Development of damage probability matrices based on Greek earthquake damage data

A comprehensive study is presented for empirical seismic vulnerability assessment of typical structural types, representative of the building stock of Southern Europe, based on a large set of damage statistics. The observational database was obtained from post-earthquake surveys carried out in the area struck by the September 7, 1999 Athens earthquake. After analysis of the collected observational data, a unified damage database has been created which comprises 180,945 damaged buildings from/after the near-field area of the earthquake. The damaged buildings are classified in specific structural types, according to the materials, seismic codes and construction techniques in Southern Europe. The seismic demand is described in terms of both the regional macroseismic intensity and the ratio αg/ao, where αg is the maximum peak ground acceleration （PGA） of the earthquake event and ao is the unique value PGA that characterizes each municipality shown on the Greek hazard map. The relative and cumulative frequencies of the different damage states for each structural type and each intensity level are computed in terms of damage ratio. Damage probability matrices （DPMs） and vulnerability curves are obtained for specific structural types. A comparison analysis is fulfilled between the produced and the existing vulnerability models.

The use of Artificial Neural Networks to estimate seismic damage and derive vulnerability functions for traditional masonry

ABSTRACT This paper discusses the adoption of Artificial Intelligence-based techniques to estimate seismic damage,not with the goal of replacing existing approaches,but as a mean to improve the precision of empirical methods.For such,damage data collected in the aftermath of the 1998 Azores earthquake(Portugal)is used to develop a comparative analysis between damage grades obtained resorting to a classic damage formulation and an innovative approach based on Artificial Neural Networks(ANNs).The analysis is carried out on the basis of a vulnerability index computed with a hybrid seismic vulnerability asssment methodology,which is subsequently used as input to both approaches.The results obtained are then compared with real post-earthquake damage observation and critically discussed taking into account the level of adjustment achieved by each approach.Finally,a computer routine that uses the ANN as an approximation function is developed and applied to derive a new vulnerability curve expression.In general terms,the ANN developed in this study allowed to obtain much better approximations than those achieved with the original vulnerability approach,which has revealed to be quite non-conservative.Similarly,the proposed vulnerability curve expression was found to provide a more accurate damage prediction than the traditional analytical expressions.