Bayesian analysis-based ground motion prediction equations for earthquake input energy

Abstract

Earthquake energy-based procedures offer a promising alternative for seismic evaluation and earthquake-resistant design of structures. Accurate determination of earthquake energy demand and the provision of an adequate energy supply to the structural system are crucial for this approach. This is where the utilization of ground motion prediction equations (GMPEs) becomes essential in achieving accurate assessment of seismic demands on structures. However, most GMPEs primarily focus on determining spectral accelerations. This study proposes a methodology to derive GMPEs by combining the Fourier amplitude spectrum, the elastic input energy spectrum, and Bayesian regression analysis. These GMPEs estimate energy-based spectral values for interplate and intraslab earthquakes recorded in the firm ground of Mexico City. Furthermore, a mathematical expression is devised to determine correlation coefficients between energy-based spectral values for interplate and intraslab earthquakes, expanding the GMPEs' applicability. Finally, a probabilistic seismic hazard analysis is conducted using the proposed GMPEs and the correlation model.