Publications

Article de presse

Ángel Javier Omella, Ricardo Celorrio, David Pardo,
Sensitivity and uncertainty analysis by discontinuous Galerkin of lock-in thermography for crack characterization,
Computer Methods in Applied Mechanics and Engineering,
Volume 373,
2021,
113523,
ISSN 0045-7825,
https://doi.org/10.1016/j.cma.2020.113523.


DOI: https://doi.org/10.1016/j.cma.2020.113523
Article de presse

María González, Magdalena Strugaru,
Stabilization and a posteriori error analysis of a mixed FEM for convection–diffusion problems with mixed boundary conditions,
Journal of Computational and Applied Mathematics,
Volume 381,
2021,
113015,
ISSN 0377-0427,
https://doi.org/10.1016/j.cam.2020.113015


DOI: https://doi.org/10.1016/j.cam.2020.113015
Article de presse

Dieter Werthmüller, Raphael Rochlitz, Octavio Castillo-Reyes, Lindsey Heagy, Towards an open-source landscape for 3-D CSEM modelling, Geophysical Journal International, Volume 227, Issue 1, October 2021, Pages 644–659, https://doi.org/10.1093/gji/ggab238


DOI: https://doi.org/10.1093/gji/ggab238
Publication de débats de conférence / atelier

Strobbia, C. and Ourabah, A. and Bos, S. and Gallego, P. and Strobbia, C., Will the New Seismic Technology Shake the Geothermal Industry?, 2021, 2021, 1, 1-5, https://doi.org/10.3997/2214-4609.202112969


DOI: https://doi.org/10.3997/2214-4609.202112969
Article de presse

Garcia-Sanchez, D., Fernandez-Navamuel, A., Sánchez, D.Z. et al. Bearing assessment tool for longitudinal bridge performance. Journal of Civil Structural Health Monitoring 10, 1023–1036 (2020).  https://doi.org/10.1007/s13349-020-00432-1


DOI: https://doi.org/10.1007/s13349-020-00432-1
Article de presse

Shahriari, M., Pardo, D. Borehole resistivity simulations of oil-water transition zones with a 1.5D numerical solver. Computational Geosciences 24, 1285–1299 (2020). https://doi.org/10.1007/s10596-020-09946-5


DOI: https://doi.org/10.1007/s10596-020-09946-5
Article de presse

Shahriari, M, Pardo, D, Rivera, JA, et al. Error control and loss functions for the deep learning inversion of borehole resistivity measurements. Int J Numer Methods Eng. 2021; 122: 1629- 1657. https://doi.org/10.1002/nme.6593


DOI: https://doi.org/10.1002/nme.6593