Simulating the seismic response of embankments via artificial neural networks

Authors:
Yiannis Tsompanakis;Nikos D. Lagaros;Prodromos N. Psarropoulos;Evaggelos C. Georgopoulos
Affiliations:
Department of Applied Sciences, Technical University of Crete, Chania, Greece;School of Civil Engineering, National Technical University of Athens, Greece;Department of Infrastructure Engineering, Hellenic Air-Force Academy, Athens, Greece;Department of Applied Sciences, Technical University of Crete, Chania, Greece
Venue:
Advances in Engineering Software
Year:
2009

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Abstract

Geotechnical earthquake engineering may generally be considered as an ''imprecise'' scientific area due to the unavoidable uncertainties and the simplifications adopted during the design process of geostructures. Therefore, relatively accurate predictions using advanced soft computing (SC) techniques can be tolerated rather than solving a problem conventionally. Artificial neural networks (ANNs), being one of the most popular SC techniques, have been used in many fields of science and technology, as well as, into an increasing number of earthquake engineering applications on structures and infrastructures. In this work the implementation of ANNs is focused on the simulation of the seismic response of a typical embankment. The dynamic response of the embankment is evaluated utilizing the finite-element method, where the nonlinear behavior of the geo-materials can be taken into account by an equivalent-linear procedure. In the present study, this extremely time-consuming process is replaced by properly trained ANNs.