Research Information System
7th International Conference on Earthquake Engineering and Seismology-ICEES, Antalya, Turkey, 6 - 10 November 2023, vol.401, pp.137-155, (Full Text)
Ground motion simulation techniques can be valuable tools, particularly in regions with limited recorded accelerograms, as they can provide region-specific ground motion time series for response history analyses. These region-specific ground motions can be critical in predicting and mitigating the impact of potentially catastrophic future earthquakes, which could result in massive destruction, loss of life, and significant economic damage worldwide. These simulation techniques require accurate modelling and calibration of various input parameters in terms of source, path, and site effects. Verification of these parameters can be accomplished by comparing real time series from past events against simulated data. This study aims to simulate the recorded time series of the 9th July 1998 Faial earthquake (Mw = 6.2) using two stochastic simulation approaches: (1) a source-based stochastic finitefault approach based on a dynamic corner frequency concept and (2) a site-based stochastic ground motion simulation approach. Alternative models are employed and tested, and the best model is determined utilizing goodness of fit score. Using the complementary error function, the discrepancies between the real and simulated record sets are evaluated in terms of various seismological parameters, including peak ground acceleration, peak ground velocity, the ratio of peak ground velocity to peak ground acceleration, Arias intensity, cumulative absolute velocity, acceleration spectrum intensity, modified acceleration spectrum intensity for the period range of 0.1-2.5 s, velocity spectrum intensity, Housner intensity, significant duration, bracketed duration, Fourier amplitude spectra within the frequency range of 0.25-10 Hz and pseudo response spectra within the period range of 0.1-4 s. The results of the simulations from both approaches suggest satisfactory fits between the real and simulated time series, which imply that the input parameters are verified for the event of interest.