Correlation of Spectral Acceleration Values from NGA Ground Motion Models

By Jack W. Baker, N. Jayaram. 2008

583 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering

View Paper: https://www.semanticscholar.org/paper/0c5311a6935c9cf2e111fa8a8daabd9567de53b3

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In Civil and Structural Engineering

1. K. Tarbali
2. Brendon Bradley
3. P. Bazzurro
4. M. Kohrangi
5. S. Kotha
6. P. Heresi
7. Eduardo Miranda
8. C. Loth

Citations in the corpus

• Ground motion selection for scenario ruptures using the generalised conditional intensity measure (GCIM) method (2015, methodology): “These specific weight vectors considered are chosen aEquations are functions of vibration period and given by the following references: BJ08 in Baker and Jayaram [13], B11(b) in Bradley [15], B12(b) in Bradley [17], B11(a) in Bradley [14], B12(c) in Bradley [18], B11(c) in Bradley [16] and B14(a) in”
• Ground-motion models for average spectral acceleration in a period range: direct and indirect methods (2017, methodology): “Correlation coefficient estimates (called BJ08) based on the method by Baker and Jayaram (2008) but applied on the residuals of GMPE-SA developed by Chiou and Youngs (2008) using the NGA-West ground motion dataset (Chiou et al. 2008).”
• Quantification of model uncertainty and variability in Newmark displacement analysis (2018, unknown): “Note: the following references are used to obtain the correlation coefficients: ρ(PGA, Ia), ρ(PGA, PGV) and ρ(Ia, PGV) [30]; ρ(PGA, Sa(T= 1 s)) [31]; ρ(Ia, Sa (T = 1 s)) [32] and ρ(PGV, Sa(T= 1 s)) [33].”
• Uncertainty in intraevent spatial correlation of elastic pseudo-acceleration spectral ordinates (2018, background): “…have shown that response spectral ordinates can be assumed to be lognormally distributed random variables (e.g., Abrahamson 1988; Jayaram and Baker 2008), and GMPEs can be used to estimate their median and dispersion as a function of the event magnitude, source-to-site distance, and other…”
• A generalized conditional intensity measure approach and holistic ground‐motion selection (2010, methodology): “The basis of the CMS is that spectral accelerations at multiple vibration periods can be assumed to have a multivariate lognormal distribution (recently validated by Jayaram and Baker [8]).”
• A spatial cross‐correlation model of spectral accelerations at multiple periods (2013, methodology): “Previous studies have proposed empirical equations to pred ict the sill [7,12,18,19], as it is equal to the covariance between (Ti) and (Tj) at the same site ( h = 0): Sij = Cij(0) (24) Three methods were investigated in order to achieve a robust estimation of the sill: (i) a direct computation of C”
• Conditional Spectrum Computation Incorporating Multiple Causal Earthquakes and Ground-Motion Prediction Models (2013, unknown): “…coefficient between pairs of ε values at two periods, ρ ( ε ( T i ) , ε ( T ∗ )) (hereinafter referred to as ρ ( T i , T ∗ ) ) (from e.g., Baker and Jayaram, 2008) The spectrum defined by µ lnSa ( T i ) | lnSa ( T ∗ ) in Equation 2 has been termed the “CMS”, as it specifies the mean values…”