The high‐frequency limit of usable response spectral ordinates from filtered analogue and digital strong‐motion accelerograms

Abstract

The range of response frequencies for which spectral ordinates obtained from accelerograms may be considered reliable is limited by several factors, primary among them being the effects of filters that are routinely applied to remove noise from the records. Considerable attention has been focused on the low-frequency limit of the usable spectral ordinates because of various engineering applications requiring long-period spectral accelerations or displacements but only recently have rational approaches to selecting the high-frequency limit been proposed. Since there are applications for which the high-frequency spectral ordinates are important, the approaches to this issue presented in the recent studies are reviewed and their application to the ground-motion database from Europe and the Middle East is explored. On the basis of the results of these analyses, it is concluded that a large proportion of this dataset can be used to provide reliable estimates of response spectral ordinates at much shorter periods than may have previously been considered feasible. S. AKKAR ET AL.ordinates are of particular importance. The importance of high-frequency response is also increased when the vertical component of motion is of consideration, especially if the vertical spectrum is to be obtained through the use of vertical-to-horizontal spectral ratios to scale the horizontal response spectrum.Another application for which high-frequency ordinates can be important, albeit indirectly, is the inversion of empirical ground-motion predictions to find equivalent stochastic parameters [3], which can then be used to apply host-to-target conversions to transport models from one region to another [4]. The stability of such inversions is improved if the response spectrum is defined in detail across a wide range of response frequencies, and in particular at high frequencies.Ground-motion prediction equations (GMPEs) for response spectral accelerations have generally provided coefficients for the prediction of peak ground acceleration (PGA) and the spectral acceleration at a large number of response periods. The shortest period for which coefficients are presented has varied significantly among published models [5], but the reasons behind the selection of the minimum period (other than 0.0 s, corresponding to PGA) is often not explicitly stated. In some cases the shortest period may have been chosen purely on the basis of the smallest value deemed to be of relevance to structural engineering. In other cases, the minimum period may have been inferred from the nature of the instruments that produced the record, since analogue accelerographs are generally incapable of capturing motions at frequencies equal to or greater than that of the transducer. For the SMA-1 accelerograph, for example, the instrument response distorts ground motion with frequencies of greater than about 20 Hz [6]. Although procedures have been developed to apply corrections for the effect of the transducer frequency, it has been noted that their application will amplify b...

Empirical ground-motion models for point- and extended-source crustal earthquake scenarios in Europe and the Middle East

“…Another innovation in these new equations is the extension of the range of periods at the shorter end, following new insights into the relatively low sensitivity of short-period ordinates to the high-frequency filtering of accelerograms (Douglas and Boore, 2011;Akkar et al, 2011). provided coefficients at short periods as an extension of the model of Akkar and Bommer (2010), as well as exploring the options for interpolating missing coefficients at short periods; the new models presented in this article include 62 spectral ordinates starting from the period of 0.01s.…”

“…This rapid drop-off is due to a large proportion of records from analogue instruments within the databank used despite the conversion of most European strong-motion networks to digital accelerometers in the past decade. The Akkar et al (2011) criteria to account for low-pass filtering effects on the short period spectral ordinates (T<0.05s) were not followed as its application did not result in significant changes in the total number of data in this period range.…”

A New Procedure for Selecting and Ranking Ground-Motion Prediction Equations (GMPEs): The Euclidean Distance-Based Ranking (EDR) Method

“…We implemented a uniform data processing procedure that is based on fourthorder acausal Butterworth band-pass filtering. The high-pass and low-pass filter cutoff values were mainly identified by following the discussions in Akkar and Bommer (2006) and Akkar et al (2011). The candidate GMPEs for testing are derived for shallow active crustal regions.…”

Extending ground-motion prediction equations for spectral accelerations to higher response frequencies

“…Whereas Bommer (2007b, 2010) only applied low-cut filters to the records, for this study each record was also subjected to an individually selected high-cut filter, where necessary. The criteria for selecting these high-cut filters are discussed in detail by Akkar et al (2011), who also discuss the criterion established for selecting the lower limit for usable periods of the band-pass filtered records. Whereas for regressions on spectral ordinates at long periods, Akkar and Bommer (2010) removed records individually at periods beyond their usable limit, for the short-period equations it was decided to remove any record that failed the criterion at 0.05, 0.04, 0.03, 0.02 or 0.01 s from the regressions at each of these periods, as well as for PGA (Akkar et al 2011).…”

“…The criteria for selecting these high-cut filters are discussed in detail by Akkar et al (2011), who also discuss the criterion established for selecting the lower limit for usable periods of the band-pass filtered records. Whereas for regressions on spectral ordinates at long periods, Akkar and Bommer (2010) removed records individually at periods beyond their usable limit, for the short-period equations it was decided to remove any record that failed the criterion at 0.05, 0.04, 0.03, 0.02 or 0.01 s from the regressions at each of these periods, as well as for PGA (Akkar et al 2011). For periods of 0.10 s and greater, the high-cut filter was found to exert no influence at all, so the coefficients presented by Akkar and Bommer (2010) at those periods remain unchanged.…”