• DE
  • EN
  • FR
  • Base de données et galerie internationale d'ouvrages d'art et du génie civil

Publicité

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Auteur(s):



Médium: article de revue
Langue(s): en 
Publié dans: Advances in Civil Engineering, , v. 2020
Page(s): 1-16
DOI: 10.1155/2020/4961963
Abstrait:

Both numerical simulations and data-driven methods have been applied in dam’s displacement modeling. For monitored displacement data-driven methods, the physical mechanism and structural correlations were rarely discussed. In order to take the spatial and temporal correlations among all monitoring points into account, we took the first step toward integrating the finite element method into a data-driven model. As the data-driven method, we selected the random coefficient model, which can make each explanatory variable coefficient of all monitoring points following one or several normal distributions. In this way, explanatory variables are constrained. Another contribution of the proposed model is that the actual elastic modulus at each monitoring point can be back-calculated. Moreover, with a Lagrange polynomial interpolation, we can obtain the distribution field of elastic modulus, rather than gaining one value for the whole dam in previous studies. The proposed model was validated by a case study of the concrete arch dam in Jinping-I hydropower station. It has a better prediction precision than the random coefficient model without the finite element method.

Copyright: © Chenfei Shao et al. et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10421179
  • Publié(e) le:
    02.05.2020
  • Modifié(e) le:
    02.05.2020