Application of metamodel-based techniques for the efficient seismic analysis of structural systemsReport as inadecuate




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1 Chaire Sciences des Systèmes et Défis Energétiques EDF-ECP-Supélec LGI - Laboratoire Génie Industriel - EA 2606, SSEC - Chaire Sciences des Systèmes et Défis Energétiques EDF-ECP-Supélec 2 Department of Energy, Politecnico di Milano 3 MSSMat - Laboratoire de mécanique des sols, structures et matériaux

Abstract : We look at the failure behavior of structural systems under the occurrence of seismic events. Detailed, long-running Finite Element Models FEMs are typically adopted for the simulation of the system structural response. However, since a very large number of simulations e.g., several thousands is usually required for an accurate assessment of the system failure behavior under different seismic conditions, the computational burden associated to the approach may be at times impractical. To address this issue, we resort to fast-running Artificial Neural Network ANN regression models, optimally trained to approximate the response of the original FEM. In particular, we embrace a wrapper approach based on Genetic Algorithm GA optimization to search for the optimal set of model inputs features that maximize the ANN representation accuracy. The ANN is trained, validated and tested with respect to the optimal feature subset identified; then, the results are compared with those produced by the original FEM. We illustrate the approach on a case study of seismic risk assessment involving the estimation of the fragility curves for a masonry structure.





Author: Elisa Ferrario - Nicola Pedroni - Enrico Zio - Fernando Lopez-Caballero -

Source: https://hal.archives-ouvertes.fr/



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