A new approach to site classification: Mixed-effects Ground Motion Prediction Equation with spectral clustering of site amplification functions

By S. Kotha, F. Cotton, Dino Bindi. Soil Dynamics and Earthquake Engineering, 2018

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Abstract With increasing amount of strong motion data, Ground Motion Prediction Equation (GMPE) developers are able to quantify empirical site amplification functions ( Δ S 2 S s ) from GMPE residuals, for use in site-specific Probabilistic Seismic Hazard Assessment. In this study, we first derive a GMPE for 5% damped Pseudo Spectral Acceleration (g) of Active Shallow Crustal earthquakes in Japan with 3.4 ≤ M w ≤ 7.3 and 0 ≤ R JB 600 km . Using k-mean spectral clustering technique, we then classify our estimated Δ S 2 S s ( T = 0.01 – 2 s ) of 588 well-characterized sites, into 8 site clusters with distinct mean site amplification functions, and within-cluster site-to-site variability ~ 50% smaller than the overall dataset variability (ϕS2S). Following an evaluation of existing schemes, we propose a revised data-driven site classification characterized by kernel density distributions of Vs30, Vs10, H800, and predominant period (TG) of the site clusters

Subfields: Civil and Structural Engineering, Geophysics

View Paper: https://www.semanticscholar.org/paper/99b65f0b1b765ceab1af116359172d7842c112e9