Estimation of the story response parameters through the seismic input energy for moment-resisting frames

The energy-based seismic design method is considered more reliable as it considers frequency content, duration, and pulse type of the seismic excitation in addition to the hysteretic behavior of the structural members. A comprehensive design can be achieved when the energy capacity of the structure exceeds the energy demand from earthquakes. To reach this goal, the distribution of the total seismic input energy should be determined at floor levels first. A new practical method is proposed in this study to estimate the story-wise distribution of seismic input energy on the moment-resisting frame (MRF) type buildings. Once the input energy distribution is obtained, the displacement, velocity, and acceleration responses at floor levels can be achieved using a reverse calculation. The method was validated by testing nonlinear response history analyses (NRHA) on four benchmark steel MRF-type buildings. Based on the results of the study, it can be stated that the proposed method yields very accurate results for predicting the nonlinear seismic demands of MRF-type buildings without having to perform computationally expensive nonlinear analyses. The mean relative differences between the estimated nonlinear responses based on the proposed methodology and NRHA results were calculated as around 12%, 20%, 17%, and 13% for the total seismic input energy, input energy, relative velocity at floor levels, and story displacements, respectively.

Automated summary

The energy-based seismic design method considers various factors such as frequency content, duration, pulse type of seismic excitation, and hysteretic behavior. The study proposes a new practical method to estimate the distribution of seismic input energy on moment-resisting frame (MRF) buildings. The method was validated through testing on benchmark MRF-type buildings, showing accurate results for predicting nonlinear seismic demands without the need for computationally expensive analyses.