DAVID PARDO ZUBIAUR-rekin lankidetzan egindako argitalpenak (12)

2024

  1. Deep neural network for damage detection in Infante Dom Henrique bridge using multi-sensor data

    Structural Health Monitoring

  2. r-Adaptive deep learning method for solving partial differential equations

    Computers and Mathematics with Applications, Vol. 153, pp. 33-42

2023

  1. Bridge damage identification under varying environmental and operational conditions combining Deep Learning and numerical simulations

    Mechanical Systems and Signal Processing, Vol. 200

2022

  1. A Finite Element based Deep Learning solver for parametric PDEs

    Computer Methods in Applied Mechanics and Engineering, Vol. 391

  2. Deep learning enhanced principal component analysis for structural health monitoring

    Structural Health Monitoring, Vol. 21, Núm. 4, pp. 1710-1722

  3. On quadrature rules for solving Partial Differential Equations using Neural Networks

    Computer Methods in Applied Mechanics and Engineering, Vol. 393

  4. Supervised Deep Learning with Finite Element simulations for damage identification in bridges

    Engineering Structures, Vol. 257

  5. r−adaptive meshes using Deep Neural Networks for solving Partial Differential Equations

    Congress on Numerical Methods in Engineering CMN 2022 (2022. Las Palmas de Gran Canaria)

2021

  1. A simulation method for the computation of the effective P-wave velocity in heterogeneous rocks

    Computational Mechanics, Vol. 67, Núm. 3, pp. 845-865

  2. Modeling extra-deep electromagnetic logs using a deep neural network

    Geophysics, Vol. 86, Núm. 3, pp. E269-E281

  3. Sensitivity and uncertainty analysis by discontinuous Galerkin of lock-in thermography for crack characterization

    Computer Methods in Applied Mechanics and Engineering, Vol. 373

  4. Uncertainty Quantification on the Inversion of Geosteering Measurements using Deep Learning

    3rd EAGE/SPE Geosteering Workshop