Stochastic ground motion simulation with geological site effects in damage asessment

Damage assessment of structures with a mechanical non linear model demands the representation of seismic action in terms of an accelerogram (dynamic analysis) or a response spectrum (pushover analysis). Stochastic ground motion simulation is largely used in regions where seismic strong-motion records are available in insufficient number. In this work we present a variation of the stochastic finite-fault method with dynamic corner frequency that includes the geological site effects. The method was implemented in a computer program named SIMULSIS that generate time series (accelerograms) and response spectra. The program was tested with the MW= 7.3 Landers earthquake (June 28, 1992) and managed to reproduce its effects. In the present work we used it to reproduce the effects of the 1980’s Azores earthquake (January 1, 1980) in several islands, with different possible local site conditions. In those places, the response spectra are presented and compared with the buildings damage observed.

Prediction of the solar radiation using RBF neural networks and ground-to-sky images

In this study, Artificial Neural Networks are applied to multistep long term solar radiation prediction. The networks are trained as one-step-ahead predictors and iterated over time to obtain multi-step longer term predictions. Auto-regressive and Auto-regressive with exogenous inputs solar radiationmodels are compared, considering cloudiness indices as inputs in the latter case. These indices are obtained through pixel classification of ground-to-sky images. The input-output structure of the neural network models is selected using evolutionary computation methods.