Simplified approaches for Arias Intensity correction of synthetic accelerograms

For the generation of synthetic accelerograms, spectrum compatibility is usually emphasized. However, it is well known that the correct evaluation of the seismic response depends on suitable seismic inputs. For example, Arias Intensity, that measures the energy of an earthquake and which attracts more and more attention in probabilistic seismic analysis, cannot be ignored. Thus, simplified methods which could generate both spectrum-compatible and energy-compatible accelerograms are required. This study focuses on the correction of Arias Intensity when generating artificial synthetic accelerograms for given specific earthquake records. Two simple and efficient approaches are proposed. The first approach introduces an energy-compatible algorithm to the spectrum-compatible model, which enables the generated accelerograms to match both the target response spectrum in the frequency domain and Arias Intensity in the time domain. The second approach refers to an empirical way in which empirical envelope shape functions are directly defined based on the energy distribution profile of given earthquake records. The two approaches are validated using various earthquake records, their performance is proven satisfactory and their application is straightforward in the relative fields of earthquake engineering.

[1]  Sanaz Rezaeian,et al.  Stochastic Modeling and Simulation of Ground Motions for Performance-Based Earthquake Engineering , 2010 .

[2]  Robert E. Kayen,et al.  Assessment of Liquefaction Potential during Earthquakes by Arias Intensity , 1997 .

[3]  Agathoklis Giaralis,et al.  Time–frequency representation of earthquake accelerograms and inelastic structural response records using the adaptive chirplet decomposition and empirical mode decomposition , 2007 .

[4]  R. Narayana Iyengar,et al.  Generation of spectrum compatible accelerograms , 1979 .

[5]  Armen Der Kiureghian,et al.  Simulation of synthetic ground motions for specified earthquake and site characteristics , 2010 .

[6]  Jonathan D. Bray,et al.  Empirical attenuation relationship for Arias Intensity , 2003 .

[7]  Miguel Herraiz,et al.  AN APPROACH TO THE MEASUREMENT OF THE POTENTIAL STRUCTURAL DAMAGE OF EARTHQUAKE GROUND MOTIONS , 1997 .

[8]  Shie Qian,et al.  Simulations of non‐stationary frequency content and its importance to seismic assessment of structures , 2002 .

[9]  Shih-Chi Liu,et al.  Autocorrelation and power spectral density functions of the Parkfield earthquake of June 27, 1966 , 1969 .

[10]  Steven L. Kramer,et al.  Ground Motion Intensity Measures for Liquefaction Hazard Evaluation , 2006 .

[11]  Roberto Villaverde,et al.  Fundamental Concepts of Earthquake Engineering , 2009 .

[12]  Tsuyoshi Takada,et al.  Wavelet‐Based Generation of Energy‐ and Spectrum‐Compatible Earthquake Time Histories , 2009, Comput. Aided Civ. Infrastructure Eng..

[13]  M. K. Kaul,et al.  Stochastic characterization of earthquakes through their response spectrum , 1978 .

[14]  Irmela Zentner,et al.  Enrichment of seismic ground motion databases using Karhunen–Loève expansion , 2012 .

[15]  Xie Yitong.  A Modification Method of Earthquake Ground Motions for Matching Multi-dimensional Energy Input Spectra and Peak Velocity , 2012 .

[16]  P. C. Jennings,et al.  Simulated earthquake motions , 1968 .

[17]  Gary C. Hart,et al.  Simulation of artificial earthquakes , 1973 .

[18]  Farzad Naeim,et al.  On the Use of Design Spectrum Compatible Time Histories , 1995 .

[19]  D. Boore.  Effect of Baseline Corrections on Displacements and Response Spectra for Several Recordings of the 1999 Chi-Chi, Taiwan, Earthquake , 2004 .

[20]  Angelo Masi,et al.  Selection of Natural and Synthetic Accelerograms for Seismic Vulnerability Studies on Reinforced Concrete Frames , 2011 .

[21]  Pierfrancesco Cacciola,et al.  Combination of modal responses consistent with seismic input representation , 2004 .

[22]  Y. K. Wen,et al.  Modeling of nonstationary ground motion and analysis of inelastic structural response , 1990 .

[23]  Edwin L. Harp,et al.  Shaking intensity thresholds for rock falls and slides: Evidence from 1987 Whittier Narrows and superstition hills earthquake strong-motion records , 1995 .

[24]  Giuseppe Marano,et al.  An energy-based envelope function for the stochastic simulation of earthquake accelerograms , 2009 .

[25]  G. Marano,et al.  Parameters Identification of Stochastic Nonstationary Process Used in Earthquake Modelling , 2013 .

[26]  Irmela Zentner,et al.  Numerical methods for seismic fragility analysis of structures and components in nuclear industry - Application to a reactor coolant system , 2011 .

[27]  Amr S. Elnashai,et al.  The effect of material and ground motion uncertainty on the seismic vulnerability curves of RC structure , 2006 .

[28]  Armen Der Kiureghian,et al.  A stochastic ground motion model with separable temporal and spectral nonstationarities , 2008 .

[29]  J. B. Berrill,et al.  New predictive equations for Arias intensity from crustal earthquakes in New Zealand , 2009 .

[30]  Janusz Wasowski,et al.  An Approach to Time-Probabilistic Evaluation of Seismically Induced Landslide Hazard , 2003 .

[31]  Angelo Masi,et al.  Seismic Vulnerability Assessment of Gravity Load Designed R/C Frames , 2003 .

[32]  Giuseppe Carlo Marano,et al.  The Role of Modulation Function in Nonstationary Stochastic Earthquake Model , 2014 .