Attenuation Relationships for Iran

The purpose of this study is to derive the attenuation relationships for PGA, PGV, and EPA parameters for areas within the seismic zones of Zagros, Alborz and Central Iran with rock and soil substructures. In order to do so, at first the available scientific data including the methods used for deriving attenuation relationships and the parameters involved have been gathered. Afterwards, all the efforts have been focused on gathering a thorough catalogue of earthquakes occurred in Iran. In this regard, a majority of the available catalogs in Iran have been gathered and corrected through different methods and finally a set of 89 earthquake events including 307 earthquake records with reliable data was chosen.

Since in order to derive the attenuation relationships it is essential to extract the parameters from the acceleration records, a great effort was placed on gathering the earthquake acceleration records of Iran. This resulted in building a database of a majority of the earthquake records up to the year of 2004. Afterwards, correction methods applicable to earthquakes records of Iran considering the type of machines used and the ground type were examined which resulted in certain guidelines for correction of earthquake acceleration record data related to Iran.

In the next step the needed parameters were extracted from the earthquake acceleration record data which were consequently divided into two seismic zones of Zagros, and Alborz and Central Iran according to tectonic conditions. After examination of the parameters and choosing the most appropriate among them, the attenuation relationships were derived for such parameters.     

Generation of Multiple Earthquake Accelerograms Compatible with Spectrum Via the Wavelet Packet Transform and Stochastic Neural Networks

The principal purpose of this article is to present a novel methodology based on wavelet packet transform techniques and stochastic neural networks to generate more artificial earthquake accelerograms from available data, which are compatible with specified response spectra or the design spectra. The proposed method uses the decomposing capabilities of wavelet packet transform on earthquake accelerograms, and the learning abilities of stochastic neural network to expand the knowledge of the inverse mapping from response spectrum to coefficients of wavelet packet transform of earthquake accelerogram. This methodology results in a stochastic ensemble of wavelet packet transform coefficients of earthquake accelerograms and, they are used to the generate accelerograms applying the inverse wavelet packet transform. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to train and test the neural network, aiming at the demonstration of the method effectiveness.     

Probabilistic Performance Assessment of Retrofitted Skewed Multi Span Continuous Concrete I-girder Bridges

The unique dynamic response of skewed bridges causes them to experience more noticeable damage compared to straight bridges during seismic events. The effectiveness of different retrofit strategies on the fragility of skewed bridges can change with the skew angle. This article assesses the impact of skew angle and various retrofit strategies on the fragility of multi span continuous concrete I-girder bridges. The results indicate that the level of effectiveness of a retrofit strategy is highly dependent on the skew angle and damage state of interest and an appropriate retrofit strategy should be chosen based on the vulnerability of the components.