Now showing items 1-3 of 3

    • Deep learning enhanced principal component analysis for structural health monitoring 

      Fernandez-Navamuel, A.Autoridad BCAM; Magalhães, Filipe; Zamora-Sánchez, Diego; Omella, Ángel J.; Garcia-Sanchez, David; Pardo, D.Autoridad BCAM (2022-01-01)
      This paper proposes a Deep Learning Enhanced Principal Component Analysis (PCA) approach for outlier detection to assess the structural condition of bridges. We employ partially explainable autoencoder architecture to ...
    • A Finite Element based Deep Learning solver for parametric PDEs 

      Uriarte, C.Autoridad BCAM; Pardo, D.Autoridad BCAM; Omella, A. J. (2021)
      We introduce a dynamic Deep Learning (DL) architecture based on the Finite Element Method (FEM) to solve linear parametric Partial Differential Equations(PDEs). The connections between neurons in the architecture mimic the ...
    • Supervised Deep Learning with Finite Element simulations for damage identification in bridges 

      Fernandez-Navamuel, A.Autoridad BCAM; Zamora-Sánchez, Diego; Omella, Ángel J.; Pardo, D.Autoridad BCAM; Garcia-Sanchez, David; Magalhães, Filipe (2022-04-15)
      This work proposes a supervised Deep Learning approach for damage identification in bridge structures. We employ a hybrid methodology that incorporates Finite Element simulations to enrich the training phase of a Deep ...