TITLE:
Neural Network Approach to Response of Buildings Due to Earthquake Excitation
AUTHORS:
Sayantan Chakraborty, Prashant Kumar, Swapan Kumar Chakraborty
KEYWORDS:
Neural Network; Anisotropic Building; Soft Ground Floor
JOURNAL NAME:
International Journal of Geosciences,
Vol.3 No.3,
July
19,
2012
ABSTRACT: The present article investigates the physical phenomena associated with the wave passage effect into a building considering the ground floor as the soft floor with the conformity of the up-to-date scenario of the construction of high rise buildings, due to shear excitation of the base. The aim of the study is to analyse the post-earthquake situation of the building in respect to its health. With this vision, the ensuing problem on two-dimensional building models, non-incorporating soil-structure interaction, is being tackled by both analytical and neural network approaches. Computational results from both ends (of the approaches) show that the wave energy does not always propagate from the ground into the building, but for lower frequency range it sails to the building without any disturbances. However, for higher frequency range, the computational results show that the building experiences large “torsional” deformations, as a result the building may collapse. Finally, both the approaches maintain a good agreement among themselves. The present investigation may lead to a long way in contributing to better and more rational, simplified design criteria.