arXiv:2005.08919, 2020 | 5 | 2020 |
| r-Adaptive deep learning method for solving partial differential equations ÁJ Omella, D Pardo Computers & Mathematics with Applications 153, 33-42, 2024 | 3 | 2024 |
| A multi-physics approach for minimising motor losses on the WLTP driving cycle I Martinez, DJ Palomar, M Garate, D Pardo, ÁJ Omella, J Garcia, A Peña IET Digital Library, 2022 | 2 | 2022 |
| DISCONTINUOUS GALERKIN METHOD ÁJ Omella, R Celorrio Monografías Matemáticas García de Galdeano 40, 95-104, 2015 | 2 | 2015 |
| Resolución numérica de problemas inversos en termografía activa para la caracterización de grietas ÁJ Omella Milián Universidad de Zaragoza, 2017 | 1 | 2017 |
| Finite element model for crack characterization by lock-in thermography R Celorrio, AJ Omella QIRT, p 108, 2014 | 1 | 2014 |
| Deep neural network for damage detection in Infante Dom Henrique bridge using multi-sensor data A Fernandez-Navamuel, D Pardo, F Magalhães, D Zamora-Sánchez, ... Structural Health Monitoring, 14759217241227455, 2024 | | 2024 |
| r-Adaptive deep learning method for solving partial di erential equations D Pardo, AJ Omella | | 2024 |
| г-adaptive meshes using Deep Neural Networks for solving Partial Differential Equations AJ Omella, D Pardo | | 2022 |
| A simulation method for the computation of the effective P-wave velocity in heterogeneous rocks ÁJ Omella, J Alvarez-Aramberri, M Strugaru, V Darrigrand, D Pardo, ... Computational Mechanics 67, 845-865, 2021 | | 2021 |
David PardoIkerbasque, University of the Basque Country (UPV/EHU), and BCAMDirección de correo verificada de ehu.eus
