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stat.AP2026
Scalable Gaussian Process for Learning Non-Ergodic Ground Motion Model from Physics-Based Simulations with Application to Power Infrastructure Assessment
Jinyan Zhao, Grigorios Lavrentiadis, Domniki Asimaki
This study presents the development and application of a scalable non-ergodic ground motion model (NGMM) for the Los Angeles area. The NGMM is trained and validated on physics-base…
stat.AP2024
Data-driven Characterization of Near-Surface Velocity in the San Francisco Bay Area: A Stationary and Spatially Varying Approach
Grigorios Lavrentiadis, Elnaz Seylabi, Feiruo Xia +3
This study presents the development of two new sedimentary velocity models for the San Francisco Bay Area (SFBA) to improve the near-surface representation of shear-wave velocity (…