Neural network model for seismic response of braced buildings - Doran, Bilge; Shen, Jiehua 'Jay'; Wen, Rou; Akbas, Bulent; Bozer, Ali (ICE PUBLISHING, 2017)
Non-ductile, concentrically braced frames are a common lateral force-resisting system used in low-to-moderate seismic regions in the USA. However, their dynamic responses to earthquake ground motions have not been well examined. Structural engineers usually design them conservatively as brittle structures with a small response-modification factor, while building codes restrict their use to low-rise buildings. In this paper, seismic responses of two typical non-ductile concentrically braced frames, one of three storeys and one of nine storeys, were predicted through a neural network model. Twelve input parameters, covering non-linear features from structural components and the uncertain nature of earthquake ground motions, were used in the modelling. Numerical results extracted from thousands of non-linear time-history analyses under one set of moderate ground motions were used to develop the model. Sensitivity analyses were conducted to evaluate the impacts of input parameters on the peak inter-storey drift ratio, designed as an output parameter in the model. The results are shown to be promising considering the uncertainties in both ground motions and the characteristics of structures.
Keywords: mathematical modelling; seismic engineering; steel structures; Construction & Building Technology; Engineering