Ground-Motion Prediction Models for Arias Intensity and Cumulative Absolute Velocity for Japanese Earthquakes Considering Single-Station Sigma and Within-Event Spatial Correlation

摘要

Arias intensity (AI) and cumulative absolute velocity (CAV) are ground-motion measures that have been found to be well-suited to application in a number of problems in earthquake engineering. Both measures reflect multiple characteristics of the ground motion (e.g. amplitude and duration), despite being scalar measures. In this study, new ground-motion prediction models for the average horizontal component of AI and CAV are developed, using an extended database of strong-motion records from Japan, including the 2011 Tohoku event. The models are valid for magnitude greater than 5.0, rupture distance less than 300 km, and focal depth less than 150 km. The models are novel as they take account of ground-motion data from the 2011 Tohoku earthquake whilst incorporating other important features, such as event type and regional anelastic attenuation. The residuals from the ground-motion modeling are analyzed in detail to gain further insights into the uncertainties related to the developed median prediction equations for AI and CAV. The site-to-site standard deviations are computed and spatial correlation analysis is carried out for AI and CAV, considering both within-event residuals and within-event single-site residuals for individual events as well as for the combined dataset.